A genomic perspective on HLA evolution

How HLA diversity is apportioned: influence of selection and relevance to transplantation

In his 1972 paper ‘The apportionment of human diversity’, Lewontin showed that, when averaged over loci, genetic diversity is predominantly attributable to differences among individuals within populations. However, selection can alter the apportionment of diversity of specific genes or genomic regions. We examine genetic diversity at the human leucocyte antigen (HLA) loci, located within the major histocompatibility complex (MHC) region. HLA genes code for proteins that are critical to adaptive immunity and are well-documented targets of balancing selection. The single-nucleotide polymorphisms (SNPs) within HLA genes show strong signatures of balancing selection on large timescales and are broadly shared among populations, displaying low F_ST values. However, when we analyse haplotypes defined by these SNPs (which define ‘HLA alleles’), we find marked differences in frequencies between geographic regions. These differences are not reflected in the F_ST values because of the extreme polymorphism at HLA loci, illustrating challenges in interpreting F_ST. Differences in the frequency of HLA alleles among geographic regions are relevant to bone-marrow transplantation, which requires genetic identity at HLA loci between patient and donor. We discuss the case of Brazil's bone marrow registry, where a deficit of enrolled volunteers with African ancestry reduces the chance of finding donors for individuals with an MHC region of African ancestry.

This article is part of the theme issue ‘Celebrating 50 years since Lewontin's apportionment of human diversity’.

The genomic signatures of natural selection in admixed human populations

Admixture has been a pervasive phenomenon in human history, extensively shaping 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 remain poorly characterized. Here, we use extensive computer simulations to evaluate the power of several neutrality statistics to detect natural selection in the admixed population, assuming multiple admixture scenarios. We show that statistics based on admixture proportions, F_adm and LAD, show high power to detect mutations that are beneficial in the admixed population, whereas other statistics, including iHS and F_ST, falsely detect neutral mutations that have been selected in the source populations only. By combining F_adm and LAD into a single, powerful 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 Africans and in Malagasy, North Africans, and South Asians, respectively. Our approach also uncovers other cases of adaptive admixture, including APOL1 in Fulani nomads and PKN2 in East Indonesians, involved in resistance to infection and metabolism, respectively. Collectively, our study provides evidence that adaptive admixture has occurred in human populations whose genetic history is characterized by periods of isolation and spatial expansions resulting in increased gene flow.

HLA3D: an integrated structure-based computational toolkit for immunotherapy

Motivation

The human major histocompatibility complex (MHC), also known as human leukocyte antigen (HLA), plays an important role in the adaptive immune system by presenting non-self-peptides to T cell receptors. The MHC region has been shown to be associated with a variety of diseases, including autoimmune diseases, organ transplantation and tumours. However, structural analytic tools of HLA are still sparse compared to the number of identified HLA alleles, which hinders the disclosure of its pathogenic mechanism.

Result

To provide an integrative analysis of HLA, we first collected 1296 amino acid sequences, 256 protein data bank structures, 120 000 frequency data of HLA alleles in different populations, 73 000 publications and 39 000 disease-associated single nucleotide polymorphism sites, as well as 212 modelled HLA heterodimer structures. Then, we put forward two new strategies for building up a toolkit for transplantation and tumour immunotherapy, designing risk alignment pipeline and antigenic peptide prediction pipeline by integrating different resources and bioinformatic tools. By integrating 100 000 calculated HLA conformation difference and online tools, risk alignment pipeline provides users with the functions of structural alignment, sequence alignment, residue visualization and risk report generation of mismatched HLA molecules. For tumour antigen prediction, we first predicted 370 000 immunogenic peptides based on the affinity between peptides and MHC to generate the neoantigen catalogue for 11 common tumours. We then designed an antigenic peptide prediction pipeline to provide the functions of mutation prediction, peptide prediction, immunogenicity assessment and docking simulation. We also present a case study of hepatitis B virus mutations associated with liver cancer that demonstrates the high legitimacy of our antigenic peptide prediction process. HLA3D, including different HLA analytic tools and the prediction pipelines, is available at http://www.hla3d.cn/.

High Resolution HLA ∼A, ∼B, ∼C, ∼DRB1, ∼DQA1, and ∼DQB1 Diversity in South African Populations

Background: Lack of HLA data in southern African populations hampers disease association studies and our understanding of genetic diversity in these populations. We aimed to determine HLA diversity in South African populations using high resolution HLA ∼A, ∼B, ∼C, ∼DRB1, ∼DQA1 and ∼DQB1 data, from 3005 previously typed individuals.

Methods: We determined allele and haplotype frequencies, deviations from Hardy-Weinberg equilibrium (HWE), linkage disequilibrium (LD) and neutrality test. South African HLA class I data was additionally compared to other global populations using non-metrical multidimensional scaling (NMDS), genetic distances and principal component analysis (PCA).

Results: All loci strongly (p < 0.0001) deviated from HWE, coupled with excessive heterozygosity in most loci. Two of the three most frequent alleles, HLA ∼DQA1*05:02 (0.2584) and HLA ∼C*17:01 (0.1488) were previously reported in South African populations at lower frequencies. NMDS showed genetic distinctness of South African populations. Phylogenetic analysis and PCA clustered our current dataset with previous South African studies. Additionally, South Africans seem to be related to other sub-Saharan populations using HLA class I allele frequencies.

Discussion and Conclusion: Despite the retrospective nature of the study, data missingness, the imbalance of sample sizes for each locus and haplotype pairs, and induced methodological difficulties, this study provides a unique and large HLA dataset of South Africans, which might be a useful resource to support anthropological studies, disease association studies, population based vaccine development and donor recruitment programs. We additionally provide simulated high resolution HLA class I data to augment the mixed resolution typing results generated from this study.

Evolution of host-microbe cell adherence by receptor domain shuffling

Stable adherence to epithelial surfaces is required for colonization by diverse host-associated microbes. Successful attachment of pathogenic microbes to host cells via adhesin molecules is also the first step in many devastating infections. Despite the primacy of epithelial adherence in establishing host-microbe associations, the evolutionary processes that shape this crucial interface remain enigmatic. Carcinoembryonic antigen-related cell adhesion molecules (CEACAMs) encompass a multifunctional family of vertebrate cell surface proteins which are recurrent targets of bacterial adhesins at epithelial barriers. Here, we show that multiple members of the primate CEACAM family exhibit evidence of repeated natural selection at protein surfaces targeted by bacteria, consistent with pathogen-driven evolution. Divergence of CEACAM proteins between even closely related great apes is sufficient to control molecular interactions with a range of bacterial adhesins. Phylogenetic analyses further reveal that repeated gene conversion of CEACAM extracellular domains during primate divergence plays a key role in limiting bacterial adhesin host tropism. Moreover, we demonstrate that gene conversion has continued to shape CEACAM diversity within human populations, with abundant human CEACAM1 variants mediating evasion of adhesins from pathogenic Neisseria. Together this work reveals a mechanism by which gene conversion shapes first contact between microbes and animal hosts.

Trillions of bacteria live in and on the human body. Most of them are harmless but some can cause serious infections. To grow in or on the body, bacteria often attach to proteins on the surface of cells that make up the lining of tissues like the gut or the throat. In some cases, bacteria use these proteins to invade the cells causing an infection. Genetic mutations in the genes encoding these proteins that protect against infection are more likely to be passed on to future generations. This may lead to rapid spread of these beneficial genes in a population.

A family of proteins called CEACAMs are frequent targets of infection-causing bacteria. These proteins have been shown to play a role in cancer progression. But they also play many helpful roles in the body, including helping transmit messages between cells, aiding cell growth, and helping the immune system recognize pathogens. Scientists are not sure if these multi-tasking CEACAM proteins can evolve to evade bacteria without affecting their other roles.

Baker et al. show that CEACAM proteins targeted by bacteria have undergone rapid evolution in primates. In the experiments, human genes encoding CEACAMs were compared with equivalent genes from 19 different primates. Baker et al. found the changes in human and primate CEACAMs often occur through a process called gene conversion. Gene conversion occurs when DNA sections are copied and pasted from one gene to another. Using laboratory experiments, they showed that some of these changes enabled CEACAM proteins to prevent certain harmful bacteria from binding.

