The genomic history of the Aegean palatial civilizations.

The Cycladic, the Minoan, and the Helladic (Mycenaean) cultures define the Bronze Age (BA) of Greece. Urbanism, complex social structures, craft and agricultural specialization, and the earliest forms of writing characterize this iconic period. We sequenced six Early to Middle BA whole genomes, along with 11 mitochondrial genomes, sampled from the three BA cultures of the Aegean Sea. The Early BA (EBA) genomes are homogeneous and derive most of their ancestry from Neolithic Aegeans, contrary to earlier hypotheses that the Neolithic-EBA cultural transition was due to massive population turnover. EBA Aegeans were shaped by relatively small-scale migration from East of the Aegean, as evidenced by the Caucasus-related ancestry also detected in Anatolians. In contrast, Middle BA (MBA) individuals of northern Greece differ from EBA populations in showing ∼50% Pontic-Caspian Steppe-related ancestry, dated at ca. 2,600-2,000 BCE. Such gene flow events during the MBA contributed toward shaping present-day Greek genomes.

Harnessing deep learning for population genetic inference.

In population genetics, the emergence of large-scale genomic data for various species and populations has provided new opportunities to understand the evolutionary forces that drive genetic diversity using statistical inference. However, the era of population genomics presents new challenges in analysing the massive amounts of genomes and variants. Deep learning has demonstrated state-of-the-art performance for numerous applications involving large-scale data. Recently, deep learning approaches have gained popularity in population genetics; facilitated by the advent of massive genomic data sets, powerful computational hardware and complex deep learning architectures, they have been used to identify population structure, infer demographic history and investigate natural selection. Here, we introduce common deep learning architectures and provide comprehensive guidelines for implementing deep learning models for population genetic inference. We also discuss current challenges and future directions for applying deep learning in population genetics, focusing on efficiency, robustness and interpretability.

Evolutionary and functional analyses of LRP5 in archaic and extant modern humans.

BACKGROUND: The human lineage has undergone a postcranial skeleton gracilization (i.e. lower bone mass and strength relative to body size) compared to other primates and archaic populations such as the Neanderthals. This gracilization has been traditionally explained by differences in the mechanical load that our ancestors exercised. However, there is growing evidence that gracilization could also be genetically influenced. RESULTS: We have analyzed the LRP5 gene, which is known to be associated with high bone mineral density conditions, from an evolutionary and functional point of view. Taking advantage of the published genomes of archaic Homo populations, our results suggest that this gene has a complex evolutionary history both between archaic and living humans and within living human populations. In particular, we identified the presence of different selective pressures in archaics and extant modern humans, as well as evidence of positive selection in the African and South East Asian populations from the 1000 Genomes Project. Furthermore, we observed a very limited evidence of archaic introgression in this gene (only at three haplotypes of East Asian ancestry out of the 1000 Genomes), compatible with a general erasing of the fingerprint of archaic introgression due to functional differences in archaics compared to extant modern humans. In agreement with this hypothesis, we observed private mutations in the archaic genomes that we experimentally validated as putatively increasing bone mineral density. In particular, four of five archaic missense mutations affecting the first ß-propeller of LRP5 displayed enhanced Wnt pathway activation, of which two also displayed reduced negative regulation. CONCLUSIONS: In summary, these data suggest a genetic component contributing to the understanding of skeletal differences between extant modern humans and archaic Homo populations.

A genomic history of Aboriginal Australia.

The population history of Aboriginal Australians remains largely uncharacterized. Here we generate high-coverage genomes for 83 Aboriginal Australians (speakers of Pama-Nyungan languages) and 25 Papuans from the New Guinea Highlands. We find that Papuan and Aboriginal Australian ancestors diversified 25-40 thousand years ago (kya), suggesting pre-Holocene population structure in the ancient continent of Sahul (Australia, New Guinea and Tasmania). However, all of the studied Aboriginal Australians descend from a single founding population that differentiated ~10-32 kya. We infer a population expansion in northeast Australia during the Holocene epoch (past 10,000 years) associated with limited gene flow from this region to the rest of Australia, consistent with the spread of the Pama-Nyungan languages. We estimate that Aboriginal Australians and Papuans diverged from Eurasians 51-72 kya, following a single out-of-Africa dispersal, and subsequently admixed with archaic populations. Finally, we report evidence of selection in Aboriginal Australians potentially associated with living in the desert.

BMD Loci Contribute to Ethnic and Developmental Differences in Skeletal Fragility across Populations: Assessment of Evolutionary Selection Pressures.

