Genomic Signatures of Selective Pressures and Introgression from Archaic Hominins at Human Innate Immunity Genes

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.

Protective and stochastic correlation between infectious diseases and autoimmune disorders

A priori, early exposure to a wide range of bacteria, viruses, and parasites appears to fortify and regulate the immune system, potentially reducing the risk of autoimmune diseases. However, improving hygiene conditions in numerous societies has led to a reduction in these microbial exposures, which, according to certain theories, could contribute to an increase in autoimmune diseases. Indeed, molecular mimicry is a key factor triggering immune system reactions; while it seeks pathogens, it can bind to self-molecules, leading to autoimmune diseases associated with microbial infections. On the other hand, a hygiene-based approach aimed at reducing the load of infectious agents through better personal hygiene can be beneficial for such pathologies. This review sheds light on how the evolution of the innate immune system, following the evolution of molecular patterns associated with microbes, contributes to our protection but may also trigger autoimmune diseases linked to microbes. Furthermore, it addresses how hygiene conditions shield us against autoimmune diseases related to microbes but may lead to autoimmune pathologies not associated with microbes.

Inherited human RelB deficiency impairs innate and adaptive immunity to infection

We report two unrelated adults with homozygous (P1) or compound heterozygous (P2) private loss-of-function variants of V-Rel Reticuloendotheliosis Viral Oncogene Homolog B (RELB). The resulting deficiency of functional RelB impairs the induction of NFKB2 mRNA and NF-κB2 (p100/p52) protein by lymphotoxin in the fibroblasts of the patients. These defects are rescued by transduction with wild-type RELB complementary DNA (cDNA). By contrast, the response of RelB-deficient fibroblasts to Tumor Necrosis Factor (TNF) or IL-1β via the canonical NF-κB pathway remains intact. P1 and P2 have low proportions of naïve CD4+ and CD8+ T cells and of memory B cells. Moreover, their naïve B cells cannot differentiate into immunoglobulin G (IgG)- or immunoglobulin A (IgA)-secreting cells in response to CD40L/IL-21, and the development of IL-17A/F-producing T cells is strongly impaired in vitro. Finally, the patients produce neutralizing autoantibodies against type I interferons (IFNs), even after hematopoietic stem cell transplantation, attesting to a persistent dysfunction of thymic epithelial cells in T cell selection and central tolerance to some autoantigens. Thus, inherited human RelB deficiency disrupts the alternative NF-κB pathway, underlying a T- and B cell immunodeficiency, which, together with neutralizing autoantibodies against type I IFNs, confers a predisposition to viral, bacterial, and fungal infections.

Local genetic adaptation to habitat in wild chimpanzees

How populations adapt to their environment is a fundamental question in biology. Yet we know surprisingly little about this process, especially for endangered species such as non-human great apes. Chimpanzees, our closest living relatives, are particularly interesting because they inhabit diverse habitats, from rainforest to woodland-savannah. Whether genetic adaptation facilitates such habitat diversity remains unknown, despite having wide implications for evolutionary biology and conservation. Using 828 newly generated exomes from wild chimpanzees, we find evidence of fine-scale genetic adaptation to habitat. Notably, adaptation to malaria in forest chimpanzees is mediated by the same genes underlying adaptation to malaria in humans. This work demonstrates the power of non-invasive samples to reveal genetic adaptations in endangered populations and highlights the importance of adaptive genetic diversity for chimpanzees.

Adaptive Evolution of Two Distinct Adaptive Haplotypes of Neanderthal Origin at the Immunoglobulin Heavy-chain Locus in East Asian and European Populations

Immunoglobulins (Igs) have a crucial role in humoral immunity. Two recent studies have reported a high-frequency Neanderthal-introgressed haplotype throughout Eurasia and a high-frequency Neanderthal-introgressed haplotype specific to southern East Asia at the immunoglobulin heavy-chain (IGH) gene locus on chromosome 14q32.33. Surprisingly, we found the previously reported high-frequency Neanderthal-introgressed haplotype does not exist throughout Eurasia. Instead, our study identified two distinct high-frequency haplotypes of putative Neanderthal origin in East Asia and Europe, although they shared introgressed alleles. Notably, the alleles of putative Neanderthal origin reduced the expression of IGHG1 and increased the expression of IGHG2 and IGHG3 in various tissues. These putatively introgressed alleles also affected the production of IgG1 upon antigen stimulation and increased the risk of systemic lupus erythematosus. Additionally, the greatest genetic differentiation across the whole genome between southern and northern East Asians was observed for the East Asian haplotype of putative Neanderthal origin. The frequency decreased from southern to northern East Asia and correlated positively with the genome-wide proportion of southern East Asian ancestry, indicating that this putative positive selection likely occurred in the common ancestor of southern East Asian populations before the admixture with northern East Asian populations.

G-quadruplex propensity in H. neanderthalensis, H. sapiens and Denisovans mitochondrial genomes

Current methods of processing archaeological samples combined with advances in sequencing methods lead to disclosure of a large part of H. neanderthalensis and Denisovans genetic information. It is hardly surprising that the genome variability between modern humans, Denisovans and H. neanderthalensis is relatively limited. Genomic studies may provide insight on the metabolism of extinct human species or lineages. Detailed analysis of G-quadruplex sequences in H. neanderthalensis and Denisovans mitochondrial DNA showed us interesting features. Relatively similar patterns in mitochondrial DNA are found compared to modern humans, with one notable exception for H. neanderthalensis. An interesting difference between H. neanderthalensis and H. sapiens corresponds to a motif found in the D-loop region of mtDNA, which is responsible for mitochondrial DNA replication. This area is directly responsible for the number of mitochondria and consequently for the efficient energy metabolism of cell. H. neanderthalensis harbor a long uninterrupted run of guanines in this region, which may cause problems for replication, in contrast with H. sapiens, for which this run is generally shorter and interrupted. One may propose that the predominant H. sapiens motif provided a selective advantage for modern humans regarding mtDNA replication and function.