The experiments suggest that some versions of CEACAM genes may protect humans or other primates against bacterial infections. Studies in natural populations are needed to test if this is the case. Learning more about how CEACAM proteins evolve and what they do may help scientists better understand the role they play in cancer and help improve cancer care. Studying CEACAM evolution may also help scientists understand how bacteria and other pathogens drive protein evolution in the body.

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

Human immune diversity: from evolution to modernity

The extreme diversity of the human immune system, forged and maintained throughout evolutionary history, provides a potent defense against opportunistic pathogens. At the same time, this immune variation is the substrate upon which a plethora of immune-associated diseases develop. Genetic analysis suggests that thousands of individually weak loci together drive up to half of the observed immune variation. Intense selection maintains this genetic diversity, even selecting for the introgressed Neanderthal or Denisovan alleles that have reintroduced variation lost during the out-of-Africa migration. Variations in age, sex, diet, environmental exposure, and microbiome each potentially explain the residual variation, with proof-of-concept studies demonstrating both plausible mechanisms and correlative associations. The confounding interaction of many of these variables currently makes it difficult to assign definitive contributions. Here, we review the current state of play in the field, identify the key unknowns in the causality of immune variation, and identify the multidisciplinary pathways toward an improved understanding.

HLA-G genetic diversity and evolutive aspects in worldwide populations

HLA-G is a promiscuous immune checkpoint molecule. The HLA-G gene presents substantial nucleotide variability in its regulatory regions. However, it encodes a limited number of proteins compared to classical HLA class I genes. We characterized the HLA-G genetic variability in 4640 individuals from 88 different population samples across the globe by using a state-of-the-art method to characterize polymorphisms and haplotypes from high-coverage next-generation sequencing data. We also provide insights regarding the HLA-G genetic diversity and a resource for future studies evaluating HLA-G polymorphisms in different populations and association studies. Despite the great haplotype variability, we demonstrated that: (1) most of the HLA-G polymorphisms are in introns and regulatory sequences, and these are the sites with evidence of balancing selection, (2) linkage disequilibrium is high throughout the gene, extending up to HLA-A, (3) there are few proteins frequently observed in worldwide populations, with lack of variation in residues associated with major HLA-G biological properties (dimer formation, interaction with leukocyte receptors). These observations corroborate the role of HLA-G as an immune checkpoint molecule rather than as an antigen-presenting molecule. Understanding HLA-G variability across populations is relevant for disease association and functional studies.

Epstein-Barr Virus and the Origin of Myalgic Encephalomyelitis or Chronic Fatigue Syndrome

Myalgic encephalomyelitis or chronic fatigue syndrome (ME/CFS) affects approximately 1% of the general population. It is a chronic, disabling, multi-system disease for which there is no effective treatment. This is probably related to the limited knowledge about its origin. Here, we summarized the current knowledge about the pathogenesis of ME/CFS and revisit the immunopathobiology of Epstein-Barr virus (EBV) infection. Given the similarities between EBV-associated autoimmune diseases and cancer in terms of poor T cell surveillance of cells with EBV latency, expanded EBV-infected cells in peripheral blood and increased antibodies against EBV, we hypothesize that there could be a common etiology generated by cells with EBV latency that escape immune surveillance. Albeit inconclusive, multiple studies in patients with ME/CFS have suggested an altered cellular immunity and augmented Th2 response that could result from mechanisms of evasion to some pathogens such as EBV, which has been identified as a risk factor in a subset of ME/CFS patients. Namely, cells with latency may evade the immune system in individuals with genetic predisposition to develop ME/CFS and in consequence, there could be poor CD4 T cell immunity to mitogens and other specific antigens, as it has been described in some individuals. Ultimately, we hypothesize that within ME/CFS there is a subgroup of patients with DRB1 and DQB1 alleles that could confer greater susceptibility to EBV, where immune evasion mechanisms generated by cells with latency induce immunodeficiency. Accordingly, we propose new endeavors to investigate if anti-EBV therapies could be effective in selected ME/CFS patients.

Frequency of HLA Alleles in a Group of Severe COVID-19 Iranian Patients

Background:

Human Leukocyte Antigen (HLA) system composed of a group of related proteins with important functions in the immune system. Several studies have reported that there is a significant association between specific HLA alleles and the susceptibility to different infectious diseases. This study aimed to detect the specific HLA alleles that cause higher susceptibility to COVID-19, we analyzed the HLA allele frequency distribution in Iranian patients with a severe form of COVID-19.

Methods:

Overall, 48 severe cases of COVID-19 that were hospitalized and required intensive care unit (ICU) admission between Oct and Dec 2020 were included in this study. Genomic DNA was extracted from the peripheral blood samples and HLA typing (Locus A, B, and DR) was performed for the patients.

Results:

After analyzing and comparing the results with a reference group of 500 Iranian individuals, a significant association was found for HLA-B*38, HLA-A*68, HLA-A*24, and HLA-DRB1*01.

Conclusion:

These results may be valuable for studying the potential association of specific HLA alleles with susceptibility to COVID-19 and mortality due to the disease.

A sex-specific evolutionary interaction between ADCY9 and CETP

Pharmacogenomic studies have revealed associations between rs1967309 in the adenylyl cyclase type 9 (ADCY9) gene and clinical responses to the cholesteryl ester transfer protein (CETP) modulator dalcetrapib, however, the mechanism behind this interaction is still unknown. Here, we characterized selective signals at the locus associated with the pharmacogenomic response in human populations and we show that rs1967309 region exhibits signatures of positive selection in several human populations. Furthermore, we identified a variant in CETP, rs158477, which is in long-range linkage disequilibrium with rs1967309 in the Peruvian population. The signal is mainly seen in males, a sex-specific result that is replicated in the LIMAA cohort of over 3400 Peruvians. Analyses of RNA-seq data further suggest an epistatic interaction on CETP expression levels between the two SNPs in multiple tissues, which also differs between males and females. We also detected interaction effects of the two SNPs with sex on cardiovascular phenotypes in the UK Biobank, in line with the sex-specific genotype associations found in Peruvians at these loci. We propose that ADCY9 and CETP coevolved during recent human evolution due to sex-specific selection, which points toward a biological link between dalcetrapib's pharmacogene ADCY9 and its therapeutic target CETP.

Allelic and haplotypic HLA diversity in indigenous Malaysian populations explored using Next Generation Sequencing

The heterogenous population of Malaysia includes more than 50 indigenous groups, and characterizing their HLA diversity would not only provide insights to their ancestry, but also on the effects of natural selection on their genome. We utilized hybridization-based sequence capture and short-read sequencing on the HLA region of 172 individuals representing seven indigenous groups in Malaysia (Jehai, Kintaq, Temiar, Mah Meri, Seletar, Temuan, Bidayuh). Allele and haplotype frequencies of HLA-A, -B, -C, -DRB1, -DQA1, -DQB1, -DPA1, and -DPB1 revealed several ancestry-informative markers. Using SNP-based heterozygosity and pairwise Fst, we observed signals of natural selection, particularly in HLA-A, -C and -DPB1 genes. Consequently, we showed the impact of natural selection on phylogenetic inference using HLA and non-HLA SNPs. We demonstrate the utility of Next Generation Sequencing for generating unambiguous, high-throughput, high-resolution HLA data that adds to our knowledge of HLA diversity and natural selection in indigenous minority groups.

A high-resolution HLA reference panel capturing global population diversity enables multi-ancestry fine-mapping in HIV host response

Fine-mapping to plausible causal variation may be more effective in multi-ancestry cohorts, particularly in the MHC, which has population-specific structure. To enable such studies, we constructed a large (n = 21,546) HLA reference panel spanning five global populations based on whole-genome sequences. Despite population-specific long-range haplotypes, we demonstrated accurate imputation at G-group resolution (94.2%, 93.7%, 97.8% and 93.7% in admixed African (AA), East Asian (EAS), European (EUR) and Latino (LAT) populations). Applying HLA imputation to genome-wide association study data for HIV-1 viral load in three populations (EUR, AA and LAT), we obviated effects of previously reported associations from population-specific HIV studies and discovered a novel association at position 156 in HLA-B. We pinpointed the MHC association to three amino acid positions (97, 67 and 156) marking three consecutive pockets (C, B and D) within the HLA-B peptide-binding groove, explaining 12.9% of trait variance.

