Abstract
Neanderthal ancestry remains across modern Eurasian genomes and introgressed sequences influence diverse phenotypes. Here, we demonstrate that introgressed sequences reintroduced thousands of ancestral alleles that were lost in Eurasian populations before introgression. Our simulations and variant effect predictions argue that these reintroduced alleles (RAs) are more likely to be tolerated by modern humans than are introgressed Neanderthal-derived alleles (NDAs) due to their distinct evolutionary histories. Consistent with this, we show enrichment for RAs and depletion for NDAs on introgressed haplotypes with expression quantitative trait loci (eQTL) and phenotype associations. Analysis of available cross-population eQTLs and massively parallel reporter assay data show that RAs commonly influence gene expression independent of linked NDAs. We further validate these independent effects for one RA in vitro. Finally, we demonstrate that NDAs are depleted for regulatory activity compared to RAs, while RAs have activity levels similar to non-introgressed variants. In summary, our study reveals that Neanderthal introgression reintroduced thousands of lost ancestral variants with gene regulatory activity and that these RAs were more tolerated than NDAs. Thus, RAs and their distinct evolutionary histories must be considered when evaluating the effects of introgression.
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Data availability
All results reported in this paper are available in supplementary material and/or on the project’s github repository (https://github.com/DaRinker/Neanderthal.reintroduction).
Code availability
Full code used in this analysis are available on the project’s github (https://github.com/DaRinker/Neanderthal.reintroduction).
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Acknowledgements
We thank B. Haller, P. Messer and K. Harris for advice on evolutionary simulations. We thank R. Tewhey for discussions of MPRA results. We thank L. Colbran and other members of the Capra Lab for helpful comments on the figures and manuscript. This work was supported by the National Institutes of Health grant nos. T32EY021453 to C.N.S., T32GM080178 to D.S., K22CA184308 to E.H. and R01GM115836 and R35GM127087 to J.A.C. This work was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University, Nashville, TN, USA.
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D.C.R., C.N.S., E.M. and J.A.C. conceived and conducted the computational analyses. D.S. and E.H. performed the luciferase assays. D.C.R. and J.A.C. wrote the manuscript with input from all authors.
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Extended data
Extended Data Fig. 1 Introgressed allele class assignment decision tree and allele count summary.
Decision tree by which 1000 Genomes variants in perfect LD with Neanderthal tag SNPs were classified as RAs and NDAs. The counts of variants making it to each of the numbered steps (1–5) is summarized in the lower table.
Extended Data Fig. 2 Evolutionary simulations suggest that RAs are common and more tolerated than NDAs.
a, The demographic model used to simulate human–Neanderthal admixture and quantify the reintroduction of lost alleles. The model and effective population sizes (Ne) were based on previous simulations of Neanderthal admixture. We considered models in which mutations incurred a fitness cost (mildly purifying selection) or no fitness cost (strict neutrality). Two different admixture fractions (f = 0.02 and f = 0.04) and three mutation rates were used in the simulations (Methods). b, The ratios of RAs to NDAs over 100 simulated Eurasian populations. The simulations predict approximately one RA for every two NDAs, and these estimates are robust to changes in the simulated Neanderthal admixture fraction. Misclassification of non-RAs as RAs due to independent, convergent mutations is extremely rare and the overall false discovery rate for LD-based RA identification is below ~1% (Supplementary Tables 3). While these forward-time simulations only approximate the demographic histories of these populations, the observed RA/NDAs ratio are qualitatively consistent with the simulations (Fig. 2). c, Boxplots summarize the frequencies of these potentially confounding NDAs among all sites that would be called as RAs at the time of admixture (c.f. Figure 1). The incidence of these confounding mutations is slightly higher under a purely neutral model (left) than under a model in which new mutations can be deleterious (right). d, Comparison of the effect of elevated mutation rates on the incidence of potentially confounding variants. Under a neutral model, the false positive rate scales with the mutation rate. The highest rate (μ= 7e-7) provides an estimate for CpG sites and results in a 3% false positive rate. Each boxplot represents 100 simulated populations. e, Selection coefficients in Eurasians from SLiM simulations with high (0.04) and low (0.02) admixture fractions. Each boxplot summarizes the average selection coefficient of all alleles in each introgressed class in each of 100 simulated modern Eurasian populations. The differences between the selection coefficients between RAs and NDAs is large and not dependent upon admixture fraction (~2.5×, P ≈ 0, Mann–Whitney U-test test).
Extended Data Fig. 3 Introgressed allele sharing across three Eurasian populations.
Venn diagram showing the fractions of each introgressed variant class that are shared between populations.
