Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions in combination with co-expression analysis reveal candidate genes affecting oil accumulation in Brassica napus.
One of the breeding goals in rapeseed production is to enhance the seed oil content to cater to the increased demand for vegetable oils due to a growing global population. To investigate the genetic basis of variation in seed oil content, we used 60 K Brassica Infinium SNP array along with phenotype data of 203 Chinese semi-winter rapeseed accessions to perform a genome-wide analysis of haplotype blocks associated with the oil content. Nine haplotype regions harbouring lipid synthesis/transport-, carbohydrate metabolism- and photosynthesis-related genes were identified as significantly associated with the oil content and were mapped to chromosomes A02, A04, A05, A07, C03, C04, C05, C08 and C09, respectively. Regional association analysis of 50 re-sequenced Chinese semi-winter rapeseed accessions combined with transcriptome datasets from 13 accessions was further performed on these nine haplotype regions. This revealed natural variation in the BnTGD3-A02 and BnSSE1-A05 gene regions correlated with the phenotypic variation of the oil content within the A02 and A04 chromosome haplotype regions, respectively. Moreover, co-expression network analysis revealed that BnTGD3-A02 and BnSSE1-A05 were directly linked with fatty acid beta-oxidation-related gene BnKAT2-C04, thus forming a molecular network involved in the potential regulation of seed oil accumulation. The results of this study could be used to combine favourable haplotype alleles for further improvement of the seed oil content in rapeseed.
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Arai Y, Nakashita H, Suzuki Y et al (2002) Synthesis of a novel class of polyhydroxyalkanoates in Arabidopsis peroxisomes, and their use in monitoring short-chain-length intermediates of beta-oxidation. Plant Cell Physiol 43:555–562
Anders S, Pyl PT, Huber W (2015) HTSeq-a python framework to work with high-throughput sequencing data. Bioinformatics 31:166–169
Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc B 57:289–300
Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120
Bradbury PJ, Zhang Z, Kroon DE, Casstevens TM, Ramdoss Y, Buckler ES (2007) TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics 23:2633–2635
Browning BL, Browning SR (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 84:210–223
Chalhoub B, Denoeud F, Liu S et al (2014) Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science 345:950–9533
Chao H, Wang H, Wang X et al (2017) Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus. Sci Rep 7:46295
Chen G, Woodfield H, Pan X, Harwood J, Weselake R (2015) Acyl-trafficking during plant oil accumulation. Lipids 50:1057–1068
Collard BC, Mackill DJ (2008) Marker-assisted selection: an approach for precision plant breeding in the twenty-first century. Philos Trans R Soc Lond B Biol Sci 363:557–572
Cui P, Lin Q, Fang D et al (2018) Tung Tree (Vernicia fordii, Hemsl.) Genome and transcriptome sequencing reveals co-ordinate up-regulation of fatty acid β-oxidation and triacylglycerol biosynthesis pathways during eleostearic acid accumulation in seeds. Plant Cell Physiol 59:1990–2003
Delourme R, Falentin C, Huteau V, Clouet V, Horvais R, Gandon B, Specel S, Hanneton L, Dheu JE, Deschamps M, Margale E, Vincourt P, Renard M (2006) Genetic control of oil content in oilseed rape (Brassica napus L.). Theor Appl Genet 113:1331–1345
Dong H, Tan C, Li Y et al (2018) Genome-wide association study reveals both overlapping and independent genetic loci to control seed weight and silique length in Brassica napus. Front Plant Sci 9:921
Edwards D, Batley J, Snowdon RJ (2013) Accessing complex crop genomes with next-generation sequencing. Theor Appl Genet 126:1–11
Ekman A, Hayden DM, Dehesh K, Bülow L, Stymne S (2008) Carbon partitioning between oil and carbohydrates in developing oat (Avena sativa L.) seeds. J Exp Bot 59:4247–4257
Focks N, Benning C (1998) wrinkled1: a novel, low-seed-oil mutant of Arabidopsis with a deficiency in the seed-specific regulation of carbohydrate metabolism. Plant Physiol 118:91–101
