Y DNA: Step-by-Step Big Y Analysis

Many males take the Big Y-700 test offered by FamilyTreeDNA, so named because testers receive the most granular haplogroup SNP results in addition to 700+ included STR marker results. If you’re not familiar with those terms, you might enjoy the article, STRs vs SNPs, Multiple DNA Personalities.

The Big Y test gives testers the best of both, along with contributing to the building of the Y phylotree. You can read about the additions to the Y tree via the Big Y, plus how it helped my own Estes project, here.

Some men order this test of their own volition, some at the request of a family member, and some in response to project administrators who are studying a specific topic – like a particular surname.

The Big Y-700 test is the most complete Y DNA test offered, testing millions of locations on the Y chromosome to reveal mutations, some unique and never before discovered, many of which are useful to genealogists. The Big Y-700 includes the traditional Y DNA STR marker testing along with SNP results that define haplogroups. Translated, both types of test results are compared to other men for genealogy, which is the primary goal of DNA testing.

Being a female, I often recruit males in my family surname lines and sponsor testing. My McNiel line, historic haplogroup R-M222, has been particularly frustrating both genealogically as well as genetically after hitting a brick wall in the 1700s. My McNeill cousin agreed to take a Big Y test, and this analysis walks through the process of understanding what those results are revealing.

After my McNeill cousin’s Big Y results came back from the lab, I spent a significant amount of time turning over every leaf to extract as much information as possible, both from the Big Y-700 DNA test itself and as part of a broader set of intertwined genetic information and genealogical evidence.

I invite you along on this journey as I explain the questions we hoped to answer and then evaluate Big Y DNA results along with other information to shed light on those quandaries.

I will warn you, this article is long because it’s a step-by-step instruction manual for you to follow when interpreting your own Big Y results. I’d suggest you simply read this article the first time to get a feel for the landscape, before working through the process with your own results. There’s so much available that most people leave laying on the table because they don’t understand how to extract the full potential of these test results.

If you’d like to read more about the Big Y-700 test, the FamilyTreeDNA white paper is here, and I wrote about the Big Y-700 when it was introduced, here.

You can read an overview of Y DNA, here, and Y DNA: The Dictionary of DNA, here.

Ok, get yourself a cuppa joe, settle in, and let’s go!

George and Thomas McNiel – Who Were They?

George and Thomas McNiel appear together in Spotsylvania County, Virginia records. Y DNA results, in combination with early records, suggest that these two men were brothers.

I wrote about discovering that Thomas McNeil’s descendant had taken a Y DNA test and matched George’s descendants, here, and about my ancestor George McNiel, here.

McNiel family history in Wilkes County, NC, recorded in a letter written in 1898 by George McNiel’s grandson tells us that George McNiel, born about 1720, came from Scotland with his two brothers, John and Thomas. Elsewhere, it was reported that the McNiel brothers sailed from Glasgow, Scotland and that George had been educated at the University of Edinburgh for the Presbyterian ministry but had a change of religious conviction during the voyage. As a result, a theological tiff developed that split the brothers.

George, eventually, if not immediately, became a Baptist preacher. His origins remain uncertain.

The brothers reportedly arrived about 1750 in Maryland, although I have no confirmation. By 1754, Thomas McNeil appeared in the Spotsylvania County, VA records with a male being apprenticed to him as a tailor. In 1757, in Spotsylvania County, the first record of George McNeil showed James Pey being apprenticed to learn the occupation of tailor.

If George and Thomas were indeed tailors, that’s not generally a country occupation and would imply that they both apprenticed as such when they were growing up, wherever that was.

Thomas McNeil is recorded in one Spotsylvania deed as being from King and Queen County, VA. If this is the case, and George and Thomas McNiel lived in King and Queen, at least for a time, this would explain the lack of early records, as King and Queen is a thrice-burned county. If there was a third brother, John, I find no record of him.

My now-deceased cousin, George McNiel, initially tested for the McNiel Y DNA and also functioned for decades as the family historian. George, along with his wife, inventoried the many cemeteries of Wilkes County, NC.

George believed through oral history that the family descended from the McNiel’s of Barra.

McNiel Big Y Kisumul

George had this lovely framed print of Kisimul Castle, seat of the McNiel Clan on the Isle of Barra, proudly displayed on his wall.

That myth was dispelled with the initial DNA testing when our line did not match the Barra line, as can be seen in the MacNeil DNA project, much to George’s disappointment. As George himself said, the McNiel history is both mysterious and contradictory. Amen to that, George!

McNiel Big Y Niall 9 Hostages

However, in place of that history, we were instead awarded the Niall of the 9 Hostages badge, created many years ago based on a 12 marker STR result profile. Additionally, the McNiel DNA was assigned to haplogroup R-M222. Of course, today’s that’s a far upstream haplogroup, but 15+ years ago, we had only a fraction of the testing or knowledge that we do today.

The name McNeil, McNiel, or however you spell it, resembles Niall, so on the surface, this made at least some sense. George was encouraged by the new information, even though he still grieved the loss of Kisimul Castle.

Of course, this also caused us to wonder about the story stating our line had originated in Scotland because Niall of the 9 Hostages lived in Ireland.

Niall of the 9 Hostages

Niall of the 9 Hostages was reportedly a High King of Ireland sometime between the 6th and 10th centuries. However, actual historical records place him living someplace in the mid-late 300s to early 400s, with his death reported in different sources as occurring before 382 and alternatively about 411. The Annals of the Four Masters dates his reign to 379-405, and Foras Feasa ar Eirinn says from 368-395. Activities of his sons are reported between 379 and 405.

In other words, Niall lived in Ireland about 1500-1600 years ago, give or take.

Migration

Generally, migration was primarily from Scotland to Ireland, not the reverse, at least as far as we know in recorded history. Many Scottish families settled in the Ulster Plantation beginning in 1606 in what is now Northern Ireland. The Scots-Irish immigration to the states had begun by 1718. Many Protestant Scottish families immigrated from Ireland carrying the traditional “Mc” names and Presbyterian religion, clearly indicating their Scottish heritage. The Irish were traditionally Catholic. George could have been one of these immigrants.

We have unresolved conflicts between the following pieces of McNeil history:

  • Descended from McNeil’s of Barra – disproved through original Y DNA testing.
  • Immigrated from Glasgow, Scotland, and schooled in the Presbyterian religion in Edinburgh.
  • Descended from the Ui Neill dynasty, an Irish royal family dominating the northern half of Ireland from the 6th to 10th centuries.

Of course, it’s possible that our McNiel/McNeil line could have been descended from the Ui Neill dynasty AND also lived in Scotland before immigrating.

It’s also possible that they immigrated from Ireland, not Scotland.

And finally, it’s possible that the McNeil surname and M222 descent are not related and those two things are independent and happenstance.

A New Y DNA Tester

Since cousin George is, sadly, deceased, we needed a new male Y DNA tester to represent our McNiel line. Fortunately, one such cousin graciously agreed to take the Big Y-700 test so that we might, hopefully, answer numerous questions:

  • Does the McNiel line have a unique haplogroup, and if so, what does it tell us?
  • Does our McNiel line descend from Ireland or Scotland?
  • Where are our closest geographic clusters?
  • What can we tell by tracing our haplogroup back in time?
  • Do any other men match the McNiel haplogroup, and what do we know about their history?
  • Does the Y DNA align with any specific clans, clan history, or prehistory contributing to clans?

With DNA, you don’t know what you don’t know until you test.

Welcome – New Haplogroup

I was excited to see my McNeill cousin’s results arrive. He had graciously allowed me access, so I eagerly took a look.

He had been assigned to haplogroup R-BY18350.

McNiel Big Y branch

Initially, I saw that indeed, six men matched my McNeill cousin, assigned to the same haplogroup. Those surnames were:

  • Scott
  • McCollum
  • Glass
  • McMichael
  • Murphy
  • Campbell

Notice that I said, “were.” That’s right, because shortly after the results were returned, based on markers called private variants, Family Tree DNA assigned a new haplogroup to my McNeill cousin.

Drum roll please!!!

Haplogroup R-BY18332

McNiel Big Y BY18332

Additionally, my cousin’s Big Y test resulted in several branches being split, shown on the Block Tree below.

McNIel Big Y block tree

How cool is this!

This Block Tree graphic shows, visually, that our McNiel line is closest to McCollum and Campbell testers, and is a brother clade to those branches showing to the left and right of our new R-BY18332. It’s worth noting that BY25938 is an equivalent SNP to BY18332, at least today. In the future, perhaps another tester will test, allowing those two branches to be further subdivided.

Furthermore, after the new branches were added, Cousin McNeill has no more Private Variants, which are unnamed SNPs. There were all utilized in naming additional tree branches!

I wrote about the Big Y Block Tree here.

Niall (Or Whoever) Was Prolific

The first thing that became immediately obvious was how successful our progenitor was.

McNiel Big Y M222 project

click to enlarge

In the MacNeil DNA project, 38 men with various surname spellings descend from M222. There are more in the database who haven’t joined the MacNeil project.

Whoever originally carried SNP R-M222, someplace between 2400 and 5900 years ago, according to the block tree, either had many sons who had sons, or his descendants did. One thing is for sure, his line certainly is in no jeopardy of dying out today.

The Haplogroup R-M222 DNA Project, which studies this particular haplogroup, reads like a who’s who of Irish surnames.

Big Y Match Results

Big Y matches must have no more than 30 SNP differences total, including private variants and named SNPs combined. Named SNPs function as haplogroup names. In other words, Cousin McNeill’s terminal SNP, meaning the SNP furthest down on the tree, R-BY18332, is also his haplogroup name.

Private variants are mutations that have occurred in the line being tested, but not yet in other lines. Occurrences of private variants in multiple testers allow the Private Variant to be named and placed on the haplotree.

Of course, Family Tree DNA offers two types of Y DNA testing, STR testing which is the traditional 12, 25, 37, 67 and 111 marker testing panels, and the Big Y-700 test which provides testers with:

  • All 111 STR markers used for matching and comparison
  • Another 589+ STR markers only available through the Big Y test increasing the total STR markers tested from 111 to minimally 700
  • A scan of the Y chromosome, looking for new and known SNPs and STR mutations

Of course, these tests keep on giving, both with matching and in the case of the Big Y – continued haplogroup discovery and refinement in the future as more testers test. The Big Y is an investment as a test that keeps on giving, not just a one-time purchase.

I wrote about the Big Y-700 when it was introduced here and a bit later here.

Let’s see what the results tell us. We’ll start by taking a look at the matches, the first place that most testers begin.

Mcniel Big Y STR menu

Regular Y DNA STR matching shows the results for the STR results through 111 markers. The Big Y section, below, provides results for the Big Y SNPs, Big Y matches and additional STR results above 111 markers.

McNiel Big Y menu

Let’s take a look.

STR and SNP Testing

Of Cousin McNeil’s matches, 2 Big Y testers and several STR testers carry some variant of the Neal, Neel, McNiel, McNeil, O’Neil, etc. surnames by many spellings.

While STR matching is focused primarily on a genealogical timeframe, meaning current to roughly 500-800 years in the past, SNP testing reaches much further back in time.

