Welcome to Acta Agronomica Sinica,

Acta Agron Sin ›› 2016, Vol. 42 ›› Issue (03): 344-352.doi: 10.3724/SP.J.1006.2016.000344

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

Genome-Wide Association Analysis of Height of Podding and Thickness of Pod Canopy in Brassica napus

LU Kun1,**,WANG Teng-Yue1,**,XU Xin-Fu1,TANG Zhang-Lin1,QU Cun-Ming1,HE Bin2,LIANG Ying1,LI Jia-Na1,*   

  1. 1 College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China; 2 Agricultural Technology Extension Stationin Lincang City, Lincang 677000, China
  • Received:2015-08-24 Revised:2015-11-20 Online:2016-03-12 Published:2015-12-07
  • Supported by:

    This study was supported by the National Basic Research Program of China (973 Program) (2015CB150201), the National Science Foundation of China (U1302266 and 31401412), the Program of Introducing International Super Agricultural Science and Technology(948 Program) (2011-G23), the Key Technologies Research and Development Program of China (2013BAD01B03-12) and the 111 Project (B12006).

Abstract:

Layer of pod canopy is an important photosynthetic and seed storage part in rapeseed, providing important contribution to yield. In this study, 412 representative Brassica napus varieties (or lines) were genotyped using the Brassica 60 K Illumina Infinium SNP array by genome-wide association analysis of the height of podding (HP) and thickness of pod canopy (TPC). A total of 16 significant SNPs were identified, including two and four SNPs associated with HP and TPC in Chongqing, each of them explained 5.61%–5.69% and 5.94%–6.31% of phenotypic variation, respectively. Five and one significant SNPs accounting for 12.66%–13.97% and 22.43% of the phenotypic variation for HP and TPC in Yunnan, respectively, were also detected. Three and one significant SNPs associated with the difference of HP and TPC between two environments were detected, explaining 17.33%–20.32% and 29.05% of phenotypic variation, respectively. The latter SNP marker was located in the same linkage disequilibrium (LD) interval with one of significant SNPs related to TPC in Chongqing. Functional annotation of genes within the LD intervals containing significant markers showed that several genes involved in regulation of cell organization and biogenesis, floral meristem development, number of silique, and multicellular organismal development existed, such as NSN1, TPST, and SAC1, which might result in the variation of HP and TPC through affecting the growth and development of flower or silique in B. napus. These loci and genes could be regarded as important candidate regions and genes for HP and TPC of B. napus. The results lay the foundation for revealing the genetic basis and molecular mechanism for podding traits, and improving the yield per unit area of B. napus.

Key words: Brassica napus, Genome-wide association analysis, Height of podding, Thickness of pod canopy, Yield

[1]  官春云. “农业科技创新与服务”笔谈:依托科技创新与服务加快油菜产业发展方式转变. 湖南农业大学学报(社会科学版), 2010, 11(4): 1–3

Guan C Y. Pen talk on innovation and service of agricultural science and technology: accelerate change of rapeseed industry development mode based on scientific and technological innovation. J Hunan Agric Uni (Soc Sci), 2010, 11(4): 1–3 (in Chinese with English abstract)

[2]  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

[3]  Özer H, Oral E, Dogru U. Relationships between yield and yield components on currently improved spring rapeseed cultivars. Turk J Agric For, 1999, 23: 603–608

[4]  Chen W, ZhangY, Liu X, Chen B, Tu J, Fu T. Detection of QTL for six yield-related traits in oilseed rape (Brassica napus) using DH and immortalized F2 populations. Theor Appl Genet, 2007, 115: 849–858

[5]  DiepenbrockW. Yield analysis of winter oilseed rape (Brassica napus L.): a review. Field Crops Res, 2000, 67: 35–49

[6]  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 in Brassica napus. Genetics, 2009, 182: 851–861

[7]  Quijada P A, Udall J A, Lambert B, Osborn T C. Quantitative trait analysis of seed yield and other complex traits in hybrid spring rapeseed (Brassica napus L.): 1. Identification of genomic regions from winter germplasm. Theor Appl Genet, 2006, 113:549–561

[8]  吴建忠. 甘蓝型油菜几个农艺性状对产量的影响. 中国科技论文在线精品论文, 2011, 4: 1737–1741

Wu J Z. The effects of several agronomic traits on yield in Brassica napus L. Highlights Sciencepaper Online, 2011, 4: 1737–1741 (in Chinese with English abstract)

