FamilyTreeDNA Keynote, RootsTech Wrap + Special Show Pricing Still Available

Am I ever whipped. My two live Sessions that were actually a series of three classes each took place on Friday. Yes, that means I presented 6 sessions on Friday, complete with a couple of Zoom gremlins, of course. It’s the nature of the time we live in.

RootsTech tried something new that they’ve never done before. The Zoom class sessions were restricted to 500 attendees each. RootsTech was concerned about disappointed attendees when the room was full and they couldn’t get in, so we live-streamed three of my sessions to Facebook in addition to the 500 Zoom seats.

As of this evening, 6,800 of you have viewed the Facebook video, “Associating Autosomal DNA Segments With Ancestors.” I’m stunned, and touched. Thank you, thank you. Here’s the Facebook link, and here’s the RootsTech YouTube link.

My afternoon sessions, “What Can I DO With Ancestral DNA Segments?” can be viewed here at RootsTech or here on YouTube.

I must admit, I’m really, REALLY looking forward to being together again because RootsTech without the socializing and in-person Expo Hall just isn’t the same. Still, be sure to take a virtual walk through the Expo Hall, here. There’s lots of content in the vendors” booths and it will remain available for all of 2022, until the beginning of RootsTech 2023..

Between prep for my classes and presenting, I didn’t have a lot of time to watch other sessions, but I was able to catch the FamilyTreeDNA keynote and their 2022 Product Sneak Peek. Both were quite worthwhile.

However, I just realized that FamilyTreeDNA’s special show pricing promo codes are still valid for the next two days.

 Special Prices Are Still Available

Every single test that FamilyTreeDNA offers, including UPGRADES, is on sale right now by using special RootsTech promo codes. These prices are good for two more days, through March 7th, so if you want to purchase a Y DNA test, mitochondrial, or Family Finder autosomal test, or upgrade, click here to see the prices only available at RootsTech (and to you through my blog.) It’s not too late, but it will be soon.

To order, click here to sign on or place your order.

FamilyTreeDNA’s Keynote

FamilyTreeDNA’s keynote was titled FamilyTreeDNA: 22 Years of Breaking Down Brick Walls.

I really enjoyed this session, in part because I’ve been a part of the genetic genealogy revolution and evolution from the beginning. Not only that, but I know every single person they interviewed for this video, and have for years. If you’ve been participating in genetic genealogy for some time, you’ll know many of these people too. For a minute, it was almost as good as visiting in person.

I’m going to share a few highlights from the session, but I’m also going to include information NOT in the video. I was one of the early project administrators, so I’ve been along for the ride for just a few months shy of 22 years.

FamilyTreeDNA was the first US company to enter the DNA testing space, the first to offer Y DNA testing, and the only one of the early companies that remains viable today. FamilyTreeDNA was the result of Bennett Greenspan’s dream – but initially, he was only dreaming small. Just like any other genealogist – he was dreaming about breaking down a brick wall which he explains in the video.

I’m so VERY grateful that Bennett had that dream, and persisted, because it means that now millions of us can do the same – and will into the future.

Bennett tells this better than anyone else, along with his partner, Max Blankfeld.

“Some people were fascinated,” Bennett said.

Yep, that’s for sure! I certainly was.

“Among the first genetic genealogists in the world.”

“Frontier of the genetic genealogy revolution.”

Indeed, we were and still are. Today’s genetic genealogy industry wouldn’t even exist were it not for FamilyTreeDNA and their early testers.

I love Max Blankfeld’s story of their first office, and you will too.

This IS the quintessential story of entrepreneurship.

In 2004, when FamilyTreeDNA was only four years old, they hosted the very first annual international project administrator’s conference. At that time, it was believed that the only people that would be interested in learning at that level and would attend a DNA conference would be project administrators who were managing surname and regional projects. How times have changed! This week at RootsTech, we probably had more people viewing DNA sessions than people that had tested altogether in 2004. I purchased kit number 30,087 on December 28, 2004, and kit 50,000 a year later on New Year’s Eve right at midnight!

In April 2005, Nat Geo partnered with FamilyTreeDNA and founded the Genographic Project which was scheduled to last for 5 years. They were hoping to attract 100,000 people who would be willing to test their DNA to discover their roots – and along with that – our human roots. The Genographic Project would run for an incredible 15 years.