Bacterial sepsis triggers stronger transcriptomic immune responses in larger primates

Empirical data relating body mass to immune defence against infections remain limited. Although the metabolic theory of ecology predicts that larger organisms would have weaker immune responses, recent studies have suggested that the opposite may be true. These discoveries have led to the safety factor hypothesis, which proposes that larger organisms have evolved stronger immune defences because they carry greater risks of exposure to pathogens and parasites. In this study, we simulated sepsis by exposing blood from nine primate species to a bacterial lipopolysaccharide (LPS), measured the relative expression of immune and other genes using RNAseq, and fitted phylogenetic models to determine how gene expression was related to body mass. In contrast to non-immune-annotated genes, we discovered hypermetric scaling in the LPS-induced expression of innate immune genes, such that large primates had a disproportionately greater increase in gene expression of immune genes compared to small primates. Hypermetric immune gene expression appears to support the safety factor hypothesis, though this pattern may represent a balanced evolutionary mechanism to compensate for lower per-transcript immunological effectiveness. This study contributes to the growing body of immune allometry research, highlighting its importance in understanding the complex interplay between body size and immunity over evolutionary timescales.

Copy number and selection of MHC genes in ruminants are related to habitat, average life span and diet

The ruminants, as the main group of livestock, have been extensively studied in terms of their physiology, endocrinology, biochemistry, genetics, and nutrition. Despite the wide geographic distribution and habitat diversity of animals in this group, their ecology and evolution remain poorly understood. In this study, we analyzed the gene copy number, selection, and ecological and evolutionary processes that have affected the evolution of major histocompatibility complex (MHC) genes across ruminant lineages based on available genomic data. The 51 species analyzed represented all six families of ruminants. Our finding indicated that the architecture of the MHC region is conserved in ruminants, but with variable copy numbers of MHC-I, MHC-IIA, and MHC-IIB genes. No lineage-specific gene duplication was observed in the MHC genes. The phylogenetic generalized least squares regression (PGLS) model revealed association between ecological and biological factors (habitat and lifespan) and gene duplication in DQA and DQB, but not in DRB. The selection pressure of DQA and DQB were related with lifespan, diet, and the ratio of genetic repeat elements. These results suggest that the MHC evolution in ruminants, including copy number and selection, has been influenced by genetic repeat elements, pathogen exposure risk, and intrinsic cost of possessing multiple MHC genes.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in nonmodel species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to nonmodel genomes. We apply ABC-MK to the human proteome and a set of known virus interacting proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Type I interferon pathway genetic variants in severe COVID-19

Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by SARS-CoV-2. According to the World Health Organization (WHO), there have been over 760 million reported cases and over 6 million deaths caused by this disease worldwide. The severity of COVID-19 is based on symptoms presented by the patient and is divided as asymptomatic, mild, moderate, severe, and critical. The manifestations are interconnected with genetic variations. The innate immunity is the quickest response mechanism of an organism against viruses. Type I interferon pathway plays a key role in antiviral responses due to viral replication inhibition in infected cells and adaptive immunity stimulation induced by interferon molecules. Thus, variants in type I interferon pathway's genes are being studied in different COVID-19 manifestations. This review summarizes the role of variants in type I interferon pathway's genes on prognosis and severity progression of COVID-19.

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.

Population-enriched innate immune variants may identify candidate gene targets at the intersection of cancer and cardio-metabolic disease

Both cancer and cardio-metabolic disease disparities exist among specific populations in the US. For example, African Americans experience the highest rates of breast and prostate cancer mortality and the highest incidence of obesity. Native and Hispanic Americans experience the highest rates of liver cancer mortality. At the same time, Pacific Islanders have the highest death rate attributed to type 2 diabetes (T2D), and Asian Americans experience the highest incidence of non-alcoholic fatty liver disease (NAFLD) and cancers induced by infectious agents. Notably, the pathologic progression of both cancer and cardio-metabolic diseases involves innate immunity and mechanisms of inflammation. Innate immunity in individuals is established through genetic inheritance and external stimuli to respond to environmental threats and stresses such as pathogen exposure. Further, individual genomes contain characteristic genetic markers associated with one or more geographic ancestries (ethnic groups), including protective innate immune genetic programming optimized for survival in their corresponding ancestral environment(s). This perspective explores evidence related to our working hypothesis that genetic variations in innate immune genes, particularly those that are commonly found but unevenly distributed between populations, are associated with disparities between populations in both cancer and cardio-metabolic diseases. Identifying conventional and unconventional innate immune genes that fit this profile may provide critical insights into the underlying mechanisms that connect these two families of complex diseases and offer novel targets for precision-based treatment of cancer and/or cardio-metabolic disease.

Extraction of Innate Immune Genes in Dairy Cattle and the Regulation of Their Expression in Early Embryos

As more and more of the available genomic data have been published, several databases have been developed for deciphering early mammalian embryogenesis; however, less research has been conducted on the regulation of the expression of natural immunity genes during early embryonic development in dairy cows. To this end, we explored the regulatory mechanism of innate immunity genes at the whole-genome level. Based on comparative genomics, 1473 innate immunity genes in cattle were obtained by collecting the latest reports on human innate immunity genes and updated bovine genome data for comparison, and a preliminary database of bovine innate immunity genes was constructed. In order to determine the regulatory mechanism of innate immune genes in dairy cattle early embryos, we conducted weighted co-expression network analysis of the innate immune genes at different developmental stages of dairy cattle early embryos. The results showed that specific module-related genes were significantly enriched in the MAPK signaling pathway. Protein-protein interaction (PPI) analysis showed gene interactions in each specific module, and 10 of the highest connectivity genes were chosen as potential hub genes. Finally, combined with the results for differential expressed genes (DEGs), ATF3, IL6, CD8A, CD69, CD86, HCK, ERBB3, LCK, ITGB2, LYN, and ERBB2 were identified as the key genes of innate immunity in dairy cattle early embryos. In conclusion, the bovine innate immunity gene set was determined and the co-expression network of innate immunity genes in the early embryonic stage of dairy cattle was constructed by comparing and analyzing the whole genome of bovines and humans. The findings in this study provide the basis for exploring the involvement and regulation of innate immune genes in the early embryonic development of dairy cattle.