[9]  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. pp 45–73

Qi L P. QTL analysis for the traits associated with plant architecture and silique in Brassica napus L.. PhD Disseration of Huazhong Agricultural University, Wuhan, China, 2014. pp 45–73 (in Chinese with English abstract)

[10]  王道杰, 杨翠玲, 李艳萍, 王再青. 因子分析和数量分类在油菜种质资源遗传多样性研究中的应用. 植物学研究, 2014, 3: 207–217

Wang D, Yang C, Li Y, Wang Z. Factor analysis and numerical taxonomy applied in the research of germpasm genetic polymorphism in Brassica napus L. Bot Res, 2014, 3: 207–217 (in Chinese with English abstract)

[11]  张书芬, 傅廷栋, 朱家成, 王建平, 文雁成, 马朝芝. 甘蓝型油菜产量及其构成因素的QTL定位与分析. 作物学报, 2006, 32: 1135–1142

Zhang S F, Fu T D, Zhu J C, Wang J P, Wen Y C, Ma C Z. QTL mapping and epistasis analysis for yield and its components in Brassica napus L. Acta Agron Sin, 2006, 32: 1135–1142 (in Chinese with English abstract)

[12]  王峰, 官春云. 甘蓝型油菜遗传图谱的构建及单株产量构成因素的QTL分析. 遗传, 2010, 32: 271–277

Wang F, Guan C Y. Molecular mapping and identification of quantitative trait loci foryield components in rapeseed (Brasscia napus L.). Hereditas (Beijing), 2010, 32(3): 271–277 (in Chinese with English abstract)

[13] Chen W, Zhang Y, Yao J, Ma C, Tu J, Fu T. Quantitative trait loci mapping for two seed yield component traits in an oilseed rape (Brassica napus) cross. Plant Breed, 2011, 130: 640–646

[14] Chalhoub B, Denoeud F, Liu S, Parkin I A P, Tang H, Wang X, Chiquet J, Belcram H, Tong C, Samans B, Correa M, Da Silva C, Just J, Falentin C, Koh C S, Le Clainche I, Bernard M, Bento P, Noel B, Labadie K, Alberti A, Charles M, Arnaud D, Guo H, Daviaud C, Alamery S, Jabbari K, Zhao M, Edger P P, Chelaifa H, Tack D, Lassalle G, Mestiri I, Schnel N, Le Paslier M C, Fan G, Renault V, Bayer P E, Golicz A A, Manoli S, Lee T H, Thi V H D, Chalabi S, Hu Q, Fan C, Tollenaere R, Lu Y, Battail C, Shen J, Sidebottom C H D, Wang X, Canaguier A, Chauveau A, Berard A, Deniot G, Guan M, Liu Z, Sun F, Lim Y P, Lyons E, Town C D, Bancroft I, Wang X, Meng J, Ma J, Pires J C, King G J, Brunel D, Delourme R, Renard M, Aury J M, Adams K L, Batley J, Snowdon R J, Tost J, Edwards D, Zhou Y, Hua W, Sharpe A G, Paterson A H, Guan C, Wincker P. Early allopolyploid evolution in the post-Neolithic Brassica napus oilseed genome. Science, 2014, 345: 950–953

[15] Li F, Chen B, Xu K, Gao G, Yan G, Qiao J, Li J, Li H, Li L, Xiao X.A genome-wide association study of plant height and primary branch number in rapeseed (Brassica napus). Plant Sci, 2015, doi:10.1016/j.plantsci.2015.05.012

[16] Luo X, Ma C, Yue Y, Hu K, Li Y, Duan Z, Wu M, Tu J, Shen J, Yi B, Fu T. Unravelling the complex trait of harvest index in rapeseed (Brassica napus L.) with association mapping. BMC Genom, 2015, 16: 379

[17] Li F, Chen B, Xu K, Wu J, Song W, Bancroft I, Harper AL, Trick M, Liu S, Gao G, Wang N, Yan G, Qiao J, Li J, Li H, Xiao X, Zhang T, Wu X. Genome-wide association study dissects the genetic architecture of seed weight and seed quality in rapeseed (Brassica napus L.). DNA Res, 2014, 21: 355–367

