Quantifying the contribution of Neanderthal introgression to the heritability of complex traits

Efficient Detection and Characterization of Targets of Natural Selection Using Transfer Learning

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pretrained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Efficient detection and characterization of targets of natural selection using transfer learning

Natural selection leaves detectable patterns of altered spatial diversity within genomes, and identifying affected regions is crucial for understanding species evolution. Recently, machine learning approaches applied to raw population genomic data have been developed to uncover these adaptive signatures. Convolutional neural networks (CNNs) are particularly effective for this task, as they handle large data arrays while maintaining element correlations. However, shallow CNNs may miss complex patterns due to their limited capacity, while deep CNNs can capture these patterns but require extensive data and computational power. Transfer learning addresses these challenges by utilizing a deep CNN pre-trained on a large dataset as a feature extraction tool for downstream classification and evolutionary parameter prediction. This approach reduces extensive training data generation requirements and computational needs while maintaining high performance. In this study, we developed TrIdent, a tool that uses transfer learning to enhance detection of adaptive genomic regions from image representations of multilocus variation. We evaluated TrIdent across various genetic, demographic, and adaptive settings, in addition to unphased data and other confounding factors. TrIdent demonstrated improved detection of adaptive regions compared to recent methods using similar data representations. We further explored model interpretability through class activation maps and adapted TrIdent to infer selection parameters for identified adaptive candidates. Using whole-genome haplotype data from European and African populations, TrIdent effectively recapitulated known sweep candidates and identified novel cancer, and other disease-associated genes as potential sweeps.

Gene expression patterns of the developing human face at single cell resolution reveal cell type contributions to normal facial variation and disease risk

Craniofacial development gives rise to the complex structures of the face and involves the interplay of diverse cell types. Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development from craniofacial tissues of 24 embryos that span six key time points during the embryonic period (4-8 post-conception weeks). This resource resolves the transcriptional dynamics of seven major cell types and uncovers distinct major cell types, including muscle progenitors and cranial neural crest cells (CNCCs), as well as dozens of subtypes of ectoderm and mesenchyme. Comparative analyses reveal substantial conservation of major cell types, alongside human biased differences in gene expression programs. CNCCs, which play a crucial role in craniofacial morphogenesis, exhibit the lowest marker gene conservation, underscoring their evolutionary plasticity. Spatial transcriptomics further localizes cell populations, providing a detailed view of their developmental roles and anatomical context. We also link these developmental processes to genetic variation, identifying cell type-specific enrichments for common variants associated with facial morphology and rare variants linked to orofacial clefts. Intriguingly, Neanderthal-introgressed sequences are enriched near genes with biased expression in cartilage and specialized ectodermal subtypes, suggesting their contribution to modern human craniofacial features. This atlas offers unprecedented insights into the cellular and genetic mechanisms shaping the human face, highlighting conserved and distinctly human aspects of craniofacial biology. Our findings illuminate the developmental origins of craniofacial disorders, the genetic basis of facial variation, and the evolutionary legacy of ancient hominins. This work provides a foundational resource for exploring craniofacial biology, with implications for developmental genetics, evolutionary biology, and clinical research into congenital anomalies.

Understanding the Emergence of Schizophrenia in the Light of Human Evolution: New Perspectives in Genetics

Schizophrenia is a frequent and disabling disease. The persistence of the disorder despite its harmful consequences represents an evolutionary paradox. Based on recent discoveries in genetics, scientists have formulated the "price-to-pay" hypothesis: schizophrenia would be intimately related to human evolution, particularly to brain development and human-specific higher cognitive functions. The objective of the present work is to question scientific literature about the relationship between schizophrenia and human evolution from a genetic point of view. In the last two decades, research investigated the association between schizophrenia and a few genetic evolutionary markers: Human accelerated regions, segmental duplications, and highly repetitive DNA such as the Olduvai domain. Other studies focused on the action of natural selection on schizophrenia-associated genetic variants, also thanks to the complete sequencing of archaic hominins' genomes (Neanderthal, Denisova). Results suggested that a connection between human evolution and schizophrenia may exist; nonetheless, much research is still needed, and it is possible that a definitive answer to the evolutionary paradox of schizophrenia will never be found.

Inferring human phenotypes using ancient DNA: from molecules to populations

The increasing availability of ancient DNA (aDNA) from human groups across space and time has yielded deep insights into the movements of our species. However, given the challenges of mapping from genotype to phenotype, aDNA has revealed less about the phenotypes of ancient individuals. In this review, we highlight recent advances in inferring ancient phenotypes - from the molecular to population scale - with a focus on applications enabled by new machine learning approaches. The genetic architecture of complex traits across human groups suggests that the prediction of individual-level complex traits, like behavior or disease risk, is often challenging across the relevant evolutionary distances. Thus, we propose an approach that integrates predictions of molecular phenotypes, whose mechanisms are more conserved, with nongenetic data.

The shared genetic architecture and evolution of human language and musical rhythm

This study aimed to test theoretical predictions over biological underpinnings of previously documented phenotypic correlations between human language-related and musical rhythm traits. Here, after identifying significant genetic correlations between rhythm, dyslexia and various language-related traits, we adapted multivariate methods to capture genetic signals common to genome-wide association studies of rhythm (N = 606,825) and dyslexia (N = 1,138,870). The results revealed 16 pleiotropic loci (P < 5 × 10-8) jointly associated with rhythm impairment and dyslexia, and intricate shared genetic and neurobiological architectures. The joint genetic signal was enriched for foetal and adult brain cell-specific regulatory regions, highlighting complex cellular composition in their shared underpinnings. Local genetic correlation with a key white matter tract (the left superior longitudinal fasciculus-I) substantiated hypotheses about auditory-motor connectivity as a genetically influenced, evolutionarily relevant neural endophenotype common to rhythm and language processing. Overall, we provide empirical evidence of multiple aspects of shared biology linking language and musical rhythm, contributing novel insight into the evolutionary relationships between human musicality and linguistic communication traits.