  • STR matching reaches approximately 500-800 years.
  • Big Y matching reaches approximately 1500 years.
  • SNPs and haplogroups reach back infinitely, and can be tracked historically beyond the genealogical timeframe, shedding light on our ancestors’ migration paths, helping to answer the age-old question of “where did we come from.”

These STR and Big Y time estimates are based on a maximum number of mutations for testers to be considered matches paired with known genealogy.

Big Y results consider two men a match if they have 30 or fewer total SNP differences. Using NGS (next generation sequencing) scan technology, the targeted regions of the Y chromosome are scanned multiple times, although not all regions are equally useful.

Individually tested SNPs are still occasionally available in some cases, but individual SNP testing has generally been eclipsed by the greatly more efficient enriched technology utilized with Big Y testing.

Think of SNP testing as walking up to a specific location and taking a look, while NGS scan technology is a drone flying over the entire region 30-50 times looking multiple times to be sure they see the more distant target accurately.

Multiple scans acquiring the same read in the same location, shown below in the Big Y browser tool by the pink mutations at the red arrow, confirm that NGS sequencing is quite reliable.

McNiel Big Y browser

These two types of tests, STR panels 12-111 and the SNP-based Big Y, are meant to be utilized in combination with each other.

STR markers tend to mutate faster and are less reliable, experiencing frustrating back mutations. SNPs very rarely experience this level of instability. Some regions of the Y chromosome are messier or more complicated than others, causing problems with interpreting reads reliably.

For purposes of clarity, the string of pink A reads above is “not messy,” and “A” is very clearly a mutation because all ~39 scanned reads report the same value of “A,” and according to the legend, all of those scans are high quality. Multiple combined reads of A and G, for example, in the same location, would be tough to call accurately and would be considered unreliable.

You can see examples of a few scattered pink misreads, above.

The two different kinds of tests produce results for overlapping timeframes – with STR mutations generally sifting through closer relationships and SNPs reaching back further in time.

Many more men have taken the Y DNA STR tests over the last 20 years. The Big Y tests have only been available for the past handful of years.

STR testing produces the following matches for my McNiel cousin:

STR Level STR Matches STR Matches Who Took the Big Y % STR Who Took Big Y STR Matches Who Also Match on the Big Y
12 5988 796 13 52
25 6660 725 11 57
37 878 94 11 12
67 1225 252 21 23
111 4 2 50 1

Typically, one would expect that all STR matches that took the Big Y would match on the Big Y, since STR results suggest relationships closer in time, but that’s not the case.

  • Many STR testers who have taken the Big Y seem to be just slightly too distant to be considered a Big Y match using SNPs, which flies in the face of conventional wisdom.
  • However, this could easily be a function of the fact that STRs mutate both backward and forwards and may have simply “happened” to have mutated to a common value – which suggests a closer relationship than actually exists.
  • It could also be that the SNP matching threshold needs to be raised since the enhanced and enriched Big Y-700 technology now finds more mutations than the older Big Y-500. I would like to see SNP matching expanded to 40 from 30 because it seems that clan connections may be being missed. Thirty may have been a great threshold before the more sensitive Big Y-700 test revealed more mutations, which means that people hit that 30 threshold before they did with previous tests.
  • Between the combination of STRs and SNPs mutating at the same time, some Big Y matches are pushed just out of range.

In a nutshell, the correlation I expected to find in terms of matching between STR and Big Y testing is not what I found. Let’s take a look at what we discovered.

It’s worth noting that the analysis is easier if you are working together with at least your closest matches or have access via projects to at least some of their results. You can see common STR values to 111 in projects, such as surname projects. Project administrators can view more if project members have allowed access.

Unexpected Discoveries and Gotchas

While I did expect STR matches to also match on the Big Y, I don’t expect the Big Y matches to necessarily match on the STR tests. After all, the Big Y is testing for more deep-rooted history.

Only one of the McNiel Big Y matches also matches at all levels of STR testing. That’s not surprising since Big Y matching reaches further back in time than STR testing, and indeed, not all STR testers have taken a Big Y test.

Of my McNeill cousin’s closest Big Y matches, we find the following relative to STR matching.

Surname Ancestral Location Big Y Variant/SNP Difference STR Match Level
Scott 1565 in Buccleuch, Selkirkshire, Scotland 20 12, 25, 37, 67
McCollum Not listed 21 67 only
Glass 1618 in Banbridge, County Down, Ireland 23 12, 25, 67
McMichael 1720 County Antrim, Ireland 28 67 only
Murphy Not listed 29 12, 25, 37, 67
Campbell Scotland 30 12, 25, 37, 67, 111

It’s ironic that the man who matches on all STR levels has the most variants, 30 – so many that with 1 more, he would not have been considered a Big Y match at all.

Only the Campbell man matches on all STR panels. Unfortunately, this Campbell male does not match the Clan Campbell line, so that momentary clan connection theory is immediately put to rest.

Block Tree Matches – What They Do, and Don’t, Mean

Note that a Carnes male, the other person who matches my McNeill cousin at 111 STR markers and has taken a Big Y test does not match at the Big Y level. His haplogroup BY69003 is located several branches up the tree, with our common ancestor, R-S588, having lived about 2000 years ago. Interestingly, we do match other R-S588 men.

This is an example where the total number of SNP mutations is greater than 30 for these 2 men (McNeill and Carnes), but not for my McNeill cousin compared with other men on the same S588 branch.

McNiel Big Y BY69003

By searching for Carnes on the block tree, I can view my cousin’s match to Mr. Carnes, even though they don’t match on the Big Y. STR matches who have taken the Big Y test, even if they don’t match at the Big Y level, are shown on the Block Tree on their branch.

By clicking on the haplogroup name, R-BY69003, above, I can then see three categories of information about the matches at that haplogroup level, below.

McNiel Big Y STR differences

click to enlarge

By selecting “Matches,” I can see results under the column, “Big Y.” This does NOT mean that the tester matches either Mr. Carnes or Mr. Riker on the Big Y, but is telling me that there are 14 differences out of 615 STR markers above 111 markers for Mr. Carnes, and 8 of 389 for Mr. Riker.

In other words, this Big Y column is providing STR information, not indicating a Big Y match. You can’t tell one way or another if someone shown on the Block Tree is shown there because they are a Big Y match or because they are an STR match that shares the same haplogroup.

As a cautionary note, your STR matches that have taken the Big Y ARE shown on the block tree, which is a good thing. Just don’t assume that means they are Big Y matches.

The 30 SNP threshold precludes some matches.

My research indicates that the people who match on STRs and carry the same haplogroup, but don’t match at the Big Y level, are every bit as relevant as those who do match on the Big Y.

McNIel Big Y block tree menu

If you’re not vigilant when viewing the block tree, you’ll make the assumption that you match all of the people showing on the Block Tree on the Big Y test since Block Tree appears under the Big Y tools. You have to check Big Y matches specifically to see if you match people shown on the Block Tree. You don’t necessarily match all of them on the Big Y test, and vice versa, of course.

You match Block Tree inhabitants either:

  • On the Big Y, but not the STR panels
  • On the Big Y AND at least one level of STRs between 12 and 111, inclusive
  • On STRs to someone who has taken the Big Y test, but whom you do not match on the Big Y test

Big Y-500 or Big Y-700?

McNiel Big Y STR differences

click to enlarge

Looking at the number of STR markers on the matches page of the Block Tree for BY69003, above, or on the STR Matches page is the only way to determine whether or not your match took the Big Y-700 or the Big Y-500 test.

If you add 111 to the Big Y SNP number of 615 for Mr. Carnes, the total equals 726, which is more than 700, so you know he took the Big Y-700.

If you add 111 to 389 for Mr. Riker, you get 500, which is less than 700, so you know that he took the Big Y-500 and not the Big Y-700.

There are still a very small number of men in the database who did not upgrade to 111 when they ordered their original Big Y test, but generally, this calculation methodology will work. Today, all Big Y tests are upgraded to 111 markers if they have not already tested at that level.

Why does Big Y-500 vs Big Y-700 matter? The enriched chemistry behind the testing technology improved significantly with the Big Y-700 test, enhancing Y-DNA results. I was an avowed skeptic until I saw the results myself after upgrading men in the Estes DNA project. In other words, if Big Y-500 testers upgrade, they will probably have more SNPs in common.

You may want to contact your closest Big Y-500 matches and ask if they will consider upgrading to the Big Y-700 test. For example, if we had close McNiel or similar surname matches, I would do exactly that.

Matching Both the Big Y and STRs – No Single Source

There is no single place or option to view whether or not you match someone BOTH on the Big Y AND STR markers. You can see both match categories individually, of course, but not together.

You can determine if your STR matches took the Big Y, below, and their haplogroup, which is quite useful, but you can’t tell if you match them at the Big Y level on this page.

McNiel Big Y STR match Big Y

click to enlarge

Selecting “Display Only Matches With Big Y” means displaying matches to men who took the Big Y test, not necessarily men you match on the Big Y. Mr. Conley, in the example above, does not match my McNeill cousin on the Big Y but does match him at 12 and 25 STR markers.

I hope FTDNA will add three display options:

  • Select only men that match on the Big Y in the STR panel
  • Add an option for Big Y on the advanced matches page
  • Indicate men who also match on STRs on the Big Y match page

It was cumbersome and frustrating to have to view all of the matches multiple times to compile various pieces of information in a separate spreadsheet.

No Big Y Match Download

There is also no option to download your Big Y matches. With a few matches, this doesn’t matter, but with 119 matches, or more, it does. As more people test, everyone will have more matches. That’s what we all want!

What you can do, however, is to download your STR matches from your match page at levels 12-111 individually, then combine them into one spreadsheet. (It would be nice to be able to download them all at once.)

McNiel Big Y csv

You can then add your Big Y matches manually to the STR spreadsheet, or you can simply create a separate Big Y spreadsheet. That’s what I chose to do after downloading my cousin’s 14,737 rows of STR matches. I told you that R-M222 was prolific! I wasn’t kidding.

This high number of STR matches also perfectly illustrates why the Big Y SNP results were so critical in establishing the backbone relationship structure. Using the two tools together is indispensable.

An additional benefit to downloading STR results is that you can sort the STR spreadsheet columns in surname order. This facilitates easily spotting all spelling variations of McNiel, including words like Niel, Neal and such that might be relevant but that you might not notice otherwise.

Creating a Big Y Spreadsheet

My McNiel cousin has 119 Big Y-700 matches.

I built a spreadsheet with the following columns facilitating sorting in a number of ways, with definitions as follows:

McNiel Big Y spreadsheet

click to enlarge

  • First Name
  • Last Name – You will want to search matches on your personal page at Family Tree DNA by this surname later, so be sure if there is a hyphenated name to enter it completely.
  • Haplogroup – You’ll want to sort by this field.
  • Convergent – A field you’ll complete when doing your analysis. Convergence is the common haplogroup in the tree shared by you and your match. In the case of the green matches above, which are color-coded on my spreadsheet to indicate the closest matches with my McNiel cousin, the convergent haplogroup is BY18350.
  • Common Tree Gen – This column is the generations on the Block Tree shown to this common haplogroup. In the example above, it’s between 9 and 14 SNP generations. I’ll show you where to gather this information.
  • Geographic Location – Can be garnered from 4 sources. No color in that cell indicates that this information came from the Earliest Known Ancestor (EKA) field in the STR matches. Blue indicates that I opened the tree and pulled the location information from that source. Orange means that someone else by the same surname whom the tester also Y DNA matches shows this location. I am very cautious when assigning orange, and it’s risky because it may not be accurate. A fourth source is to use Ancestry, MyHeritage, or another genealogical resource to identify a location if an individual provides genealogical information but no location in the EKA field. Utilizing genealogy databases is only possible if enough information is provided to make a unique identification. John Smith 1700-1750 won’t do it, but Seamus McDougal (1750-1810) married to Nelly Anderson might just work.
  • STR Match – Tells me if the Big Y match also matches on STR markers, and if so, which ones. Only the first 111 markers are used for matching. No STR match generally means the match is further back in time, but there are no hard and fast rules.
  • Big Y Match – My original goal was to combine this information with the STR match spreadsheet. If you don’t wish to combine the two, then you don’t need this column.
  • Tree – An easy way for me to keep track of which matches do and do not have a tree. Please upload or create a tree.