Atherosclerosis as the Damocles' sword of human evolution: insights from nonhuman ape-like primates, ancient human remains, and isolated modern human populations

Atherosclerosis is the leading cause of death worldwide, and the predominant risk factors are advanced age and high-circulating low-density lipoprotein cholesterol (LDL-C). However, the findings of atherosclerosis in relatively young mummified remains and a lack of atherosclerosis in chimpanzees despite high LDL-C call into question the role of traditional cardiovascular risk factors. The inflammatory theory of atherosclerosis may explain the discrepancies between traditional risk factors and observed phenomena in current literature. Following the divergence from chimpanzees several millennia ago, loss of function mutations in immune regulatory genes and changes in gene expression have resulted in an overactive human immune system. The ubiquity of atherosclerosis in the modern era may reflect a selective pressure that enhanced the innate immune response at the cost of atherogenesis and other chronic disease states. Evidence provided from the fields of genetics, evolutionary biology, and paleoanthropology demonstrates a sort of circular dependency between inflammation, immune system functioning, and evolution at both a species and cellular level. More recently, the role of proinflammatory stimuli, somatic mutations, and the gene-environment effect appear to be underappreciated elements in the development and progression of atherosclerosis. Neurobiological stress, metabolic syndrome, and traditional cardiovascular risk factors may instead function as intermediary links between inflammation and atherosclerosis. Therefore, considering evolution as a mechanistic process and atherosclerosis as part of the inertia of evolution, greater insight into future preventative and therapeutic interventions for atherosclerosis can be gained by examining the past.

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.

Ethnic and functional differentiation of copy number polymorphisms in Tunisian and HapMap population unveils insights on genome organizational plasticity

Admixture mapping has been useful in identifying genetic variations linked to phenotypes, adaptation and diseases. Copy number variations (CNVs) represents genomic structural variants spanning large regions of chromosomes reaching several megabases. In this investigation, the "Canary" algorithm was applied to 102 Tunisian samples and 991 individuals from eleven HapMap III populations to genotype 1279 copy number polymorphisms (CNPs). In this present work, we investigate the Tunisian population structure using the CNP makers previously identified among Tunisian. The study revealed that Sub-Saharan African populations exhibited the highest diversity with the highest proportions of allelic CNPs. Among all the African populations, Tunisia showed the least diversity. Individual ancestry proportions computed using STRUCTURE analysis revealed a major European component among Tunisians with lesser contribution from Sub-Saharan Africa and Asia. Population structure analysis indicated the genetic proximity with Europeans and noticeable distance from the Sub-Saharan African and East Asian clusters. Seven genes harbouring Tunisian high-frequent CNPs were identified known to be associated with 9 Mendelian diseases and/or phenotypes. Functional annotation of genes under selection highlighted a noteworthy enrichment of biological processes to receptor pathway and activity as well as glutathione metabolism. Additionally, pathways of potential concern for health such as drug metabolism, infectious diseases and cancers exhibited significant enrichment. The distinctive genetic makeup of the Tunisians might have been influenced by various factors including natural selection and genetic drift, resulting in the development of distinct genetic variations playing roles in specific biological processes. Our research provides a justification for focusing on the exclusive genome organization of this population and uncovers previously overlooked elements of the genome.

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.

Disentangling archaic introgression and genomic signatures of selection at human immunity genes

Pathogens and infectious diseases have imposed exceptionally strong selective pressure on ancient and modern human genomes and contributed to the current variation in many genes. There is evidence that modern humans acquired immune variants through interbreeding with ancient hominins, but the impact of such variants on human traits is not fully understood. The main objectives of this research were to infer the genetic signatures of positive selection that may be involved in adaptation to infectious diseases and to investigate the function of Neanderthal alleles identified within a set of 50 Lithuanian genomes. Introgressed regions were identified using the machine learning tool ArchIE. Recent positive selection signatures were analysed using iHS. We detected high-scoring signals of positive selection at innate immunity genes (EMB, PARP8, HLAC, and CDSN) and evaluated their interactions with the structural proteins of pathogens. Interactions with human immunodeficiency virus (HIV) 1 and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) were identified. Overall, genomic regions introgressed from Neanderthals were shown to be enriched in genes related to immunity, keratinocyte differentiation, and sensory perception.

Infectious disease in the Pleistocene: Old friends or old foes?

The impact of endemic and epidemic disease on humans has traditionally been seen as a comparatively recent historical phenomenon associated with the Neolithisation of human groups, an increase in population size led by sedentarism, and increasing contact with domesticated animals as well as species occupying opportunistic symbiotic and ectosymbiotic relationships with humans. The orthodox approach is that Neolithisation created the conditions for increasing population size able to support a reservoir of infectious disease sufficient to act as selective pressure. This orthodoxy is the result of an overly simplistic reliance on skeletal data assuming that no skeletal lesions equated to a healthy individual, underpinned by the assumption that hunter-gatherer groups were inherently healthy while agricultural groups acted as infectious disease reservoirs. The work of van Blerkom, Am. J. Phys. Anthropol., vol. suppl 37 (2003), Wolfe et al., Nature, vol. 447 (2007) and Houldcroft and Underdown, Am. J. Phys. Anthropol., vol. 160, (2016) has changed this landscape by arguing that humans and pathogens have long been fellow travelers. The package of infectious diseases experienced by our ancient ancestors may not be as dissimilar to modern infectious diseases as was once believed. The importance of DNA, from ancient and modern sources, to the study of the antiquity of infectious disease, and its role as a selective pressure cannot be overstated. Here we consider evidence of ancient epidemic and endemic infectious diseases with inferences from modern and ancient human and hominin DNA, and from circulating and extinct pathogen genomes. We argue that the pandemics of the past are a vital tool to unlock the weapons needed to fight pandemics of the future.