Bone mineral density (BMD) is a highly heritable trait used both for the diagnosis of osteoporosis in adults and to assess bone health in children. Ethnic differences in BMD have been documented, with markedly higher levels in individuals of African descent, which partially explain disparity in osteoporosis risk across populations. To date, 63 independent genetic variants have been associated with BMD in adults of Northern-European ancestry. Here, we demonstrate that at least 61 of these variants are predictive of BMD early in life by studying their compound effect within two multiethnic pediatric cohorts. Furthermore, we show that within these cohorts and across populations worldwide the frequency of those alleles associated with increased BMD is systematically elevated in individuals of Sub-Saharan African ancestry. The amount of differentiation in the BMD genetic scores among Sub-Saharan and non-Sub-Saharan populations together with neutrality tests, suggest that these allelic differences are compatible with the hypothesis of selective pressures acting on the genetic determinants of BMD. These findings constitute an explorative contribution to the role of selection on ethnic BMD differences and likely a new example of polygenic adaptation acting on a human trait.

Genetics of skin color variation in Europeans: genome-wide association studies with functional follow-up.

In the International Visible Trait Genetics (VisiGen) Consortium, we investigated the genetics of human skin color by combining a series of genome-wide association studies (GWAS) in a total of 17,262 Europeans with functional follow-up of discovered loci. Our GWAS provide the first genome-wide significant evidence for chromosome 20q11.22 harboring the ASIP gene being explicitly associated with skin color in Europeans. In addition, genomic loci at 5p13.2 (SLC45A2), 6p25.3 (IRF4), 15q13.1 (HERC2/OCA2), and 16q24.3 (MC1R) were confirmed to be involved in skin coloration in Europeans. In follow-up gene expression and regulation studies of 22 genes in 20q11.22, we highlighted two novel genes EIF2S2 and GSS, serving as competing functional candidates in this region and providing future research lines. A genetically inferred skin color score obtained from the 9 top-associated SNPs from 9 genes in 940 worldwide samples (HGDP-CEPH) showed a clear gradual pattern in Western Eurasians similar to the distribution of physical skin color, suggesting the used 9 SNPs as suitable markers for DNA prediction of skin color in Europeans and neighboring populations, relevant in future forensic and anthropological investigations.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans.

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

A genome-wide association study identifies five loci influencing facial morphology in Europeans.

Inter-individual variation in facial shape is one of the most noticeable phenotypes in humans, and it is clearly under genetic regulation; however, almost nothing is known about the genetic basis of normal human facial morphology. We therefore conducted a genome-wide association study for facial shape phenotypes in multiple discovery and replication cohorts, considering almost ten thousand individuals of European descent from several countries. Phenotyping of facial shape features was based on landmark data obtained from three-dimensional head magnetic resonance images (MRIs) and two-dimensional portrait images. We identified five independent genetic loci associated with different facial phenotypes, suggesting the involvement of five candidate genes--PRDM16, PAX3, TP63, C5orf50, and COL17A1--in the determination of the human face. Three of them have been implicated previously in vertebrate craniofacial development and disease, and the remaining two genes potentially represent novel players in the molecular networks governing facial development. Our finding at PAX3 influencing the position of the nasion replicates a recent GWAS of facial features. In addition to the reported GWA findings, we established links between common DNA variants previously associated with NSCL/P at 2p21, 8q24, 13q31, and 17q22 and normal facial-shape variations based on a candidate gene approach. Overall our study implies that DNA variants in genes essential for craniofacial development contribute with relatively small effect size to the spectrum of normal variation in human facial morphology. This observation has important consequences for future studies aiming to identify more genes involved in the human facial morphology, as well as for potential applications of DNA prediction of facial shape such as in future forensic applications.

PHOX2B polyalanine repeat length is associated with sudden infant death syndrome and unclassified sudden infant death in the Dutch population.

