Systematic trait dissection in oilseed rape provides a comprehensive view, further insight, and exact roadmap for yield determination

Author:

Liang Huabing,Ye Jiang,Wang Ying,Wang Xinfa,Zhou Xue-Rong,Batley Jacqueline,King Graham J.,Guo Liang,Tu Jinxing,Shi Jiaqin,Wang Hanzhong

Abstract

Abstract Background Yield is the most important and complex trait that is influenced by numerous relevant traits with very complicated interrelations. While there are a large number of studies on the phenotypic relationship and genetic basis of yield traits, systematic studies with further dissection focusing on yield are limited. Therefore, there is still lack of a comprehensive and in-depth understanding of the determination of yield. Results In this study, yield was systematically dissected at the phenotypic, genetic to molecular levels in oilseed rape (Brassica napus L.). The analysis of correlation, network, and principal component for 21 traits in BnaZN-RIL population showed that yield was determined by a complex trait network with key contributors. The analysis of the constructed high-density single nucleotide polymorphism (SNP) linkage map revealed the concentrated distribution of distorted and heterozygous markers, likely due to selection on genes controlling the growth period and yield heterosis. A total of 134 consensus quantitative trait loci (QTL) were identified for 21 traits, of which all were incorporated into an interconnecting QTL network with dozens of hub-QTL. Four representative hub-QTL were further dissected to the target or candidate genes that governed the causal relationships between the relevant traits. Conclusions The highly consistent results at the phenotypic, genetic, and molecular dissecting demonstrated that yield was determined by a multilayer composite network that involved numerous traits and genes showing complex up/down-stream and positive/negative regulation. This provides a systematic view, further insight, and exact roadmap for yield determination, which represents a significant advance toward the understanding and dissection of complex traits.

Funder

Agricultural Science and Technology Innovation Program of China

Agricultural Science and Technology Innovation Project of China

Fundamental Research Funds for Central Non-Profit Institute of Crop Sciences, CAAS

Natural Science Foundation of China

Agriculture Research System of MOF and MARA of China

Publisher

Springer Science and Business Media LLC

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