Category Archives: Best DNA Articles

Mining for Gold – Working With “Relatives at RootsTech”

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It’s RootsTech week. I hope you have March 3-5 set aside because it’s going to be a blast. I’ll write in a day or so about my sessions.

However, you can already utilize some of the RootsTech features for your genealogy and for DNA as well. Let’s take a look, she says, gleefully rubbing her hands together!

When you sign in to your account at RootsTech and click on “See Your Relatives at RootsTech,” you’ll see the following splash.

First – don’t panic and think, “I can’t deal with 38 thousand people,” and throw your hands up in exasperation. You don’t have to deal with that many people. Only your closest 300 or so are available for you to work with, at least easily. RootsTech has organized them for you.

But isn’t it cool to realize just how related we are in the past 15 generations!

Three Ways to View Your Relatives

There are three ways to access and view your relatives, and how you connect.

  1. Sign in and click through the above “View Relatives” link, which is what we’ll do first.
  2. Click on your friend’s social media link to see if you match someone. We’ll do this second.
  3. Sign in and search for someone. For example, I know my cousin, Katy is participating because on her social media platform, she shared and posted the “Could we be related” placard, and I clicked through earlier to verify. But now I want to see more.

Let’s Get Organized

Before we start viewing relatives, let’s organize a bit. The relatives at RootsTech feature is only available through the end of March – the 25th I think. So don’t delay starting to work with your relatives.

I created a spreadsheet.

I devised a methodology that I think makes sense. I’ll step through it with you as I work through my own list.

Click on “View Relatives” to see your relatives and how you connect with them.

As you can see, I only have 300 relatives available through this portal. I can see others, but they aren’t organized for me and available this way.

I began my spreadsheet with a list of ancestors as presented by FamilySearch.

If you click on the “By Ancestor” dropdown, you’ll see your ancestors, according to the FamilySearch tree.

You will see 7 generations of ancestors.

I simply typed each ancestor into a spreadsheet, adding a few columns that I’ll fill in for each person I’m related to through those ancestors.

Now is a good time to ask yourself if any of these ancestors have “special needs” in your genealogy.

Ancestor Focus Questions

  • Whose mtDNA do I need?
  • Whose Y DNA do I need?
  • What ancestors do I need autosomal matches from?
  • What ancestors are from overseas so might have few cousins in the database?
  • What ancestors do I need help with?

If there is something that finding cousins could help with, be sure to consider that when viewing your matches.

There are also “ancestors” in FamilySearch which are incorrect, either slightly, meaning someone added a nonexistent middle name or misspelled something, or entirely, meaning they aren’t an ancestor.

I’m including these in my spreadsheet for two reasons. First, so I can correct the tree because I owe that to my ancestors. I AM GOING TO BE PART OF THE SOLUTION!!!

I want to leave this earth a better genealogical place and I fix what I can in public trees. Ummm, especially when I realize that some of my own speculation from years back, even though I clearly stated it was speculation, is now recorded for posterity in universal trees.

I can work with the ancestors AFTER RootsTech, but I have to work with my cousins now due to the end-of-March deadline. However, I need to remember which ancestors need attention – hence, the spreadsheet.

Second, this doesn’t mean I’m not related to the cousins attributed to these ancestors. Some common ancestor is in that “slot,” it’s just that the one currently assigned needs attention. Ancestor surgery😊

Please, do not let these issues upset you to the point that you can’t enjoy and benefit from the great features that connect you to your cousins. You never know cousin you’ll meet just might have the key to unraveling a mystery. Maybe even that ancestor in question. Or maybe they have a photo or item you’ll cherish. The best part is that you already know they are interested in genealogy because they’ve signed up for RootsTech, the Relatives app, and connected themselves to the FamilySearch Tree.

One big tree is far from perfect, but you can help by improving and participating. I’m so grateful to those who came before and have done just that.

OK, now you’re ready to begin working with your cousins!!!

1 – Sign In and View Relatives

The default view is “By Location.” Locations are states and countries. However, what you actually see, I believe, is your cousins in the “closest” to “furthest” order.

You can view each cousin, or you can view your cousins by ancestor. That’s what I decided to do, in part because it allows me to focus on that ancestor and what I need from them. For example, if I’m looking for a cousin who might be able to contribute Y or mitochondrial DNA, I need to remember that when viewing how my cousins descend from our common ancestors.

Click the down arrow on your ancestor to view people descended from that person. It’s worth noting that you might want to begin working with the most distant generation, because if someone descends from a common ancestor two generations ago, they also descend from the same common ancestors seven generations ago.

In other words, Melissa is my only cousin match through Hiram Ferverda, but reaching back several generations, she’s one of several people descended from other ancestors in that line.

If I click on Melissa, I can do three things. Send her a message, view our relationship or put her on my contact list.

Contact List

The contact list stays intact when you sign in AFTER RootsTech is over.

When you click on “Contact”, RootsTech adds the name of your common ancestor. When you message someone, that message is preserved too.

I still have my messages and contacts from RootsTech last year, and earlier, so don’t neglect to do this.

Click on “Relationship” to see how you are related.

You can click on any of these ancestors to see additional information. You might be surprised to see photos in the memories section. I found a photo of one of my ancestor’s children that I didn’t know existed.

I’m adding the information about Melissa to my spreadsheet.

She is related to me through both my great-grandfather and great-grandmother, and of course their upstream ancestors too.

Click on “Message” to send your cousin a greeting.

Of course, I want to know if my cousins have DNA tested, and where. Cousin matches are critical to confirm ancestors and unravel the identity of those knotty mystery ancestors. Note that two of my sessions cover this topic, “Associating Autosomal DNA Segments With Ancestors” and “What Can I DO With Ancestral DNA Segments?”

You can also go to each DNA testing vendor where you’ve tested or uploaded and search to see if someone with that name or a similar name is on your match list.

To use a chromosome browser to be able to utilize those matching segments, you’ll need to have tested at 23andMe, FamilyTreeDNA, or MyHeritage, or uploaded your DNA file to either FamilyTreeDNA or MyHeritage. You can find matches at Ancestry and ask if they will upload their DNA file to those companies too, or to GEDmatch, to receive more matches and tools.

Under ancestors, the share button shares the “Could We Be Related” post to social media. It’s an easy, fun thing for people to do. Hopefully, they will click, signup, and then tell reply on social media to say if you’re related or not! People have been having so much fun with this in the past week or so.

This brings me to the second way you can see how you are related to people – including those more distantly related.

2 – Click On Social Media

I’m sure it comes as no surprise to you that I have LOTS of genealogy friends on social media. Many have shared the app question encouraging their friends to see if they are related.

Initially, this was a teaser and showed people how closely they were related, but didn’t show how. Now you can also see how you’re related. Here’s one of my friends.

I clicked to see if we are related, and sure enough, we are, at least supposedly. But hey, you never know, right.

I clicked to see how Katy and I are related and discovered that we are 11C2R

Now that’s a LONG WAY back, and I’m skeptical.

You can click to enlarge images.

Is this accurate?

Hmmm, I don’t know. I can validate the connection to Gideon Farris, but not to William Farris. However, I’m NOT going to discount this, because at FamilySearch, there may well be information that connects Gideon to William, and trust me, I’ll all ears. Gideon is one of my brick walls. Maybe I’ll discover that I match people who legitimately DO descend from William Farris. That would be at least SOME evidence and very encouraging!

I’m adding Katy to my spreadsheet, with a note about Gideon and William so I can check this out – after RootsTech.

This brings me to the third way to find cousins at RootsTech.

3 – Search for Attendees

Let’s say I want to see if I’m related to someone in particular. Maybe our common ancestor is further back than 7 generations, or maybe I want to check to see if I’m related to a friend or colleague.

Click on “Search,” then enter first, complete, or last names. People sometimes register with a different name or a slightly different name.

Please note that finding someone on the attendee list DOES NOT MEAN you are related. It just means they’ve registered.

I got really, really brave and typed in my husband’s name, found him, then clicked on “Relationship.”

Yes, the RootsTech tree reporting reaches back 15 generations. I’ve found legitimate very distant relationships with some people. Of course, every connection requires due diligence on your part to confirm. Don’t forget that you may be related to people in multiple ways, and this fun app only shows one path.

Have Fun

Please excuse me now because I have cousins and relationships to document. I need to run!

Don’t forget that new people will be added as they sign up for RootsTech and the Relatives feature at RootsTech. So you’ll need to check back through the end of March. Your spreadsheet will make it easy to see who you’ve already processed, and who you haven’t.

Save the Dates – March 3-5

Save the dates – March 3-5, just a couple of days away now. Be sure to check out the Expo Hall too. The vendors will be having presentations in their virtual booths and of course, sales!

Don’t forget that the times listed are MST (Mountain Standard Time.)

I’ll be telling you more about my sessions in a day or two.

Hint – my sessions are live – not recorded in advance, so you can ask questions and we can interact. I’m either brave or crazy😊, or maybe both. Let’s hope those temperamental “technology gods” smile on us those days.

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Preserving Items for Future DNA Testing – Teeth, Stamps, Envelopes, Hats, Hair and More

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I often receive questions about testing items from deceased people. Is that type of testing available, and is it successful?

The answer is some shade of grey depending on several factors.

So, let’s start with no and work our way up!

NO

Today for the normal air-breathing human, testing items for DNA in a commercial lab for genealogical purposes is not yet feasible. In part, this is due to the labor-intensive extraction costs plus the fact that often, when DNA is able to be retrieved, it’s not of sufficient quality to pass the stringent guidelines of the testing companies.

Compounding that issue is one of consent. How does the testing company actually know the item is from someone deceased AND that you have the legal right to request the specified service?

There are other problems too.

How do you know the stamp was really licked by your ancestor or the intended person and not by the person at the post office, or a family member or neighbor? You don’t.

How do you know the DNA retrieved is actually that of your ancestor or intended person and not contaminant DNA from someone else? You don’t.

And yes, I know there are companies that enter our periphery from time to time that advertise the ability to provide this service. So far, I’ve not seen consistent success which is why these companies don’t stay around long. It’s very expensive, for them and for the consumer, just to try. Regardless of the outcome.

The Technology

The intricate extraction methodology and processing is the same technology used to process forensic samples from crime scenes or to identify unknown deceased people.

Clearly, in some cases, it’s technically possible. However, remember that this type of work requires a special lab, costs in the ballpark of $2000 per sample, or more, and the results often need to be compared in a database environment that accepts partial or degraded results.

My advice – don’t even attempt this now unless you have LOTS of whatever it is from the deceased person and don’t mind sacrificing some of it, along with some big $$, and be prepared to receive no result. I’ve now tried this twice without success.

However, this isn’t the situation with someone recently deceased.

YES

While processing DNA from the recently deceased is not a commercially available service today, it’s sometimes possible.

You need to collect a DNA sample immediately after death using a swab kit. If you’re like me, you always have a DNA kit at home, but you might not be like me or you might not be at home.

You can call FamilyTreeDNA and have them overnight a kit to you or the funeral home, or you can go to the closest pharmacy and purchase an Identigene DNA kit. This brand includes swabs. Ask the mortician to swab the inside of the cheeks of the deceased. (Do NOT send the swabs in the kit to Identigene – you’re only using their swabs in order to send it to FamilyTreeDNA.)

Hopefully, there is no denture adhesive present, as that interferes with DNA processing.

While swabbing is recommended prior to embalming, if embalming has already occurred, ask them to swab anyway. The worst thing that will happen is that it won’t work. It’s worth a try.

I wrote about the process, here.

Clearly, with a swab kit, you’ll need a DNA company that uses swabs to do the processing. That eliminates both Ancestry and 23andMe which use spit kits, leaving as candidates only FamilyTreeDNA and MyHeritage. Fortunately, you can upload DNA files from one to the other.

MAYBE

Some things fall in-between yes and no, meaning taking a swab of a recently deceased person to process at FamilyTreeDNA and attempting to process an artifact.

For example, blood cards or tissue samples fall into this category. In this case, the challenge will be finding a lab that will accept that item.

FamilyTreeDNA may, but you’ll need to contact them in advance as it’s on a case-by-case basis.

Candidate Items

Please keep in mind that all items can be contaminated by handling. To handle, wear sterile gloves and use sterile tweezers. Your goal is to avoid contamination by handling or storage.

We’ll discuss storage and preservation in the next section.

Here’s a list of common candidate items and my comments:

Item Comments
Hair Can be contaminated. May not include the follicle which is your best bet for autosomal DNA. While mitochondrial DNA is most typically extracted from hair, using forensic methods, in some cases, autosomal can be extracted as well.
Envelopes and stamps High probability of contamination. Special processing needs to be utilized due to the adhesive which in some cases is animal-based which means it contains animal DNA.
Teeth Should be in good shape and not have cavities, meaning baby teeth are better candidates than extracted teeth. Normally, adult teeth aren’t extracted without a reason. Don’t throw anything away though.
Hearing aids Hearing aids often contain ear wax and skin cells and make good candidates.
Glasses nose pads The nose pad or metal connecting the nose pad to the glasses frame sometimes harbors skin cells.
Dentures Possible candidates although adhesive interferes with DNA as does soaking denture in cleaning solutions.
Electric razors Excellent candidates since residue held in razors generally contains skin cells. However, be sure your relative is the only person who used the razor. Contact the lab for instructions before extracting the contents.
Blood cards and tissue samples Excellent source but the lab needs to be contacted about whether they accept this type of sample and how to send it safely. Blood and tissue samples may be held by a medical facility if the person was hospitalized, received treatment, or a post-mortem was performed.
Hats, sweaty items, etc. Possible candidates but it depends on the item, its age, and condition. Contact the lab with specifics. With hats, check for embedded hairs which may be a better source than the hat itself.
Used Kleenex type tissue If you’re positive that the tissue was used by the target person, this is a great source of DNA.
Toothbrush Sometimes, but bacteria can be an issue. Doesn’t hurt to save a toothbrush after allowing to dry completely
Fingernail and toenail clippings Clippings are a great source of DNA. Be sure to check clippers, as some have little “catchers” built-in. Also check the drawer where clippers are stored, assuming there is only one individual using those clippers.
Travel bag If your relative traveled from time to time, check the bag in their suitcase that held their personal items. You never know what you might find. Mine holds many DNA-rich items and yours probably does too.

If your relative passed away from something communicable, you need to take that into consideration.

Storage and Preservation Guidelines

While this type of DNA processing service isn’t commercially available as an off-the-shelf service yet today, as technology improves and prices reduce, I feel confident it will be a viable, readily-available service someday. I’ve been saying that for years now, and I just hope someday isn’t too far in the future.

Your challenge is to keep your sample of whatever it is in good condition, so it doesn’t degrade irrecoverably while you are waiting.

  • NEVER store items in plastic including ziplocks or baggies. Plastic prevents air circulation and encourages mold.
  • NEVER use any type of tape or adhesive.
  • DO store each item individually in paper, like an envelope, preferable acid-free paper.
  • If you store an item in fabric, DO wash the fabric first to remove dye, stabilizers and dirt as well as DNA residue from other people. Handle the fabric with sterile gloves after washing.
  • DON’T store the item against wood and not in a cedar chest. Wood contains tannins which are acids that stain and leach into other items.
  • DON’T store the item in the sun, a hot attic or humid basement.
  • DO store the item in a safe, dark location in a temperature-controlled area of your home.
  • DO label the container the item is stored in.

I have several items from my father and grandfather that I’m keeping with the hope of someday being able to utilize them. I have them stored individually in an acid-free envelope, in a small train case, buffered by acid free tissue paper, with nothing else touching the envelope, in my closet.

I’ve also enclosed a note for my daughter, just in case she finds those one day and wonders what they are and why they are packaged in that manner.

Don’t Throw It Away

Let’s say you’ve already done DNA testing on your parent, then they pass away.

As you go through their things, you see hairbrushes and razors and maybe even find a tissue in a nightgown pocket.

You think about how those items would be good for DNA testing and you’re glad you already did that. That means you don’t need to save those things, right? Wrong!

DON’T throw those items away. They’re treasure. There may be new vendors in the future, new companies that process and utilize DNA. There will assuredly be advances in science and new products, and you may wish you had those DNA sources.

I saved my Mom’s hairbrush and Kleenexes from her bathrobe pocket for this exact reason. She lived alone and no one else would have used those items.

Complicating Circumstances

Biological processes accelerate and degrade DNA.

For example, heat.

The heat of modern-day cremations destroys all DNA, even though residual bone fragments are left.

Cold, meaning freezing, would typically preserve DNA, unless a repeated freeze/thaw cycle is involved. In other words, don’t store those teeth in a frost-free refrigerator. I know someone who froze something in an ice cube tray and suffice it to say that a guest received a VERY unexpected surprise one hot summer day. In another instance, a power failure caused everything in a freezer to be thrown away. Freezing is generally not the best choice.

If your ancestor died in a fire, or the home burned but some items were preserved – maybe.

If flooding or water was involved, again, think mold and rapid degradation. Dry those items but without high heat and not in a dryer. If you’re dealing with sewer water, dispose of the items.

The bottom line is this – if there’s enough of an item left to see and identify, other than cremains, there’s enough to preserve, just in case.

Truly, you never know. The best you can do is to begin preservation now and work with what you have.

Staying on the Right Side of the Law

I’m not a lawyer, but I do know that there are required legal procedures to exhume remains for testing. Those laws and procedures vary by location.

Do not try this at home. Contact a lawyer in the jurisdiction where the person you hope to test is buried and be prepared to convince at least five people that your need is pressing and justifiable:

  • The lawyer (bring a large check)
  • Other family members, ALL of whom will likely be required to sign and notarize their agreement
  • A judge who will ultimately decide
  • The coroner or other individual to arrange exhumation and take the sample
  • A lab to process the sample and if it’s not your DNA testing lab, agreement from your DNA lab to allow your sample to be uploaded

You’ve probably figured out why you never see anyone discussing having exhumed their dearly departed for testing. The hoops are many and the process is exorbitantly complex and expensive. Just moving a grave a mile or so down the road when a cemetery was being permanently flooded, without getting a court order or taking a biological sample cost a friend in excess of $20,000 several years ago.

Alternate Strategies

If you’re seeking the Y DNA or mitochondrial DNA of that ancestor, another family member appropriately descended may be able to serve as a proxy. Work your way up the tree to find test candidates and create a DNA Pedigree Chart.

Males inherit their father’s Y chromosome along with their surname. Everyone received their mother’s mitochondrial DNA, but only females pass it on.

Autosomal DNA, at least in part can sometimes be inferred by matching with other people from the same side through family matching, or conversely, not sharing a match with someone that you know is from either your paternal or maternal side on the same segment.

You can read more about how different kinds of DNA is passed to descendants, here.