In 2005 when the second Project Administrator’s conference was held at the National Geographic Society headquarters in Washington DC, I don’t think any of us realized the historic nature of the moment we were participating in.

I remember walking from my hotel, ironically named “Helix,” to that iconic building. I had spent my childhood reading those yellow magazines at school and dreaming of far-away places. As an adult, I had been a life-long subscriber. Never, in my wildest dreams did I imagine ever visiting Nat Geo and walking the marble Explorer’s Hall with the portraits of the founders and early explorers hanging above and keeping a watchful eye on us. We would not disappoint them.

That 100,000 participation goal was quickly reached, within weeks, and surpassed, leading us all to walk the road towards the building that housed the Explorer’s Hall, Explorers’ in Residence, and so much more.

We were all explorers, pioneers, adventurers seeking to use the DNA from our ancestors in the past to identify who they were. Using futuristic technology tools like a mirror to look backward into the dim recesses of the past.

The archaeology being unearthed and studied was no longer at the ends of the earth but within our own bodies. The final frontier. Reaching out to explore meant reaching inward, and backward in time, using the most progressive technology of the day.

Most of the administrators in attendance, all volunteers, were on a first-name basis with each other and also with Max, Bennett, and the scientists.

Here, Bennett with a member of the science team from the University of Arizona describes future research goals. Every year FamilyTreeDNA has improved its products in numerous ways.

Today, that small startup business has its own ground-breaking state-of-the-art lab. More than 10,000 DNA projects are still administered by passionate volunteer administrators who focus on what they seek – such as the history of their surname or a specific haplogroup. Their world-class lab allows FamilyTreeDNA to focus on research and science in addition to DNA processing. The lab allows constant improvement so their three types of genetic genealogy products, Y, mitochondrial and autosomal DNA.

Those three types of tests combine to provide genealogical insights and solutions. The more the science improves, the more solutions can and will be found.

If you watch the video, you’ll see 6 people who have solved particularly difficult and thorny problems. We are all long-time project administrators, all participate on a daily basis in this field and community – and all have an undying love for both genealogy and genetic genealogy.

You’ll recognize most of these people, including yours truly.

  • I talk about my mother’s heritage, unveiled through mitochondrial DNA.
  • Rob Warthen speaks about receiving a random phone call from another genealogist as his introduction to genetic genealogy. Later, he purchased a DNA test for his girlfriend, an adoptee, for Christmas and sweetened the deal by offering to “go where you’re from” for vacation. He didn’t realize why she was moved to tears – that test revealed the first piece of information she had ever known about her history. DNA changed her and Rob’s life. He eventually identified her birth parents – and went on to found both DNAAdoption.org and DNAGedcom.
  • Richard Hill was adopted and began his search in his 30s, but it would be DNA that ended his search. His moving story is told in his book, Finding Family: My Search for Roots and the Secrets in My DNA.
  • Mags Gaulden, professional genealogist and founder of Grandma’s Genes and MitoYDNA.org tells about her 91-year-old adopted client who had given up all hope of discovering her roots. Back in the 1950s, there was literally nothing in her client’s adoption file. She was reconciled to the fact that “I would never know who I was.” Mags simply could not accept that and 2 years later, Mags found her parents’ names.

  • Lara Diamond’s family was decimated during the holocaust. Lara’s family thought everyone in her grandfather’s family had been killed, but in 2013, autosomal DNA testing let her to her grandfather’s aunt who was not killed in the holocaust as everyone thought. The aunt and first cousin were living in Detroit. Lara went from almost no family to a family reunion, shown above. She says she finally met “people who look like me.”
  • Katherine Borges founded ISOGG.org, the International Society of Genetic Genealogy in 2005, following the first genetic genealogy conference in late 2004 where she realized that the genealogy community desperately needed education – beginning with DNA terms. I remember her jokingly standing in the hallway saying that she understood three words, “a, and and the.” While that’s cute today, it was real at that time because DNA was a foreign language, technology, and concept to genealogy. In fact, for years we were banned from discussing the topic on RootsWeb. The consummate genetic genealogist, Katherine carries DNA kits in her purse, even to Scotland!

Bennett says that he’s excited about the future, for the next generation of molecular scientific achievements. It was Bennett that greenlit the Million Mito project. Bennett’s challenge as a genetic genealogy/business owner was to advance the science that led to products while making enough money to be able to continue advancing the science. It was a fine line, but Max and Bennett navigated those waters quite well.