Germain V, Rylott EL, Larson TR et al (2001) Requirement for 3-ketoacyl-CoA thiolase-2 in peroxisome development, fatty acid beta-oxidation and breakdown of triacylglycerol in lipid bodies of Arabidopsis seedlings. Plant J 28:1–12
Graham IA, Eastmond PJ (2002) Pathways of straight and branched chain fatty acid catabolism in higher plants. Prog Lipid Res 41:156–181
Hardy OJ, Vekemans X (2002) Spagedi: a versatile computer program to analyze spatial genetic structure at the individual or population levels. Mol Ecol Notes 2:618–620
Harrell FE with contributions from Charles Dupont and many others (2019) Hmisc: Harrell Miscellaneous. R package version 4.2–0. https://CRAN.R-project.org/package=Hmisc
Hayashi M, Toriyama K, Kondo M, Nishimura M (1998) 2,4-Dichlorophenoxybutyric acid-resistant mutants of Arabidopsis have defects in glyoxysomal fatty acid beta-oxidation. Plant Cell 10:183–195
Hua W, Li RJ, Zhan GM, Liu J, Li J, Wang XF, Liu GH, Wang HZ (2012) Maternal control of seed oil content in Brassica napus: the role of silique wall photosynthesis. Plant J 69:432–444
Jiang C, Shi J, Li R, Long Y, Wang H, Li D, Zhao J, Meng J (2014) Quantitative trait loci that control the oil content variation of rapeseed (Brassica napus L.). Theor Appl Genet 127:957–968
Kim D, Langmead B, Salzberg SL (2015) HISAT: a fast spliced aligner with low memory requirements. Nat Methods 12:357–360
Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559
Le T, Lee I (2018) araGWAB: Network-based boosting of genome-wide association studies in Arabidopsis thaliana. Sci Rep 8:2925
Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25:1754–1760
Lin Y, Cluette-Brown JE, Goodman HM (2004) The peroxisome deficient Arabidopsis mutant sse1 exhibits impaired fatty acid synthesis. Plant Physiol 135:814–827
Lin Y, Ulanov AV, Lozovaya V, Widholm J, Zhang G, Guo J, Goodman HM (2006) Genetic and transgenic perturbations of carbon reserve production in Arabidopsis seeds reveal metabolic interactions of biochemical pathways. Planta 225:153–164
Liu S, Fan C, Li J, Cai G, Yang Q, Wu J, Yi X, Zhang C, Zhou Y (2016) A genome-wide association study reveals novel elite allelic variations in seed oil content of Brassica napus. Theor Appl Genet 129:1203–1215
Lu B, Xu C, Awai K, Jones AD, Benning C (2007) A small ATPase protein of Arabidopsis, TGD3, involved in chloroplast lipid import. J Biol Chem 282:35945–35953
Lu K, Peng L, Zhang C et al (2017) Genome-wide association and transcriptome analyses reveal candidate genes underlying yield-determining traits in Brassica napus. Front Plant Sci 8:206
Lu K, Wei L, Li X et al (2019) Whole-genome resequencing reveals Brassica napus origin and genetic loci involved in its improvement. Nat Commun 10:1154
Lv Y, Guo Z, Li X et al (2016) New insights into the genetic basis of natural chilling and coldshock tolerance in rice by genome-wide association analysis. Plant Cell Environ 39:556–570
Mendes A, Kelly AA, van Erp H, Shaw E, Powers SJ, Kurup S, Eastmond PJ (2013) bZIP67 regulates the omega-3 fatty acid content of Arabidopsis seed oil by activating fatty acid desaturase3. Plant Cell 25:3104–3116
Niu Y, Wu GZ, Ye R, Lin WH, Shi QM, Xue LJ, Xu XD, Li Y, Du YG, Xue HW (2009) Global analysis of gene expression profiles in Brassica napus developing seeds reveals a conserved lipid metabolism regulation with Arabidopsis thaliana. Mol Plant 2:1107–1122
Piepho HP, Buchse A, Emrich K (2003) A hitchhiker’s guide to mixed models for randomized experiments. J Agron Crop Sci 189:310–322
Qian L, Qian W, Snowdon RJ (2014) Sub-genomic selection patterns as a signature of breeding in the allopolyploid Brassica napus genome. BMC Genomics 15:1170
Revelle W (2018) psych: procedures for psychological, psychometric, and personality research. Northwestern University. Evanston, Illinois, USA. https://CRAN.R-project.org/package=psych
Santos-Mendoza M, Dubreucq B, Baud S, Parcy F, Caboche M, Lepiniec L (2008) Deciphering gene regulatory networks that control seed development and maturation in Arabidopsis. Plant J 54:608–620
Shin JH, Blay S, McNeney B, Graham J (2006) LDheatmap: an R function for graphical display of pairwise linkage disequilibria between single nucleotide polymorphisms. J Stat Soft 16:1–10
Si P, Mailer RJ, Galwey N, Turner DW (2003) Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Aust J Agric Res 54:397–407
