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Acta Agronomica Sinica ›› 2024, Vol. 50 ›› Issue (5): 1136-1146.doi: 10.3724/SP.J.1006.2024.34152

• CROP GENETICS & BREEDING·GERMPLASM RESOURCES·MOLECULAR GENETICS • Previous Articles     Next Articles

A combination of genome-wide association and transcriptome analysis reveal candidate genes affecting seed oil accumulation in Brassica napus

CAO Song(), YAO Min, REN Rui, JIA Yuan, XIANG Xing-Ru, LI Wen, HE Xin, LIU Zhong-Song, GUAN Chun-Yun, QIAN Lun-Wen*(), XIONG Xing-Hua*()   

  1. College of Agronomy, Hunan Agricultural University, Changsha 410128, Hunan, China
  • Received:2023-09-08 Accepted:2024-01-12 Online:2024-05-12 Published:2024-01-25
  • Contact: E-mail: xiongene@hunau.edu.cn; E-mail: qianlunwen@163.com
  • Supported by:
    Science Foundation for Distinguished Youth Scholars of Hunan Province, China(2022JJ10027);Research Foundation of Education Bureau of Hunan Province, China(21A0135);National Key Science and Technology Project(2022ZD04009)

Abstract:

Rapeseed (Brassica napus L.) is the main source of edible vegetable oil in China, and increasing seed oil content is the most effective way to increase the supply of rapeseed oil. In this study, 43 genes related to lipid synthesis were selected by analyzing the seed transcriptome data of 4 rapeseed inbred lines 25, 35, and 45 days after pollination. Among them, 33 genes were continuously up-expressed and 10 genes were continuously down-expressed from 25 to 45 days of seed development. The main genes included BnLEC1, BnABI5, BnOLEO4, and BnOBAP1a. At the same time, combined with the resequencing data of 50 semi-winter Brassica napus, 3 SNPs and 9 SNPs significantly related to oil content were detected to BnOBAP1a-A10 and BnABI5-A05, respectively, and the oil content of BnOBAP1A-A10_Hap1 was significantly higher than Hap2. The oil content of BnABI5-A05_Hap1 was significantly higher than Hap3. In addition, WGCNA was used to construct gene networks, and we found that BnOBAP1a and BnABI5 were indirectly connected through three transcription factors LEC1, HMGB3, and HTA11, which together formed a molecular network involved in the potential regulation of seed oil accumulation. The results of this study provide valuable insights for the development of haplotype functional markers, aiming to further enhance oil content in B. napus.

Key words: Brassica napus, oil content, transcriptome analysis, coexpression analysis, regional association analysis

Table 1

Statistics of oil content in mature seeds of four rapeseed varieties in Changsha"

品种
Variety
最小值
Min.
最大值
Max.
平均值±标准差
Mean±SD
变异系数
CV (%)
XY777 31.60 36.06 33.32±1.67 5.02
XY015 38.83 42.56 40.39±1.28 3.16
CS136 47.51 51.52 49.50±1.30 2.62
CS115 46.24 50.18 48.84±1.21 2.32

Fig. 1

Screening statistics of continuously up-regulated or down-regulated expression genes (a) the number of continuously up-regulated or down-regulated genes of four rapeseed varieties in Changsha area during 25-35 days and 35-45 days periods. (b) Venn diagrams of four varieties consistently up-regulated genes. (c) Venn diagrams of consistently down-regulated genes in four varieties."

Fig. 2

Enrichment analysis of 383 differential gene pathways The size of the circle represents the number of genes, and the heat map represents the value of -log10 (P-value)."

Fig. 3

Differently expressed genes (DEGs) related to oil content The expression values for RNA-seq data were log10 (fpkm+1) transformed and displayed as filled blocks, from blue to yellow to red."

