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作物学报 ›› 2020, Vol. 46 ›› Issue (01): 147-153.doi: 10.3724/SP.J.1006.2020.94060

• 研究简报 • 上一篇    

甘蓝型油菜每角粒数的全基因组关联分析

孙程明1,2,陈锋1,陈松1,彭琦1,张维1,易斌2,*(),张洁夫1,*(),傅廷栋2   

  1. 1 江苏省农业科学院经济作物研究所/农业部长江下游棉花与油菜重点实验室/江苏省现代作物生产协同创新中心, 江苏南京210014
    2 华中农业大学植物科学技术学院/作物遗传改良国家重点实验室, 湖北武汉 430070
  • 收稿日期:2019-04-15 接受日期:2019-08-09 出版日期:2020-01-12 网络出版日期:2019-09-11
  • 通讯作者: 易斌,张洁夫
  • 作者简介:E-mail: suncm8331537@gmail.com
  • 基金资助:
    本研究由国家重点研发计划项目(2018YFD0100602);国家现代农业产业技术体系建设专项(CARS-12);江苏省农业科技自主创新基金(CX(19)3055-12);江苏省基础研究计划(自然科学基金)项目(BK20190260);中央高校基本科研业务费专项资金资助项资助(2662016PY063)

Genome-wide association study of seed number per silique in rapeseed (Brassica napus L.)

SUN Cheng-Ming1,2,CHEN Feng1,CHEN Song1,PENG Qi1,ZHANG Wei1,YI Bin2,*(),ZHANG Jie-Fu1,*(),FU Ting-Dong2   

  1. 1 Institute of Industrial Crops, Jiangsu Academy of Agricultural Sciences/Key Laboratory of Cotton and Rapeseed (Nanjing), Ministry of Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing 210014, Jiangsu, China
    2 National Key Laboratory of Crop Genetic Improvement/College of Plant Science and Technology, Huazhong Agricultural University, Wuhan 430070, Hubei, China;
  • Received:2019-04-15 Accepted:2019-08-09 Published:2020-01-12 Published online:2019-09-11
  • Contact: Bin YI,Jie-Fu ZHANG
  • Supported by:
    The study was supported by the National Key Research and Development Program of China(2018YFD0100602);Earmarked Fund for China Agriculture Research System(CARS-12);Jiangsu Agriculture Science and Technology Innovation Fund(CX(19)3055-12);Natural Fund Project of Jiangsu Basic Research Program(BK20190260);Fundamental Research Funds for the Central Universities(2662016PY063)

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摘要：

每角粒数是油菜重要的产量构成因子, 增加每角粒数有助于提高油菜的籽粒产量。利用Illumina 60K SNP芯片对496份具有代表性的油菜资源进行基因型分析, 考察该群体在2个环境中的每角粒数, 利用MLM和GLM模型进行全基因组关联分析。结果表明, 本群体在2个环境中每角粒数的广义遗传力为57.7%。利用MLM和GLM模型分别检测到9个和20个位点, 所有MLM位点均得到GLM结果的验证。6个位点与前人定位的QTL重叠, 其中2个位点得到2次验证, 其余14个是新位点。在7个位点附近找到了候选基因, 其中在C09染色体的位点Bn-scaff_15576_1-p74980附近找到已克隆的油菜每角粒数基因BnaC9.SMG7b, 在其余6个位点附近找到GRDP1、SPATULA、HVA22D、DA2等已知的拟南芥每角粒数基因的同源基因。本研究结果有助于解析油菜每角粒数的遗传基础及其调控机制, 为每角粒数的遗传改良奠定了基础。

关键词: 甘蓝型油菜, 产量, 每角粒数, 关联分析, SNP标记

Abstract:

Seed number per silique (SSN) is a key component of seed yield in rapeseed, increasing SSN can improve the seed yield of plants. A collection of 496 representative rapeseed accessions was genotyped by the Illumina 60K SNP array and phenotyped for SSN in two environments. The genome-wide association study (GWAS) of SSN was performed via the MLM (Mixed linear model) and GLM (General linear model). The broad-sense heritability of SSN was 57.7%. Nine and twenty loci were detected with MLM and GLM, respectively, and all loci detected by MLM were included those by GLM. Six loci were overlapped with reported QTLs, and two of them were validated by two independent researches, and the rest 14 loci were new. We identified plausible candidate genes nearby seven loci, and the reported rapeseed SSN gene BnaC9.SMG7b was found near the locus Bn-scaff_15576_1-p74980 on C09 chromosome detected in this study. Besides, six candidates orthologous to documented Arabidopsis SSN genes, like GRDP1, SPATULA, HVA22D, and DA2, were found near our GWAS loci. The results provide an insight into the genetic basis of seed number per silique and lay a foundation for further mechanism exploration and breeding for this trait in B. napus.