Assessing the Presence of Recent Adaptation in the Human Genome With Mixture Density Regression

How much genome differences between species reflect neutral or adaptive evolution is a central question in evolutionary genomics. In humans and other mammals, the presence of adaptive versus neutral genomic evolution has proven particularly difficult to quantify. The difficulty notably stems from the highly heterogeneous organization of mammalian genomes at multiple levels (functional sequence density, recombination, etc.) which complicates the interpretation and distinction of adaptive versus neutral evolution signals. In this study, we introduce mixture density regressions (MDRs) for the study of the determinants of recent adaptation in the human genome. MDRs provide a flexible regression model based on multiple Gaussian distributions. We use MDRs to model the association between recent selection signals and multiple genomic factors likely to affect the occurrence/detection of positive selection, if the latter was present in the first place to generate these associations. We find that an MDR model with two Gaussian distributions provides an excellent fit to the genome-wide distribution of a common sweep summary statistic (integrated haplotype score), with one of the two distributions likely enriched in positive selection. We further find several factors associated with signals of recent adaptation, including the recombination rate, the density of regulatory elements in immune cells, GC content, gene expression in immune cells, the density of mammal-wide conserved elements, and the distance to the nearest virus-interacting gene. These results support the presence of strong positive selection in recent human evolution and highlight MDRs as a powerful tool to make sense of signals of recent genomic adaptation.

An efficient and robust ABC approach to infer the rate and strength of adaptation

Inferring the effects of positive selection on genomes remains a critical step in characterizing the ultimate and proximate causes of adaptation across species, and quantifying positive selection remains a challenge due to the confounding effects of many other evolutionary processes. Robust and efficient approaches for adaptation inference could help characterize the rate and strength of adaptation in non-model species for which demographic history, mutational processes, and recombination patterns are not currently well-described. Here, we introduce an efficient and user-friendly extension of the McDonald-Kreitman test (ABC-MK) for quantifying long-term protein adaptation in specific lineages of interest. We characterize the performance of our approach with forward simulations and find that it is robust to many demographic perturbations and positive selection configurations, demonstrating its suitability for applications to non-model genomes. We apply ABC-MK to the human proteome and a set of known Virus Interacting Proteins (VIPs) to test the long-term adaptation in genes interacting with viruses. We find substantially stronger signatures of positive selection on RNA-VIPs than DNA-VIPs, suggesting that RNA viruses may be an important driver of human adaptation over deep evolutionary time scales.

Dissecting human population variation in single-cell responses to SARS-CoV-2

Humans display substantial interindividual clinical variability after SARS-CoV-2 infection1-3, the genetic and immunological basis of which has begun to be deciphered4. However, the extent and drivers of population differences in immune responses to SARS-CoV-2 remain unclear. Here we report single-cell RNA-sequencing data for peripheral blood mononuclear cells-from 222 healthy donors of diverse ancestries-that were stimulated with SARS-CoV-2 or influenza A virus. We show that SARS-CoV-2 induces weaker, but more heterogeneous, interferon-stimulated gene activity compared with influenza A virus, and a unique pro-inflammatory signature in myeloid cells. Transcriptional responses to viruses display marked population differences, primarily driven by changes in cell abundance including increased lymphoid differentiation associated with latent cytomegalovirus infection. Expression quantitative trait loci and mediation analyses reveal a broad effect of cell composition on population disparities in immune responses, with genetic variants exerting a strong effect on specific loci. Furthermore, we show that natural selection has increased population differences in immune responses, particularly for variants associated with SARS-CoV-2 response in East Asians, and document the cellular and molecular mechanisms by which Neanderthal introgression has altered immune functions, such as the response of myeloid cells to viruses. Finally, colocalization and transcriptome-wide association analyses reveal an overlap between the genetic basis of immune responses to SARS-CoV-2 and COVID-19 severity, providing insights into the factors contributing to current disparities in COVID-19 risk.

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.

Molecular de-extinction of ancient antimicrobial peptides enabled by machine learning

Molecular de-extinction could offer avenues for drug discovery by reintroducing bioactive molecules that are no longer encoded by extant organisms. To prospect for antimicrobial peptides encrypted within extinct and extant human proteins, we introduce the panCleave random forest model for proteome-wide cleavage site prediction. Our model outperformed multiple protease-specific cleavage site classifiers for three modern human caspases, despite its pan-protease design. Antimicrobial activity was observed in vitro for modern and archaic protein fragments identified with panCleave. Lead peptides showed resistance to proteolysis and exhibited variable membrane permeabilization. Additionally, representative modern and archaic protein fragments showed anti-infective efficacy against A. baumannii in both a skin abscess infection model and a preclinical murine thigh infection model. These results suggest that machine-learning-based encrypted peptide prospection can identify stable, nontoxic peptide antibiotics. Moreover, we establish molecular de-extinction through paleoproteome mining as a framework for antibacterial drug discovery.

Identifying signatures of positive selection in human populations from North Africa

Because of its location, North Africa (NA) has witnessed continuous demographic movements with an impact on the genomes of present-day human populations. Genomic data describe a complex scenario with varying proportions of at least four main ancestry components: Maghrebi, Middle Eastern-, European-, and West-and-East-African-like. However, the footprint of positive selection in NA has not been studied. Here, we compile genome-wide genotyping data from 190 North Africans and individuals from surrounding populations, investigate for signatures of positive selection using allele frequencies and linkage disequilibrium-based methods and infer ancestry proportions to discern adaptive admixture from post-admixture selection events. Our results show private candidate genes for selection in NA involved in insulin processing (KIF5A), immune function (KIF5A, IL1RN, TLR3), and haemoglobin phenotypes (BCL11A). We also detect signatures of positive selection related to skin pigmentation (SLC24A5, KITLG), and immunity function (IL1R1, CD44, JAK1) shared with European populations and candidate genes associated with haemoglobin phenotypes (HPSE2, HBE1, HBG2), other immune-related (DOCK2) traits, and insulin processing (GLIS3) traits shared with West and East African populations. Finally, the SLC8A1 gene, which codifies for a sodium-calcium exchanger, was the only candidate identified under post-admixture selection in Western NA.

