ArticleScientific reports2021
Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice.
Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- Modern approaches and future prospects in lettuce breeding for controlled environment agriculture.Frontiers in plant science · 2026Review
- Root plasticity and xylem modifications drive drought resilience in okra [Frontiers in plant science · 2025Article
- Comprehensive mapping and modelling of the rice regulome landscape unveils the regulatory architecture underlying complex traits.Nature communications · 2024Article
- Genome- and Transcriptome-wide Association Studies to Discover Candidate Genes for Diverse Root Phenotypes in Cultivated Rice.Rice (New York, N.Y.) · 2023Article
- Genome-wide association study for biomass accumulation traits in soybean.Molecular breeding : new strategies in plant improvement · 2023Article
- Genetic architecture and candidate gene identification for grain size in bread wheat by GWAS.Frontiers in plant science · 2022Article
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14 authors.
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Abstract
Genetic basis and network studies underlying synergistic biomass accumulation of roots and shoots (SBA) are conducive for rational design of high-biomass rice breeding. In this study, association signals for root weight, shoot weight, and the ratio of root-to-shoot mass (R/S) were identified using 666 rice accessions by genome-wide association study, together with their sub-traits, root length, root thickness and shoot length. Most association signals for root weight and shoot weight did not show association with their sub-traits. Based on the results, we proposed a top-to-bottom model for SBA, i.e. root weight, shoot weight and R/S were determined by their highest priority in contributing to biomass in the regulatory pathway, followed by a lower priority pathway for their sub-traits. Owing to 37 enriched clusters with more than two association signals identified, the relationship among the six traits could be also involved in linkage and pleiotropy. Furthermore, a discrimination of pleiotropy and LD at sequencing level using the known gene OsPTR9 for root weight, R/S and root length was provided. The results of given moderate correlation between traits and their corresponding sub-traits, and moderate additive effects between a trait and the accumulation of excellent alleles corresponding to its sub-traits supported a bottom-to-top regulation model for SBA. This model depicted each lowest-order trait (root length, root thickness and shoot length) was determined by its own regulation loci, and competition among different traits, as well as the pleiotropy and LD. All above ensure the coordinated development of each trait and the accumulation of the total biomass, although the predominant genetic basis of SBA is still indistinguishable. The presentation of the above two models and evidence of this study shed light on dissecting the genetic architecture of SBA.
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