Biology subjects

Huerta-Sanchez, E.

Publications and source records attributed to Huerta-Sanchez, E..

At least 19 recordsLinked to original sources

bioRxiv2026

Joint ancestry inference reveals the landscape of archaic introgression in admixed populations

Studying the evolutionary history of archaic segments in recently admixed individuals requires inferring both continental and archaic ancestry in admixed genomes. Here, we present TRACTINATOR, the first deep-learning method for simultaneous inference of continental and archaic ancestry in admixed human genomes. The model combines SNP sequences, population allele-frequency information, and S* statistics to improve both inference tasks. By learning relationships between haplotypes and population allele frequencies, TRACTINATOR can generalize across genomic regions and even across different genomic datasets. We train our model using both real and synthetic data, and show that augmenting with synthetic data improves accuracy for both continental and archaic ancestry inference. Finally, we apply TRACTINATOR to admixed Latin American populations from the 1,000 Genomes Project, revealing how archaic ancestry is distributed within chromosomal segments of African, European and Indigenous American ancestry in Latin American individuals. For candidates of adaptive introgression, we also infer whether the archaic haplotype was introduced via European or Indigenous American ancestors.

bioinformatics↗

bioRxiv2026

Effects of introgressed Neanderthal alleles on present-day brain morphology

Neanderthal introgression contributed a small fraction of genetic variants to present-day non-African genomes. While differences in cranial globularity between Neanderthal and modern humans are well documented from endocasts, the phenotypic consequences of these introgressed alleles can illuminate otherwise inaccessible genetically divergent brain structures. We analyzed 370 MRI-derived brain traits--including cortical and subcortical regional measurements, cortical folding metrics, diffusion tracts--in nearly 40,000 UK Biobank participants. To quantify the impact of Neanderthal ancestry, we intersected trait-associated loci with Neanderthal-derived variants identified from introgressed segments imputed in the same subjects. Low-frequency introgressed variants were depleted for detectable effects on brain phenotypes, whereas common introgressed variants showed no comparable depletion. Conversely, Neanderthal deserts were consistently enriched for functional effects. Eight associations were fine-mapped to Neanderthal-derived variants: one locus near the gene DAAM1 was especially prominent across multiple traits, including opposite effects in the cuneus and precuneus mediated by introgressed regulatory variants. Genome-wide directional alignment of Neanderthal effects was limited but became evident when focusing on suggestive loci: frontal and parietal areas were the most consistently affected traits, though not in a direction that obviously mirrors known modern-archaic morphology divergence. Several of these loci also influenced neuropsychiatric traits, with detectable polygenic consequences against schizophrenia and towards major depression, linking neuroanatomical and neuropsychiatric impact of Neanderthal introgression. These findings suggest that while introgressed alleles affecting divergent neuroanatomy between modern humans and Neanderthals were largely purged, a subset of tolerated alleles continues to shape human brain morphology and mental health.

genomics↗

bioRxiv2026

Improving Local Ancestry Inference through Neural Networks

MotivationLocal Ancestry Inference (LAI) allows us to study evolutionary processes in admixed populations[1], uncover ancestry-specific disease risk factors[2], and to better understand the demographic history of these populations[3]. Many methods for LAI exist, however, these methods usually focus on cases of intercontinental admixture. In this work, we evaluate both existing and novel methods in challenging scenarios, such as downsampled reference panels, intracontinental admixture, and distant admixture events. ResultsWe present four novel LAI implementations based on neural network architectures, including Bidirectional Long Short-Term Memory and Transformer networks which have not previously been used for LAI. We compare these novel implementations to existing methods for LAI across a variety of scenarios using the 1 Thousand Genomes dataset and other synthetic datasets. We find that while all networks achieve high performance for intercontinental admixture scenarios, inference power is comparatively low for scenarios of intracontinental or distant admixture. We further show how our implementations achieve the best performance of all methods through specialized preprocessing and inference smoothing steps. AvailabilityAll implementations and benchmarking code available at https://github.com/Jazpy/LAINNs.