Archaic humans have contributed to large-scale variation in modern human T cell receptor genes

Human T cell receptors (TCRs) are critical for mediating immune responses to pathogens and tumors and regulating self-antigen recognition. Yet, variations in the genes encoding TCRs remain insufficiently defined. Detailed analysis of expressed TCR alpha, beta, gamma, and delta genes in 45 donors from four human populations-African, East Asian, South Asian, and European-revealed 175 additional TCR variable and junctional alleles. Most of these contained coding changes and were present at widely differing frequencies in the populations, a finding confirmed using DNA samples from the 1000 Genomes Project. Importantly, we identified three Neanderthal-derived, introgressed TCR regions including a highly divergent TRGV4 variant, which mediated altered butyrophilin-like molecule 3 (BTNL3) ligand reactivity and was frequent in all modern Eurasian population groups. Our results demonstrate remarkable variation in TCR genes in both individuals and populations, providing a strong incentive for including allelic variation in studies of TCR function in human biology.

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 candidate variant in immunity genes, lipopolysaccharide-binding protein (LBP) D283G, is hypomorphic. Finally, our analyses suggest that the risk of inflammatory disorders has increased in post-Neolithic Europeans, possibly because of antagonistic pleiotropy following genetic adaptation to pathogens.

The computational implementation of a platform of relative identity-by-descent scores algorithm for introgressive mapping

With the development of genotyping and sequencing technology, researchers working in the area of conservation genetics are able to obtain the genotypes or even the sequences of a representative sample of individuals from the population. It is of great importance to examine the genomic variants and genes that are highly preferred or pruned during the process of adaptive introgression or long-term hybridization. To the best of our knowledge, we are the first to develop a platform with computational integration of a relative identity-by-descent (rIBD) scores algorithm for introgressive mapping. The rIBD algorithm is designed for mapping the fine-scaled genomic regions under adaptive introgression between the source breeds and the admixed breed. Our rIBD calculation platform provides compact functions including reading input information and uploading of files, rIBD calculation, and presentation of the rIBD scores. We analyzed the simulated data using the rIBD calculation platform and calculated the average IBD score of 0.061 with a standard deviation of 0.124. The rIBD scores generally follow a normal distribution, and a cut-off of 0.432 and -0.310 for both positive and negative rIBD scores is derived to enable the identification of genomic regions showing significant introgression signals from the source breed to the admixed breed. A list of genomic regions with detailed calculated rIBD scores is reported, and all the rIBD scores for each of the considered windows are presented in plots on the rIBD calculation platform. Our rIBD calculation platform provides a user-friendly tool for the calculation of fine-scaled rIBD scores for each of the genomic regions to map possible functional genomic variants due to adaptive introgression or long-term hybridization.

MaLAdapt Reveals Novel Targets of Adaptive Introgression From Neanderthals and Denisovans in Worldwide Human Populations

Adaptive introgression (AI) facilitates local adaptation in a wide range of species. Many state-of-the-art methods detect AI with ad-hoc approaches that identify summary statistic outliers or intersect scans for positive selection with scans for introgressed genomic regions. Although widely used, approaches intersecting outliers are vulnerable to a high false-negative rate as the power of different methods varies, especially for complex introgression events. Moreover, population genetic processes unrelated to AI, such as background selection or heterosis, may create similar genomic signals to AI, compromising the reliability of methods that rely on neutral null distributions. In recent years, machine learning (ML) methods have been increasingly applied to population genetic questions. Here, we present a ML-based method called MaLAdapt for identifying AI loci from genome-wide sequencing data. Using an Extra-Trees Classifier algorithm, our method combines information from a large number of biologically meaningful summary statistics to capture a powerful composite signature of AI across the genome. In contrast to existing methods, MaLAdapt is especially well-powered to detect AI with mild beneficial effects, including selection on standing archaic variation, and is robust to non-AI selective sweeps, heterosis from deleterious mutations, and demographic misspecification. Furthermore, MaLAdapt outperforms existing methods for detecting AI based on the analysis of simulated data and the validation of empirical signals through visual inspection of haplotype patterns. We apply MaLAdapt to the 1000 Genomes Project human genomic data and discover novel AI candidate regions in non-African populations, including genes that are enriched in functionally important biological pathways regulating metabolism and immune responses.

Natural selection of immune and metabolic genes associated with health in two lowland Bolivian populations

A growing body of work has addressed human adaptations to diverse environments using genomic data, but few studies have connected putatively selected alleles to phenotypes, much less among underrepresented populations such as Amerindians. Studies of natural selection and genotype-phenotype relationships in underrepresented populations hold potential to uncover previously undescribed loci underlying evolutionarily and biomedically relevant traits. Here, we worked with the Tsimane and the Moseten, two Amerindian populations inhabiting the Bolivian lowlands. We focused most intensively on the Tsimane, because long-term anthropological work with this group has shown that they have a high burden of both macro and microparasites, as well as minimal cardiometabolic disease or dementia. We therefore generated genome-wide genotype data for Tsimane individuals to study natural selection, and paired this with blood mRNA-seq as well as cardiometabolic and immune biomarker data generated from a larger sample that included both populations. In the Tsimane, we identified 21 regions that are candidates for selective sweeps, as well as 5 immune traits that show evidence for polygenic selection (e.g., C-reactive protein levels and the response to coronaviruses). Genes overlapping candidate regions were strongly enriched for known involvement in immune-related traits, such as abundance of lymphocytes and eosinophils. Importantly, we were also able to draw on extensive phenotype information for the Tsimane and Moseten and link five regions (containing PSD4, MUC21 and MUC22, TOX2, ANXA6, and ABCA1) with biomarkers of immune and metabolic function. Together, our work highlights the utility of pairing evolutionary analyses with anthropological and biomedical data to gain insight into the genetic basis of health-related traits.