Fig. 4

Correlation analysis of oil content in haplotype (1,944,128-1,994,025 bp) regions of 50 resequencing materials (a) Haplotype (1,944,128-1,994,025 bp; R2=0.99) oil content correlation analysis. The solid blue line indicates a threshold P-value of 1.0×10-4 for genome-wide significance. (b)-(c) three SNPs (Chr. A10: 1,969,139; Chr. A10: 1,969,444; Chr. A10: 1,969,452, P = 1.35×10-5) was significantly correlated with oil content and was localized in the promoter region of BnOBAP1a-A10 gene. Heat maps show a strong linkage imbalance in these SNPs. Two haplotype alleles were detected in the BnOBAP1a-A10 haplotype region. (d) Comparative analysis of the oil content of the materials corresponding to the two haplotype alleles. Haplotype alleles with frequencies greater than 0.01 in the population will be used for this analysis. The box pattern shows that the material corresponding to the BnOBAP1a-A10_Hap1 allele has a higher oil content than that of BnOBAP1a-A10_Hap2. *, **, and *** mean significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively."

Fig. 5

Correlation analysis of oil content in haplotype (4,389,567-4,439,432 bp) regions of 50 resequenced materials (a) Haplotype (4,389,567-4,439,432 bp; R2=0.99) oil content correlation analysis. The solid blue line indicates a threshold P-value of 1.0×10-4 for genome-wide significance. (b)-(c) nine SNPs (A05: 4,414,567; P = 1.42×10-4) was significantly correlated with oil content and was localized in the BnABI5-A05 gene region. Heat maps show a strong linkage imbalance in these SNPs. Three haplotype alleles were detected in the haplotype region of BnABI5-A05. (d) Comparative analysis of the oil content of the materials corresponding to the three haplotype alleles. Haplotype alleles with frequencies greater than 0.01 in the population will be used for this analysis. The box pattern shows that the material corresponding to the BnABI5-A05_Hap1 allele has a higher oil content. *, **, and *** mean significant difference at the 0.05, 0.01, and 0.001 probability levels, respectively."

Fig. 6

Coexpression network analysis (a): dendrogram of module system. (b): correlation between modules and oil content. (c): comparison of gene numbers in modules. (d): gene network diagram. Octagonal red nodes represent candidate genes, and according to functional labeling, co-expression networks are divided into: lipid/fatty acid biosynthesis (red nodes), lipid transport (purple nodes), lipid/fatty acid oxidation (orange nodes), photosynthesis (green nodes), and carbohydrate metabolism (gray nodes)."

