Understanding natural selection is crucial to unveiling evolution of modern humans. Here, we report natural selection signatures in the Japanese population using 2234 high-depth whole-genome sequence (WGS) data (25.9×). Using rare singletons, we identify signals of very recent selection for the past 2000–3000 years in multiple loci (ADH cluster, MHC region, BRAP-ALDH2, SERHL2). In large-scale genome-wide association study (GWAS) dataset (n = 171,176), variants with selection signatures show enrichment in heterogeneity of derived allele frequency spectra among the geographic regions of Japan, highlighted by two major regional clusters (Hondo and Ryukyu). While the selection signatures do not show enrichment in archaic hominin-derived genome sequences, they overlap with the SNPs associated with the modern human traits. The strongest overlaps are observed for the alcohol or nutrition metabolism-related traits. Our study illustrates the value of high-depth WGS to understand evolution and their relationship with disease risk.

ObjectiveThe causality and pathogenic mechanism of microbiome composition remain elusive in many diseases, including autoimmune diseases such as rheumatoid arthritis (RA). This study aimed to elucidate gut microbiome’s role in RA pathology by a comprehensive metagenome-wide association study (MWAS).MethodsWe conducted MWAS of the RA gut microbiome in the Japanese population (n case=82, n control=42) by using whole-genome shotgun sequencing of high depth (average 13 Gb per sample). Our MWAS consisted of three major bioinformatic analytic pipelines (phylogenetic analysis, functional gene analysis and pathway analysis).ResultsPhylogenetic case–control association tests showed high abundance of multiple species belonging to the genus Prevotella (e.g., Prevotella denticola) in the RA case metagenome. The non-linear machine learning method efficiently deconvoluted the case–control phylogenetic discrepancy. Gene functional assessments showed that the abundance of one redox reaction-related gene (R6FCZ7) was significantly decreased in the RA metagenome compared with controls. A variety of biological pathways including those related to metabolism (e.g., fatty acid biosynthesis and glycosaminoglycan degradation) were enriched in the case–control comparison. A population-specific link between the metagenome and host genome was identified by comparing biological pathway enrichment between the RA metagenome and the RA genome-wide association study results. No apparent discrepancy in alpha or beta diversities of metagenome was found between RA cases and controls.ConclusionOur shotgun sequencing-based MWAS highlights a novel link among the gut microbiome, host genome and pathology of RA, which contributes to our understanding of the microbiome’s role in RA aetiology.

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Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

In the design of whole-genome sequencing (WGS) studies, sequencing depth is a crucial parameter to define variant calling accuracy and study cost, with no standard recommendations having been established. We empirically evaluated the variant calling accuracy of the WGS pipeline using ultra-deep WGS data (approximately 410×). We randomly sampled sequence reads and constructed a series of simulation WGS datasets with a variety of gradual depths (n = 54; from 0.05× to 410×). Next, we evaluated the genotype concordances of the WGS data with those in the SNP microarray data or the WGS data using all the sequence reads. In addition, we assessed the accuracy of HLA allele genotyping using the WGS data with multiple software tools (PHLAT, HLA-VBseq, HLA-HD, and SNP2HLA). The WGS data with higher depths showed higher concordance rates, and >13.7× depth achieved as high as >99% of concordance. Comparisons with the WGS data using all the sequence reads showed that SNVs achieved >95% of concordance at 17.6× depth, whereas indels showed only 60% concordance. For the accuracy of HLA allele genotyping using the WGS data, 13.7× depth showed sufficient accuracy while performance heterogeneity among the software tools was observed (the highest concordance of 96.9% was observed with HLA-HD). Improvement in HLA genotyping accuracy by further increasing the depths was limited. These results suggest a medium degree of the WGS depth setting (approximately 15×) to achieve both accurate SNV calling and cost-effectiveness, whereas relatively higher depths are required for accurate indel calling.

MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA–target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA–target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs (nTotal = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls (n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10−8). Our result highlighted that miRNA–target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.

ObjectiveThe relationship between autoimmune diseases and the gut microbiome has been intensively studied, and several autoimmunity-associated bacterial taxa have been identified. However, much less is known about the roles of the gut virome in autoimmune diseases.MethodsHere, we performed a whole gut virome analysis based on the shotgun sequencing of 476 Japanese which included patients with rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), multiple sclerosis and healthy control subjects.ResultsOur case–control comparison of the viral abundance revealed that crAss-like phages, which are one of the main components of a healthy gut virome, significantly decreased in the gut of the patients with autoimmune disease, specifically the patients with RA and SLE. In addition, Podoviridae significantly decreased in the gut of the patients with SLE. To understand how these viruses affected the bacteriome, we performed a quantitative virus–bacterium association analysis and clustered regularly interspaced short palindromic repeat-based virus–bacterium interaction analysis. We identified a symbiosis between Podoviridae and Faecalibacterium. In addition, multiple bacterial targets of crAss-like phages were identified (eg, Ruminococcus spp).ConclusionOur data suggest that the gut virome can affect our body either directly or via bacteria. Our analyses have elucidated a previously missing part of the autoimmunity-associated gut microbiome and presented new candidates that contribute to the development of autoimmune diseases.

ObjectiveAlteration of the gut microbiome has been linked to the pathogenesis of systemic lupus erythematosus (SLE). However, a comprehensive view of the gut microbiome in SLE and its interaction with the host remains to be revealed. This study aimed to reveal SLE-associated changes in the gut microbiome and its interaction with the host by a comprehensive metagenome-wide association study (MWAS) followed by integrative analysis.MethodsWe performed a MWAS of SLE based on shotgun sequencing of the gut microbial DNA from Japanese individuals (Ncase=47, Ncontrol=203). We integrated the result of the MWAS with the genome-wide association study (GWAS) data and plasma metabolite data.ResultsVia species level phylogenetic analysis, we identified and validated increases of Streptococcus intermedius and Streptococcus anginosus in the patients with SLE. Microbial gene analysis revealed increases of Streptococcus-derived genes including one involved in redox reaction. Additionally, microbial pathways related to sulfur metabolism and flagella assembly were altered in the patients with SLE. We identified an overlap in the enriched biological pathways between the metagenome and the germline genome by comparing the result of the MWAS and the GWAS of SLE (ie, MWAS-GWAS interaction). α-diversity and β-diversity analyses provided evidence of dysbiosis in the metagenome of the patients with SLE. Microbiome-metabolome association analysis identified positive dosage correlation of acylcarnitine with Streptococcus intermedius, an SLE-associated taxon.ConclusionOur MWAS followed by integrative analysis revealed SLE-associated changes in the gut microbiome and its interaction with the host, which contribute to our understanding of the relationship between the microbiome and SLE.