Unclassified sudden infant death (USID) is the sudden and unexpected death of an infant that remains unexplained after thorough case investigation including performance of a complete autopsy and review of the circumstances of death and the clinical history. When the infant is below 1 year of age and with onset of the fatal episode apparently occurring during sleep, this is referred to as sudden infant death syndrome (SIDS). USID and SIDS remain poorly understood despite the identification of several environmental and some genetic risk factors. In this study, we investigated genetic risk factors involved in the autonomous nervous system in 195 Dutch USID/SIDS cases and 846 Dutch, age-matched healthy controls. Twenty-five DNA variants from 11 genes previously implicated in the serotonin household or in the congenital central hypoventilation syndrome, of which some have been associated with SIDS before, were tested. Of all DNA variants considered, only the length variation of the polyalanine repeat in exon 3 of the PHOX2B gene was found to be statistically significantly associated with USID/SIDS in the Dutch population after multiple test correction. Interestingly, our data suggest that contraction of the PHOX2B exon 3 polyalanine repeat that we found in six of 160 SIDS and USID cases and in six of 814 controls serves as a probable genetic risk factor for USID/SIDS at least in the Dutch population. Future studies are needed to confirm this finding and to understand the functional effect of the polyalanine repeat length variation, in particular contraction, in exon 3 of the PHOX2B gene.

Implications of population history of European Romani on genetic susceptibility to disease.

OBJECTIVES: The population history of European Romani is characterized by extensive bottleneck and admixture events, but the impact of this unique demographic history on the genetic risk for disease remains unresolved. METHODS: Genome-wide SNP data on Romani, non-Romani Europeans and Indians were analyzed. The excess of homozygous variants in Romani genomes was assessed according to their potential functional effect. We also explored the frequencies of risk variants associated with five common diseases which are present at an increased prevalence in Romani compared to other Europeans. RESULTS: Slightly deleterious variants are present at increased frequencies in European Romani, likely a result of relaxed purifying selection due to bottlenecks in their population history. The frequencies of SNPs associated with common metabolic and cardiovascular diseases are also increased compared to their European hosts. CONCLUSIONS: As observed in other founder populations, we confirm the impact of bottlenecks on the abundance of slightly deleterious variants in Romani groups, probably including metabolic and cardiovascular risk variants.

Modelling the demographic history of human North African genomes points to a recent soft split divergence between populations.

BACKGROUND: North African human populations present a complex demographic scenario due to the presence of an autochthonous genetic component and population substructure, plus extensive gene flow from the Middle East, Europe, and sub-Saharan Africa. RESULTS: We conducted a comprehensive analysis of 364 genomes to construct detailed demographic models for the North African region, encompassing its two primary ethnic groups, the Arab and Amazigh populations. This was achieved through an Approximate Bayesian Computation with Deep Learning (ABC-DL) framework and a novel algorithm called Genetic Programming for Population Genetics (GP4PG). This innovative approach enabled us to effectively model intricate demographic scenarios, utilizing a subset of 16 whole genomes at > 30X coverage. The demographic model suggested by GP4PG exhibited a closer alignment with the observed data compared to the ABC-DL model. Both point to a back-to-Africa origin of North African individuals and a close relationship with Eurasian populations. Results support different origins for Amazigh and Arab populations, with Amazigh populations originating back in Epipaleolithic times, while GP4PG supports Arabization as the main source of Middle Eastern ancestry. The GP4PG model includes population substructure in surrounding populations (sub-Saharan Africa and Middle East) with continuous decaying gene flow after population split. Contrary to ABC-DL, the best GP4PG model does not require pulses of admixture from surrounding populations into North Africa pointing to soft splits as drivers of divergence in North Africa. CONCLUSIONS: We have built a demographic model on North Africa that points to a back-to-Africa expansion and a differential origin between Arab and Amazigh populations.

Genetic ancestry in population pharmacogenomics unravels distinct geographical patterns related to drug toxicity.

Genetic ancestry plays a major role in pharmacogenomics, and a deeper understanding of the genetic diversity among individuals holds immerse promise for reshaping personalized medicine. In this pivotal study, we have conducted a large-scale genomic analysis of 1,136 pharmacogenomic variants employing machine learning algorithms on 3,714 individuals from publicly available datasets to assess the risk proximity of experiencing drug-related adverse events. Our findings indicate that Admixed Americans and Europeans have demonstrated a higher risk of experiencing drug toxicity, whereas individuals with East Asian ancestry and, to a lesser extent, Oceanians displayed a lower risk proximity. Polygenic risk scores for drug-gene interactions did not necessarily follow similar assumptions, reflecting distinct genetic patterns and population-specific differences that vary depending on the drug class. Overall, our results provide evidence that genetic ancestry is a pivotal factor in population pharmacogenomics and should be further exploited to strengthen even more personalized drug therapy.

Comprehensive candidate gene study highlights UGT1A and BNC2 as new genes determining continuous skin color variation in Europeans.