bioinformatics↗

bioRxiv2025

Ancient genomic insights into Salmonella enterica Paratyphi C in Central Mexico

Salmonella enterica is a widespread pathogen of major global health relevance, with over 2,500 serovars classified into non-typhoidal and typhoidal groups. Within the typhoidal group, S. enterica Paratyphi C causes paratyphoid fever in humans. Ancient DNA from this bacterium has previously been recovered from epidemic-associated burials in Eurasia and Mexico, dating back 6,000 to 300 years. Here, we analyzed dental DNA from seven individuals (radiocarbon dated to 1800-1940 CE) buried at the Temple of the Immaculate Conception in Mexico City, Central Mexico, and identified ancient S. enterica Paratyphi C DNA in a young female with Native American ancestry. Using an in-house targeted enrichment strategy and deep shotgun sequencing, we reconstructed a S. enterica Paratyphi C genome (COYC5) with [~]11X coverage. Phylogenetic and comparative genomic analyses place COYC5 in close association with previously reported S. enterica Paratyphi C genomes associated with the 1545 cocoliztli epidemic in southern Mexico, as well as with European strains. Divergence estimates indicate that the Mexican and European lineages shared a common ancestor approximately 1,400 years before present (yBP), reflecting an ancient evolutionary split predating European colonization of Mexico. In contrast, the divergence between COYC5 and the southern Mexican genomes occurred around 516 yBP, coinciding with the onset of the colonial period. This pattern supports a European introduction of S. enterica Paratyphi C during colonization, followed by its local diversification within Mexico. Despite this regional differentiation, the conserved presence of key virulence loci--such as SPI-7 and an active shufflon system--across COYC5, southern Mexican, and European genomes underscores the enduring pathogenic potential of S. enterica Paratyphi C. The identification of this bacterium in 19th-century Mexico City provides the first genomic evidence of its persistence in urban contexts beyond major epidemic outbreaks, offering new insights into its evolutionary trajectory in Mexico. These findings raise new questions about how the pathogen spread and persisted across different ecological, social, and epidemiological contexts in ancient Mexico and the Americas.

evolutionary biology↗

bioRxiv2025

Archaic ancestry inference in imputed ancient human genomes

When modern humans expanded from Africa into Eurasia, they interbred with archaic hominins such as Neanderthals and Denisovans. This groundbreaking discovery, made in part possible through the genomic analysis of archaic remains, reshaped our understanding of human origins, and opened new research avenues to study the effects and consequences of archaic introgression. While significant progress has been made in identifying and quantifying archaic introgression, most studies have focused on contemporary individual genomic data. As a result, relatively little is known about the evolution of archaic variants within modern human populations shortly after interbreeding occurred. While analysis of ancient DNA from modern humans offers the potential to address this scientific gap, its poor quality has hindered its exploration. However, recent studies have shown that imputation using contemporary reference panels can accurately infer missing genotypes in ancient genomes. Here, we investigate the feasibility of using imputation to improve both global and local archaic ancestry inference in ancient genomes, by downsampling to different low-coverage values and imputing 20 high-coverage (>10X) ancient genomes, representing individuals from diverse temporal and geographical contexts. We tested the reliability of detecting and quantifying archaic introgression using D-statistics and the f4-ratio. We identified consistent results from the imputed and the original ancient genomes, suggesting that genomic estimates to detect and quantify introgression work well in imputed genomes. Regarding Local Ancestry Inference we find that we can identify more introgressed segments in imputed genomes than in non-imputed genomes. Surprisingly, we find that imputation accuracy is even higher in regions of archaic ancestry compared to other regions of the genome, facilitating the detection of introgressed segments in imputed genomes. Imputation also allows detection of Denisovan segments in Siberian and Alaskan individuals. We show that segments identified even at 0.0625X coverage can be used to reconstruct the history of introgressed haplotypes. For example, comparisons with archaic segments in contemporary humans reveal that the oldest individual analyzed, UstIshim, carried segments that are now found exclusively in either European or East Eurasian populations, indicating that these segments co-occurred in a shared ancestral population. By comparing only ancient individuals, we demonstrate that clustering based solely on the identified archaic segments effectively groups individuals into genetic clusters that correspond to populations defined by geography and time. This analysis shows a clear distinction between individuals with Denisovan introgression and those without, as well as a more detailed separation between Mesolithic and Neolithic Europeans, with the latter closely resembling Central Eurasian individuals. Furthermore, despite the small sample size in this study, we are able to reconstruct the origins of genes identified as candidates for adaptive introgression in contemporary populations, such as the BCN2 gene, which is an adaptively introgressed gene identified in contemporary West Eurasians. Additionally, we identify new candidates for adaptive introgression including LEMD2 and MLN in Europe. In this gene-region, imputation helps resolve the introgressed haplotype, which is closest to the Vindija Neanderthal haplotype.