Apparently, Max, Bennett, and the FamilyTreeDNA customers weren’t the only people who believe that.

In January 2021, myDNA acquired and merged with FamilyTreeDNA. Max and Bennett remain involved as board members.

Dr.Lior Rauchberger, CEO of myDNA which includes FamilyTreeDNA

Dr. Lior Rauchberger, the CEO of the merged enterprise believes in the power of genetics, including genetic genealogy, and is continuing to make investments in FamilyTreeDNA products – including new features. There have already been improvements in 2021 and in the presentation by Katy Rowe, the Product Manager for the FamilyTreeDNA products, she explains what is coming this year.

I hope you enjoyed this retrospective on the past 22 years and are looking forward to crossing new frontiers, and breaking down those brick walls, in the coming decades.

Sneak Peek at FamilyTreeDNA – New Features and Upcoming Releases

You can watch Katy Rowe’s Sneak Peek video about what’s coming, here.

Of course, while other companies need to split their focus between traditional genealogy research records and DNA, FamilyTreeDNA does not. Their only focus is genetics. They plan to make advances in every aspect of their products.

FamilyTreeDNA announced a new Help Center which you can access, here. I found lots of short videos and other helpful items. I had no idea it existed.

In 2021, customers began being able to order a combined Family Finder and myDNA test to provide insights into genealogy along with health and wellness

Wellness includes nutrition and fitness insights.

Existing customers either are or will be able to order the myDNA upgrade to their existing test. The ability to upgrade is being rolled out by groups. I haven’t had my turn yet, but when I do, I’ll test and let you know what I think. Trust me, I’m not terribly interested in how many squats I can do anymore, because I already know that number is zero, but I am very interested in nutrition and diet. I’d like to stay healthy enough to research my ancestors for a long time to come.

FamilyTreeDNA announced that over 72,000 men have taken the Big Y test which has resulted in the Y DNA tree of mankind surpassing 50,000 branches.

This is utterly amazing when you consider how far we’ve come since 2002. This also means that a very high number of men, paired with at least one other man, actually form a new branch on the Y haplotree.

The “age” of tester’s Y DNA haplogroups is now often within the 500-year range – clearly genealogical in nature. Furthermore, many leaf-tip haplogroups as defined by the Big Y SNPs are much closer than that and can differentiate between branches of a known family. The Big Y-700 is now the go-to test for Y DNA and genealogy.

Of course, all these new branches necessitate new maps and haplogroup information. These will be released shortly and will provide users with the ability to see the paths together, which is the view you see here, or track individual lines. The same is true for mitochondrial DNA as well.

Y DNA tree branch ages will be forthcoming soon too. I think this is the #1 most requested feature.

On the Mitochondrial DNA side of the house, the Million Mito project has led to a significant rewrite of the MitoTree. As you know, I’m a Million Mito team member.

Here’s Dr. Paul Maier’s branch, for example. You can see that in the current version of the Phylotree, there is one blue branch and lots of “child” branches beneath that. Of course, when we’re measuring the tree from “Eve,” the end tip leaf branches look small, but it’s there that our genealogy resides.

In the new version, yet to be released, there is much more granularity in the branches of U5a2b2a.

To put this another way, in today’s tree, haplogroup U5a2b2a is about 5,000 years old, but the newly defined branches bring the formation of Paul’s (new) haplogroup into the range of about 500 years. Similar in nature to the Y DNA tree and significantly more useful for genealogical purposes. If you have not taken a mitochondrial DNA full sequence test, please order one now. Maybe your DNA will help define a new branch on the tree plus reveal new information about your genealogy.

Stay tuned on this one. You know the Million Mito Project is near and dear to my heart.

2022 will also see much-needed improvements in the tree structure and user experience, as well as the matches pages.

There are a lot of exciting things on FamilyTreeDNA’s plate and I’m excited to see these new features and functions roll out over the next few months.

Just the Beginning

The three days of RootsTech 2022 may be over, but the content isn’t.

In fact, it’s just the beginning of being able to access valuable information at your convenience. The vendor booths will remain in the Expo Hall until RootsTech 2023, so for a full year, plus the individual instructor’s sessions will remain available for three years.

In a few days, after I take a break, I’ll publish a full list of DNA sessions, along with links for your convenience.