Natural variation in human skin pigmentation is primarily due to genetic causes rooted in recent evolutionary history. Genetic variants associated with human skin pigmentation confer risk of skin cancer and may provide useful information in forensic investigations. Almost all previous gene-mapping studies of human skin pigmentation were based on categorical skin color information known to oversimplify the continuous nature of human skin coloration. We digitally quantified skin color into hue and saturation dimensions for 5,860 Dutch Europeans based on high-resolution skin photographs. We then tested an extensive list of 14,185 single nucleotide polymorphisms in 281 candidate genes potentially involved in human skin pigmentation for association with quantitative skin color phenotypes. Confirmatory association was revealed for several known skin color genes including HERC2, MC1R, IRF4, TYR, OCA2, and ASIP. We identified two new skin color genes: genetic variants in UGT1A were significantly associated with hue and variants in BNC2 were significantly associated with saturation. Overall, digital quantification of human skin color allowed detecting new skin color genes. The variants identified in this study may also contribute to the risk of skin cancer. Our findings are also important for predicting skin color in forensic investigations.

Mutability of Y-chromosomal microsatellites: rates, characteristics, molecular bases, and forensic implications.

Nonrecombining Y-chromosomal microsatellites (Y-STRs) are widely used to infer population histories, discover genealogical relationships, and identify males for criminal justice purposes. Although a key requirement for their application is reliable mutability knowledge, empirical data are only available for a small number of Y-STRs thus far. To rectify this, we analyzed a large number of 186 Y-STR markers in nearly 2000 DNA-confirmed father-son pairs, covering an overall number of 352,999 meiotic transfers. Following confirmation by DNA sequence analysis, the retrieved mutation data were modeled via a Bayesian approach, resulting in mutation rates from 3.78 × 10(-4) (95% credible interval [CI], 1.38 × 10(-5) - 2.02 × 10(-3)) to 7.44 × 10(-2) (95% CI, 6.51 × 10(-2) - 9.09 × 10(-2)) per marker per generation. With the 924 mutations at 120 Y-STR markers, a nonsignificant excess of repeat losses versus gains (1.16:1), as well as a strong and significant excess of single-repeat versus multirepeat changes (25.23:1), was observed. Although the total repeat number influenced Y-STR locus mutability most strongly, repeat complexity, the length in base pairs of the repeated motif, and the father's age also contributed to Y-STR mutability. To exemplify how to practically utilize this knowledge, we analyzed the 13 most mutable Y-STRs in an independent sample set and empirically proved their suitability for distinguishing close and distantly related males. This finding is expected to revolutionize Y-chromosomal applications in forensic biology, from previous male lineage differentiation toward future male individual identification.

Digital quantification of human eye color highlights genetic association of three new loci.

Previous studies have successfully identified genetic variants in several genes associated with human iris (eye) color; however, they all used simplified categorical trait information. Here, we quantified continuous eye color variation into hue and saturation values using high-resolution digital full-eye photographs and conducted a genome-wide association study on 5,951 Dutch Europeans from the Rotterdam Study. Three new regions, 1q42.3, 17q25.3, and 21q22.13, were highlighted meeting the criterion for genome-wide statistically significant association. The latter two loci were replicated in 2,261 individuals from the UK and in 1,282 from Australia. The LYST gene at 1q42.3 and the DSCR9 gene at 21q22.13 serve as promising functional candidates. A model for predicting quantitative eye colors explained over 50% of trait variance in the Rotterdam Study. Over all our data exemplify that fine phenotyping is a useful strategy for finding genes involved in human complex traits.

Ghost admixture in eastern gorillas.

Archaic admixture has had a substantial impact on human evolution with multiple events across different clades, including from extinct hominins such as Neanderthals and Denisovans into modern humans. In great apes, archaic admixture has been identified in chimpanzees and bonobos but the possibility of such events has not been explored in other species. Here, we address this question using high-coverage whole-genome sequences from all four extant gorilla subspecies, including six newly sequenced eastern gorillas from previously unsampled geographic regions. Using approximate Bayesian computation with neural networks to model the demographic history of gorillas, we find a signature of admixture from an archaic 'ghost' lineage into the common ancestor of eastern gorillas but not western gorillas. We infer that up to 3% of the genome of these individuals is introgressed from an archaic lineage that diverged more than 3 million years ago from the common ancestor of all extant gorillas. This introgression event took place before the split of mountain and eastern lowland gorillas, probably more than 40 thousand years ago and may have influenced perception of bitter taste in eastern gorillas. When comparing the introgression landscapes of gorillas, humans and bonobos, we find a consistent depletion of introgressed fragments on the X chromosome across these species. However, depletion in protein-coding content is not detectable in eastern gorillas, possibly as a consequence of stronger genetic drift in this species.

