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.

Multi-omics colocalization with genome-wide association studies reveals a context-specific genetic mechanism at a childhood onset asthma risk locus

Background Genome-wide association studies (GWASs) have identified thousands of variants associated with asthma and other complex diseases. However, the functional effects of most of these variants are unknown. Moreover, GWASs do not provide context-specific information on cell types or environmental factors that affect specific disease risks and outcomes. To address these limitations, we used an upper airway epithelial cell (AEC) culture model to assess transcriptional and epigenetic responses to rhinovirus (RV), an asthma-promoting pathogen, and provide context-specific functional annotations to variants discovered in GWASs of asthma. Methods Genome-wide genetic, gene expression, and DNA methylation data in vehicle- and RV-treated upper AECs were collected from 104 individuals who had a diagnosis of airway disease (n=66) or were healthy participants (n=38). We mapped cis expression and methylation quantitative trait loci (cis-eQTLs and cis-meQTLs, respectively) in each treatment condition (RV and vehicle) in AECs from these individuals. A Bayesian test for colocalization between AEC molecular QTLs and adult onset asthma and childhood onset asthma GWAS SNPs, and a multi-ethnic GWAS of asthma, was used to assign the function to variants associated with asthma. We used Mendelian randomization to demonstrate DNA methylation effects on gene expression at asthma colocalized loci. Results Asthma and allergic disease-associated GWAS SNPs were specifically enriched among molecular QTLs in AECs, but not in GWASs from non-immune diseases, and in AEC eQTLs, but not among eQTLs from other tissues. Colocalization analyses of AEC QTLs with asthma GWAS variants revealed potential molecular mechanisms of asthma, including QTLs at the TSLP locus that were common to both the RV and vehicle treatments and to both childhood onset and adult onset asthma, as well as QTLs at the 17q12-21 asthma locus that were specific to RV exposure and childhood onset asthma, consistent with clinical and epidemiological studies of these loci. Conclusions This study provides evidence of functional effects for asthma risk variants in AECs and insight into RV-mediated transcriptional and epigenetic response mechanisms that modulate genetic effects in the airway and risk for asthma.

Integrative Epigenome Map of the Normal Human Prostate Provides Insights Into Prostate Cancer Predisposition

Cells of all tissues in the human body share almost the exact same DNA sequence, but the epigenomic landscape can be drastically distinct. To improve our understanding of the epigenetic abnormalities in prostate-related diseases, it is important to use the epigenome of normal prostate as a reference. Although previous efforts have provided critical insights into the genetic and transcriptomic features of the normal prostate, a comprehensive epigenome map has been lacking. To address this need, we conducted a Roadmap Epigenomics legacy project integrating six histone marks (H3K4me1, H3K4me3, H3K9me3, H3K36me3, H3K27me3, and H3K27ac) with complete DNA methylome, transcriptome, and chromatin accessibility data to produce a comprehensive epigenome map of normal prostate tissue. Our epigenome map is composed of 18 chromatin states each with unique signatures of DNA methylation, chromatin accessibility, and gene expression. This map provides a high-resolution comprehensive annotation of regulatory regions of the prostate, including 105,593 enhancer and 70,481 promoter elements, which account for 5.3% of the genome. By comparing with other epigenomes, we identified 7,580 prostate-specific active enhancers associated with prostate development. Epigenomic annotation of GWAS SNPs associated with prostate cancers revealed that two out of nine SNPs within prostate enhancer regions destroyed putative androgen receptor (AR) binding motif. A notable SNP rs17694493, might decouple AR’s repressive effect on CDKN2B-AS1 and cell cycle regulation, thereby playing a causal role in predisposing cancer risk. The comprehensive epigenome map of the prostate is valuable for investigating prostate-related diseases.

