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

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 genet...

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Main Authors: He, Tianhua, Hill, C., Angessa, T., Zhang, X., Chen, Kefei, Moody, D., Telfer, P., Westcott, S., Li, C.
Format: Journal Article
Language:English
Published: 2019
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/76411
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author He, Tianhua
Hill, C.
Angessa, T.
Zhang, X.
Chen, Kefei
Moody, D.
Telfer, P.
Westcott, S.
Li, C.
author_facet He, Tianhua
Hill, C.
Angessa, T.
Zhang, X.
Chen, Kefei
Moody, D.
Telfer, P.
Westcott, S.
Li, C.
author_sort He, Tianhua
building Curtin Institutional Repository
collection Online Access
description 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.
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institution Curtin University Malaysia
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spelling curtin-20.500.11937-764112019-10-03T07:34:47Z Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection He, Tianhua Hill, C. Angessa, T. Zhang, X. Chen, Kefei Moody, D. Telfer, P. Westcott, S. Li, C. Barley GWAS epistasis flowering time gene-set association analysis heritability next-generation sequencing phenology target capture target enrichment 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. 2019 Journal Article http://hdl.handle.net/20.500.11937/76411 10.1093/jxb/erz332 eng http://creativecommons.org/licenses/by-nc/4.0/ fulltext
spellingShingle Barley
GWAS
epistasis
flowering time
gene-set association analysis
heritability
next-generation sequencing
phenology
target capture
target enrichment
He, Tianhua
Hill, C.
Angessa, T.
Zhang, X.
Chen, Kefei
Moody, D.
Telfer, P.
Westcott, S.
Li, C.
Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title_full Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title_fullStr Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title_full_unstemmed Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title_short Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
title_sort gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection
topic Barley
GWAS
epistasis
flowering time
gene-set association analysis
heritability
next-generation sequencing
phenology
target capture
target enrichment
url http://hdl.handle.net/20.500.11937/76411