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Updated: Aug 11, 2026
Phloem Sap Sampling from Brassica napus for 3D-PAGE of Protein and Ribonucleoprotein Complexes
Published on: January 9, 2018
Integrating genome-wide association study with transcriptomic data to predict candidate genes influencing Brassica
Nazir Ahmad1, Sani Ibrahim1,2, Lieqiong Kuang1
1Oil Crops Research Institute of the Chinese Academy of Agricultural Sciences/Key Laboratory of Biology and Genetic Improvement of Oil Crops, Ministry of Agriculture and Rural Affairs, Wuhan, 430062, China.
Background:
Rapeseed (Brassica napus L.) is an essential source of edible oil and livestock feed, as well as a promising source of biofuel. Breeding crops with an ideal root system architecture (RSA) for high phosphorus use efficiency (PUE) is an effective way to reduce the use of phosphate fertilizers. However, the genetic mechanisms that underpin PUE in rapeseed remain elusive. To address this, we conducted a genome-wide association study (GWAS) in 327 rapeseed accessions to elucidate the genetic variability of 13 root and biomass traits under low phosphorus (LP; 0.01 mM P +). Furthermore, RNA-sequencing was performed in root among high/low phosphorus efficient groups (HP1/LP1) and high/low phosphorus stress tolerance groups (HP2/LP2) at two-time points under control and P-stress conditions.
Results:
Significant variations were observed in all measured traits, with heritabilities ranging from 0.47 to 0.72, and significant correlations were found between most of the traits. There were 39 significant trait-SNP associations and 31 suggestive associations, which integrated into 11 valid quantitative trait loci (QTL) clusters, explaining 4.24-24.43% of the phenotypic variance observed. In total, RNA-seq identified 692, 1076, 648, and 934 differentially expressed genes (DEGs) specific to HP1/LP1 and HP2/LP2 under P-stress and control conditions, respectively, while 761 and 860 DEGs common for HP1/LP1 and HP2/LP2 under both conditions. An integrated approach of GWAS, weighted co-expression network, and differential expression analysis identified 12 genes associated with root growth and development under LP stress. In this study, six genes (BnaA04g23490D, BnaA09g08440D, BnaA09g04320D, BnaA09g04350D, BnaA09g04930D, BnaA09g09290D) that showed differential expression were identified as promising candidate genes for the target traits.
Conclusion:
11 QTL clusters and 12 candidate genes associated with root and development under LP stress were identified in this study. Our study's phenotypic and genetic information may be exploited for genetic improvement of root traits to increase PUE in rapeseed.
