ArticleJournal of experimental botany2019
Gene-set association and epistatic analyses reveal complex gene interaction networks affecting flowering time in a worldwide barley collection.
Article in Journal of experimental botany, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- Machine learning to predict genotypes and genotype-environment interaction associated with complex traits for genomic selection.Plant phenomics (Washington, D.C.) · 2026Article
- Identification of adaptive selection footprints and adaptation strategies of hulless barley (Hordeum vulgare var. coeleste) on the Qinghai-Tibet Plateau.BMC genomics · 2026Article
- A novel genetic framework reveals transcriptional "butterfly effect" underlying heterosis in maize.Journal of advanced research · 2026Article
- Genome-Wide Association Study on Lodging Resistance-Related Traits in Oats.Plants (Basel, Switzerland) · 2026Article
- Genome-wide association mapping and transcriptional analysis uncover genetic determinants of minor tocopherols in rice seeds.Scientific reports · 2025Article
- Unraveling the Complexities of Flowering in Ornamental Plants: The Interplay of Genetics, Hormonal Networks, and Microbiome.Plants (Basel, Switzerland) · 2025Review
- Historic rewiring of grass flowering time pathways and implications for crop improvement under climate change.The New phytologist · 2025Review
- Assisted Gene Flow Management to Climate Change in the Annual LegumeEvolutionary applications · 2025Article
- Genome wide association analysis for biomass related traits in common vetch (Frontiers in plant science · 2025Article
- Computational Identification of Milk Trait Regulation Through Transcription Factor Cooperation in Murciano-Granadina Goats.Biology · 2024Article
- Investigating the genetic control of plant development in spring barley under speed breeding conditions.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Unlocking the genetic diversity and population structure of the newly introduced two-row spring European HerItage Barley collecTion (ExHIBiT).Frontiers in plant science · 2024Article
- Dynamics of apex and leaf development in barley as affected byFrontiers in plant science · 2024Article
- Identification of Quantitative Trait Loci Associated with Powdery Mildew Resistance in Spring Barley under Conditions of Southeastern Kazakhstan.Plants (Basel, Switzerland) · 2023Article
- New semi-dwarfing alleles with increased coleoptile length by gene editing of gibberellin 3-oxidase 1 using CRISPR-Cas9 in barley (Hordeum vulgare L.).Plant biotechnology journal · 2023Article
- Compressed variance component mixed model reveals epistasis associated with flowering inFrontiers in plant science · 2023Article
- Genome architecture and diverged selection shaping pattern of genomic differentiation in wild barley.Plant biotechnology journal · 2023Article
- Pleiotropy Structures Plant Height and Seed Weight Scaling in Barley despite Long History of Domestication and Breeding Selection.Plant phenomics (Washington, D.C.) · 2023Article
- Genome-wide association study of agronomical and root-related traits in spring barley collection grown under field conditions.Frontiers in plant science · 2023Article
- Population origin determines the adaptive potential for the advancement of flowering onset inEvolutionary applications · 2023Article
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9 authors.
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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.
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