You can also add a spreadsheet column for comments or contact information.

McNiel Big Y profile

You will also want to click your match’s name to display their profile card, paying particular attention to the “About Me” information where people sometimes enter genealogical information. Also, scan the Ancestral Surnames where the match may enter a location for a specific surname.

Private Variants

I added additional spreadsheet columns, not shown above, for Private Variant analysis. That level of analysis is beyond what most people are interested in doing, so I’m only briefly discussing this aspect. You may want to read along, so you at least understand what you are looking at.

Clicking on Private Variants in your Big Y Results shows your variants, or mutations, that are unnamed as SNPs. When they are named, they become SNPs and are placed on the haplotree.

The reference or “normal” state for the DNA allele at that location is shown as the “Reference,” and “Genotype” is the result of the tester. Reference results are not shown for each tester, because the majority are the same. Only mutations are shown.

McNiel Big Y private variants

There are 5 Private Variants, total, for my cousin. I’ve obscured the actual variant numbers and instead typed in 111111 and 222222 for the first two as examples.

McNiel Big Y nonmatching variants

In our example, there are 6 Big Y matches, with matches one and five having the non-matching variants shown above.

Non-matching variants mean that the match, Mr. Scott, in example 1, does NOT match the tester (my cousin) on those variants.

  • If the tester (you) has no mutation, you won’t have a Private Variant shown on your Private Variant page.
  • If the tester does have a Private Variant shown, and that variant shows ON their matches list of non-matching variants, it means the match does NOT match the tester, and either has the normal reference value or a different mutation. Explained another way, if you have a mutation, and that variant is listed on your match list of Non-Matching Variants, your match does NOT match you and does NOT have the same mutation.
  • If the match does NOT have the Private Variant on their list, that means the match DOES match the tester, and they both have the same mutation, making this Private Variant a candidate to be named as a new SNP.
  • If you don’t have a Private Variant listed, but it shows in the Non-Matching Variants of your match, that means you have the reference or normal value, and they have a mutation.

In example #1, above, the tester has a mutation at variant 111111, and 111111 is shown as a Non-Matching Variant to Mr. Scott, so Mr. Scott does NOT match the tester. Mr. Scott also does NOT match the tester at locations 222222 and 444444.

In example #5, 111111 is NOT shown on the Non-Matching Variant list, so Mr. Treacy DOES match the tester.

I have a terrible time wrapping my head around the double negatives, so it’s critical that I make charts.

On the chart below, I’ve listed the tester’s private variants in an individual column each, so 111111, 222222, etc.

For each match, I’ve copy and pasted their Non-Matching Variants in a column to the right of the tester’s variants, in the lavender region. In this example, I’ve typed the example variants into separate columns for each tester so you can see the difference. Remember, a non-matching variant means they do NOT match the tester’s mutation.

McNiel private variants spreadsheet

On my normal spreadsheet where the non-matching variants don’t have individuals columns, I then search for the first variant, 111111. If the variant does appear in the list, it means that match #1 does NOT have the mutation, so I DON’T put an X in the box for match #1 under 111111.

In the example above, the only match that does NOT have 111111 on their list of Non-Matching Variants is #5, so an X IS placed in that corresponding cell. I’ve highlighted that column in yellow to indicate this is a candidate for a new SNP.

You can see that no one else has the variant, 222222, so it truly is totally private. It’s not highlighted in yellow because it’s not a candidate to be a new SNP.

Everyone shares mutation 333333, so it’s a great candidate to become a new SNP, as is 555555.

Match #6 shares the mutation at 444444, but no one else does.

This is a manual illustration of an automated process that occurs at Family Tree DNA. After Big Y matches are returned, automated software creates private variant lists of potential new haplogroups that are then reviewed internally where SNPs are evaluated, named, and placed on the tree if appropriate.

If you follow this process and discover matches, you probably don’t need to do anything, as the automated review process will likely catch up within a few days to weeks.

Big Y Matches

In the case of the McNiel line, it was exciting to discover several private variants, mutations that were not yet named SNPs, found in several matches that were candidates to be named as SNPs and placed on the Y haplotree.

Sure enough, a few days later, my McNeill cousin had a new haplogroup assignment.

Most people have at least one Private Variant, locations in which they do NOT match another tester. When several people have these same mutations, and they are high-quality reads, the Private Variant qualifies to be added to the haplotree as a SNP, a task performed at FamilyTreeDNA by Michael Sager.

If you ever have the opportunity to hear Michael speak, please do so. You can watch Michael’s presentation at Genetic Genealogy Ireland (GGI) titled “The Tree of Mankind,” on YouTube, here, compliments of Maurice Gleeson who coordinates GGI. Maurice has also written about the Gleeson Y DNA project analysis, here.

As a result of Cousin McNeill’s test, six new SNPs have been added to the Y haplotree, the tree of mankind. You can see our new haplogroup for our branch, BY18332, with an equivalent SNP, BY25938, along with three sibling branches to the left and right on the tree.

McNiel Big Y block tree 4 branch

Big Y testing not only answers genealogical questions, it advances science by building out the tree of mankind too.

The surname of the men who share the same haplogroup, R-BY18332, meaning the named SNP furthest down the tree, are McCollum and Campbell. Not what I expected. I expected to find a McNeil who does match on at least some STR markers. This is exactly why the Big Y is so critical to define the tree structure, then use STR matches to flesh it out.

Taking the Big Y-700 test provided granularity between 6 matches, shown above, who were all initially assigned to the same branch of the tree, BY18350, but were subsequently divided into 4 separate branches. My McNiel cousin is no longer equally as distant from all 6 men. We now know that our McNiel line is genetically closer on the Y chromosome to Campbell and McCollum and further distant from Murphy, Scott, McMichael, and Glass.

Not All SNP Matches are STR Matches

Not all SNP matches are also STR matches. Some relationships are too far back in time. However, in this case, while each person on the BY18350 branches matches at some STR level, only the Campbell individual matches at all STR levels.

Remember that variants (mutations) are accumulating down both respective branches of the tree at the same time, meaning one per roughly every 100 years (if 100 is the average number we want to use) for both testers. A total of 30 variants or mutations difference, an average of 15 on each branch of the tree (McNiel and their match) would suggest a common ancestor about 1500 years ago, so each Big Y match should have a common ancestor 1500 years ago or closer. At least on average, in theory.

The Big Y test match threshold is 30 variants, so if there were any more mismatches with the Campbell male, they would not have been a Big Y match, even though they have the exact same haplogroup.

Having the same haplogroup means that their terminal SNP is identical, the SNP furthest down the tree today, at least until someone matches one of them on their Private Variants (if any remain unnamed) and a new terminal SNP is assigned to one or both of them.

Mutations, and when they happen, are truly a roll of the dice. This is why viewing all of your Big Y Block Tree matches is critical, even if they don’t show on your Big Y match list. One more variant and Campbell would have not been shown as a match, yet he is actually quite close, on the same branch, and matches on all STR panels as well.

SNPs Establish the Backbone Structure

I always view the block tree first to provide a branching tree structure, then incorporate STR matches into the equation. Both can equally as important to genealogy, but haplogroup assignment is the most accurate tool, regardless of whether the two individuals match on the Big Y test, especially if the haplogroups are relatively close.

Let’s work with the Block Tree.

The Block Tree

McNIel Big Y block tree menu

Clicking on the link to the Block Tree in the Big Y results immediately displays the tester’s branch on the tree, below.

click to enlarge

On the left side are SNP generation markers. Keep in mind that approximate SNP generations are marked every 5 generations. The most recent generations are based on the number of private variants that have not yet been assigned as branches on the tree. It’s possible that when they are assigned that they will be placed upstream someplace, meaning that placement will reduce the number of early branches and perhaps increase the number of older branches.

The common haplogroup of all of the branches shown here with the upper red arrow is R-BY3344, about 15 SNP generations ago. If you’re using 100 years per SNP generation, that’s about 1500 years. If you’re using 80 years, then 1200 years ago. Some people use even fewer years for calculations.

If some of the private variants in the closer branches disappear, then the common ancestral branch may shift to closer in time.

This tree will always be approximate because some branches can never be detected. They have disappeared entirely over time when no males exist to reproduce.

Conversely, subclades have been born since a common ancestor clade whose descendants haven’t yet tested. As more people test, more clades will be discovered.

Therefore, most recent common ancestor (MRCA) haplogroup ages can only be estimated, based on who has tested and what we know today. The tree branches also vary depending on whether testers have taken the Big Y-500 or the more sensitive Big Y-700, which detects more variants. The Y haplotree is a combination of both.

Big Y-500 results will not be as granular and potentially do not position test-takers as far down the tree as Big Y-700 results would if they upgraded. You’ll need to factor that into your analysis if you’re drawing genealogical conclusions based on these results, especially close results.

You’ll note that the direct path of descent is shown above with arrows from BY3344 through the first blue box with 5 equivalent SNPS, to the next white box, our branch, with two equivalent SNPs. Our McNeil ancestor, the McCollum tester, and the Campell tester have no unresolved private variants between them, which suggests they are probably closer in time than 10 generations back. You can see that the SNP generations are pushed “up” by the neighbor variants.

Because of the fact that private variants don’t occur on a clock cycle and occur in individual lines at an unsteady rate, we must use averages.

That means that when we look further “up” the tree, clicking generation by generation on the up arrow above BY3344, the SNP generations on the left side “adjust” based on what is beneath, and unseen at that level.

The Block Tree Adjusts

Note, in the example above, BY3344 is at SNP generation 15.

Next, I clicked one generation upstream, to R-S668.

McNiel Big Y block tree S668

click to enlarge

You can see that S668 is about 21 SNP generations upstream, and now BY3344 is listed as 20 generations, not 15. You can see our branch, BY3344, but you can no longer see subclades or our matches below that branch in this view.

You can, however, see two matches that descend through S668, brother branches to BY3344, red arrows at far right.

Clicking on the up arrow one more time shows us haplogroup S673, below, and the child branches. The three child branches on which the tester has matches are shown with red arrows.

McNiel Big Y S673

click to enlarge

You’ll immediately notice that now S668 is shown at 19 SNP generations, not 20, and S673 is shown at 20. This SNP generation difference between views is a function of dealing with aggregated and averaged private variants on combined lines and causes the SNP generations to shift. This is also why I always say “about.”