Thank You Shout Outs

I want to say a HUGE thank you to RootsTech for hosting the conference and making it free. I specifically want to express my gratitude to the many, many people working diligently behind the scenes during the last year, and frantically during the past three days.

Another huge thank you to the speakers and vendors whose efforts provide the content for the conference.

And special thanks to you for loving genealogy, taking your time to watch and learn, and for reading this blog.

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AutoKinship at GEDmatch by Genetic Affairs

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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Genealogy Research

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

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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What Article Topics Would You Like in 2022?

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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Share the Love!

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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Identify Your Ancestors – Follow Nested Ancestral Segments

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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Register for RootsTech 2022 Now – It’s Free!

Just the good news we need to end the year. RootsTech 2022, sponsored by FamilySearch, is entirely virtual and completely free – again.

In 2021, over a million people “attended” RootsTech and you can be one of those lucky people in March 2022 too.

In 2022, there will be more than 1500 sessions presented by hundreds of speakers from around the globe in many languages. Of course, that’s in addition to the vendor Expo booths, which I love, and the DNA Basics Learning Center.

The 2022 sessions and speakers aren’t listed yet, but this would be a good time to view any of the 2021 sessions that you never got a chance to. What better thing could you be doing for New Year’s Eve😊

Sign Up!

You can sign up for RootsTech 2022 here, for free.

I’ll let you know as soon as the 2022 sessions are added. The sessions showing are the 2021 classes which RootsTech has graciously made available for the entire year. I don’t know how long they will be viewable, so if you want to watch, please do so now.

As you might imagine, the 2022 speakers are busily (should I say crazily) designing and recording their content. You’ll be seeing me in both recorded sessions (about my new book, DNA for Native American Genealogy,) sharing success-story testimonials, and in several live sessions too.

Yes, some sessions will be live this time and the live sessions will be recorded for later playback. I like to interact with people, so I’ve decided to cross my fingers that the internet gremlins don’t visit me those days! I have seven exciting sessions under construction.

Be sure to test your Y, mitochondrial and autosomal DNA and upload your autosomal DNA to multiple locations in advance so you are prepared to benefit from all of the DNA track presentations and a multitude of wonderful speakers. There’s still time today and tomorrow to take advantage of end-of-the year sales.

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Thank you so much.

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Y DNA Tree of Mankind Reaches 50,000 Branches

Today is a really, REALLY big day in the genetic genealogy world.

The Y DNA tree of mankind at FamilyTreeDNA has reached 50,000 branches. That’s quite a milestone!

There’s been remarkably rapid growth in the past three years, as shown below.

From the FamilyTreeDNA blog article announcing this milestone event, we see the growth from 2018 to present cumulatively and within each haplogroup. Of course, haplogroup R, present in very high frequencies in Europe, forms the base of this mountain, but every haplogroup has achieved significant gains – which benefits all testers.

Who is Branch 50,000?

Michael Sager, the phylogeneticist at FamilyTreeDNA just added branch 50,000.

Drum roll please! Who is it? Surprisingly, it’s NOT found in haplogroup R, but a man from Vanuatu, a country in Oceania.

The new branch is a member of haplogroup S – specifically S-FTC416, immediately downstream of S-P315. Haplogroup S is found in Indonesia, Micronesia and other Pacific Island nations, including Australia and New Zealand.

This man was a new customer who joins a couple of Aboriginal samples found in academic papers from Kuranda (Queensland, Australia) and 3 ancient samples from Vanuatu.

How cool is that!!!

We’ve Come a LONG Way!

The Y DNA phylogenetic tree has been growing like wildfire.

  • Back in 2002, there were 153 branches on the Y-DNA tree, and a total of 243 known SNPs. (Some SNPs were either duplicates or not yet placed on the tree which explains the difference.)
  • In 2008, six years later, the tree had doubled to 311 branches and 600 SNPs. At the FamilyTreeDNA International Conference that year, attendees received this poster. I remember the project administrators marveling about how large the tree had grown.
  • In 2010, two years later, the tree was comprised of 440 branches and 800 SNPs. That poster was even larger, and it was the last year that the phylotree would fit onto a poster.
  • By 2012, when the Genographic Project V2 was announced, that bombshell announcement included information that the Genographic project was testing for 12,000 SNP locations on their chip, not all of which had been classified.
  • In 2014, when FamilyTreeDNA and Genographic jointly released their new Y tree to celebrate DNA Day, the Y tree had grown to more than 6200 SNPS, of which, more than 1200 were end-of-branch terminal SNPs. If this had been a poster, it would have been more than 62 feet long.