Extended Data Fig. 4 Reintroduced alleles cluster within introgressed Neanderthal haplotypes.
a, Scatter plot of the numbers of RAs and NDAs contained on all introgressed haplotypes in EUR. The correlation between the NDA and RA content is moderate (Pearson’s r2 = 0.46), with 18% of the haplotypes containing no RAs and 10% having more RAs than NDAs. b, Scatter plot of the number of introgressed variants on each haplotype versus haplotype length. The NDA content of a haplotype is proportional to its length (r2 = 0.85), but the number of RAs in each haplotype is less strongly correlated with length (r2 = 0.56). c, Heatmap of the fraction of NDAs and RAs in density percentiles (high to low, left to right) averaged over all introgressed Eurasian haplotypes. This information is summarized in a cumulative density function (CDF) above the heatmaps. A higher fraction of all RAs are found in the most dense percentiles; this reflects the fact that RAs are often present in more dense clusters than are NDAs.
Extended Data Fig. 5 Reintroduced alleles have different predicted fitness effects than Neanderthal-derived alleles.
a, In modern European (EUR) populations, RAs are predicted to be significantly less deleterious than NDAs by CADD (median scaled CADD: NDA=2.67; RA=2.1; P≈0). The upper tail of highly deleterious mutations (CADD score >10) is highlighted in the inset. Results are similar for unscaled scores. b, At the haplotype level, the maximum RA CADD score per introgressed haplotype is significantly lower than for NDAs (median scaled max CADD: NDA=13.3; RA=5.8; P≈0). This is in part due to the overall difference demonstrated in (a) and to the greater number of NDAs per haplotype. RAs are rarely the most deleterious variant per haplotype. Results in East Asian and South Asian populations are similar (data not shown).
Extended Data Fig. 6 PolyPhen2 predicts RAs to be less damaging than NDAs.
PolyPhen2 is more likely to classify RAs as ‘benign’ in all three Eurasian populations. Conversely, NDAs are more likely to be classified as ‘damaging’ in both EUR and SAS populations. The y-axis reports the difference in PolyPhen category membership for each population (that is, the fraction all RAs in the population in the PolyPhen category minus the fraction of all NDAs in population in the PolyPhen category). Per population hypergeometric test is calculated on the enrichment (positive delta) or depletion (negative delta) for RA content within each PolyPhen category.
Extended Data Fig. 7 Distribution of RegulomeDB scores among all introgressed Eurasian SNPs.
Comparison of the composition of NDAs and RAs within in each functional category of RegulomeDB. Boxplots refer to 1000 independently samples sets of background variiants matched on the allele frequency and local LD structure of the highest frequency Neanderthal tag SNP per introgressed EUR haplotype (Vernot 2016).
Extended Data Fig. 8 Comparison of allele frequencies across Eurasian populations.
Stratified by presence/absence of allele in modern sub-Saharan African populations. Reintroduced Ancestral Alleles (RAAs) that are also present in modern African (AFR) populations segregate at higher allele frequencies (AF) in all Eurasian populations than RAAs for which the allele is absent in AFR. Intra-population median differences in AF are displayed along with P values (Mann–Whitney U-test). Outliers are not shown. Circles indicate mean AF.
Extended Data Fig. 9 RA sublass composition of introgressed haplotypes containing GWAS hits.
The fraction of RAs among introgressed alleles on introgressed haplotypes in EUR that contain GWAS Catalog associations in Europeans versus introgressed haplotypes having no reported GWAS associations.
Extended Data Fig. 10 RA fraction in introgressed haplotypes containing eQTL in GTEx tissues.
Summary of the RA fraction among introgressed variants in Neanderthal haplotypes in Europeans (EUR). Boxplots show the distributions RA fractions of all haplotypes containing at least one introgressed eQTL (RA or NDA) in the given GTEx tissue (grey box plots). These distributions are then compared pairwise with distribution for introgressed haplotypes that contain no introgressed GTEx eQTL (top, blue boxplot; n = 4237). Haplotypes containing GTEx eQTL have RA contents higher than non-eQTL containing haplotypes in 46 tissues, with 34 of the tissues (*) having a significantly higher the RA fraction (P < 0.05, Mann–Whitney U-Test).
Supplementary information
Supplementary Information
Supplementary Tables 1–11.
Supplementary Data 1
List of NDAs and RAs for each Eurasian population.
Supplementary Data 2
Table of GWAS hits for NDAs and RAs.
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Rinker, D.C., Simonti, C.N., McArthur, E. et al. Neanderthal introgression reintroduced functional ancestral alleles lost in Eurasian populations. Nat Ecol Evol 4, 1332–1341 (2020). https://doi.org/10.1038/s41559-020-1261-z
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DOI: https://doi.org/10.1038/s41559-020-1261-z
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