Biology subjects

Patin, E.

Publications and source records attributed to Patin, E..

At least 19 recordsLinked to original sources

bioRxiv2026

A 4,000-year genomic history of Bantu speakers from the Congo rainforest

The Congo rainforest was the heartland of the Bantu Expansion, yet its demographic history remains partially understood. We inferred past population dynamics using genomes from 960 sub-Saharan Africans, including four newly sequenced ancient individuals from Iroungou cave and 176 present-day individuals from Gabon. Bantu-speaking populations began differentiating ~4,000 years ago, preceding explosive population growth by a millennium. Distinct southward dispersals contributed to the ancestry of Bantu speakers in Gabon and elsewhere in sub-Saharan Africa, with the ~700-year-old Iroungou individuals providing the closest genetic proxies for the latter. Both Bantu speakers and hunter-gatherers from the Congo rainforest experienced a major demographic crisis ~1,500 years ago, coinciding with an archaeological hiatus. These findings illuminate early Bantu dispersals and the subsequent, unexplained collapse of rainforest populations.

genomics↗

bioRxiv2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases

MotivationEpigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. ResultsWe developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG-searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. Availability and implementationThe eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

genetics↗

bioRxiv2026

Immune context unmasks regulatory effects of Neanderthal and Denisovan introgression

Neanderthal and Denisovan introgression have left a pervasive footprint in the human genome, yet its regulatory consequences remain poorly understood. Here we use a massively parallel reporter assay to characterize the cis-regulatory activity of 4,161 high-frequency introgressed variants across respiratory (A549), hepatic (HepG2), and hematopoietic (K562) cells exposed to immune and infectious stimuli. We find that ~18% of variants show differential activity between archaic and modern alleles, including 94 whose effects are revealed or modulated by stimulation, often in a cell type-specific manner. We identify loci, including STAT2, IL23A, and RNF41, where clusters of introgressed alleles exert coordinated regulatory effects consistent with adaptive programs. Finally, we dissect the mechanisms underlying the association between Neanderthal introgression and COVID-19 severity and show that the risk allele rs17713054-A, which displays the strongest effect in our assay, increases activity of a TNF--responsive enhancer in lung epithelial cells, directly upregulating SLC6A20.Together, these findings reveal widespread context-dependent regulatory effects of archaic introgression, with broad evolutionary and biomedical implications.

evolutionary biology↗

bioRxiv2025

Deep learning analyses of DNA sequences resolve the retention of the Duffy-null resistance to Plasmodium vivax malaria in Africa

P. vivax, the most geographically widespread human malaria parasite with millions of clinical cases per year, is however quasi absent in sub-Saharan Africa. Positive selection targeting the rs2814778 protective mutation, also known as the Duffy-null allele, may explain the absence (or quasi absence) of vivax in sub-Saharan Africa by a progressive purge of the pathogen due to a quasi-fixation of the Duffy-null allele and the resulting high rates of protected carriers in western, central and eastern populations. Yet, while positive selection has been clearly evidenced in admixed populations coexisting with vivax, the selection model currently admitted poorly explains the lack of the Duffy-null allele in Europe, or in Asia where the pathogen is mainly observed. In this article, several validated Deep Learning methods applied to high coverage sequence data obtained in 589 African individuals resolved this retention of the Duffy-null resistance to vivax in Africa. The CNN and GAN algorithms implemented in this study also predict a rise in frequency of the Duffy-null mutation due to selection 25-35 kya years ago in the western part of Africa, a geographical region and a time frame overlapping with the rise of another protective mutation, {beta}S, the sickle-cell mutation protective at heterozygous state against the malaria caused by P. falciparum. In addition, the pattern of Duffy-null haplotypes highlights a quick spread of the Duffy-null allele in sub-Saharan Africa due to post-admixture selection events following the road of the recent Bantu expansion. Independent lines of evidence describing malaria as a life-threatening disease in West Africa from [~]30 kya, together with a rise in frequency followed by recent disseminations of the Duffy-null resistance, open new perspectives about both the history of malaria as a major human disease and the history of the main protective mutations in Africa.

evolutionary biology↗

bioRxiv2024

Genetic Basis, Quantitative Nature, and Functional Relevance of Evolutionarily Conserved DNA Methylation