Key words: Brassica napus L., yield, seed number per silique, GWAS, SNP

表1

关联群体每角粒数性状的统计分析"

环境
Environment		 最小值
Min.		 最大值
Max.		 平均值±标准差
Mean ± SD		 变异系数
CV
2014/2015 Taizhou 8.83 27.73 21.45±2.36 0.11
2015/2016 Taizhou 11.00 26.24 20.56±1.99 0.10

图1

关联群体在2个环境的每角粒数分布"

表2

MLM每角粒数显著关联位点"

标记
Marker		 染色体
Chr.		 位置
Position		 -lg (P) 表型变异
R2 (%)		 环境
Environment		 已报道QTL
Reported QTL
Bn-A01-p3904495 A01 3,530,446 5.01 0.03832 16TZ [5]
Bn-A04-p10393460 A04 11,537,744 5.15 0.03946 15TZ
Bn-A07-p22251229 A07 23,650,401 4.78 0.03896 15TZ
Bn-A08-p14749618 A08 12,312,967 4.37 0.03265 15TZ [7]
Bn-scaff_15936_1-p270915 C01 36,405,870 4.66 0.03521 BLUP [5-6]
Bn-scaff_15712_6-p1336179 C02 38,045,422 4.33 0.04469 15TZ, 16TZ
Bn-scaff_23954_1-p220801 C03 11,576,750 4.49 0.03371 15TZ
Bn-scaff_16027_1-p367097 C04 1,254,637 4.52 0.03698 15TZ
Bn-scaff_23907_1-p3780 C04 7,268,977 5.09 0.04605 BLUP

图2

油菜每角粒数全基因组关联分析(MLM) A: 每角粒数BLUP值MLM曼哈顿图; B: 15TZ每角粒数MLM曼哈顿图; C: 16TZ每角粒数MLM曼哈顿图。水平线代表Bonferroni阈值。"

表3

GLM每角粒数显著关联位点"

标记
Marker		 染色体
Chr.		 位置
Position		 -lg (P) 表型变异
R2 (%)		 环境
Environment		 已报道QTL
Reported QTL
Bn-A01-p3904495 A01 3,530,446 5.05 0.0357 16TZ [5]
Bn-A04-p10393460 A04 11,537,744 5.79 0.0408 15TZ
Bn-A07-p9916502 A07 11,196,091 4.50 0.0404 BLUP
Bn-A07-p22251229 A07 23,650,401 4.41 0.0322 15TZ
Bn-A08-p14749618 A08 12,312,967 4.74 0.0327 15TZ [7]
Bn-scaff_15838_1-p1554155 C01 1,926,096 4.41 0.0437 16TZ [8]
Bn-scaff_15936_1-p270915 C01 36,405,870 5.13 0.0353 BLUP [5-6]
Bn-scaff_15712_6-p1336179 C02 38,045,422 4.66 0.0435 16TZ
Bn-scaff_23954_1-p635109 C03 11,205,203 4.78 0.0330 15TZ
Bn-scaff_16027_1-p367097 C04 1,254,637 4.62 0.0365 15TZ
Bn-scaff_23907_1-p3780 C04 7,268,977 5.59 0.0483 15TZ,BLUP
Bn-scaff_19253_1-p524524 C04 15,606,945 4.29 0.0290 BLUP
Bn-scaff_15936_1-p357665 C05 9,508,115 4.78 0.0453 BLUP
Bn-scaff_16064_1-p1144443 C06 24,511,029 4.74 0.0327 15TZ
Bn-scaff_17484_1-p132976 C07 5,857,563 4.60 0.0317 15TZ
Bn-scaff_20084_1-p104549 C07 9,638,283 5.36 0.0375 15TZ
Bn-scaff_16069_1-p1651456 C07 38,070,340 5.23 0.0365 15TZ
Bn-scaff_16069_1-p3780494 C07 40,184,749 4.35 0.0302 16TZ
Bn-scaff_15808_1-p420800 C09 37,129,614 5.15 0.0365 16TZ [5]
Bn-scaff_15576_1-p74980 C09 41,126,168 4.35 0.0303 16TZ [5,19]

图3

油菜每角粒数全基因组关联分析(GLM) A: 每角粒数BLUP值GLM曼哈顿图; B: 15TZ每角粒数GLM曼哈顿图; C: 16TZ每角粒数GLM曼哈顿图。水平线代表Bonferroni阈值。"

表4

每角粒数关联位点候选基因信息"