As you continue to click up the tree, the shifting SNP generations continue, reminding us that we can’t truly see back in time. We can only achieve approximations, but those approximations improve as more people test, and more SNPs are named and placed in their proper places on the phylotree.

I love the Block Tree, although I wish I could see further side-to-side, allowing me to view all of the matches on one expanded tree so I can easily see their relationships to the tester, and each other.

Countries and Origins

In addition to displaying shared averaged autosomal origins of testers on a particular branch, if they have taken the Family Finder test and opted-in to sharing origins (ethnicity) results, you can also view the countries indicated by testers on that branch along with downstream branches of the tree.

McNiel Big Y countries

click to enlarge

For example, the Countries tab for S673 is shown above. I can see matches on this branch with no downstream haplogroup currently assigned, as well as cumulative results from downstream branches.

Still, I need to be able to view this information in a more linear format.

The Block Tree and spreadsheet information beautifully augment the haplotree, so let’s take a look.

The Haplotree

On your Y DNA results page, click on the “Haplotree and SNPs” link.

McNIel Big Y haplotree menu

click to enlarge

The Y haplotree will be displayed in pedigree style, quite familiar to genealogists. The SNP legend will be shown at the top of the display. In some cases, “presumed positive” results occur where coverage is lacking, back mutations or read errors are encountered. Presumed positive is based on positive SNPs further down the tree. In other words, that yellow SNP below must read positive or downstream ones wouldn’t.

McNIel Big Y pedigree descent

click to enlarge

The tester’s branch is shown with the grey bar. To the right of the haplogroup-defining SNP are listed the branch and equivalent SNP names. At far right, we see the total equivalent SNPs along with three dots that display the Country Report. I wish the haplotree also showed my matches, or at least my matching surnames, allowing me to click through. It doesn’t, so I have to return to the Big Y page or STR Matches page, or both.

I’ve starred each branch through which my McNiell cousin descends. Sibling branches are shown in grey. As you’ll recall from the Block Tree, we do have matches on those sibling branches, shown side by side with our branch.

The small numbers to the right of the haplogroup names indicate the number of downstream branches. BY18350 has three, all displayed. But looking upstream a bit, we see that DF97 has 135 downstream branches. We also have matches on several of those branches. To show those branches, simply click on the haplogroup.

The challenge for me, with 119 McNeill matches, is that I want to see a combination of the block tree, my spreadsheet information, and the haplotree. The block tree shows the names, my spreadsheet tells me on which branches to look for those matches. Many aren’t easily visible on the block tree because they are downstream on sibling branches.

Here’s where you can find and view different pieces of information.

Data and Sources STR Matches Page Big Y Matches Page Block Tree Haplogroups & SNPs Page
STR matches Yes No, but would like to see who matches at which STR levels If they have taken Big Y test, but doesn’t mean they match on Big Y matching No
SNP matches *1 Shows if STR match has common haplogroup, but not if tester matches on Big Y No, but would like to see who matches at which STR level Big Y matches and STR matches that aren’t Big Y matches are both shown No, but need this feature – see combined haplotree/ block tree
Other Haplogroup Branch Residents Yes, both estimated and tested No, use block tree or click through to profile card, would like to see haplogroup listed for Big Y matches Yes, both Big Y and STR tested, not estimated. Cannot tell if person is Big Y match or STR match, or both. No individuals, but would like that as part of countries report, see combined haplotree/block tree
Fully Expanded Phylotree No No Would like ability to see all branches with whom any Big Y or STR match resides at one time, even if it requires scrolling Yes, but no match information. Matches report could be added like on Block Tree.
Averaged Ethnicities if Have FF Test No No Yes, by haplogroup branch No
Countries Matches map STR only No, need Big Y matches map Yes Yes
Earliest Known Ancestor Yes No, but can click through to profile card No No
Customer Trees Yes No, need this link No No
Profile Card Yes, click through Yes, click through Yes, click through No match info on this page
Downloadable data By STR panel only, would like complete download with 1 click, also if Big Y or FF match Not available at all No No
Path to common haplogroup No No, but would like to see matches haplogroup and convergent haplogroup displayed No, would like the path to convergent haplogroup displayed as an option No, see combined match-block -haplotree in next section

*1 – the best way to see the haplogroup of a Big Y match is to click on their name to view their profile card since haplogroup is not displayed on the Big Y match page. If you happen to also match on STRs, their haplogroup is shown there as well. You can also search for their name using the block tree search function to view their haplogroup.

Necessity being the mother of invention, I created a combined match/block tree/haplotree.

And I really, REALLY hope Family Tree DNA implements something like this because, trust me, this was NOT fun! However, now that it’s done, it is extremely useful. With fewer matches, it should be a breeze.

Here are the steps to create the combined reference tree.

Combo Match/Block/Haplotree

I used Snagit to grab screenshots of the various portions of the haplotree and typed the surnames of the matches in the location of our common convergent haplogroup, taken from the spreadsheet. I also added the SNP generations in red for that haplogroup, at far left, to get some idea of when that common ancestor occurred.

McNIel Big Y combo tree

click to enlarge

This is, in essence, the end-goal of this exercise. There are a few steps to gather data.

Following the path of two matches (the tester and a specific match) you can find their common haplogroup. If your match is shown on the block tree in the same view with your branch, it’s easy to see your common convergent parent haplogroup. If you can’t see the common haplogroup, it’s takes a few extra steps by clicking up the block tree, as illustrated in an earlier section.

We need the ability to click on a match and have a tree display showing both paths to the common haplogroup.

McNiel Big Y convergent

I simulated this functionality in a spreadsheet with my McNiel cousin, a Riley match, and an Ocain match whose terminal SNP is the convergent SNP (M222) between Riley and McNiel. Of course, I’d also like to be able to click to see everyone on one chart on their appropriate branches.

Combining this information onto the haplotree, in the first image, below, M222, 4 men match my McNeill cousin – 2 who show M222 as their terminal SNP, and 2 downstream of M222 on a divergent branch that isn’t our direct branch. In other words, M222 is the convergence point for all 4 men plus my McNeill cousin.

McNiel Big Y M222 haplotree

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In the graphic below, you can see that M222 has a very large number of equivalent SNPs, which will likely become downstream haplogroups at some point in the future. However, today, these equivalent SNPs push M222 from 25 generations to 59. We’ll discuss how this meshes with known history in a minute.

McNiel Big Y M222 block tree

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Two men, Ocain and Ransom, who have both taken the Big Y, whose terminal SNP is M222, match my McNiel cousin. If their common ancestor was actually 59 generations in the past, it’s very, very unlikely that they would match at all given the 30 mutation threshold.

On my reconstructed Match/Block/Haplotree, I included the estimated SNP generations as well. We are starting with the most distant haplogroups and working our way forward in time with the graphics, below.

Make no mistake, there are thousands more men who descend from M222 that have tested, but all of those men except 4 have more than 30 mutations total, so they are not shown as Big Y matches, and they are not shown individually on the Block Tree because they neither match on the Big Y or STR tests. However, there is a way to view information for non-matching men who test positive for M222.

McNiel Big Y M222 countries

click to enlarge

Looking at the Block Tree for M222, many STR match men took a SNP test only to confirm M222, so they would be shown positive for the M222 SNP on STR results and, therefore, in the detailed view of M222 on the Block tree.

Haplogroup information about men who took the M222 test and whom the tester doesn’t match at all are shown here as well in the country and branch totals for R-M222. Their names aren’t displayed because they don’t match the tester on either type of Y DNA test.

Back to constructing my combined tree, I’ve left S658 in both images, above and below, as an overlap placeholder, as we move further down, or towards current, on the haplotree.

McNiel Big Y combo tree center

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Note that BY18350, above, is also an overlap connecting below.

You’ll recall that as a result of the Big Y test, BY18350 was split and now has three child branches plus one person whose terminal SNP is BY18350. All of the men shown below were on one branch until Big Y results revealed that BY18350 needed to be split, with multiple new haplogroups added to the tree.

McNiel Big Y combo tree current

click to enlarge

Using this combination of tools, it’s straightforward for me to see now that our McNiel line is closest to the Campbell tester from Scotland according to the Big Y test + STRs.

Equal according to the Big Y test, but slightly more distant, according to STR matching, is McCollum. The next closest would be sibling branches. Then in the parent group of the other three, BY18350, we find Glass from Scotland.

In BY18350 and subgroups, we find several Scotland locations and one Northern Ireland, which was likely from Scotland initially, given the surname and Ulster Plantation era.

The next upstream parent haplogroup is BY3344, which looks to be weighted towards ancestors from Scotland, shown on the country card, below.

McNiel Big Y BY3344

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This suggests that the origins of the McNiel line was, perhaps, in Scotland, but it doesn’t tell us whether or not George and presumably, Thomas, immigrated from Ireland or Scotland.

This combined tree, with SNPs, surnames from Big Y matches, along with Country information, allows me to see who is really more closely related and who is further away.

What I didn’t do, and probably should, is to add in all of the STR matches who have taken the Big Y test, shown on their convergent branch – but that’s just beyond the scope of time I’m willing to invest, at least for now, given that hundreds of STR matches have taken the Big Y test, and the work of building the combined tree is all manual today.

For those reading this article without access to the Y phylogenetic tree, there’s a public version of the Y and mitochondrial phylotrees available, here.

What About Those McNiels?

No other known McNiel descendants from either Thomas or George have taken the Big Y test, so I didn’t expect any to match, but I am interested in other men by similar surnames. Does ANY other McNiel have a Big Y match?

As it turns out, there are two, plus one STR match who took a Big Y test, but is not a Big Y match.

However, as you can see on the combined match/block/haplotree, above, the closest other Big Y-matching McNeil male is found at about 19 SNP generations, or roughly 1900 years ago. Even if you remove some of the variants in the lower generations that are based on an average number of individual variants, you’re still about 1200 years in the past. It’s extremely doubtful that any surname would survive in both lines from the year 800 or so.

That McNeil tester’s ancestor was born in 1747 in Tranent, Scotland.

The second Big Y-matching person is an O’Neil, a few branches further up in the tree.

The convergent SNP of the two branches, meaning O’Neil and McNeill are at approximately the 21 generation level. The O’Neil man’s Neill ancestor is found in 1843 in Cookestown, County Tyrone, Ireland.

McNiel Big Y convergent McNeil lines

I created a spreadsheet showing convergent lines:

  • The McNeill man with haplogroup A4697 (ancestor Tranent, Scotland) is clearly closest genetically.
  • O’Neill BY91591, who is brother clades with Neel and Neal, all Irish, is another Big Y match.
  • The McNeill man with haplogroup FT91182 is an STR match, but not a Big Y match.

The convergent haplogroup of all of these men is DF105 at about the 22 SNP generation marker.

STRs

Let’s turn back to STR tests, with results that produce matches closer in time.