Increased risk of severe clinical course of COVID-19 in carriers of HLA-C*04:01

BACKGROUND

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic, there has been increasing urgency to identify pathophysiological characteristics leading to severe clinical course in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Human leukocyte antigen alleles (HLA) have been suggested as potential genetic host factors that affect individual immune response to SARS-CoV-2. We sought to evaluate this hypothesis by conducting a multicenter study using HLA sequencing.

METHODS

We analyzed the association between COVID-19 severity and HLAs in 435 individuals from Germany (n = 135), Spain (n = 133), Switzerland (n = 20) and the United States (n = 147), who had been enrolled from March 2020 to August 2020. This study included patients older than 18 years, diagnosed with COVID-19 and representing the full spectrum of the disease. Finally, we tested our results by meta-analysing data from prior genome-wide association studies (GWAS).

FINDINGS

We describe a potential association of HLA-C*04:01 with severe clinical course of COVID-19. Carriers of HLA-C*04:01 had twice the risk of intubation when infected with SARS-CoV-2 (risk ratio 1.5 [95% CI 1.1-2.1], odds ratio 3.5 [95% CI 1.9-6.6], adjusted p-value = 0.0074). These findings are based on data from four countries and corroborated by independent results from GWAS. Our findings are biologically plausible, as HLA-C*04:01 has fewer predicted bindings sites for relevant SARS-CoV-2 peptides compared to other HLA alleles.

INTERPRETATION

HLA-C*04:01 carrier state is associated with severe clinical course in SARS-CoV-2. Our findings suggest that HLA class I alleles have a relevant role in immune defense against SARS-CoV-2.

FUNDING

Funded by Roche Sequencing Solutions, Inc.

MHC Variants Associated With Symptomatic Versus Asymptomatic SARS-CoV-2 Infection in Highly Exposed Individuals

Despite the high number of individuals infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) who develop coronavirus disease 2019 (COVID-19) symptoms worldwide, many exposed individuals remain asymptomatic and/or uninfected and seronegative. This could be explained by a combination of environmental (exposure), immunological (previous infection), epigenetic, and genetic factors. Aiming to identify genetic factors involved in immune response in symptomatic COVID-19 as compared to asymptomatic exposed individuals, we analyzed 83 Brazilian couples where one individual was infected and symptomatic while the partner remained asymptomatic and serum-negative for at least 6 months despite sharing the same bedroom during the infection. We refer to these as "discordant couples". We performed whole-exome sequencing followed by a state-of-the-art method to call genotypes and haplotypes across the highly polymorphic major histocompatibility complex (MHC) region. The discordant partners had comparable ages and genetic ancestry, but women were overrepresented (65%) in the asymptomatic group. In the antigen-presentation pathway, we observed an association between HLA-DRB1 alleles encoding Lys at residue 71 (mostly DRB1*03:01 and DRB1*04:01) and DOB*01:02 with symptomatic infections and HLA-A alleles encoding 144Q/151R with asymptomatic seronegative women. Among the genes related to immune modulation, we detected variants in MICA and MICB associated with symptomatic infections. These variants are related to higher expression of soluble MICA and low expression of MICB. Thus, quantitative differences in these molecules that modulate natural killer (NK) activity could contribute to susceptibility to COVID-19 by downregulating NK cell cytotoxic activity in infected individuals but not in the asymptomatic partners.

HLA class II peptide-binding-region analysis reveals funneling of polymorphism in action

BACKGROUND

HLA-class II proteins hold important roles in key physiological processes. The purpose of this study was to compile all class II alleles reported in human population and investigate patterns in pocket variants and their combinations, focusing on the peptide-binding region (PBR).

METHODS

For this purpose, all protein sequences of DPA1, DQA1, DPB1, DQB1 and DRB1 were selected and filtered, in order to have full PBR sequences. Proportional representation was used for pocket variants while population data were also used.

RESULTS

All pocket variants and PBR sequences were retrieved and analyzed based on the preference of amino acids and their properties in all pocket positions. The observed number of pocket variants combinations was much lower than the possible inferred, suggesting that PBR formation is under strict funneling. Also, although class II proteins are very polymorphic, in the majority of the reported alleles in all populations, a significantly less polymorphic pocket core was found.

CONCLUSIONS

Pocket variability of five HLA class II proteins was studied revealing favorable properties of each protein. The actual PBR sequences of HLA class II proteins appear to be governed by restrictions that lead to the establishment of only a fraction of the possible combinations and the polymorphism recorded is the result of intense funneling based on function.

How natural selection shapes genetic differentiation in the MHC region: A case study with Native Americans

The Human Leukocyte Antigen (HLA) loci are extremely well documented targets of balancing selection, yet few studies have explored how selection affects population differentiation at these loci. In the present study we investigate genetic differentiation at HLA genes by comparing differentiation at microsatellites distributed genomewide to those in the MHC region. Our study uses a sample of 494 individuals from 30 human populations, 28 of which are Native Americans, all of whom were typed for genomewide and MHC region microsatellites. We find greater differentiation in the MHC than in the remainder of the genome (FST-MHC = 0.130 and FST-Genomic = 0.087), and use a permutation approach to show that this difference is statistically significant, and not accounted for by confounding factors. This finding lies in the opposite direction to the expectation that balancing selection reduces population differentiation. We interpret our findings as evidence that selection favors different sets of alleles in distinct localities, leading to increased differentiation. Thus, balancing selection at HLA genes simultaneously increases intra-population polymorphism and inter-population differentiation in Native Americans.

High-resolution HLA allele and haplotype frequencies in several unrelated populations determined by next generation sequencing: 17th International HLA and Immunogenetics Workshop joint report

The primary goal of the unrelated population HLA diversity (UPHD) component of the 17th International HLA and Immunogenetics Workshop was to characterize HLA alleles at maximum allelic-resolution in worldwide populations and re-evaluate patterns of HLA diversity across populations. The UPHD project included HLA genotype and sequence data, generated by various next-generation sequencing methods, from 4,240 individuals collated from 12 different countries. Population data included well-defined large datasets from the USA and smaller samples from Europe, Australia, and Western Asia. Allele and haplotype frequencies varied across populations from distant geographical regions. HLA genetic diversity estimated at 2- and 4-field allelic resolution revealed that diversity at the majority of loci, particularly for European-descent populations, was lower at the 2-field resolution. Several common alleles with identical protein sequences differing only by intronic substitutions were found in distinct haplotypes, revealing a more detailed characterization of linkage between variants within the HLA region. The examination of coding and non-coding nucleotide variation revealed many examples in which almost complete biunivocal relations between common alleles at different loci were observed resulting in higher linkage disequilibrium. Our reference data of HLA profiles characterized at maximum resolution from many populations is useful for anthropological studies, unrelated donor searches, transplantation, and disease association studies.

Adaptive Admixture of HLA Class I Allotypes Enhanced Genetically Determined Strength of Natural Killer Cells in East Asians

Human natural killer (NK) cells are essential for controlling infection, cancer, and fetal development. NK cell functions are modulated by interactions between polymorphic inhibitory killer cell immunoglobulin-like receptors (KIR) and polymorphic HLA-A, -B, and -C ligands expressed on tissue cells. All HLA-C alleles encode a KIR ligand and contribute to reproduction and immunity. In contrast, only some HLA-A and -B alleles encode KIR ligands and they focus on immunity. By high-resolution analysis of KIR and HLA-A, -B, and -C genes, we show that the Chinese Southern Han (CHS) are significantly enriched for interactions between inhibitory KIR and HLA-A and -B. This enrichment has had substantial input through population admixture with neighboring populations, who contributed HLA class I haplotypes expressing the KIR ligands B*46:01 and B*58:01, which subsequently rose to high frequency by natural selection. Consequently, over 80% of Southern Han HLA haplotypes encode more than one KIR ligand. Complementing the high number of KIR ligands, the CHS KIR locus combines a high frequency of genes expressing potent inhibitory KIR, with a low frequency of those expressing activating KIR. The Southern Han centromeric KIR region encodes strong, conserved, inhibitory HLA-C-specific receptors, and the telomeric region provides a high number and diversity of inhibitory HLA-A and -B-specific receptors. In all these characteristics, the CHS represent other East Asians, whose NK cell repertoires are thus enhanced in quantity, diversity, and effector strength, likely augmenting resistance to endemic viral infections.

