Post by Admin on May 17, 2022 17:55:30 GMT
Genetic trait reconstruction and the phenotypic legacy of ancient Europeans
When comparing modern European genomes in the UK Biobank to ancient Europeans, we find strong differentiation at certain sets of trait-associated variants, and differential contribution of different ancestry groups to various traits. We reconstructed polygenic scores for phenotypes in ancient individuals, using effect size estimates obtained from GWASs performed using the >400,000 UK Biobank genomes 107 (http://www.nealelab.is/uk-biobank) and looked for overdispersion among these scores across ancient populations, beyond what would be expected under a null model of genetic drift 194 (Supplementary Note 4c). We stress that polygenic scores and QX statistic may both be affected by population stratification, so these results should be interpreted with caution 195–198. The most significantly overdispersed scores are for variants associated with pigmentation, anthropometric differences and disorders related to diet and sugar levels, including diabetes (Fig. 9). We also find psychological trait scores with evidence for overdispersion related to mood instability and irritability, with Western Hunter-gatherers generally showing smaller genetic scores for these traits than Neolithic Farmers. Intriguingly, we find highly inconsistent predictions of height based on polygenic scores in western hunter-gatherer and Siberian groups computed using effect sizes estimated from two different - yet largely overlapping - GWAS cohorts (Supplementary Note 4c), highlighting how sensitive polygenic score predictions are to the choice of cohort, particularly when ancient populations are genetically divergent from the reference GWAS cohort198. Taking this into account, we do observe that the Eastern hunter-gatherer and individuals associated with the Yamnaya culture have consistently high genetic values for height, which in turn contribute to stature increases in Bronze Age Europe, relative to the earlier Neolithic populations45,80,199.
We performed an additional analysis to examine the data for strong alignments between axes of trait-association 200 and ancestry gradients, rather than relying on particular choices for population clusters (Supplementary Note 4e). Along the population structure axis separating ancient East Asian and Siberian genomes from Steppe and Western European genomes (Fig. 1), we find significant correlations with trait-association components related to impedance, body measurements, blood measurements, eye measurement and skin disorders. Along the axis separating Mesolithic hunter-gatherers from Anatolian and Neolithic farmer individuals, we find significant correlations with trait-association components related to skin disorders, diet and lifestyle traits, mental health status, and spirometry-related traits (Fig. 9). Our findings show that these phenotypes were genetically different among ancient groups with very different lifestyles. However, we note that the realised value of these traits is highly dependent on environmental factors and gene-environment interactions, which we do not model in this analysis.
In addition to the above reconstructions of genetic traits among the ancient individuals, we also estimated the contribution from different ancestral populations (EHG, CHG, WHG, Yamnaya and Anatolian farmer) to variation in polygenic phenotypes in present-day individuals, leveraging the exceptional resolution offered by the UK Biobank genomes 107 to investigate this. We calculated ancestry-specific polygenic risk scores based on the chromosome painting of the >400,000 UKB genomes (Supplementary Note 4h); this allowed us to identify if any of the ancient ancestry components were over-represented in modern UK populations at loci significantly associated with a given trait, and also avoids exporting risk scores over space and time. Working with large numbers of imputed ancient genomes provides high statistical power to use ancient populations as “ancestral sources”. We focused on phenotypes whose polygenic scores were significantly over-dispersed in the ancient populations (Supplementary Note 4c), as well as a single high effect variant, ApoE4, known to be a significant risk factor in Alzheimer’s Disease (201, 202). We emphasise that this approach makes no reference to ancient phenotypes but describes how these ancestries contributed to the modern genetic landscape. In light of the ancestry gradients within the British Isles and Eurasia (Fig. 5), these results support the hypothesis that ancestry-mediated geographic variation in disease risks and phenotypes is commonplace. It points to a way forward for disentangling how ancestry contributed to differences in risk of genetic disease – including metabolic and mental health disorders – between present-day populations.
Taken together, these analyses help to settle the famous discussion of selection in Europe relating to height 45, 80, 203. The finding that steppe individuals have consistently high genetic values for height (Supplementary Note 4c), is mirrored by the UK Biobank results, which find that the ‘Steppe’ ancestral components (Yamnaya/EHG) contributed to increased height in present-day populations (Supplementary Note 4h). This shows that the height differences in Europe between north and south may not be due to selection, as claimed in many previous studies, but may be a consequence of differential ancestry.