Summary

Today, testing most artifact items isn’t a viable strategy to retrieve DNA, but there are some notable exceptions. Alternate testing strategies may prove more fruitful

However, taking appropriate measures to preserve these items for future testing is a great strategy. The worst that can happen is that it doesn’t work. You’ll never know if you don’t take those preservation steps today.

The best outcome, of course, is that one day your ancestor’s DNA will be able to assist your genealogy. I can hardly wait!

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If you haven’t already subscribed (it’s free,) you can receive an email whenever I publish by clicking the “follow” button on the main blog page, here.

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I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

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AutoKinship at GEDmatch by Genetic Affairs

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Genetic Affairs has created a new version of AutoKinship at GEDmatch. The new AutoKinship report adds new features, allows for more kits to be included in the analysis, and integrates multiple reports together:

  • AutoCluster – the autoclusters we all know and love
  • AutoSegment – clusters based on segments
  • AutoTree – reconstructed tree based on GEDCOM files of you and your matches, even if you don’t have a tree
  • AutoKinship – the original AutoKinship report provided genetic trees. The new AutoKinship report includes AutoTree, combines both, and adds features called AutoKinship Tree. (Trust me on this one – you’ll see in a minute!)
  • Matches
    • Common Ancestors with your ancestors
    • Common Ancestors between matches, even if they don’t match your tree
    • Common Locations

Maybe the best news is that some reports provide automatic triangulation because, at GEDmatch, it’s possible to not only see how you match multiple people, but also if those people match each other on that same segment. Of course, triangulation requires three-way matching in addition to the identification of common ancestors which is part of what AutoKinship provides, in multiple ways.

Let’s step through the included reports and features one at a time, using my clusters as an example.

Order Your Report

As a Tier 1 GEDmatch customer, sign in, select AutoKinship and order your report.

Note that there are now two clustering settings, the default setting and one that will provide more dense clusters. The last setting is the default setting for AutoKinship, since it has been shown to produce better AutoKinship results.

You can also select the number of kits to consider. Since this tool is free with a GEDmatch Tier 1 subscription, you can start small and rerun if you wish, as often as you wish.

Currently, a maximum of 500 matches can be included, but that will be increased to 1000 in the future. Your top 500 matches will be included that fall within the cM matching parameters specified.

I’m leaving this at the maximum 400 cM threshold, so every match below that is included. I generally leave this default threshold because otherwise my closest matches will be in a huge number of clusters which may cause processing issues.

For a special use case where you will want to increase the cM threshold, see the Special Use Cases section near the end of this article.

You can select a low number of matches, like 25 or 50 which is particularly useful if you want to examine the closest matches of a kit without a tree.

Keep in mind that there is currently a maximum processing time of 10 minutes allowed per report. This means that if you have large clusters, which are the last ones processed, you may not have AutoKinship results for those clusters.

This also means that if you select a high cM threshold and include all 500 allowable matches, you will receive the report but the AutoKinship results may not be complete.

When finished, your report will be delivered to you as a download link with an attached zipped file which you will need to save someplace where you can find it.

Unzip

If you’re a PC user, you’ll need to unzip or extract the files before you can use the files. You’ll see the zipper on the file.

If you don’t extract the contents, you can click on the file to open which will display a list of the files, so it looks like the files are extracted, but they aren’t.

You can see that the file is still zipped.

You can click on the html file which will display the AutoCluster correctly too, but when you click on any other link within that file, you’ll receive this error message if the file is still zipped.

If this happens to you, it means the file is still zipped. Close the files you have open, right click on the yellow zipped file folder and “extract all.”

Then click on the HTML link again and everything should work.

Ok, on to the fun part – the tools.

Tools

I’ve written about most of these tools individually before, except for the new combinations of course. I’ve put all of the Genetic Affairs Tools, Instructions and Resources in one article that you can find here.

I recommend that you take a look to be sure you’re using each tool to its greatest advantage.

AutoCluster

Click on the html file and watch your AutoCluster fly into place. I always, always love this part.

The first thing I noticed about my AutoCluster at GEDmatch is that it’s HUGE! I have a total of 144 clusters and that’s just amazing!

Information about the cluster file, including the number of matches, maximum and minimum cM used for the report, and minimum cluster size appears beneath your cluster chart.

22 people met the criteria but didn’t have other matches that did, so they are listed for my review, but not included in the cluster chart.

At first glance, the clusters look small, but don’t despair, they really aren’t.

My clusters only look small because the tool was VERY successful, and I have many matches in my clusters. The chart has to be scaled to be able to display on a computer monitor.

New Layout

Genetic Affairs has introduced a new layout for the various included tools.

Each section opens to provide a brief description of the tool and what is occurring. This new tool includes four previous tools plus a new one, AutoCluster Tree, as follows:

AutoCluster

AutoCluster first organizes your DNA matches into shared match clusters that likely represent branches of your family. Everyone in a cluster will likely be on the same ancestral line, although the MRCA between any of the matches and between you and any match may vary. The generational level of the clusters may vary as well. One may be your paternal grandmother’s branch, another may be your paternal grandfather’s father’s branch.

AutoSegment

AutoSegment organizes your matches based on triangulating segments. AutoSegment employs the positional information of segments (chromosome and start and stop position) to identify overlapping segments in order to link DNA matches. In addition, triangulated data is used to collaborate these links. Using the user defined minimum overlap of a DNA segment we perform a clustering of overlapping DNA segments to identify segment clusters. The overlap is calculated in centimorgans using human genetic recombination maps. Another aspect of overlapping segments is the fact that some regions of our genome seem to have more matches as compared to the other regions. These so-called pile-up areas can influence the clustering. The removal of known pile-up regions based on the paper of Li et al 2014 is optional and is not performed for this analysis However, a pileup report is provided that allows you to examine your genome for pileup regions.

AutoTree

By comparing the tree of the tested person and the trees from the members of a certain cluster, we can identify ancestors that are common amongst those trees. First, we collect the surnames that are present in the trees and create a network using the similarity between surnames. Next, we perform a clustering on this network to identify clusters of similar surnames. A similar clustering is performed based on a network using the first names of members of each surname cluster. Our last clustering uses the birth and death years of members of a cluster to find similar persons. As a consequence, initially large clusters (based on the surnames) are divided up into smaller clusters using the first name and birth/death year clustering.

AutoKinship

AutoKinship automatically predicts family trees based on the amount of DNA your DNA matches share with you and each other. Note that AutoKinship does not require any known genealogical trees from your DNA matches. Instead, AutoKinship looks at the predicted relationships between your DNA matches, and calculates many different paths you could all be related to each other. The probabilities used by this AutoKinship analysis are based on simulated data for GEDmatch matches and are kindly provided by Brit Nicholson (methodology described here). Based on the shared cM data between shared matches, we create different trees based on the putative relationships. We then use the probabilities to test every scenario which are then ranked.

AutoKinship Tree

Predicted trees from the AutoTree analysis are based on genealogical trees shared by the DNA matches and, if available, shared by the tested person. The relationships between DNA matches based on their common ancestors as provided AutoTree are used to perform an AutoKinship analysis and are overlayed on the predicted AutoKinship tree.

AutoKinship Tree is New

AutoKinship Tree is the new feature that combines the features of both AutoTree and AutoKinship. You receive:

  • Common ancestors between you and your matches
  • Trees of people who don’t share your common ancestors but share ancestors with each other
  • Combined with relationship predictions and
  • A segment analysis

Of course, the relative success of the tree tools depends upon how many people have uploaded GEDCOM files.

Big hint, if you haven’t uploaded your family tree, do so now. If you are an adoptee or searching for a parent and don’t know who your ancestors are, AutoKinship Tree does its best without your tree information, and you will still benefit from the trees of others combined with predicted relationships based on DNA.

It’s easier to show you than to tell you, so let’s step through my results one section at a time.

I’m going to be using cluster 5 which has 32 members and cluster 136 which has 8 members. Ironically, cluster 136 is a much more useful cluster, with 8 good matches, than cluster 5 which includes 32 people.

Results of the AutoKinship Analyses

As you scroll down your results, you’ll see a grid beneath the Explanation area.

It’s easy to see which cluster received results for each tool. My cluster 5 has results in each category, along with surnames. (Notice that you can search for surnames which displays only the clusters that contain that surname.)

I can click on each icon to see what’s there waiting for me.

Additionally, you can click at the top on the blue middle “here” for an overview of all common ancestors. Who can resist that, right?

Click on the ancestor’s name or the tree link to view more information.

You can also view common locations too by clicking on the blue “here” at far right. A location, all by itself, is a HUGE hint.

Clicking on the tree link shows you the tree of the tester with ancestors at that location. I had several others from North Carolina, generally, and other locations specifically. Let’s take a look at a few examples.

Common Ancestor Clusters

Click on the first blue link to view all common ancestors.

Common Ancestor Clusters summarize all of the clusters by ancestor. In other words, if any of your matches have ancestors in common in their tree, they are listed here.

These clusters include NOT just the people who share ancestors in a tree with you, but who also share known ancestors with each other BUT NOT YOU. That may be incredibly important when you are trying to identify your ancestors – as in brick walls. Your ancestors may be their ancestors too, or your common segments might lead to your common ancestors if you complete their tree.

There are other important hints too.

In my case, above, Jacob Lentz is my known ancestor.

However, Sarah Barron is not my ancestor, nor is John Vincent Dodson. They are the descendants of my Dodson ancestor though. I recognized that surname and those people. In other instances, recognizing a common geography may be your clue for figuring out how you connect.

In the cluster column at left, you can see the cluster number in which these people are found.

Common Locations Table

Clicking on the second link provides a Common Location Table

Some locations are general, like a state, and others are town, county or even village names. Whatever people have included in their GEDCOM files that can be connected.

Looking at this first entry, I recognize some of the ancestral surnames of Karen’s ancestors. The fact that we are found in the same cluster and share DNA indicates a common ancestor someplace.

Check for this same person in additional locations, then, look at their tree.

Ok, back to the AutoKinship Analysis Table and Cluster 136.

Cluster 136

I’m going to use Cluster 136 as an example because this cluster has generated great reports using all of the tools, indicated by the icon under each column heading. Some clusters won’t have enough information for everything so the tools generate as much as possible.

Scrolling down to Cluster 136 in the AutoCluster Information report, just beneath the list of clusters, I can see my 8 matches in that cluster.

Of course, I can click on the links for specific information, or contact them via email. At the end of this article in the “Tell Me Everything” section, I’ll provide a way to retrieve as much information as possible about any one match. For now, let’s move to the AutoTree.

Cluster 136 AutoTree

Clicking on the icon under AutoTree shows me how two of the matches in this cluster are related to each other and myself.

Note that the centimorgan badges listed refer to the number of cM that I share with each of these people, not how much they share with each other.

Click on any of the people to see additional information.

When I click on J Lentz m F Moselman, a popup box shows me how this couple is related to me and my matches.

Of course, you can also view the Y DNA or mitochondrial DNA haplogroups if the testers have provided that information when they set up their GEDmatch profile information.

Just click on the little icons.

If the testers have not provided that information, you can always check at FamilyTreeDNA or 23andMe, if they have tested at either of those vendors, to view their haplogroup information.

Today, GEDmatch kit numbers are assigned randomly, but in the early days, before Genesis, the leading letter of A meant AncestryDNA, F or T for FamilyTreeDNA, M for 23andMe and H for MyHeritage. If the kit number is something else, perform a one-to-one or a one-to-many report which will display the source of their DNA file.

The small number, 136 in this case, beside the cM number indicates the cluster or clusters that these people are members of. Some people are members of multiple clusters

Let’s see what’s next.

Cluster 136 Common Ancestors

Clicking on the Ancestors icon provides a report that shows all of the Ancestor Clusters in cluster 136.

The difference between this ancestor chart and the larger chart is that this only shows ancestors for cluster 136, while the larger chart shows ancestors for the entire AutoCluster report.

Cluster 136 Locations

All of the locations shown are included in trees of people who cluster together in cluster 136. Of course, this does NOT mean that these locations are all relevant to cluster 136. However, finding my own tree listed might provide an important clue.

Using the location tool, I discover 5 separate location clusters. This location cluster includes me with each tester’s ancestors who are found in Montgomery County, Ohio.

The difference between this chart for cluster 136 only and the larger location chart is that every location in this chart is relevant for people who all cluster together meaning we all share some ancestral line.

Viewing the trees of other people in the cluster may suggest ancestors or locations that are essential for breaking down brick walls.

Cluster 136 AutoKinship

Clicking on the anchor in the AutoKinship column provides a genetically reconstructed tree based on how closely each of the people match me, and each other. Clearly, in order to be able to provide this prediction, information about how your matches also match each other, or don’t, is required.

Again, the cM amount shown is the cM match with me, not with each other. However, if you click on a match, a popup will be shown that shows the shared cM between that person and the other matches as well as the relationship prediction between them in this tree

So, Bill matches David with a total of 354.3 cM and they are positioned as first cousins once removed in this tree. The probability of the match being a 1C1R (first cousin once removed) is 64.9%, meaning of course that other relationships are possible.

Note that Bill and David ALSO share a segment with me in autosegment cluster 185, on chromosome 3.

It’s important to note that while 136 is the autocluster number, meaning that colored block on the report, WITHIN clusters, autosegment clusters are formed and numbered. 

Each autosegment cluster receives its own number and the numbers are for the entire report. You will have more autosegment clusters than autoclusters, because at least some of the colorful autoclusters will contain more than one segment cluster.

Remember, autoclusters are those colorful boxes of matches that fly into place. Autosegment clusters are the matching triangulated clusters on chromosomes and they are represented by the blue bars, shown below.

AutoCluster 136 contains 5 different autosegment clusters, but Bill is only included in one of those autosegment clusters.

You’ll notice that there are some people, like Robin at the bottom, who do match some other people in the cluster, but either not enough people, or not enough overlapping DNA to be included as an autocluster member.

The small colored chromosomes with numbers, boxed in red, indicate the chromosome on which this person matches me.

If you click on that chromosome icon, you’ll see a popup detailing everyone who matches me on that segment.

Note that in some cases a member of a segment cluster, like Robin, did not make it in the AutoCluster cluster. You can spot these occurrences by scrolling down and looking at the cluster column which will then be empty for that particular match.

Reconstructed AutoKinship Trees in Most Likely Order

Scrolling down the page, next we see that we have multiple possible trees to view. We are shown the most likely tree first.

Tree likelihood is constructed based on the combined probability of my matching cM to an individual plus their likely relationship to each other based on the amount of DNA they share with each other as well.

In my case, all of the first 8 trees are equally as likely to be accurate, based on autosomal genetic relationships only. The ninth tree is only very slightly less likely to be accurate.

The X chromosome is not utilized separately in this analysis, nor are Y or mitochondrial DNA haplogroups if provided.

DNA Relationship Matrix

Continuing to scroll down, we next see the DNA matrix that shows relationships for cluster 5 in a grid format. Click on “Download Relationship Matrix” to view in a spreadsheet.

Keep scrolling for the next view which is the Individual Segment Cluster Information

Individual Segment Cluster Information

Remember that we are still focused on only one cluster – in this case, cluster 136. Each cluster contains people who all match at least some subset of other people in the cluster. Some people will match each other and the tested person on the same chromosome segment, and some won’t. What we generally see within clusters are “subclusters” of people who match each other on different chromosomes and segments. Also, some matches from cluster 136 might match other people but those matches might not be a member of cluster 136.

In autocluster 136, I have 14 DNA segments that converge into 5 segment clusters with my matches. Here’s segment cluster 185 that consists of two people in addition to me. Note that for individuals to be included in these segment clusters at GEDmatch, they must triangulate with people in the same segment cluster.

From left to right, we see the following information:

  • AutoCluster number 136, shown below

  • Segment cluster 185. This is a segment cluster within autocluster 136.

  • Segment cluster 185 occurs on chromosome 3, between the designated start and stop locations.
  • The segment representation shows the overlapping portions of the two matches, to me. You can easily see that they overlap almost exactly with each other as well.
  • The SNP count is shown, followed by the name and cM count.

Cluster 136 AutoKinship Tree

The AutoKinship Tree column is different from the AutoKinship column in one fundamental way. The new AutoKinship Tree feature combines the genealogical AutoTree and the genetic AutoKinship output together in one report.

You can see that the “prior” genealogical tree information that one of my matches also descends from Jacob Lentz (and wife, if you click further) has now been included. The matches without trees have been reconstructed around the known genealogy based on how they match me and each other.

I was already aware of how I’m related to Bill, David, *C and *R, but I don’t know how I am related to these other people. Based on their kit identifier, I can go to the vendor where they tested and utilize tools there, and I can check to see if they have uploaded their DNA files elsewhere to discover additional records information or critical matches. Now at least I know where in the tree to search.

Cluster 136 AutoSegment

Clicking on AutoSegment provides you with segment information. Each cluster is painted on your chromosomes.

By hovering over the darkly colored segments, which are segment clusters, you can view who you match, although to view multiple matches, continue scrolling.

In the next section, you’ll see the two segment clusters contained wholly within cluster 136.

Following that is the same information for segment clusters partially linked to cluster 136, but not contained wholly within 136.

Bonus – Tell Me Everything – Individual Match Clusters

We’ve focused specifically on the AutoKinship tools, but if you’re interested in “everything” about one specific match, you can approach things from that perspective too. I often look at a cluster, then focus on individuals, beginning with those I can identify which focuses my search.

If you click on any person in your match list, you’ll receive a report focusing on that person in your autocluster.

Let’s use cousin Bill as an example. I know how he’s related to me.

You can choose to display your chosen cluster by:

  • Cluster
  • Number of shared matches
  • Shared cM with the tester
  • Name

I would suggest experimenting with all of the options and see which one displays information that is most useful to the question you’re trying to answer.

Beneath the cluster for Bill, you’ll see the relevant information about the cluster itself. Bill has cluster matches on two different chromosomes.

The AutoCluster Cluster member Information report shows you how much DNA each cluster member shares with the tested person, which is me, and with each other cluster member. It’s easy to see at a glance who Bill is most closely related to by the number of cMs shared.

Only one of Bill’s chromosomes, #3, is included in clusters, but this tells me immediately that this/these segments on chromosome 3 triangulate between me, Bill, and at least one other person.

Segments shown in orange (chromosome 22) match me, but are not included in a cluster.

Special Use Cases – Unknown People

For adoptees and people trying to figure out how they are related to closer relatives, especially those without a tree, this new combined AutoKinship tool is wonderful.

400 cM is the upper default limit when running the report, meaning that close family members will not be included because they would be included in many clusters. However, you can make a different selection. If you’re trying to determine how several closely related people intersect, select a high threshold to include everyone.

Select a lower number of matches, like 25 or 50.

In this example, ‘no limit” was selected as the upper total match threshold and 25 closest matches.

