ArticlePlant biotechnology journal2020
Phenomics-based GWAS analysis reveals the genetic architecture for drought resistance in cotton.
Article in Plant biotechnology journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed, 96 citations in OpenAlex.
- Integrating high-throughput phenomics and GWAS unravels the HaCBF4-Horticulture research · 2026Article
- Identification of candidate genes regulating seed oil and protein content in Brassica napus via integrated genome-wide association and transcriptome analysis.BMC plant biology · 2026Article
- Multi-locus GWAS uncovers favorable alleles and candidate genes underlying water stress response in chrysanthemum.BMC plant biology · 2026Article
- Dissecting the genetic architecture of seed-related traits in Brassica napus by integrating multi-omics analysis and VIS-NIR hyperspectral imaging.Genome biology · 2026Article
- Genome-wide association study bridging genomics-phenomics gap in natural plant populations.Journal of applied genetics · 2026Review
- Excavation and effect analysis of interaction sites between upland cotton yield and fiber quality traits and environmental factors.BMC plant biology · 2026Article
- Development of a Liquid-Phased Probe Array for Upland Cotton and Its Application in Cultivar Identification.Genes · 2025Article
- Establishment of a high-throughput field defoliation data survey strategy combined with genome-wide association studies to reveal the genetic basis of defoliation in cotton.Plant phenomics (Washington, D.C.) · 2025Article
- Integrated GWAS and Transcriptome Analysis Reveal the Genetic and Molecular Basis of Low Nitrogen Tolerance in Maize Seedlings.Plants (Basel, Switzerland) · 2025Article
- Review
- GWAS and GS analysis revealed the selection and prediction efficiency for yield, plant morphological, and fiber quality in Gossypium barbadense.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Profile of Dr. Zhang Xianlong.Science China. Life sciences · 2025Article
- Drought stress responses deconstructed: A comprehensive approach for Norway spruce seedlings using high-throughput phenotyping with integrated metabolomics and transcriptomics.Plant phenomics (Washington, D.C.) · 2025Article
- A system genetics analysis uncovers the regulatory variants controlling drought response in wheat.Plant biotechnology journal · 2025Article
- A genome-wide association study reveals the genetic architecture of 19 agronomic traits in broomcorn millet (Panicum miliaceum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Article
- Phenomics-assisted genetic dissection and molecular design of drought resistance in rice.Plant communications · 2025Article
- RGB imaging-based evaluation of waterlogging tolerance in cultivated and wild chrysanthemums.Plant phenomics (Washington, D.C.) · 2025Article
- Combining UAV multisensor field phenotyping and genome-wide association studies to reveal the genetic basis of plant height in cotton (Plant phenomics (Washington, D.C.) · 2025Article
- CSGDN: contrastive signed graph diffusion network for predicting crop gene-phenotype associations.Briefings in bioinformatics · 2024Article
- Identification of QTNs and Their Candidate Genes for Boll Number and Boll Weight in Upland Cotton.Genes · 2024Article
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
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Abstract
Drought resistance (DR) is a complex trait that is regulated by a variety of genes. Without comprehensive profiling of DR-related traits, the knowledge of the genetic architecture for DR in cotton remains limited. Thus, there is a need to bridge the gap between genomics and phenomics. In this study, an automatic phenotyping platform (APP) was systematically applied to examine 119 image-based digital traits (i-traits) during drought stress at the seedling stage, across a natural population of 200 representative upland cotton accessions. Some novel i-traits, as well as some traditional i-traits, were used to evaluate the DR in cotton. The phenomics data allowed us to identify 390 genetic loci by genome-wide association study (GWAS) using 56 morphological and 63 texture i-traits. DR-related genes, including GhRD2, GhNAC4, GhHAT22 and GhDREB2, were identified as candidate genes by some digital traits. Further analysis of candidate genes showed that Gh_A04G0377 and Gh_A04G0378 functioned as negative regulators for cotton drought response. Based on the combined digital phenotyping, GWAS analysis and transcriptome data, we conclude that the phenomics dataset provides an excellent resource to characterize key genetic loci with an unprecedented resolution which can inform future genome-based breeding for improved DR in cotton.
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