[18] Hatzig S V, Frisch M, Breuer F, Nesi N, Ducournau S, Wagner M H, Leckband G, Abbadi A, Snowdon R J. Genome-wide association mapping unravels the genetic control of seed germination and vigor in Brassica napus. Front Plant Sci, 2015, 6: 221

[19] Pritchard J K, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics, 2000, 155: 945–959

[20] Earl D A, vonHoldt B M. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conserv Genet Resour, 2012, 4: 359–361

[21] 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

[22] Ginestet C. ggplot2: elegant graphics for data analysis. J Roy Stat Soc A, 2011, 174: 245–246

[23] Turner S D. qqman: an R package for visualizing GWAS results using QQ and manhattan plots. BioRxiv, 2014:005165

[24] Barrett J C, Fry B, Maller J, Daly M J. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics, 2005, 21: 263–265

[25] 杨光. 油菜高效结角层结构的研究, 扬州大学硕士学位论文, 江苏扬州, 2002. p 11

Yang G. The study of high-efficient pod canopy of oilseed rape. Master Disseration of Yangzhou University, Yangzhou, China, 2022. p 11 (in Chinese with English abstract)

[26] 浦惠明, 戚存扣, 傅寿仲. 油菜角果的生长特性及其源库效应. 江苏农业科学, 1993, 3: 22–25

Pu H M, Qi C K, Fu S Z. Growth characteristic of pod and source-sink response in oilseed. Jiangsu Agric Sci, 1993, 3: 22–25 (in Chinese with English abstract)

[27] 冷锁虎, 朱耕如, 邓秀兰. 油菜籽粒干物质来源的研究. 作物学报, 1992, 18: 250–257

Leng S H, Zhu G R, Deng X L. Studies on the sources of the dry matter in the seed of rapeseed. Acta Agron Sin, 1992, 18: 250–257 (in Chinese with English abstract)

[28] Jeon Y, Park Y J, Cho H K, Jung H J, Ahn T K, Kang H, Pai H S. The nucleolar GTPase nucleostemin-like 1 plays a role in plant growth and senescence by modulating ribosome biogenesis. J ExpBot, 2015: erv337

[29] Komori R, Amano Y, Ogawa-Ohnishi M, Matsubayashi Y. Identification of tyrosylprotein sulfotransferase in Arabidopsis. Proc Natl Acad Sci USA, 2009, 106: 15067–15072