Influence of Genetic Polymorphisms on Response to Biologics in Moderate-to-Severe Psoriasis

Psoriasis is a chronic inflammatory skin pathology of autoimmune origin and unknown etiology. There are various therapies for treating it, including a wide range of biopharmaceuticals indicated in moderate-to-severe psoriasis. Depending on their therapeutic target, they are classified as tumor necrosis factor inhibitors (anti-TNF) or cytokine inhibitors (interleukin-12, 23, and 17 antagonists). Although they have proved effective and safe, in clinical practice, many patients show a short- and long-term suboptimal response and even varying degrees of toxicity. This variability in response may be influenced by genetic factors, such as polymorphisms in the genes involved in the pathological environment, metabolism or mechanism of action of the drug that could affect the effectiveness and toxicity of biological therapies. This review assesses pharmacogenetic studies of the impact of genetic factors on response to biopharmaceuticals and toxicity in patients diagnosed with moderate-to-severe psoriasis. The results suggest that polymorphisms detected in the HLA genes, in genes that encode cytokines (TNF, IL genes, TNFAIP3), transporters (PDE3A-SLCO1C1, SLC12A8), receptors (TNFRSF1B, CD84, FCGR2A and FCGR3A, IL17RA, IL23R, TLR genes, PGLYRP4) and associated proteins (TNFAIP3, LY96, TIRAP, FBXL19), as well as other genes implicated in the pathogenesis of psoriasis (CDKAL1, CARD14, PTTG1, MAP3K1, ZNF816A, GBP6, CTNNA2, HTR2A, CTLA4, TAP1) can be used in the future as predictive markers of treatment response and/or toxicity with biological therapies in patients diagnosed with moderate-to-severe psoriasis, tailoring treatment to the individual patient.

Prioritizing non-coding regions based on human genomic constraint and sequence context with deep learning

Elucidating functionality in non-coding regions is a key challenge in human genomics. It has been shown that intolerance to variation of coding and proximal non-coding sequence is a strong predictor of human disease relevance. Here, we integrate intolerance to variation, functional genomic annotations and primary genomic sequence to build JARVIS: a comprehensive deep learning model to prioritize non-coding regions, outperforming other human lineage-specific scores. Despite being agnostic to evolutionary conservation, JARVIS performs comparably or outperforms conservation-based scores in classifying pathogenic single-nucleotide and structural variants. In constructing JARVIS, we introduce the genome-wide residual variation intolerance score (gwRVIS), applying a sliding-window approach to whole genome sequencing data from 62,784 individuals. gwRVIS distinguishes Mendelian disease genes from more tolerant CCDS regions and highlights ultra-conserved non-coding elements as the most intolerant regions in the human genome. Both JARVIS and gwRVIS capture previously inaccessible human-lineage constraint information and will enhance our understanding of the non-coding genome.

Intolerance to variation is a strong indicator of disease relevance for coding regions of the human genome. Here, the authors present JARVIS, a deep learning method integrating intolerance to variation in non-coding regions and sequence-specific annotations to infer non-coding variant pathogenicity.

Diversity of KIR genes and their HLA-C ligands in Ugandan populations with historically varied malaria transmission intensity

BACKGROUND

Malaria is one of the most serious infectious diseases in the world. The malaria burden is greatly affected by human immunity, and immune responses vary between populations. Genetic diversity in KIR and HLA-C genes, which are important in immunity to infectious diseases, is likely to play a role in this heterogeneity. Several studies have shown that KIR and HLA-C genes influence the immune response to viral infections, but few studies have examined the role of KIR and HLA-C in malaria infection, and these have used low-resolution genotyping. The aim of this study was to determine whether genetic variation in KIR and their HLA-C ligands differ in Ugandan populations with historically varied malaria transmission intensity using more comprehensive genotyping approaches.

METHODS

High throughput multiplex quantitative real-time PCR method was used to genotype KIR genetic variants and copy number variation and a high-throughput real-time PCR method was developed to genotype HLA-C1 and C2 allotypes for 1344 participants, aged 6 months to 10 years, enrolled from Ugandan populations with historically high (Tororo District), medium (Jinja District) and low (Kanungu District) malaria transmission intensity.

RESULTS

The prevalence of KIR3DS1, KIR2DL5, KIR2DS5, and KIR2DS1 genes was significantly lower in populations from Kanungu compared to Tororo (7.6 vs 13.2%: p = 0.006, 57.2 vs 66.4%: p = 0.005, 33.2 vs 46.6%: p < 0.001, and 19.7 vs 26.7%: p = 0.014, respectively) or Jinja (7.6 vs 18.1%: p < 0.001, 57.2 vs 63.8%: p = 0.048, 33.2 vs 43.5%: p = 0.002, and 19.7 vs 30.4%: p < 0.001, respectively). The prevalence of homozygous HLA-C2 was significantly higher in populations from Kanungu (31.6%) compared to Jinja (21.4%), p = 0.043, with no significant difference between Kanungu and Tororo (26.7%), p = 0.296.

CONCLUSIONS

The KIR3DS1, KIR2DL5, KIR2DS5 and KIR2DS1 genes may partly explain differences in transmission intensity of malaria since these genes have been positively selected for in places with historically high malaria transmission intensity. The high-throughput, multiplex, real-time HLA-C genotyping PCR method developed will be useful in disease-association studies involving large cohorts.

HLApers: HLA Typing and Quantification of Expression with Personalized Index

The plethora of RNA-seq data which have been generated in the recent years constitutes an attractive resource to investigate HLA variation and its relationship with normal and disease phenotypes, such as cancer. However, next generation sequencing (NGS) brings new challenges to HLA analysis because of the mapping bias introduced by aligning short reads originated from polymorphic genes to a single reference genome. Here we describe HLApers, a pipeline which adapts widely used tools for analysis of standard RNA-seq data to infer HLA genotypes and estimate expression. By generating reliable expression estimates for each HLA allele that an individual carries, HLApers allows a better understanding of the relationship between HLA alleles and phenotypes manifested by an individual.

Replication of HLA class II locus association with susceptibility to podoconiosis in three Ethiopian ethnic groups

Podoconiosis, a debilitating lymphoedema of the leg, results from barefoot exposure to volcanic clay soil in genetically susceptible individuals. A previous genome-wide association study (GWAS) conducted in the Wolaita ethnic group from Ethiopia showed association between single nucleotide polymorphisms (SNPs) in the HLA class II region and podoconiosis. We aimed to conduct a second GWAS in a new sample (N = 1892) collected from the Wolaita and two other Ethiopian populations, the Amhara and the Oromo, also affected by podoconiosis. Fourteen SNPs in the HLA class II region showed significant genome-wide association (P < 5.0 × 10⁻⁸) with podoconiosis. The lead SNP was rs9270911 (P = 5.51 × 10⁻¹⁰; OR 1.53; 95% CI 1.34–1.74), located near HLA-DRB1. Inclusion of data from the first GWAS (combined N = 2289) identified 47 SNPs in the class II HLA region that were significantly associated with podoconiosis (lead SNP also rs9270911 (P = 2.25 × 10⁻¹²). No new loci outside of the HLA class II region were identified in this more highly-powered second GWAS. Our findings confirm the HLA class II association with podoconiosis suggesting HLA-mediated abnormal induction and regulation of immune responses may have a direct role in its pathogenesis.