AutoKinship then constructs a genetic tree and tells you which trees are possible and most likely. If some people do have trees, that common ancestor information would be included as well.

Note that when matches occur over the 400 cM threshold, there will be too many common chromosome matches so the chromosome numbers are omitted. Just check the other reports.

This tool would have helped a great deal with a recent close match who didn’t know how they are related to my family.

You can see this methodology in action and judge its accuracy by reconstructing your own family, assuming some of your known family members have uploaded to GEDmatch. Try it out.

It’s a Lot!

I know there’s a lot here to absorb, but take your time and refer back to this article as needed.

This flexible new tool combines DNA matching, genealogy trees, genetic trees, locations, autoclusters, a chromosome browser, and triangulation. It took me a few passes and working with different clusters to understand and absorb the information that is being provided.

For people who don’t know who their parents or close relatives are, these tools are amazing. Not only can they determine who they are related to, and who is related to each other, but with the use of trees, they can view common ancestors which provides possible ancestors for them too.

For people painting their triangulated segments at DNAPainter, AutoKinship provides triangulation groups that can be automatically painted using the Cluster Auto Painter, here, plus helps to identify that common ancestor. You can read more about DNAPainter, here.

For people seeking to break down brick walls, AutoKinship Tree provides assistance by providing tree matching between your matches for common ancestors NOT IN YOUR TREE, but that ARE in theirs. Your brick walls are clearly not (yet) identified in your tree, although that’s our fervent hope, right?

Even if your matches’ trees don’t go far enough back, as a genealogist, you can extend those trees further to hopefully reveal a previously unknown common ancestor.

The Best Things You Can Do

Aside from DNA testing, the three best things you can do to help yourself, and your clusters are:

  • Upload your GEDCOM file, complete with locations, so you have readily available trees. Ask your matches to do so as well. Trees help you and others too.
  • Encourage people you match at Ancestry who provides no chromosome segment information or chromosome browser to upload a copy of their DNA files and tree.
  • Test your family members and cousins, and encourage them to upload their DNA and their trees. Offer to assist them. You can find step-by-step download/upload instructions here.

Have fun!

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I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

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RootsTech Launches “Relatives at RootsTech” App – Are We Related?

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FamilySearch has launched their updated “Relatives at RootsTech” app just in time for RootsTech’s opening day, February 18th.

You can see how this works for yourself, here, AND see if we are related, according to the trees at FamilySearch. Click on this link and find out IF we’re related and how distantly. Starting February 18th, we’ll be able to find out HOW we’re related.

And yes, before you say it, those trees aren’t always accurate, but one of three situations will occur:

  • The connection is accurate.
  • It’s not accurate and you can correct it as a service to yourself all that follow.
  • The tree contains new information that will serve as a hint for you and lead to either condition one or two, above.

When you click on my link, you’ll be prompted to set up or update your own account, or you can simply enter www.familysearch.org/en/connect.

Please be sure to register for Full Access RootsTech, for free, while you’re there.

OK, here’s how this works.

Connect

You can click on “Join Event,” or you can scroll down for more info about other things you can do.

More Info

You can see who else shares a surname.

You can see how Relatives at RootsTech works.

You can see how many other people have signed up for this app and where they live.

On Valentines Day, more than 360,000 people had signed up for RootsTech itself, and that number is rising rapidly now. Last year, attendance reached over 1 million and this year’s signups are slightly ahead of last year’s at this time.

I hope all of the attendees sign up for Relatives at RootsTech so we can all see how we’re related.

Join Event

When you click on “Join Event,” you’ll be promoted to either join FamilySearch or update your profile to grant permission for FamilySearch to display your connection to your cousins.

You can personalize the experience by uploading a photo.

I uploaded a portrait so people will recognize me. We can’t see each other in person this year, but we can at least smile when we see our cousins’ photos.

You’ll be asked for some pretty basic information.

Starting on February 18th, you’ll be able to see exactly how you’re related to your cousins.

In the couple hours it took me to write this article, the total participants signed up for the Relatives at RootsTech app increased by more than 2,500 to 15,640.

Register for RootsTech

Be sure to register for RootsTech when you’re updating your profile.

RootsTech is totally free with a dynamite lineup. Why wouldn’t anyone sign up for All Access?

Keynotes

One of the other generous speakers, Dr. Penny Walters, created this collage of the keynote speakers including Thais Pacholek, Molly Yeh, Azumah Nelson, Diego Torres, Matthew Modine, Apollonia Poilane, Maysoon Zayid, Elder Ulisses Soares and his wife, Sister Rosana Soares.

#chooseconnection

RootsTech encourages us to #chooseconnection and see how we’re connected to each other, to history and to our homeland. Ironically, I didn’t know this when I was creating my sessions. My session, “Native American DNA – Ancient and Contemporary Maps” speaks to connection in just about every way possible. I hope you will join me for this session and several more too.

The speaker session agenda will be released soon, and you will be able to create an individual playlist.

After you update your account so that you can connect with others, you’ll be prompted to share. I posted this link to both Facebook and Twitter, and of course, I’m sharing with you here.

Beginning on February 18th and continuing beyond RootsTech, until March 25th, you’ll be able to see exactly how you are related to your cousins who have also signed up and opted in!

I have to tell you, several people have already commented, telling me we are cousins. I didn’t know we shared ancestors. I’m having so doggone much fun!

So, are we related?

Here’s the link to see for yourself. Let me know. I can’t wait to find out exactly how.

I’m starting a RootsTech friends spreadsheet to track exactly how I’m related to whom. Some of you HAVE to have info that I don’t and vice versa. That’s what sharing is all about, and maybe our DNA matches too!

Maybe you’d like to start a spreadsheet and keep track too. Be sure to collect contact information so you can connect after the conference. How many cousins will you find at RootsTech?

Are you doing anything special to prepare? Please share in the comments and let’s make this the best RootsTech ever.

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I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

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Join Me on Genealogy Quick Start TV LIVE on Thursday, February 10

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I’m excited to be a guest on Genealogy Quick Start TV with Shamele Jordon, this Thursday, February 10 from 3-4 Eastern time. Genealogy Quick Start is a live broadcast television show which airs on PhillyCAM, Philadelphia’s public access station. If you’re not local, don’t worry, you can still tune in easily at the time of the show.

This is an interactive genealogy TV program, not recorded and not a webinar.

Shamele and I will be talking about DNA and Native American Genealogy, both the topic and the book.

Does your family have an oral history that includes Native American heritage? If so, join us and learn the steps you can take to unravel this puzzle using various DNA tools and techniques.

We invite you to chat, comment, and ask questions.. Come join the fun.

Hope to see you Thursday!

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You’re always welcome to forward articles or links to friends and share on social media.

If you haven’t already subscribed (it’s free,) you can receive an email whenever I publish by clicking the “follow” button on the main blog page, here.

You Can Help Keep This Blog Free

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

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DNA from 459 Ancient British Isles Burials Reveals Relationships – Does Yours Match?

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In December 2021, two major papers were released that focused on the ancient DNA of burials from Great Britain. The paper, A high-resolution picture of kinship practices in an Early Neolithic tomb by Fowler et al provided a genetic analysis of 35 individuals from a Cotswold Neolithic burial who were found to be a multi-generational family unit. In Large-scale migration into Britain during the Middle to Late Bronze Age by Patterson et, the authors generated genome-wide data for 793 ancient burials from the British Isles and continental Europe to determine who settled Great Britain, from where, and when.

Of course, the very first thing genealogists want to know is, “Am I related?”

If we are related, it’s far too distant for the reach of autosomal DNA, but Y DNA and mitochondrial DNA might just be very interesting. If you haven’t yet tested your mother’s line mitochondrial DNA for males and females both, and paternal line Y DNA for males only, you’re in luck because you can purchase those tests here.

These two papers combined provide a significant window into the past in Great Britain; England, Scotland, Wales, and nearby islands.

First, let’s take a look at the Cotswold region.

The Cotswolds

Ancient DNA was retrieved from a cairn burial in the Cotswolds, a hilly region of Southwest England.

By Saffron Blaze – Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=15675403

Even today, the paused-in-time stone houses, fences, and ancient gardens harken back to earlier times.

By Peter K Burian – Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=70384620

Stunningly beautiful and historically important, the Cotswolds is a protected landscape that includes Neolithic burial chambers (3950-2450 BCE), Bronze and Iron Age forts, Roman villas, and eventually, the Celtic pathway known as Fosse Way.

The Hazelton North Long-Tomb Burial Site

The Fowler paper explores the kinship practices and relationships between the Cotswolds burials.

Click to enlarge images

The North Hazelton site was endangered due to repeated plowing in a farmer’s field. Excavation of the tomb occurred in 1981. A book was published in 1990 with a pdf file available at that link. The photo from 1979 on page 3 shows that the burial cairn only looks to be a slight rise in the field.

You can see on the map below from the UK Megalithic site map that there are many other locations in close proximity to the Hazelton North site, some with similarly arranged burials.

The paper’s authors state that there are 100 long cairns within 50 km of Hazelton North, and one only 80 meters away. Excavation in those tombs, along with archaeological evaluation would be needed to determine the ages of the cairns, if burial practices were the same or similar, and if any of the individuals were related to each other or the individuals in the North Hazelton cairn. In other words, were these separate cemeteries of an extended family, or disconnected burial grounds of different groups of people over time.

While the North Hazelton site no longer exists, as it was entirely excavated, on the same page, you can see photos before excavation, along with the main chamber which now resides in the Corinium Museum in Cirencester, just a few kilometers away.

The Fowler team analyzed 35 individuals who lived about 5,700 years ago, at least 100 years after cattle and cereal cultivation was introduced to Britain along with the construction of megalithic monuments. Stonehenge, the most well-known megalith, is located about 90 miles away and is estimated to be about 5,100 years old. The burials from Stonehenge indicate that they were primarily Early European Farmers (EEF) from Anatolia who first moved to Iberia, then on to Britain.

The remains analyzed in this paper were excavated from the Hazelton North Megalithic long-cairn type tomb.

The tomb was built between 5,695 and 5,650 years ago, with the stonework of the north passage collapsing and sealing off the north chamber between 5,660 and 5,630 years ago. All burials stopped in this location about 5,620 years ago, so the site was only in use for about 80 years.

The tomb seems to have been built with multiple passages in anticipation of planned burials by genealogical association. The arrangement of burials was determined by kinship, at least until the passage wall of the North chamber collapsed. The southern and northern chambers each housed two females’ descendants, respectively. While the male progenitor was significant in that this entire tomb was clearly his family tomb, the arrangement of the burials within the chambers suggests that the women were socially significant in the community, and to their families as well.

Osteological analysis reveals at least 41 individuals, 22 of whom were adults. Strontium isotope analysis indicates that most of the individuals had spent time in their childhood at least 40 km away. Authors of a 2015 paper interpret this to mean that the population as a whole was not sedentary, meaning that they may have moved with their livestock from place to place, perhaps based on seasons. Of course, this also calls into question what happened if an individual died while the group was not in the location of the burial cairn.

Of those individuals, 27 people were part of a 5-generation family with many interrelationships.

Of the 15 intergenerational genetic transmissions, all were through men, meaning every third, fourth or fifth generation individual was connected to the original patriarch through only males, suggesting that patrilineal descent determined who was buried in a Neolithic tomb. This also tells us that patrilineal social practices were persistent.

26 of 35 people with genetic data were male. Male burials in other Cotswold tombs outnumber females 1.6 to 1. The remains of some women must have been treated differently.

No adult lineage daughters were present in the tomb, although two infant daughters were, suggesting that adult daughters were out-married, outside of either the community or this specific family lineage. They would have been buried in their husband’s tomb, just as these women were buried here.

The male progenitor reproduced with 4 females, producing 14 adult sons who were buried in the tomb. All four females were buried in the tomb, in two chambers, suggesting that women, at least high-status women were buried with their partners and not in their father’s tomb.

The lineages of two of those women were buried in the same half of the tomb over all generations, suggesting maternal lineages were socially important.

The burials included four men who did not descend from the male progenitors of the clan lineage but DID descend from women who also had children with the progenitors. The authors state that this suggests that the progenitor men adopted the four children of their mates into their lineage, but it also raises the possibility that the progenitor men were not aware that those four men were not their descendants.

Multiple reproductive partners of men were not related to each other, but multiple reproductive partners of women were.

Eight individuals found within the tomb were not closely related to the main lineages. This could mean that they were partners of men who did not reproduce, or who had only adult daughters. It could also mean they were socially important, but not biologically related to either each other nor the tomb’s family members whose DNA was sampled.

Of those who are related, inbreeding had been avoided meaning the parents of individuals were not related to each other based on runs of homozygosity (ROH).

Some of the remains from the north chamber had been gnawed by scavengers, apparently before burial, and three cremations were buried at the entrance including an infant, a child, and an adult. This might answer the question of what happened if someone died while the group was away from the burial site.

Individuals in the north tomb exhibited osteoarthritis typical of other burials in southern England, and signs of nutritional stress in childhood.

The south chamber burials were more co-mingled and dispersed among neighboring compartments.

In the Guardian article, World’s oldest family tree revealed in 5,700-year-old Cotswolds tomb, a genetic pedigree chart was drawn based on the burials, their relationship to each other, and burial locations.

As discussed in this PNAS paper, Megalithic tombs in western and northern Neolithic Europe were linked to a kindred society, other Neolithic tomb burials in Europe were also reflective of a kinship system.

The question remains, where did the Cotswold settlers come from? Who were they descended from and related to? The second paper provides insights to that question.

Who Migrated into Britain, and When?

Patterson et al tell us that their DNA analysis of 793 individuals increased the data from the Middle (1550-1150 BCE) to Late Bronze (1150-750 BCE) and Iron Age (70-BCE-43CE) in Britain by 12-fold, and from Western and Central Europe by 3.5 times.

They also reveal that present-day people from England and Wales carry more ancestry derived from Early European Farmers than people from the Early Bronze Age.

The DNA contributed from Early European Farmers (EEF) increased over time in people in the southern portion of Britain and Wales, which includes the Cotswold region, but did not increase in northern Britain (Scotland,) nor in Kent. Specifically, from 31% in the Early Bronze Age to 34% in the Middle Bronze Age to 35% in the Late Bronze Age to 38% in the Iron Age.

While the EEF DNA increased over time in the Southwest area of Britain, it decreased in other regions. This means that the increase could not be explained by migration from northern continental Europe in the medieval period because those early migrants carried even less Early European Farmer ancestry than the inhabitants of Southwest Britain. Therefore, if those two populations had admixed, the results would be progressively lower EEF in Southwest Britain, not higher.

To fully evaluate this data, the team sequenced earlier samples from both Britain and mainland Europe in addition to the Cotswold burials, targeting 1.2 million SNP locations.

In addition to DNA sequencing, they also utilized radiocarbon dating to confirm the age of the remains.

Results for low-coverage individuals, meaning those with less than 30,000 SNPs scanned at least once, were removed from the data set.

123 individuals were identified as related to each other from 48 families within the third degree. Third-degree relatives share approximately 12.5% of their DNA and would include first cousins, great-grandparents/children, granduncles/aunts, half uncles/aunts/nieces/nephews.

Lactase persistence, the ability to digest the lactose in milk was significantly higher in this population than in either the rest of Britain or Central and Western Europe by a factor of 5 or greater.

The DNA of the Cotswold burial groups and others found from this early timeframe in Southwest Britain and Wales is most similar to ancient burials from France.

A Eupedia megalithic culture page shows a map of various major megalithic sites in both Europe and the British Isles.

Based on charts in Figure 4 of the paper, the location in Europe with the highest percentage of EEF about 4300 years ago (2300 BCE) was the Iberian Peninsula – Spain and Portugal, a location that neighbors France. Lactase persistence began increasing about that time and dramatically rose about 3500 years ago (1500 BCE.)

Y DNA haplogroup R-L21/M529 went from 0% in the Neolithic era (3950-2450 BCE,) or about 5950-4450 years ago) in Britain to 90% in all of Britain in the Early Bronze Era (2450-1550 BCE or 4450-3550 years ago), then dropped slowly to about 70% in the Iron Age in Western England and Wales, then 50% in western Britain and Wales and 20% in Central and Eastern Britain in the Modern Era.

You can read more about this research in this Phys.org article: Geneticists’ new research on ancient Britain contains insights on language, ancestry, kinship, milk, and more about Megalithic burials in France in this Smithsonian Magazine article: Europe’s Megalithic Monuments Originated in France and Spread by Sea Routes, new Study Suggests.

Are You Connected?

The paper authors made the resequenced Y DNA and mitochondrial DNA information available for analysis.

Of course, we all want to know if we are connected with these people, especially if our families have origins in the British Isles.

The R&D team at FamilyTreeDNA downloaded the Y DNA and mitochondrial DNA sequences and linked them to mapped locations. They also correlated samples to Y DNA and mitochondrial DNA haplogroups and linked them to their respective public trees here and here. The Y DNA sometimes contained additional SNP information which allowed a more granular haplogroup to be assigned.

I want to specifically thank Goran Runfeldt, head of R&D, for making this valuable information available and useful for genealogists by downloading, reformatting, and mapping the data, and Michael Sager, phylogeneticist in the FamilyTreeDNA lab, for reanalyzing the Y DNA results and refining them beyond the papers.

Now, let’s get to the best part.

The Map

This map shows the locations of 459 ancient British Isles burials included in the papers, both in the Cotswolds and throughout the rest of Great Britain.

There are significantly more mitochondrial DNA haplogroups represented than Y DNA. Of course, everyone, males and females both have mitochondrial DNA, so everyone can test, but only males carry Y DNA.

The next map shows the distribution of the base mitochondrial haplogroups.

  • H=light green (181 samples)
  • U=rust (70 samples)
  • K=burgundy (68 samples)
  • J=yellow (46 samples)
  • T=dark green (43 samples)
  • V=grey (16 samples)
  • X=dark teal (9 samples)
  • I=orange (6 samples)
  • W=purple (6 samples)
  • N=brown (2 samples)

The most common mitochondrial haplogroup found is H which is unsurprising given that H is the most common haplogroup in Europe as well.

It’s interesting to note that there is no clear haplogroup distribution pattern for either Y DNA or mitochondrial  DNA, with the exception of the North Hazelton burials themselves as outlined in the paper.

There were only three ancient major Y DNA haplogroups discovered.

  • R=green (179 samples)
  • I=gold (50 samples)
  • G=blue (5 samples)

225 total samples were female and had no Y chromosome. A few male Y chromosomes were not recoverable.

Of course, some samples on the maps fall directly beneath other samples, so it’s difficult to discern multiple samples from the same location.

For that, and for more granular haplogroups, we need to refer to the data itself.

