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Genetic basis and network underlying synergistic roots and shoots biomass accumulation revealed by genome-wide association studies in rice

文献类型： 外文期刊

作者： Zhao, Yan 1 ; Yin, Zhigang 1 ; Wang, Xueqiang 1 ; Jiang, Conghui 1 ; Aslam, Muhammad Mahran 1 ; Gao, Fenghua 1 ; Pan, 1 ;

作者机构： 1.State Key Lab Agrobiotechnol Beijing Key Lab Crop, China Agr Univ, Coll Agron & Biotechnol, Beijing 100193, Peoples R China

2.Shandong Agr Univ, State Key Lab Crop Biol, Shandong Key Lab Crop Biol, Coll Agron, Tai An 271018, Shandong, Peoples R China

3.Rice Res Inst Guangxi Acad Agr Sci, Guangxi Key Lab Rice Genet & Breeding, Nanning 530007, Peoples R China

期刊名称：SCIENTIFIC REPORTS （ 影响因子：4.38； 五年影响因子：5.134 ）

ISSN： 2045-2322

年卷期： 2021 年 11 卷 1 期

页码：

收录情况： SCI

摘要： 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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