From that point on, the trajectory was unstoppable.

The earliest SNP-seeking product called Walk the Y had been introduced followed by the first-generation powerful Big Y NGS DNA scanning product.

That’s 1300% growth, or said another way, the database increased by 13 times in four years.

In the three years since, many of those SNPs, plus private variants that had not yet been named at that point have been added to the tree.

In January 2019, the Big Y-700 was announced and many people upgraded. The Big Y-700 provided dramatically increased resolution, meaning that test could find more mutations or SNPs. The effect of this granularity is that the Big Y-700 is discovering mutations and new SNPs in a genealogical timeframe, where the original haplogroups a few years ago could only piece together deeper ancestry.

The Big Y-700 has made a HUGE difference for genealogists.

  • Today, in December of 2021, the tree hit 50,000 branches. That poster would be more than 500 feet long, almost twice the length of a football field.

I have to wonder how many more branches are out there just waiting to be found? How many will we find in the next year? Or the next?

The pace doesn’t show any signs of slowing down, that’s for sure. Adding academic and ancient samples to the tree helps a great deal in terms of adding context to our knowledge.

What gems does your family’s Y DNA hold?

How Does a SNP or Variant Get Added to the Tree?

You might be wondering how all of this happens.

A SNP, which becomes a haplogroup has three states of “being,” following discovery.

  1. When the mutation, termed a SNP (single nucleotide polymorphism), pronounced “snip” is found in the first male, it’s simply called a variant. In other words, it varies from the nucleotide that is normally found in that position in that one man.
  2. When the SNP is found in multiple men, assuming it’s found consistently in multiple scans, and it’s in an area that is “clean” and not genetically “noisy,” then the SNP is given a name like R-ZS3700 or R-BY154784, and the SNP is placed on the tree in its correct position. From my article last week about using Y DNA STR and SNP markers for genealogy, you can see that both of those haplogroups have multiple men who have been found with those mutations.
  3. Some SNPs are equivalent SNPs. For example, in the image below, the SNP FT702 today is equivalent to R-ZS3700, meaning it’s found in the same men that carry R-ZS3700. Eventually, many equivalent SNPs form a separate tree branch.

One day, some man may test that does have R-ZS3700 but does NOT have FT702, which means that a new branch will be formed.

When men tested that had R-BY154784, that new branch was added to the left of R-ZS3700, because not all men with R-ZS3700 have the mutation R-BY154784.

You’ll notice that the teal blocks indicate the number of private variants which are mutations that have not yet been found in other men in this same branch structure, and those variants are therefore not yet named SNPs.

If You’ve Already Tested, How Do You Receive a New Haplogroup?

It’s worth noting here that none of the terminal SNPs that define these branches were available using the older Big Y tests which illustrates clearly why it’s important to upgrade from the Big Y or Big Y-500 to the Big Y-700.

In my Estes line, the terminal SNP in the Big Y-500 was R-BY490. These same men upgraded to the Big Y-700 and have now been assigned to four different, distinct, genealogically significant lineages based on SNPs discovered after they upgraded. Some men have three new SNPs that weren’t available in earlier tests. In real terms, that’s the difference between the common ancestor born in 1495 and descendants of John R. Estes who died in the 1880s. Genealogically speaking, that’s night and day.

If you haven’t taken a Big Y test, I heartily recommend it – even if you don’t have STR matches. I talked about why, here. Men can purchase the Big Y initially, or sign on to your account and upgrade if you’ve already taken another test.

In a nutshell, the Big Y-700 test provides testers with two types of tools that work both together and separately to provide genealogically relevant information.

Not to mention – you may be responsible for growing the tree of mankind, one branch at a time. What’s waiting for you?

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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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Black Friday Starts Now – MyHeritage DNA Only $39!

MyHeritage has dropped the price of DNA tests to $39 for their Black Friday Sale.

I’ve never previously seen DNA kits prices this low. You can purchase, here.

DNA Plus More

The great thing about DNA at MyHeritage is that you receive emails like this one I received yesterday telling me that my DNA match, Fred, is my 4th cousin once removed!