Archaic hominin admixture and its consequences for modern humans

As anatomically modern humans dispersed out of Africa, they encountered and mated with now extinct hominins, including Neanderthals and Denisovans. It is now well established that all non-African individuals derive approximately 2% of their genome from Neanderthal ancestors and individuals of Melanesian and Australian aboriginal ancestry inherited an additional 2%-5% of their genomes from Denisovan ancestors. Attention has started to shift from documenting amounts of archaic admixture and identifying introgressed segments to understanding their molecular, phenotypic, and evolutionary consequences and refining models of human history. Here, we review recent insights into admixture between modern and archaic humans, emphasizing methodological innovations and the functional and phenotypic effects Neanderthal and Denisovan sequences have in contemporary individuals.

The trait-specific timing of accelerated genomic change in the human lineage

Humans exhibit distinct characteristics compared to our primate and ancient hominin ancestors. To investigate genomic bursts in the evolution of these traits, we use two complementary approaches to examine enrichment among genome-wide association study loci spanning diseases and AI-based image-derived brain, heart, and skeletal tissue phenotypes with genomic regions reflecting four evolutionary divergence points. These regions cover epigenetic differences among humans and rhesus macaques, human accelerated regions (HARs), ancient selective sweeps, and Neanderthal-introgressed alleles. Skeletal traits such as pelvic width and limb proportions showed enrichment in evolutionary annotations that mirror morphological changes in the primate fossil record. Additionally, we observe enrichment of loci associated with the longitudinal fasciculus in human-gained epigenetic elements since macaques, the visual cortex in HARs, and the thalamus proper in Neanderthal-introgressed alleles, implying that associated cognitive functions such as language processing, decision-making, sensory signaling, and motor control are enriched at different evolutionary depths.

Archaic introgression contributed to shape the adaptive modulation of angiogenesis and cardiovascular traits in human high-altitude populations from the Himalayas

It is well established that several Homo sapiens populations experienced admixture with extinct human species during their evolutionary history. Sometimes, such a gene flow could have played a role in modulating their capability to cope with a variety of selective pressures, thus resulting in archaic adaptive introgression events. A paradigmatic example of this evolutionary mechanism is offered by the EPAS1 gene, whose most frequent haplotype in Himalayan highlanders was proved to reduce their susceptibility to chronic mountain sickness and to be introduced in the gene pool of their ancestors by admixture with Denisovans. In this study, we aimed at further expanding the investigation of the impact of archaic introgression on more complex adaptive responses to hypobaric hypoxia evolved by populations of Tibetan/Sherpa ancestry, which have been plausibly mediated by soft selective sweeps and/or polygenic adaptations rather than by hard selective sweeps. For this purpose, we used a combination of composite-likelihood and gene network-based methods to detect adaptive loci in introgressed chromosomal segments from Tibetan WGS data and to shortlist those presenting Denisovan-like derived alleles that participate to the same functional pathways and are absent in populations of African ancestry, which are supposed to do not have experienced Denisovan admixture. According to this approach, we identified multiple genes putatively involved in archaic introgression events and that, especially as regards TBC1D1, RASGRF2, PRKAG2, and KRAS, have plausibly contributed to shape the adaptive modulation of angiogenesis and of certain cardiovascular traits in high-altitude Himalayan peoples. These findings provided unprecedented evidence about the complexity of the adaptive phenotype evolved by these human groups to cope with challenges imposed by hypobaric hypoxia, offering new insights into the tangled interplay of genetic determinants that mediates the physiological adjustments crucial for human adaptation to the high-altitude environment.

The Fate of a Polygenic Phenotype Within the Genomic Landscapes of Introgression in the European Seabass Hybrid Zone

Unraveling the evolutionary mechanisms and consequences of hybridization is a major concern in biology. Many studies have documented the interplay between recombination and selection in modulating the genomic landscape of introgression, but few have considered how associations with phenotype may affect this landscape. Here, we use the European seabass (Dicentrarchus labrax), a key species in marine aquaculture that undergoes natural hybridization, to determine how selection on phenotype modulates the introgression landscape between Atlantic and Mediterranean lineages. We use a high-density single nucleotide polymorphism array to assess individual local ancestry along the genome and improve the mapping of muscle fat content, a polygenic trait that is divergent between lineages. Taking into account variation in recombination rates, we reveal a purging of Atlantic ancestry in the admixed Mediterranean populations. While Atlantic individuals had higher muscle fat content, we observed that genomic regions associated with this trait in Mediterranean populations displayed reduced introgression of Atlantic ancestry. These results emphasize how selection against maladapted alleles shapes the genomic landscape of introgression.

Genome-Wide Association Study Identifies Genes for Hair Growth and Patterning are Associated With Pilonidal Disease

BACKGROUND

Pilonidal sinus disease is a highly morbid condition characterized by the formation of chronic sinus tracts throughout the sacrococcygeal region. Despite its commonality and strong association with family history, no prior investigation of genetic risk factors for pilonidal sinus disease exists.

OBJECTIVE

To identify genetic risk factors for pilonidal sinus disease.

DESIGN

A genome-wide association study.

SETTINGS

The United Kingdom Biobank, FinnGen Biobank, and Penn Medicine BioBank.

PATIENTS

There were 772,072 participants.

MAIN OUTCOME MEASURE

Genome-wide significant variants ( p < 5 × 10 -8 ) were mapped to genes using physical distance and gene expression in skin. Genetic correlation between pilonidal sinus disease and morphometric, androgen-driven, and hair phenotypes was estimated with linkage disequilibrium score regression. Finally, a genome-first approach to rare predicted deleterious variants in hair shaft genes TCHH , PADI3 , and TGM3 was conducted for association with pilonidal sinus disease via the Penn Medicine BioBank.

