Transcriptome-wide association study identified candidate genes associated with gut microbiota.
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ABSTRACT: Background
Gut microbiota is closely associated with host health and disease occurrence. Host genetic factor plays an important role in shaping gut microbial communities. The specific mechanism of host-regulated gene expression affecting gut microbiota has not been elucidated yet. Here we conducted a transcriptome-wide association study (TWAS) for gut microbiota by leveraging expression imputation from large-scale GWAS data sets.Results
TWAS detected multiple tissue-specific candidate genes for gut microbiota, such as FUT2 for genus Bifidobacterium in transverse colon (PPERM.ANL = 1.68 × 10-3) and SFTPD for an unclassified genus of Proteobacteria in transverse colon (PPERM.ANL = 5.69 × 10-3). Fine mapping replicated 3 candidate genes in TWAS, such as HELLS for Streptococcus (PIP = 0.685) in sigmoid colon, ANO7 for Erysipelotrichaceae (PIP = 0.449) in sigmoid colon. Functional analyses detected 94 significant GO terms and 11 pathways for various taxa in total, such as GO_NUCLEOSIDE_DIPHOSPHATASE_ACTIVITY for Butyrivibrio (FDR P = 1.30 × 10-4), KEGG_RENIN_ANGIOTENSIN_SYSTEM for Anaerostipes (FDR P = 3.16 × 10-2). Literature search results showed 12 genes prioritized by TWAS were associated with 12 diseases. For instance, SFTPD for an unclassified genus of Proteobacteria was related to atherosclerosis, and FUT2 for Bifidobacterium was associated with Crohn's disease.Conclusions
Our study results provided novel insights for understanding the genetic mechanism of gut microbiota, and attempted to provide clues for revealing the influence of genetic factors on gut microbiota for the occurrence and development of diseases.
SUBMITTER: Pan C
PROVIDER: S-EPMC8684646 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Genome-wide association studies (GWAS) have so far identified 25 loci associated with glioma risk, with most showing specificity for either glioblastoma (GBM) or non-GBM tumors. The majority of these GWAS susceptibility variants reside in noncoding regions and the causal genes underlying the associations are largely unknown. Here we performed a transcriptome-wide association study to search for novel risk loci and candidate causal genes at known GWAS loci using Genotype-Tissue Expression Project (GTEx) data to predict cis-predicted gene expression in relation to GBM and non-GBM risk in conjunction with GWAS summary statistics on 12,488 glioma cases (6,183 GBM and 5,820 non-GBM) and 18,169 controls. Imposing a Bonferroni-corrected significance level of P < 5.69 × 10-6, we identified 31 genes, including GALNT6 at 12q13.33, as a candidate novel risk locus for GBM (mean Z = 4.43; P = 5.68 × 10-6). GALNT6 resides at least 55 Mb away from any previously identified glioma risk variant, while all other 30 significantly associated genes were located within 1 Mb of known GWAS-identified loci and were not significant after conditioning on the known GWAS-identified variants. These data identify a novel locus (GALNT6 at 12q13.33) and 30 genes at 12 known glioma risk loci associated with glioma risk, providing further insights into glioma tumorigenesis. SIGNIFICANCE: This study identifies new genes associated with glioma risk, increasing understanding of how these tumors develop.
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Project description:BackgroundStroke is a major public health burden worldwide. Although genetic variation is known to play a role in the pathogenesis of stroke, the specific pathogenic mechanisms are still unclear. Transcriptome-wide association studies (TWAS) is a powerful approach to prioritize candidate risk genes underlying complex traits. However, this approach has not been applied in stroke.MethodsWe conducted an integrative analysis of TWAS using data from the MEGASTROKE Consortium and gene expression profiling to identify candidate genes for the pathogenesis of stroke. Gene ontology (GO) enrichment analysis was also conducted to detect functional gene sets.ResultsThe TWAS identified 515 transcriptome-wide significant tissue-specific genes, among which SLC25A44 (P = 5.46E-10) and LRCH1 (P = 1.54E-6) were significant by Bonferroni test for stroke. After validation with gene expression profiling, 19 unique genes were recognized. GO enrichment analysis identified eight significant GO functional gene sets, including regulation of cell shape (P = 0.0059), face morphogenesis (P = 0.0247), and positive regulation of ATPase activity (P = 0.0256).ConclusionsOur study identified multiple stroke-associated genes and gene sets, and this analysis provided novel insights into the genetic mechanisms underlying stroke.
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Project description:Lodging reduces rice yield, but increasing lodging resistance (LR) usually limits yield potential. Stem strength and leaf type are major traits related to LR and yield, respectively. Hence, understanding the genetic basis of stem strength and leaf type is of help to reduce lodging and increase yield in LR breeding. Here, we carried out an association analysis to identify quantitative trait locus (QTLs) affecting stem strength-related traits (internode length/IL, stem wall thickness/SWT, stem outer diameter/SOD, and stem inner diameter/SID) and leaf type-associated traits (Flag leaf length/FLL, Flag leaf angle/FLA, Flag leaf width/FLW, leaf-rolling/LFR and SPAD/Soil, and plant analyzer development) using a diverse panel of 550 accessions and evaluated over two years. Genome-wide association study (GWAS) using 4,076,837 high-quality single-nucleotide polymorphisms (SNPs) identified 89 QTLs for the nine traits. Next, through "gene-based association analysis, haplotype analysis, and functional annotation", the scope was narrowed down step by step. Finally, we identified 21 candidate genes in 9 important QTLs that included four reported genes (TUT1, OsCCC1, CFL1, and ACL-D), and seventeen novel candidate genes. Introgression of alleles, which are beneficial for both stem strength and leaf type, or pyramiding stem strength alleles and leaf type alleles, can be employed for LR breeding. All in all, the experimental data and the identified candidate genes in this study provide a useful reference for the genetic improvement of rice LR.
