1. Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice
- Author
-
Yinghua Pan, Conghui Jiang, Jianyin Xie, Xiaoyang Zhu, Hongliang Zhang, Yanhe Liu, Muhammad Mahran Aslam, Xueqiang Wang, Yan Zhao, Fenghua Gao, Zichao Li, Luhao Dong, Zhigang Yin, and Jinjie Li
- Subjects
0106 biological sciences ,0301 basic medicine ,Genotype ,Genetic Linkage ,media_common.quotation_subject ,Science ,Quantitative Trait Loci ,Genome-wide association study ,Biology ,01 natural sciences ,Plant Roots ,Polymorphism, Single Nucleotide ,Competition (biology) ,Article ,03 medical and health sciences ,Pleiotropy ,Botany ,Genetics ,Biomass ,Allele ,Gene ,Alleles ,media_common ,Multidisciplinary ,food and beverages ,Oryza ,Genetic architecture ,Computational biology and bioinformatics ,Plant Breeding ,030104 developmental biology ,Shoot ,Trait ,Medicine ,Plant sciences ,Plant Shoots ,010606 plant biology & botany ,Genome-Wide Association Study - 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.
- Published
- 2021