Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

Keqi Li; Jie Wang; Lieqiong Kuang; Ze Tian; Xinfa Wang; Xiaoling Dun; Jinxing Tu; Hanzhong Wang

doi:10.1186/s13068-021-02032-7

Genome-wide association study and transcriptome analysis reveal key genes affecting root growth dynamics in rapeseed

Biotechnol Biofuels. 2021 Sep 10;14(1):178. doi: 10.1186/s13068-021-02032-7.

Authors

Keqi Li^#^{1

2}, Jie Wang^#¹, Lieqiong Kuang¹, Ze Tian¹, Xinfa Wang¹, Xiaoling Dun³, Jinxing Tu², Hanzhong Wang¹

Affiliations

¹ Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062, China.
² National Key Laboratory of Crop Genetic Improvement, Huazhong Agricultural University, Wuhan, 430062, China.
³ Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture, Wuhan, 430062, China. dunxiaoling@caas.cn.

^# Contributed equally.

Abstract

Background: In terms of global demand, rapeseed is the third-largest oilseed crop after soybeans and palm, which produces vegetable oil for human consumption and biofuel for industrial production. Roots are vital organs for plant to absorb water and attain mineral nutrients, thus they are of great importance to plant productivity. However, the genetic mechanisms regulating root development in rapeseed remain unclear. In the present study, seven root-related traits and shoot biomass traits in 280 Brassica napus accessions at five continuous vegetative stages were measured to establish the genetic basis of root growth in rapeseed.

Results: The persistent and stage-specific genetic mechanisms were revealed by root dynamic analysis. Sixteen persistent and 32 stage-specific quantitative trait loci (QTL) clusters were identified through genome-wide association study (GWAS). Root samples with contrasting (slow and fast) growth rates throughout the investigated stages and those with obvious stage-specific changes in growth rates were subjected to transcriptome analysis. A total of 367 differentially expressed genes (DEGs) with persistent differential expressions throughout root development were identified, and these DEGs were significantly enriched in GO terms, such as energy metabolism and response to biotic or abiotic stress. Totally, 485 stage-specific DEGs with different expressions at specific stage were identified, and these DEGs were enriched in GO terms, such as nitrogen metabolism. Four candidate genes were identified as key persistent genetic factors and eight as stage-specific ones by integrating GWAS, weighted gene co-expression network analysis (WGCNA), and differential expression analysis. These candidate genes were speculated to regulate root system development, and they were less than 100 kb away from peak SNPs of QTL clusters. The homologs of three genes (BnaA03g52990D, BnaA06g37280D, and BnaA09g07580D) out of 12 candidate genes have been reported to regulate root development in previous studies.

Conclusions: Sixteen QTL clusters and four candidate genes controlling persistently root development, and 32 QTL clusters and eight candidate genes stage-specifically regulating root growth in rapeseed were detected in this study. Our results provide new insights into the temporal genetic mechanisms of root growth by identifying key candidate QTL/genes in rapeseed.

Keywords: GWAS; Persistent; Rapeseed; Root growth; Stage-specific; WGCNA.

Abstract

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