Complex patterns shape immune genes diversity during invasion of common raccoon in Europe - Selection in action despite genetic drift

Rapid adaptation is common in invasive populations and is crucial to their long-term success. The primary target of selection in the invasive species' new range is standing genetic variation. Therefore, genetic drift and natural selection acting on existing variation are key evolutionary processes through which invaders will evolve over a short timescale. In this study, we used the case of the raccoon Procyon lotor invasion in Europe to identify the forces shaping the diversity of immune genes during invasion. The genes involved in the defence against infection should be under intense selection pressure in the invasive range where novel pathogens are expected to occur. To disentangle the selective and demographic processes shaping the adaptive immune diversity of its invasive and expanding populations, we have developed species-specific single-nucleotide polymorphism markers located in the coding regions of targeted immune-related genes. We characterised the genetic diversity of 110 functionally important immune genes in two invasive and one native raccoon genetic clusters, each presenting a different demographic history. Despite the strong effect of demographic processes in the invasive clusters, we detected a subset of genes exhibiting the diversity pattern suggestive of selection. The most likely process shaping the variation in those genes was balancing selection. The selected genes belong to toll-like receptors and cytokine-related genes. Our results suggest that the prevalence of selection depends on the level of diversity, that is - less genetically diverse invasive population from the Czech Republic displayed fewer signs of selection. Our results highlight the role of standing genetic variation in adapting to new environment. Understanding the evolutionary mechanisms behind invasion success would enable predicting how populations may respond to environmental change.

The role of Neanderthal introgression in liver cancer

BACKGROUND

Neanderthal introgressed DNA has been linked to different normal and disease traits including immunity and metabolism-two important functions that are altered in liver cancer. However, there is limited understanding of the relationship between Neanderthal introgression and liver cancer risk. The aim of this study was to investigate the relationship between Neanderthal introgression and liver cancer risk.

METHODS

Using germline and somatic DNA and tumor RNA from liver cancer patients from The Cancer Genome Atlas, along with ancestry-match germline DNA from unaffected individuals from the 1000 Genomes Resource, and allele specific expression data from normal liver tissue from The Genotype-Tissue Expression project we investigated whether Neanderthal introgression impacts cancer etiology. Using a previously generated set of Neanderthal alleles, we identified Neanderthal introgressed haplotypes. We then tested whether somatic mutations are enriched or depleted on Neanderthal introgressed haplotypes compared to modern haplotypes. We also computationally assessed whether somatic mutations have a functional effect or show evidence of regulating expression of Neanderthal haplotypes. Finally, we compared patterns of Neanderthal introgression in liver cancer patients and the general population.

RESULTS

We find Neanderthal introgressed haplotypes exhibit an excess of somatic mutations compared to modern haplotypes. Variant Effect Predictor analysis revealed that most of the somatic mutations on these Neanderthal introgressed haplotypes are not functional. We did observe expression differences of Neanderthal alleles between tumor and normal for four genes that also showed a pattern of enrichment of somatic mutations on Neanderthal haplotypes. However, gene expression was similar between liver cancer patients with modern ancestry and liver cancer patients with Neanderthal ancestry at these genes. Provocatively, when analyzing all genes, we find evidence of Neanderthal introgression regulating expression in tumor from liver cancer patients in two genes, ARK1C4 and OAS1. Finally, we find that most genes do not show a difference in the proportion of Neanderthal introgression between liver cancer patients and the general population.

CONCLUSION

Our results suggest that Neanderthal introgression provides opportunity for somatic mutations to accumulate, and that some Neanderthal introgression may impact liver cancer risk.

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.

Integrating Single-Cell Transcriptome and Network Analysis to Characterize the Therapeutic Response of Chronic Myeloid Leukemia

Chronic myeloid leukemia (CML) is a myeloproliferative disease characterized by a unique BCR-ABL fusion gene. Tyrosine kinase inhibitors (TKIs) were developed to target the BCR-ABL oncoprotein, inhibiting its abnormal kinase activity. TKI treatments have significantly improved CML patient outcomes. However, the patients can develop drug resistance and relapse after therapy discontinues largely due to intratumor heterogeneity. It is critical to understand the differences in therapeutic responses among subpopulations of cells. Single-cell RNA sequencing measures the transcriptome of individual cells, allowing us to differentiate and analyze individual cell populations. Here, we integrated a single-cell RNA sequencing profile of CML stem cells and network analysis to decipher the mechanisms of distinct TKI responses. Compared to normal hematopoietic stem cells, a set of genes that were concordantly differentially expressed in various types of stem cells of CML patients was revealed. Further transcription regulatory network analysis found that most of these genes were directly controlled by one or more transcript factors and the genes have more regulators in the cells of the patients who responded to the treatment. The molecular markers including a known drug-resistance gene and novel gene signatures for treatment response were also identified. Moreover, we combined protein-protein interaction network construction with a cancer drug database and uncovered the drugs that target the marker genes directly or indirectly via the protein interactions. The gene signatures and their interacted proteins identified by this work can be used for treatment response prediction and lead to new strategies for drug resistance monitoring and prevention. Our single-cell-based findings offered novel insights into the mechanisms underlying the therapeutic response of CML.