[30] Zhong R, Burk D H, Nairn C J, Wood-Jones A, Morrison W H, Ye Z H. Mutation of SAC1, an Arabidopsis SAC domain phosphoinositide phosphatase, causes alterations in cell morphogenesis, cell wall synthesis, and actin organization. Plant Cell, 2005, 17: 1449–1466
[1] CHEN Song-Yu, DING Yi-Juan, SUN Jun-Ming, HUANG Deng-Wen, YANG Nan, DAI Yu-Han, WAN Hua-Fang, QIAN Wei. Genome-wide identification of BnCNGC and the gene expression analysis in Brassica napus challenged with Sclerotinia sclerotiorum and PEG-simulated drought [J]. Acta Agronomica Sinica, 2022, 48(6): 1357-1371.
[2] WANG Dan, ZHOU Bao-Yuan, MA Wei, GE Jun-Zhu, DING Zai-Song, LI Cong-Feng, ZHAO Ming. Characteristics of the annual distribution and utilization of climate resource for double maize cropping system in the middle reaches of Yangtze River [J]. Acta Agronomica Sinica, 2022, 48(6): 1437-1450.
[3] WANG Wang-Nian, GE Jun-Zhu, YANG Hai-Chang, YIN Fa-Ting, HUANG Tai-Li, KUAI Jie, WANG Jing, WANG Bo, ZHOU Guang-Sheng, FU Ting-Dong. Adaptation of feed crops to saline-alkali soil stress and effect of improving saline-alkali soil [J]. Acta Agronomica Sinica, 2022, 48(6): 1451-1462.
[4] YAN Jia-Qian, GU Yi-Biao, XUE Zhang-Yi, ZHOU Tian-Yang, GE Qian-Qian, ZHANG Hao, LIU Li-Jun, WANG Zhi-Qin, GU Jun-Fei, YANG Jian-Chang, ZHOU Zhen-Ling, XU Da-Yong. Different responses of rice cultivars to salt stress and the underlying mechanisms [J]. Acta Agronomica Sinica, 2022, 48(6): 1463-1475.
[5] YANG Huan, ZHOU Ying, CHEN Ping, DU Qing, ZHENG Ben-Chuan, PU Tian, WEN Jing, YANG Wen-Yu, YONG Tai-Wen. Effects of nutrient uptake and utilization on yield of maize-legume strip intercropping system [J]. Acta Agronomica Sinica, 2022, 48(6): 1476-1487.
[6] CHEN Jing, REN Bai-Zhao, ZHAO Bin, LIU Peng, ZHANG Ji-Wang. Regulation of leaf-spraying glycine betaine on yield formation and antioxidation of summer maize sowed in different dates [J]. Acta Agronomica Sinica, 2022, 48(6): 1502-1515.
[7] LI Yi-Jun, LYU Hou-Quan. Effect of agricultural meteorological disasters on the production corn in the Northeast China [J]. Acta Agronomica Sinica, 2022, 48(6): 1537-1545.
[8] SHI Yan-Yan, MA Zhi-Hua, WU Chun-Hua, ZHOU Yong-Jin, LI Rong. Effects of ridge tillage with film mulching in furrow on photosynthetic characteristics of potato and yield formation in dryland farming [J]. Acta Agronomica Sinica, 2022, 48(5): 1288-1297.
[9] YAN Xiao-Yu, GUO Wen-Jun, QIN Du-Lin, WANG Shuang-Lei, NIE Jun-Jun, ZHAO Na, QI Jie, SONG Xian-Liang, MAO Li-Li, SUN Xue-Zhen. Effects of cotton stubble return and subsoiling on dry matter accumulation, nutrient uptake, and yield of cotton in coastal saline-alkali soil [J]. Acta Agronomica Sinica, 2022, 48(5): 1235-1247.
[10] KE Jian, CHEN Ting-Ting, WU Zhou, ZHU Tie-Zhong, SUN Jie, HE Hai-Bing, YOU Cui-Cui, ZHU De-Quan, WU Li-Quan. Suitable varieties and high-yielding population characteristics of late season rice in the northern margin area of double-cropping rice along the Yangtze River [J]. Acta Agronomica Sinica, 2022, 48(4): 1005-1016.
[11] YUAN Da-Shuang, DENG Wan-Yu, WANG Zhen, PENG Qian, ZHANG Xiao-Li, YAO Meng-Nan, MIAO Wen-Jie, ZHU Dong-Ming, LI Jia-Na, LIANG Ying. Cloning and functional analysis of BnMAPK2 gene in Brassica napus [J]. Acta Agronomica Sinica, 2022, 48(4): 840-850.
[12] LI Rui-Dong, YIN Yang-Yang, SONG Wen-Wen, WU Ting-Ting, SUN Shi, HAN Tian-Fu, XU Cai-Long, WU Cun-Xiang, HU Shui-Xiu. Effects of close planting densities on assimilate accumulation and yield of soybean with different plant branching types [J]. Acta Agronomica Sinica, 2022, 48(4): 942-951.
[13] WANG Lyu, CUI Yue-Zhen, WU Yu-Hong, HAO Xing-Shun, ZHANG Chun-Hui, WANG Jun-Yi, LIU Yi-Xin, LI Xiao-Gang, QIN Yu-Hang. Effects of rice stalks mulching combined with green manure (Astragalus smicus L.) incorporated into soil and reducing nitrogen fertilizer rate on rice yield and soil fertility [J]. Acta Agronomica Sinica, 2022, 48(4): 952-961.
[14] DU Hao, CHENG Yu-Han, LI Tai, HOU Zhi-Hong, LI Yong-Li, NAN Hai-Yang, DONG Li-Dong, LIU Bao-Hui, CHENG Qun. Improving seed number per pod of soybean by molecular breeding based on Ln locus [J]. Acta Agronomica Sinica, 2022, 48(3): 565-571.
[15] HUANG Cheng, LIANG Xiao-Mei, DAI Cheng, WEN Jing, YI Bin, TU Jin-Xing, SHEN Jin-Xiong, FU Ting-Dong, MA Chao-Zhi. Genome wide analysis of BnAPs gene family in Brassica napus [J]. Acta Agronomica Sinica, 2022, 48(3): 597-607.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!