GWAS and Coexpression Network Combination Uncovers Effect Loci in the Accumulation of Glucosinolates Content in Brassica napus
LIU Wei1, YAO Ming1, KANG Yu1, WANG Mei1, XIE Pan1, HE Xin1, LIU Zhong-Song1, GUAN Chun-Yun1, QIAN Wei3, HUA Wei2, QIAN Lun-Wen1,*
1 Collaborative Innovation Center of Grain and Oil Crops in South China, Hunan Agricultural University, Changsha 410128, China; 2 Key Laboratory for Biological Sciences of Oil Crops Ministry of Agriculture/Oil Crops Research Institute, Chinese Academy of Agriculture Sciences, Wuhan 430062, China; 3 College of Agronomy and Biotechnology, Southwest University, Chongqing 400716, China
Abstract:Reducing the content of seed glucosinolates (GSL) has a positive impact on the seed quality of Brassica napus. In this study, genome-wide association study (GWAS) of seed GSL content was performed by using the 60K Brassica infinium single nucleotide polymorphism (SNP) array in 203 oilseed rape accessions. A total of 20 SNPs were detected significant associated with GSL content and located on the A02, A03, A09, C03, C08, and C09 chromosomes. A linkage disequilibrium analysis was performed on flanking sequence of these significantly associated SNP loci, and a haplotype region (57830409~58283210 bp; r2 = 0.96) was detected significantly associated with GSL content on the C03 chromosome. This haplotype region carrying an orthologues of Arabidopsis gene BCAT4 (branched-chain aminotransferase 4) was involved in GSL biosynthesis process. Based on the above results, regional association analysis revealed BnBCAT4-C03(BnaC03g68450D) gene region structural variation effected the accumulation of GSL in this haplotype region by genome-wide resequencing data of 50 accessions. Meanwhile,co-expression network analysis suggested BnBCAT4-C03 gene relationship with genes in the pathway of glucosinolates synthesis that formed molecular networks regulation in the synthesis and accumulation of GSL content. Our results would be benefit for the development of haplotype functional markers to further reduce GSL content in rapeseed.
刘蔚, 姚敏, 康郁, 王美, 解盼, 何昕, 刘忠松, 官春云, 钱伟, 华玮, 钱论文. GWAS结合共表达网络分析挖掘影响油菜种子硫苷积累的作用位点[J]. 农业生物技术学报, 2019, 27(10): 1729-1741.
LIU Wei, YAO Ming, KANG Yu, WANG Mei, XIE Pan, HE Xin, LIU Zhong-Song, GUAN Chun-Yun, QIAN Wei, HUA Wei, QIAN Lun-Wen. GWAS and Coexpression Network Combination Uncovers Effect Loci in the Accumulation of Glucosinolates Content in Brassica napus. 农业生物技术学报, 2019, 27(10): 1729-1741.
1 程坤, 杨丽梅, 方智远, 等. 2010. 十字花科植物中主要硫代葡萄糖苷合成与调节基因的研究进展[J]. 中国蔬菜, 1(12): 1-6.).(Cheng K, Yang L M, Fang Z Y, et al. 2010. Research progress on regulation and synthesis genes on glucosinolates biosynthesis in Crucifer [J]. Chinese vegetables, 1(12): 1-6.) 2 荐红举, 魏丽娟, 李加纳, 等. 2014. 利用SNP高密度遗传连锁图谱定位甘蓝型油菜种子硫苷含量的QTL[J]. 作物学报, (8): 1386-1391. (Jian HJ, Wei L J, Li G N, et al. 2014. Mapping quantitative traits loci for seed glucosinolate content in Brassica napus# using high-density SNP map [J]. Acta Agronomica Sinica, (8): 1386-1391.) 3 王月, 朱宝, 蒋金金, 等. 2015. 菜籽饼粕饲用价值及其品质改良的研究进展[J]. 分子植物育种, 13(04): 929-936. (Wang Y, Zhu B, Jiang J J, Wang Y P.2015. An review on feeding value and quality improvement of rapeseed meal[J]. Molecular Plant Breeding, 13(04): 929-936.) 4 杨宇昕, 桑志勤, 许诚, 等. 2019. 利用 WGCNA 进行玉米花期基因共表达模块鉴定[J]. 作物学报, 45(2): 161-174. (Yang Y X, Sang Z Q, Xu C, et al.2019. Identification of maize flowering gene co-expression modules by WGCNA[J]. Acta Agronomica Sinica, 45(2): 161-174.) 5 Aulchenko Y S, Ripke S, Isaacs A, et al.2007. GenABEL: An R library for genome-wide association analysis[J]. Bioinformatics, 23: 1294-1296. 6 Bradbury P J, Zhang Z, Kroon D E, et al.2007. TASSEL: Software for association mapping of complex traits in diverse samples[J]. Bioinformatics, 23(19): 2633-2635. 7 Fang C, Ma Y, Wu S, et al.2017. Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean[J]. Genome Biology, 18(1): 161. 8 Fu Y L, Lu K, Qian L W, et al.2015. Development of genic cleavage markers in association with seed glucosinolate content in canola[J]. Theoretical and Applied Genetics, 128(6): 1029-1037. 9 Gigolashvili T, Yatusevich R, Berger B, et al.2010. The R2R3-MYB transcription factor HAG1/MYB28 is a regulator of methionine-derived glucosinolate biosynthesis in Arabidopsis thaliana[J]. Plant Journal for Cell & Molecular Biology, 51(2): 247-261. 10 Gigolashvili T, Yatusevich R, Rollwitz I, et al.2009. The plastidic bile acid transporter 5 is required for the biosynthesis of methionine-derived glucosinolates in Arabidopsis thaliana[J]. Plant Cell, 21(6): 1813-1829. 11 Harper A L, Trick M, Higgins J, et al.2012. Associative transcriptomics of traits in the polyploid crop species Brassica napus[J]. Nature Biotechnology, 30(8): 798-802. 12 Harrell F E.[2019-01-27]. Package 'Hmisc'[EB/OL]. https://cran.r-project.org/web/packages/Hmisc/Hmisc.pdf 13 Howell P M, Sharpe A G, Lydiate D J, et al.2003. Homoeologous loci control the accumulation of seed glucosinolates in oilseed rape[J]. Genome, 46: 454-460. 14 Hull A K, Vij R, Celenza J L.2000. Arabidopsis cytochrome P450s that catalyze the first step of tryptophan-dependent indole-3-acetic acid biosynthesis[J]. Proceedings of the National Academy of Sciences of the USA, 97(5): 2379-2384. 15 Kroymann J, Textor S, Tokuhisa JG, et al.2001. A gene controlling variation in Arabidopsis glucosinolate composition is part of the methionine chain elongation pathway[J]. Plant Physiology, 127(3): 1077-1088. 16 Langfelder P, Horvath S.2008. WGCNA: An R package for weighted correlation network analysis[J]. BMC Bioinformatics, 9: 559. 17 Li F, Chen B, Xu K, et al.2014. Genome-wide association sudy dissects the genetic architecture of seed weight and seed quality in rapeseed[J]. DNA Research, 21(4): 355-367. 18 Lu G, Harper A L, Trick M, et al.2014. Associative transcriptomics study dissects the genetic architecture of sgeed glucosinolate content in Brassica napus[J]. DNA research, 21(6): 613-25. 19 Mithen R.2001. Glucosinolates-biochemistry, genetics and biological activity[J]. Plant Growth Regulation, 34: 91-103. 20 Qian L W, Qian W, Snowdon R J.2014. Sub-genomic selection patterns as a signature of breeding in the allopolyploid Brassica napus genome[J]. BMC Genomics, 15(1):1170. 21 Qian L W, Qian W, Snowdon R J.2016. Haplotype hitchhiking promotes trait coselection in Brassica napus[J]. Plant Biotechnology Journal, 14(7): 1578-1588. 22 Qu C M, Li S M, Duan X J, et al.2015. Identification of candidate genes for seed glucosinolate content using association mapping in Brassica napus L[J]. Genes, 6(4): 1215-1229. 23 Revelle W R.[2019-01-13]. Package 'psych'[EB/OL].https://cran.r-project.org/web/packages/psych/psych.pdf 24 Schuster J, Knill T, Reichelt M, et al.2006. BRANCHED-CHAN AMINOTRANSFERASE4 is part of the chain elongation pathway in the biosynthesis of methionine-derived glucosinolates in Arabidopsis[J]. Plant Cell, 18(10): 2664-2679. 25 Smoot M E, Ono K, Ruscheinski J, et al.2011. Cytoscape 2.8: New features for data integration and network visualization[J]. Bioinformatics, 27(3): 431-432. 26 Turner S D.[2014-05-24]. QQman: An R package for visualizing GWAS results using QQ and manhattan plots[J/OL]. BioRxiv, DOI:10.1101/005165. 27 Zhang J, Yang Y, Zheng K, et al.2018. Genome-wide association studies and expression-based quantitative trait loci analyses reveal roles of HCT2 in caffeoylquinic acid biosynthesis and its regulation by defense-responsive transcription factors in Populus[J]. New Phytologist, 220(2): 502-516. 28 Zhao J, Meng J.2010. Detection of loci controlling seed glucosinolate content and their association with Sclerotinia resistance in Brassica napus[J]. Plant Breeding, 122(1): 19-23.