Family still matters: Human social motivation across 42 countries during a global pandemic

The COVID-19 pandemic caused drastic social changes for many people, including separation from friends and coworkers, enforced close contact with family, and reductions in mobility. Here we assess the extent to which people's evolutionarily-relevant basic motivations and goals—fundamental social motives such as Affiliation and Kin Care—might have been affected. To address this question, we gathered data on fundamental social motives in 42 countries (N = 15,915) across two waves, including 19 countries (N = 10,907) for which data were gathered both before and during the pandemic (pre-pandemic wave: 32 countries, N = 8998; 3302 male, 5585 female; M_age = 24.43, SD = 7.91; mid-pandemic wave: 29 countries, N = 6917; 2249 male, 4218 female; M_age = 28.59, SD = 11.31). Samples include data collected online (e.g., Prolific, MTurk), at universities, and via community sampling. We found that Disease Avoidance motivation was substantially higher during the pandemic, and that most of the other fundamental social motives showed small, yet significant, differences across waves. Most sensibly, concern with caring for one's children was higher during the pandemic, and concerns with Mate Seeking and Status were lower. Earlier findings showing the prioritization of family motives over mating motives (and even over Disease Avoidance motives) were replicated during the pandemic. Finally, well-being remained positively associated with family-related motives and negatively associated with mating motives during the pandemic, as in the pre-pandemic samples. Our results provide further evidence for the robust primacy of family-related motivations even during this unique disruption of social life.

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.

Transcriptome innovations in primates revealed by single-molecule long-read sequencing

Transcriptomic diversity greatly contributes to the fundamentals of disease, lineage-specific biology, and environmental adaptation. However, much of the actual isoform repertoire contributing to shaping primate evolution remains unknown. Here, we combined deep long- and short-read sequencing complemented with mass spectrometry proteomics in a panel of lymphoblastoid cell lines (LCLs) from human, three other great apes, and rhesus macaque, producing the largest full-length isoform catalog in primates to date. Around half of the captured isoforms are not annotated in their reference genomes, significantly expanding the gene models in primates. Furthermore, our comparative analyses unveil hundreds of transcriptomic innovations and isoform usage changes related to immune function and immunological disorders. The confluence of these evolutionary innovations with signals of positive selection and their limited impact in the proteome points to changes in alternative splicing in genes involved in immune response as an important target of recent regulatory divergence in primates.

The immunogenetic impact of European colonization in the Americas

The introduction of pathogens originating from Eurasia into the Americas during early European contact has been associated with high mortality rates among Indigenous peoples, likely contributing to their historical and precipitous population decline. However, the biological impacts of imported infectious diseases and resulting epidemics, especially in terms of pathogenic effects on the Indigenous immunity, remain poorly understood and highly contentious to this day. Here, we examine multidisciplinary evidence underpinning colonization-related immune genetic change, providing contextualization from anthropological studies, paleomicrobiological evidence of contrasting host-pathogen coevolutionary histories, and the timings of disease emergence. We further summarize current studies examining genetic signals reflecting post-contact Indigenous population bottlenecks, admixture with European and other populations, and the putative effects of natural selection, with a focus on ancient DNA studies and immunity-related findings. Considering current genetic evidence, together with a population genetics theoretical approach, we show that post-contact Indigenous immune adaptation, possibly influenced by selection exerted by introduced pathogens, is highly complex and likely to be affected by multifactorial causes. Disentangling putative adaptive signals from those of genetic drift thus remains a significant challenge, highlighting the need for the implementation of population genetic approaches that model the short time spans and complex demographic histories under consideration. This review adds to current understandings of post-contact immunity evolution in Indigenous peoples of America, with important implications for bettering our understanding of human adaptation in the face of emerging infectious diseases.

The genetic and evolutionary determinants of COVID-19 susceptibility

Devastating pandemics, such as that due to COVID-19, can provide strong testimony to our knowledge of the genetic and evolutionary determinants of infectious disease susceptibility and severity. One of the most remarkable aspects of such outbreaks is the stunning interindividual variability observed in the course of infection. In recent decades, enormous progress has been made in the field of the human genetics of infectious diseases, and an increasing number of human genetic factors have been reported to explain, to a great extent, the observed variability for a large number of infectious agents. However, our understanding of the cellular, molecular, and immunological mechanisms underlying such disparities between individuals and ethnic groups, remains very limited. Here, we discuss recent findings relating to human genetic predisposition to infectious disease, from an immunological or population genetic perspective, and show how these and other innovative approaches have been applied to deciphering the genetic basis of human susceptibility to COVID-19 and the severity of this disease. From an evolutionary perspective, we show how past demographic and selection events characterizing the history of our species, including admixture with archaic humans, such as Neanderthals, facilitated modern human adaptation to the threats imposed by ancient pathogens. In the context of emerging infectious diseases, these past episodes of genetic adaptation may contribute to some of the observed population differences in the outcome of SARS-CoV-2 infection and the severity of COVID-19 illness.

Warthog Genomes Resolve an Evolutionary Conundrum and Reveal Introgression of Disease Resistance Genes

African wild pigs have a contentious evolutionary and biogeographic history. Until recently, desert warthog (Phacochoerus aethiopicus) and common warthog (P. africanus) were considered a single species. Molecular evidence surprisingly suggested they diverged at least 4.4 million years ago, and possibly outside of Africa. We sequenced the first whole-genomes of four desert warthogs and 35 common warthogs from throughout their range. We show that these two species diverged much later than previously estimated, 400,000–1,700,000 years ago depending on assumptions of gene flow. This brings it into agreement with the paleontological record. We found that the common warthog originated in western Africa and subsequently colonized eastern and southern Africa. During this range expansion, the common warthog interbred with the desert warthog, presumably in eastern Africa, underlining this region’s importance in African biogeography. We found that immune system–related genes may have adaptively introgressed into common warthogs, indicating that resistance to novel diseases was one of the most potent drivers of evolution as common warthogs expanded their range. Hence, we solve some of the key controversies surrounding warthog evolution and reveal a complex evolutionary history involving range expansion, introgression, and adaptation to new diseases.