Shared Signature of Recent Positive Selection on the TSBP1-BTNL2-HLA-DRA Genes in Five Native Populations from North Borneo

North Borneo (NB) is home to more than 40 native populations. These natives are believed to have undergone local adaptation in response to environmental challenges such as the mosquito-abundant tropical rainforest. We attempted to trace the footprints of natural selection from the genomic data of NB native populations using a panel of ∼2.2 million genome-wide single nucleotide polymorphisms. As a result, an ∼13-kb haplotype in the Major Histocompatibility Complex Class II region encompassing candidate genes TSBP1–BTNL2–HLA-DRA was identified to be undergoing natural selection. This putative signature of positive selection is shared among the five NB populations and is estimated to have arisen ∼5.5 thousand years (∼220 generations) ago, which coincides with the period of Austronesian expansion. Owing to the long history of endemic malaria in NB, the putative signature of positive selection is postulated to be driven by Plasmodium parasite infection. The findings of this study imply that despite high levels of genetic differentiation, the NB populations might have experienced similar local genetic adaptation resulting from stresses of the shared environment.

Infections of the lung: a predictive, preventive and personalized perspective through the lens of evolution, the emergence of SARS-CoV-2 and its pathogenesis

The long evolutionary battle between humans and pathogens has played an important role in shaping the current network of host-pathogen interactions. Each organ brings new challenges from the perspective of a pathogen to establish a suitable niche for survival while subverting the protective mechanisms of the host. Lungs, the organ for oxygen exchange, have been an easy target for pathogens due to its accessibility. The organ has evolved diverse capabilities to provide the flexibility required for an organism's health and at the same time maintain protective functionality to prevent and resolve assault by pathogens. The pathogenic invasions are strongly challenged by healthy lung architecture which includes the presence and activity of the epithelium, mucous, antimicrobial proteins, surfactants, and immune cells. Competitively, the pathogens in the form of viruses, bacteria, and fungi have evolved an arsenal of strategies that can over-ride the host's protective mechanisms. While bacteria such as Mycobacterium tuberculosis (M. tuberculosis) can survive in dormant form for years before getting active in humans, novel pathogens can wreak havoc as they pose a high risk of morbidity and mortality in a very short duration of time. Recently, a coronavirus strain SARS-CoV-2 has caused a pandemic which provides us an opportunity to look at the host manipulative strategies used by respiratory pathogens. Their ability to hide, modify, evade, and exploit cell's processes are key to their survival. While pathogens like M. tuberculosis have been infecting humans for thousands of years, SARS-CoV-2 has been the cause of the recent pandemic. Molecular understanding of the strategies used by these pathogens could greatly serve in design of predictive, preventive, personalized medicine (PPPM). In this article, we have emphasized on the clinically relevant evasive strategies of the pathogens in the lungs with emphasis on M. tuberculosis and SARS-CoV-2. The molecular basis of these evasive strategies illuminated through advances in genomics, cell, and structural biology can assist in the mapping of vulnerable molecular networks which can be exploited translationally. These evolutionary approaches can further assist in generating screening and therapeutic options for susceptible populations and could be a promising approach for the prediction, prevention of disease, and the development of personalized medicines. Further, tailoring the clinical data of COVID-19 patients with their physiological responses in light of known host-respiratory pathogen interactions can provide opportunities to improve patient profiling and stratification according to identified therapeutic targets.

Demographic history and selection at HLA loci in Native Americans

The American continent was the last to be occupied by modern humans, and native populations bear the marks of recent expansions, bottlenecks, natural selection, and population substructure. Here we investigate how this demographic history has shaped genetic variation at the strongly selected HLA loci. In order to disentangle the relative contributions of selection and demography process, we assembled a dataset with genome-wide microsatellites and HLA-A, -B, -C, and -DRB1 typing data for a set of 424 Native American individuals. We find that demographic history explains a sizeable fraction of HLA variation, both within and among populations. A striking feature of HLA variation in the Americas is the existence of alleles which are present in the continent but either absent or very rare elsewhere in the world. We show that this feature is consistent with demographic history (i.e., the combination of changes in population size associated with bottlenecks and subsequent population expansions). However, signatures of selection at HLA loci are still visible, with significant evidence selection at deeper timescales for most loci and populations, as well as population differentiation at HLA loci exceeding that seen at neutral markers.

Flexible Mixture Model Approaches That Accommodate Footprint Size Variability for Robust Detection of Balancing Selection

Long-term balancing selection typically leaves narrow footprints of increased genetic diversity, and therefore most detection approaches only achieve optimal performances when sufficiently small genomic regions (i.e., windows) are examined. Such methods are sensitive to window sizes and suffer substantial losses in power when windows are large. Here, we employ mixture models to construct a set of five composite likelihood ratio test statistics, which we collectively term B statistics. These statistics are agnostic to window sizes and can operate on diverse forms of input data. Through simulations, we show that they exhibit comparable power to the best-performing current methods, and retain substantially high power regardless of window sizes. They also display considerable robustness to high mutation rates and uneven recombination landscapes, as well as an array of other common confounding scenarios. Moreover, we applied a specific version of the B statistics, termed B2, to a human population-genomic data set and recovered many top candidates from prior studies, including the then-uncharacterized STPG2 and CCDC169-SOHLH2, both of which are related to gamete functions. We further applied B2 on a bonobo population-genomic data set. In addition to the MHC-DQ genes, we uncovered several novel candidate genes, such as KLRD1, involved in viral defense, and SCN9A, associated with pain perception. Finally, we show that our methods can be extended to account for multiallelic balancing selection and integrated the set of statistics into open-source software named BalLeRMix for future applications by the scientific community.

Gene expression variability in human and chimpanzee populations share common determinants

Inter-individual variation in gene expression has been shown to be heritable and is often associated with differences in disease susceptibility between individuals. Many studies focused on mapping associations between genetic and gene regulatory variation, yet much less attention has been paid to the evolutionary processes that shape the observed differences in gene regulation between individuals in humans or any other primate. To begin addressing this gap, we performed a comparative analysis of gene expression variability and expression quantitative trait loci (eQTLs) in humans and chimpanzees, using gene expression data from primary heart samples. We found that expression variability in both species is often determined by non-genetic sources, such as cell-type heterogeneity. However, we also provide evidence that inter-individual variation in gene regulation can be genetically controlled, and that the degree of such variability is generally conserved in humans and chimpanzees. In particular, we found a significant overlap of orthologous genes associated with eQTLs in both species. We conclude that gene expression variability in humans and chimpanzees often evolves under similar evolutionary pressures.

Genetic diversity, evolution and selection in the major histocompatibility complex DRB and DQB loci in the family Equidae

Background

The mammalian Major Histocompatibility Complex (MHC) is a genetic region containing highly polymorphic genes with immunological functions. MHC class I and class II genes encode antigen-presenting molecules expressed on the cell surface. The MHC class II sub-region contains genes expressed in antigen presenting cells. The antigen binding site is encoded by the second exon of genes encoding antigen presenting molecules. The exon 2 sequences of these MHC genes have evolved under the selective pressure of pathogens. Interspecific differences can be observed in the class II sub-region. The family Equidae includes a variety of domesticated, and free-ranging species inhabiting a range of habitats exposed to different pathogens and represents a model for studying this important part of the immunogenome. While equine MHC class II DRA and DQA loci have received attention, the genetic diversity and effects of selection on DRB and DQB loci have been largely overlooked. This study aimed to provide the first in-depth analysis of the MHC class II DRB and DQB loci in the Equidae family.

Results

Three DRB and two DQB genes were identified in the genomes of all equids. The genes DRB2, DRB3 and DQB3 showed high sequence conservation, while polymorphisms were more frequent at DRB1 and DQB1 across all species analyzed. DQB2 was not found in the genome of the Asiatic asses Equus hemionus kulan and E. h. onager. The bioinformatic analysis of non-zero-coverage-bases of DRB and DQB genes in 14 equine individual genomes revealed differences among individual genes. Evidence for recombination was found for DRB1, DRB2, DQB1 and DQB2 genes. Trans-species allele sharing was identified in all genes except DRB1. Site-specific selection analysis predicted genes evolving under positive selection both at DRB and DQB loci. No selected amino acid sites were identified in DQB3.

