ArticlePlant biotechnology journal2023
Deciphering genetic basis of developmental and agronomic traits by integrating high-throughput optical phenotyping and genome-wide association studies in wheat.
Article in Plant biotechnology journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 44 citations in OpenAlex.
- Improving Nitrogen Use Efficiency in Wheat: Integrating Agronomic, Genomics, and Remote Sensing for Sustainable Production.Plant, cell & environment · 2026Review
- Genetic dissection of a key dynamic growth period QTL for source-sink-related traits and its breeding application potential in wheat.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026Article
- UNet-ECA-Bio: a biologically informed deep learning model for high-throughput micro-phenotyping of rice stem vascular bundles.Frontiers in plant science · 2026Article
- Genome-wide association mapping and candidate genes analysis of high-throughput image descriptors for wheat frost tolerance.Stress biology · 2025Article
- GPS: Harnessing data fusion strategies to improve the accuracy of machine learning-based genomic and phenotypic selection.Plant communications · 2025Article
- Review
- Chromatin loops gather targets of upstream regulators together for efficient gene transcription regulation during vernalization in wheat.Genome biology · 2024Article
- Genome-wide association study for seedling heat tolerance under two temperature conditions in bread wheat (Triticum aestivum L.).BMC plant biology · 2024Article
- Integrated VIS/NIR Spectrum and Genome-Wide Association Study for Genetic Dissection of Cellulose Crystallinity in Wheat Stems.International journal of molecular sciences · 2024Article
- Genome wide association and haplotype analyses for the crease depth trait in bread wheat (Frontiers in plant science · 2023Article
Corrections and comments
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Authors and funding
25 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dissecting the genetic basis of complex traits such as dynamic growth and yield potential is a major challenge in crops. Monitoring the growth throughout growing season in a large wheat population to uncover the temporal genetic controls for plant growth and yield-related traits has so far not been explored. In this study, a diverse wheat panel composed of 288 lines was monitored by a non-invasive and high-throughput phenotyping platform to collect growth traits from seedling to grain filling stage and their relationship with yield-related traits was further explored. Whole genome re-sequencing of the panel provided 12.64 million markers for a high-resolution genome-wide association analysis using 190 image-based traits and 17 agronomic traits. A total of 8327 marker-trait associations were detected and clustered into 1605 quantitative trait loci (QTLs) including a number of known genes or QTLs. We identified 277 pleiotropic QTLs controlling multiple traits at different growth stages which revealed temporal dynamics of QTLs action on plant development and yield production in wheat. A candidate gene related to plant growth that was detected by image traits was further validated. Particularly, our study demonstrated that the yield-related traits are largely predictable using models developed based on i-traits and provide possibility for high-throughput early selection, thus to accelerate breeding process. Our study explored the genetic architecture of growth and yield-related traits by combining high-throughput phenotyping and genotyping, which further unravelled the complex and stage-specific contributions of genetic loci to optimize growth and yield in wheat.
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