How to Use the Data

Each sample is identified by:

  • A sample ID from the papers
  • Sex
  • Location with a google map link.
  • Age calibrated to BCE, before current era, which means roughly how many years before about the year 1 that someone lived. To determine approximately how long ago one of these people lived, add 2000 to the BCE date. For example, 3500 BCE equates to 5500 years ago.
  • Y DNA haplogroup for male samples where recoverable, linked to FamilyTreeDNA’s public Y DNA haplotree.
  • Mitochondrial DNA haplogroup for all but 2 samples where mitochondrial results were not recoverable, linked to FamilyTreeDNA’s public mitochondrial DNA haplotree.

If you have tested your full sequence mitochondrial DNA, you can use the browser search function (ctrl+F) on a PC to search for your haplogroup. For example. Searching for haplogroup H61 produces 5 results. Click on the sample locations to view where they were found. Are they in close proximity to each other? In the same burial?

Four were found at the same location in the Channel Islands, and one in Kent. Where is your ancestor from?

For Y DNA, you can search for your haplogroup, but if you’ve taken the Big Y test and don’t find your specific haplogroup, you might want to use the Y DNA tree to search for successive upstream haplogroups to see where your closest ancient match might be found. Of course, if you’re haplogroup G, it’s pretty easy to just take a look without searching for each individual haplogroup. Just search for “G-“.

For each sample, be sure to click on the haplogroup name itself to view its location on the tree and where else in the world this haplogroup is found. Let’s look at a couple of examples.

Sample: I26628 (Female)
Location: Channel Islands, Alderney, Longis Common
Age: 756-416 calBCE
mtDNA: H61

Mitochondrial haplogroup H61, above, is fairly rare and currently found sparsely in several countries including England, Germany, Hungary, Belarus, Ireland, Netherlands, the UK, and France. The flags indicate the location of FamilyTreeDNA testers’ earliest known ancestor of their mitochondrial, meaning direct matrilineal, line.

Click on the haplogroup link to view the results in the Y or mtDNA trees.

Next, let’s look at a Y DNA sample.

Sample: I16427 (Male)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 4234-3979 calBCE
Y-DNA: I-M423
mtDNA: X2b-T226C

Haplogroup I-M423 itself is found most frequently in Germany, Poland, Ukraine, Scotland and Ireland, but note that it also has 648 downstream branches defined. You may match I-M423 by virtue of belonging to a downstream branch.

Do you match any of these ancient samples, and where were your ancestors from?

Sample: I26630 (Male)
Location: Channel Islands, Alderney, Longis Common
Age: 749-403 calBCE
mtDNA: H61

Sample: I16430 (Female)
Location: Channel Islands, Alderney, Longis Common
Age: 337-52 calBCE
mtDNA: H61

Sample: I16505 (Female)
Location: Channel Islands, Alderney, Longis Common
Age: 174-45 calBCE
mtDNA: H61

Sample: I26629 (Female)
Location: Channel Islands, Alderney, Longis Common
Age: 170 calBCE – 90 calCE
mtDNA: U5a1b1

Sample: I16437 (Female)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 4241-4050 calBCE
mtDNA: K1b1a1

Sample: I16444 (Male)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 4228-3968 calBCE
Y-DNA: I-FT376000
mtDNA: J1c1b1

Sample: I16429 (Male)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 3088-2914 calBCE
mtDNA: K1

Sample: I16425 (Female)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 3083-2912 calBCE
mtDNA: K1a4a1

Sample: I16438 (Male)
Location: Channel Islands, Guernsey, Vale, Le Déhus
Age: 2567-2301 calBCE
Y-DNA: I-L623
mtDNA: J1c8

Sample: I16436 (Male)
Location: Channel Islands, Herm, The Common
Age: 3954-3773 calBCE
Y-DNA: I-CTS7213
mtDNA: HV

Sample: I16435 (Male)
Location: Channel Islands, Herm, The Common
Age: 3646-3527 calBCE
mtDNA: H

Sample: I16597 (Male)
Location: England, Bedfordshire, Broom Quarry
Age: 404-209 calBCE
Y-DNA: R-DF49
mtDNA: H1-C16355T

Sample: I21293 (Female)
Location: England, Bedfordshire, Broom Quarry
Age: 425-200 BCE
mtDNA: J1c1b

Sample: I11151 (Male)
Location: England, Bedfordshire, Broom Quarry
Age: 379-197 calBCE
Y-DNA: R-FT44983
mtDNA: K1a-T195C!

Sample: I11150 (Male)
Location: England, Bedfordshire, Broom Quarry
Age: 381-197 calBCE
Y-DNA: R-FT335377
mtDNA: H15a1

Sample: I19047 (Male)
Location: England, Cambridgeshire, Babraham Research Campus (ARC05), ARES site
Age: 1-50 CE
Y-DNA: R-M269
mtDNA: H2a

Sample: I19045 (Male)
Location: England, Cambridgeshire, Marshall’s Jaguar Land Rover New Showroom (JLU15)
Age: 388-206 calBCE
Y-DNA: G-S23438
mtDNA: U4a2

Sample: I19046 (Male)
Location: England, Cambridgeshire, Marshall’s Jaguar Land Rover New Showroom (JLU15)
Age: 383-197 calBCE
Y-DNA: R-P312
mtDNA: H1t

Sample: I19044 (Male)
Location: England, Cambridgeshire, Marshall’s Jaguar Land Rover New Showroom (JLU15)
Age: 381-199 calBCE
Y-DNA: R-FT50512
mtDNA: K1a-T195C!

Sample: I11152 (Male)
Location: England, Cambridgeshire, Over
Age: 355-59 calBCE
Y-DNA: G-Z16775
mtDNA: U3a1

Sample: I11149 (Male)
Location: England, Cambridgeshire, Teversham (Marshall’s) Evaluation
Age: 733-397 calBCE
Y-DNA: R-Z156
mtDNA: V

Sample: I11154 (Female)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 743-404 calBCE
mtDNA: H5a1

Sample: I13729 (Female)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 512-236 calBCE
mtDNA: H1ag1

Sample: I11153 (Male)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 405-209 calBCE
Y-DNA: R-FGC33066
mtDNA: H3b

Sample: I13727 (Female)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 389-208 calBCE
mtDNA: T1a1

Sample: I13728 (Male)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 381-179 calBCE
Y-DNA: R-P312
mtDNA: T2a1a

Sample: I13687 (Female)
Location: England, Cambridgeshire, Trumpington Meadows
Age: 368-173 calBCE
mtDNA: W1c

Sample: I11156 (Male)
Location: England, Cambridgeshire, Whittlesey, Bradley Fen
Age: 382-200 calBCE
Y-DNA: R-CTS8704
mtDNA: J1c3

Sample: I11997 (Male)
Location: England, Cambridgeshire, Whittlesey, Bradley Fen
Age: 377-197 calBCE
Y-DNA: R-FGC36434
mtDNA: X2b-T226C

Sample: I16620 (Female)
Location: England, Co. Durham, Hartlepool, Catcote
Age: 340 BCE – 6 CE
mtDNA: H1bs

Sample: I12790 (Female)
Location: England, Cornwall, Newquay, Tregunnel
Age: 400-100 BCE
mtDNA: H2a1

Sample: I12793 (Male)
Location: England, Cornwall, Newquay, Tregunnel
Age: 400-100 BCE
Y-DNA: R-L21
mtDNA: H2a1

Sample: I12792 (Female)
Location: England, Cornwall, Newquay, Tregunnel
Age: 400-100 BCE
mtDNA: H2a1

Sample: I16387 (Male)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
Y-DNA: R-P312
mtDNA: N/A

Sample: I16456 (Female)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
mtDNA: T1a1’3

Sample: I16455 (Male)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
Y-DNA: R-Z290
mtDNA: T1

Sample: I16386 (Female)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
mtDNA: T1a1

Sample: I16458 (Male)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
Y-DNA: R-L21
mtDNA: T2c1d-T152C!

Sample: I16457 (Female)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
mtDNA: T1a1

Sample: I16450 (Male)
Location: England, Cornwall, Newquay, Trethellan Farm
Age: 300 BCE – 100 CE
Y-DNA: R-FT32396
mtDNA: T1a1

Sample: I16424 (Female)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 2285-2036 calBCE
mtDNA: R1b

Sample: I6769 (Male)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 754-416 calBCE
Y-DNA: R-BY168376
mtDNA: H6a1b2

Sample: I16380 (Male)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
Y-DNA: R-ZP298
mtDNA: U4b1a1a1

Sample: I16388 (Female)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
mtDNA: J1c1

Sample: I16440 (Male)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
Y-DNA: R-P312
mtDNA: T2c1d-T152C!

Sample: I16441 (Female)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
mtDNA: J1c2e

Sample: I16442 (Female)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
mtDNA: U4b1a1a1

Sample: I16439 (Female)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
mtDNA: T2c1d-T152C!

Sample: I12772 (Male)
Location: England, Cornwall, Padstow, St. Merryn, Harlyn Bay
Age: 800 BCE – 43 CE
Y-DNA: G-CTS2230
mtDNA: T2c1d-T152C!

Sample: I16453 (Male)
Location: England, Cornwall, St. Mawes, Tregear Vean
Age: 800-1 BCE
Y-DNA: I-M253
mtDNA: U5a2a1

Sample: I16454 (Male)
Location: England, Cornwall, St. Merryn, Constantine Island
Age: 1381-1056 calBCE
Y-DNA: R-Z290
mtDNA: U5b2b2

Sample: I20997 (Male)
Location: England, Cumbria, Ulverston, Birkrigg Common
Age: 2450-1800 BCE
Y-DNA: R-A286
mtDNA: X2b4a

Sample: I12776 (Female)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 1918-1750 calBCE
mtDNA: U4a2c

Sample: I12774 (Male)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 758-416 calBCE
Y-DNA: R-P312
mtDNA: H10b

Sample: I12771 (Male)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 513-210 calBCE
Y-DNA: R-FT5780
mtDNA: U5b2a2a

Sample: I12778 (Male)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 381-203 calBCE
Y-DNA: R-DF5
mtDNA: H4a1a2

Sample: I3014 (Female)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 377-177 calBCE
mtDNA: H

Sample: I12775 (Male)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 361-177 calBCE
Y-DNA: R-BY9405
mtDNA: U5a1b1e

Sample: I12770 (Female)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 390-171 calBCE
mtDNA: H3b1b1

Sample: I12779 (Female)
Location: England, Derbyshire, Brassington, Carsington Pasture Cave
Age: 370-197 calBCE
mtDNA: T2b4c

Sample: I20620 (Female)
Location: England, Derbyshire, Fin Cop
Age: 382-204 calBCE
mtDNA: T2a1b1

Sample: I20627 (Female)
Location: England, Derbyshire, Fin Cop
Age: 376-203 calBCE
mtDNA: V2b

Sample: I20623 (Female)
Location: England, Derbyshire, Fin Cop
Age: 400-150 BCE
mtDNA: V2b

Sample: I20624 (Male)
Location: England, Derbyshire, Fin Cop
Age: 356-108 calBCE
Y-DNA: R-M269
mtDNA: U2e1a1

Sample: I20622 (Male)
Location: England, Derbyshire, Fin Cop
Age: 357-60 calBCE
Y-DNA: I-Y3713
mtDNA: T2c1d1

Sample: I20634 (Male)
Location: England, Derbyshire, Fin Cop
Age: 400-50 BCE
Y-DNA: R-M269
mtDNA: K2b1a1a

Sample: I20630 (Male)
Location: England, Derbyshire, Fin Cop
Age: 400-50 BCE
Y-DNA: R-L21
mtDNA: H1au1b

Sample: I20632 (Male)
Location: England, Derbyshire, Fin Cop
Age: 400-50 BCE
Y-DNA: R-P310
mtDNA: V2b

Sample: I20621 (Female)
Location: England, Derbyshire, Fin Cop
Age: 400-50 BCE
mtDNA: T2c1d1

Sample: I20631 (Female)
Location: England, Derbyshire, Fin Cop
Age: 400-50 BCE
mtDNA: V2b

Sample: I20628 (Male)
Location: England, Derbyshire, Fin Cop
Age: 351-52 calBCE
Y-DNA: R-DF13
mtDNA: I2a

Sample: I20626 (Male)
Location: England, Derbyshire, Fin Cop
Age: 346-53 calBCE
Y-DNA: I-P222
mtDNA: H7b

Sample: I20625 (Male)
Location: England, Derbyshire, Fin Cop
Age: 343-49 calBCE
Y-DNA: R-P310
mtDNA: T1a1

Sample: I27382 (Male)
Location: England, Dorset, Long Bredy, Bottle Knap
Age: 774-540 calBCE
Y-DNA: R-BY116228
mtDNA: H1

Sample: I27383 (Female)
Location: England, Dorset, Long Bredy, Bottle Knap
Age: 750-411 calBCE
mtDNA: U4c1

Sample: I27381 (Female)
Location: England, Dorset, Long Bredy, Bottle Knap
Age: 748-406 calBCE
mtDNA: U4c1

Sample: I20615 (Female)
Location: England, Dorset, Worth Matravers, Football Field
Age: 100 BCE – 50 CE
mtDNA: H1i

Sample: I22065 (Male)
Location: England, East Riding of Yorkshire, Burstwick
Age: 351-55 calBCE
Y-DNA: R-P312
mtDNA: H

Sample: I22052 (Female)
Location: England, East Riding of Yorkshire, East Coast Pipeline (field 16)
Age: 344-52 calBCE
mtDNA: U2e2a1a

Sample: I22060 (Male)
Location: England, East Riding of Yorkshire, East Coast Pipeline (field 9)
Age: 343-1 calBCE
Y-DNA: R-BY154824
mtDNA: H4a1a3a

Sample: I0527 (Female)
Location: England, East Riding of Yorkshire, East Riding, North Ferriby, Melton Quarry
Age: 400-100 BCE
mtDNA: U2e1

Sample: I0525 (Female)
Location: England, East Riding of Yorkshire, Melton
Age: 100 BCE – 50 CE
mtDNA: U2e1e

Sample: I7629 (Male)
Location: England, East Riding of Yorkshire, North Ferriby, Melton Quarry
Age: 1201-933 calBCE
Y-DNA: R-DF13
mtDNA: H17

Sample: I5503 (Female)
Location: England, East Riding of Yorkshire, Nunburnholme Wold
Age: 334-42 calBCE
mtDNA: U5b1c2

Sample: I5502 (Male)
Location: England, East Riding of Yorkshire, Nunburnholme Wold
Age: 196-4 calBCE
Y-DNA: R-FT96564
mtDNA: H3

Sample: I11033 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 717-395 calBCE
mtDNA: H2a3b

Sample: I14100 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 409-229 calBCE
Y-DNA: R-DF13
mtDNA: J1c9

Sample: I12412 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 387-205 calBCE
mtDNA: K1c1a

Sample: I5507 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 387-206 calBCE
mtDNA: H2a3b

Sample: I5506 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 358-111 calBCE
mtDNA: K1c1a

Sample: I5504 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: T1a1

Sample: I5505 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-L21
mtDNA: V16

Sample: I14103 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H53

Sample: I5510 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: K1c1a

Sample: I13755 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I5509 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-PH4760
mtDNA: K1c1a

Sample: I13758 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-L2
mtDNA: H2a3b

Sample: I14107 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-CTS6919
mtDNA: K1c1a

Sample: I13760 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-DF13
mtDNA: H2a3b

Sample: I13751 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I13754 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-P312
mtDNA: U5b2b3

Sample: I13757 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: T2c1d1a

Sample: I13756 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: K1c1a

Sample: I13753 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-Z251
mtDNA: H2a3b

Sample: I14099 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I14101 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I14105 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-P312
mtDNA: H2a3b

Sample: I14102 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-FT84170
mtDNA: K1c1a

Sample: I14108 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: V2a

Sample: I14104 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-DF13
mtDNA: H

Sample: I13759 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-BY3865
mtDNA: H2a3b

Sample: I11034 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I12411 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I12415 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: J1c9

Sample: I12413 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-BY50764
mtDNA: H2a3b

Sample: I12414 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
mtDNA: H2a3b

Sample: I5508 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-BY11863
mtDNA: J1c9

Sample: I5511 (Male)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 400-50 BCE
Y-DNA: R-DF63
mtDNA: J1c9

Sample: I13752 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 346-53 calBCE
mtDNA: J1c9

Sample: I14106 (Female)
Location: England, East Riding of Yorkshire, Pocklington (Burnby Lane)
Age: 176 calBCE – 6 calCE
mtDNA: K1c1a

Sample: I18606 (Male)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 10)
Age: 1919-1742 calBCE
Y-DNA: R-DF13
mtDNA: K1b1a1

Sample: I19220 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 10)
Age: 1894-1695 calBCE
mtDNA: H3g1

Sample: I14326 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 13)
Age: 3074-2892 calBCE
mtDNA: H1c

Sample: I22056 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 16)
Age: 391-201 calBCE
mtDNA: H4a1a3a

Sample: I22055 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 16)
Age: 391-201 calBCE
mtDNA: K1b1a1c1

Sample: I14327 (Male)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 16)
Age: 340-47 calBCE
Y-DNA: R-BY41416
mtDNA: H5

Sample: I22064 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 16)
Age: 105 calBCE – 64 calCE
mtDNA: H4a1a3a

Sample: I22057 (Female)
Location: England, East Riding of Yorkshire, Thornholme, East Coast Pipeline (field 16)
Age: 104 calBCE – 65 calCE
mtDNA: H2a1k

Sample: I22062 (Male)
Location: England, East Riding of Yorkshire, Thornholme, Town Pasture
Age: 50 calBCE – 116 calCE
Y-DNA: R-BY23382
mtDNA: K1a-T195C!