Searching my STR download spreadsheet for similar surnames, I discovered several surname matches, mining the Earliest Known Ancestor information, profiles and trees produced data as follows:

Ancestor STR Match Level Location
George Charles Neil 12, 25, match on Big Y A4697 1747-1814 Tranent, Scotland
Hugh McNeil 25 (tested at 67) Born 1800 Country Antrim, Northern Ireland
Duncan McNeill 12 (tested at 111) Married 1789, Argyllshire, Scotland
William McNeill 12, 25 (tested at 37) Blackbraes, Stirlingshire, Scotland
William McNiel 25 (tested at 67) Born 1832 Scotland
Patrick McNiel 25 (tested at 111) Trien East, County Roscommon, Ireland
Daniel McNeill 25 (tested at 67) Born 1764 Londonderry, Northern Ireland
McNeil 12 (tested at 67) 1800 Ireland
McNeill (2 matches) 25 (tested Big Y-  SNP FT91182) 1810, Antrim, Northern Ireland
Neal 25 – (tested Big Y, SNP BY146184) Antrim, Northern Ireland
Neel (2 matches) 67 (tested at 111, and Big Y) 1750 Ireland, Northern Ireland

Our best clue that includes a Big Y and STR match is a descendant of George Charles Neil born in Tranent, Scotland, in 1747.

Perhaps our second-best clue comes in the form of a 111 marker match to a descendant of one Thomas McNeil who appears in records as early as 1753 and died in 1761 In Rombout Precinct, Dutchess County, NY where his son John was born. This line and another match at a lower level both reportedly track back to early New Hampshire in the 1600s.

The MacNeil DNA Project tells us the following:

Participant 106370 descends from Isaiah McNeil b. 14 May 1786 Schaghticoke, Rensselaer Co. NY and d. 28 Aug 1855 Poughkeepsie, Dutchess Co., NY, who married Alida VanSchoonhoven.

Isaiah’s parents were John McNeal, baptized 21 Jun 1761 Rombout, Dutchess Co., NY, d. 15 Feb 1820 Stillwater, Saratoga Co., NY and Helena Van De Bogart.

John’s parents were Thomas McNeal, b.c. 1725, d. 14 Aug 1761 NY and Rachel Haff.

Thomas’s parents were John McNeal Jr., b. around 1700, d. 1762 Wallkill, Orange Co., NY (now Ulster Co. formed 1683) and Martha Borland.

John’s parents were John McNeal Sr. and ? From. It appears that John Sr. and his family were this participant’s first generation of Americans.

Searching this line on Ancestry, I discovered additional information that, if accurate, may be relevant. This lineage, if correct, and it may not be, possibly reaching back to Edinburgh, Scotland. While the information gathered from Ancestry trees is certainly not compelling in and of itself, it provides a place to begin research.

Unfortunately, based on matches shown on the MacNeil DNA Project public page, STR marker mutations for kits 30279, B78471 and 417040 when compared to others don’t aid in clustering or indicating which men might be related to this group more closely than others using line-marker mutations.

Matches Map

Let’s take a look at what the STR Matches Map tells us.

McNiel Big Y matches map menu

This 67 marker Matches Map shows the locations of the earliest known ancestors of STR matches who have entered location information.

McNiel Big Y matches mapMcNiel Big Y matches map legend

My McNeill cousin’s closest matches are scattered with no clear cluster pattern.

Unfortunately, there is no corresponding map for Big Y matches.

SNP Map

The SNP map provided under the Y DNA results allows testers to view the locations where specific haplogroups are found.

McNiel Big Y SNP map

The SNP map marks an area where at least two or more people have claimed their most distant known ancestor to be. The cluster size is the maximum amount of miles between people that is allowed in order for a marker indicating a cluster at a location to appear. So for example, the sample size is at least 2 people who have tested, and listed their most distant known ancestor, the cluster is the radius those two people can be found in. So, if you have 10 red dots, that means in 1000 miles there are 10 clusters of at least two people for that particular SNP. Note that these locations do NOT include people who have tested positive for downstream locations, although it does include people who have taken individual SNP tests.

Working my way from the McNiel haplogroup backward in time on the SNP map, neither BY18332 nor BY18350 have enough people who’ve tested, or they didn’t provide a location.

Moving to the next haplogroup up the tree, two clusters are formed for BY3344, shown below.

McNIel Big Y BY3344 map

S668, below.

McNiel Big Y S668 map

It’s interesting that one cluster includes Glasgow.

S673, below.

McNiel Big Y S673 map

DF85, below:

McNiel Big Y DF85 map

DF105 below:

McNiel BIg Y DF105 map

M222, below:

McNiel Big Y M222 map

For R-M222, I’ve cropped the locations beyond Ireland and Scotland. Clearly, RM222 is the most prevalent in Ireland, followed by Scotland. Wherever M222 originated, it has saturated Ireland and spread widely in Scotland as well.

R-M222

R-M222, the SNP initially thought to indicate Niall of the 9 Hostages, occurred roughly 25-59 SNP generations in the past. If this age is even remotely accurate, averaging by 80 years per generation often utilized for Big Y results, produces an age of 2000 – 4720 years. I find it extremely difficult to believe any semblance of a surname survived that long. Even if you reduce the time in the past to the historical narrative, roughly the year 400, 1600 years, I still have a difficult time believing the McNiel surname is a result of being a descendant of Niall of the 9 Hostages directly, although oral history does have staying power, especially in a clan setting where clan membership confers an advantage.

Surname or not, clearly, our line along with the others whom we match on the Big Y do descend from a prolific common ancestor. It’s very unlikely that the mutation occurred in Niall’s generation, and much more likely that other men carried M222 and shared a common ancestor with Niall at some point in the distant past.

McNiel Conclusion – Is There One?

If I had two McNiel wishes, they would be:

  • Finding records someplace in Virginia that connect George and presumably brothers Thomas and John to their parents.
  • A McNiel male from wherever our McNiel line originated becoming inspired to Y DNA test. Finding a male from the homeland might point the way to records in which I could potentially find baptismal records for George about 1720 and Thomas about 1724, along with possibly John, if he existed.

I remain hopeful for a McNiel from Edinburgh, or perhaps Glasgow.

I feel reasonably confident that our line originated genetically in Scotland. That likely precludes Niall of the 9 Hostages as a direct ancestor, but perhaps not. Certainly, one of his descendants could have crossed the channel to Scotland. Or, perhaps, our common ancestor is further back in time. Based on the maps, it’s clear that M222 saturates Ireland and is found widely in Scotland as well.

A great deal depends on the actual age of M222 and where it originated. Certainly, Niall had ancestors too, and the Ui Neill dynasty reaches further back, genetically, than their recorded history in Ireland. Given the density of M222 and spread, it’s very likely that M222 did, in fact, originate in Ireland or, alternatively, very early in Scotland and proliferated in Ireland.

If the Ui Neill dynasty was represented in the persona of the High King, Niall of the 9 Hostages, 1600 years ago, his M222 ancestors were clearly inhabiting Ireland earlier.

We may not be descended from Niall personally, but we are assuredly related to him, sharing a common ancestor sometime back in the prehistory of Ireland and Scotland. That man would sire most of the Irish men today and clearly, many Scots as well.

Our ancestors, whoever they were, were indeed in Ireland millennia ago. R-M222, our ancestor, was the ancestor of the Ui Neill dynasty and of our own Reverend George McNiel.

Our ancestors may have been at Knowth and New Grange, and yes, perhaps even at Tara.

Tara Niall mound in sun

Someplace in the mists of history, one man made a different choice, perhaps paddling across the channel, never to return, resulting in M222 descendants being found in Scotland. His descendants include our McNeil ancestors, who still slumber someplace, awaiting discovery.

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Generational Inheritance

Autosomal DNA testing has opened up the brave new world for genealogists.  Along with that opportunity comes some amount of frustration and sometimes desperation to wring every possible tidbit of information out of autosomal results, sometimes resulting in pushing the envelope of what the technology and DNA can tell us.

I often have clients who want me to take a look at DNA results from people several generations removed from each other and try to determine if the ancestors are likely to be brothers, for example.  While that’s fairly feasible in the first few generations, the further back in time one goes, the less reliably we can say much of anything about how DNA is transmitted.  Hence, the less we can say, reliably, about relationships between people.

The best we can ever do is to talk in averages.  It’s like a coin flip.  Take a coin out right now and flip it 10 times.  I just did, and did not get 5 heads and 5 tails, which the average would predict.  But averages are comprised of a large number of outcomes divided by the actual number of events.  That isn’t the same thing as saying if one repeats the event 10 times that you will have 5 heads and 5 tails, or the average.  Each of those 10 flips are entirely independent, so you could have any of 11 different outcomes:

  • 0 heads 10 tails
  • 1 head 9 tails
  • 2 heads 8 tails
  • 3 heads 7 tails
  • 4 heads 6 tails
  • 5 heads 5 tails
  • 6 heads 4 tails
  • 7 heads 3 tails
  • 8 heads 2 tails
  • 9 heads 1 tail
  • 10 heads 0 tails

What the average does say is that in the end, you are most likely to have an average of 5 heads and 5 tails – and the larger the series of events, the more likely you are to reach that average.

My 10 single event flips were 4 heads and 6 tails, clearly not the average.  But if I did 10 series of coin flips, I bet my average would be 5 and 5 – and at 100 flips, it’s almost assured to be 50-50 – because the population, or number of events, has increased to the point where the average is almost assured.

You can see above, that while the average does indeed map to 5-5, or the 50-50 rule, the results of the individual flips are no respecter of that rule and are not connected to the final average outcome.  For example, if one set of flips is entirely tails and one set of flips is entirely heads, the average is still 50/50 which is not at all reflective of the actual events.

And so it goes with inheritance too.

However, we have come to expect that the 50% rule applies most of the time.  We knowriffle shuffle that it does, absolutely, with parents.  We do receive 50% of our DNA from each parent, but which 50%?.  From there, it can vary, meaning that we don’t necessarily get 25% of each grandparent’s DNA.  So while we receive 50% in total from each parent, we don’t necessarily receive every other segment or location, so it’s not like a rifle card shuffle where every other card is interspersed.

If one parents DNA sequence is:

TACGTACGTACG

A child cannot be presumed to receive every other allele, shown in red below.

TACGTACGTACG

The child could receive any portion of this particular segment, all of it, or none of it.

So, if you don’t receive every other allele from a parent, then how do you receive your DNA and how does that 50% division happen?  The bottom line is that we don’t know, but we are learning.  This article is the result of a learning experience.

Over time, genetic genealogists have come to expect that we are most likely to receive 25% of our DNA from each grandparent – which is statistically true when there are enough inheritance events.  This reflects our expectation of the standard deviation, where about 2/3rds of the results will be within the closest 25% in either direction of the center.  You can see expected standard deviation here.

This means that I would expect an inheritance frequency chart to look like this.

expected inheritance frequency

In this graph above, about half of the time, we inherit 50% of the DNA of any particular segment, and the rest of the time we inherit some different amount, with the most frequently inherited amounts being closer to the 50% mark and the outliers being increasingly rare as you approach 0% and 100% of a particular segment.

But does this predictability hold when we’re not talking about hundreds of events….when we’re not talking about population genetics….but our own family genetics, meaning one transmission event, from parent to child?  Because if that expected 50% factor doesn’t hold true, then that affects DRAMATICALLY what we can say about how related we are to someone 5 or 6 generations ago and how can we analyze individual chromosome data.

I have been uncomfortable with this situation for some time now, and the increasing incidence of anecdotal evidence has caused me to become increasingly more uncomfortable.

There are repeated anecdotal instances of significant segments that “hold” intact for many generations.  Statistically, this should not happen.  When this does happen, we, as genetic genealogists, consider ourselves lucky to be one of the 1% at the end of spectrum, that genetic karma has smiled upon us.  But is that true?  Are we at the lucky 1% end of the spectrum?

