Welcome to Acta Agronomica Sinica,

Acta Agron Sin ›› 2017, Vol. 43 ›› Issue (02): 179-189.doi: 10.3724/SP.J.1006.2017.00179

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

QTL Mapping for Seedling Dry Weight and Fresh Weight under Salt Stress and Candidate Genes Analysis in Brassica napus L.

HOU Lin-Tao**,WANG Teng-Yue**,JIAN Hong-Ju,WANG Jia,LI Jia-Na,LIU Lie-Zhao*   

  1. College of Agronomy and Biotechnology, Southwest University, Chongqing 400715, China
  • Received:2016-04-20 Revised:2016-09-18 Online:2017-02-12 Published:2016-09-27
  • Contact: 刘列钊, E-mail: liezhao2003@126.com, Tel: 023-6825070
  • Supported by:

    The study was supported by the National Natural Science Foundation of China (31371655).

Abstract:

Salt stress is one of the main abiotic stresses affecting crop yield and it would be very important by using the salt tolerance related markers in rapeseed breeding to improve the oilseed production. In this research, the Brassica napus L high generation recombinant inbred lines (RIL) population derived from the cross of GH06 and P174 via single seed descent propagation was used for QTL mapping and candidate gene analysis. The fresh and dry weight of leaf and root were measured at 25 days after the seedlings were grown in Hoagland solution with 16 g L–1 NaCl. Composite interval mapping (CIM) was used to identify the related QTLs according to the high density SNP genetic map, and the candidate gene expression in the extreme lines tested by qRT-PCR. A total of 19 QTLs were identified in the control and salt stress treatment, and six QTLs were mapped on chromosomes A02, A04 and C03 under salt stress, with contribution rate ranged from 7.16% to 16.15%. Eight genes were identified according to the BLAST of genes in the QTL confidence intervals and the salt stress related genes in Arabidopsis. The expression of four candidate genes in the extreme lines showed that BnaA02g14680D and BnaA02g14490D under salt stress treatment for 48 or 72 hours had higher expression than the control, which indicates that the expressions are induced by salt stress. The relative expressions of gene BnaC03g64030D in sensitive extreme lines were higher than those in tolerant extreme lines. There were no changed in expression for gene BnaC03g62830D in sensitive extreme lines but increased expression at 48 hours and reduced expression at 72 hours after salt treatment in tolerant extreme lines, showing the enhance of plant salt tolerance possibly. Our research laid a foundation for the function research of salt tolerant gene in rapeseed and the breeding of salt tolerant rapeseed.