[1] Liu S, Fan C, Li J, Cai G, Yang Q, Wu J, Yi X, Zhang C, Zhou Y. A genome-wide association study reveals novel elite allelic variations in seed oil content of Brassica napus. Theor Appl Genet, 2016, 129: 3-15.
[2] Hua W, Liu J, Wang H. Molecular regulation and genetic improvement of seed oil content in Brassica napus L. Front Agric Sci Eng, 2016, 3: 186-194.
[3] 王汉中. 未来15年中国油菜遗传改良策略. 中国油料作物学报, 2004, 26: 98-101.
Wang H Z. Strategy for rapeseed genetic improvement in China in the coming fifteen years. Chin J Oil Crop Sci, 2004, 26: 98-101 (in Chinese with English abstract).
[4] Xin F W, Gui H L, Qing Y, Wei H, Jing L, Wang H Z. Genetic analysis on oil content in rapeseed (Brassica napus L.). Euphytica, 2010, 173: 17-24.
doi: 10.1007/s10681-009-0062-x
[5] Hua W, Li R J, Zhan G M, Liu J, Li J, Wang X F, Liu G H, Wang H Z. Maternal control of seed oil content in Brassica napus: the role of silique wall photosynthesis. Plant J, 2012, 69: 32-44.
[6] Yan L G, Ping S, Nan W, Jing W, Bin Y, Chao Z M, Jin X T, Ji T Z, Ting D F, Jin X S. Genetic effects and genotype × environment interactions govern seed oil content in Brassica napus L. BMC Genet, 2017, 18: 1.
doi: 10.1186/s12863-016-0468-0
[7] Jing L, Wei H, Hong L Y, Gao M Z, Rong J L, Lin B D, Xin F W, Gui H L, Wang H Z. The BnGRF2 gene (GRF2-like gene from Brassica napus) enhances seed oil production through regulating cell number and plant photosynthesis. J Exp Bot, 2012, 63: 3727-3740.
doi: 10.1093/jxb/ers066 pmid: 22442419
[8] Chao H, Wang H, Wang X, Guo L, Gu J, Zhao W, Li B, Chen D, Raboanatahiry N, Li M. Genetic dissection of seed oil and protein content and identification of networks associated with oil content in Brassica napus. Sci Rep, 2017, 7: 46295.
doi: 10.1038/srep46295
[9] Shi J, Lang C, Wang F, Wu X, Liu R, Zheng T, Zhang D, Chen J, Wu G. Depressed expression of FAE1 and FAD2 genes modifies fatty acid profiles and storage compounds accumulation in Brassica napus seeds. Plant Sci, 2017, 263: 177-182.
doi: 10.1016/j.plantsci.2017.07.014
[10] Frentzen M. Acyltransferases from basic science to modified seed oils. Eur J Lipid Sci Technol, 2010, 100: 161-166.
[11] Hills M J. Control of storage-product synthesis in seeds. Curr Opin Plant Biol, 2004, 7: 302-308.
doi: 10.1016/j.pbi.2004.03.003 pmid: 15134751
[12] Bates P D, Johnson S R, Cao X, Li J, Nam J W, Jaworski J G, Ohlrogge J B, Browse J. Fatty acid synthesis is inhibited by inefficient utilization of unusual fatty acids for glycerolipid assembly. Proc Natl Acad Sci USA, 2014, 111: 4-9.
[13] Turnham E, Northcote D H. Changes in the activity of acetyl-CoA carboxylase during rape-seed formation. Biochem J, 1983, 212: 3-9.
[14] Weselake R J, Shah S, Tang M, Quant P A, Snyder C L, Furukawa-Stoffer T L, Zhu W, Taylor D C, Zou J, Kumar A, Hall L, Laroche A, Rakow G, Raney P, Moloney M M, Harwood J L. Metabolic control analysis is helpful for informed genetic manipulation of oilseed rape (Brassica napus) to increase seed oil content. J Exp Bot, 2008, 59: 3-9.
[15] Lock Y Y, Snyder C L, Zhu W, Siloto R M, Weselake R J, Shah S. Antisense suppression of type 1 diacylglycerol acyltransferase adversely affects plant development in Brassica napus. Physiol Plant, 2009, 137: 61-71.
doi: 10.1111/ppl.2009.137.issue-1
[16] Kagaya Y, Toyoshima R, Okuda R, Usui H, Yamamoto A, Hattori T. LEAFY COTYLEDON1 controls seed storage protein genes through its regulation of FUSCA3 and ABSCISIC ACID INSENSITIVE3. Plant Cell Physiol, 2005, 46: 399-406.
doi: 10.1093/pcp/pci048