Conclusions

The organization of the MHC class II sub-region of equids is similar across all species of the family. Genomic sequences, along with phylogenetic trees suggesting effects of selection as well as trans-species polymorphism support the contention that pathogen-driven positive selection has shaped the MHC class II DRB/DQB sub-regions in the Equidae.

In silico tools for accurate HLA and KIR inference from clinical sequencing data empower immunogenetics on individual-patient and population scales

Immunogenetic variation in humans is important in research, clinical diagnosis and increasingly a target for therapeutic intervention. Two highly polymorphic loci play critical roles, namely the human leukocyte antigen (HLA) system, which is the human version of the major histocompatibility complex (MHC), and the Killer-cell immunoglobulin-like receptors (KIR) that are relevant for responses of natural killer (NK) and some subsets of T cells. Their accurate classification has typically required the use of dedicated biological specimens and a combination of in vitro and in silico efforts. Increased availability of next generation sequencing data has led to the development of ancillary computational solutions. Here, we report an evaluation of recently published algorithms to computationally infer complex immunogenetic variation in the form of HLA alleles and KIR haplotypes from whole-genome or whole-exome sequencing data. For both HLA allele and KIR gene typing, we identified tools that yielded >97% overall accuracy for four-digit HLA types, and >99% overall accuracy for KIR gene presence, suggesting the readiness of in silico solutions for use in clinical and high-throughput research settings.

Canalization and Robustness in Human Genetics and Disease

Canalization refers to the evolution of populations such that the number of individuals who deviate from the optimum trait, or experience disease, is minimized. In the presence of rapid cultural, environmental, or genetic change, the reverse process of decanalization may contribute to observed increases in disease prevalence. This review starts by defining relevant concepts, drawing distinctions between the canalization of populations and robustness of individuals. It then considers evidence pertaining to three continuous traits and six domains of disease. In each case, existing genetic evidence for genotype-by-environment interactions is insufficient to support a strong inference of decanalization, but we argue that the advent of genome-wide polygenic risk assessment now makes an empirical evaluation of the role of canalization in preventing disease possible. Finally, the contributions of both rare and common variants to congenital abnormality and adult onset disease are considered in light of a new kerplunk model of genetic effects.

Recombinant HA-based vaccine outperforms split and subunit vaccines in elicitation of influenza-specific CD4 T cells and CD4 T cell-dependent antibody responses in humans

Although traditional egg-based inactivated influenza vaccines can protect against infection, there have been significant efforts to develop improved formats to overcome disadvantages of this platform. Here, we have assessed human CD4 T cell responses to a traditional egg-based influenza vaccine with recently available cell-derived vaccines and recombinant baculovirus-derived vaccines. Adults were administered either egg-derived Fluzone^®, mammalian cell-derived Flucelvax^® or recombinant HA (Flublok^®). CD4 T cell responses to each HA protein were assessed by cytokine EliSpot and intracellular staining assays. The specificity and magnitude of antibody responses were quantified by ELISA and HAI assays. By all criteria, Flublok vaccine exhibited superior performance in eliciting both CD4 T cell responses and HA-specific antibody responses, whether measured by mean response magnitude or percent of responders. Although the mechanism(s) underlying this advantage is not yet clear, it is likely that both qualitative and quantitative features of the vaccines impact the response.

Hla-C genetic diversity and evolutionary insights in two samples from Brazil and Benin

Human leukocyte antigen-C (HLA-C) is a classical HLA class I molecule that binds and presents peptides to cytotoxic T lymphocytes in the cell surface. HLA-C has a dual function because it also interacts with Killer-cell immunoglobulin-like receptors (KIR) receptors expressed in natural killer and T cells, modulating their activity. The structure and diversity of the HLA-C regulatory regions, as well as the relationship among variants along the HLA-C locus, are poorly addressed, and few population-based studies explored the HLA-C variability in the entire gene in different population samples. Here we present a molecular and bioinformatics method to evaluate the entire HLA-C diversity, including regulatory sequences. Then, we applied this method to survey the HLA-C diversity in two population samples with different demographic histories, one highly admixed from Brazil with major European contribution, and one from Benin with major African contribution. The HLA-C promoter and 3'UTR were very polymorphic with the presence of few, but highly divergent haplotypes. These segments also present conserved sequences that are shared among different primate species. Nucleotide diversity was higher in other segments rather than exons 2 and 3, particularly around exon 5 and the second half of the 3'UTR region. We detected evidence of balancing selection on the entire HLA-C locus and positive selection in the HLA-C leader peptide, for both populations. HLA-C motifs previously associated with KIR interaction and expression regulation are similar between both populations. Each allele group is associated with specific regulatory sequences, reflecting the high linkage disequilibrium along the entire HLA-C locus in both populations.

Genetics of Immune Disease in the Horse

Host defenses against infection by viruses, bacteria, fungi, and parasites are critical to survival. It has been estimated that upwards of 7% of the coding genes of mammals function in immunity and inflammation. This high level of genomic investment in defense has resulted in an immune system characterized by extraordinary complexity and many levels of redundancy. Because so many genes are involved with immunity, there are many opportunities for mutations to arise that have negative effects. However, redundancy in the mammalian defense system and the adaptive nature of key immune mechanisms buffer the untoward outcomes of many such deleterious mutations.

Coronavirus 2019 outbreak pathogenesis: Why China and Italy?

COVID-19 has spread to most countries in the world. However, there are differences in the rate of infection in different countries. Specifically, high incidence was reported in specific areas in China (Wuhan) and Italy (Lombardy). These differences may be related to different Human Leucocyte Antigen (HLA) patterns in various geographic areas. We suggest HLA spreading between Italy and China is related to the travels of Marco Polo through the Silk Road as a potential historic explanation to COVID-19 spreading.

Next-generation sequencing of 11 HLA loci in a large dengue vaccine cohort from the Philippines

HLA genotyping by next-generation sequencing (NGS) has evolved with significant advancements in the last decade. Here we describe full-length HLA genotyping of 11 loci in 612 individuals comprising a dengue vaccine cohort from Cebu province in the Philippines. The multi-locus individual tagging NGS (MIT-NGS) method that we developed initially for genotyping 4-6 loci in one MiSeq run was expanded to 11 loci including HLA-A, B, C, DPA1, DPB1, DQA1, DQB1, DRB1, and DRB3/4/5. This change did not affect the overall coverage or depth of the sequencing reads. HLA alleles with frequencies greater than 10% were A*11:01:01, A*24:02:01, A*24:07:01, A*34:01:01, B*38:02:01, B*15:35, B*35:05:01, C*07:02:01, C*04:01:01, DPA1*02:02:02, DPB1*05:01:01, DPB1*01:01:01, DQA1*01:02:01, DQA1*06:01:01, DQB1*05:02:01, DQB1*03:01:01, DRB1*15:02:01, DRB1*12:02:01, DRB3*03:01:03, DRB4*01:03:01, and DRB5*01:01:01. Improvements in sequencing library preparation provide uniform and even coverage across all exons and introns. This has led to a marked reduction in allele imbalance and dropout. Furthermore, including more loci, such as DRB3/4/5, decreases cross-mapping and incorrect allele assignment at the DRB1 locus. The increased number of loci sequenced for each sample does not reduce the number of samples that can be multiplexed on a single MiSeq run and is therefore more cost-efficient. We believe that such improvements will help HLA genotyping by NGS to gain momentum over other conventional methods by increasing confidence in the calls.