Key words: Brassica napus L, Salt stress, QTL, SNP, Candidate gene

[1]杨真, 王宝山. 中国盐渍土资源现状及改良利用对策. 山东农业科学, 2015, 47(4): 125–130
    Yang Z, Wang B S. Present status of saline soil resources and countermeasures for improvement and utilization in China. Shandong Agric Sci, 2015, 47(4): 125–130 (in Chinese with English abstract)
[2]Qadir M, Ghafoor A, Murtaza G. Amelioration strategies for saline soils: A review. Land Degrad Devel, 2000, 11: 501–521
[3]沈金雄, 傅廷栋. 我国油菜生产、改良与食用油供给安全. 中国农业科技导报, 2011, 13(1): 1–8
    Shen J X, Fu T D. Rapeseed production, improvement and edible oil supply in China. J Agric Sci Technol, 2011, 13(1): 1–8 (in Chinese with English abstract)
[4]陈宗金, 蔡士宾, 杨继书, 张巧凤, 吴纪中, 蒋彦婕, 颜伟, 吴小有. 主要农作物芽期耐盐性比较研究. 农业科学, 2012, 2(4): 59–65
    Chen Z J, Cai S B, Yang J S, Zhang Q F, Wu J Z, Jiang Y J, Yan W, Wu X Y. Comparison of salinity tolerance among main crops at germination stage. Hans J Agric Sci, 2012, 2(4): 59–65 (in Chinese with English abstract)
[5]王佳丽, 黄贤金, 钟太洋, 陈志刚. 盐碱地可持续利用研究综述. 地理学报, 2011, 66: 673–684
    Wang J L, Huang X J, Zhong T Y, Chen Z G. Review on Saline-alkali land sustainable utilization research. Acta Geograph Sin, 2011, 66: 673–684 (in Chinese with English abstract)
[6]易斌, 陈伟, 马朝芝, 傅廷栋, 涂金星. 甘蓝型油菜产量及相关性状的QTL分析. 作物学报, 2006, 32: 676–682
    Yi B, Chen W, Ma C Z, Fu T D, Tu J X. Mapping of quantitative trait loci for yield and yield components in Brassica napus L. Acta Agron Sin, 2006, 32: 676–682 (in Chinese with English abstract)
[7]Yang P, Shu C, Chen L, Xu J S, Wu J S, Liu K D. Identification of a major QTL for silique length and seed weight in oilseed rape (Brassica napus L.). Theor Appl Genet, 2012, 125: 285–296
[8]孙美玉. 甘蓝型油菜含油量QTLs定位及候选基因筛选. 中国农业科学院博士论文, 湖北武汉, 2012. pp 51–54
    Sun M Y. Mapping of QTLs and Screening of Candidate Genes for Oil Content in Brassica napus. PhD Dissertation of Chinese Academy of Agricultural Sciences, Wuhan, China, 2012. pp 51–54 (in Chinese with English abstract)
[9]Yang M, Ding G D, Shi L, Feng J, Xu F S, Meng J L. Quantitative trait loci for root morphology in response to low phosphorus stress in Brassica napus. Theor Appl Genet, 2010, 121: 181–193
[10]张凤启, 刘越英, 程晓辉, 童超波, 董彩华, 唐敏强, 黄军艳, 刘胜毅. 利用高密度SNP标记定位甘蓝型油菜株高QTL. 中国油料作物学报, 2014, 36: 695–700
    Zhang F Q, Liu Y Y, Cheng X H, Tong C B, Dong C H, Tang M Q, Huang J Y, Liu S Y. QTL mapping of plant height using high density SNP markers in Brassica napus. Chin J Oil Crop Sci, 2014, 36: 695–700 (in Chinese with English abstract)
[11]Y?ld?z M, Akçal? N, Terzi H. Proteomic and biochemical responses of canola (Brassica napus L.) exposed to salinity stress and exogenous lipoic acid. J Plant Physiol, 2015, 179: 90–99
[12]刘国红, 姜超强, 刘兆普, 梁明祥, 殷祥贞, 郑青松. 盐胁迫对油菜幼苗生长和光合特征的影响. 生态与农村环境学报, 2012, 28(2): 157–164
    Liu G H, Jiang C Q, Liu Z P, Liang M X, Yin X Z, Zheng Q S. Effects of salt stress on growth and photosynthetic traits of Canola seedlings. J Ecol Rural Environ, 2012, 28(2): 157–164 (in Chinese with English abstract)