Sequencing at lymphoid neoplasm susceptibility loci maps six myeloma risk genes

Inherited genetic risk factors play a role in multiple myeloma (MM), yet considerable missing heritability exists. Rare risk variants at genome-wide association study (GWAS) loci are a new avenue to explore. Pleiotropy between lymphoid neoplasms (LNs) has been suggested in family history and genetic studies, but no studies have interrogated sequencing for pleiotropic genes or rare risk variants. Sequencing genetically enriched cases can help discover rarer variants. We analyzed exome sequencing in familial or early-onset MM cases to identify rare, functionally relevant variants near GWAS loci for a range of LNs. A total of 149 distinct and significant LN GWAS loci have been published. We identified six recurrent, rare, potentially deleterious variants within 5 kb of significant GWAS SNPs in 75 MM cases. Mutations were observed in BTNL2, EOMES, TNFRSF13B, IRF8, ACOXL, and TSPAN32. All six genes replicated in an independent set of 255 early-onset MM or familial MM or precursor cases. Expansion of our analyses to the full length of these six genes resulted in a list of 39 rare and deleterious variants, 7 of which segregated in MM families. Three genes also had significant rare variant burden in 733 sporadic MM cases compared with 935 control individuals: IRF8 (p = 1.0x10−6), EOMES (p = 6.0x10−6), and BTNL2 (p = 2.1x10−3). Together, our results implicate six genes in MM risk, provide support for genetic pleiotropy between LN subtypes, and demonstrate the utility of sequencing genetically enriched cases to identify functionally relevant variants near GWAS loci.

The Long Life Family Study: Sequencing Exceptional Pedigrees for Rare Protective Variants

The Long Life Family Study (LLFS) has longitudinally measured key aging phenotypes on 4,953 participants (539 pedigrees) in the USA and Denmark selected for exceptional familial longevity. On average, both generations of the LLFS sample are healthier than average for their age/sex, for many phenotypes. However, the pedigrees are heterogeneous, with different families showing familial clustering of protection for different phenotypes. Linkage analyses identified extremely strong genetic linkage peaks for many cross-sectional as well as longitudinal trajectory rates of change phenotypes. These peaks are NOT explained by GWAS SNPs (either measured or imputed). Pedigree specific HLODs and preliminary deep sequencing suggests that these peaks are driven by rare, protective variants running in selected pedigrees. Whole Genome Sequencing, a third longitudinal visit, and extensive OMICs (transcriptomics, epigenomics, metabolomics and proteomics) will help us resolve the mechanisms behind these protective genetically linked variants, and could illuminate new biology and enable new therapeutics.

Evidence for enhancer noncoding RNAs (enhancer-ncRNAs) with gene regulatory functions relevant to neurodevelopmental disorders

Noncoding RNAs (ncRNAs) comprise a significant proportion of the mammalian genome, but their biological significance in neurodevelopment disorders is poorly understood. In this study, we identified 908 brain-enriched noncoding RNAs comprising at least one nervous system-related eQTL polymorphism that is associated with protein coding genes and also overlap with chromatin states characterised as enhancers. We referred to such noncoding RNAs with putative enhancer activity as brain ‘enhancer-ncRNAs’. By integrating GWAS SNPs and Copy Number Variation (CNV) data from neurodevelopment disorders, we found that 265 enhancer-ncRNAs were either mutated (CNV deletion or duplication) or contain at least one GWAS SNPs in the context of such conditions. Of these, the eQTL-associated gene for 82 enhancer-ncRNAs did not overlap with either GWAS SNPs or CNVs suggesting in such contexts that mutations to neurodevelopment gene enhancers disrupt ncRNA interaction. Taken together, we identified 49 novel NDD-associated ncRNAs that influence genomic enhancers during neurodevelopment, suggesting enhancer mutations may be relevant to the functions for such ncRNAs in neurodevelopmental disorders.

Support for the genetic hypothesis of the Black-white achievement gap using polygenic scores and tests for divergent selection

Using the latest methods to detect divergent evolution and polygenic selection, I test the hypothesis that race differences (European-African) in IQ are due to genetic differences.The genetic variants identified by the largest GWAS of education showed clear signatures of differentiation between Africans and Europeans. Across different phenotypes (educational attainment, cognitive performance, math ability), GWAS SNPs had significantly higher average Fst than control SNPs. Contrary to a previous report, the same effect was found also for a GWAS based on a within-family design, that used differences in educational attainment between siblings to partial out shared environmental effects. Polygenic scores for all phenotypes and GWAS types (including within-family design) were higher for Europeans than for Africans.