标记
Marker		 油菜基因
Rapeseed gene		 染色体
Chr.		 位置
Position		 拟南芥同源基因
Ar. homolog
Bn-A04-p10393460 BnaA04g13080 A04 11,015,882 GRDP1
Bn-A07-p9916502 BnaA07g13170 A07 11,744,966 GLE1
Bn-A08-p14749618 BnaA08g15580 A08 12,923,783 SPATULA
Bn-scaff_23954_1-p635109 BnaC03g21140 C03 11,367,292 DA2
Bn-scaff_16069_1-p3780494 BnaC07g39210 C07 40,210,953 HVA22D
Bn-scaff_15808_1-p420800 BnaC09g33680 C09 36,922,347 MSI1
Bn-scaff_15576_1-p74980 BnaC09g38310 C09 41,208,383 SMG7b
[1] 王汉中 . 我国油菜产业发展的历史回顾与展望. 中国油料作物学报, 2010,32:300-302.
Wang H Z . Review and future development of rapeseed industry in China. Chin J Oil Crop Sci, 2010,32:300-302 (in Chinese with English abstract).
[2] 李永鹏, 程焱, 蔡光勤, 范楚川, 周永明 . 油菜每角果粒数差异的细胞学基础和分子机理. 中国科学: 生命科学, 2014,44:822-831.
Li Y P, Cheng Y, Cai G Q, Fan C C, Zhou Y M . Cytological basis and molecular mechanism of variation in number of seeds per pod in Brassica napus. Sci Sin Vitae, 2014,44:822-831 (in Chinese with English abstract).
[3] Yang Y, Wang Y, Zhan J, Shi J, Wang X, Liu G, Wang H . Genetic and cytological analyses of the natural variation of seed number per pod in rapeseed (Brassica napus L.). Front Plant Sci, 2017,8:1890. doi: 10.3389/fpls.2017.01890.
doi: 10.3389/fpls.2017.01890 pmid: 29163611
[4] Shi J, Li R, Qiu D, Jiang C, Long Y, Morgan C, Bancroft I, Zhao J, Meng J . Unraveling the complex trait of crop yield with quantitative trait loci mapping inBrassica napus. Genetics, 2009,182:851-861.
doi: 10.1534/genetics.109.101642 pmid: 19414564
[5] Luo Z, Wang M, Long Y, Huang Y, Shi L, Zhang C, Liu X, Fitt B D, Xiang J, Mason A S . Incorporating pleiotropic quantitative trait loci in dissection of complex traits: seed yield in rapeseed as an example. Theor Appl Genet, 2017,130:1569-1585.
doi: 10.1007/s00122-017-2911-7 pmid: 28455767
[6] 漆丽萍 . 甘蓝型油菜株型与角果相关性状的QTL分析. 华中农业大学博士学位论文, 湖北武汉, 2014.
Qi L P . QTL Analysis for the Traits Associated with Plant Architecture and Silique in Brassica napus L. PhD Dissertation of Huazhong Agricultural University, Wuhan, Hubei, China, 2014 (in Chinese with English abstract).
[7] Cai G, Yang Q, Chen H, Yang Q, Zhang C, Fan C, Zhou Y . Genetic dissection of plant architecture and yield-related traits in Brassica napus. Sci Rep, 2016,6:21625. doi: 10.1038/srep 21625.
doi: 10.1038/srep21625 pmid: 26880301
[8] Yang Y, Shi J, Wang X, Liu G, Wang H . Genetic architecture and mechanism of seed number per pod in rapeseed: elucidated through linkage and near-isogenic line analysis. Sci Rep, 2016,6:24124. doi: 10.1038/srep24124.
doi: 10.1038/srep24124 pmid: 27067010
[9] Sun C, Wang B, Yan L, Hu K, Liu S, Zhou Y, Guan C, Zhang Z, Li J, Zhang J, Chen S, Wen J, Ma C, Tu J, Shen J, Fu T, Yi B . Genome-wide association study provides insight into the genetic control of plant height in rapeseed (Brassica napus L.). Front Plant Sci, 2016,7:1102. doi: 10.3389/fpls.2016.01102.
doi: 10.3389/fpls.2016.01102 pmid: 27512396
[10] Lu K, Wei L, Li X, Wang Y, Wu J, Liu M, Zhang C, Chen Z, Xiao Z, Jian H . Whole-genome resequencing revealsBrassica napus origin and genetic loci involved in its improvement. Nat Commun, 2019,10:1154. doi: 10.1038/s41467-019-09134-9.
doi: 10.1038/s41467-019-09134-9 pmid: 30858362
[11] Chen L, Wan H, Qian J, Guo J, Sun C, Wen J, Yi B, Ma C, Tu J, Song L . Genome-wide association study of cadmium accumulation at the seedling stage in rapeseed (Brassica napus L.). Front Plant Sci, 2018,9:375. doi: 10.3389/fpls.2018.00375.
doi: 10.3389/fpls.2018.00375 pmid: 29725340