Sample: I12931 (Male)
Location: England, Gloucestershire, Bishop’s Cleeve, Cleevelands
Age: 50-200 CE
Y-DNA: I-L160
mtDNA: H6a2

Sample: I12927 (Male)
Location: England, Gloucestershire, Bishop’s Cleeve, Cleevelands
Age: 50-200 CE
Y-DNA: R-PR1289
mtDNA: U5b3b1

Sample: I12932 (Female)
Location: England, Gloucestershire, Bishop’s Cleeve, Cleevelands
Age: 50-200 CE
mtDNA: H1bs

Sample: I12791 (Male)
Location: England, Gloucestershire, Bourton-on-the-water, Greystones Farm
Age: 200-1 BCE
Y-DNA: I-BY17900
mtDNA: H1e1a

Sample: I12785 (Male)
Location: England, Gloucestershire, Bourton-on-the-water, Greystones Farm
Age: 200-1 BCE
Y-DNA: R-DF21
mtDNA: J1c1b2

Sample: I12926 (Male)
Location: England, Gloucestershire, Fairford, Saxon Way
Age: 400-100 BCE
Y-DNA: R-L21
mtDNA: H2a2a2

Sample: I21392 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: 3710–3630 calBCE
Y-DNA: I-M284
mtDNA: J2b1a

Sample: I12439 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
Y-DNA: I-Y3709
mtDNA: K1b1a

Sample: I30304 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
Y-DNA: I-L1195
mtDNA: K1b1a

Sample: I13888 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
mtDNA: K1b1a

Sample: I21388 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
Y-DNA: I-Y3709
mtDNA: U8b1b

Sample: I13892 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: 3910–3630 calBCE
Y-DNA: I-Y3709
mtDNA: T2e1

Sample: I30334 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
mtDNA: K1a3a1

Sample: I21390 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: 3950–3630 calBCE
mtDNA: U8b1b

Sample: I30300 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
Y-DNA: I-Y3709
mtDNA: N1b1b

Sample: I13899 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North chamber
Age: N/A
Y-DNA: I-Y3712
mtDNA: U3a1

Sample: I13893 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North entrance
Age: 3650–3380 calBCE
Y-DNA: I-Y3709
mtDNA: K1a4

Sample: I13897 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North entrance
Age: 3500–3340 calBCE
Y-DNA: I-Y3712
mtDNA: V

Sample: I13898 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North entrance
Age: 3700–3530 calBCE
Y-DNA: I-Y3709
mtDNA: K1a3a1

Sample: I12437 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, North entrance
Age: 3790–3510 calBCE
Y-DNA: I-Y3709
mtDNA: K1a3a1

Sample: I21389 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: 3720-3520 calBCE
Y-DNA: I-Y3709
mtDNA: H1

Sample: I30311 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
Y-DNA: I-Y3709
mtDNA: U5b1-T16189C!-T16192C!

Sample: I21387 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
mtDNA: K1d

Sample: I12440 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
Y-DNA: I-Y3709
mtDNA: K2b1

Sample: I30302 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
mtDNA: K2b1

Sample: I13889 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
mtDNA: K1b1a1d

Sample: I13896 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber
Age: N/A
mtDNA: J1c1b1

Sample: I21395 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber, south entrance
Age: N/A
Y-DNA: I-Y3709
mtDNA: J1c1b1

Sample: I13891 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber, south passage
Age: N/A
Y-DNA: I-Y3709
mtDNA: U5b1-T16189C!-T16192C!

Sample: I12438 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South chamber, south passage
Age: N/A
Y-DNA: I-L1195
mtDNA: W5

Sample: I30293 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance
Age: N/A
mtDNA: U5b1-T16189C!

Sample: I30332 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance
Age: N/A
Y-DNA: I-CTS616
mtDNA: N/A

Sample: I21385 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance
Age: N/A
Y-DNA: I-FT344600
mtDNA: K1d

Sample: I13895 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance
Age: N/A
Y-DNA: I-Y3709
mtDNA: U8b1b

Sample: I30301 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance
Age: N/A
Y-DNA: I-Y3712
mtDNA: U5a2d

Sample: I20818 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South entrance, south passage
Age: 3970–3640 calBCE
Y-DNA: I-Y3712
mtDNA: J1c1

Sample: I13890 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South passage
Age: N/A
Y-DNA: I-L1193
mtDNA: T2e1

Sample: I21393 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South passage
Age: N/A
Y-DNA: I-L1195
mtDNA: K1b1a

Sample: I20821 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South passage
Age: N/A
Y-DNA: I-Y3709
mtDNA: H5

Sample: I30299 (Male)
Location: England, Gloucestershire, Hazleton North Long Cairn, South passage
Age: N/A
Y-DNA: I-Y3709
mtDNA: K2b1

Sample: I21391 (Female)
Location: England, Gloucestershire, Hazleton North Long Cairn, Uncertain
Age: N/A
mtDNA: K1b1a1

Sample: I12786 (Male)
Location: England, Gloucestershire, Lechlade-on-Thames, Lechlade Memorial Hall/Skate Park
Age: 2289-2052 calBCE
Y-DNA: R-DF13
mtDNA: J1c2

Sample: I12935 (Male)
Location: England, Gloucestershire, Lechlade-on-Thames, Lechlade Memorial Hall/Skate Park
Age: 2200-1900 BCE
Y-DNA: R-DF21
mtDNA: H1ah2

Sample: I12783 (Male)
Location: England, Gloucestershire, Lechlade-on-Thames, Lechlade Memorial Hall/Skate Park
Age: 783-541 calBCE
Y-DNA: R-DF21
mtDNA: J1c5

Sample: I12787 (Female)
Location: England, Gloucestershire, Lechlade-on-Thames, Lechlade Memorial Hall/Skate Park
Age: 539-387 calBCE
mtDNA: H2a2a1

Sample: I13717 (Female)
Location: England, Hampshire, Barton-Stacey Pipeline
Age: 398-208 calBCE
mtDNA: U5a1a1

Sample: I16611 (Male)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 401-208 calBCE
Y-DNA: R-Z16539
mtDNA: H1c

Sample: I17261 (Male)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 372-175 calBCE
Y-DNA: R-DF63
mtDNA: R0a

Sample: I20987 (Male)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
Y-DNA: R-DF63
mtDNA: U5b2b3

Sample: I20985 (Female)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
mtDNA: U4a3a

Sample: I17262 (Female)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 357-57 calBCE
mtDNA: T2b

Sample: I20983 (Female)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
mtDNA: H3b-G16129A!

Sample: I20986 (Female)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
mtDNA: HV0-T195C!

Sample: I20982 (Male)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
Y-DNA: R-L20
mtDNA: J1c3

Sample: I20984 (Female)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 450-1 BCE
mtDNA: H1j6

Sample: I16609 (Male)
Location: England, Hampshire, Middle Wallop, Suddern Farm
Age: 341-46 calBCE
mtDNA: J1c2e

Sample: I16612 (Female)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 658-397 calBCE
mtDNA: H3

Sample: I17267 (Female)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 450-100 BCE
mtDNA: V

Sample: I20988 (Male)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 450-100 BCE
Y-DNA: I-Y3713
mtDNA: T2b19

Sample: I17264 (Male)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 450-100 BCE
Y-DNA: R-BY4297
mtDNA: U2e1f1

Sample: I20990 (Female)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 362-171 calBCE
mtDNA: J1c1b1a

Sample: I17266 (Female)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 355-60 calBCE
mtDNA: U5b1b1-T16192C!

Sample: I20989 (Male)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 354-59 calBCE
Y-DNA: R-P312
mtDNA: K1c1

Sample: I16613 (Male)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 351-54 calBCE
mtDNA: J1b1a1

Sample: I17263 (Female)
Location: England, Hampshire, Nether Wallop, Danebury
Age: 346-52 calBCE
mtDNA: J1c1c

Sample: I17260 (Male)
Location: England, Hampshire, Stockbridge, New Buildings
Age: 800-400 BCE
Y-DNA: R-S1051
mtDNA: U5a1a2a

Sample: I17259 (Male)
Location: England, Hampshire, Stockbridge, New Buildings
Age: 725-400 calBCE
Y-DNA: I-S16030
mtDNA: H5a1

Sample: I17258 (Female)
Location: England, Hampshire, Stockbridge, New Buildings
Age: 542-396 calBCE
mtDNA: K1a2

Sample: I19042 (Female)
Location: England, Hampshire, Winnall Down
Age: 715-48 calBCE
mtDNA: T2b33

Sample: I19043 (Female)
Location: England, Hampshire, Winnall Down
Age: 400-100 BCE
mtDNA: J1c1

Sample: I19037 (Female)
Location: England, Hampshire, Winnall Down
Age: 400-100 BCE
mtDNA: J1b1a1b

Sample: I19040 (Female)
Location: England, Hampshire, Winnall Down
Age: 400-100 BCE
mtDNA: H1m

Sample: I14742 (Male)
Location: England, Kent, Cliffs End Farm
Age: 1011-860 calBCE
Y-DNA: R-P312
mtDNA: H1-T16189C!

Sample: I14377 (Female)
Location: England, Kent, Cliffs End Farm
Age: 1014-836 calBCE
mtDNA: U5b1b1d

Sample: I14864 (Female)
Location: England, Kent, Cliffs End Farm
Age: 983-816 calBCE
mtDNA: T2b

Sample: I14862 (Female)
Location: England, Kent, Cliffs End Farm
Age: 982-812 calBCE
mtDNA: H1

Sample: I14865 (Female)
Location: England, Kent, Cliffs End Farm
Age: 967-811 calBCE
mtDNA: H

Sample: I14861 (Male)
Location: England, Kent, Cliffs End Farm
Age: 912-808 calBCE
Y-DNA: R-FGC23071
mtDNA: V

Sample: I14358 (Male)
Location: England, Kent, Cliffs End Farm
Age: 912-807 calBCE
Y-DNA: R-L21
mtDNA: H3

Sample: I14379 (Female)
Location: England, Kent, Cliffs End Farm
Age: 903-807 calBCE
mtDNA: T2c1d-T152C!

Sample: I14745 (Female)
Location: England, Kent, Cliffs End Farm
Age: 900-798 calBCE
mtDNA: X2b

Sample: I14743 (Male)
Location: England, Kent, Cliffs End Farm
Age: 779-524 calBCE
Y-DNA: R-L151
mtDNA: I4a

Sample: I14381 (Female)
Location: England, Kent, Cliffs End Farm
Age: 727-400 calBCE
mtDNA: U5b2b1a1

Sample: I14857 (Female)
Location: England, Kent, Cliffs End Farm
Age: 719-384 calBCE
mtDNA: H3an

Sample: I14747 (Female)
Location: England, Kent, Cliffs End Farm
Age: 514-391 calBCE
mtDNA: H3

Sample: I14378 (Female)
Location: England, Kent, Cliffs End Farm
Age: 400-208 calBCE
mtDNA: I2

Sample: I14858 (Female)
Location: England, Kent, Cliffs End Farm
Age: 396-207 calBCE
mtDNA: J1c1

Sample: I14380 (Male)
Location: England, Kent, Cliffs End Farm
Age: 387-203 calBCE
Y-DNA: R-FTB53005
mtDNA: T2e1

Sample: I14860 (Female)
Location: England, Kent, Cliffs End Farm
Age: 386-198 calBCE
mtDNA: X2b-T226C

Sample: I14859 (Male)
Location: England, Kent, Cliffs End Farm
Age: 377-203 calBCE
Y-DNA: R-P312
mtDNA: H7d3

Sample: I14866 (Male)
Location: England, Kent, Cliffs End Farm
Age: 372-197 calBCE
Y-DNA: I-BY152642
mtDNA: H1at1

Sample: I14863 (Female)
Location: England, Kent, Cliffs End Farm
Age: 360-201 calBCE
mtDNA: U5b1b1-T16192C!

Sample: I13714 (Male)
Location: England, Kent, East Kent Access Road
Age: 1533-1417 calBCE
Y-DNA: R-CTS6919
mtDNA: H1c8

Sample: I19915 (Female)
Location: England, Kent, East Kent Access Road
Age: 1519-1422 calBCE
mtDNA: K1c1

Sample: I19913 (Female)
Location: England, Kent, East Kent Access Road
Age: 1408-1226 calBCE
mtDNA: J1c2e

Sample: I13710 (Male)
Location: England, Kent, East Kent Access Road
Age: 1411-1203 calBCE
Y-DNA: R-DF63
mtDNA: I4a

Sample: I13711 (Male)
Location: England, Kent, East Kent Access Road
Age: 1048-920 calBCE
Y-DNA: R-BY28644
mtDNA: H61

Sample: I13712 (Male)
Location: England, Kent, East Kent Access Road
Age: 1011-916 calBCE
Y-DNA: R-DF13
mtDNA: U5b2b3a

Sample: I13713 (Male)
Location: England, Kent, East Kent Access Road
Age: 1055-837 calBCE
Y-DNA: R-L21
mtDNA: H1c

Sample: I19872 (Female)
Location: England, Kent, East Kent Access Road
Age: 403-209 calBCE
mtDNA: H13a1a1

Sample: I13732 (Male)
Location: England, Kent, East Kent Access Road
Age: 401-208 calBCE
Y-DNA: R-A7835
mtDNA: U5b2c1

Sample: I19873 (Male)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
Y-DNA: R-BY3616
mtDNA: U5b2b

Sample: I13615 (Male)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
Y-DNA: R-DF13
mtDNA: H1c

Sample: I19907 (Female)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
mtDNA: U2e1a1

Sample: I19910 (Female)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
mtDNA: U4a2

Sample: I19911 (Male)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
Y-DNA: R-DF13
mtDNA: K1a4a1

Sample: I19874 (Female)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
mtDNA: H1ax

Sample: I19908 (Female)
Location: England, Kent, East Kent Access Road
Age: 400-200 BCE
mtDNA: K2b1a

Sample: I13731 (Male)
Location: England, Kent, East Kent Access Road
Age: 393-206 calBCE
Y-DNA: R-DF13
mtDNA: U5a1a1g

Sample: I13730 (Male)
Location: England, Kent, East Kent Access Road
Age: 390-202 calBCE
Y-DNA: R-S5668
mtDNA: H1bb

Sample: I19914 (Female)
Location: England, Kent, East Kent Access Road
Age: 387-200 calBCE
mtDNA: H3g1

Sample: I19909 (Male)
Location: England, Kent, East Kent Access Road
Age: 381-197 calBCE
Y-DNA: R-BY9003
mtDNA: T1a1-C152T!!

Sample: I19912 (Female)
Location: England, Kent, East Kent Access Road
Age: 368-173 calBCE
mtDNA: H1bs

Sample: I13616 (Female)
Location: England, Kent, East Kent Access Road
Age: 356-49 calBCE
mtDNA: H1b1-T16362C

Sample: I19870 (Female)
Location: England, Kent, East Kent Access Road
Age: 200-1 BCE
mtDNA: T1a1

Sample: I19869 (Female)
Location: England, Kent, East Kent Access Road
Age: 175 calBCE – 8 calCE
mtDNA: T1a1

Sample: I1774 (Male)
Location: England, Kent, Isle of Sheppey, Neats Court
Age: 1879-1627 calBCE
Y-DNA: R-M269
mtDNA: U4b1a2

Sample: I13716 (Female)
Location: England, Kent, Margetts Pit
Age: 1391-1129 calBCE
mtDNA: H11a

Sample: I13617 (Female)
Location: England, Kent, Margetts Pit
Age: 1214-1052 calBCE
mtDNA: H

Sample: I18599 (Female)
Location: England, Kent, Sittingbourne, Highsted
Age: 43 calBCE – 110 calCE
mtDNA: H

Sample: I3083 (Male)
Location: England, London, River Thames, Putney Foreshore
Age: 387-201 calBCE
Y-DNA: R-P310
mtDNA: R

Sample: I16463 (Male)
Location: England, North Yorkshire, Cockerham, Elbolton Cave
Age: 4000-3500 BCE
Y-DNA: I-L1195
mtDNA: H4a1a2

Sample: I16403 (Male)
Location: England, North Yorkshire, Cockerham, Elbolton Cave
Age: 1600-1350 BCE
Y-DNA: R-DF13
mtDNA: K2a

Sample: I16394 (Male)
Location: England, North Yorkshire, Grassington, 3 Barrow Sites
Age: 2400-1600 BCE
Y-DNA: R-P297
mtDNA: K1c1

Sample: I16395 (Female)
Location: England, North Yorkshire, Grassington, 3 Barrow Sites
Age: 2400-1600 BCE
mtDNA: U5b1

Sample: I16396 (Female)
Location: England, North Yorkshire, Grassington, 3 Barrow Sites
Age: 2400-1600 BCE
mtDNA: K1a4a1

Sample: I16400 (Male)
Location: England, North Yorkshire, Grassington, 3 Barrow Sites
Age: 2400-1500 BCE
Y-DNA: R-Z290
mtDNA: U3a1

Sample: I3035 (Male)
Location: England, North Yorkshire, Ingleborough Hill, Fox Holes Cave
Age: 4000-3500 BCE
Y-DNA: R-A7208
mtDNA: H5a1

Sample: I12936 (Female)
Location: England, North Yorkshire, Raven Scar Cave
Age: 1090-900 BCE
mtDNA: J1c5f

Sample: I16469 (Male)
Location: England, North Yorkshire, Raven Scar Cave
Age: 1090-900 BCE
Y-DNA: R-P312
mtDNA: H3-T152C!