Unexpected island effects at an extreme: reduced Y chromosome and mitochondrial DNA diversity in Nias.

The amount of genetic diversity in a population is determined by demographic and selection events in its history. Human populations which exhibit greatly reduced overall genetic diversity, presumably resulting from severe bottlenecks or founder events, are particularly interesting, not least because of their potential to serve as valuable resources for health studies. Here, we present an unexpected case, the human population of Nias Island in Indonesia, that exhibits severely reduced Y chromosome (non-recombining portion of the Y chromosome [NRY]) and to a lesser extent also reduced mitochondrial DNA (mtDNA) diversity as compared with most other populations from the Asia/Oceania region. Our genetic data, collected from more than 400 individuals from across the island, suggest a strong previously undetected bottleneck or founder event in the human population history of Nias, more pronounced for males than for females, followed by subsequent genetic isolation. Our findings are unexpected given the island's geographic proximity to the genetically highly diverse Southeast Asian world, as well as our previous knowledge about the human history of Nias. Furthermore, all NRY and virtually all mtDNA haplogroups observed in Nias can be attributed to the Austronesian expansion, in line with linguistic data, and in contrast with archaeological evidence for a pre-Austronesian occupation of Nias that, as we show here, left no significant genetic footprints in the contemporary population. Our work underlines the importance of human genetic diversity studies not only for a better understanding of human population history but also because of the potential relevance for genetic disease-mapping studies.

Adaptive evolution of loci covarying with the human African Pygmy phenotype.

African Pygmies are hunter-gatherer populations from the equatorial rainforest that present the lowest height averages among humans. The biological basis and the putative adaptive role of the short stature of Pygmy populations has been one of the most intriguing topics for human biologists in the last century, which still remains elusive. Worldwide convergent evolution of the Pygmy size suggests the presence of strong selective pressures on the phenotype. We developed a novel approach to survey the genetic architecture of phenotypes and applied it to study the genomic covariation between allele frequencies and height measurements among Pygmy and non-Pygmy populations. Among the regions that were most associated with the phenotype, we identified a significant excess of genes with pivotal roles in bone homeostasis, such as PPPT3B and the height associated SUPT3H-RUNX2. We hypothesize that skeletal remodeling could be a key biological process underlying the Pygmy phenotype. In addition, we showed that these regions have most likely evolved under positive selection. These results constitute the first genetic hint of adaptive evolution in the African Pygmy phenotype, which is consistent with the independent emergence of the Pygmy height in other continents with similar environments.

Assessing the digenic model in rare disorders using population sequencing data.

An important fraction of patients with rare disorders remains with no clear genetic diagnostic, even after whole-exome or whole-genome sequencing, posing a difficulty in giving adequate treatment and genetic counseling. The analysis of genomic data in rare disorders mostly considers the presence of single gene variants in coding regions that follow a concrete monogenic mode of inheritance. A digenic inheritance, with variants in two functionally-related genes in the same individual, is a plausible alternative that might explain the genetic basis of the disease in some cases. In this case, digenic disease combinations should be absent or underrepresented in healthy individuals. We develop a framework to evaluate the significance of digenic combinations and test its statistical power in different scenarios. We suggest that this approach will be relevant with the advent of new sequencing efforts including hundreds of thousands of samples.

The power of geohistorical boundaries for modeling the genetic background of human populations: The case of the rural catalan Pyrenees.

The genetic variation of the European population at a macro-geographic scale follows genetic gradients which reflect main migration events. However, less is known about factors affecting mating patterns at a micro-geographic scale. In this study we have analyzed 726,718 autosomal single nucleotide variants in 435 individuals from the catalan Pyrenees covering around 200 km of a vast and abrupt region in the north of the Iberian Peninsula, for which we have information about the geographic origin of all grand-parents and parents. At a macro-geographic scale, our analyses recapitulate the genetic gradient observed in Spain. However, we also identified the presence of micro-population substructure among the sampled individuals. Such micro-population substructure does not correlate with geographic barriers such as the expected by the orography of the considered region, but by the bishoprics present in the covered geographic area. These results support that, on top of main human migrations, long ongoing socio-cultural factors have also shaped the genetic diversity observed at rural populations.