[12] Xu L, Hu K, Zhang Z, Guan C, Chen S, Hua W, Li J, Wen J, Yi B, Shen J . Genome-wide association study reveals the genetic architecture of flowering time in rapeseed (Brassica napus L.). DNA Res, 2015,23:43-52.
doi: 10.1093/dnares/dsv035 pmid: 26659471
[13] Merk H L, Yarnes S C, Van Deynze A, Tong N, Menda N, Mueller L A, Mutschler M A, Loewen S A, Myers J R, Francis D M . Trait diversity and potential for selection indices based on variation among regionally adapted processing tomato germplasm. J Am Soc Hortic Sci, 2012,137:427-437.
[14] Ihaka R, Gentleman R . R: a language for data analysis and graphics. J Comput Graph Stat, 1996,5:299-314.
doi: 10.1002/rcm.8315 pmid: 30366355
[15] Evanno G, Regnaut S, Goudet J . Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol, 2005,14:2611-2620.
doi: 10.1111/j.1365-294X.2005.02553.x pmid: 15969739
[16] Hardy O J, Vekemans X . SPAGeDi: a versatile computer program to analyse spatial genetic structure at the individual or population levels. Mol Ecol Notes, 2002,2:618-620.
doi: 10.1016/j.yebeh.2019.106687 pmid: 31816478
[17] 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, 2007,23:2633-2635.
doi: 10.1093/bioinformatics/btm308 pmid: 17586829
[18] Turner S D . qqman: an R package for visualizing GWAS results using QQ and manhattan plots. BioRxiv, 2014, 1: 005165. doi: http://dx.doi.org/10.1101/005165.
[19] Li S, Chen L, Zhang L, Li X, Liu Y, Wu Z, Dong F, Wan L, Liu K, Hong D . BnaC9. SMG7b functions as a positive regulator of the number of seeds per silique in Brassica napus by regulating the formation of functional female gametophytes. Plant Physiol, 2015,169:2744-2760.
doi: 10.1104/pp.15.01040 pmid: 26494121
[20] Rodríguez-Hernández A A, Muro-Medina C V, Ramírez-Alonso J I, Jiménez-Bremont J F . Modification of AtGRDP1 gene expression affects silique and seed development inArabidopsis thaliana. Biochem Biophys Res Common, 2017,486:252-256.
doi: 10.1016/j.bbrc.2017.03.015 pmid: 28285133
[21] Xia T, Li N, Dumenil J, Li J, Kamenski A, Bevan M W, Gao F, Li Y . The ubiquitin receptor DA1 interacts with the E3 ubiquitin ligase DA2 to regulate seed and organ size in Arabidopsis. Plant Cell, 2013,25:3347-3359.
doi: 10.1105/tpc.113.115063
[22] Braud C, Zheng W, Xiao W . LONO1 encoding a nucleoporin is required for embryogenesis and seed viability in Arabidopsis. Plant Physiol, 2012,160:823-836.
doi: 10.1104/pp.112.202192 pmid: 22898497
[23] Groszmann M, Paicu T, Smyth D R . Functional domains of SPATULA, a bHLH transcription factor involved in carpel and fruit development in Arabidopsis. Plant J, 2008,55:40-52.
doi: 10.1111/j.1365-313X.2008.03469.x pmid: 18315540
[24] Chen N N, Chen H R, Yeh S Y, Vittore G, Ho H D . Autophagy is enhanced and floral development is impaired in AtHVA22d RNA interference Arabidopsis. Plant Physiol, 2009,149:1679-1689.
doi: 10.1104/pp.108.131490 pmid: 19151132
[25] Leroy O, Hennig L, Breuninger H, Laux T, Köhler C . Polycomb group proteins function in the female gametophyte to determine seed development in plants. Development, 2007,134:3639-3648.
doi: 10.1242/dev.009027 pmid: 17855429
[26] Yang Y, Zhu K, Li H, Han S, Meng Q, Khan S U, Fan C, Xie K, Zhou Y . Precise editing of CLAVATA genes in Brassica napus L. regulates multilocular silique development. Plant Biotechnol J, 2018,16:1322-1335.
doi: 10.1111/pbi.12872 pmid: 29250878
[27] Shah S, Karunarathna N L, Jung C, Emrani N . An APETALA1 ortholog affects plant architecture and seed yield component in oilseed rape (Brassica napus L.). BMC Plant Biol, 2018,18:380. doi: 10.1186/s12870-018-1606-9.
doi: 10.1186/s12870-018-1606-9 pmid: 30594150
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