Sample: I16467 (Male)
Location: England, North Yorkshire, Raven Scar Cave
Age: 1090-900 BCE
Y-DNA: R-M269
mtDNA: U5a1g1

Sample: I16459 (Unknown sex)
Location: England, North Yorkshire, Raven Scar Cave
Age: 1090-900 BCE
mtDNA: H

Sample: I19587 (Male)
Location: England, North Yorkshire, Scorton Quarry
Age: 195 calBCE – 7 calCE
Y-DNA: G-L140
mtDNA: K2a

Sample: I14097 (Male)
Location: England, North Yorkshire, Scorton Quarry
Age: 162 calBCE – 26 calCE
Y-DNA: R-P310
mtDNA: H66a1

Sample: I14096 (Male)
Location: England, North Yorkshire, Scorton Quarry
Age: 101 calBCE – 59 calCE
Y-DNA: R-FTA11009
mtDNA: H4a1a2a

Sample: I20583 (Male)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 387-201 calBCE
Y-DNA: R-BY175423
mtDNA: K1a4a1

Sample: I20582 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 368-165 calBCE
mtDNA: H10

Sample: I21272 (Male)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
Y-DNA: R-S5488
mtDNA: V

Sample: I21276 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
mtDNA: K1a4a1

Sample: I21277 (Male)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
Y-DNA: R-DF13
mtDNA: K1a4a1

Sample: I21274 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
mtDNA: K1a4a1

Sample: I21275 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
mtDNA: K1a4a1

Sample: I21271 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 400-100 BCE
mtDNA: W1c

Sample: I20584 (Female)
Location: England, Oxfordshire, Stanton Harcourt, Gravelly Guy
Age: 355-54 calBCE
mtDNA: K1a4a1

Sample: I14808 (Female)
Location: England, Oxfordshire, Thame
Age: 401-209 calBCE
mtDNA: H1

Sample: I14802 (Female)
Location: England, Oxfordshire, Thame
Age: 393-206 calBCE
mtDNA: X2d

Sample: I14807 (Male)
Location: England, Oxfordshire, Thame
Age: 391-204 calBCE
Y-DNA: R-DF49
mtDNA: T1a1

Sample: I14804 (Female)
Location: England, Oxfordshire, Thame
Age: 387-201 calBCE
mtDNA: H1o

Sample: I14806 (Female)
Location: England, Oxfordshire, Thame
Age: 386-198 calBCE
mtDNA: H1bb

Sample: I14800 (Male)
Location: England, Oxfordshire, Thame
Age: 382-197 calBCE
Y-DNA: R-Z253
mtDNA: J2b1

Sample: I14803 (Male)
Location: England, Oxfordshire, Thame
Age: 370-175 calBCE
Y-DNA: R-P312
mtDNA: H2a1

Sample: I14801 (Female)
Location: England, Oxfordshire, Thame
Age: 362-163 calBCE
mtDNA: X2b-T226C

Sample: I14809 (Male)
Location: England, Oxfordshire, Thame
Age: 358-108 calBCE
Y-DNA: R-P312
mtDNA: V7

Sample: I2446 (Female)
Location: England, Oxfordshire, Yarnton
Age: 2454-2139 calBCE
mtDNA: K1b1a1

Sample: I2448 (Male)
Location: England, Oxfordshire, Yarnton
Age: 1500-1000 BCE
Y-DNA: R-DF63
mtDNA: U8a2

Sample: I20585 (Female)
Location: England, Oxfordshire, Yarnton
Age: 800-400 BCE
mtDNA: K1c1

Sample: I21180 (Male)
Location: England, Oxfordshire, Yarnton
Age: 396-209 calBCE
Y-DNA: R-DF13
mtDNA: H7a1

Sample: I19209 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
mtDNA: H

Sample: I19211 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
Y-DNA: R-L21
mtDNA: H1

Sample: I20589 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
Y-DNA: R-Z52
mtDNA: V

Sample: I20586 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
Y-DNA: R-L21
mtDNA: J2b1a

Sample: I21178 (Female)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
mtDNA: T2b3-C151T

Sample: I21182 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
Y-DNA: R-BY15941
mtDNA: J1c2

Sample: I21181 (Male)
Location: England, Oxfordshire, Yarnton
Age: 400-200 BCE
Y-DNA: R-DF13
mtDNA: H3

Sample: I20587 (Male)
Location: England, Oxfordshire, Yarnton
Age: 389-208 calBCE
Y-DNA: R-DF63
mtDNA: K1a2a

Sample: I19207 (Male)
Location: England, Oxfordshire, Yarnton
Age: 382-205 calBCE
Y-DNA: R-M269
mtDNA: H

Sample: I21179 (Female)
Location: England, Oxfordshire, Yarnton
Age: 381-201 calBCE
mtDNA: T2b

Sample: I20588 (Male)
Location: England, Oxfordshire, Yarnton
Age: 366-197 calBCE
Y-DNA: G-BY27899
mtDNA: V

Sample: I19210 (Female)
Location: England, Oxfordshire, Yarnton
Age: 355-118 calBCE
mtDNA: H1cg

Sample: I3019 (Male)
Location: England, Somerset, Cheddar, Totty Pot
Age: 4000-2400 BCE
Y-DNA: R-P310
mtDNA: H4a1a-T195C!

Sample: I16591 (Male)
Location: England, Somerset, Christon, Dibbles Farm
Age: 408-232 calBCE
Y-DNA: R-Z290
mtDNA: H13a1a1

Sample: I11148 (Female)
Location: England, Somerset, Christon, Dibbles Farm
Age: 407-211 calBCE
mtDNA: U6d1

Sample: I13685 (Female)
Location: England, Somerset, Christon, Dibbles Farm
Age: 400-208 calBCE
mtDNA: U5a1b1e

Sample: I11147 (Female)
Location: England, Somerset, Christon, Dibbles Farm
Age: 392-204 calBCE
mtDNA: U5a1b1e

Sample: I16592 (Male)
Location: England, Somerset, Christon, Dibbles Farm
Age: 387-199 calBCE
Y-DNA: R-FGC19329
mtDNA: U5a1b1e

Sample: I17014 (Male)
Location: England, Somerset, Christon, Dibbles Farm
Age: 381-179 calBCE
Y-DNA: R-DF63
mtDNA: U5b1b1d

Sample: I17015 (Female)
Location: England, Somerset, Christon, Dibbles Farm
Age: 380-197 calBCE
mtDNA: H2a2a1

Sample: I17016 (Male)
Location: England, Somerset, Christon, Dibbles Farm
Age: 377-178 calBCE
Y-DNA: R-BY3231
mtDNA: U2e1a1

Sample: I17017 (Female)
Location: England, Somerset, Christon, Dibbles Farm
Age: 196 calBCE – 5 calCE
mtDNA: U5b1-T16189C!

Sample: I19653 (Male)
Location: England, Somerset, Ham Hill
Age: 400-200 BCE
Y-DNA: R-L151
mtDNA: H1n6

Sample: I19856 (Female)
Location: England, Somerset, Ham Hill
Age: 400-200 BCE
mtDNA: R2’JT

Sample: I19654 (Female)
Location: England, Somerset, Ham Hill
Age: 400-200 BCE
mtDNA: H1c3a

Sample: I19652 (Female)
Location: England, Somerset, Ham Hill
Age: 395-205 calBCE
mtDNA: J1c2a2

Sample: I19656 (Male)
Location: England, Somerset, Ham Hill
Age: 387-198 calBCE
Y-DNA: R-DF13
mtDNA: H5’36

Sample: I16593 (Female)
Location: England, Somerset, Ham Hill
Age: 382-197 calBCE
mtDNA: H7b

Sample: I13680 (Male)
Location: England, Somerset, Ham Hill
Age: 366-176 calBCE
Y-DNA: R-L21
mtDNA: U5a2a1

Sample: I19655 (Female)
Location: England, Somerset, Ham Hill
Age: 400-100 BCE
mtDNA: H1c3a

Sample: I19855 (Male)
Location: England, Somerset, Ham Hill
Age: 400-100 BCE
Y-DNA: R-L21
mtDNA: H1ak1

Sample: I19854 (Female)
Location: England, Somerset, Ham Hill
Age: 400-100 BCE
mtDNA: J1c2a2

Sample: I11993 (Female)
Location: England, Somerset, Ham Hill
Age: 400-100 BCE
mtDNA: J1c2a2

Sample: I11994 (Female)
Location: England, Somerset, Ham Hill
Age: 400-100 BCE
mtDNA: U5a2c3a

Sample: I19657 (Female)
Location: England, Somerset, Ham Hill
Age: 356-59 calBCE
mtDNA: H5s

Sample: I21315 (Male)
Location: England, Somerset, Ham Hill
Age: 173 calBCE – 5 calCE
Y-DNA: R-M269
mtDNA: T1a1’3

Sample: I13684 (Female)
Location: England, Somerset, Meare Lake Village West
Age: 541-391 calBCE
mtDNA: W1-T119C

Sample: I11146 (Male)
Location: England, Somerset, Meare Lake Village West
Age: 400-200 BCE
Y-DNA: R-P310
mtDNA: J1c1c

Sample: I13682 (Male)
Location: England, Somerset, Mells Down, Kingsdown Camp
Age: 793-544 calBCE
Y-DNA: R-BY168376
mtDNA: H5a1

Sample: I6748 (Male)
Location: England, Somerset, Mendip, Hay Wood Cave
Age: 3956-3769 calBCE
mtDNA: H

Sample: I11145 (Male)
Location: England, Somerset, North Perrott, North Perrott Manor
Age: 166 calBCE – 14 calCE
Y-DNA: R-Z251
mtDNA: H1q

Sample: I11144 (Male)
Location: England, Somerset, North Perrott, North Perrott Manor
Age: 149 calBCE – 65 calCE
Y-DNA: R-A9857
mtDNA: H5’36

Sample: I5365 (Female)
Location: England, Somerset, Priddy
Age: 103 calBCE – 107 calCE
mtDNA: U5a1b1e

Sample: I11995 (Female)
Location: England, Somerset, South Cadbury, Cadbury Castle
Age: 742-399 calBCE
mtDNA: H2a5

Sample: I21303 (Female)
Location: England, Somerset, South Cadbury, Cadbury Castle
Age: 153 calBCE – 25 calCE
mtDNA: H2a5

Sample: I21302 (Male)
Location: England, Somerset, South Cadbury, Cadbury Castle
Age: 46 calBCE – 117 calCE
Y-DNA: R-DF13
mtDNA: K1a-T195C!

Sample: I6776 (Male)
Location: England, Somerset, Storgoursey, Wick Barrow
Age: 2400-2000 BCE
Y-DNA: R-P312
mtDNA: R

Sample: I21306 (Male)
Location: England, Somerset, Tickenham, Diamond Cottage
Age: 2200-1400 BCE
Y-DNA: R-BY31082
mtDNA: H1an1

Sample: I21305 (Male)
Location: England, Somerset, Weston-super-Mare, Grove Park Road
Age: 800 BCE – 100 CE
Y-DNA: R-DF13
mtDNA: H1

Sample: I16596 (Male)
Location: England, Somerset, Worlebury
Age: 400-50 BCE
mtDNA: H3b-G16129A!

Sample: I13681 (Male)
Location: England, Somerset, Worlebury
Age: 400-50 BCE
mtDNA: H3b-G16129A!

Sample: I11143 (Male)
Location: England, Somerset, Worlebury
Age: 352-53 calBCE
Y-DNA: R-FT5780
mtDNA: H3b-G16129A!

Sample: I13726 (Male)
Location: England, Somerset, Worlebury
Age: 351-52 calBCE
Y-DNA: R-BY23964
mtDNA: H13a1a1

Sample: I11991 (Male)
Location: England, Somerset, Worlebury
Age: 349-50 calBCE
Y-DNA: R-DF13
mtDNA: H3b-G16129A!

Sample: I11992 (Male)
Location: England, Somerset, Worlebury
Age: 343-50 calBCE
Y-DNA: R-DF13
mtDNA: H3b-G16129A!

Sample: I11142 (Male)
Location: England, Somerset, Worlebury
Age: 197-44 calBCE
Y-DNA: R-PR1289
mtDNA: H3b-G16129A!

Sample: I16619 (Male)
Location: England, Sussex, Brighton, Bevendean
Age: 361-106 calBCE
mtDNA: H49

Sample: I16617 (Female)
Location: England, Sussex, Brighton, Black Rock
Age: 777-516 calBCE
mtDNA: H4a1a1a

Sample: I16615 (Female)
Location: England, Sussex, Brighton, Coldean Lane, Varley Hall
Age: 1259-912 calBCE
mtDNA: K1c1

Sample: I14543 (Female)
Location: England, Sussex, Brighton, Ditchling Road
Age: 2450-1600 BCE
mtDNA: K1a4a1g

Sample: I16616 (Female)
Location: England, Sussex, Brighton, Mile Oak
Age: 1410-1227 calBCE
mtDNA: H13a1a1

Sample: I14552 (Male)
Location: England, Sussex, Brighton, Moulsecoomb
Age: 92 calBCE – 110 calCE
Y-DNA: R-P312
mtDNA: J1c2

Sample: I14553 (Male)
Location: England, Sussex, Brighton, Roedean Crescent
Age: 1954-1749 calBCE
Y-DNA: R-S15808
mtDNA: H5c

Sample: I14551 (Female)
Location: England, Sussex, Brighton, Slonk Hill
Age: 514-234 calBCE
mtDNA: H6a1a

Sample: I7632 (Male)
Location: England, Sussex, Brighton, Slonk Hill
Age: 391-203 calBCE
Y-DNA: R-CTS4528
mtDNA: H1

Sample: I14550 (Female)
Location: England, Sussex, Brighton, Slonk Hill
Age: 700 BCE – 900 CE
mtDNA: H3-T152C!

Sample: I16618 (Female)
Location: England, Sussex, Brighton, Surrendon Road
Age: 787-544 calBCE
mtDNA: K1a4

Sample: I14549 (Female)
Location: England, Sussex, Brighton, Woodingdean
Age: 401-208 calBCE
mtDNA: H1

Sample: I27379 (Male)
Location: England, Sussex, North Bersted
Age: 174-51 calBCE
Y-DNA: R-FGC56332
mtDNA: H7d

Sample: I27380 (Male)
Location: England, Sussex, Westbourne, ‘Racton Man’
Age: 2453-2146 cal BCE
Y-DNA: R-Z290
mtDNA: H3k1

Sample: I2611 (Male)
Location: England, Tyne and Wear, Blaydon, Summerhill
Age: 3092-2905 calBCE
Y-DNA: R-L21
mtDNA: U5a2d1

Sample: I14837 (Female)
Location: England, West Yorkshire, Dalton Parlours
Age: 381 calBCE – 6 calCE
mtDNA: K1a4a1c

Sample: I14347 (Male)
Location: England, West Yorkshire, Wattle Syke
Age: 371-176 calBCE
Y-DNA: R-DF23
mtDNA: K2a

Sample: I14348 (Female)
Location: England, West Yorkshire, Wattle Syke
Age: 368-173 calBCE
mtDNA: U3a1c

Sample: I14353 (Male)
Location: England, West Yorkshire, Wattle Syke
Age: 349-51 calBCE
Y-DNA: R-L21
mtDNA: U5b2a1a1

Sample: I14352 (Female)
Location: England, West Yorkshire, Wattle Syke
Age: 193-6 calBCE
mtDNA: K2a

Sample: I14351 (Female)
Location: England, West Yorkshire, Wattle Syke
Age: 193-6 calBCE
mtDNA: K2a

Sample: I14359 (Male)
Location: England, West Yorkshire, Wattle Syke
Age: 200 BCE – 100 CE
mtDNA: J1c1

Sample: I14360 (Female)
Location: England, West Yorkshire, Wattle Syke
Age: 151 calBCE – 62 calCE
mtDNA: J1c1

Sample: I14200 (Male)
Location: England, Wiltshire, Amesbury Down
Age: 2470-2239 calBCE
Y-DNA: R-L151
mtDNA: K1b1a

Sample: I2565 (Male)
Location: England, Wiltshire, Amesbury Down
Age: 2456-2146 calBCE
Y-DNA: R-L21
mtDNA: W1-T119C

Sample: I2419 (Female)
Location: England, Wiltshire, Amesbury Down
Age: 2393-2144 calBCE
mtDNA: H1

Sample: I2598 (Male)
Location: England, Wiltshire, Amesbury Down
Age: 2139-1950 calBCE
Y-DNA: R-P310
mtDNA: H

Sample: I19287 (Female)
Location: England, Wiltshire, Amesbury Down
Age: 761-422 calBCE
mtDNA: K1b1a

Sample: I16602 (Female)
Location: England, Wiltshire, Amesbury Down
Age: 734-403 calBCE
mtDNA: H1aq

Sample: I16600 (Male)
Location: England, Wiltshire, Amesbury Down
Age: 713-381 calBCE
Y-DNA: R-P310
mtDNA: T2b1

Sample: I16599 (Male)
Location: England, Wiltshire, Amesbury Down
Age: 411-208 calBCE
Y-DNA: R-DF13
mtDNA: T2b1

Sample: I16601 (Female)
Location: England, Wiltshire, Amesbury Down
Age: 343-43 calBCE
mtDNA: H17

Sample: I21309 (Male)
Location: England, Wiltshire, Battlesbury Bowl
Age: 354-57 calBCE
Y-DNA: R-FGC33840
mtDNA: X2b-T226C

Sample: I21307 (Male)
Location: England, Wiltshire, Battlesbury Bowl
Age: 346-52 calBCE
Y-DNA: R-P310
mtDNA: H7d

Sample: I21310 (Female)
Location: England, Wiltshire, Battlesbury Bowl
Age: 386 calBCE – 58 calCE
mtDNA: U4c1

Sample: I21311 (Female)
Location: England, Wiltshire, Battlesbury Bowl
Age: 336-49 calBCE
mtDNA: H16-T152C!

Sample: I21308 (Male)
Location: England, Wiltshire, Battlesbury Bowl
Age: 356 calBCE – 110 calCE
Y-DNA: R-P312
mtDNA: J1c1b

Sample: I21313 (Male)
Location: England, Wiltshire, Casterley Camp
Age: 354-57 calBCE
Y-DNA: R-P312
mtDNA: H3g

Sample: I21312 (Male)
Location: England, Wiltshire, Casterley Camp
Age: 343-51 calBCE
Y-DNA: R-BY129194
mtDNA: J1b1a1

Sample: I21314 (Female)
Location: England, Wiltshire, Casterley Camp
Age: 342-51 calBCE
mtDNA: V23

Sample: I16595 (Female)
Location: England, Wiltshire, Longbridge Deverill, Cow Down
Age: 387-204 calBCE
mtDNA: T2b9

Sample: I12608 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 1055-904 calBCE
mtDNA: H3ap

Sample: I12614 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 1100-800 BCE
mtDNA: K1a1b1

Sample: I12612 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 1100-800 BCE
mtDNA: U1a1a

Sample: I12611 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 1100-800 BCE
mtDNA: I2

Sample: I12613 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 1100-800 BCE
mtDNA: H1

Sample: I12624 (Female)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 900-800 BCE
mtDNA: H3

Sample: I12610 (Male)
Location: England, Wiltshire, Potterne, Blackberry Field
Age: 765-489 calBCE
Y-DNA: R-M269
mtDNA: J1c1

Sample: I19858 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 1532-1431 calBCE
Y-DNA: R-Z290
mtDNA: J2b1a

Sample: I19857 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 1518-1425 calBCE
Y-DNA: R-L617
mtDNA: J2b1a

Sample: I19859 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 1504-1403 calBCE
Y-DNA: I-S2497
mtDNA: H3

Sample: I19860 (Female)
Location: England, Wiltshire, Rowbarrow
Age: 1503-1401 calBCE
mtDNA: T2b21

Sample: I19867 (Female)
Location: England, Wiltshire, Rowbarrow
Age: 780-541 calBCE
mtDNA: H3-T16311C!

Sample: I19861 (Female)
Location: England, Wiltshire, Rowbarrow
Age: 779-541 calBCE
mtDNA: U2e2a1c

Sample: I13688 (Female)
Location: England, Wiltshire, Rowbarrow
Age: 775-516 calBCE
mtDNA: H1-C16239T

Sample: I19868 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 771-476 calBCE
Y-DNA: R-DF13
mtDNA: T2e1a

Sample: I19862 (Female)
Location: England, Wiltshire, Rowbarrow
Age: 767-423 calBCE
mtDNA: H5a1f

Sample: I13689 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 753-411 calBCE
Y-DNA: R-BY4297
mtDNA: K1a3a

Sample: I13690 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 750-408 calBCE
mtDNA: H1b3

Sample: I19863 (Male)
Location: England, Wiltshire, Rowbarrow
Age: 460-382 calBCE
Y-DNA: R-DF13
mtDNA: N1a1a1a2

Sample: I4949 (Male)
Location: England, Wiltshire, Winterbourne Monkton, North Millbarrow
Age: 3624-3376 calBCE
Y-DNA: I-M284
mtDNA: T2b

Sample: I8582 (Female)
Location: Isle of Man, Rushen, Strandhall
Age: 2195-1973 calBCE
mtDNA: H2a1e1

Sample: I12312 (Male)
Location: Scotland, Argyll and Bute, Isle of Ulva, Ulva Cave
Age: 3751-3636 calBCE
Y-DNA: I-P214
mtDNA: K1a-T195C!