[13]郑青松, 刘海燕, 隆小华, 刘兆普, 牛丹丹, 高影影. 盐胁迫对油菜幼苗离子吸收和分配的影响. 中国油料作物学报, 2010, 32: 65–70
    Zheng Q S, Liu H Y, Long X H, Liu Z P, Niu D D, Gao Y Y. Effects of salt stress on ionic absorption and distribution of rapeseed seedlings. Chin J Oil Crop Sci, 2010, 32: 65–70 (in Chinese with English abstract)
[14]Li Z, Mei S F, Mei Z, Liu X L, Fu T D, Zhou G S, Tu J X. Mapping of QTL associated with waterlogging tolerance and drought resistance during the seedling stage in oilseed rape (Brassica napus). Euphytica, 2014, 197(3): 341–353
[15]荐红举, 肖阳, 李加纳, 马珍珍, 魏丽娟, 刘列钊. 利用SNP遗传图谱定位盐、旱胁迫下甘蓝型油菜种子发芽率的QTL. 作物学报, 2014, 40: 629–635
    Jian H J, Xiao Y, Li J N, Ma Z Z, Wei L J, Liu L Z. QTL mapping for germination percentage under salinity and drought stresses in Brassica napus L. using a SNP genetic map. Acta Agron Sin, 2014, 40: 629–635 (in Chinese with English abstract)
[16]Moursi Y S S. Genetic Mapping of QTL Controlling Salt Tolerance and Glucosinolates in Brassica napus and Brassica oleracea. PhD Dissertation of Georg-August-University, Germany, Göttingen, 2014. pp 73–78
[17]Liu L Z, Qu C M, Wittkop B, Yi B, Xiao Y, He Y J, Snowdon R J, Li J N. High-Density SNP Map for Accurate Mapping of Seed Fibre QTL in Brassica napus L. PloS One, 2013, 8: e83052. DOI:10.1371/journal.pone.0083052
[18]Wang S, Basten C J, Zeng Z B. Windows QTL Cartographer. Ver.2.5 [computer program] Department of Statistics, North Carolina State University, Raleigh, NC, 2006. http://statgen.ncsu.edu/qtlcart/WQTLCart.htm
[19]Lander E S, Botstein D. Mapping mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics, 1989, 121: 185–199
[20]Mccouch S R, Cho Y G, Yano M, Paul E, Blinstrub M, Morishima H, Kinoshita T. Report on QTL nomenclature. Rice Genet Newslett, 1997, 14: 11–13
[21]Chalhoub B, Denoeud F, Liu S Y, Isobe I A, Tang H B, Wang X Y,Chiquet J, Belcram H, Tong C B, Samans B, Corréa M, Silva C D, Just J, Falentin C, Koh S H, Clainche I L, Bernard M, Bento P, Noel B, Labadie K, Alberti A, Charles M, Arnaud D, Guo H, Daviaud C, Alamery S, Jabbari K, Zhao M X, Edger P P, Chelaifa H, Tack D, Lassalle G, Mestiri I, Schnel N, Paslier M L, Fan G Y, Renault V, Bayer P E, Golicz A A, Manoli S, Lee T H, Thi V H D, Chalabi S, Hu Q, Fan C C, Tollenaere R, Lu Y H, Battail C, Shen J X, Sidebottom C H. D, Wang X F, Canaguier A, Chauveau A, Bérard A, Deniot G, Guan M, Liu Z S, Sun F M, Lim Y P, Lyons E, Christopher D, Town, Ian B, Wang X W, Meng J L, Ma J X, Pires J C, Graham J, King, Brunel D, Delourme R, Renard M, Aury J M, Adams K L, Batley J, Snowdon R J, Tost J, Edwards D, Zhou Y M, Hua W, Sharpe A G, Paterson A H, Guan C Y, Wincker P. Early allopolyploid evolution in the post-neolithic Brassica napus oilseed genome. Science, 2014, 345: 950–953
[22]Feng J L, Li J J, Gao Z X, Lu Y R, Yu J Y, Zheng Q, Yan S N, Zhang W J, He H, Ma L G, Zhu Z G. SKIP confers osmotic tolerance during salt stress by controlling alternative gene splicing in Arabidopsis. Mol Plant, 2015, 87: 1038–1052