Note that Fred is just one of 88 of my DNA matches that have Theories of Family Relativity, showing how I may be related to that match. That’s an incredible benefit.

Sure enough, when I click on “View Theory,” I see that Fred and I share ancestors Francoise Lafaille and Marguerite de Forest.

Click to enlarge image

MyHeritage can provide Theories to their customers when the customer has BOTH taken a DNA test AND uploaded or created a tree. I’ve provided some tips on how you can receive more Theories of Family Relativity, here.

If you haven’t yet tested your DNA at MyHeritage, there has never been a better time. You can click here to order tests for yourself and other family members. Free shipping on two or more kits, too.

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DNA for Native American Genealogy – Hot Off the Press!

Drum roll please…my new book, DNA for Native American Genealogy, was just released today, published by Genealogical.com.

I’m so excited! I expected publication around the holidays. What a pleasant surprise.

This 190-page book has been a labor of love, almost a year in the making. There’s a lot.

  • Vendor Tools – The book incorporates information about how to make the best use of the autosomal DNA tools offered by all 4 of the major testing vendors; FamilyTreeDNA, MyHeritage, Ancestry, and 23andMe.
  • Chromosome Painting – I’ve detailed how to use DNAPainter to identify which ancestor(s) your Native heritage descends from by painting your population/ethnicity segments provided by FamilyTreeDNA and 23andMe.
  • Y and Mitochondrial DNA – I’ve described how and when to utilize the important Y and mitochondrial DNA tests, for you and other family members.
  • Maps – Everyone wants to know about ancient DNA. I’ve included ancient DNA information complete with maps of ancient DNA sites by major Native haplogroups, gathered from many academic papers, as well as mapped contemporary DNA locations.
  • Haplogroups – Locations in the Americas, by haplogroup, where individual haplogroups and subgroups are found. Some haplogroups are regional in nature. If you happen to have one of these haplogroups, that’s a BIG HINT about where your ancestor lived.
  • Tribes – Want to know, by tribe, which haplogroups have been identified? Got you covered there too.
  • Checklist – I’ve provided a checklist type of roadmap for you to follow, along with an extensive glossary.
  • Questions – I’ve answered lots of frequently asked questions. For example – what about joining a tribe? I’ve explained how tribes work in the US and Canada, complete with links for relevant forms and further information.

But wait, there’s more…

New Revelations!!!

There is scientific evidence suggesting that two haplogroups not previously identified as Native are actually found in very low frequencies in the Native population. Not only do I describe these haplogroups, but I provide their locations on a map.

I hope other people will test and come forward with similar results in these same haplogroups to further solidify this finding.

It’s important to understand the criteria required for including these haplogroups as (potentially) Native. In general, they:

  • Must be found multiple times outside of a family group
  • Must be unexplained by any other scenario
  • Must be well-documented both genetically as well as using traditional genealogical records
  • Must be otherwise absent in the surrounding populations

This part of the research for the book was absolutely fascinating to me.

Description

Here’s the book description at Genealogical.com:

DNA for Native American Genealogy is the first book to offer detailed information and advice specifically aimed at family historians interested in fleshing out their Native American family tree through DNA testing.

Figuring out how to incorporate DNA testing into your Native American genealogy research can be difficult and daunting. What types of DNA tests are available, and which vendors offer them? What other tools are available? How is Native American DNA determined or recognized in your DNA? What information about your Native American ancestors can DNA testing uncover? This book addresses those questions and much more.

Included are step-by-step instructions, with illustrations, on how to use DNA testing at the four major DNA testing companies to further your genealogy and confirm or identify your Native American ancestors. Among the many other topics covered are the following:

    • Tribes in the United States and First Nations in Canada
    • Ethnicity
    • Chromosome painting
    • Population Genetics and how ethnicity is assigned
    • Genetic groups and communities
    • Y DNA paternal direct line male testing for you and your family members
    • Mitochondrial DNA maternal direct line testing for you and your family members
    • Autosomal DNA matching and ethnicity comparisons
    • Creating a DNA pedigree chart
    • Native American haplogroups, by region and tribe
    • Ancient and contemporary Native American DNA

Special features include numerous charts and maps; a roadmap and checklist giving you clear instructions on how to proceed; and a glossary to help you decipher the technical language associated with DNA testing.