Sample: I12314 (Female)
Location: Scotland, Argyll and Bute, Oban, Carding Mill Bay II
Age: 3647-3533 calBCE
mtDNA: T2b

Sample: I12313 (Female)
Location: Scotland, Argyll and Bute, Oban, Carding Mill Bay II
Age: 3700-3350 BCE
mtDNA: T2b

Sample: I12317 (Male)
Location: Scotland, Argyll and Bute, Oban, Carding Mill Bay II
Age: 3629-3377 calBCE
Y-DNA: I-A8742
mtDNA: H5

Sample: I2658 (Male)
Location: Scotland, Argyll and Bute, Oban, Macarthur Cave
Age: 4000-3700 BCE
mtDNA: W1-T119C

Sample: I3137 (Male)
Location: Scotland, Argyll and Bute, Oban, Raschoille Cave
Age: 3800-3000 BCE
Y-DNA: I-S2599
mtDNA: HV0-T195C!

Sample: I3139 (Female)
Location: Scotland, Argyll and Bute, Oban, Raschoille Cave
Age: 3800-3000 BCE
mtDNA: H45

Sample: I16498 (Female)
Location: Scotland, East Lothian, Broxmouth
Age: 750-404 calBCE
mtDNA: H2a1

Sample: I2692 (Female)
Location: Scotland, East Lothian, Broxmouth
Age: 727-396 calBCE
mtDNA: H2a1

Sample: I16422 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 364-121 calBCE
Y-DNA: R-L151
mtDNA: H3-T152C!

Sample: I2695 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 364-121 calBCE
Y-DNA: R-P312
mtDNA: H2a1

Sample: I2694 (Female)
Location: Scotland, East Lothian, Broxmouth
Age: 361-110 calBCE
mtDNA: H1ak1

Sample: I2696 (Female)
Location: Scotland, East Lothian, Broxmouth
Age: 355-55 calBCE
mtDNA: U5a2b4a

Sample: I16503 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 349-51 calBCE
Y-DNA: R-Z30597
mtDNA: H1ak1

Sample: I16416 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 346-51 calBCE
Y-DNA: R-Z30597
mtDNA: H3-T152C!

Sample: I2693 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 197 calBCE – 1 calCE
Y-DNA: R-P310
mtDNA: H3-T152C!

Sample: I16504 (Male)
Location: Scotland, East Lothian, Broxmouth
Age: 42 calBCE – 116 calCE
Y-DNA: R-DF13
mtDNA: H1as

Sample: I16448 (Female)
Location: Scotland, East Lothian, Innerwick, Thurston Mains
Age: 2337-2138 calBCE
mtDNA: K1b1a1

Sample: I5471 (Female)
Location: Scotland, East Lothian, Innerwick, Thurston Mains
Age: 2269-1985 calBCE
mtDNA: H1c3a

Sample: I2413 (Female)
Location: Scotland, East Lothian, Innerwick, Thurston Mains
Age: 2114-1900 calBCE
mtDNA: H1a1

Sample: I16499 (Male)
Location: Scotland, East Lothian, North Berwick, Law Road
Age: 337-43 calBCE
Y-DNA: R-ZP18
mtDNA: I2a

Sample: I16495 (Female)
Location: Scotland, East Lothian, North Berwick, Law Road
Age: 196 calBCE – 3 calCE
mtDNA: H6a1a8

Sample: I16418 (Male)
Location: Scotland, East Lothian, North Berwick, Law Road
Age: 97 calBCE – 107 calCE
Y-DNA: I-L1195
mtDNA: U5a1d2a

Sample: I16413 (Female)
Location: Scotland, East Lothian, North Berwick, Law Road
Age: 44 calBCE – 117 calCE
mtDNA: H6a1a8

Sample: I2569 (Male)
Location: Scotland, Eweford Cottages
Age: 2140-1901 calBCE
Y-DNA: R-P312
mtDNA: K1a3a

Sample: I3567 (Male)
Location: Scotland, Highland, Applecross
Age: 173 calBCE – 8 calCE
Y-DNA: R-FT221759
mtDNA: J1c3b

Sample: I3566 (Male)
Location: Scotland, Highland, Applecross
Age: 170 calBCE – 10 calCE
Y-DNA: R-L21
mtDNA: H13a1a

Sample: I3568 (Male)
Location: Scotland, Highland, Applecross
Age: 42 calBCE – 119 calCE
Y-DNA: R-A277
mtDNA: H7a1

Sample: I19286 (Male)
Location: Scotland, Highland, Embo
Age: 3331-3022 calBCE
Y-DNA: I-M170
mtDNA: J1c1

Sample: I2824 (Male)
Location: Scotland, Isle of Harris, Northton
Age: 41 calBCE – 121 calCE
Y-DNA: R-M269
mtDNA: H13a1a

Sample: I2656 (Male)
Location: Scotland, Longniddry, Grainfoot
Age: 1283-940 calBCE
Y-DNA: R-P312
mtDNA: H2a2a2

Sample: I2983 (Female)
Location: Scotland, Orkney, Bu
Age: 399-207 calBCE
mtDNA: U2e2a1c

Sample: I2982 (Male)
Location: Scotland, Orkney, Bu
Age: 395-207 calBCE
Y-DNA: R-Z16400
mtDNA: H7a1

Sample: I2799 (Male)
Location: Scotland, Orkney, Howe of Howe
Age: 152 calBCE – 22 calCE
Y-DNA: R-DF49
mtDNA: H1

Sample: I2629 (Male)
Location: Scotland, Orkney, Isbister
Age: 3350-2350 BCE
Y-DNA: I-L161
mtDNA: J1c1b

Sample: I2796 (Male)
Location: Scotland, Orkney, Point of Cott
Age: 3706-3536 calBCE
Y-DNA: I-FGC7113
mtDNA: H3

Sample: I5474 (Female)
Location: Scotland, Scottish Borders, Cumledge (Auchencraw Park)
Age: 151 calBCE – 77 calCE
mtDNA: K1a26

Sample: I2699 (Male)
Location: Scotland, South Uist, Hornish Point
Age: 159 calBCE – 26 calCE
mtDNA: V10

Sample: I16412 (Male)
Location: Scotland, Stirling, Coneypark Cairn (Cist 1)
Age: 2134-2056 calBCE
Y-DNA: I-CTS616
mtDNA: R

Sample: I27384 (Male)
Location: Scotland, West Lothian, House of Binns
Age: 90 calBCE – 110 calCE
Y-DNA: R-L21
mtDNA: H2a2a1g

Sample: I27385 (Male)
Location: Scotland, West Lothian, House of Binns
Age: 43 calBCE – 117 calCE
Y-DNA: R-L1066
mtDNA: T2b19

Sample: I16475 (Male)
Location: Wales, Clwyd, Dinorben
Age: 550-1 BCE
Y-DNA: R-P312
mtDNA: X2b

Sample: I16514 (Female)
Location: Wales, Clwyd, Dinorben
Age: 550-1 BCE
mtDNA: HV0

Sample: I16410 (Female)
Location: Wales, Clwyd, Dinorben
Age: 550-1 BCE
mtDNA: T2b

Sample: I16479 (Unknown sex)
Location: Wales, Conwy, Llandudno, Little Ormes Head, Ogof Rhiwledyn
Age: 1500-1100 BCE
mtDNA: H

Sample: I16491 (Male)
Location: Wales, Denbighshire, Llanferres, Orchid Cave
Age: 2876-2680 calBCE
Y-DNA: I-L1195
mtDNA: U5b2b

Sample: I6771 (Female)
Location: Wales, Glamorgan, Llantwit Major, Llanmaes
Age: 169 calBCE – 2 calCE
mtDNA: U4b1a

Sample: I16471 (Female)
Location: Wales, Glamorgan, Llantwit Major, Llanmaes
Age: 200 BCE – 50 CE
mtDNA: H2a

Sample: I16405 (Male)
Location: Wales, Glamorgan, RAF St Athan
Age: 397-205 calBCE
Y-DNA: R-DF13
mtDNA: K1a-T195C!

Sample: I5440 (Male)
Location: Wales, Glamorgan, St. Fagan’s
Age: 1500-1322 calBCE
Y-DNA: R-L151
mtDNA: K1c1

Sample: I2574 (Female)
Location: Wales, North Wales, Llandudno, Great Orme
Age: 1417-1226 calBCE
mtDNA: U5a1a2b

Sample: I16476 (Female)
Location: Wales, West Glamorgan, Gower Peninsula, Port Eynon, Culver Hole Cave
Age: 1600-1200 BCE
mtDNA: H24

Sample: I16488 (Male)
Location: Wales, West Glamorgan, Gower Peninsula, Port Eynon, Culver Hole Cave
Age: 1201-1015 calBCE
Y-DNA: R-L21
mtDNA: U5a1b1

_____________________________________________________________

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DNA Shows Peter Johnson and Mary Polly Philips Are My Relatives, But Are They My Ancestors? – 52 Ancestors #350

Posted on by
10

One of the requests by several people for 2022 article topics revolved in some way around solving challenges and showing my work.

In this case, I’m going to show both my work and the work of a newly-discovered cousin, Greg Simkins.

Let’s start by reminding you of something I said last week in Darcus Johnson (c1750-c1835) Chain Carrier – Say What??.

Darcus is reported in many trees to be the daughter of Peter Johnson (Johnston, Johnstone) and his wife Mary Polly Phillips. Peter reportedly lived in Pennsylvania and died in Allegheny County, PA. However, I am FAR from convinced that this couple was Darcus’s parents.

The distance from Shenandoah County, VA to Allegheny Co., PA is prohibitive for courting.

The Shenandoah County records need to be thoroughly researched with various Johnson families reconstructed. I’m hoping that perhaps someone has already done that and a Johnson family was living not terribly far from Jacob Dobkins father, John Dobkins. That would be the place to start.

Greg, Peter Johnson’s descendant through son James reached out to me.

Hi Roberta, I read your essay today on Dorcas Johnson. I wanted to write to you because I am a descendant of Dorcas’s brother James and have DNA matches to support our connection.

Clearly, I was very interested, but I learned long ago not to get too excited.

Then, Greg kindly shared his tree and DNA results with me. He was also generous enough to allow me to incorporate his information into this article. So yes, this article is possible entirely thanks to Greg.

I was guardedly excited about Greg’s communication, but I wasn’t prepared for the HUGE shock about to follow!

Whoa!!!

Greg has done his homework and stayed after school.

First, he tracked the descendants of Peter through all of his children, to present, where possible, and added them into his trees at the genealogy vendors. The vendors can do much better work for you with as much ammunition as you can provide.

Second, he has doggedly tracked matches at MyHeritage, FamilyTreeDNA, Ancestry and GEDmatch that descend through Peter Johnson and Mary Polly Phillips’s children. By doggedly, I mean he has spent hundreds to thousands of hours by his estimation – and based on what I see, I would certainly agree. In doing so, he pushed his own line back from his great-great-grandmother, Elizabeth Johnson, three generations to Peter Johnson and Mary Polly Phillips – and proved its accuracy using DNA.

Altogether, Greg has identified almost 250 matches that descend from Peter Johnson and Mary Polly Phillips, and mapped those segments across his chromosomes.

Greg made notes for each match by entering the number of matching cMs into their profile names as a suffix in his tree. For example, “David Johnson 10cM” instead of “David Johnson Jr.” or Sr.  That way, it’s easy to quickly see who is a match and by how much. Brilliant! I’m adopting that strategy. It won’t affect what other people see, because no living people are shown in trees.

Of course, DNA is on top of traditional genealogical research that we are all familiar with that connects people via deeds, wills, and other records.

Additionally, Greg records research information for individuals as a word document or pdf file and attaches them as documents to the person’s profile in his tree. His tree is searchable and shareable, so this means those resources are available to other people too. We want other researchers to find us and our records for EXACTLY this reason.

One thing to note is that if you are using Ancestry and use the Notes function on profiles, the notes don’t show to people with whom you share your tree, but links, sources and attached documents do.

Greg has included both “Other Sources” and “Web Links” below.

Click images to enlarge

For example, if I click on Greg’s link to Historic Pittsburg, I see the land grant location for Peter Johnson. Wow, this was unexpected.

Ok, I love maps and I’m hooked. Notice the names of the neighbors too. You’ll see Applegate again. Also, note that Thomas Applegate sold his patent to Richard Johnson. Remember the FAN club – friends and neighbors.

Ok, back to DNA for now.

The Children

Ancestors with large families are the best for finding present-day DNA matches. Of course, that’s because there are more candidates. More descendants and that means more people who might test someplace. This is also why you want to be sure to have your DNA in all 4 major DNA vendors, FamilyTreeDNA, MyHeritage, Ancestry, and 23andMe, plus GEDmatch.

This is a portion of Greg’s tree that includes the children of Peter Johnson and Mary Polly Phillips. Note that two Johnson females married Dobkins men. I’ve always suspected that Margaret Johnson and Dorcas Johnson were sisters, but unless we could use mitochondrial DNA, or figure out who the parents of either Peter or Mary are, there’s no good way to prove it.

We’re gathering some very valuable evidence.

At Ancestry, Greg has 85 matches on his ThruLines for Peter Johnson and Mary Polly Phillips, respectively.

  • Of course, Greg has the most matches for his own line through Peter’s son James Johnson (1752-1826) who married Elizabeth Lindsay and died in Lawrence County, IL: 35 matches.
  • Next is Margaret Johnson (1780-1833) who married Evan Dobkins in Dunmore County, VA, brother of my ancestor, Jacob Dobkins. She probably died in Cocke County, TN: 25 matches. Dorcas named one of her children Margaret and Margaret may have named one of her children Dorcas.
  • Solomon Johnson (1765-1843) married Frances Warne and stayed in Allegheny County, PA: 8 matches. Notice one of Peter’s neighbors was a Warner family. Dorcas named one of her children Solomon, a fairly unusual name.
  • Mary Johnson (1770-1833) married Garrett Wall Applegate and died in Harrison County, IN: 7 matches. The Applegates were Peter Johnson’s neighbors and Garrett served in the Revolutionary War in the 8th VA Regiment. Clearly, some of these settlers came from or spent time in Virginia.
  • Dorcas Johnson (c1750-c1835) married Jacob Dobkins in Dunmore County, VA and died in Claiborne County, TN: 5 matches.
  • Peter Johnson (1753-1840) married Eleanor “Nellie” Peter and died in Jefferson County, KY: 4 matches.
  • Richard D. Johnson (1752-1818) married Hannah Dungan and Elizabeth Nash: 2 matches.

Unfortunately, since most of those matches are between 7 and 20 cM, and Ancestry does not display shared matches under 20 cM, we can’t use Ancestry’s comparison tool to see if these people also match each other. That’s VERY unfortunate and extremely frustrating.

Greg matches more people from this line at MyHeritage, GEDmatch and FamilyTreeDNA, and thankfully, those vendors all three provide segment information AND shared match information.

Cousins Are Critical

While Greg, unfortunately, does not match me, he does match several of my cousins whose tests I manage.

Two of those cousins both descend from Darcus Johnson through her daughter Jenny Dobkins, through her daughter Elizabeth Campbell, through her daughter Rutha Dodson, through her sons John Y. Estes and Lazarus Estes, respectively.

Another descends through Jenny Dobkins son, William Newton Campbell for another 5 generations. These individuals all match on a 17 cM segment of Chromosome 20.

Other known cousins match Greg on different chromosomes.

Looking at their shared matches at FamilyTreeDNA, we find more Dobkins, Dodson and Campbell cousins, some that were previously unknown to me. One of those cousins also descends through William Newton Campbell’s daughter for another 4 generations and matches on the same segment of chromosome 20.

DNAPainter

Emails have been flying back and forth between me and Greg, each one with some piece of information that one of us has found that we want to be sure the other has too. Having research buddies is wonderful!

Then, Greg sent a screenshot of a portion of his chromosome 20 from DNAPainter that includes the DNA of the cousins mentioned above. I didn’t realize Greg was using DNAPainter. It’s an understatement to say I’m thrilled because DNAPainter does the cross-vendor triangulation work automatically for you.

Just look at all of those matches that carry this Johnson/Phillips segment of chromosome 20. Holy chimloda.

Greg also sent his DNAPainter sharing link, and it turns out that this is only a partial list, with one of my cousins highlighted, dead center in the list of Peter Johnson’s and Mary Polly Phillip’s descendants. Greg has even more not shown.

Trying Not to Jump to Conclusions

I’m trying so hard NOT to jump to conclusions, but this is just SOOOO EXCITING!

Little doubt remains that indeed, Peter Johnson and Mary Polly Phillips are the parents of Dorcas Johnson who married Jacob Dobkins and also of Margaret Johnson who married Evan Dobkins. I’ve eliminated the possibility of other common ancestors, as much as possible, and verified that the descent is through multiple children. This particular segment on chromosome 20 reaches across multiple children’s lines.

I say little doubt remains, because some doubt does remain. It’s possible that perhaps Dorcas and her sister weren’t actually daughters of Peter Johnson, but maybe children of his brother? Peter was reported to have a brother James, a sheriff in Cumberland County, PA. but again, we lack proof. If Dorcas is Peter Johnson’s niece, her descendants would still be expected to match some of the descendants of Peter and his wife.

Also complicating matters is the fact that Greg also has a Campbell brick wall with a James Campbell born about 1790 who lived in Fayette County, PA, in the far northwest corner of the state. Therefore, DNA matches through Dorcas Johnson Dobkins’s daughters Jenny and Elizabeth who married Campbell brothers need to be verified through her children’s lines that do NOT descend through her daughters who married Campbell men.

Nagging Questions

I know, I’m being a spoilsport, but I still have questions that need answers.

For example, I still need to account for how the Johnson girls managed to get to Shenandoah County, VA (Dunmore County at that time) to meet the Dobkins boys, spend enough time there to court, and then marry Evan and Jacob nine months apart in 1775. Surely they were living there. Young women simply did not travel, especially not great distances, and marriages occurred in the bride’s home county. Yet, they married in Shenandoah County, VA, not in PA.

What About the Records?

We are by no means done. In fact, I’ve just begun. I have some catching up to do. Greg has focused on Peter Johnson and Mary Polly Phillips in Pennsylvania. I need to focus on Virginia.

Of course, the next challenge is actual records.

What exists and what doesn’t? FamilySearch provides a list for Dunmore County, here, and Shenandoah, here.

Was Peter Johnson ever in Dunmore County that became Shenandoah County, VA, and if so when and where? If not, how the heck did his two daughters marry the Dobkins boys in 1775? Was there another Johnson man in Dunmore during that time? Was it James?