RESULTS

A genome-wide association study comprising 2835 individuals with pilonidal sinus disease identified 5 genome-wide significant loci, prioritizing HDAC9, TBX15, WARS2, RP11-293M10.1 , PRKAR1B , TWIST1, GPATCH2L, NEK9 , and EIF2B2 , as putative causal genes; several of these genes have known roles in balding and hair patterning. There was a significant correlation between the genetic background of pilonidal sinus disease and the androgen-driven hair traits of male pattern baldness and young age at first facial hair. In a candidate analysis of genes associated with syndromic hair disorders, rare coding variants in TCHH , a monogenic cause of uncombable hair syndrome, were associated with increased prevalence of pilonidal sinus disease (OR 4.81 [95% CI, 2.06-11.2]).

LIMITATIONS

This study is limited to European ancestry. However, because there is a higher incidence of pilonidal sinus disease in men of European ancestry, this analysis is focused on the at-risk population.

CONCLUSIONS

Genetic analysis of pilonidal sinus disease identified shared genetic architecture with hair biology and androgen-driven traits. As the first study investigating the genetic basis of pilonidal sinus disease, this provides biological insight into the long-appreciated connection between the disease state, male sex, and hair. See Video abstract.

UN ESTUDIO DE ASOCIACIN DEL GENOMA COMPLETO IDENTIFICA GENES DEL CRECIMIENTO Y EL PATRN DEL PELO ASOCIADOS A LA ENFERMEDAD PILONIDAL

ANTECEDENTES:La enfermedad del seno pilonidal es una condición muy mórbida caracterizada por la formación de tractos sinusales crónicos en toda la región sacrococcígea. A pesar de su frecuencia y su fuerte asociación con los antecedentes familiares, no se han investigado previamente los factores de riesgo genéticos de la enfermedad sinusal pilonidal.OBJETIVO:Identificar factores genéticos de riesgo para la enfermedad del seno pilonidal.DISEÑO:Estudio de asociación de genoma completo.CONJUNTOS:Biobanco del Reino Unido, Biobanco FinnGen y Biobanco PennMedicine.PACIENTES:772.072 participantes.MEDIDA DE RESULTADO PRINCIPAL:Las variantes significativas en todo el genoma (p < 5x10-8) se asignaron a genes utilizando la distancia física y la expresión génica en la piel. La correlación genética entre la enfermedad del seno pilonidal y los fenotipos morfométricos, androgénicos y de cabello se estimó con regresión de puntuación LD. Por último, se realizó una aproximación genómica a variantes deletéreas raras predichas en los genes del tallo piloso TCHH, PADI3 y TGM3 para su asociación con la enfermedad del seno pilonidal a través del Biobanco PennMedicine.RESULTADOS:El estudio de asociación de todo el genoma, que incluyó a 2.835 individuos con enfermedad del seno pilonidal, identificó 5 loci significativos en todo el genoma, dando prioridad a HDAC9, TBX15, WARS2, RP11-293M10.1, PRKAR1B, TWIST1, GPATCH2L, NEK9 y EIF2B2, como genes causales putativos; varios de estos genes tienen funciones conocidas en la calvicie y el patrón del cabello. Se observó una correlación significativa entre los antecedentes genéticos de la enfermedad del seno pilonidal y los de los rasgos calvicie de patrón masculino y edad temprana del primer vello facial impulsados por andrógenos. En un análisis de genes candidatos asociados a trastornos capilares sindrómicos, las variantes raras de codificación en TCHH, una causa monogénica del síndrome capilar incombustible, se asociaron a una mayor prevalencia de la enfermedad del seno pilonidal (OR 4,81 [IC del 5%, 2,06-11,2]).LIMITACIONES:Este estudio se limita a la ascendencia europea. Sin embargo, debido a que hay una mayor incidencia de la enfermedad sinusal pilonidal en los hombres de ascendencia europea, este análisis se centra en la población de riesgo.CONCLUSIÓN:El análisis genético de la enfermedad del seno pilonidal identificó una arquitectura genética compartida con la biología del cabello y los rasgos impulsados por andrógenos. Siendo el primer estudio que investiga las bases genéticas de la enfermedad del seno pilonidal, esto proporciona una visión biológica de la conexión, apreciada desde hace tiempo, entre el estado de la enfermedad, el sexo masculino y el cabello. (Traducción-Dr. Aurian Garcia Gonzalez ).

Denisovan admixture facilitated environmental adaptation in Papua New Guinean populations

Neandertals and Denisovans, having inhabited distinct regions in Eurasia and possibly Oceania for over 200,000 y, experienced ample time to adapt to diverse environmental challenges these regions presented. Among present-day human populations, Papua New Guineans (PNG) stand out as one of the few carrying substantial amounts of both Neandertal and Denisovan DNA, a result of past admixture events with these archaic human groups. This study investigates the distribution of introgressed Denisovan and Neandertal DNA within two distinct PNG populations, residing in the highlands of Mt Wilhelm and the lowlands of Daru Island. These locations exhibit unique environmental features, some of which may parallel the challenges that archaic humans once confronted and adapted to. Our results show that PNG highlanders carry higher levels of Denisovan DNA compared to PNG lowlanders. Among the Denisovan-like haplotypes with higher frequencies in highlander populations, those exhibiting the greatest frequency difference compared to lowlander populations also demonstrate more pronounced differences in population frequencies than frequency-matched nonarchaic variants. Two of the five most highly differentiated of those haplotypes reside in genomic areas linked to brain development genes. Conversely, Denisovan-like haplotypes more frequent in lowlanders overlap with genes associated with immune response processes. Our findings suggest that Denisovan DNA has provided genetic variation associated with brain biology and immune response to PNG genomes, some of which might have facilitated adaptive processes to environmental challenges.

