More Ancient DNA Samples For Comparison

Felix Chandrakumar has prepared and added three additional ancient DNA kits to GedMatch.  Thanks Felix!  This is a wonderful service you’re performing for the genetic genealogy community!

  • The Linearbandkeramik (LBK) sample, also referenced as “Stuttgart,” reflecting where it was discovered in Germany.  This individual was an early farmer dating from about 7,500 years ago and was one of the samples analyzed for the paper, Ancient genomes suggest three ancestral populations for present-day Europeans. Kit F999916
  • The La Brana-Arintero sample from Leon, Spain, about 7000 years old, represents a pre-agricultural European human genome – in other words, before the agriculturists from the Near East arrived. In an article at Science Daily, they have reconstructed his face. Original academic article available here. Kit F999915
  • The Mal’ta sample, from Siberia, about 24,000 years of age. The results were discussed in article, Native American Gene Flow – Europe?, Asia and the Americas, and the original article is available here. Kit F999914

These kits, along with the ones listed earlier, give us the opportunity to compare our own DNA with that of ancient people in specific populations.  It’s like taking a step back in time and seeing if we carry any of the same small segments as these people did – suggesting of course that we descend from the same population.

This Ancient European DNA map by Richard Stevens shows the European locations where ancient DNA has been retrieved.

ancient dna map2

Recent discussion has focused on determining what matches to these specimens actually mean to genetic genealogists today.  We obviously don’t have that answer at this point.  We know that, due to their age, these samples are not close relatives in terms of genealogy generations, but in some cases, we find that we have matches far larger than one would expect to be found utilizing the 50% washout per generation math.

Endogamy, especially in a closed population such as Native Americans is certainly one explanation.  That doesn’t explain the European matches however – either to Anzick, the Native American specimen, nor Europeans to the European samples.  The higher no-call rate in the autosomal files can contribute as well, but wouldn’t account for all matches.  In some cases, maybe everyone carries the same DNA because the population carries that DNA in very high rates – but the population carries the DNA in very high rates because the ancient ancestors did as well…so this is a bit of circular logic.  All that said, we’re still left wondering what is real and what is Memorex, so to speak?

Ancient DNA is changing our understanding of the human past, and that of our ancestors.  It allows us a connection to the ancient people that is tangible, parts of them found in us today, as unbelievable as it seems.

When Svante Paabo discovered that modern Europeans all carry pieces of Neanderthal DNA, he too was struck by what I’ll call “the disbelief factor,” thinking, of course, that it can’t possibly be true.  He discussed this at length in his book, Neanderthal Man, In Search of Lost Genomes, and the steps taken by his team to prove that the matches weren’t in error or due to some problem with the ancient genome reconstruction process.  Indeed, all Europeans and Asians carry both Neanderthal and Denisovan DNA, and by the same process of the DNA being carried by the entire population at one point, which must be the avenue for contemporary humans to carry other ancient DNA as well.  As we find individual matches to small pieces of DNA with these matches, how much of that is “real” versus convergence or a result of no-calls in the ancient files?

In that vein, I find this article from Dienekes Anthropology Blog quite interesting,  found in the ASHG Titles of Interest from the upcoming Conference in October in San Diego, CA.

Reducing pervasive false positive identical-by-descent segments detected by large-scale pedigree analysis. E. Y. Durand, N. Eriksson, C. Y. McLean.

“Analysis of genomic segments shared identical-by-descent (IBD) between individuals is fundamental to many genetic applications, from demographic inference to estimating the heritability of diseases. A large number of methods to detect IBD segments have been developed recently. However, IBD detection accuracy in non-simulated data is largely unknown. In principle, it can be evaluated using known pedigrees, as IBD segments are by definition inherited without recombination down a family tree. We extracted 25,432 genotyped European individuals containing 2,952 father-mother-child trios from the 23andMe, Inc. dataset. We then used GERMLINE, a widely used IBD detection method, to detect IBD segments within this cohort. Exploiting known familial relationships, we identified a false positive rate over 67% for 2-4 centiMorgan (cM) segments, in sharp contrast with accuracies reported in simulated data at these sizes. We show that nearly all false positives arise due to allowing switch errors between haplotypes when detecting IBD, a necessity for retrieving long (> 6 cM) segments in the presence of imperfect phasing. We introduce HaploScore, a novel, computationally efficient metric that enables detection and filtering of false positive IBD segments on population-scale datasets. HaploScore scores IBD segments proportional to the number of switch errors they contain. Thus, it enables filtering of spurious segments reported due to GERMLINE being overly permissive to imperfect phasing. We replicate the false IBD findings and demonstrate the generalizability of HaploScore to alternative genotyping arrays using an independent cohort of 555 European individuals from the 1000 Genomes project. HaploScore can be readily adapted to improve the accuracy of segments reported by any IBD detection method, provided that estimates of the genotyping error rate and switch error rate are available.”