genomics↗

bioRxiv2025

An archaic reference-free method to jointly infer Neanderthal and Denisovan introgressed segments in modern human genomes

Admixture between populations is a common feature of human history. Admixture events introduce new genetic variation that can fuel evolution. Characterizing the significance of admixture events on the evolution of a population across various species is of great interest to evolutionary geneticists. Local Ancestry Inference (LAI) methods infer genetic ancestry of an individual at a particular chromosomal location. Certain methods specialize in detecting archaic introgression, which consists of interbreeding between modern and archaic humans like Neanderthals and Denisovans. Most current LAI methods allow the detection of a single archaic ancestry, and post-processing may distinguish between multiple waves of introgression. These methods vary in how they choose archaic or modern reference genomes for the inference. Here, we present a new HMM-based method (DAIseg), which has the advantage of simultaneously distinguishing between multiple waves of ancient and recent admixture, using only modern human reference genomes. Simulations demonstrate that DAIseg achieves higher overall performance than state-of-the-art methods. We also apply DAIseg to Papuan populations to jointly detect Denisovan and Neanderthal introgressed segments, and identify a higher number of archaic segments than previous methods. Analysis of inferred introgressed segments, shows that we can identify evidence for two Denisovan introgression events in Papuans without having any post-processing and filtering. Overall, on top of being able to deal with both Archaic and recent admixture, DAIseg provides a more principled approach for detecting and classifying Denisovan and Neanderthal segments which will improve downstream analysis of introgressed segments to infer the impact of archaic introgression in humans.

bioinformatics↗

bioRxiv2024

Diffusion-based artificial genomes and their usefulness for local ancestry inference

The creation of synthetic data through generative modeling has emerged as a significant area of research in genomics, offering versatile applications from tailoring functional sequences with specific attributes to generating high-quality, privacy-preserving in silico genomes. Notwithstanding these advancements, a key challenge remains: while some methods exist to evaluate artificially generated genomic data, comprehensive tools to assess its usefulness are still limited. To tackle this issue and present a promising use case, we test artificial genomes within the framework of population genetics and local ancestry inference (LAI). Building on previous work in deep generative modeling for genomics, we introduce a novel, frugal diffusion model and show that it produces high-quality genomic data. We then assess the performance of a downstream machine learning LAI model trained on composite datasets comprising both real and/or synthetic data. Our findings reveal that the LAI model achieves comparable performance when trained exclusively on real data versus high-quality synthetic data. Moreover, we highlight how data augmentation using high-quality artificial genomes significantly benefits the LAI model, particularly when real data is limited. Finally, we compare the conventional use of a single synthetic dataset to a robust ensemble approach, wherein multiple LAI models are trained on diverse synthetic datasets, and their predictions are aggregated. Our study highlights the potential of frugal diffusion-based generative models and synthetic data integration in genomics. This approach could improve fair representation across populations by overcoming data accessibility challenges, while ensuring the reliability of genomic analyses conducted on artificial data.

bioinformatics↗

bioRxiv2024

Natural selection acting on complex traits hampers the predictive accuracy of polygenic scores in ancient samples

The prediction of phenotypes from ancient humans has gained interest due to its potential to investigate the evolution of complex traits. These predictions are commonly performed using polygenic scores computed with DNA information from ancient humans along with genome-wide association studies (GWAS) data from present-day humans. However, numerous evolutionary processes could impact the prediction of phenotypes from ancient humans based on polygenic scores. In this work we investigate how natural selection impacts phenotypic predictions on ancient individuals using polygenic scores. We use simulations of an additive trait to analyze how natural selection impacts phenotypic predictions with polygenic scores. We simulate a trait evolving under neutrality, stabilizing selection and directional selection. We find that stabilizing and directional selection have contrasting effects on ancient phenotypic predictions. Stabilizing selection accelerates the loss of large-effect alleles contributing to trait variation. Conversely, directional selection accelerates the loss of small and large-effect alleles that drive individuals farther away from the optimal phenotypic value. These effects result in specific shared genetic variation patterns between ancient and modern populations which hamper the accuracy of polygenic scores to predict phenotypes. Furthermore, we conducted simulations that include realistic strengths of stabilizing selection and heritability estimates to show how natural selection could impact the predictive accuracy of ancient polygenic scores for two widely studied traits: height and body mass index. We emphasize the importance of considering how natural selection can decrease the reliability of ancient polygenic scores to perform phenotypic predictions on an ancient population.