Likewise, European hunter gatherers are genetically predicted to have dark skin pigmentation and dark brown hair 11, 20, 21, 79, 83, 168, 204, 205, and indeed we see that the WHG, EHG and CHG components contributed to these phenotypes in present-day individuals whereas the Yamnaya and Anatolian farmer ancestry contributed to light brown/blonde hair pigmentation (Supplementary Note 4h). Interestingly, loci associated with overdispersed mood-related polygenic phenotypes recorded among the UK Biobank individuals (like increased anxiety, guilty feelings, and irritability) showed an overrepresentation of the Anatolian farmer ancestry component; and the WHG component showed a strikingly high contribution to traits related to diabetes. We also found that the ApoE4 effect allele is preferentially found on a WHG/EHG haplotypic background, suggesting it likely was brought to western Europe by early hunter-gatherers (Supplementary Note 4h). This is in line with the present-day European distribution of this allele, which is highest in north-eastern Europe, where the proportion of these ancestries are higher than in other regions of the continent 206.
Conclusion
Our study has provided fundamental new insights into one of the most transformative periods of human biological and cultural evolution. We have demonstrated that a clear east-west division known from Stone Age material culture, extending from the Black Sea to the Baltic and persisting across several millennia, was genetically deeply rooted in populations with different ancestries. We showed that the genetic impact of the Neolithic transition was highly distinct, east and west of this boundary. We have identified a hitherto unknown source of ancestry in hunter-gatherers from the Middle Don region contributing ancestry to the Yamnaya pastoralists, and we have documented how the later spread of steppe-related ancestry into Europe was very rapid and mediated through admixture with people from the Globular Amphora Culture. Additionally, we have observed two near-complete population replacements in Denmark within just 1,000 years, concomitantly with major changes in material culture, which rules out cultural diffusion as a main driver and settles generation-long archaeological debates. Our analyses revealed that the ability to detect signatures of natural selection in modern human genomes is drastically limited by conflicting selection pressures in different ancestral populations masking the signals. Developing methods to trace selection in individual ancestry components allowed us to effectively double the number of significant selection peaks, which helped clarify the trajectories of a number of traits related to diet and lifestyle. Our results emphasise how the interplay between major ancient selection and admixture events occurring across Europe and Asia in the Stone and Bronze Ages have profoundly shaped patterns of genetic variation in modern human populations.
Data availability
All collapsed and paired-end sequence data for novel samples sequenced in this study will be made publicly available on the European Nucleotide Archive, together with trimmed sequence alignment map files, aligned using human build GRCh37. Previously published ancient genomic data used in this study is detailed in Supplementary Table VII, and are all already publicly available
When comparing modern European genomes in the UK Biobank to ancient Europeans, we find strong differentiation at certain sets of trait-associated variants, and differential contribution of different ancestry groups to various traits. We reconstructed polygenic scores for phenotypes in ancient individuals, using effect size estimates obtained from GWASs performed using the >400,000 UK Biobank genomes 107 (http://www.nealelab.is/uk-biobank) and looked for overdispersion among these scores across ancient populations, beyond what would be expected under a null model of genetic drift 194 (Supplementary Note 4c). We stress that polygenic scores and QX statistic may both be affected by population stratification, so these results should be interpreted with caution 195–198. The most significantly overdispersed scores are for variants associated with pigmentation, anthropometric differences and disorders related to diet and sugar levels, including diabetes (Fig. 9). We also find psychological trait scores with evidence for overdispersion related to mood instability and irritability, with Western Hunter-gatherers generally showing smaller genetic scores for these traits than Neolithic Farmers. Intriguingly, we find highly inconsistent predictions of height based on polygenic scores in western hunter-gatherer and Siberian groups computed using effect sizes estimated from two different - yet largely overlapping - GWAS cohorts (Supplementary Note 4c), highlighting how sensitive polygenic score predictions are to the choice of cohort, particularly when ancient populations are genetically divergent from the reference GWAS cohort198. Taking this into account, we do observe that the Eastern hunter-gatherer and individuals associated with the Yamnaya culture have consistently high genetic values for height, which in turn contribute to stature increases in Bronze Age Europe, relative to the earlier Neolithic populations45,80,199.
We performed an additional analysis to examine the data for strong alignments between axes of trait-association 200 and ancestry gradients, rather than relying on particular choices for population clusters (Supplementary Note 4e). Along the population structure axis separating ancient East Asian and Siberian genomes from Steppe and Western European genomes (Fig. 1), we find significant correlations with trait-association components related to impedance, body measurements, blood measurements, eye measurement and skin disorders. Along the axis separating Mesolithic hunter-gatherers from Anatolian and Neolithic farmer individuals, we find significant correlations with trait-association components related to skin disorders, diet and lifestyle traits, mental health status, and spirometry-related traits (Fig. 9). Our findings show that these phenotypes were genetically different among ancient groups with very different lifestyles. However, we note that the realised value of these traits is highly dependent on environmental factors and gene-environment interactions, which we do not model in this analysis.