DNA methylation (DNAm) is a key epigenetic mark that modulates regulatory elements and gene expression, playing a crucial role in mammalian development and physiological function. Despite extensive characterization of DNAm profiles across species, little is known about its evolutionary conservation. Here, we conducted a comparative epigenome-wide analysis of great apes to identify and characterize sequence- and methylation-conserved CpGs (MCCs). Using 202 DNAm arrays, alongside 6 matched genotype and 13 matched transcriptomic datasets, we identified 11,500 MCCs for which methylation was evolutionarily related to sequences of CpGs and methylation quantitative trait loci. MCCs were the most stable across healthy human tissues and exhibited weaker genetic associations than other CpGs. Moreover, MCCs showed minimal associations with demographic, environmental factors, and noncancer diseases, yet demonstrated stronger associations with certain cancers than other CpGs, particularly gastrointestinal cancers. Functional enrichment analysis revealed that genes associated with MCC methylation in cancer were enriched for cancer driver genes and canonical cancer pathways, highlighting a significant regulatory role for MCCs in tumorigenesis. Collectively, our findings reveal the extent of DNAm conservation in great ape evolution, its association with genetic conservation, and its relevance to human diseases. These integrative analyses offer evolutionary insights into epigenetic variation and its functional implications in human populations.

genetics↗

bioRxiv2024

Nested admixture during and after the Trans-Atlantic Slave Trade on the island of Sao Tome

Human admixture history is rarely a simple process in which distinct populations, previously isolated for a long time, come into contact once to form an admixed population. In this study, we aim to reconstruct the complex admixture histories of the population of Sao Tome, an island in the Gulf of Guinea that was the site of the first slave-based plantation economy, and experienced successive waves of forced and deliberate migration from Africa. We examined 2.5 million SNPs newly genotyped in 96 Sao Tomeans and found that geography alone cannot explain the observed patterns of genetic differentiation within the island. We defined five genetic groups in Sao Tome based on the hypothesis that individuals sharing the most haplotypes are more likely to share similar genetic histories. Using Identical-by-Descent and different local ancestry inference methods, we inferred shared ancestries between 70 African and European populations and each Sao Tomean genetic group. We identified admixture events between admixed groups that were previously isolated on the island, showing how recently admixed populations can be themselves the sources of other admixture events. This study demonstrates how complex admixture and isolation histories during and after the Transatlantic Slave-Trade shaped extant individual genetic patterns at a local scale in Africa.

genetics↗

bioRxiv2024

Common DNA sequence variation influences epigenetic aging in African populations

Aging is associated with genome-wide changes in DNA methylation in humans, facilitating the development of epigenetic age prediction models. However, most of these models have been trained primarily on European-ancestry individuals, and none account for the impact of methylation quantitative trait loci (meQTL). To address these gaps, we analyzed the relationships between age, genotype, and CpG methylation in 3 understudied populations: central African Baka (n = 35), southern African {ddagger}Khomani San (n = 52), and southern African Himba (n = 51). We find that published prediction methods yield higher mean errors in these cohorts compared to European-ancestry individuals, and find that unaccounted-for DNA sequence variation may be a significant factor underlying this loss of accuracy. We leverage information about the associations between DNA genotype and CpG methylation to develop an age predictor that is minimally influenced by meQTL, and show that this model remains accurate across a broad range of genetic backgrounds. Intriguingly, we also find that the older individuals and those exhibiting relatively lower epigenetic age acceleration in our cohorts tend to carry more epigenetic age-reducing genetic variants, suggesting a novel mechanism by which heritable factors can influence longevity.

genetics↗

bioRxiv2023

A multivariate outcome test of covariance

Multivariate analysis is becoming central in studies investigating high-throughput molecular data, yet, some important features of these data are seldom explored. Here, we present MANOCCA (Multivariate Analysis of Conditional CovAriance), a powerful method to test for the effect of a predictor on the covariance matrix of a multivariate outcome. The proposed test is by construction orthogonal to tests based on the mean and variance, and is able to capture effects that are missed by both approaches. We first compare the performances of MANOCCA with existing correlation-based methods and show that MANOCCA is the only test correctly calibrated in simulation mimicking omics data. We then investigate the impact of reducing the dimensionality of the data using principal component analysis when the sample size is smaller than the number of pairwise covariance terms analysed. We show that, in many realistic scenarios, the maximum power can be achieved with a limited number of components. Finally, we apply MANOCCA to 1,000 healthy individuals from the Milieu Interieur cohort, to assess the effect of health, lifestyle and genetic factors on the covariance of two sets of phenotypes, blood biomarkers and flow cytometry-based immune phenotypes. Our analyses identify significant associations between multiple factors and the covariance of both omics data.