[23]Hong S W, Jon J H, Kwak J M, Nam H G. Identification of a receptor-like protein kinase gene rapidly induced by abscisic acid, dehydration, high salt, and cold treatments in Arabidopsis thaliana. Plant Physiol, 1997, 113: 1203–1212
[24]Woei-Jiun G, Tuan-Hua D H. An abscisic acid-induced protein, HVA22, inhibits gibberellin-mediated programmed cell death in cereal aleurone cells. Plant Physiol, 2008, 148: 1182–1182
[25]Elfving N, Davoinea C, Benllochb R, Blomberga J, Brännströma K, Müllerc D, Nilssond A, Ulfstedtd M, Ronned H, Wingsleb G, Nilssonb O, Björklunda S. The Arabidopsis thaliana Med25 mediator subunit integrates environmental cues to control plant development. PNAS, 2011, 108: 8245–8250
[26]Ortega-Amaro MA, Rodriguez-Hernandez AA, Rodriguez-Kessler M, Hernandez-Lucero E, Rosales Mendoza S, Ibañez-Salazar A, Delgado P, Jimenez Bremont JF. Overexpression of AtGRDP2, a novel glycine-rich domain protein, accelerates plant growth and improves stress tolerance. Front Plant Sci, 2015, 5: 782–783
[27]Seifert G J, Xue H, Acet T. The Arabidopsis thaliana Fasciclin like arabinogalactan protein 4 gene acts synergistically with abscisic acid signalling to control root growth. Ann Bot, 2014, 114: 1125–1133
[28]Ohnuma T, Numata T, Osawa T, Mizuhara M, Lampela O, Juffer A H, Skriver K, Fukamizo T. A class V chitinase from Arabidopsis thaliana: gene responses, enzymatic properties, and crystallographic analysis. Planta, 2011, 234: 123–137
[29]Glass M, Barkwill S, Unda F, Mansfield S D. Endo-β-1,4-glucanases impact plant cell wall development by influencing cellulose crystallization. J Integ Plant Biol, 2015, 57: 396–410
[30]Munns R, Tester M. Mechanisms of salinity tolerance. Ann Rev Plant Biol, 2008, 59: 651–681
[31]Ashraf M, McNeilly T. Salinity tolerance in Brassica oilseeds. Crit Rev Plant Sci, 2004, 23: 157–174
[32]Tunçtürk M, Tunçtürk R, Yildirim B, Çiftçi V. Changes of micronutrients, dry weight and plant development in canola (Brassica napus L.) cultivars under salt stress. Afric J Biotechnol, 2011, 10: 3726–3730
[33]Yeo A R. Molecular biology of salt tolerance in the context of whole-plant physiology. J Exp Bot, 1998, 49: 915–929
[34]Flowers T J, Yeo A R. Breeding for salinity resistance in crop plants: Where next? Aust J Plant Physiol, 1995, 22: 875–884
[35]Osakabe Y, Mizuno S, Tanaka H, Maruyama K, Osakabe K, Todaka D, Fujita Y, Kobayashi M, Shinozaki K, Yamaguchi-Shinozaki K. Overproduction of the membrane-bound receptor-like protein kinase 1, RPK1, enhances abiotic stress tolerance in Arabidopsis. J Biol Chem, 2010, 285: 9190–9201
[36]Shi C C, Feng C C, Yang M M, Li J L, Li X X, Zhao B C, Huang Z J, Ge R C. Overexpression of the receptor-like protein kinase genes AtRPK1 and OsRPK1 reduces the salt tolerance of Arabidopsis thaliana. Plant Sci, 2014, 217: 63–70
[37]Long W H, Zou X L, Zhang X K. Transcriptome analysis of canola (Brassica napus) under salt stress at the germination stage. PloS One, 2015, 10(2): e0116217.