The immunogenetic diversity of the HLA system in Mexico correlates with underlying population genetic structure

We studied HLA class I (HLA-A, -B) and class II (HLA-DRB1, -DQB1) allele groups and alleles by PCR-SSP based typing in a total of 15,318 mixed ancestry Mexicans from all the states of the country divided into 78 sample sets, providing information regarding allelic and haplotypic frequencies and their linkage disequilibrium, as well as admixture estimates and genetic substructure. We identified the presence of 4268 unique HLA extended haplotypes across Mexico and find that the ten most frequent (HF > 1%) HLA haplotypes with significant linkage disequilibrium (Δ'≥0.1) in Mexico (accounting for 20% of the haplotypic diversity of the country) are of primarily Native American ancestry (A*02~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*08~DQB1*04, A*68~B*39~DRB1*04~DQB1*03:02, A*02~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*14~DQB1*03:01, A*24~B*35~DRB1*04~DQB1*03:02, A*24~B*39~DRB1*04~DQB1*03:02, A*02~B*40:02~DRB1*04~DQB1*03:02, A*68~B*35~DRB1*04~DQB1*03:02, A*02~B*15:01~DRB1*04~DQB1*03:02). Admixture estimates obtained by a maximum likelihood method using HLA-A/-B/-DRB1 as genetic estimators revealed that the main genetic components in Mexico as a whole are Native American (ranging from 37.8% in the northern part of the country to 81.5% in the southeastern region) and European (ranging from 11.5% in the southeast to 62.6% in northern Mexico). African admixture ranged from 0.0 to 12.7% not following any specific pattern. We were able to detect three major immunogenetic clusters correlating with genetic diversity and differential admixture within Mexico: North, Central and Southeast, which is in accordance with previous reports using genome-wide data. Our findings provide insights into the population immunogenetic substructure of the whole country and add to the knowledge of mixed ancestry Latin American population genetics, important for disease association studies, detection of demographic signatures on population variation and improved allocation of public health resources.

Association of HLA-DRB1∗09:01 with tIgE levels among African-ancestry individuals with asthma

BACKGROUND

Asthma is a complex chronic inflammatory disease of the airways. Association studies between HLA and asthma were first reported in the 1970s, and yet, the precise role of HLA alleles in asthma is not fully understood. Numerous genome-wide association studies were recently conducted on asthma, but were always limited to simple genetic markers (single nucleotide polymorphisms) and not complex HLA gene polymorphisms (alleles/haplotypes), therefore not capturing the biological relevance of this complex locus for asthma pathogenesis.

OBJECTIVE

To run the first HLA-centric association study with asthma and specific asthma-related phenotypes in a large cohort of African-ancestry individuals.

METHODS

We collected high-density genomics data for the Consortium on Asthma among African-ancestry Populations in the Americas (N = 4993) participants. Using computer-intensive machine-learning attribute bagging methods to infer HLA alleles, and Easy-HLA to infer HLA 5-gene haplotypes, we conducted a high-throughput HLA-centric association study of asthma susceptibility and total serum IgE (tIgE) levels in subjects with and without asthma.

RESULTS

Among the 1607 individuals with asthma, 972 had available tIgE levels, with a mean tIgE level of 198.7 IU/mL. We could not identify any association with asthma susceptibility. However, we showed that HLA-DRB1∗09:01 was associated with increased tIgE levels (P = 8.5 × 10-4; weighted effect size, 0.51 [0.15-0.87]).

CONCLUSIONS

We identified for the first time an HLA allele associated with tIgE levels in African-ancestry individuals with asthma. Our report emphasizes that by leveraging powerful computational machine-learning methods, specific/extreme phenotypes, and population diversity, we can explore HLA gene polymorphisms in depth and reveal the full extent of complex disease associations.

An ancient view on host pathogen interaction across time and space

The ancient DNA revolution provided diverse fields with an unprecedented opportunity to look back into the past and shed light on research aspects that were until now subject to speculation and inference from modern data. In particular enrichment methods that allow the targeted retrieval of millions of SNP positions from ancient human genomes, or even complete bacterial and viral genomes have the potential to revolutionize our understanding of host pathogen interactions. Ancient DNA combined with new bioinformatic tools now even allows actual allele calling for immunogenetic systems such as Human Leukocyte Antigen (HLA) across time and space. The coming years will provide us with frequency data of human immunity genes, such as HLA, as well as genome wide data of ancient pathogens from many time periods of human history, and will therefore provide us with a dynamic view on historical human adaptation to pathogen exposure on a population wide scale.

HIV-1 p24Gag adaptation to modern and archaic HLA-allele frequency differences in ethnic groups contributes to viral subtype diversification

Pathogen-driven selection and past interbreeding with archaic human lineages have resulted in differences in human leukocyte antigen (HLA)-allele frequencies between modern human populations. Whether or not this variation affects pathogen subtype diversification is unknown. Here we show a strong positive correlation between ethnic diversity in African countries and both human immunodeficiency virus (HIV)-1 p24gag and subtype diversity. We demonstrate that ethnic HLA-allele differences between populations have influenced HIV-1 subtype diversification as the virus adapted to escape common antiviral immune responses. The evolution of HIV Subtype B (HIV-B), which does not appear to be indigenous to Africa, is strongly affected by immune responses associated with Eurasian HLA variants acquired through adaptive introgression from Neanderthals and Denisovans. Furthermore, we show that the increasing and disproportionate number of HIV-infections among African Americans in the USA drive HIV-B evolution towards an Africa-centric HIV-1 state. Similar adaptation of other pathogens to HLA variants common in affected populations is likely.

Variations in killer-cell immunoglobulin-like receptor and human leukocyte antigen genes and immunity to malaria

Malaria is one of the deadliest infectious diseases in the world. Immune responses to Plasmodium falciparum malaria vary among individuals and between populations. Human genetic variation in immune system genes is likely to play a role in this heterogeneity. Natural killer (NK) cells produce inflammatory cytokines in response to malaria infection, kill intraerythrocytic Plasmodium falciparum parasites by cytolysis, and participate in the initiation and development of adaptive immune responses to plasmodial infection. These functions are modulated by interactions between killer-cell immunoglobulin-like receptors (KIRs) and human leukocyte antigens (HLAs). Therefore, variations in KIR and HLA genes can have a direct impact on NK cell functions. Understanding the role of KIRs and HLAs in immunity to malaria can help to better characterize antimalarial immune responses. In this review, we summarize the different KIRs and HLAs associated with immunity to malaria thus far.

Common, intermediate and well-documented HLA alleles in world populations: CIWD version 3.0.0

A catalog of common, intermediate and well-documented (CIWD) HLA-A, -B, -C, -DRB1, -DRB3, -DRB4, -DRB5, -DQB1 and -DPB1 alleles has been compiled from over 8 million individuals using data from 20 unrelated hematopoietic stem cell volunteer donor registries. Individuals are divided into seven geographic/ancestral/ethnic groups and data are summarized for each group and for the total population. P (two-field) and G group assignments are divided into one of four frequency categories: common (≥1 in 10 000), intermediate (≥1 in 100 000), well-documented (≥5 occurrences) or not-CIWD. Overall 26% of alleles in IPD-IMGT/HLA version 3.31.0 at P group resolution fall into the three CIWD categories. The two-field catalog includes 18% (n = 545) common, 17% (n = 513) intermediate, and 65% (n = 1997) well-documented alleles. Full-field allele frequency data are provided but are limited in value by the variations in resolution used by the registries. A recommended CIWD list is based on the most frequent category in the total or any of the seven geographic/ancestral/ethnic groups. Data are also provided so users can compile a catalog specific to the population groups that they serve. Comparisons are made to three previous CWD reports representing more limited population groups. This catalog, CIWD version 3.0.0, is a step closer to the collection of global HLA frequencies and to a clearer view of HLA diversity in the human population as a whole.

Sequence-structure-function relationships in class I MHC: A local frustration perspective

Class I Major Histocompatibility Complex (MHC) binds short antigenic peptides with the help of Peptide Loading Complex (PLC), and presents them to T-cell Receptors (TCRs) of cytotoxic T-cells and Killer-cell Immunglobulin-like Receptors (KIRs) of Natural Killer (NK) cells. With more than 10000 alleles, human MHC (Human Leukocyte Antigen, HLA) is the most polymorphic protein in humans. This allelic diversity provides a wide coverage of peptide sequence space, yet does not affect the three-dimensional structure of the complex. Moreover, TCRs mostly interact with HLA in a common diagonal binding mode, and KIR-HLA interaction is allele-dependent. With the aim of establishing a framework for understanding the relationships between polymorphism (sequence), structure (conserved fold) and function (protein interactions) of the human MHC, we performed here a local frustration analysis on pMHC homology models covering 1436 HLA I alleles. An analysis of local frustration profiles indicated that (1) variations in MHC fold are unlikely due to minimally-frustrated and relatively conserved residues within the HLA peptide-binding groove, (2) high frustration patches on HLA helices are either involved in or near interaction sites of MHC with the TCR, KIR, or tapasin of the PLC, and (3) peptide ligands mainly stabilize the F-pocket of HLA binding groove.