[17] Wang H, Guo J, Lambert K N, Lin Y. Developmental control of Arabidopsis seed oil biosynthesis. Planta, 2007, 226: 73-83.
doi: 10.1007/s00425-006-0469-8
[18] Wu X L, Liu Z H, Hu Z H, Huang R Z. BnWRI1 coordinates fatty acid biosynthesis and photosynthesis pathways during oil accumulation in rapeseed. J Integr Plant Biol, 2014, 56: 82-93.
[19] Elahi N, Duncan R W, Stasolla C. Decreased seed oil production in FUSCA3 Brassica napus mutant plants. Plant Physiol Biochem, 2015, 96: 22-30.
[20] Elahi N, Duncan R W, Stasolla C. Modification of oil and glucosinolate content in canola seeds with altered expression of Brassica napus LEAFY COTYLEDON1. Plant Physiol Biochem, 2016, 100: 52-63.
doi: 10.1016/j.plaphy.2015.12.022
[21] Wang Z, Qiao Y, Zhang J, Shi W, Zhang J. Genome wide identification of microRNAs involved in fatty acid and lipid metabolism of Brassica napus by small RNA and degradome sequencing. Gene, 2017, 619: 61-70.
doi: 10.1016/j.gene.2017.03.040
[22] Xu H M, Kong X D, Chen F, Huang J X, Lou X Y, Zhao J Y. Transcriptome analysis of Brassica napus pod using RNA-Seq and identification of lipid-related candidate genes. BMC Genomics, 2015, 16: 858.
doi: 10.1186/s12864-015-2062-7
[23] Shah S, Weinholdt C, Jedrusik N, Molina C, Zou J, Große I, Schiessl S, Jung C, Emrani N. Whole-transcriptome analysis reveals genetic factors underlying flowering time regulation in rapeseed (Brassica napus L.). Plant Cell Environ, 2018, 41: 1935-1947.
doi: 10.1111/pce.v41.8
[24] Zhao C, Xie M, Liang L, Yang L, Han H, Qin X, Zhao J, Hou Y, Dai W, Du C, Xiang Y, Liu S, Huang X. Genome-wide association analysis combined with quantitative trait loci mapping and dynamic transcriptome unveil the genetic control of seed oil content in Brassica napus L. Front Plant Sci, 2022, 13: 929197.
doi: 10.3389/fpls.2022.929197
[25] He Y, Wu D, Wei D, Fu Y, Cui Y, Dong H, Tan C, Qian W. GWAS, QTL mapping and gene expression analyses in Brassica napus reveal genetic control of branching morphogenesis. Sci Rep, 2017, 7: 15971.
doi: 10.1038/s41598-017-15976-4
[26] Gajardo H, Wittkop B, Soto-Cerda B, Higgins E, Parkin I, Snowdon R, Federico M, Iniguez-Luy F. Association mapping of seed quality traits in Brassica napus L. using GWAS and candidate QTL approaches. Mol Breed, 2015, 35: 143.
doi: 10.1007/s11032-015-0340-3
[27] Liu S, Fan C, Li J, Cai G, Yang Q, Wu J, Yi X, Zhang C, Zhou Y. A genome-wide association study reveals novel elite allelic variations in seed oil content of Brassica napus. Theor Appl Genet, 2016, 129: 3-15.
[28] Xiao Z, Zhang C, Tang F, Yang B, Zhang L, Liu J, Huo Q, Wang S, Li S, Wei L, Du H, Qu C, Lu K, Li J, Li N. Identification of candidate genes controlling oil content by combination of genome-wide association and transcriptome analysis in the oilseed crop Brassica napus. Biotechnol Biofuels, 2019, 12: 216.
doi: 10.1186/s13068-019-1557-x
[29] Cun M Q, Le D J, Fu Y F, Hui Y Z, Kun L, Li J W, Xin F X, Ying L, Shi M L, Rui W, Jia N L. Genome-wide association mapping and identification of candidate genes for fatty acid composition in Brassica napus L. using SNP markers. BMC Genomics, 2017, 18: 232.
doi: 10.1186/s12864-017-3607-8
[30] Zhao C, Xie M, Liang L, Yang L, Han H, Qin X, Zhao J, Hou Y, Dai W, Du C, Xiang Y, Liu S, Huang X. Genome-wide association analysis combined with quantitative trait loci mapping and dynamic transcriptome unveil the genetic control of seed oil content in Brassica napus L. Front Plant Sci, 2022, 13: 929197.
doi: 10.3389/fpls.2022.929197