bioinformatics↗

bioRxiv2023

Deep estimation of the intensity and timing of selection from ancient genomes

Leveraging past allele frequencies has proven to be key to identify the impact of natural selection across time. However, this approach often suffers from imprecise estimations of the intensity (s) and timing (T) of selection particularly when ancient samples are scarce in specific epochs. Here, we aimed at bypassing the computation of past allele frequencies by implementing new convolutional neural networks (CNNs) algorithms that directly use ancient genotypes sampled across time to refine the estimations of selection parameters. Using computer simulations, we first show that genotype-based CNNs consistently outperform an approximate Bayesian computation (ABC) approach based on past allele frequency trajectories, regardless of the selection model assumed and of the amount of ancient genotypes available. When applying this method to empirical data from modern and ancient Europeans, we confirmed the reported excess of selection events in post-Neolithic Europe, independently of the continental subregion studied. Furthermore, we substantially refined the ABC-based estimations of s and T for a set of positively-and negatively-selected variants recently identified, including iconic cases of positive selection and experimentally validated disease-risk variants. Thanks to our CNN predictions we provide support to the history of recent and strong selection in northern Europe associated to the Black Death pandemic and confirm the heavy burden recently imposed by tuberculosis in Europe. These findings collectively support that detecting the imprints of natural selection on ancient genomes are crucial for unraveling the past history of severe human diseases.

evolutionary biology↗

bioRxiv2022

Environmental and genetic drivers of population differences in SARS-CoV-2 immune responses

Humans display vast clinical variability upon SARS-CoV-2 infection1-3, partly due to genetic and immunological factors4. However, the magnitude of population differences in immune responses to SARS-CoV-2 and the mechanisms underlying such variation remain unknown. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells from 222 healthy donors of various ancestries stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces a weaker, but more heterogeneous interferon-stimulated gene activity than influenza A virus, and a unique pro-inflammatory signature in myeloid cells. We observe marked population differences in transcriptional responses to viral exposure that reflect environmentally induced cellular heterogeneity, as illustrated by higher rates of cytomegalovirus infection, affecting lymphoid cells, in African-descent individuals. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell proportions on population differences in immune responses, with genetic variants having a narrower but stronger effect on specific loci. Additionally, natural selection has increased immune response differentiation across populations, particularly for variants associated with SARS-CoV-2 responses in East Asians. We document the cellular and molecular mechanisms through which Neanderthal introgression has altered immune functions, such as its impact on the myeloid response in Europeans. Finally, colocalization analyses reveal an overlap between the genetic architecture of immune responses to SARS-CoV-2 and COVID-19 severity. Collectively, these findings suggest that adaptive evolution targeting immunity has also contributed to current disparities in COVID-19 risk.

genomics↗

bioRxiv2022

Genetic adaptation to pathogens and increased risk of inflammatory disorders in post-Neolithic Europe

Ancient genomics can directly detect human genetic adaptation to environmental cues. However, it remains unclear how pathogens have exerted selective pressures on human genome diversity across different epochs and affected present-day inflammatory disease risk. Here, we use an ancestry-aware approximate Bayesian computation framework to estimate the nature, strength, and time of onset of selection acting on 2,879 ancient and modern European genomes from the last 10,000 years. We found that the bulk of genetic adaptation occurred after the start of the Bronze Age, <4,500 years ago, and was enriched in genes relating to host-pathogen interactions. Furthermore, we detected directional selection acting on specific leukocytic lineages and experimentally demonstrated that the strongest negatively selected immunity gene variant -- the lipopolysaccharide-binding protein gene (LBP) D283G -- is hypomorphic. Finally, our analyses suggest that the risk of inflammatory disorders has progressively increased in post-Neolithic Europeans, partly due to antagonistic pleiotropy following genetic adaptation to pathogens.

genetics↗

bioRxiv2022

The genomic landscape of contemporary western Remote Oceanians

The Vanuatu archipelago served as a gateway to Remote Oceania during one of the most extensive human migrations to uninhabited lands, ~3,000 years ago. Ancient DNA studies suggest an initial settlement by East Asian-related peoples that was quickly followed by the arrival of Papuan-related populations, leading to a major population turnover. Yet, there is uncertainty over the population processes and the sociocultural factors that have shaped the genomic diversity of ni-Vanuatu, who present nowadays among the worlds highest linguistic and cultural diversity. Here, we report new genome-wide data for 1,433 contemporary ni-Vanuatu from 29 different islands, including 287 couples. We find that ni-Vanuatu derive their East Asian- and Papuan-related ancestry from the same source populations and descend from relatively synchronous, sex-biased admixture events that occurred ~1,700-2,300 years ago, indicating a peopling history common to all the archipelago. However, East Asian-related ancestry proportions differ markedly across islands, suggesting that the Papuan-related population turnover was geographically uneven. Furthermore, we detect Polynesian ancestry arriving ~600-1,000 years ago to South Vanuatu in both Polynesian- and non-Polynesian-speaking populations. Lastly, we provide evidence for a tendency of spouses to carry similar genetic ancestry, when accounting for relatedness avoidance. The signal is not driven by strong genetic effects of specific loci or trait-associated variants, suggesting that it results instead from social assortative mating. Altogether, our findings provide insight into both the genetic history of ni-Vanuatu populations and how sociocultural processes have shaped the diversity of their genomes.