I’m pleased to see that they are addressing smaller segments, in the 2cM-4cM range, because those are the ranges some are finding in matches to these ancient genomes.  A few matches are even larger.

Of course, all of this ancient matching has caused an upsurge in interest in the cultures and populations of these ancient people whose DNA we carry.

I find this graphic very interesting from the paper, Toward a new history and geography of human genes informed by ancient DNA, just published this month, by Joseph Pickrell and David Reich.  This map, which shows the population movement into and out of geographic regions of the world in the past, is especially interesting in that several back migrations are shown into Africa.  I’ve never seen the “history of the world in population migration” summed up quite so succinctly before, but it helps us understand why certain DNA is found in specific locations.

population man

Copyright @2014 Elsevier Ltd, Trends in Genetics, 2014, 30, 377-389DOI: (10/1016/j.tig.2014.07.007

As we find and fully sequence additional ancient DNA specimens, we’ll be able to better understand how the ancient populations were related to each other, and then, how we descend from each of them.

This is a fascinating age of personal discovery!

24 thoughts on “More Ancient DNA Samples For Comparison

  1. I find this fascinating also. What I would find really interesting would be DNA from the Lichtenstein Cave remains uploaded to GedMatch. I share the I2a2b (L-38) Y DNA haplogroup as found in most of the male remains in this cave.

      • If I set it to > 3cM and > 100 SNPs, I get the following:

        Comparing Kit M011125 (Paul Conroy) and F999916 (Linearbandkeramik)

        Minimum threshold size to be included in total = 100 SNPs
        Mismatch-bunching Limit = 50 SNPs
        Minimum segment cM to be included in total = 3.0 cM

        Chr Start Location End Location Centimorgans (cM) SNPs
        1 240744201 244772762 11.0 858
        2 215991238 217344350 3.2 327
        2 222442086 225342937 3.8 555
        3 72292228 73510299 3.1 266
        3 173353038 174806420 3.3 302
        4 14168962 16027032 3.4 409
        4 25203654 26736776 3.6 279
        4 54348560 56332245 3.1 363
        4 175359233 177585749 3.2 409
        5 6966626 8947289 3.7 486
        8 118355227 122057793 3.3 826
        10 2470445 3781224 5.9 402
        10 89154174 92127252 3.0 704
        12 6786167 8099511 3.2 248
        12 111640806 113672107 3.4 469
        14 22920742 24650231 3.6 443
        15 25007748 26805134 5.9 254
        16 8657604 10628697 4.4 546
        16 17075737 18768636 3.3 243
        17 6399031 8122992 3.7 390
        17 9099927 9717026 3.2 148
        17 50347267 52030451 3.2 353
        19 2438858 3135083 3.6 141
        19 5042332 6592342 3.6 253
        19 35767923 38190911 3.8 398
        20 6928635 8256944 3.4 303
        20 51844911 53580493 3.9 430
        22 46912402 47541093 4.3 243
        Largest segment = 11.0 cM
        Total of segments > 3 cM = 110.0 cM

  2. Roberta, The map from Richard Stevens only shows locations where Y-chromosome DNA has been found. Ancient DNA research mostly focuses on autosomal DNA and mtDNA. I don’t know if there is a similar map showing the locations where autosomal DNA and mtDNA have been found. There have been some big advances in ancient DNA testing and it’s wonderful that so many of these samples are now becoming available for further analysis.

    The 23andMe Haploscore paper was made available online in advance of its print publication earlier this year. The full text can be found here:

    http://mbe.oxfordjournals.org/content/early/2014/04/30/molbev.msu151.full.pdf+html

      • I matched the Linearbankeramike on all of the Chromosomes any the largest was 4.1.Thank you for all of the information you give so freely. Here are my results:
        The GEDmatch.Com Autosomal Comparison
        Comparing Kit F999916 (Linearbandkeramik) and M171859 (*ljwc)