This phenomenon is shown clearly in the Vannoy project where 5 cousins who descend from Elijah Vannoy born in 1786 share a very significant portion of chromosome 15.  These people are all 5 generations or more distantly related from the common ancestor, (approximate 4th cousins) and should share less than 1% of their DNA in total, and certainly no large, unbroken segments.   As you can see, below, that’s not the case.  We don’t know why or how some DNA clumps together like this and is transmitted in complete (or nearly complete) segments, but they obviously are.  We often call these “sticky segments” for lack of a better term.

cousin 1

I downloaded this chromosome 15 information into a spreadsheet where I can sort it by chromosome.  Below you can see the segments on chromosome 15 where these cousins match me.

cousin 2

Chromosome 15 is a total of 141 cM in length and has 17,269 SNPs.  Therefore, at 5 generations removed, we would expect to see these people share a total of 4.4cM and 540 SNPs, or less for those more distantly related.  This would be under the matching threshold at either Family Tree DNA or 23andMe, so they would not be shown as matches at all.  Clearly, this isn’t the case for these 5 cousins.  This DNA held together and was passed intact for a total of 25 different individual inheritance events (5 cousins times 5 events, or  generations, each.)  I wrote about this in the article titles “Why Are My Predicted Cousin Relationships Wrong?”

Finally, I had a client who just would not accept no for an answer, wanted desperately to know the genetically projected relationship between two men who lived in the 1700s, and I felt an obligation to look into generational inheritance further.

About this same time, I had been working with my own matches at 23andMe.  Two of my children have tested there as well, a son and a daughter, so all of my matches at 23andMe obviously match me, and may or may not match my children.  This presented the perfect opportunity to study the amount of DNA transmitted in each inheritance event between me and both children.

Utilizing the reports at www.dnagedcom.com, I was able to download all of my matches into a spreadsheet, but then to also download all of the people on my match list that all of my matches match too.

I know, that was a tongue twister.  Maybe an example will help.

I match John Doe.  My match list looks like this and goes on for 353 lines.

match list

I only match John Doe on one chromosome at one location.  But finding who else on my match list of 353 people that John Doe matches is important because it gives me clues as to who is related to whom and descends from the same ancestor.  This is especially true if you recognize some of the people that your match matches, like your first cousin, for example.  This suggests, below that John Doe is related to me through the same ancestor as my first cousin, especially if John matches me with even more people who share that ancestor.   If my cousin and I both match John Doe on the same segment, that is strongly suggestive that this segment comes from a common ancestor, like in the previous Vannoy example.

Therefore, I methodically went through and downloaded every single one of my matches matches (from my match list) to see who was also on their list, and built myself a large spreadsheet.  That spreadsheet exercise is a topic for another article.  The important thing about this process is that how much DNA each of my children match with John Doe tells me exactly how much of my DNA each of my children inherited from me, versus their father, in that segment of DNA.

match comparison

In the above example, I match John Doe on Chromosome 11 from 37,000,000-63,000,000.  Looking at the expected 50% inheritance, or normal distribution, both of my children should match John Doe at half of that.  But look at what happened.  Both of my children inherited almost exactly all of the same DNA that I had to give.  Both of them inherited just slightly less in terms of genetic distance (cM) and also in terms of the number of SNPs.

It’s this type of information that has made me increasingly skeptical about the 50% bell curve standard deviation rule as applied to individual, not population, genetics.  The bell curve, of course, implies that the 50% percentile is the most likely even to occur, with the 49th being next most likely, etc.

This does not seem to be holding true.  In fact, in this one example alone, we have two examples of nearly 100% of the data being passed, not 50% in each inheritance event.  This is the type of one-off anecdotal evidence that has been making me increasingly uncomfortable.

I wanted something more than anecdotal evidence.  I copied all of the match information for myself and my children with my matches to one spreadsheet.  There are two genetic measures that can be utilized, centimorgans (cM) or total SNPs. I am using cM for these examples unless I state otherwise.

In total, there were 594 inheritance events shown as matches between me and others, and those same others and my children.

Upon further analysis of those inheritance events, 6 of them were actually not inheritance events from me.  In other words, those people matched me and my children on different chromosomes.  This means that the matches to my children were not through me, but from their father’s side or were IBS, Inherited by State.

son daughter comparison

This first chart is extremely interesting.  Including all inheritance events, 55% of the time, my children received none of the DNA I had to give them.  Whoa Nellie.  That is not what I expected to see.  They “should have” received half of my DNA, but instead, half of the time, they received none.

The balance of the time, they received some of my DNA 23% of the time and all of my DNA 21% of the time.  That also is not what I expected to see.

Furthermore, there is only one inheritance event in which one of my children actually inherited exactly half of what I had to offer, so significantly less than 1% at .1%.  In other words, what we expected to see actually happened the least often and was vanishingly rare when not looking at averages but at actual inheritance events.

Let’s talk about that “none” figure for a minute.  In this case, none isn’t really accurate, but I can’t be more accurate.  None means that 23andMe showed no match.  Their threshold for matching is 7cM (genetic distance) and 700 SNPS for the first matching segment, and then 5cM and 700 SNPS for secondary matching segments.  However, if you have over 1000 matches, which I do, matches begin to “fall off,” the smallest ones first, so you can’t tell what the functional match threshold is for you or for the people you match.  We can only guess, based on their published thresholds.

So let’s look at this another way.

Of the 329 times that my children received none of my DNA, 105 of those transmissions would be expected to be under the 700cM threshold, based on a 50% calculation of how many cMs I matched with the individual.  However, not all of those expected events were actually under the threshold, and many transmissions that were not expected to be under that threshold, were.  Therefore, 224, or 68% of those “none” events were not expected if you look at how much of my DNA the child would be expected to inherit at 50%.

Another very interesting anomaly that pops right up is the number of cases where my children inherited more than I had to give them.  In the example below, you can see that I match Jane Doe with 15.2cM and 2859 SNPs, but my daughter matches Jane with 16.3cM and 2960 on the same chromosome.

spreadsheet layout

There are a few possibilities to explain this:

  • My daughter also matches this person on her father’s side at this transition point.
  • My daughter matches this person IBS at this point.
  • The 23andMe matching software is trying to compensate for misreads.
  • There are misreads or no calls in my file.

There of course may be a combination of several of these factors, but the most likely is the fact that she is IBS at this location and the matching software is trying to be generous to compensate for possible no-calls and misreads.  I suggest this because they are almost uniformly very small amounts.

Therefore when my children match me at 100% or greater, I simply counted it as an exact match.  I was surprised at how many of these instances there were.  Most were just slightly over the value of 2 in the “times expected” column.  To explain how this column functions, a value of 1 is the expected amount – or 50% of my DNA.  A value of 2 means that the child inherited all of the DNA I had to offer in that location.  Any value over 2 means that one or more of the bulleted possibilities above occurred.

Between both of my children, there were a total of 75, or 60% with values greater than 2 on cMs and 96, or 80%, on SNPs, meaning that my children matched those people on more DNA at that location than I had to offer.  The range was from 2 to 2.4 with the exception of one match that was at 3.7.  That one could well be a valid transition (other parent) match.

There has been a lot of discussion recently about X chromosome inheritance.  In this case, the X would be like any other chromosome, since I have two Xs to recombine and give to my children, so I did not remove X matches from these calculations.  The X is shown as chromosome 99 here and 23 on the graphs to enable correct column sorting/graphing.

In the chart below, inheritance events are charted by chromosome.  The “Total” columns are the combined events of both my son and daughter.  The blue and pink columns are the inheritance events for both of them, which equal the total, of course.

The “none” column reflects transmissions on that chromosome where my children received none of my DNA.  The “some” column reflects transmission events where my children received some portion of my DNA between 0 (none) and 100% (all).  The “all” column reflects events where my children received all of the DNA that I had to offer.

chromosomal comparison

I graphed these events.

total inheritance graph

The graph shows the total inheritance events between both of my children by chromosome.  Number 23 in these charts is the X chromosome.

son inheritance graph

daughter inheritance graph

These inheritance numbers cause me to wonder what is going on with chromosome 5 in the case of both my daughter and son, and also chromosome 6 with my son.  I wonder if this would be uniform across families relative to chromosome 5, or if it is simply an anomaly within my family inheritance events.  It seems odd that the same anomaly would occur with both children.

son daughter inheritance graph

What this shows is that we are not dealing with a distribution curve where the majority of the events are at the 50% level and those that are not are progressively nearer to the 50% level than either end.  In other words, the Expected Inheritance Frequency is not what was found.

expected inheritance frequency

The actual curve, based on the inheritance events observed here, is shown below, where every event that was over the value of 2, or 100%, was normalized to 2.  This graph is dramatically different than the expected frequency, above.

actual inheritance frequency

Looking at this, it becomes immediately evident that we inherit either all of nothing of our parents DNA segments 85% of the time, and only about 15% of the time we inherit only a portion of our parents DNA segments.  Very, very rarely is the portion we inherit actually 50%, one tenth of one percent of the time.

Now that we understand that individual generational inheritance is not a 50-50 bell curve event, what does this mean to us as genetic genealogists?

I asked fellow genetic genealogist, Dr. David Pike, a mathematician to look this over and he offered the following commentary:

“As relationships get more distant, the number of blocks of DNA that are likely to be shared diminishes greatly.  Once down to one block, then really there are three outcomes for subsequent inheritance:  either the block is passed intact, no part of it is passed on, or recombination happens and a portion of it is passed on.  If we ignore this recombination effect (which should rarely affect a small block) then the block is either passed on in an “all or nothing” manner.  There’s essentially no middle ground with small blocks and even with lots of examples it doesn’t really make sense to expect an average of 50%.  As an analogy, consider the human population:  with about half of us being female and about half of us being male, the “average” person should therefore be androgynous, and yet very few people are indeed androgynous.”

In other words, even if you do have a segment that is 10 cMs in length, it’s not 10 coin flips, it’s one coin flip and it’s going to either be all, nothing or a portion thereof, and it’s more than 6 times more likely to be all or nothing than to be a partial inheritance.

So how do we resolve the fact that when we are looking at the 700,000 or so locations tested at Family Tree DNA and the 600,000 locations tested at 23andMe, that we can in fact use the averages to predict relationships, at least in closely related individuals, but we can’t utilize that same methodology in these types of individual situations?  There are many inheritance events being taken into consideration, 600,000 – 700,000, an amount that is mathematically high enough to over overcome the individual inheritance issues.  In other words, at this level, we can utilize averages.  However, when we move past the larger population model, the individual model simply doesn’t fit anymore for individual event inheritance – in other words, looking at individual segments.

Dr. Pike was kind enough to explain this in mathematical terms, but ones that the rest of us can understand:

“I think that part of what is at stake is the distinction between continuous versus discrete events.  These are mathematical terms, so to illustrate with an example, the number line from 0 to 10 is continuous and includes *all* numbers between them, such 2.55, pi, etc.  A discrete model, however, would involve only a finite number of elements, such as just the eleven integers from 0 to 10 inclusive.  In the discrete model there is nothing “in between” consecutive elements (such as 3 and 4), whereas in the continuous model there are infinitely elements between them.