genomics↗

bioRxiv2021

The genomic signatures of natural selection in admixed human populations

Admixture has been a pervasive phenomenon in human history, shaping extensively the patterns of population genetic diversity. There is increasing evidence to suggest that admixture can also facilitate genetic adaptation to local environments, i.e., admixed populations acquire beneficial mutations from source populations, a process that we refer to as adaptive admixture. However, the role of adaptive admixture in human evolution and the power to detect it are poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, accounting for background selection and assuming different admixture scenarios. We show that two statistics based on admixture proportions, Fadm and LAD, show high power to detect mutations that are beneficial in the admixed population, whereas iHS and FST falsely detect neutral mutations that have been selected in the source populations only. By combining Fadm and LAD into a single statistic, we scanned the genomes of 15 worldwide, admixed populations for signatures of adaptive admixture. We confirm that lactase persistence and resistance to malaria have been under adaptive admixture in West Africa and in Madagascar, North Africa and South Asia, respectively. Our approach also uncovers new cases of adaptive admixture, including the APOL1/MYH9 locus in the Fulani nomads and PKN2 in East Indonesians, involved in resistance to infection and metabolism, respectively. Collectively, our study provides new evidence that adaptive admixture has occurred in multiple human populations, whose genetic history is characterized by periods of isolation and spatial expansions resulting in increased gene flow. Author summaryAdaptive introgression, i.e., the acquisition of adaptive traits through hybridization with another species, is a well-documented phenomenon in evolution. Conversely, adaptive admixture, i.e., the acquisition of adaptive traits through admixture between populations of the same species, is poorly described. In this study, we evaluate the importance of adaptive admixture in human recent evolutionary history. We first determine the expected signatures of adaptive admixture on patterns of genomic diversity, using realistic simulations. We then identify the methods that are the most powerful to detect such molecular signatures. Finally, by using the methods identified as the most powerful, we search for cases of adaptive admixture in the genomes of 15 admixed populations from around the globe. We find evidence that adaptive admixture has occurred in several populations from Northeast Africa, Southeast Asia and Oceania. This study suggests that admixture has indeed facilitated human genetic adaptation, particularly at genes involved in metabolism and resistance against pathogens.

genetics↗

bioRxiv2021

Factors Driving DNA Methylation Variation in Human Blood

Epigenetic changes are required for normal development, yet the nature and respective contribution of factors that drive epigenetic variation in humans remain to be fully characterized. Here, we assessed how the blood DNA methylome of 884 adults is affected by DNA sequence variation, age, sex and 139 factors relating to life habits and immunity. Furthermore, we investigated whether these effects are mediated or not by changes in cellular composition, measured by deep immunophenotyping. We show that DNA methylation differs substantially between naive and memory T cells, supporting the need for adjustment on these cell-types. By doing so, we find that latent cytomegalovirus infection drives DNA methylation variation and provide further support that the increased dispersion of DNA methylation with aging is due to epigenetic drift. Finally, our results indicate that cellular composition and DNA sequence variation are the strongest predictors of DNA methylation, highlighting critical factors for medical epigenomics studies.

genomics↗

bioRxiv2020

Negative selection on human genes causing severe inborn errors depends on disease outcome and both the mode and mechanism of inheritance

BackgroundGenetic variants underlying severe diseases are less likely to be transmitted to the next generation, and are thus gradually and selectively eliminated from the population through negative selection. Here, we study the determinants of this evolutionary process in genes underlying severe diseases in humans. ResultsWe propose a novel approach, CoNeS, integrating known negative selection scores through principal component projection. We compare evidence for negative selection at 319 genes underlying inborn errors of immunity (IEI), which are life-threatening monogenic disorders. We find that genes underlying autosomal dominant (AD) or X-linked IEI are under stronger negative selection than those underlying autosomal recessive (AR) IEI, which are under no stronger selection than genes not known to be disease-causing. However, we find that genes with mutations causing AR IEI that are lethal before reproductive maturity and that display complete penetrance are under stronger negative selection than other genes underlying AR IEI. We also find that genes underlying AD IEI by haploinsufficiency are under stronger negative selection than other genes underlying AD IEI. Finally, we replicate these results in a study of 1,140 genes causing inborn errors of neurodevelopment. ConclusionsThese findings collectively show that the clinical outcomes of inborn errors, together with the mode and mechanism of inheritance of these errors, determine the strength of negative selection acting on severe disease-causing genes. These findings suggest that estimating the intensity of negative selection with CoNeS may facilitate the selection of candidate genes in patients suspected to carry an inborn error.