evolutionary biology↗

bioRxiv2023

Simulation-based Benchmarking of Ancient Haplotype Inference for Detecting Population Structure

Paleogenomic data has informed us about the movements, growth, and relationships of ancient populations. It has also given us context for medically relevant adaptations that appear in present-day humans due to introgression from other hominids, and it continues to help us characterize the evolutionary history of humans. However, ancient DNA (aDNA) presents several practical challenges as various factors such as deamination, high fragmentation, environmental contamination of aDNA, and low amounts of recoverable endogenous DNA, make aDNA recovery and analysis more difficult than modern DNA. Most studies with aDNA leverage only SNP data, and only a few studies have made inferences on human demographic history based on haplotype data, possibly because haplotype estimation (or phasing) has not yet been systematically evaluated in the context of aDNA. Here, we evaluate how the unique challenges of aDNA can impact phasing quality. We also develop a software tool that simulates aDNA taking into account the features of aDNA as well as the evolutionary history of the population. We measured phasing error as a function of aDNA quality and demographic history, and found that low phasing error is achievable even for very ancient individuals ([~] 400 generations in the past) as long as contamination and read depth are adequate. Our results show that population splits or bottleneck events occurring between the reference and phased populations affect phasing quality, with bottlenecks resulting in the highest average error rates. Finally, we found that using estimated haplotypes, even if not completely accurate, is superior to using the simulated genotype data when reconstructing changes in population structure after population splits between present-day and ancient populations. AvailabilityAll software used for simulation and analysis is available at github.com/Jazpy/Paleogenomic-Datasim

bioinformatics↗

bioRxiv2023

The MUC19 gene in Denisovans, Neanderthals, and Modern Humans: An Evolutionary History of Recurrent Introgression and Natural Selection

We study the gene MUC19, for which some modern humans carry a Denisovan-like haplotype. MUC19 is a mucin, a glycoprotein that forms gels with various biological functions. We find diagnostic variants for the Denisovan-like MUC19 haplotype at high frequencies in admixed Latin American individuals, and at highest frequency in 23 ancient Indigenous American individuals, all predating population admixture with Europeans and Africans. We find that the Denisovan-like MUC19 haplotype is under positive selection and carries a higher copy number of a 30 base-pair variable number tandem repeat, and that copy numbers of this repeat are exceedingly high in American populations. Finally, some Neanderthals carry the Denisovan-like MUC19 haplotype, and that it was likely introgressed into human populations through Neanderthal introgression rather than Denisovan introgression. One-Sentence SummaryModern humans and Neanderthals carry a Denisovan variant of the MUC19 gene, which is under positive selection in populations of Indigenous American ancestry.

evolutionary biology↗

bioRxiv2023

The impact of modern admixture on archaic human ancestry in human populations

Admixture, the genetic merging of parental populations resulting in mixed ancestry, has occurred frequently throughout the course of human history. Numerous admixture events have occurred between human populations across the world, as well as introgression between humans and archaic humans, Neanderthals and Denisovans. One example are genomes from populations in the Americas, as these are often mosaics of different ancestries due to recent admixture events as part of European colonization. In this study, we analyzed admixed populations from the Americas to assess whether the proportion and location of admixed segments due to recent admixture impact an individuals archaic ancestry. We identified a positive correlation between non-African ancestry and archaic alleles, as well as a slight enrichment of Denisovan alleles in Indigenous American segments relative to European segments in admixed genomes. We also identify several genes as candidates for adaptive introgression, based on archaic alleles present at high frequency in admixed American populations but low frequency in East Asian populations. These results provide insights into how recent admixture events between modern humans redistributed archaic ancestry in admixed genomes.

genomics↗

bioRxiv2022

The Utility of Ancestral and Derived Allele Sharing for Genome-Wide Inferences of Introgression