        Minimum threshold size to be included in total = 200 SNPs
        Mismatch-bunching Limit = 125 SNPs
        Minimum segment cM to be included in total = 1.5 cM
        Chr Start Location End Location Centimorgans (cM) SNPs
        1 7893665 9160682 2.1 373
        1 11737218 12516148 2.3 306
        1 119240838 120866130 1.6 369
        1 145517682 150813513 3.4 906
        2 4407267 4953828 1.6 222
        2 8887646 9599248 1.8 202
        2 15213211 15866885 1.6 215
        2 56892754 58991504 1.5 626
        2 72356501 74037181 2.0 319
        2 113105947 114930145 1.9 616
        2 130385289 132855747 3.3 271
        2 133048174 134133367 1.6 424
        2 150379011 151944644 1.5 506
        2 155025150 156177143 1.6 271
        3 38400455 40227618 1.5 630
        3 87486250 99283123 1.7 1313
        3 103293144 105808982 1.5 585
        3 133907470 134824678 1.6 275
        3 142561999 144085800 2.0 358
        4 993022 2306623 1.6 274
        4 24919726 25528576 1.5 227
        4 40139049 40975788 1.8 292
        4 83597896 84675832 1.8 305
        4 110417709 112302364 2.2 579
        5 41445603 50346406 1.5 897
        6 14761028 15598530 1.6 248
        6 41490909 42791039 2.6 446
        6 43072447 43781561 1.8 211
        6 104415386 105880754 1.6 382
        6 167075064 167580552 1.9 241
        7 7104066 7781184 1.5 340
        7 56292292 64412925 1.6 462
        7 75304244 76955460 1.7 343
        7 78529647 79724980 1.7 307
        7 121807619 125842423 2.6 1043
        7 141603981 142802391 1.5 343
        8 1998622 2668458 1.8 358
        8 6024489 6713422 2.0 496
        8 52109380 53365209 1.5 357
        8 55633098 57462102 1.7 510
        8 133263098 134094965 1.8 307
        8 141480770 142516105 1.9 261
        9 17018235 17894496 1.7 308
        9 79604583 81084044 2.2 513
        9 88494823 89174834 1.5 259
        9 90534113 91345966 1.7 237
        9 91419861 92619818 2.4 437
        9 109584228 110285669 1.6 309
        9 116811333 117994445 1.6 410
        9 128502416 130625694 2.8 536
        9 138191298 138844941 1.6 230
        10 12416983 13201247 2.3 473
        10 29808505 30856389 2.5 487
        10 126147900 126875149 1.8 336
        10 127245941 127839117 1.6 247
        10 129374492 130007110 1.9 303
        11 20615255 21340442 1.6 396
        11 21385711 22345607 1.8 330
        11 116026958 116813642 1.7 302
        11 126147537 127405311 2.3 403
        11 130985007 131893529 2.7 457
        12 8022225 9262599 2.9 342
        12 12974404 14366359 2.4 643
        12 15059492 15969517 1.6 257
        12 20842004 21862546 1.7 666
        12 74512097 76670076 2.8 638
        13 21997613 22567382 1.6 263
        14 30387385 31399822 1.8 204
        14 31617475 32403231 3.0 332
        14 91214828 92261636 1.9 451
        14 95978370 96683579 1.6 281
        15 35751177 36947159 2.3 423
        15 66800813 67858954 2.2 297
        15 79312374 80157846 1.8 240
        16 1074819 2806900 4.1 920
        16 5349852 5887603 2.3 298
        16 82413250 82853444 1.9 307
        17 4621145 5753252 2.7 451
        17 27115167 28345093 2.1 262
        18 5405501 6030997 2.3 322
        20 7573122 8375561 1.8 322
        20 50060701 51153829 1.6 394
        20 52134700 52688222 1.5 231
        20 60474346 61202072 1.9 247
        22 20392213 21193779 1.8 297
        22 26498252 27915080 1.5 299
        22 42758945 43150427 1.9 231
        Largest segment = 4.1 cM
        Total of segments > 1.5 cM = 169.8 cM
        ank you for all of the information you give so freely. Here are my results

    • There are two different studies that have maps of where autosomal DNA has been found. I copied some of the following from the map by Richard Stevens and some from what Felix has at http://www.y-str.org/p/ancient-dna.html


      La Braña Valdelugueros, León, Spain Mesolithic Hunter-Gatherer 7,000 ybp
      Oetzi Tyrolean Iceman Ötztal Alps, Italy Chalcolithic 5,300 ybp
      Gökhem2 Scandinavia Neolithic TRB farmer 5,000 ybp (Skoglund, Malmström et al. 2014)
      AJvide58 Eksta, Gotland, Sweden 5,000 ybp Mesolithic Skoglund et al;
      Mal’ta MA-1 South-Central Siberia 24,000 ybp Raghavan et al Nature (2013)
      Clovis Anzick Wilsall, Park County, Montana 12,600 ybp
      Saqqaq Palaeo-Eskimo Greenland 4,000 ybp Rasmussen et al. Feb 2010

      http://www.nature.com/nature/journal/v513/n7518/fig_tab/nature13673_F1.html
      Linearbandkeramik LBK Stuttgart, Germany Lazaridis et al Nature 513, 409–413 (2014).
      Loschbour Heffingen, Luxembourg Mesolithic Hunter-Gatherer 6220-5990 BC Lazaridis, I. et al. (2013)
      Motala12 Sweden Mesolithic Hunter-Gatherers 6000 BC Lazaridis, I. et al. (2013)

  3. Thanks, Roberta. I found far more matching DNA with this sample than with the others.

    Felix advised me to use a cut-off of 200 SNPs, 2cM, and 200 as the mismatch-bunching limit. Under those crieria, I got:
    Largest segment = 4.7 cM
    Total of segments > 2 cM = 181.0 cM

    In contrast, for La Braña, it was:
    Largest segment = 2.1 cM
    Total of segments > 2 cM = 2.1 cM
    That is, 1segment. Of course, I could get a lot more by lowering the cut-offs.