Where was Peter Johnson in 1775 when Dorcas and Margaret were marrying? Can we positively account for him in Pennsylvania or elsewhere?

Some information has been published about Peter Johnson, but those critical years are unaccounted for.

It appears that the Virginia Archives has a copy of the 1774-1776 rent rolls for Dunmore County, but they aren’t online. That’s the best place to start. Fingers crossed for one Peter Johnson living right beside John Dobkins, Jacob’s father. Now THAT would convince me.

Stay tuned!

Note – If you’d like to view Greg’s tree at Ancestry, its name is “MyHeritage Tree Simkins” and you can find it by searching for Maude Gertrude Wilson born in 1876 in Logan County, Illinois, died January 27, 1950 in Ramsey County, Minnesota, and married Harry A. Simkins. Elizabeth Ann Johnson (1830-1874) is Maude’s grandmother.

_____________________________________________________________

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What Article Topics Would You Like in 2022?

Posted on by
134

I have lots of ideas about what I’d like to write about, but I work with genetic genealogy every day and what I’d like to write about might not be the same as what you want to read. As always, I’ll include articles about new features, tools, vendor announcements, and opportunities such as sales.

As for the rest, I’d like your opinion. What would you like to see me cover? Before I ask these 10 questions, and you answer, please note that you can search the blog by keyword or topic to see if I’ve already covered a topic.

  1. Are you interested in DNA basics? If so, which topics?
  2. Would you enjoy more vendor-specific articles? If so, which vendors and topics?
  3. Would you like tool-specific instruction? If so, which tools?
  4. Would you like more articles in the Concepts series? If so, are there specific genetic concepts you’d like to see covered?
  5. Would you like examples of how to integrate the genetics aspect with traditional genealogy? Can you give me an example?
  6. Would you like intermediate or advanced topics? If so, which ones?
  7. Would you like me to write and publish a new book? If so, what topic(s)? Traditional printed bound book, e-book, or both?
  8. Would you be interested in other publication types such as Podcasts, YouTube videos, or something else? If so, in addition to my blog articles, or instead of blog articles? How would I resolve privacy issues showing live screens of my results?
  9. You’re always welcome to share my blog articles by forwarding emails, links, or on social media. Do you share my articles with others? If so, where and how do you share?
  10. What are your favorite articles and types of articles? What do you find exciting? Why?

I welcome your input in the comments. You can just write free-format or answer by question number. If you have ideas that I’ve missed, please add those too.

I can’t wait to see your suggestions. 2022 is going to be a great year!

_____________________________________________________________

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If you haven’t already subscribed (it’s free,) you can receive an email whenever I publish by clicking the “follow” button on the main blog page, here.

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I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

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Identify Your Ancestors – Follow Nested Ancestral Segments

Posted on by
15

I don’t think that we actively think about our DNA segments as nested ancestors, like Russian Matryoshka dolls, but they are.

That’s exactly why segment information is critical for genealogists. Every segment, and every portion of a segment, has an incredibly important history. In fact, you could say that the further back in time we can track a segment, the more important it becomes.

Let’s see how to unveil nested segments. I’ll use my chromosome 20 as an example because it’s a smaller chromosome. But first, let’s start with my pedigree chart.

Pedigree

Click images to enlarge.

Before we talk about nested segments that originated with specific ancestors, it’s important to take a look at the closest portion of my maternal pedigree chart. My DNA segments came from and through these people. I’ll be working with the first 5 generations, beginning with my mother as generation #1.

Generation 1 – Parents

In the first generation, we receive a copy of each chromosome from each parent. I have a copy of chromosome 20 from my mother and a copy from my father.

At FamilyTreeDNA, you can see that I match my mother on the entire tested region of each chromosome.

Therefore, the entire length of each of my chromosomes is assigned to both mother and father because I received a copy from each parent. I’m fortunate that my mother’s DNA was able to be tested before she passed away.

We see that each copy of chromosome 20 is a total of 110.20 cM long with 17,695 SNPs.

Of course, my mother inherited the DNA on her chromosome 20 from multiple ancestors whose DNA combined in her parents, a portion of which was inherited by my mother. Mom received one chromosome from each of her parents.

I inherited only one copy of each chromosome (In this case, chromosome 20) from Mom, so the DNA of her two parents was divided and recombined so that I inherited a portion of my maternal chromosome 20 from both of my maternal grandparents.

Identifying Maternal and Paternal Matches

Associating matches with your maternal or paternal side is easy at FamilyTreeDNA because their Family Finder matching does it automatically for you if you upload (or create) a tree and link matches that you can identify to their proper place in your tree.

FamilyTreeDNA then uses that matching segment information from known, identified relatives in your tree to place people who match you both on at least one significant-sized segment in the correct maternal, paternal, (or both) buckets. That’s triangulation, and it happens automatically. All you have to do is click on the Maternal tab to view your triangulated maternal matches. As you can see, I have 1432 matches identified as maternal. 

Some other DNA testing companies and third-party tools provide segment information and various types of triangulation information, but they aren’t automated for your entire match list like Family Finder matching at FamilyTreeDNA.

You can read about triangulation in action at MyHeritage, here, 23andMe, here, GEDmatch, here, and DNAPainter, which we’ll use, here. Genetic Affairs AutoKinship tool incorporates triangulation, as does their AutoSegment Triangulation Cluster Tool at GEDmatch. I’ve compiled a reference resource for triangulation, here.

Every DNA testing vendor has people in their database that haven’t tested anyplace else. Your best strategy for finding nested segments and identifying matches to specific ancestors is to test at or transfer your DNA file to every vendor plus GEDmatch where people who test at Ancestry sometimes upload for matching. Ancestry does not provide segment information or a chromosome browser so you’ll sometimes find Ancestry testers have uploaded to GEDmatch, FamilyTreeDNA  or MyHeritage where segment information is readily available. I’ve created step-by-step download/upload instructions for all vendors, here.

Generation 2 – Grandparents

In the second generation, meaning that of my grandparents, I inherited portions of my maternal and paternal grandmother’s and grandfather’s chromosomes.

My maternal and paternal chromosomes can be divided into two pieces or groups each, one for each grandparent.

Using DNAPainter, we can see my father’s chromosome 20 on top and my mother’s on the bottom. I have previously identified segments assigned to specific ancestors which are represented by different colors on these chromosomes. You can read more about how to use DNAPainter, here.

We can divide the DNA inherited from each parent into the DNA inherited from each grandparent based on the trees of people we match. If we test cousins from each side, assigning segments maternally or paternally becomes much, much easier. That’s exactly why I’ve tested several.

For the rest of this article, I’m focusing only on my mother’s side because the concepts and methods are the same regardless of whether you’re working on your maternal side or your paternal side.

Using DNAPainter, I expanded my mother’s chromosome 20 in order to see all of the people I’ve painted on my mother’s side.

DNAPainter allows us to paint matching segments from multiple testing vendors and assign them to specific ancestors as we identify common ancestors with our matches.

Based on these matches, I’ve divided these maternal matches into two categories:

  • Maternal grandmother, meaning my mother’s mother, bracketed in red boxes
  • Maternal grandfather, meaning my mother’s father, bracketed in black boxes.

The text and arrows in these graphics refer to the colors of the brackets/boxes, and NOT the colors of the segments beside people’s names. For example, if you look at the large black box at far right, you’ll see several people, with their matching segments identified by multiple colored bars. The different colored segments (bars) mean I’ve associated the match with different ancestors in multiple or various levels of generations.

Generation 3 – Great-grandparents

Within those maternal and paternal grandparent segments, more nested information is available.

The black Ferverda grandfather segments are further divided into black, from Hiram Ferverda, and gold from his wife Eva Miller. The same concept applies to the red grandmother segments which are now divided into red representing Nora Kirsch and purple representing Curtis Lore, her husband.

While I have only been able to assign the first four segments (at the top) to one person/ancestor, there’s an entire group of matches who share the grouping of segments at right, in gold, descended through Eva Miller. The Miller line is Brethren and Mennonite with lots of testers, so this is a common pattern in my DNA matches.

Eva Miller, the gold ancestor, has two parents, Margaret Elizabeth Lentz and John David Miller, so her segments would come from those two sides.

Generation 4 and 5 – Fuschia Segment

I was able to track the segment shown in fuschia indicated by the blue arrow to Jacob Lentz and his wife Fredericka Ruhle, German immigrant ancestors. Other people in this same match (triangulation) group descend from Margaret Elizabeth Lentz and John David Miller – but that fuschia match is the one that shows us where that segment originated. This allows us to assign that entire gold/blue bracketed set of segments to a specific ancestor or ancestral couple because they triangulate, meaning they all match me and each other.

Therefore, all of the segments that match with the fuschia segment also track back to Jacob Lentz and Fredericka Ruhle, or to their ancestors. We would need people who descend from Jacob’s parents and/or Fredericka’s parents to determine the origins of that segment.

In other words, we know all of these people share a common source of that segment, even if we don’t yet know exactly who that common ancestor was or when they lived. That’s what the process of tracking back discovers.

To be very clear, I received that segment through Jacob and Fredericka, but some of those matches who I have not been able to associate with either Jacob or Fredericka may descend from either Jacob or Fredericka’s ancestors, not Jacob and Fredericka themselves. Connecting the dots between Jacob/Fredericka and their ancestors may be enlightening as to the even older source of that segment.

Let’s take a look at nested segments on my pedigree chart.

Nested Pedigree

Click to enlarge.

You can see the progression of nesting on my pedigree chart, using the same colors for the brackets/boxes. The black Ferverda box at the grandparent level encompasses the entire paternal side of my mother’s ancestry, and the red includes her mother’s entire side. This is identical to the DNAPainter graphic, just expressed on my pedigree chart instead of my chromosome 20.

Then the black gets broken into smaller nested segments of black, gold and fuschia, while the red gets broken into red and purple.

If I had more matches that could be assigned to ancestors, I would have even more nested levels. Of course, if I was using all of my chromosomes, not just 20, I would be able to go back further as well.

You can see that as we move further back in time, the bracketed areas assigned to each color become smaller and smaller, as do the actual segments as viewed on my DNAPainter chromosomes.

Segments Get Progressively Smaller

You can see in the pedigree chart and segment painting above that the segments we inherit from specific ancestors divide over time. As we move further and further back in our tree, the segments inherited from any specific ancestor get smaller and smaller too.

Dr. Paul Maier in the MyOrigins 3.0 White Paper provides this informative graphic that shows the reduction in segments and the number of ancestors whose DNA we carry reaching back in time.

I refer to this as a porcupine chart.

Eventually, we inherit no segments from red ancestors, and the pieces of DNA that we inherit from the distant blue ancestors become so small and fragmented that they cannot be positively identified as coming from a specific ancestor when compared to and matched with other people. That’s why vendors don’t show small segment matches, although different vendors utilize different segment thresholds.

The debate about how small is too small continues, but the answer is not simply segment size alone. There is no one-size-fits-all answer.

As segments become smaller, the probability, or chances that we match another person by chance (IBC) increases. Proof that someone shares a specific ancestor, especially when dealing with increasingly smaller segments is a function of multiple factors, such as tree completeness for both people, shared matches, parental match confirmation, and more. I wrote about What Constitutes Proof, here.

In the Family Finder Matching White Paper, Dr. Maier provides this chart reflecting IBD (Identical By Descent) and IBC (Identical By Chance) segments and the associated false positivity rate. That means how likely you are to match someone on a segment of that size by chance and NOT because you both share the DNA from a common ancestor.

I wrote Concepts: Identical by Descent, State, Population and Chance to help you better understand how this works.

In the chart below, I’ve combined the generations, relationships, # of ancestors, assuming no duplicates, birth year range based on an approximate 30-year generation, percent of DNA assuming exactly half of each ancestor’s DNA descends in each generation (which we know isn’t exactly accurate), and the average amount of total inherited cMs using that same assumption.

Note that beginning with the 7th generation, on average, we can expect to inherit less than 1% of the DNA of an ancestor, or approximately 55 total cM which may be inherited in multiple segments.

The amount of actual cMs inherited in each generation can vary widely and explains why, beginning with third cousins, some people won’t share DNA from a common ancestor above the various vendor matching thresholds. Yet, other cousins several generations removed will match. Inheritance is random.

Parallel Inheritance

In order to match someone else descended from that 11th generation ancestor, BOTH you AND your match will need to have inherited the exact SAME DNA segment, across 11 generations EACH in order to match. This means that 11 transmission events for each person will need to have taken place in parallel with that identical segment being passed from parent to child in each line. For 22 rolls of the genetic dice in a row, the same segment gets selected to be passed on.

You can see why we all need to work to prove that distant matches are valid.

The further back in time we work, the more factors we must take into consideration, and the more confirming proof is needed that a match with another individual is a result of a shared ancestor.

Having said that, shared distant matches ARE the key to breaking through brick-wall ancestors. We just need to be sure we are chasing the real deal and not a red herring.

Exciting Possibilities

The most exciting possibility is that some segments are actually passed intact for several generations, meaning those segments don’t divide into segments too small for matching.

For example, the 22 cM fuschia segment that tracks through generations 4 and 5 to Jacob Lentz and Fredericka Ruhle has been passed either intact or nearly intact to all of those people who stack up and match each other and me on that segment. 22 cM is definitely NOT a small segment and we know that it descended from either Jacob or Fredericka, or perhaps combined segments from each. In any case, if someone from the Lentz line in Germany tested and matched me on that segment (and by inference, the rest of these people too), we would know that segment descended to me from Jacob Lentz – or at least the part we match on if we don’t match on the entire segment.

This is exactly what nested segments are…breadcrumbs to ancestors.

Part of that 22cM segment could be descended from Jacob and part from Fredericka. Then of Jacob’s portion, for example, pieces could descend from both his mother and father.

This is why we track individual segments back in time to discern their origin.

The Promise of the Future

The promise of the future is when a group of other people triangulate on a reasonably sized segment AND know where it came from. When we match that triangulation group, their identified segment may well help break down our brick walls because we match all of them on that same segment.

It is exactly this technique that has helped me identify a Womack segment on my paternal line. I still haven’t identified our common ancestor, but I have confirmed that the Womacks and my Moore/Rice family interacted as neighbors 8 generations ago and likely settled together in Amelia county, migrating from eastern Virginia. In time, perhaps I’ll be able to identify the common Womack ancestor and the link into either my Moore or Rice lines.

I’m hoping for a similar breakthrough on my mother’s side for Philip Jacob Miller’s wife, Magdalena, 7 generations back in my tree. We know Magdalena was Brethren and where they lived when they took up housekeeping. We don’t know who her parents were. However, there are thousands of Miller descendants, so it’s possible that eventually, we will be able to break down that brick wall by using nested segments – ours and people who descend from Magdalena’s siblings, aunts, and uncles.

Whoever those people were, at least some of their descendants will likely match me and/or my cousins on at least one nested Miller segment that will be the same segment identified to their ancestors.

Genealogy is a team sport and solving puzzles using nested segments requires that someone out there is working on identifying triangulated segments that track to their common ancestors – which will be my ancestors too. I have my fingers crossed that someone is working on that triangulation group and I find them or they find me. Of course, I’m working to triangulate and identify my segments to specific ancestors – hoping for a meeting in the middle – that much-desired bridge to the past.

By the time you’ve run out of other records, nested segments are your last chance to identify those elusive ancestors. 

Do you have genealogical brick walls that nested segments could solve?

__________________________________________________________

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2021 Favorite Articles

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8

It’s that time of the year again when we welcome the next year.

2021 was markedly different than anything that came before. (Is that ever an understatement!)

Maybe you had more time for genealogy and spent time researching!

So, what did we read in 2021? Which of my blog articles were the most popular?

In reverse order, beginning with number 10, we have:

This timeless article published in 2015 explains how to calculate the amount of any specific heritage you carry based on your ancestors.

Just something fun that’s like your regular pedigree chart, except color coded locations instead of ancestors. Here’s mine

The Autosegment Triangulation Cluster Tool is a brand new tool introduced in October 2021. Created by Genetic Affairs for GEDmatch, this tool combines autoclusters and triangulation.

Many people don’t realize that we actually don’t inherit exactly 25% of our DNA from each grandparent, nor why.

This enlightening article co-authored with statistician Philip Gammon explains how this works, and why it affects all of your matches.

Who doesn’t love learning about ancient DNA and the messages it conveys. Does your Y or mitochondrial DNA match any of these burials? Take a look. You might be surprised.

How can you tell if you are full or half siblings with another person? You might think this is a really straightforward question with an easy answer, but it isn’t. And trust me, if you EVER find yourself in a position of needing to know, you really need to know urgently.

Using simple match, it’s easy to figure how much of your ancestor’s DNA you “should” have, but that’s now how inheritance actually works. This article explains why and shows different inheritance scenarios.

That 28 day timer has expired, but the article can still be useful in terms of educating yourself. This should also be read in conjunction with Ancestry Retreats, by Judy Russell.

If I had a dollar for every time I’ve heard someone say that their ethnicity percentages were “wrong,” I’d be a rich woman, living in a villa in sun-drenched Tuscany😊

This extremely popular article has either been first or second every year since it was published. Ethnicity is both exciting and perplexing.

As genealogists, the first thing we need to do is to calculate what, according to our genealogy, we would expect those percentages to be. Of course, we also need to factor in the fact that we don’t inherit exactly the same amount of DNA from each grandparent. I explain how I calculated my “expected” percentages of ethnicity based on my known tree. That’s the best place to start.

Please note that I am no longer updating the vendor comparison charts in the article. Some vendors no longer release updates to the entire database at the same time, and some “tweak” results periodically without making an announcement. You’ll need to compare your own results at the different vendors at the same point in time to avoid comparing apples and oranges.

The #1 Article for 2021 is…

  1. Proving Native American Ancestry Using DNA

This article has either been first (7 times) or second (twice) for 9 years running. Now you know why I chose this topic for my new book, DNA for Native American Genealogy.

If you’re searching for your Native American ancestry, I’ve provided step-by-step instructions, both with and without some percentage of Native showing in your autosomal DNA percentages.

Make 2022 a Great Year!

Here’s wishing you the best in 2022. I hope your brick walls cave. What are you doing to help that along? Do you have a strategy in mind?

__________________________________________________________

Follow DNAexplain on Facebook, here or follow me on Twitter, here. You can also subscribe to receive emails when I publish articles by clicking the “Follow” button at www.DNAexplain.com.

You’re always welcome to forward articles or links to friends.

Help Out, Please

I receive a small contribution when you click on some of the links to vendors in my articles. This does NOT increase the price you pay but helps me to keep the lights on and this informational blog free for everyone. Please click on the links in the articles or to the vendors below if you are purchasing products or DNA testing.

Thank you so much.

DNA Purchases and Free Uploads

Genealogy Products and Services

My Book

Genealogy Books

Genealogy Research