Reconstructing the genetic history of late Neanderthals


New paper (behind paywall) Reconstructing the genetic history of late Neanderthals, by Mateja Hajdinjak, Qiaomei Fu, Alexander Hübner, et al. Nature (2018).

Abstract (edited):

Although it has previously been shown that Neanderthals contributed DNA to modern humans, not much is known about the genetic diversity of Neanderthals or the relationship between late Neanderthal populations at the time at which their last interactions with early modern humans occurred and before they eventually disappeared. Our ability to retrieve DNA from a larger number of Neanderthal individuals has been limited by poor preservation of endogenous DNA and contamination of Neanderthal skeletal remains by large amounts of microbial and present-day human DNA. Here we use hypochlorite treatment6 of as little as 9 mg of bone or tooth powder to generate between 1- and 2.7-fold genomic coverage of five Neanderthals who lived around 39,000 to 47,000 years ago (that is, late Neanderthals), thereby doubling the number of Neanderthals for which genome sequences are available. Genetic similarity among late Neanderthals is well predicted by their geographical location, and comparison to the genome of an older Neanderthal from the Caucasus indicates that a population turnover is likely to have occurred, either in the Caucasus or throughout Europe, towards the end of Neanderthal history. We find that the bulk of Neanderthal gene flow into early modern humans originated from one or more source populations that diverged from the Neanderthals that were studied here at least 70,000 years ago, but after they split from a previously sequenced Neanderthal from Siberia around 150,000 years ago. Although four of the Neanderthals studied here post-date the putative arrival of early modern humans into Europe, we do not detect any recent gene flow from early modern humans in their ancestry.

Phylogenetic relationships of late Neanderthals. a, Bayesian phylogenetic tree of mitochondrial genomes of 23 Neanderthals, 3 Denisovans, 64 modern humans and a hominin from Sima de los Huesos. The posterior probabilities for the branches are shown. b, Neighbour-joining tree of Y chromosome sequences of Mezmaiskaya 2, Spy 94a, 175 present-day humans21 and two present-day humans carrying the A00 haplogroup30. The number of substitutions is shown above the branches. c, Neighbour-joining tree of nuclear genomes based on autosomal transversions among late Neanderthals, Vindija 33.19, Mezmaiskaya 1, Altai Neanderthal, Denisovan and 12 present-day humans. Bootstrap support values after 1,000 replications are shown.

Interesting excerpts (edited):

(…) Mezmaiskaya 2 shared more derived alleles with the other late Neanderthals than with Mezmaiskaya 1 (− 2.13 ≤ Z ≤ − 9.56; Supplementary Information 9), suggesting that there was a population turnover towards the end of Neanderthal history. This turnover may have been the result of a population related to western Neanderthals replacing earlier Neanderthals in the Caucasus, or the replacement of Neanderthals in western Europe by a population related to Mezmaiskaya 2. The timing of this turnover coincides with pronounced climatic fluctuations during Marine Isotope Stage 3 between 60 and 24 ka, when extreme cold periods in northern Europe may have triggered the local extinction of Neanderthal populations and subsequent re-colonization from refugia in southern Europe or western Asia.

(…) the majority of gene flow into early modern humans appears to have originated from one or more Neanderthal populations that diverged from other late Neanderthals after their split from the Altai Neanderthal about 150 ka, but before the split from Mezmaiskaya 1 at least 90 ka. Owing to the scarcity of overlapping genetic data from Oase 1, whose genome revealed an unusually high percentage of Neanderthal ancestry11, we were unable to resolve whether one of these late Neanderthals was significantly closer than others to the introgressing Neanderthal in Oase 1.

Interbreeding between Neanderthals and early modern humans is likely to have occurred intermittently, presumably resulting in gene flow in both directions. However, when we applied an approach that uses the extended length of haplotypes expected from recent introgression into the analysed late Neanderthals, we did not find any indications of recent gene flow from early modern humans to the late Neanderthals. We caution that given the small number of analysed Neanderthals we cannot exclude that such gene flow occurred. However, it is striking that Oase 1, one of two early modern humans that overlapped in time with late Neanderthals, showed evidence for recent additional Neanderthal introgression whereas none of the late Neanderthals analysed here do. This may indicate that gene flow affected the ancestry of modern human populations more than it did Neanderthals


Genomics reveals four prehistoric migration waves into South-East Asia

Open access preprint article at bioRxiv Ancient Genomics Reveals Four Prehistoric Migration Waves into Southeast Asia, by McColl, Racimo, Vinner, et al. (2018).