[31] Uzunova M, Ecke W, Weissleder K, Röbbelen G. 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, 1995, 90: 194-204.
doi: 10.1007/BF00222202 pmid: 24173891
[32] Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 2009, 25: 1754-1760.
doi: 10.1093/bioinformatics/btp324 pmid: 19451168
[33] Browning B L, Browning S R. A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet, 2009, 84: 10-23.
[34] Bradbury P J, Zhang Z, Kroon D E, Casstevens T M, Ramdoss Y, Buckler E S. TASSEL: software for association mapping of complex traits in diverse samples. Bioinformatics, 2007, 23: 3-5.
[35] Lu K, Peng L, Zhang C, Lu J, Yang B, Xiao Z, Liang Y, Xu X, Qu C, Zhang K, Liu L, Zhu Q, Fu M, Yuan X, Li J. Genome-wide association and transcriptome analyses reveal candidate genes underlying yield-determining traits in Brassica napus. Front Plant Sci, 2017, 8: 206.
[36] Turner S D. QQman: an R package for visualizing GWAS results using QQ and manhattan plots. BioRxiv, 2014, 005165.
[37] Langfelder P, Horvath S. WGCNA: an R package for weighted correlation network analysis. BMC Bioinform, 2008, 9: 559.
doi: 10.1186/1471-2105-9-559
[38] Shannon P, Markiel A, Ozier O, Baliga N S, Wang J T, Ramage D, Amin N, Schwikowski B, Ideker T. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res, 2003, 13: 498-504.
[39] Si P, Mailer R J, Galwey N, Turner D W. Influence of genotype and environment on oil and protein concentrations of canola (Brassica napus L.) grown across southern Australia. Aust J Agric Res, 2003, 54: 397-407.
doi: 10.1071/AR01203
[40] Tang S, Zhao H, Lu S, Yu L, Zhang G, Zhang Y, Yang Q Y, Zhou Y, Wang X, Ma W, Xie W, Guo L. Genome- and transcriptome-wide association studies provide insights into the genetic basis of natural variation of seed oil content in Brassica napus. Mol Plant, 2021, 14: 470-487.
doi: 10.1016/j.molp.2020.12.003
[41] Tang M Q, Zhang Y Y, Liu Y Y, Tong C B, Cheng X H, Zhu W, Li Z Y, Huang J Y, Liu S Y. Mapping loci controlling fatty acid profiles and oil and protein content by genome-wide association study in Brassica napus. Crop J, 2019, 7: 217-226.
doi: 10.1016/j.cj.2018.10.007
[42] Zhao C, Xie M, Liang L, Yang L, Han H, Qin X, Zhao J, Hou Y, Dai W, Du C, Xiang Y, Liu S, Huang X. Genome-wide association analysis combined with quantitative trait loci mapping and dynamic transcriptome unveil the genetic control of seed oil content in Brassica napus L. Front Plant Sci, 2022, 13: 929197.
doi: 10.3389/fpls.2022.929197
[43] López-Ribera I, La Paz J L, Repiso C, García N, Miquel M, Hernández M L, Martínez-Rivas J M, Vicient C M. The evolutionary conserved oil body associated protein OBAP1 participates in the regulation of oil body size. Plant Physiol, 2014, 164: 37-49.
[44] Kong Y, Chen S, Yang Y, An C. ABA-insensitive (ABI) 4 and ABI5 synergistically regulate DGAT1 expression in Arabidopsis seedlings under stress. FEBS Lett, 2013, 587: 76-82.
[45] Yeap W, Lee F L, Shan D, Musa H, Appleton D R, Kulaveerasingam H. WRI1-1, ABI5, NF-YA3 and NF-YC2 increase oil biosynthesis in coordination with hormonal signaling during fruit development in oil palm. Plant J, 2017, 91: 97-113.
doi: 10.1111/tpj.2017.91.issue-1
[46] Crowe A J, Abenes M, Plant A, Moloney M M. The seed-specific transactivator, ABI3, induces oleosin gene expression. Plant Sci, 2000, 151: 171-181.
doi: 10.1016/s0168-9452(99)00214-9 pmid: 10808073
[47] Nakamura S, Lynch T J, Finkelstein R R. Physical interactions between ABA response loci of Arabidopsis. Plant J, 2001, 26: 27-35.
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