Purchase the Book and Participate

I’ve included answers to questions that I’ve received repeatedly for many years about Native American heritage and DNA. Why Native DNA might show in your DNA, why it might not – along with alternate ways to seek that information.

You can order DNA for Native American Genealogy, here.

For customers in Canada and outside the US, you can use the Amazon link, here, to reduce the high shipping/customs costs.

I hope you’ll use the information in the book to determine the appropriate tests for your situation and fully utilize the tools available to genealogists today to either confirm those family rumors, put them to rest – or maybe discover a previously unknown Native ancestor.

Please feel free to share this article with anyone who might be interested.

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Disclosure

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

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Sitting Bull’s Hair Confirms Relationship With Great-Grandson

Tȟatȟáŋka Íyotake, known as the legendary Lakota warrior and leader, Sitting Bull, was born about 1831 and was killed in 1890. You’ll probably remember him for his victory over Custer and his troops in 1876 at the Battle of Little Big Horn, known as the Battle of Greasy Grass to the Native people and as Custer’s Last Stand colloquially.

By Orlando Scott Goff – Heritage Auctions, Public Domain, https://commons.wikimedia.org/w/index.php?curid=27530348

Pictured here, Sitting Bull was photographed in 1881.

After Sitting Bull’s murder, his scalp lock, a braided length of hair used to hold his feather in place was cut from his body as a souvenir of the grizzly event. In 1896, the scalp lock along with his leggings were donated to and held by the Smithsonian Museum for more than a century before being returned to his family in 2007. Sitting Bull’s great-grandson, Ernie LaPointe, now in his 70s, along with his three sisters are Sitting Bull’s closest living relatives.

The family needed to unquestionably prove a familial connection to be allowed to make decisions about Sitting Bull’s gravesite and remains. Genetic analysis was employed to augment traditional genealogical records. According to Ernie, “over the years, many people have tried to question the relationship that I and my sisters have to Sitting Bull.”

After the return of Sitting Bull’s scalp lock to Ernie LaPointe, Professor Eske Willerslev, one of the pioneers in ancient DNA, contacted Ernie and offered to assist the family by analyzing the hair sample.

By Von Bern – Sitting Bull family portrait, Public Domain, https://commons.wikimedia.org/w/index.php?curid=49894969

Original text from the back of the above image:

“4 generations of Sitting Bull: Sitting Bull, two wives, their daughter, her daughter, her baby” “Copy from Mrs. Edward M. Johnson collection Spiritwood, N. Dak.” Sitting Bull and family 1882 at Ft Randall rear L-R Good Feather Woman (sister), Walks Looking (daughter) front L-R Her Holy Door (mother), Sitting Bull, Many Horses (daughter) with her son, Courting a Woman

LaPointe and his sisters descend from Sitting Bull through their mother, through one of Sitting Bull’s three daughters, so neither Y nor mitochondrial DNA were options to prove that they were the great-grandchildren of Sitting Bull. Generally, neither Y nor mitochondrial DNA establish exact recent relationships, but confirm or disprove lineage relationships.

DNA From Sitting Bull’s Hair

In 2007, obtaining autosomal DNA from hair was virtually impossible, even from contemporary hair, let alone hair that’s more than a century old. However, today, the technology involved has improved. Additionally, it’s also possible that some of the DNA from Sitting Bull’s skin or skin flakes were held within the scalp lock itself.

The fact that the hair had been treated with arsenic for preservation while in the possession of the Smithsonian made DNA analysis even more difficult. Unlike traditional contemporary DNA tests, a full autosomal sequence was not able to be obtained. Small fragments of autosomal DNA from the braid were able to be pieced together well enough to compare to Ernie LaPointe and other Lakota people, showing that Ernie and his family match Sitting Bull’s hair more closely than other Lakota.

The academic paper published by Willerslev, with other researchers and authors including LaPointe provides the following abstract:

Only a small portion of the braid was utilized for the analysis. The rest was burned in a spiritual ceremony. You can read the scientific paper, here.

This analysis of Sitting Bull’s hair opens the door for the remains in the two potential burial sites to be evaluated to see if they match the DNA retrieved from the scalp lock – enabling the family to rebury Sitting Bull in a location of their choice.

You can read additional coverage, here, here, here, and here.

Establishing a Relationship

Sitting Bull’s DNA is considered ancient DNA because it’s not contemporary, and it was degraded. But the definition of ancient needs to be put in context.