Abstract (emphasis mine):

Two distinct population models have been put forward to explain present-day human diversity in Southeast Asia. The first model proposes long-term continuity (Regional Continuity model) while the other suggests two waves of dispersal (Two Layer model). Here, we use whole-genome capture in combination with shotgun sequencing to generate 25 ancient human genome sequences from mainland and island Southeast Asia, and directly test the two competing hypotheses. We find that early genomes from Hoabinhian hunter-gatherer contexts in Laos and Malaysia have genetic affinities with the Onge hunter-gatherers from the Andaman Islands, while Southeast Asian Neolithic farmers have a distinct East Asian genomic ancestry related to present-day Austroasiatic-speaking populations. We also identify two further migratory events, consistent with the expansion of speakers of Austronesian languages into Island Southeast Asia ca. 4 kya, and the expansion by East Asians into northern Vietnam ca. 2 kya. These findings support the Two Layer model for the early peopling of Southeast Asia and highlight the complexities of dispersal patterns from East Asia.

A model for plausible migration routes into Southeast Asia, based on the ancestry patterns observed in the ancient genomes.


Indo-European pastoralists healthier than modern populations? Genomic health improving over time


A new paper has appeared at BioRxiv, The Genomic Health Of Ancient Hominins (2017) by Berence, Cooper and Lachance.

Important results are available at:

While the study’s many limitations are obvious to the authors, they still suggest certain interesting possibilities as the most important conclusions:

  • In general, Genetic risk scores (GRS) are similar to present-day individuals
  • Genomic health seems to be improving over time
  • Pastoralists could have been healthier than older and modern populations

Some details and shortcomings of the study (most stated by them, bold is from me) include:

  • Allele selection: only some of the known autosomal disease-associated SNPs were included
  • Discovered disease-associated SNPs are known to be biased toward European diseases
  • Ancient sample selection and genomic quality: only 147 ancient genomes were included, from 449 available, with a conventional cut made at 50% of the focal 3180 disease-associated loci. These samples did not include the same loci. All this can affect whether an individual has high or low GRS (a relationship was found between GRS percentiles and sequencing coverage for ancient samples).
  • Phase 3 of the 1000 Genomes Project was used. However, many disease alleles that segregated in the past remain undiscovered – therefore, GRS for ancient individuals should be considered to be underestimated.
  • Genetic risk scores were calculated for each individual (with different sets of disease-associated loci), hence they were not comparable across individuals. So GRS were standardized as GRS percentiles, with certain assumptions, comparing them to modern individuals
  • Multiple comparisons with all data available, using multiple groups, in the small sample selected: comparisons were made between standardized GRS percentile, sample age (i.e. estimated date), mode of subsistance, and geographic location.
  • Older samples have worse coverage, especially Altai Neandertal, Ust’-Ishim, and Denisovan (which might influence results in hunter-gatherers)
  • Northern ancient individuals (using latitude values) show healthier genomes: but, most ancient individuals are from Eurasia, and samples are heterogeneous.
  • Agriculturalists show a higher genetic risk for dental/periodontal diseases than hunger-gatherers and pastoralists. However, this disease has the smallest number of risk loci (k = 40), so risk in older samples might be underestimated, and pastoralists are the more recent agriculturalist population (most used agriculture as a complementary diet), so it is only natural that selection had an impact over time in this aspect.
  • Pastoralists have the smallest sample size (19 samples) and geographic range, so conclusions about this group are still less trustworthy.
  • Genetic risk percentile ≠ Genomic health ≠ phenotypic health (not deterministic), and also disease-associated alleles in modern populations ≠ same effects in past environments.

To sum up, an interesting approach to studying genomic health with the scarce data available, but too many comparisons, with too many hypotheses being tested, which remind to a brute-force attack on data that can therefore yield statistically significant results anytime, anywhere.