It’s not unlike comparing a whole spectrum against a finite handful of a few options.  In some cases the distinction is easily blurred, such as if you conduct a survey and ask people to rate a politician on a discrete scale of 0 to 10… in this case it makes intuitive sense to say that the politician’s average rating was 7.32 (for example) even though 7.32 was not one of the options within the discrete scale.

In the realm of DNA, suppose that cousins Alice and Bob share 9 blocks of DNA with each other and we ask how many blocks Alice is likely to share with Bob’s unborn son.  The answer is discrete, and with each block having a roughly 50/50 chance we expect that there will likely be 4 or 5 blocks shared by Alice and Bob Jr., although the randomness of it could result in anywhere from 0 to 9 of the blocks being shared.  Although it doesn’t make practical sense to say that “four and a half” blocks will likely be shared [well, unless we allow recombination to split a block and thereby produce a shared “half block”], there is still some intuitive comfort in saying that 4.5 is the average of what we would expect, but in reality, either 4 or 5 blocks are shared.

But when we get to the extreme situation of there being only 1 block, for which the discrete options are only 0 or 1 block shared, yes or no, our comfortable familiarity with the continuous model fails us.  There are lots of analogies here, such as what is the average of a coin toss, what is the average answer to a True/False question, what the average gender of the population, etc.

Discrete models with lots of options can serve as good approximations of continuous situations, and vice-versa, which is probably part of what’s to blame for confusion here.

Really DNA inheritance is discrete, but with very many possible segments [such as if we divided the genome up into 10 cM segments and asked how many of Alice’s paternal segments will be inherited by one of her children, we can get away with a continuous model and essentially say that the answer is roughly 50%.  Really though, if there are 3000 of these blocks, the actual answer is one of the integers:  0, 1, 2, …, 2999, 3000.  The reality is discrete even though we like the continuous model for predicting it.

However, discrete situations with very few options simply cannot be modelled continuously.”

Back to our situation where we are attempting to determine a relationship of 2 men born in the 1700s whose descendants share fragments of DNA today.  When we see a particularly large fragment of DNA, we can’t make any assumptions about age or how long it has been in existence by “reverse engineering” it’s path to a common ancestor by doubling the amount of DNA in every generation.  In other words, based on the evidence we see above, it has most likely been passed entirely intact, not divided.  In the case of the Vannoy DNA, it looks like the ends have been shaved a few times, but the majority of the segment was passed entirely intact.  In fact, you can’t double the DNA inherited by each individual 5 times, because in at least one case, Buster, doubling his total matching cM, 100, even once would yield a number of cM greater the size of chromosome 15 at 141 cM.

Conversely, when we see no DNA matches, for example, in people who “should be” distant cousins, we can’t draw any conclusions about that either.  If the DNA didn’t get passed in the first generation – and according to the numbers we just saw – 58% doesn’t get passed at all, and 26% gets passed in its entirety, leaving only about 15% to receive some portion of one parent’s DNA, which is uniformly NOT 50% except for one instance in almost 1000 events (.1%) – then all bets for subsequent generations are off – they can’t inherit their half if their half is already gone or wasn’t half to begin with.

Based on mathematical model, Probability of Recombination, Dr. Pike has this to say:

If I’m reading this right, a 10 cM block has a 10% chance of being split into parts during the recombination process of a single conception. Although 10% is not completely negligible, it’s small enough that we can essentially consider “all” or “nothing” as the two dominant outcomes.

This is the fundamental underlying reason why testing companies are hesitant to predict specific relationships – they typically predict ranges of relationships – 1st to 3rd cousin, for example, based on a combination of averages – of the percentages of DNA shared, the number of segments, the size of segments, the number of SNPs etc.  The testing company, of course, can have no knowledge of how our individual DNA is or was actually passed, meaning how much ancestral DNA we do or don’t receive, so they must rely on those averages, which are very reliable as a continuous population model, and apparently, much less so as discrete individual events.

I would suggest that while we certainly have a large enough sample of inheritance events between me and my two children to be statistically relevant, it’s not large enough study to draw any broad sweeping conclusions. It is, after all, only 3 people and we don’t know how this data might hold up compared to a much larger sample of family inheritance events.  I’d like to see 100 or 1000 of these types of studies.

I would be very interested to see how this information holds up for anyone else who would be willing to do the same type of information download of their data for parent/multiple sibling inheritance.  I will gladly make my spreadsheet with the calculations available as a template to anyone who wants to do the same type of study.

I wonder if we would see certain chromosomes that always have higher or lower generational inheritance factors, like the “none” spike we see on chromosome 5.  I wonder if we would see a consistent pattern of male or female children inheriting more or less (all or none) from their parents.  I wonder what other kinds of information would reveal itself in a larger study, and if it would enable us to “weight” match information by chromosome or chromosome/gender, further refining our ability to understand our genetic relationships and to more accurately predict relationships.

I want to thank Dr. David Pike for reviewing and assisting with this article and in particular, for being infinitely patient and making the application of the math to genetics understandable for non-mathematicians.  If you would like to see an example of Dr. Pike’s professional work, here is one of his papers.  You can find his personal web page here and his wonderful DNA analysis tools here.

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Clovis People Are Native Americans, and from Asia, not Europe

In a paper published in Nature today, titled “The genome of a Late Pleistocene human from a Clovis burial site in western Montana,” by Rasmussen et al, the authors conclude that the DNA of a Clovis child is ancestral to Native Americans.  Said another way, this Clovis child was a descendant, along with Native people today, of the original migrants from Asia who crossed the Bering Strait.

This paper, over 50 pages including supplemental material, is behind a paywall but it is very worthwhile for anyone who is specifically interested in either Native American or ancient burials.  This paper is full of graphics and extremely interesting for a number of reasons.

First, it marks what I hope is perhaps a spirit of cooperation between genetic research and several Native tribes.

Second, it utilized new techniques to provide details about the individual and who in world populations today they most resemble.

Third, it utilized full genome sequencing and the analysis is extremely thorough.

Let’s talk about these findings in more detail, concentrating on information provided within the paper.

The Clovis are defined as the oldest widespread complex in North America dating fromClovis point about 13,000 to 12,600 calendar years before present.  The Clovis culture is often characterized by the distinctive Clovis style projectile point.  Until this paper, the origins and genetic legacy of the Clovis people have been debated.

These remains were recovered from the only known Clovis site that is both archaeological and funerary, the Anzick site, on private land in western Montana.  Therefore, the NAGPRA Act does not apply to these remains, but the authors of the paper were very careful to work with a number of Native American tribes in the region in the process of the scientific research.  Sarah L. Anzick, a geneticist and one of the authors of the paper, is a member of the Anzick family whose land the remains were found upon.  The tribes did not object to the research but have requested to rebury the bones.

The bones found were those of a male infant child and were located directly below the Clovis materials and covered in red ochre.  They have been dated  to about 12,707-12,556 years of age and are the oldest North or South American remains to be genetically sequenced.

All 4 types of DNA were recovered from bone fragment shavings: mitochondrial, Y chromosome, autosomal and X chromosome.

Mitochondrial DNA

The mitochondrial haplogroup of the child was D4h3a, a rather rare Native American haplogroup.  Today, subgroups exist, but this D4h3a sample has none of those mutations so has been placed at the base of the D4h3a tree branch, as shown below in a grapic from the paper.  Therefore, D4h3a itself must be older than this skeleton, and they estimate the age of D4h3a to be 13,000 plus or minus 2,600 years, or older.

Clovis mtDNA

Today D4h3a is found along the Pacific coast in both North and South America (Chile, Peru, Ecuador, Bolivia, Brazil) and has been found in ancient populations.  The highest percentage of D4h3a is found at 22% of the Cayapa population in Equador.  An ancient sample has been found in British Columbia, along with current members of the Metlakatla First Nation Community near Prince Rupert, BC.

Much younger remains have been found in Tierra del Fuego in South America, dating from 100-400 years ago and from the Klunk Mound cemetery site in West-Central Illinois dating from 1800 years ago.

It’s sister branch, D4h3b consists of only one D4h3 lineage found in Eastern China.

Y Chromosomal DNA

The Y chromosome was determined to be haplogroup Q-L54.  Haplogroup Q and subgroup Q-L54 originated in Asia and two Q-L54 descendants predominate in the Americas: Q-M3 which has been observed exclusively in Native-Americans and Northeastern Siberians and Q-L54.

The tree researchers constructed is shown below.

Clovis Y

They estimate the divergence between haplogroups Q-L54 and Q-M3, the two major haplogroup Q Native lines, to be about 16,900 years ago, or from between 13,000 – 19,700.

The researchers shared with us the methodology they used to determine when their most common recent ancestor (MCRA) lived.

“The modern samples have accumulated an average of 48.7 transversions [basic mutations] since their MCRA lived and we observed 12 in Anzick.  We infer an average of approximately 36.7 (48.7-12) transversions to have accumulated in the past 12.6 thousands years and therefore estimate the divergence time of Q-M3 and Q-L54 to be approximately 16.8 thousands years (12.6ky x 48.7/36.7).”

Autosomal

They termed their autosomal analysis “genome-wide genetic affinity.”  They compared the Anzick individual with 52 Native populations for which known European and African genetic segments have been “masked,” or excluded.  This analysis showed that the Anzick individual showed a closer affinity to all 52 Native American populations than to any extant or ancient Eurasian population using several different, and some innovative and new, analysis techniques.

Surprisingly, the Anzick infant showed less shared genetic history with 7 northern Native American tribes from Canada and the Artic including 3 Northern Amerind-speaking groups.  Those 7 most distant groups are:  Aleutians, East Greenlanders, West Greenlanders, Chipewyan, Algonquin, Cree and Ojibwa.

They were closer to 44 Native populations from Central and South America, shown on the map below by the red dots.  In fact, South American populations all share a closer genetic affinity with the Anzick individual than they do with modern day North American Native American individuals.

Clovis autosomal cropped

The researchers proposed three migration models that might be plausible to support these findings, and utilized different types of analysis to eliminate two of the three.  The resulting analysis suggests that the split between the North and South American lines happened either before or at the time the Anzick individual lived, and the Anzick individual falls into the South American group, not the North American group.  In other words, the structural split pre-dates the Anzick child.  They conclude on this matter that “the North American and South American groups became isolated with little or no gene flow between the two groups following the death of the Anzick individual.”  This model also implies an early divergence between these two groups.

Clovis branch

In Eurasia, genetic affinity with the Anzick individual decreases with distance from the Bering Strait.

The researchers then utilized the genetic sequence of the 24,000 year old MA-1 individual from Mal’ta, Siberia, a 40,000 year old individual “Tianyuan” from China and the 4000 year old Saqqaq Palaeo-Eskimo from Greenland.

Again, the Anzick child showed a closer genetic affinity to all Native groups than to either MA-1 or the Saqqaq individual.  The Saqqaq individual is closest to the Greenland Inuit populations and the Siberian populations close to the Bering Strait.  Compared to MA-1, Anzick is closer to both East Asian and Native American populations, while MA-1 is closer to European populations.  This is consistent with earlier conclusions stating that “the Native American lineage absorbed gene flow from an East Asian lineage as well as a lineage related to the MA-1 individual.”  They also found that Anzick is closer to the Native population and the East Asian population than to the Tianyuan individual who seems equally related to a geographically wide range of Eurasian populations.  For additional information, you can see their charts in figure 5 in their supplementary data file.