Targeted analysis of polymorphic loci from low-coverage shotgun sequence data allows accurate genotyping of HLA genes in historical human populations

The highly polymorphic human leukocyte antigen (HLA) plays a crucial role in adaptive immunity and is associated with various complex diseases. Accurate analysis of HLA genes using ancient DNA (aDNA) data is crucial for understanding their role in human adaptation to pathogens. Here, we describe the TARGT pipeline for targeted analysis of polymorphic loci from low-coverage shotgun sequence data. The pipeline was successfully applied to medieval aDNA samples and validated using both simulated aDNA and modern empirical sequence data from the 1000 Genomes Project. Thus the TARGT pipeline enables accurate analysis of HLA polymorphisms in historical (and modern) human populations.

HLA Heterozygote Advantage against HIV-1 Is Driven by Quantitative and Qualitative Differences in HLA Allele-Specific Peptide Presentation

Pathogen-mediated balancing selection is regarded as a key driver of host immunogenetic diversity. A hallmark for balancing selection in humans is the heterozygote advantage at genes of the human leukocyte antigen (HLA), resulting in improved HIV-1 control. However, the actual mechanism of the observed heterozygote advantage is still elusive. HLA heterozygotes may present a broader array of antigenic viral peptides to immune cells, possibly resulting in a more efficient cytotoxic T-cell response. Alternatively, heterozygosity may simply increase the chance to carry the most protective HLA alleles, as individual HLA alleles are known to differ substantially in their association with HIV-1 control. Here, we used data from 6,311 HIV-1-infected individuals to explore the relative contribution of quantitative and qualitative aspects of peptide presentation in HLA heterozygote advantage against HIV. Screening the entire HIV-1 proteome, we observed that heterozygous individuals exhibited a broader array of HIV-1 peptides presented by their HLA class I alleles. In addition, viral load was negatively correlated with the breadth of the HIV-1 peptide repertoire bound by an individual's HLA variants, particularly at HLA-B. This suggests that heterozygote advantage at HLA-B is at least in part mediated by quantitative peptide presentation. We also observed higher HIV-1 sequence diversity among HLA-B heterozygous individuals, suggesting stronger evolutionary pressure from HLA heterozygosity. However, HLA heterozygotes were also more likely to carry certain HLA alleles, including the highly protective HLA-B*57:01 variant, indicating that HLA heterozygote advantage ultimately results from a combination of quantitative and qualitative effects in antigen presentation.

Analysis of Killer Immunoglobulin-Like Receptor Genes in Colorectal Cancer

Natural killer cells (NK cells) play a major role in the immune response to cancer. An important element of NK target recognition is the binding of human leucocyte antigen (HLA) class I molecules by killer immunoglobulin-like receptors (KIRs). Colorectal carcinoma (CRC) is one of the most common types of inflammation-based cancer. The purpose of the present study was to investigate the presence of KIR genes and HLA class I and II alleles in 1074 CRC patients and 1272 controls. We imputed data from single-nucleotide polymorphism (SNP) Illumina OncoArray to identify associations at HLA (HLA–A, B, C, DPB1, DQA1, DQB1, and DRB1) and KIRs (HIBAG and KIR*IMP, respectively). For association analysis, we used PLINK (v1.9), the PyHLA software, and R version 3.4.0. Only three SNP markers showed suggestive associations (p < 10⁻³; rs16896742, rs28367832, and rs9277952). The frequency of KIR2DS3 was significantly increased in the CRC patients compared to healthy controls (p < 0.005). Our results suggest that the implication of NK cells in CRC may not act through allele combinations in KIR and HLA genes. Much larger studies in ethnically homogeneous populations are needed to rule out the possible role of allelic combinations in KIR and HLA genes in CRC risk.

Inter- and intrabreed diversity of the major histocompatibility complex (MHC) in primitive and draft horse breeds

Background

Polymorphism of major histocompatibility complex (MHC) genes ensures effective immune responses against a wide array of pathogens. However, artificial selection, as performed in the case of domestic animals, may influence MHC diversity. Here, we investigate and compare the MHC diversity of three populations of horses, for which different breeding policies were applied, to evaluate the impact of artificial selection and the environment on MHC polymorphism.

Methods

Samples of DNA were taken from 100 Polish draft horses, 38 stabled Konik Polski horses and 32 semiferal Konik Polski horses. MHC alleles and haplotype diversity within and between these populations of horses was estimated from 11 MHC microsatellite loci.

Results

MHC diversity measured based on allelic richness, observed heterozygosity, expected heterozygosity and polymorphism content was similar across the MHC microsatellite loci in all three populations. The highest expected heterozygosity was detected in semiferal primitive horses (He = 0.74), while the lowest was calculated for draft horses (He = 0.65). In total, 203 haplotypes were determined (111 in Polish draft horses, 43 in semiferal Konik Polski horses and 49 in stabled Konik Polski horses), and four haplotypes were shared between the two populations of Koniks. None of these haplotypes were present in any of the previously investigated horse breeds. Intra-MHC recombination events were detected in all three populations. However, the population of semiferal Konik horses showed the highest recombination frequency among the three horse populations. In addition, three recombination events were detected.

Conclusions

These results showed that despite the different breeding policies, the MHC allele and haplotype diversity was similarly high in all three horse populations. Nevertheless, the proportion of new haplotypes in the offspring was the highest in semiferal Konik Polski horses, which indicates the influence of the environment on MHC diversity in horses. Thus, we speculate that the genetic makeup of the domestic horse MHC might be more strongly influenced by the environment than by artificial selection. Moreover, intra-MHC conversion, insertion, and deletion and intra-MHC recombination may be proposed as mechanisms underlying the generation of new MHC haplotypes in horses.

Impact of polymorphic transposable elements on transcription in lymphoblastoid cell lines from public data

BACKGROUND

Transposable elements (TEs) are DNA sequences able to mobilize themselves and to increase their copy-number in the host genome. In the past, they have been considered mainly selfish DNA without evident functions. Nevertheless, currently they are believed to have been extensively involved in the evolution of primate genomes, especially from a regulatory perspective. Due to their recent activity they are also one of the primary sources of structural variants (SVs) in the human genome. By taking advantage of sequencing technologies and bioinformatics tools, recent surveys uncovered specific TE structural variants (TEVs) that gave rise to polymorphisms in human populations. When combined with RNA-seq data this information provides the opportunity to study the potential impact of TEs on gene expression in human.

RESULTS

In this work, we assessed the effects of the presence of specific TEs in cis on the expression of flanking genes by producing associations between polymorphic TEs and flanking gene expression levels in human lymphoblastoid cell lines. By using public data from the 1000 Genome Project and the Geuvadis consortium, we exploited an expression quantitative trait loci (eQTL) approach integrated with additional bioinformatics data mining analyses. We uncovered human loci enriched for common, less common and rare TEVs and identified 323 significant TEV-cis-eQTL associations. SINE-R/VNTR/Alus (SVAs) resulted the TE class with the strongest effects on gene expression. We also unveiled differential functional enrichments on genes associated to TEVs, genes associated to TEV-cis-eQTLs and genes associated to the genomic regions mostly enriched in TEV-cis-eQTLs highlighting, at multiple levels, the impact of TEVs on the host genome. Finally, we also identified polymorphic TEs putatively embedded in transcriptional units, proposing a novel mechanism in which TEVs may mediate individual-specific traits.

CONCLUSION

We contributed to unveiling the effect of polymorphic TEs on transcription in lymphoblastoid cell lines.