Functional characterization of archaic-specific variants in mitonuclear genes: insights from comparative analysis in S. cerevisiae

Neanderthal and Denisovan hybridisation with modern humans has generated a non-random genomic distribution of introgressed regions, the result of drift and selection dynamics. Cross-species genomic incompatibility and more efficient removal of slightly deleterious archaic variants have been proposed as selection-based processes involved in the post-hybridisation purge of archaic introgressed regions. Both scenarios require the presence of functionally different alleles across Homo species onto which selection operated differently according to which populations hosted them, but only a few of these variants have been pinpointed so far. In order to identify functionally divergent archaic variants removed in humans, we focused on mitonuclear genes, which are underrepresented in the genomic landscape of archaic humans. We searched for non-synonymous, fixed, archaic-derived variants present in mitonuclear genes, rare or absent in human populations. We then compared the functional impact of archaic and human variants in the model organism Saccharomyces cerevisiae. Notably, a variant within the mitochondrial tyrosyl-tRNA synthetase 2 (YARS2) gene exhibited a significant decrease in respiratory activity and a substantial reduction of Cox2 levels, a proxy for mitochondrial protein biosynthesis, coupled with the accumulation of the YARS2 protein precursor and a lower amount of mature enzyme. Our work suggests that this variant is associated with mitochondrial functionality impairment, thus contributing to the purging of archaic introgression in YARS2. While different molecular mechanisms may have impacted other mitonuclear genes, our approach can be extended to the functional screening of mitonuclear genetic variants present across species and populations.

SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models

SUMMARY

The increasing development of sequence-based machine learning models has raised the demand for manipulating sequences for this application. However, existing approaches to edit and evaluate genome sequences using models have limitations, such as incompatibility with structural variants, challenges in identifying responsible sequence perturbations, and the need for vcf file inputs and phased data. To address these bottlenecks, we present Sequence Mutator for Predictive Models (SuPreMo), a scalable and comprehensive tool for performing and supporting in silico mutagenesis experiments. We then demonstrate how pairs of reference and perturbed sequences can be used with machine learning models to prioritize pathogenic variants or discover new functional sequences.

AVAILABILITY AND IMPLEMENTATION

SuPreMo was written in Python, and can be run using only one line of code to generate both sequences and 3D genome disruption scores. The codebase, instructions for installation and use, and tutorials are on the GitHub page: https://github.com/ketringjoni/SuPreMo.

Asian-European differentiation of schizophrenia-associated genes driven by admixture and natural selection

The European-centered genome-wide association studies of schizophrenia (SCZ) may not be well applied to non-European populations. We analyzed 1,592 reported SCZ-associated genes using the public genome data and found an overall higher Asian-European differentiation on the SCZ-associated variants than at the genome-wide level. Notable examples included 15 missense variants, a regulatory variant SLC5A10-rs1624825, and a damaging variant TSPAN18-rs1001292. Independent local adaptations in recent 25,000 years, after the Asian-European divergence, could have contributed to such genetic differentiation, as were identified at a missense mutation LTN1-rs57646126-A in Asians, and a non-risk allele ZSWIM6-rs72761442-G in Europeans. Altai-Neanderthal-derived alleles may have opposite effects on SCZ susceptibility between ancestries. Furthermore, adaptive introgression was detected on the non-risk haplotype at 1q21.2 in Europeans, while in Asians it was observed on the SCZ risk haplotype at 3p21.31 which is also potentially ultra-violet protective. This study emphasizes the importance of including more representative Asian samples in future SCZ studies.

A Neanderthal haplotype introgressed into the human genome confers protection against membranous nephropathy

Class 2 HLA and PLA2R1 alleles are exceptionally strong genetic risk factors for membranous nephropathy (MN), leading, through an unknown mechanism, to a targeted autoimmune response. Introgressed archaic haplotypes (introduced from an archaic human genome into the modern human genome) might influence phenotypes through gene dysregulation. Here, we investigated the genomic region surrounding the PLA2R1 gene. We reconstructed the phylogeny of Neanderthal and modern haplotypes in this region and calculated the probability of the observed clustering being the result of introgression or common descent. We imputed variants for the participants in our previous genome-wide association study and we compared the distribution of Neanderthal variants between MN cases and controls. The region associated with the lead MN risk locus in the PLA2R1 gene was confirmed and showed that, within a 507 kb region enriched in introgressed sequence, a stringently defined 105 kb haplotype, intersecting the coding regions for PLA2R1 and ITGB6, is inherited from Neanderthals. Thus, introgressed Neanderthal haplotypes overlapping PLA2R1 are differentially represented in MN cases and controls, with enrichment In controls suggesting a protective effect.

Biogeographic Perspectives on Human Genetic Diversification

Modern humans originated in Africa 300,000 yr ago, and before leaving their continent of origin, they underwent a process of intense diversification involving complex demographic dynamics. Upon exiting Africa, different populations emerged on the four other inhabited continents, shaped by the interplay of various evolutionary processes, such as migrations, founder effects, and natural selection. Within each region, continental populations, in turn, diversified and evolved almost independently for millennia. As a backdrop to this diversification, introgressions from archaic species contributed to establishing different patterns of genetic diversity in different geographic regions, reshaping our understanding of our species' variability. With the increasing availability of genomic data, it has become possible to delineate the subcontinental human population structure precisely. However, the bias toward the genomic research focused on populations from the global North has limited our understanding of the real diversity of our species and the processes and events that guided different human groups throughout their evolutionary history. This perspective is part of a series of articles celebrating 40 yr since our journal, Molecular Biology and Evolution, was founded (Russo et al. 2024). The perspective is accompanied by virtual issues, a selection of papers on human diversification published by Genome Biology and Evolution and Molecular Biology and Evolution.

The genetic changes that shaped Neandertals, Denisovans, and modern humans

Modern human ancestors diverged from the ancestors of Neandertals and Denisovans about 600,000 years ago. Until about 40,000 years ago, these three groups existed in parallel, occasionally met, and exchanged genes. A critical question is why modern humans, and not the other two groups, survived, became numerous, and developed complex cultures. Here, we discuss genetic differences among the groups and some of their functional consequences. As more present-day genome sequences become available from diverse groups, we predict that very few, if any, differences will distinguish all modern humans from all Neandertals and Denisovans. We propose that the genetic basis of what constitutes a modern human is best thought of as a combination of genetic features, where perhaps none of them is present in each and every present-day individual.