I have constructed the table below to summarize who matches who, generally speaking.

who matches who

In addition, a French population was compared and only showed an affiliation with the Mal’ta individual and generically, Tianyuan who matches all Eurasians at some level.

Conclusions

The researchers concluded that the Clovis infant belonged to a meta-population from which many contemporary Native Americans are descended and is closely related to all indigenous American populations.  In essence, contemporary Native Americans are “effectively direct descendants of the people who made and used Clovis tools and buried this child,” covering it with red ochre.

Furthermore, the data refutes the possibility that Clovis originated via a European, Solutrean, migration to the Americas.

I would certainly be interested to see this same type of analysis performed on remains from the eastern Canadian or eastern seaboard United States on the earliest burials.  Pre-contact European admixture has been a hotly contested question, especially in the Hudson Bay region, for a very long time, but we have yet to see any pre-Columbus era contact burials that produce any genetic evidence of such.

Additionally, the Ohio burial suggests that perhaps the mitochondrial DNA haplogroup is or was more widespread geographically in North American than is known today.  A wider comparison to Native American DNA would be beneficial, were it possible. A quick look at various Native DNA and haplogroup projects at Family Tree DNA doesn’t show this haplogroup in locations outside of the ones discussed here.  Haplogroup Q, of course, is ubiquitous in the Native population.

National Geographic article about this revelation including photos of where the remains were found.  They can make a tuft of grass look great!

Another article can be found at Voice of America News.

Science has a bit more.

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

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Native American Maternal Haplogroup A2a and B2a Dispersion

Recently, in Phys.org, they published a good overview of a couple of recently written genetic papers dealing with Native American ancestry.  I particularly like this overview, because it’s written in plain English for the non-scientific reader.

In a nutshell, there has been ongoing debate that has been unresolved surrounding whether or not there was one or more migrations into the Americas.  These papers use these terms a little differently.  They not only talk about entry into the Americas but also dispersion within the Americans, which really is a secondary topic and happened, obviously, after the initial entry event(s).

The primary graphic in this article, show below, from the PNAS article, shows the distribution within the Americas of Native American haplogroups A2a and B2a.

a2a, b2a

Schematic phylogeny of complete mtDNA sequences belonging to haplogroups A2a and B2a. A maximum-likelihood (ML) time scale is shown. (Inset) A list of exact age values for each clade. Credit: Copyright © PNAS, doi:10.1073/pnas.0905753107

As you can see, the locations of these haplogroups are quite different and the various distribution models set forth in the papers account for this difference in geography.

One of the aspects of this paper, and the two academic papers on which it is based, that I find particularly encouraging is that the researchers are utilizing full sequence mitochondrial DNA, not just the HVR1 or HVR1+HVR2 regions which has all too often been done in the past.  In all fairness, until rather recently, the expense of running the full sequence was quite high and there were few (if any) other results in the academic data bases to compare the results with.  Now, the cost is quite reasonable, thanks in part to genetic genealogy and new technologies, and so the academic testing standards are changing.  If you’ll note, Alessandro Achilli, one of the authors of these papers and others about Native Americans as well, also comments towards the end that full genome testing will be being utilized soon.  I look forward to this new era of research, not only for Native Americans but for all of us searching for our roots.

Read the Phys.org paper at: http://phys.org/news/2013-09-mitochondrial-genome-north-american-migration.html#jCp

The original academic papers are found here and here.  I encourage anyone with a serious interest in this topic to read these as well.

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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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Mitochondrial DNA Smartmatching – The Rest of the Story

Sometimes, a match is not a match.  I know, now I’ve gone and ruined your day…

One of the questions that everyone wants the answer to when looking at matches, regardless of what kind of DNA testing we’re talking about, is “how long ago?”  How long ago did I share a common ancestor with my match?  Seems like a pretty simple question doesn’t it?

The answer, especially with mitochondrial DNA is not terribly straightforward.  A perfect example of this fell into my lap this week, and I’m sharing it with you.

Mitochondrial DNA – A Short Primer

There are three regions that are tested in mitochondrial DNA testing for genealogy.  The HVR1 and HVR2 regions are tested at most testing companies, and at Family Tree DNA, the rest of the mitochondria, called the coding region, is tested as well with the full mitochondrial sequence test.  This is the mitochondrial equivalent of Paul Harvey’s “the rest of the story,” and of course we all know that the real story is always in “the rest of the story” or he wouldn’t be telling us about it!

Many times, the rest of the story is critically important.  In mitochondrial DNA, it’s the only way to obtain your full haplogroup designation.  If you don’t want to just be haplogroup J or A or H, you can test the coding region by taking the full sequence test and find out that you’re J1c2 or A2 or H21, and discover the story that goes with that haplogroup.  Guaranteed, it’s a lot more specific than the one that goes with simple J, A or H.  Often it’s the difference between where your ancestor was 2000 years ago and 20,000 years ago – and they probably covered a lot of territory in 18,000 years!

Let’s take a quick look at mitochondrial DNA.

To begin with, the HVR1 and HVR2 regions are called HVR for a reason – it’s short for hypervariable.  And of course, that means they vary, or mutate, a lot more rapidly, as compared to the coding region of the mitochondrial DNA.

In layman’s terms, think of a clock.  No, not a digital clock, an old-fashioned alarm clock.

alarm clock

The entire mitochondrial DNA has 16,569 locations.  The HVR1 and HVR2 regions take up the space on the clock face from 5 till until 5 after the hour.   The rest is the coding region – the mitochondrial “rest of the story.”  The coding region mutates much slower than the two HVR regions.

Just to be sure we’re on the same page, let’s talk for just a minute about how mitochondrial haplogroup assignments work.  For a detailed discussion of haplogroup assignments and how they are done, see Bill Hurst’s discussion here.

Generally a base haplogroup can be reasonably assigned by HVR1 region testing, but not always.  Sometimes they change with full sequence testing – so what you think you know may not be the end result.

My full haplogroup is J1c2f.  My base haplogroup is J.  I’m on the first branch of J, J1.  On branch J1, I’m on the third stick, c, J1c.  On the third stick J1c, I’m on the second twig, J1c2.  On the second twig, J1c2, I’m leaf f, or J1c2f.  Each of these branches of haplogroup J is determined by a specific mutation that happened long ago and was then passed to all of that person’s offspring, between them and me today.  The question is always, how long ago?

Mutation Rates – How Long Ago is Long Ago?

While we have a tip calculator at Family Tree DNA for Y-line DNA to predict how long ago 2 Y-line matches shared a most recent common ancestor, we don’t have anything similar for mitochondrial DNA, partly because of the great variation in the mutation rates for the various regions of mitochondrial DNA.  Family Tree DNA does provide guidelines for the HVR1 region, but they are so broad as to be relatively useless genealogically.  For example, at the 50th percentile, you are likely to have a common ancestor with someone whom you match exactly on the HVR1 mutations in 52 generations, or about 1300 years ago, in the year 713.  Wait, I know just who that is in my family tree!

These estimates do not take into account the HVR2 or coding regions.

I did some research jointly with another researcher not long ago attempting to determine the mutation rate for those regions, and we found estimates that ranged from 500 years to several thousand years per mutation occurrence and it wasn’t always clear in the publications whether they were referring to the entire mitochondria or just certain portions.  And then there are those pesky hot-spots that for some reason mutate a whole lot faster than other locations.  We’re not even going there.  Suffice it to say there is a wide divergence in opinion among academics, so we probably won’t be seeing any type of mito-tip calculator anytime soon.

Enter SmartMatching

Family Tree DNA does their best to make our matches useful to us and to eliminate matches that we know aren’t genealogically relevant.

For example, this week, I was working on a client’s DNA Report.  Let’s call him Joe.  Joe is haplogroup J1c2.  I am haplogroup J1c2f.  J1c2f has one additional haplogroup defining mutation, in the coding region, that J1c2 does not have.

Joe and I did not show as matches at Family Tree DNA, even though our HVR1 and HVR2 regions are exact matches.  Now, for a minute, that gave me a bit of a start.  In fact, I didn’t even realize that we were exact matches until I was working with his results at MitoSearch and recognized my own User ID.

I had to think for a minute about why we would not be considered matches at Family Tree DNA, and I was just about ready to submit a bug report, when I realized the answer was my extended haplogroup.  This, by the way, is the picture-perfect example of why you need full sequence testing.

Family Tree DNA knows that we both tested at the full sequence level.  They know that with a different haplogroup, we don’t share a common ancestor in hundreds to thousands of years, so it doesn’t matter if we match exactly on the HVR1 and HVR2 levels, we DON’T match on a haplogroup defining mutation, which, in this case, happens to be in the coding region, found only with full sequence testing.  Even if we have only one mismatch at the full sequence level, if it’s a haplogroup defining marker, we are not considered matches.  Said a different way, if our only difference was location 9055 and 9055 was NOT a haplogroup defining mutation, we would have been considered a match on all three levels – exact matches at the HVR1 and HVR2 levels and a 1 mutation difference at the full sequence level.  So how a mutation is identified, whether it’s haplogroup defining or not, is critical.

In our case, I carry a mutation at marker 9055 in the coding region that defines haplogroup J1c2f.  Joe doesn’t have this mutation, so he is not J1c2f, just J1c2.  So we don’t match.

So – How Long Ago for Me and Joe?

Dr. Behar in his “Copernican Reassessment of the Mitochondrial DNA Tree,” which has become the virtual Bible of mitochondrial DNA, estimates that the J1c2f haplogroup defining mutation at location 9055 occurred about 2000 years ago, plus or minus another 3000 years, which means my ancestor who had that mutation could have lived as long ago as 5000 years.

The mutations that define haplogroup J1c2 occurred about 9800 years ago, plus or minus another 2000.  So we know that Joe and I share a common ancestor about 7,800 – 11,800 years ago and our lines diverged sometime between then and 2,000 – 5,000 years ago.  So, in round numbers our common ancestor lived between 2,000 and 9,800 years ago.  Not much chance of identifying that person!

The ability to eliminate “near-misses” where the HVR1+HVR2 matches but the people aren’t in the same haplogroup, which is extremely common in haplogroup H, is actually a very useful feature that Family Tree DNA nicknamed SmartMatching.  With over 1000 matches at the HVR1 level, more than 200 at the HVR1+HVR2 level and another 50+ at the full sequence level, Joe certainly didn’t need to have any “misleading” matches included that could have been eliminating by a logic process.

So while Joe and I match, technically, if you only look at the HVR1 and HVR2 levels, we don’t really match, and that’s not evident at MitoSearch or at Ancestry or anyplace else that does not take into consideration both full sequence AND haplogroup defining mutations.  Family Tree DNA is the only company that does this.

It’s interesting to think about the fact that 2 people can match exactly at the HVR1+HVR2 levels, but the distance of the relationship can be vastly different.  I also match my mother on the HVR1+HVR2 levels, exactly, and our common ancestor is her.  So the distance to a common ancestor with an exact HVR1+HVR2 match can be anyplace from one generation (Mom) to thousands of years (Joe), and there is no way to tell the difference without full sequence testing and in this case, SmartMatching.

And that, my friends, is the rest of the story!