Identify QTLs and candidate genes underlying source-, sink-, and grain yield-related traits in rice by integrated analysis of bi-parental and natural populations

Yun Wang; Junmin Wang; Laiyuan Zhai; Chengwei Liang; Kai Chen; Jianlong Xu

doi:10.1371/journal.pone.0237774

Identify QTLs and candidate genes underlying source-, sink-, and grain yield-related traits in rice by integrated analysis of bi-parental and natural populations

PLoS One. 2020 Aug 14;15(8):e0237774. doi: 10.1371/journal.pone.0237774. eCollection 2020.

Authors

Yun Wang¹, Junmin Wang², Laiyuan Zhai^{1

3}, Chengwei Liang¹, Kai Chen⁴, Jianlong Xu^{3

4}

Affiliations

¹ Rice Research Institute, Shenyang Agricultural University, Shenyang, Liaoning, China.
² The Institute of Crops and Nuclear Technology Utilization, Zhejiang Academy of Agricultural Sciences, Hangzhou, Zhejiang, China.
³ Institute of Crop Sciences/National Key Facility for Crop Gene Resources and Genetic Improvement, Chinese Academy of Agricultural Sciences, Beijing, China.
⁴ Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong, China.

Abstract

The source-sink relationship determines the ultimate grain yield of rice. In this study, we used a set of reciprocal introgression lines (ILs) derived from Xuishui09 × IR2061 to map quantitative trait loci (QTLs) that were associated with sink-, source-, and grain yield-related traits. A total of 95 QTLs influencing eight measured traits were identified using 6181 high-quality single nucleotide polymorphism markers. Nine background-independent QTLs were consistently detected in seven chromosomal regions in different genetic backgrounds. Seven QTLs clusters simultaneously affected sink-, source-, and grain yield-related traits, probably due to the genetic basis of significant correlations of grain yield with source and sink traits. We selected 15 candidate genes in the four QTLs consistently identified in the two populations by performing gene-based association and haplotype analyses using 2288 accessions from the 3K project. Among these, LOC_Os03g48970 for qTSN3b, LOC_Os06g04710 for qFLL6a, and LOC_Os07g32510 for qTGW7 were considered as the most likely candidate genes based on functional annotations. These results provide a basis for further study of candidate genes and for the development of high-yield rice varieties by balancing source-sink relationships using marker-assisted selection.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Chromosomes, Plant / genetics
Edible Grain / genetics*
Edible Grain / growth & development
Genes, Plant
Oryza / genetics*
Oryza / growth & development
Polymorphism, Single Nucleotide
Quantitative Trait Loci*

Grants and funding

This work was funded by the National Key R&D Program of China to KC (grant no. 2017YFD0100100), the National Key R&D Program of China to JX (grant no. 2016YFD0100301), the 863 Key Project from the Chinese Ministry of Science & Technology to JX (grant no. 2014AA10A601), the National Natural Science Foundation of China to YW (grant no. 31671602) and the Agricultural Science and Technology Innovation Program and the Cooperation and Innovation Mission to JX (grant no. CAAS-ZDXT202001). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.