[1] HU Wen-Jing, LI Dong-Sheng, YI Xin, ZHANG Chun-Mei, ZHANG Yong. Molecular mapping and validation of quantitative trait loci for spike-related traits and plant height in wheat [J]. Acta Agronomica Sinica, 2022, 48(6): 1346-1356.
[2] TIAN Tian, CHEN Li-Juan, HE Hua-Qin. Identification of rice blast resistance candidate genes based on integrating Meta-QTL and RNA-seq analysis [J]. Acta Agronomica Sinica, 2022, 48(6): 1372-1388.
[3] 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.
[4] YU Chun-Miao, ZHANG Yong, WANG Hao-Rang, YANG Xing-Yong, DONG Quan-Zhong, XUE Hong, ZHANG Ming-Ming, LI Wei-Wei, WANG Lei, HU Kai-Feng, GU Yong-Zhe, QIU Li-Juan. Construction of a high density genetic map between cultivated and semi-wild soybeans and identification of QTLs for plant height [J]. Acta Agronomica Sinica, 2022, 48(5): 1091-1102.
[5] LEI Xin-Hui, WAN Chen-Xi, TAO Jin-Cai, LENG Jia-Jun, WU Yi-Xin, WANG Jia-Le, WANG Peng-Ke, YANG Qing-Hua, FENG Bai-Li, GAO Jin-Feng. Effects of soaking seeds with MT and EBR on germination and seedling growth in buckwheat under salt stress [J]. Acta Agronomica Sinica, 2022, 48(5): 1210-1221.
[6] LIU Dan, ZHOU Cai-E, WANG Xiao-Ting, WU Qi-Meng, ZHANG Xu, WANG Qi-Lin, ZENG Qing-Dong, KANG Zhen-Sheng, HAN De-Jun, WU Jian-Hui. Rapid identification of adult plant wheat stripe rust resistance gene YrC271 using high-throughput SNP array-based bulked segregant analysis [J]. Acta Agronomica Sinica, 2022, 48(3): 553-564.
[7] HUANG Li, CHEN Yu-Ning, LUO Huai-Yong, ZHOU Xiao-Jing, LIU Nian, CHEN Wei-Gang, LEI Yong, LIAO Bo-Shou, JIANG Hui-Fang. Advances of QTL mapping for seed size related traits in peanut [J]. Acta Agronomica Sinica, 2022, 48(2): 280-291.
[8] ZHENG Xiang-Hua, YE Jun-Hua, CHENG Chao-Ping, WEI Xing-Hua, YE Xin-Fu, YANG Yao-Long. Xian-geng identification by SNP markers in Oryza sativa L. [J]. Acta Agronomica Sinica, 2022, 48(2): 342-352.
[9] ZHANG Yan-Bo, WANG Yuan, FENG Gan-Yu, DUAN Hui-Rong, LIU Hai-Ying. QTLs analysis of oil and three main fatty acid contents in cottonseeds [J]. Acta Agronomica Sinica, 2022, 48(2): 380-395.
[10] XU De-Rong, SUN Chao, BI Zhen-Zhen, QIN Tian-Yuan, WANG Yi-Hao, LI Cheng-Ju, FAN You-Fang, LIU Yin-Du, ZHANG Jun-Lian, BAI Jiang-Ping. Identification of StDRO1 gene polymorphism and association analysis with root traits in potato [J]. Acta Agronomica Sinica, 2022, 48(1): 76-85.
[11] ZENG Wei-Ying, LAI Zhen-Guang, SUN Zu-Dong, YANG Shou-Zhen, CHEN Huai-Zhu, TANG Xiang-Min. Identification of the candidate genes of soybean resistance to bean pyralid (Lamprosema indicata Fabricius) by BSA-Seq and RNA-Seq [J]. Acta Agronomica Sinica, 2021, 47(8): 1460-1471.
[12] ZHANG Bo, PEI Rui-Qing, YANG Wei-Feng, ZHU Hai-Tao, LIU Gui-Fu, ZHANG Gui-Quan, WANG Shao-Kui. Mapping and identification QTLs controlling grain size in rice (Oryza sativa L.) by using single segment substitution lines derived from IAPAR9 [J]. Acta Agronomica Sinica, 2021, 47(8): 1472-1480.
[13] DAI Liang-Xiang, XU Yang, ZHANG Guan-Chu, SHI Xiao-Long, QIN Fei-Fei, DING Hong, ZHANG Zhi-Meng. Response of rhizosphere bacterial community diversity to salt stress in peanut [J]. Acta Agronomica Sinica, 2021, 47(8): 1581-1592.
[14] GENG La, HUANG Ye-Chang, LI Meng-Di, XIE Shang-Geng, YE Ling-Zhen, ZHANG Guo-Ping. Genome-wide association study of β-glucan content in barley grains [J]. Acta Agronomica Sinica, 2021, 47(7): 1205-1214.
[15] LUO Lan, LEI Li-Xia, LIU Jin, ZHANG Rui-Hua, JIN Gui-Xiu, CUI Di, LI Mao-Mao, MA Xiao-Ding, ZHAO Zheng-Wu, HAN Long-Zhi. Mapping QTLs for yield-related traits using chromosome segment substitution lines of Dongxiang common wild rice (Oryza rufipogon Griff.) and Nipponbare (Oryza sativa L.) [J]. Acta Agronomica Sinica, 2021, 47(7): 1391-1401.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!