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| S-EPMC7572664 | biostudies-literature
Project description:BackgroundAlthough 20 pancreatic cancer susceptibility loci have been identified through genome-wide association studies in individuals of European ancestry, much of its heritability remains unexplained and the genes responsible largely unknown.MethodsTo discover novel pancreatic cancer risk loci and possible causal genes, we performed a pancreatic cancer transcriptome-wide association study in Europeans using three approaches: FUSION, MetaXcan, and Summary-MulTiXcan. We integrated genome-wide association studies summary statistics from 9040 pancreatic cancer cases and 12 496 controls, with gene expression prediction models built using transcriptome data from histologically normal pancreatic tissue samples (NCI Laboratory of Translational Genomics [n = 95] and Genotype-Tissue Expression v7 [n = 174] datasets) and data from 48 different tissues (Genotype-Tissue Expression v7, n = 74-421 samples).ResultsWe identified 25 genes whose genetically predicted expression was statistically significantly associated with pancreatic cancer risk (false discovery rate < .05), including 14 candidate genes at 11 novel loci (1p36.12: CELA3B; 9q31.1: SMC2, SMC2-AS1; 10q23.31: RP11-80H5.9; 12q13.13: SMUG1; 14q32.33: BTBD6; 15q23: HEXA; 15q26.1: RCCD1; 17q12: PNMT, CDK12, PGAP3; 17q22: SUPT4H1; 18q11.22: RP11-888D10.3; and 19p13.11: PGPEP1) and 11 at six known risk loci (5p15.33: TERT, CLPTM1L, ZDHHC11B; 7p14.1: INHBA; 9q34.2: ABO; 13q12.2: PDX1; 13q22.1: KLF5; and 16q23.1: WDR59, CFDP1, BCAR1, TMEM170A). The association for 12 of these genes (CELA3B, SMC2, and PNMT at novel risk loci and TERT, CLPTM1L, INHBA, ABO, PDX1, KLF5, WDR59, CFDP1, and BCAR1 at known loci) remained statistically significant after Bonferroni correction.ConclusionsBy integrating gene expression and genotype data, we identified novel pancreatic cancer risk loci and candidate functional genes that warrant further investigation.
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Project description:IntroductionCataract is the leading cause of blindness among the elderly worldwide. Twin and family studies support an important role for genetic factors in cataract susceptibility with heritability estimates up to 58%. To date, 55 loci for cataract have been identified by genome-wide association studies (GWAS), however, much work remains to identify the causal genes. Here, we conducted a transcriptome-wide association study (TWAS) of cataract to prioritize causal genes and identify novel ones, and examine the impact of their expression.MethodsWe performed tissue-specific and multi-tissue TWAS analyses to assess associations between imputed gene expression from 54 tissues (including 49 from the Genotype Tissue Expression (GTEx) Project v8) with cataract using FUSION software. Meta-analyzed GWAS summary statistics from 59,944 cataract cases and 478,571 controls, all of European ancestry and from two cohorts (GERA and UK Biobank) were used. We then examined the expression of the novel genes in the lens tissue using the iSyTE database.ResultsAcross tissue-specific and multi-tissue analyses, we identified 99 genes for which genetically predicted gene expression was associated with cataract after correcting for multiple testing. Of these 99 genes, 20 (AC007773.1, ANKH, ASIP, ATP13A2, CAPZB, CEP95, COQ6, CREB1, CROCC, DDX5, EFEMP1, EIF2S2, ESRRB, GOSR2, HERC4, INSRR, NIPSNAP2, PICALM, SENP3, and SH3YL1) did not overlap with previously reported cataract-associated loci. Tissue-specific analysis identified 202 significant gene-tissue associations for cataract, of which 166 (82.2%), representing 9 unique genes, were attributed to the previously reported 11q13.3 locus. Tissue-enrichment analysis revealed that gastrointestinal tissues represented one of the highest proportions of the Bonferroni-significant gene-tissue associations (21.3%). Moreover, this gastrointestinal tissue type was the only anatomical category significantly enriched in our results, after correcting for the number of tissue donors and imputable genes for each reference panel. Finally, most of the novel cataract genes (e.g., Capzb) were robustly expressed in iSyTE lens data.DiscussionOur results provide evidence of the utility of imputation-based TWAS approaches to characterize known GWAS risk loci and identify novel candidate genes that may increase our understanding of cataract etiology. Our findings also highlight the fact that expression of genes associated with cataract susceptibility is not necessarily restricted to lens tissue.
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