Shannon P, Markiel A, Ozier O et al (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13:2498–2504
Song J, Guan Z, Hu J et al (2020) Eight high-quality genomes reveal pan-genome architecture and ecotype differentiation of Brassica napus. Nat Plants 6:34–45
Sterken R, Kiekens R, Boruc J, Zhang F, Vercauteren A, Vercauteren I, De Smet L, Dhondt S, Inzé D, De Veylder L, Russinova E, Vuylsteke M (2012) Combined linkage and association mapping reveals CYCD5;1 as a quantitative trait gene for endoreduplication in Arabidopsis. Proc Natl Acad Sci USA 109:4678–4683
Strimmer K (2008) fdrtool: a versatile R package for estimating local and tail area-based false discovery rates. Bioinformatics 24:1461–1462
Sun M, Hua W, Liu J, Huang S, Wang X, Liu G, Wang H (2012) Design of new genome-and gene-sourced primers and identification of QTL for seed oil content in a specially high-oil Brassica napus cultivar. PLoS ONE 7:e47037
Tang MQ, Zhang YY, Liu YY, Tong CB, Cheng XH, Zhu W, Li ZY, Huang JY, Liu SY (2019) Mapping loci controlling fatty acid profiles and oil and protein content by genome-wide association study in Brassica napus. The Crop J 7:217–226
Teh L, Möllers C (2016) Genetic variation and inheritance of phytosterol and oil content in a doubled haploid population derived from the winter oilseed rape Sansibar × Oase cross. Theor Appl Genet 129:181–199
Turner SD (2018) QQman: an R package for visualizing GWAS results using Q-Q and manhattan plots. J Open Source Software 3:731
Uzunova M, Ecke W, Weissleder K, Robbelen G (1995) Mapping the genome of rapeseed (Brassica napus L.). I. Construction of an RFLP linkage map and localization of QTLs for seed glucosinolate content. Theor Appl Genet 90:194–204
Voss-Fels K, Snowdon RJ (2016) Understanding and utilizing crop genome diversity via high-resolution genotyping. Plant Biotechnol J 14:1086–1094
Wang HZ (2004) Strategy for rapeseed genetic improvement in China in the coming fifteen years. Chin J Oil Crop Sci 26:98–101
Wang H, Liu J, Hua W (2016) Molecular regulation and genetic improvement of seed oil content in Brassica napus L. Front Agr Sci Eng 3:186
Wang X, Wang H, Long Y et al (2013) Identification of QTLs associated with oil content in a high-oil Brassica napus cultivar and construction of a high-density consensus map for QTLs comparison in B. napus. PLoS ONE 8:e80569
Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer, New York
Wu D, Liang Z, Yan T et al (2019) Whole-genome resequencing of a worldwide collection of rapeseed accessions reveals the genetic basis of ecotype divergence. Mol plant 12:30–43
Xiao Z, Zhang C, Tang F et al (2019) Identification of candidate genes controlling oil content by combination of genome-wide association and transcriptome analysis in the oilseed crop Brassica napus. Biotechnol Biofuels 12:216
Yu J, Pressoir G, Briggs WH (2006) A unified mixed-model method for association mapping that accounts for multiple levels of relatedness. Nat Genet 38:203–208
Zhao J, Huang J, Chen F, Xu F, Ni X, Xu H, Wang Y, Jiang C, Wang H, Xu A, Huang R, Li D, Meng J (2012) Molecular mapping of Arabidopsis thaliana lipid-related orthologous genes in Brassica napus. Theor Appl Genet 124:407–421
Zhao JY, Becker HC, Zhang DQ, Zhang YF, Ecke W (2005) Oil content in a European Chinese rapeseed population: QTL with additive and epistatic effects and their genotype-environment interactions. Crop Sci 45:51–59
Zheng X, Levine D, Shen J, Gogarten S, Laurie C, Weir B (2012) A High-performance computing toolset for relatedness and principal component analysis of SNP data. Bioinformatics 28:3326–3328
This study was funded by the National Natural Science Foundation of China (grant no. 31801399), the National Basic Research and Development Programme (2015CB150206) and the National Key Research and Development Project (grant no. 2017YFD0101703).
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Communicated by Albrecht E. Melchinger.
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Yao, M., Guan, M., Yang, Q. et al. Regional association analysis coupled with transcriptome analyses reveal candidate genes affecting seed oil accumulation in Brassica napus. Theor Appl Genet 134, 1545–1555 (2021). https://doi.org/10.1007/s00122-021-03788-0