More than a decade of genetic research on the Denisovans

Denisovans, a group of now extinct humans who lived in Eastern Eurasia in the Middle and Late Pleistocene, were first identified from DNA sequences just over a decade ago. Only ten fragmentary remains from two sites have been attributed to Denisovans based entirely on molecular information. Nevertheless, there has been great interest in using genetic data to understand Denisovans and their place in human history. From the reconstruction of a single high-quality genome, it has been possible to infer their population history, including events of admixture with other human groups. Additionally, the identification of Denisovan DNA in the genomes of present-day individuals has provided insights into the timing and routes of dispersal of ancient modern humans into Asia and Oceania, as well as the contributions of archaic DNA to the physiology of present-day people. In this Review, we synthesize more than a decade of research on Denisovans, reconcile controversies and summarize insights into their population history and phenotype. We also highlight how our growing knowledge about Denisovans has provided insights into our own evolutionary history.

Temporal Variation in Introgressed Segments' Length Statistics Computed from a Limited Number of Ancient Genomes Sheds Light on Past Admixture Pulses

Hybridization is recognized as an important evolutionary force, but identifying and timing admixture events between divergent lineages remain a major aim of evolutionary biology. While this has traditionally been done using inferential tools on contemporary genomes, the latest advances in paleogenomics have provided a growing wealth of temporally distributed genomic data. Here, we used individual-based simulations to generate chromosome-level genomic data for a 2-population system and described temporal neutral introgression patterns under a single- and 2-pulse admixture model. We computed 6 summary statistics aiming to inform the timing and number of admixture pulses between interbreeding entities: lengths of introgressed sequences and their variance within genomes, as well as genome-wide introgression proportions and related measures. The first 2 statistics could confidently be used to infer interlineage hybridization history, peaking at the beginning and shortly after an admixture pulse. Temporal variation in introgression proportions and related statistics provided more limited insights, particularly when considering their application to ancient genomes still scant in number. Lastly, we computed these statistics on Homo sapiens paleogenomes and successfully inferred the hybridization pulse from Neanderthal that occurred approximately 40 to 60 kya. The scarce number of genomes dating from this period prevented more precise inferences, but the accumulation of paleogenomic data opens promising perspectives as our approach only requires a limited number of ancient genomes.

Archaic Introgression Shaped Human Circadian Traits

When the ancestors of modern Eurasians migrated out of Africa and interbred with Eurasian archaic hominins, namely, Neanderthals and Denisovans, DNA of archaic ancestry integrated into the genomes of anatomically modern humans. This process potentially accelerated adaptation to Eurasian environmental factors, including reduced ultraviolet radiation and increased variation in seasonal dynamics. However, whether these groups differed substantially in circadian biology and whether archaic introgression adaptively contributed to human chronotypes remain unknown. Here, we traced the evolution of chronotype based on genomes from archaic hominins and present-day humans. First, we inferred differences in circadian gene sequences, splicing, and regulation between archaic hominins and modern humans. We identified 28 circadian genes containing variants with potential to alter splicing in archaics (e.g., CLOCK, PER2, RORB, and RORC) and 16 circadian genes likely divergently regulated between present-day humans and archaic hominins, including RORA. These differences suggest the potential for introgression to modify circadian gene expression. Testing this hypothesis, we found that introgressed variants are enriched among expression quantitative trait loci for circadian genes. Supporting the functional relevance of these regulatory effects, we found that many introgressed alleles have associations with chronotype. Strikingly, the strongest introgressed effects on chronotype increase morningness, consistent with adaptations to high latitude in other species. Finally, we identified several circadian loci with evidence of adaptive introgression or latitudinal clines in allele frequency. These findings identify differences in circadian gene regulation between modern humans and archaic hominins and support the contribution of introgression via coordinated effects on variation in human chronotype.

SuPreMo: a computational tool for streamlining in silico perturbation using sequence-based predictive models

Computationally editing genome sequences is a common bioinformatics task, but current approaches have limitations, such as incompatibility with structural variants, challenges in identifying responsible sequence perturbations, and the need for vcf file inputs and phased data. To address these bottlenecks, we present Sequence Mutator for Predictive Models (SuPreMo), a scalable and comprehensive tool for performing in silico mutagenesis. We then demonstrate how pairs of reference and perturbed sequences can be used with machine learning models to prioritize pathogenic variants or discover new functional sequences.

The shared genetic architecture and evolution of human language and musical rhythm

Rhythm and language-related traits are phenotypically correlated, but their genetic overlap is largely unknown. Here, we leveraged two large-scale genome-wide association studies performed to shed light on the shared genetics of rhythm (N=606,825) and dyslexia (N=1,138,870). Our results reveal an intricate shared genetic and neurobiological architecture, and lay groundwork for resolving longstanding debates about the potential co-evolution of human language and musical traits.

Exploring the Neandertal legacy of pancreatic ductal adenocarcinoma risk in Eurasians

BACKGROUND

The genomes of present-day non-Africans are composed of 1-3% of Neandertal-derived DNA as a consequence of admixture events between Neandertals and anatomically modern humans about 50-60 thousand years ago. Neandertal-introgressed single nucleotide polymorphisms (aSNPs) have been associated with modern human disease-related traits, which are risk factors for pancreatic ductal adenocarcinoma (PDAC), such as obesity, type 2 diabetes, and inflammation. In this study, we aimed at investigating the role of aSNPs in PDAC in three Eurasian populations.