Sitting Bull’s “ancient DNA” is not the same thing as “ancient DNA” from thousands of years ago. In part, because we know positively that the DNA from thousands of years ago will not match anyone genealogically today – although it may match people at a population level (or by chance) with small fragments of DNA. We know the identity of Sitting Bull, who, on the other hand, would be expected to match close family members and other more distantly related members of the tribe.

Ernie and his sisters are great-grandchildren of Sitting Bull, so they would be expected to share about 887 cM of DNA in total, ranging from 485 cM to 1486 cM.

In an endogamous population, one could be expected to share even more total DNA, but that additional DNA would likely be in smaller fragments, not contiguous segments.

Great-Grandchildren Matches

For example, two great-grandchildren match their great-grandmother on 902 cM and 751 cM of DNA, respectively, with a longest contiguous block of 130 cM and 72 cM.

Another pair matches a great-grandfather at 1051 cM and 970 cM, with longest blocks of 220 cM and 141 cM.

A person would be expected to share about 12.5% of their autosomal DNA with a given great-grandparent. I wrote about how much we can expect to inherit, on average, from any ancestor, here.

In terms of the types of DNA matches that we are used to for genealogy, a great-grandparent would be one of our closest matches. Other relationships that could share about the same amount of DNA include a great-aunt/uncle/niece or nephew, a half-aunt/uncle/niece or nephew, a first cousin, half first cousin, first cousin once removed, or a great-grandchild.

Courtesy of DNAPainter

Since Sitting Bull’s DNA was extracted from hair, and we know unquestionably where that hair had been since 1896 when it was donated to the Smithsonian, we can eliminate some of those relationships. Furthermore, the genetic analysis supports the genealogical records.

What About Hair, DNA, and Your Genealogy?

I’m sure you’re wondering how this applies to you and your genealogy.

Like so many other people, I have a hair WITH a follicle belonging to my father and letters written by my paternal grandfather in envelopes that I hope he licked to seal. I tried several years ago, at different times, unsuccessfully. to have both of their DNA extracted to use for genealogy. Not only were the endeavors unsuccessful, but those attempts were also VERY expensive.

IT’S NOT SOUP YET!

I know how desperately we want to utilize those items for our genealogy, but the technology still is not ripe yet. Not then and not now. At least, not for regular consumers.

Remember that this extraction took a very specialized ancient DNA lab and many highly skilled individuals. It also took a total of 14 years. The DNA obtained was highly fragmented and had to be reassembled, with lots of pieces still missing. Then it had to be compared to currently living individuals. The ancient DNA autosomal file, like other autosomal forensic files, would NOT pass quality control at any of the DNA processing companies today, where the required QA pass rate is in the ballpark of 98%.

This type of ancient DNA extraction has only been successfully done using autosomal DNA once before, in 2015 on the remains of someone who died in 1916. While Y and mitochondrial DNA has been used to rule out, or *not* rule out direct patrilineal or matrilineal relationships in other burials, highly degraded autosomal DNA is much more difficult to utilize to establish relationships. The relationships must be close in nature so that enough of the genome can be reconstructed to infer a close familial relationship

I realize that more than one company has entered this space over the past several years, and you might also notice that they have either exited said space or are have not achieved any measure of reproducible success. Do NOT chance a valuable irreplaceable sample to any company just yet. This type of processing is not a standard offering – but ongoing research opens the door for more improvement in the future. I still have my fingers crossed.

If you are interested in preserving your items, such as hair, teeth, hairbrushes, electric razors, etc. for future analysis, be sure to keep them in paper, preferably acid-free (archival) paper, NOT plastic, and in a relatively temperature-controlled environment. By that, I mean NOT in the attic and NOT in a humid basement. Someplace in the house, comfortable for regular humans, and not sealed in a ziplock baggie. Don’t touch or handle them either.

Test Older Relatives NOW!

If you can test your oldest relatives, do it now. Grandparents, great-grandparents, aunts, uncles, great-aunts/uncles. All of your oldest family members. Don’t wait.

FamilyTreeDNA performs the test you order and is the only DNA testing company that archives the DNA sample for 25 years. The remaining DNA is available to order upgrades or new products as technology advances.

That’s exactly how and why some younger people have great-grandparent DNA available for matching today, even if their great-grandparents have walked on to the other side and joined Sitting Bull.

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