genetics↗

bioRxiv2020

Stability and dynamics of the human gut microbiome and its association with systemic immune traits

Analysis of 1,363 deeply sequenced gut microbiome samples from 946 healthy donors of the Milieu Interieur cohort provides new opportunities to discover how the gut microbiome is associated with host factors and lifestyle parameters. Using a genome-based taxonomy to achieve higher resolution analysis, we found an enrichment of Prevotella species in males, and that bacterial profiles are dynamic across five decades of life (20-69), with Bacteroidota species consistently increased with age while Actinobacteriota species, including Bifidobacterium, decreased. Longitudinal sampling revealed short-term stability exceeds inter-individual differences; however, the degree of stability was variable between donors and influenced by their baseline community composition. We then integrated the microbiome results with systemic immunophenotypes to show that host/microbe associations discovered in animal models, such as T regulatory cells and short chain fatty acids, could be validated in human data. These results will enable personalized medicine approaches for microbial therapeutics and biomarkers.

microbiology↗

bioRxiv2019

A genome-wide Approximate Bayesian Computation approach suggests only limited numbers of soft sweeps in humans over the last 100,000 years

Over the last 100,000 years, humans have spread across the globe and encountered a highly diverse set of environments to which they have had to adapt. Genome-wide scans of selection are powerful to detect selective sweeps. However, because of unknown fractions of undetected sweeps and false discoveries, the numbers of detected sweeps often poorly reflect actual numbers of selective sweeps in populations. The thousands of soft sweeps on standing variation recently evidenced in humans have also been interpreted as a majority of mis-classified neutral regions. In such a context, the extent of human adaptation remains little understood. We present a new rationale to estimate these actual numbers of sweeps expected over the last 100,000 years (denoted by X) from genome-wide population data, both considering hard sweeps and selective sweeps on standing variation. We implemented an approximate Bayesian computation framework and showed, based on computer simulations, that such a method can properly estimate X. We then jointly estimated the number of selective sweeps, their mean intensity and age in several 1000G African, European and Asian populations. Our estimations of X, found weakly sensitive to demographic misspecifications, revealed very limited numbers of sweeps regardless the frequency of the selected alleles at the onset of selection and the completion of sweeps. We estimated [~]80 sweeps in average across fifteen 1000G populations when assuming incomplete sweeps only and [~]140 selective sweeps in non-African populations when incorporating complete sweeps in our simulations. The method proposed may help to address controversies on the number of selective sweeps in populations, guiding further genome-wide investigations of recent positive selection.

evolutionary biology↗

bioRxiv2019

Two common disease-associated TYK2 variants impact exon splicing and TYK2 dosage

TYK2 belongs to the JAK protein tyrosine kinase family and mediates signaling of numerous antiviral and immunoregulatory cytokines (type I and type III IFNs, IL-10, IL-12, IL-22, IL-23) in immune and non-immune cells. After many years of genetic association studies, TYK2 is recognized as a susceptibility gene for some inflammatory and autoimmune diseases (AID). Seven TYK2 variants have been associated with AIDs in Europeans, and establishing their causality remains challenging. Previous work showed that a protective variant (P1104A) is hypomorphic and also a risk allele for mycobacterial infection. Here, we have studied two AID-associated common TYK2 variants: rs12720270 located in intron 7 and rs2304256, a non-synonymous variant in exon 8 that causes a valine to phenylalanine substitution (c.1084 G > T, Val362Phe). We found that this amino acid substitution does not alter TYK2 expression, catalytic activity or ability to relay signaling in EBV-B cell lines or in reconstituted TYK2-null cells. Based on in silico predictions that these variants may impact splicing of exon 8, we: i) analyzed TYK2 transcripts in genotyped EBV-B cells and in CRISPR/Cas9-edited cells, ii) measured splicing using minigene assays, and iii) performed eQTL (expression quantitative trait locus) analysis of TYK2 transcripts in primary monocytes and whole blood cells. Our results reveal that the two variants promote the inclusion of exon 8, which, we demonstrate, is essential for TYK2 binding to cognate receptors. In addition and in line with GTEx (Genetic Tissue Expression) data, our eQTL results show that rs2304256 mildly enhances TYK2 expression in whole blood. In all, these findings suggest that these TYK2 variants are not neutral but instead have a potential impact in AID.

immunology↗