RESULTS

The high-coverage Vindija Neandertal genome was used to select aSNPs in non-African populations from 1000 Genomes project phase 3 data. Then, the association between aSNPs and PDAC risk was tested independently in Europeans and East Asians, using existing GWAS data on more than 200 000 individuals. We did not find any significant associations between aSNPs and PDAC in samples of European descent, whereas, in East Asians, we observed that the Chr10p12.1-rs117585753-T allele (MAF = 10%) increased the risk to develop PDAC (OR = 1.35, 95%CI 1.19-1.54, P = 3.59 × 10-6), with a P-value close to a threshold that takes into account multiple testing.

CONCLUSIONS

Our results show only a minimal contribution of Neandertal SNPs to PDAC risk.

Resurrecting the alternative splicing landscape of archaic hominins using machine learning

Alternative splicing contributes to adaptation and divergence in many species. However, it has not been possible to directly compare splicing between modern and archaic hominins. Here, we unmask the recent evolution of this previously unobservable regulatory mechanism by applying SpliceAI, a machine-learning algorithm that identifies splice-altering variants (SAVs), to high-coverage genomes from three Neanderthals and a Denisovan. We discover 5,950 putative archaic SAVs, of which 2,186 are archaic-specific and 3,607 also occur in modern humans via introgression (244) or shared ancestry (3,520). Archaic-specific SAVs are enriched in genes that contribute to traits potentially relevant to hominin phenotypic divergence, such as the epidermis, respiration and spinal rigidity. Compared to shared SAVs, archaic-specific SAVs occur in sites under weaker selection and are more common in genes with tissue-specific expression. Further underscoring the importance of negative selection on SAVs, Neanderthal lineages with low effective population sizes are enriched for SAVs compared to Denisovan and shared SAVs. Finally, we find that nearly all introgressed SAVs in humans were shared across the three Neanderthals, suggesting that older SAVs were more tolerated in human genomes. Our results reveal the splicing landscape of archaic hominins and identify potential contributions of splicing to phenotypic differences among hominins.

Large-scale functional screen identifies genetic variants with splicing effects in modern and archaic humans

Humans coexisted and interbred with other hominins which later became extinct. These archaic hominins are known to us only through fossil records and for two cases, genome sequences. Here, we engineer Neanderthal and Denisovan sequences into thousands of artificial genes to reconstruct the pre-mRNA processing patterns of these extinct populations. Of the 5,169 alleles tested in this massively parallel splicing reporter assay (MaPSy), we report 962 exonic splicing mutations that correspond to differences in exon recognition between extant and extinct hominins. Using MaPSy splicing variants, predicted splicing variants, and splicing quantitative trait loci, we show that splice-disrupting variants experienced greater purifying selection in anatomically modern humans than that in Neanderthals. Adaptively introgressed variants were enriched for moderate-effect splicing variants, consistent with positive selection for alternative spliced alleles following introgression. As particularly compelling examples, we characterized a unique tissue-specific alternative splicing variant at the adaptively introgressed innate immunity gene TLR1, as well as a unique Neanderthal introgressed alternative splicing variant in the gene HSPG2 that encodes perlecan. We further identified potentially pathogenic splicing variants found only in Neanderthals and Denisovans in genes related to sperm maturation and immunity. Finally, we found splicing variants that may contribute to variation among modern humans in total bilirubin, balding, hemoglobin levels, and lung capacity. Our findings provide unique insights into natural selection acting on splicing in human evolution and demonstrate how functional assays can be used to identify candidate causal variants underlying differences in gene regulation and phenotype.

The contribution of Neanderthal introgression and natural selection to neurodegenerative diseases

Humans are thought to be more susceptible to neurodegeneration than equivalently-aged primates. It is not known whether this vulnerability is specific to anatomically-modern humans or shared with other hominids. The contribution of introgressed Neanderthal DNA to neurodegenerative disorders remains uncertain. It is also unclear how common variants associated with neurodegenerative disease risk are maintained by natural selection in the population despite their deleterious effects. In this study, we aimed to quantify the genome-wide contribution of Neanderthal introgression and positive selection to the heritability of complex neurodegenerative disorders to address these questions. We used stratified-linkage disequilibrium score regression to investigate the relationship between five SNP-based signatures of natural selection, reflecting different timepoints of evolution, and genome-wide associated variants of the three most prevalent neurodegenerative disorders: Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease. We found no evidence for enrichment of positively-selected SNPs in the heritability of Alzheimer's disease, amyotrophic lateral sclerosis and Parkinson's disease, suggesting that common deleterious disease variants are unlikely to be maintained by positive selection. There was no enrichment of Neanderthal introgression in the SNP-heritability of these disorders, suggesting that Neanderthal admixture is unlikely to have contributed to disease risk. These findings provide insight into the origins of neurodegenerative disorders within the evolution of Homo sapiens and addresses a long-standing debate, showing that Neanderthal admixture is unlikely to have contributed to common genetic risk of neurodegeneration in anatomically-modern humans.

The lingering effects of Neanderthal introgression on human complex traits

The genetic variants introduced into the ancestors of modern humans from interbreeding with Neanderthals have been suggested to contribute an unexpected extent to complex human traits. However, testing this hypothesis has been challenging due to the idiosyncratic population genetic properties of introgressed variants. We developed rigorous methods to assess the contribution of introgressed Neanderthal variants to heritable trait variation and applied these methods to analyze 235,592 introgressed Neanderthal variants and 96 distinct phenotypes measured in about 300,000 unrelated white British individuals in the UK Biobank. Introgressed Neanderthal variants make a significant contribution to trait variation (explaining 0.12% of trait variation on average). However, the contribution of introgressed variants tends to be significantly depleted relative to modern human variants matched for allele frequency and linkage disequilibrium (about 59% depletion on average), consistent with purifying selection on introgressed variants. Different from previous studies (McArthur et al., 2021), we find no evidence for elevated heritability across the phenotypes examined. We identified 348 independent significant associations of introgressed Neanderthal variants with 64 phenotypes. Previous work (Skov et al., 2020) has suggested that a majority of such associations are likely driven by statistical association with nearby modern human variants that are the true causal variants. Applying a customized fine-mapping led us to identify 112 regions across 47 phenotypes containing 4303 unique genetic variants where introgressed variants are highly likely to have a phenotypic effect. Examination of these variants reveals their substantial impact on genes that are important for the immune system, development, and metabolism.