The past decade has ushered in a resurgence of studies highlighting the importance of introgression throughout the Tree of Life. Several methods exist for detecting and quantifying introgression on a genomic scale, yet the majority of these methods primarily utilize signals of derived allele sharing between donor and recipient populations. In this study, we exploit the fact that introgression will not only result in derived allele sharing but also the reintroduction of ancestral alleles to derive new estimators of the admixture proportion. Using coalescent simulations, we assess the performance of our new methods and the methods proposed in Lopez Fang et al. 2022 to assess the utility of incorporating shared ancestral variation into genome-wide inferences of introgression. Using coalescent theory, simulations, and applying our methods to human and canid data, we find that methods incorporating ancestral allele sharing are comparable to their derived allele sharing counterparts, in turn providing researchers with the opportunity to utilize more of the genomic signature of introgression.

evolutionary biology↗

bioRxiv2022

Integrating sex-bias into studies of archaic admixture on chromosome X

Evidence of interbreeding between archaic hominins and humans comes from methods that infer the locations of segments of archaic haplotypes, or archaic coverage using the genomes of people living today. As more estimates of archaic coverage have emerged, it has become clear that most of this coverage is found on the autosomes-- very little is retained on chromosome X. Here, we summarize published estimates of archaic coverage on autosomes and chromosome X from extant human samples. We find on average 7.9 times more archaic coverage on autosomes than chromosome X, and identify broad continental patterns in this ratio: greatest in American samples, and least in South Asian samples. We also perform extensive simulation studies to investigate how the amount of archaic coverage, lengths of coverage, and rates of purging of archaic coverage are affected by sex-bias caused by an unequal sex ratio within the archaic introgressors. Our results generally confirm that, with increasing male sex-bias, less archaic coverage is retained on chromosome X. Ours is the first study to explicitly model such sex-bias and its potential role in creating the dearth of archaic coverage on chromosome X. Author summaryTens of thousands of years ago, humans interbred with our close hominin relatives (e.g. Neanderthals), which we know from finding segments of archaic hominin DNA in our genomes. Up to 4% of a human genome may be archaic DNA, but most of that archaic part is on the autosomes (the non-sex chromosomes). Chromosome X usually contains 3 to 10 times less archaic DNA than the autosomes. Also unlike the autosomes, it is always passed down by mothers, but only sometimes by fathers. There are several hypotheses for why chromosome X has less archaic DNA than the autosomes; one that has not been fully explored is whether the archaic hominins that interbred with our ancestors were mostly male or mostly female, known as sex-bias. In this paper, we use simulations to investigate whether sex-bias could produce less archaic DNA on chromosome X. Using simulation studies, we find that when the archaics are mostly male, modern humans end up with less archaic DNA on chromosome X than their autosomes, compared to when there is a female-bias or no sex-bias. Therefore, male sex-bias could be contributing to the difference in the amount of archaic DNA on chromosome X versus the autosomes. Of course, there are still plenty of other factors to be explored about how demography and selection have shaped our DNA. Studying patterns like this helps us learn more about early hominin natural history, and contextualizes archaic interbreeding events among other sex-biased events in human history.

evolutionary biology↗

bioRxiv2022

Demographic history and genetic structure in pre-Hispanic Central Mexico

Aridoamerica and Mesoamerica are two distinct cultural areas that hosted numerous pre-Hispanic civilizations between 2,500 BCE and 1,521 CE. The division between these regions shifted southward due to severe droughts ca. 1,100 years ago, allegedly driving demographic changes and population replacement in some sites in central Mexico. Here, we present shotgun genome-wide data from 12 individuals and 26 mitochondrial genomes from eight pre-Hispanic archaeological sites across Mexico, including two at the shifting border of Aridoamerica and Mesoamerica. We find population continuity spanning the climate change episode and a broad preservation of the genetic structure across present-day Mexico for the last 2,300 years. Lastly, we identify a contribution to pre-Hispanic populations of northern and central Mexico from an ancient unsampled ghost population.

genomics↗

bioRxiv2022

Leveraging shared ancestral variation to detect local introgression

Introgression is a common evolutionary phenomenon that results in shared genetic material across non-sister taxa. Existing statistical methods such as Pattersons D statistic can detect introgression by measuring an excess of shared derived alleles between populations. The D statistic is effective to detect genome-wide patterns of introgression but can give spurious inferences of introgression when applied to local regions. We propose a new statistic, D+, that leverages both shared ancestral and derived alleles to infer local introgressed regions. Incorporating both shared derived and ancestral alleles increases the number of informative sites per region, improving our ability to identify local introgression. We use a coalescent framework to derive the expected value of this statistic as a function of different demographic parameters under an instantaneous admixture model and use coalescent simulations to compute the power and precision of D+. While the power of D and D+ is comparable, D+ has better precision than D. We apply D+ to empirical data from the 1000 Genome Project and Heliconius butterflies to infer local targets of introgression in humans and in butterflies.