Ecological and genomic vulnerability to climate change across native populations of Robusta coffee (Coffea canephora)

The assessment of population vulnerability under climate change is crucial for planning conservation as well as for ensuring food security. Coffea canephora is, in its native habitat, an understorey tree that is mainly distributed in the lowland rainforests of tropical Africa. Also known as Robusta, its commercial value constitutes a significant revenue for many human populations in tropical countries. Comparing ecological and genomic vulnerabilities within the species' native range can provide valuable insights about habitat loss and the species' adaptive potential, allowing to identify genotypes that may act as a resource for varietal improvement. By applying species distribution models, we assessed ecological vulnerability as the decrease in climatic suitability under future climatic conditions from 492 occurrences. We then quantified genomic vulnerability (or risk of maladaptation) as the allelic composition change required to keep pace with predicted climate change. Genomic vulnerability was estimated from genomic environmental correlations throughout the native range. Suitable habitat was predicted to diminish to half its size by 2050, with populations near coastlines and around the Congo River being the most vulnerable. Whole-genome sequencing revealed 165 candidate SNPs associated with climatic adaptation in C. canephora, which were located in genes involved in plant response to biotic and abiotic stressors. Genomic vulnerability was higher for populations in West Africa and in the region at the border between DRC and Uganda. Despite an overall low correlation between genomic and ecological vulnerability at broad scale, these two components of vulnerability overlap spatially in ways that may become damaging. Genomic vulnerability was estimated to be 23% higher in populations where habitat will be lost in 2050 compared to regions where habitat will remain suitable. These results highlight how ecological and genomic vulnerabilities are relevant when planning on how to cope with climate change regarding an economically important species.

Advances in Our Understanding of the Interaction of Drugs with T-cells: Implications for the Discovery of Biomarkers in Severe Cutaneous Drug Reactions

Drugs can activate different cells of the immune system and initiate an immune response that can lead to life-threatening diseases collectively known as severe cutaneous adverse reactions (SCARs). Antibiotics, anticonvulsants, and antiretrovirals are involved in the development of SCARs by the activation of αβ naïve T-cells. However, other subsets of lymphocytes known as nonconventional T-cells with a limited T-cell receptor repertoire and innate and adaptative functions also recognize drugs and drug-like molecules, but their role in the pathogenesis of SCARs has only just begun to be explored. Despite 30 years of advances in our understanding of the mechanisms in which drugs interact with T-cells and the pathways for tissue injury seen during T-cell activation, at present, the development of useful clinical biomarkers for SCARs or predictive preclinical in vitro assays that could identify immunogenic moieties during drug discovery is an unmet goal. Therefore, the present review focuses on (i) advances in the understanding of the pathogenesis of SCARs reactions, (ii) a description of the interaction of drugs with conventional and nonconventional T-cells, and (iii) the current state of soluble blood circulating biomarker candidates for SCARs.

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.

Integrative genetic and immune cell analysis of plasma proteins in healthy donors identifies novel associations involving primary immune deficiency genes

BACKGROUND

Blood plasma proteins play an important role in immune defense against pathogens, including cytokine signaling, the complement system, and the acute-phase response. Recent large-scale studies have reported genetic (i.e., protein quantitative trait loci, pQTLs) and non-genetic factors, such as age and sex, as major determinants to inter-individual variability in immune response variation. However, the contribution of blood-cell composition to plasma protein heterogeneity has not been fully characterized and may act as a mediating factor in association studies.

METHODS

Here, we evaluated plasma protein levels from 400 unrelated healthy individuals of western European ancestry, who were stratified by sex and two decades of life (20-29 and 60-69 years), from the Milieu Intérieur cohort. We quantified 229 proteins by Luminex in a clinically certified laboratory and their levels of variation were analyzed together with 5.2 million single-nucleotide polymorphisms. With respect to non-genetic variables, we included 254 lifestyle and biochemical factors, as well as counts of seven circulating immune cell populations measured by hemogram and standardized flow cytometry.

RESULTS

Collectively, we found 152 significant associations involving 49 proteins and 20 non-genetic variables. Consistent with previous studies, age and sex showed a global, pervasive impact on plasma protein heterogeneity, while body mass index and other health status variables were among the non-genetic factors with the highest number of associations. After controlling for these covariates, we identified 100 and 12 pQTLs acting in cis and trans, respectively, collectively associated with 87 plasma proteins and including 19 novel genetic associations. Genetic factors explained the largest fraction of the variability of plasma protein levels, as compared to non-genetic factors. In addition, blood-cell fractions, including leukocytes, lymphocytes, monocytes, neutrophils, eosinophils, basophils, and platelets, had a larger contribution to inter-individual variability than age and sex and appeared as confounders of specific genetic associations. Finally, we identified new genetic associations with plasma protein levels of five monogenic Mendelian disease genes including two primary immunodeficiency genes (Ficolin-3 and FAS).

CONCLUSIONS

Our study identified novel genetic and non-genetic factors associated to plasma protein levels which may inform health status and disease management.

Detection of Neanderthal Adaptively Introgressed Genetic Variants That Modulate Reporter Gene Expression in Human Immune Cells

Although some variation introgressed from Neanderthals has undergone selective sweeps, little is known about its functional significance. We used a Massively Parallel Reporter Assay (MPRA) to assay 5,353 high-frequency introgressed variants for their ability to modulate the gene expression within 170 bp of endogenous sequence. We identified 2,548 variants in active putative cis-regulatory elements (CREs) and 292 expression-modulating variants (emVars). These emVars are predicted to alter the binding motifs of important immune transcription factors, are enriched for associations with neutrophil and white blood cell count, and are associated with the expression of genes that function in innate immune pathways including inflammatory response and antiviral defense. We combined the MPRA data with other data sets to identify strong candidates to be driver variants of positive selection including an emVar that may contribute to protection against severe COVID-19 response. We endogenously deleted two CREs containing expression-modulation variants linked to immune function, rs11624425 and rs80317430, identifying their primary genic targets as ELMSAN1, and PAN2 and STAT2, respectively, three genes differentially expressed during influenza infection. Overall, we present the first database of experimentally identified expression-modulating Neanderthal-introgressed alleles contributing to potential immune response in modern humans.