Long-range regulatory effects of Neandertal DNA in modern humans

The admixture between modern humans and Neandertals has resulted in ∼2% of the genomes of present-day non-Africans being composed of Neandertal DNA. Introgressed Neandertal DNA has been demonstrated to significantly affect the transcriptomic landscape in people today and via this molecular mechanism influence phenotype variation as well. However, little is known about how much of that regulatory impact is mediated through long-range regulatory effects that have been shown to explain ∼20% of expression variation. Here we identified 60 transcription factors (TFs) with their top cis-eQTL SNP in GTEx being of Neandertal ancestry and predicted long-range Neandertal DNA-induced regulatory effects by screening for the predicted target genes of those TFs. We show that the TFs form a significantly connected protein-protein interaction network. Among them are JUN and PRDM5, two brain-expressed TFs that have their predicted target genes enriched in regions devoid of Neandertal DNA. Archaic cis-eQTLs for the 60 TFs include multiple candidates for local adaptation, some of which show significant allele frequency increases over the last ∼10,000 years. A large proportion of the cis-eQTL-associated archaic SNPs have additional associations with various immune traits, schizophrenia, blood cell type composition and anthropometric measures. Finally, we demonstrate that our results are consistent with those of Neandertal DNA-associated empirical trans-eQTLs. Our results suggest that Neandertal DNA significantly influences regulatory networks, that its regulatory reach goes beyond the 40% of genomic sequence it still covers in present-day non-Africans and that via the investigated mechanism Neandertal DNA influences the phenotypic variation in people today.

Insights into brain evolution through the genotype-phenotype connection

It has recently become possible to start exploring how the genotype translates into human brain morphology and behavior by combining detailed genomic and phenotypic data from thousands of present-day people with archaic genomes of extinct humans, and gene expression data. As a starting point into this emerging interdisciplinary domain, we highlight current debates about which aspects of the modern human brain are unique. We review recent developments from (1) comparative primate neuroscience-a fast-growing field offering an invaluable framework for understanding general mechanisms and the evolution of human-specific traits. (2) paleoanthropology-based on evidence from endocranial imprints in fossil skulls, we trace the evolution from the ape-like brain phenotype of early hominins more than 3 million years ago to the unusual globular brain shape of present-day people. (3) Genomics of present-day and extinct humans. The morphological and genetic differences between modern humans and our closest extinct cousins, the Neandertals, offer important clues about the genetic underpinnings of brain morphology and behavior. The functional consequences of these genetic differences can be tested in animal models, and brain organoids.

Genetic variations within human gained enhancer elements affect human brain sulcal morphology

The expansion of the cerebral cortex is one of the most distinctive changes in the evolution of the human brain. Cortical expansion and related increases in cortical folding may have contributed to emergence of our capacities for high-order cognitive abilities. Molecular analysis of humans, archaic hominins, and non-human primates has allowed identification of chromosomal regions showing evolutionary changes at different points of our phylogenetic history. In this study, we assessed the contributions of genomic annotations spanning 30 million years to human sulcal morphology measured via MRI in more than 18,000 participants from the UK Biobank. We found that variation within brain-expressed human gained enhancers, regulatory genetic elements that emerged since our last common ancestor with Old World monkeys, explained more trait heritability than expected for the left and right calloso-marginal posterior fissures and the right central sulcus. Intriguingly, these are sulci that have been previously linked to the evolution of locomotion in primates and later on bipedalism in our hominin ancestors.

Denisovan introgression has shaped the immune system of present-day Papuans

Modern humans have admixed with multiple archaic hominins. Papuans, in particular, owe up to 5% of their genome to Denisovans, a sister group to Neanderthals whose remains have only been identified in Siberia and Tibet. Unfortunately, the biological and evolutionary significance of these introgression events remain poorly understood. Here we investigate the function of both Denisovan and Neanderthal alleles characterised within a set of 56 genomes from Papuan individuals. By comparing the distribution of archaic and non-archaic variants we assess the consequences of archaic admixture across a multitude of different cell types and functional elements. We observe an enrichment of archaic alleles within cis-regulatory elements and transcribed regions of the genome, with Denisovan variants strongly affecting elements active within immune-related cells. We identify 16,048 and 10,032 high-confidence Denisovan and Neanderthal variants that fall within annotated cis-regulatory elements and with the potential to alter the affinity of multiple transcription factors to their cognate DNA motifs, highlighting a likely mechanism by which introgressed DNA can impact phenotypes. Lastly, we experimentally validate these predictions by testing the regulatory potential of five Denisovan variants segregating within Papuan individuals, and find that two are associated with a significant reduction of transcriptional activity in plasmid reporter assays. Together, these data provide support for a widespread contribution of archaic DNA in shaping the present levels of modern human genetic diversity, with different archaic ancestries potentially affecting multiple phenotypic traits within non-Africans.

Denisovan and Neanderthal archaic introgression differentially impacted the genetics of complex traits in modern populations

BACKGROUND

Introgression from extinct Neanderthal and Denisovan human species has been shown to contribute to the genetic pool of modern human populations and their phenotypic spectrum. Evidence of how Neanderthal introgression shaped the genetics of human traits and diseases has been extensively studied in populations of European descent, with signatures of admixture reported for instance in genes associated with pigmentation, immunity, and metabolic traits. However, limited information is currently available about the impact of archaic introgression on other ancestry groups. Additionally, to date, no study has been conducted with respect to the impact of Denisovan introgression on the health and disease of modern populations. Here, we compare the way evolutionary pressures shaped the genetics of complex traits in East Asian and European populations, and provide evidence of the impact of Denisovan introgression on the health of East Asian and Central/South Asian populations.