    The contrast is clear! Reckon we’re descended much more from these LBK folks than from the hunter-gatherers at La Braña and elsewhere. Not sure I would have chosen that, but there it is. Looking forward to trying more samples and seeing others’ results.

    • Hi Bonnie. I have similar results to you on my kit with same settings. Much more for the LBK and little on the La Brana and elsewhere.

      LBK:
      Largest segment = 5.9 cM
      Total of segments > 2 cM = 227.6 cM

      La Brana:
      Largest segment = 2.5 cM
      Total of segments > 2 cM = 7.1 cM

      Clovis:
      Largest segment = 3.4 cM
      Total of segments > 2 cM = 54.1 cM

  4. I am about half-way down LBK’s One-to-Many match list. Here’s my autosomal comparison, with reasonably high thresholds given that I’m running a comparison against ancient DNA:

    Comparing Kit A769393 (*ccollinsmith) and F999916 (Linearbandkeramik)

    Minimum threshold size to be included in total = 500 SNPs
    Mismatch-bunching Limit = 500 SNPs
    Minimum segment cM to be included in total = 2.0 cM

    Chr Start Location End Location Centimorgans (cM) SNPs
    5 11674007 14812246 3.7 593
    6 42816606 44750003 4.6 581
    11 40099920 42604974 2.1 586
    11 66599045 69054154 2.0 541
    14 20350588 21859955 6.9 522
    15 55818434 57376751 4.0 538
    Largest segment = 6.9 cM
    Total of segments > 2 cM = 23.4 cM

    Here’s my X-DNA comparison, using the same thresholds:

    Comparing Kit A769393 (*ccollinsmith)(F) and F999916 (Linearbandkeramik)(U)

    Minimum threshold size to be included in total = 500 SNPs
    Mismatch-bunching Limit = 500 SNPs
    Minimum segment cM to be included in total = 2.0 cM

    Chr Start Location End Location Centimorgans (cM) SNPs
    X 32490835 38524800 8.4 716
    Largest segment = 8.4 cM
    Total of segments > 2 cM = 8.4 cM Actual.

    My maternal aunt’s results are weird. If I run her at the same thresholds, she only gets one segment on the X and it does not overlap mine. If I run her at lower thresholds, though, she gets a larger segment than I do in the same location:

    Chr Start Location End Location Centimorgans (cM) SNPs
    X 32235686 38996765 10.7 839

    My direct maternal line is J1c4 (so, proven Middle Eastern Farmer ancestry), and from what I understand, J samples were found in an LBK site. My mother’s maternal grandparents came from Rostock, on the northeast Baltic German coast.

  5. If Felix is reading this, I wonder if he is going to prepare AJvide58 from Gotland, as based on Davidski’s admixture calculator, this is my top match, much better than LBK.

    BTW, I’m Irish from Ireland.

  6. Felix has a new SNP by SNP analysis of Clovis Anzick.
    http://www.fc.id.au/2014/10/clovis-anzick-dna-match-snp-by-snp.html
    Felix still believes that the ancient specimens from F999913 through F999918 are only 500-1,000 years old or have been contaminated. The admixture results of the specimens and of living people contradict his conclusion because the admixture results do not match living people even though the results of ‘One-to-many’ matches and ‘One-to-one’ compare do match living people. That matching is too close to living people for it not to show on admixture results if it was a recent specimen or contamination. The likelihood that 3 completely different studies all with erroneous radiocarbon dating or contamination and the different studies showing different admixture results in the studies themselves and in the Gedmatch calculators is extremely low. The Lazaridis study even compares the results of the other studies with his additional specimens. His Hunter-Gatherers match the La Braña Hunter-Gatherer closer than the LBK Stuttgart and the Chalcothic Ötzi the Iceman which are closer to each other and the Skoglund farmer. If they were all recent specimens from 1,000 years ago they would all have similar admixture since there had been so much population movement by that time all of the European specimens would have similar MDLP K23b or Eurogenes ANE K7 or Eurogenes K13 results. That isn’t happening. There is something happening with the ‘One-to-many’ matches and ‘One-to-one’ compare that isn’t understood by anyone but it is not possible that it proves all to those specimens to have erroneous radiocarbon dating or contamination. It is actually the other way around. The radiocarbon dating and the admixture results are proving that the ‘One-to-many’ matches and ‘One-to-one’ compare is erroneous when using ancient samples.

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