In addition to the above reconstructions of genetic traits among the ancient individuals, we also estimated the contribution from different ancestral populations (EHG, CHG, WHG, Yamnaya and Anatolian farmer) to variation in polygenic phenotypes in present-day individuals, leveraging the exceptional resolution offered by the UK Biobank genomes 107 to investigate this. We calculated ancestry-specific polygenic risk scores based on the chromosome painting of the >400,000 UKB genomes (Supplementary Note 4h); this allowed us to identify if any of the ancient ancestry components were over-represented in modern UK populations at loci significantly associated with a given trait, and also avoids exporting risk scores over space and time. Working with large numbers of imputed ancient genomes provides high statistical power to use ancient populations as “ancestral sources”. We focused on phenotypes whose polygenic scores were significantly over-dispersed in the ancient populations (Supplementary Note 4c), as well as a single high effect variant, ApoE4, known to be a significant risk factor in Alzheimer’s Disease (201, 202). We emphasise that this approach makes no reference to ancient phenotypes but describes how these ancestries contributed to the modern genetic landscape. In light of the ancestry gradients within the British Isles and Eurasia (Fig. 5), these results support the hypothesis that ancestry-mediated geographic variation in disease risks and phenotypes is commonplace. It points to a way forward for disentangling how ancestry contributed to differences in risk of genetic disease – including metabolic and mental health disorders – between present-day populations.
Taken together, these analyses help to settle the famous discussion of selection in Europe relating to height 45, 80, 203. The finding that steppe individuals have consistently high genetic values for height (Supplementary Note 4c), is mirrored by the UK Biobank results, which find that the ‘Steppe’ ancestral components (Yamnaya/EHG) contributed to increased height in present-day populations (Supplementary Note 4h). This shows that the height differences in Europe between north and south may not be due to selection, as claimed in many previous studies, but may be a consequence of differential ancestry.
Likewise, European hunter gatherers are genetically predicted to have dark skin pigmentation and dark brown hair 11, 20, 21, 79, 83, 168, 204, 205, and indeed we see that the WHG, EHG and CHG components contributed to these phenotypes in present-day individuals whereas the Yamnaya and Anatolian farmer ancestry contributed to light brown/blonde hair pigmentation (Supplementary Note 4h). Interestingly, loci associated with overdispersed mood-related polygenic phenotypes recorded among the UK Biobank individuals (like increased anxiety, guilty feelings, and irritability) showed an overrepresentation of the Anatolian farmer ancestry component; and the WHG component showed a strikingly high contribution to traits related to diabetes. We also found that the ApoE4 effect allele is preferentially found on a WHG/EHG haplotypic background, suggesting it likely was brought to western Europe by early hunter-gatherers (Supplementary Note 4h). This is in line with the present-day European distribution of this allele, which is highest in north-eastern Europe, where the proportion of these ancestries are higher than in other regions of the continent 206.
Conclusion
Our study has provided fundamental new insights into one of the most transformative periods of human biological and cultural evolution. We have demonstrated that a clear east-west division known from Stone Age material culture, extending from the Black Sea to the Baltic and persisting across several millennia, was genetically deeply rooted in populations with different ancestries. We showed that the genetic impact of the Neolithic transition was highly distinct, east and west of this boundary. We have identified a hitherto unknown source of ancestry in hunter-gatherers from the Middle Don region contributing ancestry to the Yamnaya pastoralists, and we have documented how the later spread of steppe-related ancestry into Europe was very rapid and mediated through admixture with people from the Globular Amphora Culture. Additionally, we have observed two near-complete population replacements in Denmark within just 1,000 years, concomitantly with major changes in material culture, which rules out cultural diffusion as a main driver and settles generation-long archaeological debates. Our analyses revealed that the ability to detect signatures of natural selection in modern human genomes is drastically limited by conflicting selection pressures in different ancestral populations masking the signals. Developing methods to trace selection in individual ancestry components allowed us to effectively double the number of significant selection peaks, which helped clarify the trajectories of a number of traits related to diet and lifestyle. Our results emphasise how the interplay between major ancient selection and admixture events occurring across Europe and Asia in the Stone and Bronze Ages have profoundly shaped patterns of genetic variation in modern human populations.
Data availability
All collapsed and paired-end sequence data for novel samples sequenced in this study will be made publicly available on the European Nucleotide Archive, together with trimmed sequence alignment map files, aligned using human build GRCh37. Previously published ancient genomic data used in this study is detailed in Supplementary Table VII, and are all already publicly available