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Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.

ABSTRACT: Single-marker genome-wide association studies (GWAS) have successfully detected associations between single nucleotide polymorphisms (SNPs) and agronomic traits such as flowering time and grain yield in barley. However, the analysis of individual SNPs can only account for a small proportion of genetic variation, and can only provide limited knowledge on gene network interactions. Gene-based GWAS approaches provide enormous opportunity both to combine genetic information and to examine interactions among genetic variants. Here, we revisited a previously published phenotypic and genotypic data set of 895 barley varieties grown in two years at four different field locations in Australia. We employed statistical models to examine gene-phenotype associations, as well as two-way epistasis analyses to increase the capability to find novel genes that have significant roles in controlling flowering time in barley. Genetic associations were tested between flowering time and corresponding genotypes of 174 putative flowering time-related genes. Gene-phenotype association analysis detected 113 genes associated with flowering time in barley, demonstrating the unprecedented power of gene-based analysis. Subsequent two-way epistasis analysis revealed 19 pairs of gene×gene interactions involved in controlling flowering time. Our study demonstrates that gene-based association approaches can provide higher capacity for future crop improvement to increase crop performance and adaptation to different environments.

SUBMITTER: He T

PROVIDER: S-EPMC6812734 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature

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Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.

He Tianhua T Hill Camilla Beate CB Angessa Tefera Tolera TT Zhang Xiao-Qi XQ Chen Kefei K Moody David D Telfer Paul P Westcott Sharon S Li Chengdao C

Journal of experimental botany 20191001 20

Single-marker genome-wide association studies (GWAS) have successfully detected associations between single nucleotide polymorphisms (SNPs) and agronomic traits such as flowering time and grain yield in barley. However, the analysis of individual SNPs can only account for a small proportion of genetic variation, and can only provide limited knowledge on gene network interactions. Gene-based GWAS approaches provide enormous opportunity both to combine genetic information and to examine interactio ...[more]

PMID: 31504706

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Project description:Drought is a devastating environmental constraint affecting the agronomic production of barley. To facilitate the breeding process, abundant germplasm resources and reliable evaluation systems to identify the true drought-tolerant barley genotypes are needed. In this study, 237 cultivated and 190 wild barley genotypes, originating from 28 countries, were screened for drought tolerance under the conditions of both water deficit and polyethylene glycol (PEG)-simulated drought at seedling stage. Drought stress significantly reduced the plant growth of all barley genotypes, but no significant difference in drought-induced reduction in the performance of barley seedlings was observed under these two drought conditions. Both cultivated and wild barley subspecies displayed considerable genotypic variability in drought tolerance, which underpinned the identification of 18 genotypes contrasting in drought tolerance. A comparative analysis of drought effects on biomass, water relation, photosynthesis, and osmotic adjustment was undertaken using these contrasting barley genotypes, in order to verify the reliability of the screening and to obtain the credible traits as screening criteria of drought tolerance in barley. As expected, the selected drought-tolerant genotypes showed much less reduction in shoot biomass than drought-sensitive ones under water deficit, which was significantly positively correlated with the results of large-scale screening, confirming the reliability of the screening for drought tolerance under two drought conditions in this study. Likewise, the traits of water relation, photosynthetic activity, and osmotic adjustment differed greatly between the contrasting genotypes under water deficit stress, and they were highly correlated to the growth of barley seedlings, suggesting the potential of them to be the selection criteria for drought tolerance. The analysis of the variable importance of these traits in drought tolerance indicated that sap osmolality and relative water content in the youngest fully-expanded leaf are the suitable selection criteria of screening for drought tolerance in barley at seedling stage.

Project description:Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.

Dataset Information

Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.

Publications

Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.

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