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Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study.

ABSTRACT: BACKGROUND: Many studies have shown that the abundance level of gene expression is heritable. Analogous to the traditional genetic study, most researchers treat the expression of one gene as a quantitative trait and map it to expression quantitative trait loci (eQTL). This is 1D-trait mapping. 1D-trait mapping ignores the trait-trait interaction completely, which is a major shortcoming. RESULTS: To overcome this limitation, we study the expression of a pair of genes and treat the variation in their co-expression pattern as a two dimensional quantitative trait. We develop a method to find gene pairs, whose co-expression patterns, including both signs and strengths, are mediated by genetic variations and map these 2D-traits to the corresponding genetic loci. We report several applications by combining 1D-trait mapping with 2D-trait mapping, including the contribution of genetic variations to the perturbations in the regulatory mechanisms of yeast metabolic pathways. CONCLUSION: Our approach of 2D-trait mapping provides a novel and effective way to connect the genetic variation with higher order biological modules via gene expression profiles.

SUBMITTER: Sun W

PROVIDER: S-EPMC2432080 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study.

Sun Wei W Yuan Shinsheng S Li Ker-Chau KC

BMC genomics 20080523

<h4>Background</h4>Many studies have shown that the abundance level of gene expression is heritable. Analogous to the traditional genetic study, most researchers treat the expression of one gene as a quantitative trait and map it to expression quantitative trait loci (eQTL). This is 1D-trait mapping. 1D-trait mapping ignores the trait-trait interaction completely, which is a major shortcoming.<h4>Results</h4>To overcome this limitation, we study the expression of a pair of genes and treat the va ...[more]

PMID: 18498664

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Project description:BackgroundExpression quantitative trait loci (eQTL) have been identified using tissue or cell samples from diverse human populations, thus enhancing our understanding of regulation of gene expression. However, few studies have attempted to identify eQTL in racially admixed populations such as Hispanics.MethodsWe performed a systematic eQTL study to identify regulatory variants of gene expression in whole blood from 121 Puerto Rican children with (n = 63) and without (n = 58) asthma. Genome-wide genotyping was conducted using the Illumina Omni2.5M Bead Chip, and gene expression was assessed using the Illumina HT-12 microarray. After completing quality control, we performed a pair-wise genome analysis of ~15 K transcripts and ~1.3 M SNPs for both local and distal effects. This analysis was conducted under a regression framework adjusting for age, gender and principal components derived from both genotypic and mRNA data. We used a false discovery rate (FDR) approach to identify significant eQTL signals, which were next compared to top eQTL signals from existing eQTL databases. We then performed a pathway analysis for our top genes.ResultsWe identified 36,720 local pairs in 3,391 unique genes and 1,851 distal pairs in 446 unique genes at FDR <0.05, corresponding to unadjusted P values lower than 1.5x10-4 and 4.5x10-9, respectively. A significant proportion of genes identified in our study overlapped with those identified in previous studies. We also found an enrichment of disease-related genes in our eQTL list.ConclusionsWe present results from the first eQTL study in Puerto Rican children, who are members of a unique Hispanic cohort disproportionately affected with asthma, prematurity, obesity and other common diseases. Our study confirmed eQTL signals identified in other ethnic groups, while also detecting additional eQTLs unique to our study population. The identified eQTLs will help prioritize findings from future genome-wide association studies in Puerto Ricans.

Project description:Background & aimsIn contrast to most other common diseases, few genetic variants have been identified that impact risk of cirrhosis. We aimed to identify new genetic variants that predispose to cirrhosis, to test whether such variants, aggregated into a polygenic score, enable genomic risk stratification, and to test whether alcohol intake or body mass index interacts with polygenic predisposition.MethodsWe conducted a multi-trait genome-wide association study combining cirrhosis and alanine aminotransferase levels performed in 5 discovery studies (UK Biobank, Vanderbilt BioVU, Atherosclerosis Risk in Communities study, and 2 case-control studies including 4829 individuals with cirrhosis and 72,705 controls and 362,539 individuals with alanine aminotransferase levels). Identified variants were replicated in 3 studies (Partners HealthCare Biobank, FinnGen, and Biobank Japan including 3554 individuals with cirrhosis and 343,826 controls). A polygenic score was tested in Partners HealthCare Biobank.ResultsFive previously reported and 7 newly identified genetic variants were associated with cirrhosis in both the discovery studies multi-trait genome-wide association study (P < 5 × 10-8) and the replication studies (P < .05), including a missense variant in the APOE gene and a noncoding variant near EFN1A. These 12 variants were used to generate a polygenic score. Among Partners HealthCare Biobank individuals, high polygenic score-defined as the top quintile of the distribution-was associated with significantly increased risk of cirrhosis (odds ratio, 2.26; P < .001) and related comorbidities compared with the lowest quintile. Risk was even more pronounced among those with extreme polygenic risk (top 1% of the distribution, odds ratio, 3.16; P < .001). The impact of extreme polygenic risk was substantially more pronounced in those with elevated alcohol consumption or body mass index. Modeled as risk by age 75 years, probability of cirrhosis with extreme polygenic risk was 13.7%, 20.1%, and 48.2% among individuals with no or modest, moderate, and increased alcohol consumption, respectively (Pinteraction < .001). Similarly, probability among those with extreme polygenic risk was 6.5%, 10.3%, and 19.5% among individuals with normal weight, overweight, and obesity, respectively (Pinteraction < .001).ConclusionsTwelve independent genetic variants, 7 of which are newly identified in this study, conferred risk for cirrhosis. Aggregated into a polygenic score, these variants identified a subset of the population at substantially increased risk who are most susceptible to the hepatotoxic effects of excess alcohol consumption or obesity.

Dataset Information

Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study.

Publications

Trait-trait dynamic interaction: 2D-trait eQTL mapping for genetic variation study.

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