RESULTS

Leveraging genome-wide association statistics from the Biobank Japan and UK Biobank, we assessed whether Denisovan and Neanderthal introgression together with other evolutionary genomic signatures were enriched for the heritability of physiological and pathological conditions in populations of East Asian and European descent. In EAS, Denisovan-introgressed loci were enriched for coronary artery disease heritability (1.69-fold enrichment, p=0.003). No enrichment for archaic introgression was observed in EUR. We also performed a phenome-wide association study of Denisovan and Neanderthal alleles in six ancestry groups available in the UK Biobank. In EAS, the Denisovan-introgressed SNP rs62391664 in the major histocompatibility complex region was associated with albumin/globulin ratio (beta=-0.17, p=3.57×10^-7). Neanderthal-introgressed alleles were associated with psychiatric and cognitive traits in EAS (e.g., "No Bipolar or Depression"-rs79043717 beta=-1.5, p=1.1×10^-7), and with blood biomarkers (e.g., alkaline phosphatase-rs11244089 beta=0.1, p=3.69×10^-116) and red hair color (rs60733936 beta=-0.86, p=4.49×10^-165) in EUR. In the other ancestry groups, Neanderthal alleles were associated with several traits, also including the use of certain medications (e.g., Central/South East Asia: indapamide - rs732632 beta=-2.38, p=5.22×10^-7).

CONCLUSIONS

Our study provides novel evidence regarding the impact of archaic introgression on the genetics of complex traits in worldwide populations, highlighting the specific contribution of Denisovan introgression in EAS populations.

Neandertal introgression partitions the genetic landscape of neuropsychiatric disorders and associated behavioral phenotypes

Despite advances in identifying the genetic basis of psychiatric and neurological disorders, fundamental questions about their evolutionary origins remain elusive. Here, introgressed variants from archaic humans such as Neandertals can serve as an intriguing research paradigm. We compared the number of associations for Neandertal variants to the number of associations of frequency-matched non-archaic variants with regard to human CNS disorders (neurological and psychiatric), nervous system drug prescriptions (as a proxy for disease), and related, non-disease phenotypes in the UK biobank (UKBB). While no enrichment for Neandertal genetic variants were observed in the UKBB for psychiatric or neurological disease categories, we found significant associations with certain behavioral phenotypes including pain, chronotype/sleep, smoking and alcohol consumption. In some instances, the enrichment signal was driven by Neandertal variants that represented the strongest association genome-wide. SNPs within a Neandertal haplotype that was associated with smoking in the UKBB could be replicated in four independent genomics datasets.Our data suggest that evolutionary processes in recent human evolution like admixture with Neandertals significantly contribute to behavioral phenotypes but not psychiatric and neurological diseases. These findings help to link genetic variants in a population to putative past beneficial effects, which likely only indirectly contribute to pathology in modern day humans.

Using neuroimaging genomics to investigate the evolution of human brain structure

Alterations in brain size and organization represent some of the most distinctive changes in the emergence of our species. Yet, there is limited understanding of how genetic factors contributed to altered neuroanatomy during human evolution. Here, we analyze neuroimaging and genetic data from up to 30,000 people in the UK Biobank and integrate with genomic annotations for different aspects of human evolution, including those based on ancient DNA and comparative genomics. We show that previously reported signals of recent polygenic selection for cortical anatomy are not replicable in a more ancestrally homogeneous sample. We then investigate relationships between evolutionary annotations and common genetic variants shaping cortical surface area and white-matter connectivity for each hemisphere. Our analyses identify single-nucleotide polymorphism heritability enrichment in human-gained regulatory elements that are active in early brain development, affecting surface areas of several parts of the cortex, including left-hemispheric speech-associated regions. We also detect heritability depletion in genomic regions with Neanderthal ancestry for connectivity of the uncinate fasciculus; this is a white-matter tract involved in memory, language, and socioemotional processing with relevance to neuropsychiatric disorders. Finally, we show that common genetic loci associated with left-hemispheric pars triangularis surface area overlap with a human-gained enhancer and affect regulation of ZIC4, a gene implicated in neurogenesis. This work demonstrates how genomic investigations of present-day neuroanatomical variation can help shed light on the complexities of our evolutionary past.

The contribution of Neanderthal introgression to modern human traits

Neanderthals, our closest extinct relatives, lived in western Eurasia from 400,000 years ago until they went extinct around 40,000 years ago. DNA retrieved from ancient specimens revealed that Neanderthals mated with modern human contemporaries. As a consequence, introgressed Neanderthal DNA survives scattered across the human genome such that 1-4% of the genome of present-day people outside Africa are inherited from Neanderthal ancestors. Patterns of Neanderthal introgressed genomic sequences suggest that Neanderthal alleles had distinct fates in the modern human genetic background. Some Neanderthal alleles facilitated human adaptation to new environments such as novel climate conditions, UV exposure levels and pathogens, while others had deleterious consequences. Here, we review the body of work on Neanderthal introgression over the past decade. We describe how evolutionary forces shaped the genomic landscape of Neanderthal introgression and highlight the impact of introgressed alleles on human biology and phenotypic variation.

Predicting Archaic Hominin Phenotypes from Genomic Data

Ancient DNA provides a powerful window into the biology of extant and extinct species, including humans' closest relatives: Denisovans and Neanderthals. Here, we review what is known about archaic hominin phenotypes from genomic data and how those inferences have been made. We contend that understanding the influence of variants on lower-level molecular phenotypes-such as gene expression and protein function-is a promising approach to using ancient DNA to learn about archaic hominin traits. Molecular phenotypes have simpler genetic architectures than organism-level complex phenotypes, and this approach enables moving beyond association studies by proposing hypotheses about the effects of archaic variants that are testable in model systems. The major challenge to understanding archaic hominin phenotypes is broadening our ability to accurately map genotypes to phenotypes, but ongoing advances ensure that there will be much more to learn about archaic hominin phenotypes from their genomes. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 23 is October 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.