evolutionary biology↗

bioRxiv2021

Archaic introgression and variation in pharmacogenes and implications for local adaptation

Modern humans carry both Neanderthal and Denisovan (archaic) genome elements that are part of the human gene pool and affect the life and health of living individuals. The impact of archaic DNA may be particularly evident in pharmacogenes - genes responsible for the processing of exogenous substances such as food, pollutants, and medications. However, the health implications and contribution of archaic ancestry in pharmacogenes of modern humans remains understudied. Here, we explore eleven key cytochrome P450 genes (CYP450) involved in drug metabolizing reactions in three Neanderthal and one Denisovan individuals as well as examine archaic introgression in modern human populations. We infer the metabolizing efficiency of these eleven CYP450 genes in archaic individuals and find important phenotypic differences relative to modern human variants. We identify several single nucleotide variants shared between archaic and modern humans in each gene, including some potentially function-altering mutations in archaic CYP450 genes, which may result in altered metabolism in living people carrying these variants. We highlight three genes which show evidence for archaic introgression into modern humans, as well as one additional gene that shows evidence for a gene duplication found only in Neanderthals and modern Africans.

evolutionary biology↗

bioRxiv2020

The history and evolution of the Denisovan-EPAS1 haplotype in Tibetans

Recent studies suggest that admixture with archaic hominins played an important role in facilitating biological adaptations to new environments. For example, interbreeding with Denisovans facilitated the adaptation to high altitude environments on the Tibetan Plateau. Specifically, the EPAS1 gene, a transcription factor that regulates the response to hypoxia, exhibits strong signatures of both positive selection and introgression from Denisovans in Tibetan individuals. Interestingly, despite being geographically closer to the Denisova cave, East Asian populations do not harbor as much Denisovan ancestry as populations from Melanesia. Recently, two studies have suggested two independent waves of Denisovan admixture into East Asians, one of which is shared with South Asians and Oceanians. Here we leverage data from EPAS1 in 78 Tibetan individuals to interrogate which of these two introgression events introduced the EPAS1 beneficial sequence into the ancestral population of Tibetans, and we use the distribution of introgressed segment lengths at this locus to infer the timing of the introgression and selection event. We find that the introgression event unique to East Asians most likely introduced the beneficial haplotype into the ancestral population of Tibetans around 43,000 (15,700-60,000) years ago, and selection started 12,000 (1,925-50,000) years ago. Our estimates suggest that one of the most convincing examples of adaptive introgression is in fact selection acting on standing archaic variation.

evolutionary biology↗

bioRxiv2020

ABO genetic variation in Neanderthals and Denisovans

1Variation at the ABO locus was one of the earliest sources of data in the study of human population identity and history, and to this day remains widely genotyped due to its importance in blood and tissue transfusions. Here, we look at ABO blood type variants in our archaic relatives: Neanderthals and Denisovans. Our goal is to understand the genetic landscape of the ABO gene in archaic humans, and how it relates to modern human ABO variation. We found two derived Neanderthal variants of the O allele in the Siberian Neanderthals (O1 and O2), one of these variants is shared with an European Neanderthal, who is a heterozygote for this O1 variant and a rare cis-AB variant. The Denisovan individual is heterozygous for two ancestral variant of the O1 allele, similar to variants found widely in modern humans. Perhaps more surprisingly, the O2 allele variant found in Siberian Neanderthals can be found at low frequencies in modern Europeans and Southeast Asians, and the O1 allele variant found in Siberian and European Neanderthal is also found at very low frequency in modern East Asians. Our genetic distance analyses suggest both alleles survive in modern humans due to inbreeding with Neanderthals. We find that the sequence backgrounds of the surviving Neanderthal-like O alleles in modern humans retain a higher sequence divergence than other surviving Neanderthal genome fragments, supporting a view of balancing selection operating in the Neanderthal ABO alleles by retaining highly diverse haplotypes compared to portions of the genome evolving neutrally.

genomics↗