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Acta Agronomica Sinica ›› 2018, Vol. 44 ›› Issue (03): 385-396.doi: 10.3724/SP.J.1006.2018.00385


QTL Mapping of Yield Traits Using Drought Tolerance Selected Backcrossing Introgression Lines in Sunflower

Pin LYU1(), Hai-Feng YU2, Jian-Hua HOU1,*()   

  1. 1 College of Agriculture, Inner Mongolia Agricultural University
    2 Institute of Crop Research, Inner Mongolia Academy of Agricultural and Animal Husbandry Sciences, Hohhot 010010, Inner Mongolia, China
  • Received:2017-05-15 Accepted:2017-11-21 Online:2018-03-12 Published:2017-12-01
  • Contact: Jian-Hua HOU E-mail:18847123096@163.com;houjh68@163.com
  • Supported by:
    This study was supported by the National Natural Science Foundation of China (31160288).


Drought is one of the most important factors to decrease the yield of sunflower. The BC3F2 selected backcrossing introgression lines of oil sunflower population including 45 lines were developed by drought-tolerance screening for yield using Helianthus annuus K55 with excellent comprehensive characters and drought sensitivity as recurrent parent and K58 with drought-tolerance as donor parent. The genotypes of selected backcrossing introgression lines were obtained with the whole genome SSR and SNP markers. QTLs affecting five yield traits were detected under both drought stress and well watered conditions in Hohhot and Wuchuan respectively by one-way ANOVA and Chi-square test based on the Genetic Hitchhiking Effect. The QTLs detected by one-way ANOVA were grouped into three types based on their behaviors: type I was the QTLs detected in both watered conditions, including four QTLs affecting hundred-seed weight (HSW) in Wuchuan and two QTLs affecting seed yield (SY) and three QTLs affecting filled seeds per plant (FSP) in Hohhot, which were considered to be able to directly contribute to drought tolerance; type II was the QTLs detected only under drought stress, including 30 QTLs in Hohhot and 27 QTLs in Wuchuan; type III was the QTLs detected only in well watered condition, including 38 QTLs in Hohhot and 64 QTLs in Wuchuan. There 274 loci were detected by chi-square test, among them 14 loci could be detected by ANOVA and chi-square test simultaneously, which might be the key loci for drought tolerance of sunflower. The results lay a foundation of efficient drought tolerance molecular breeding and provide useful drought tolerance materials for sunflower.

Key words: sunflower, drought tolerance, selected backcrossing introgression lines, yield traits, QTL

Table 1

Phenotypic performance of traits for parents and drought-tolerance population"

干旱胁迫 Drought stress 正常供水 Well watered
P1 P2 BC3F2 P1 P2 BC3F2
Seed yield (g plant-1)
E1 19.94 26.82 21.59±11.06 28.55 33.12 31.29±14.38
E2 18.99 25.05 19.69±6.16 28.60 32.07 38.38±15.08
Disk stem (cm)
E1 13.67 13.17 12.74±2.27 15.77 15.04 16.91±2.41
E2 10.03 9.19 11.04±2.54 15.07 14.71 14.33±2.35
Seed-setting rate (%)
E1 47.70 55.86 52.40±7.05 72.94 79.03 79.10±5.87
E2 52.00 61.95 62.00±9.28 74.00 80.23 84.11±6.11
Hundred-seed weight (g)
E1 4.05 3.76 3.62±0.84 5.00 4.56 4.87±1.16
E2 3.80 3.51 3.53±0.60 4.40 4.31 5.40±0.88
Filled-seeds per plant
E1 473.00 684.00 558.70±184.25 589.00 762.33 689.82±207.42
E2 469.00 695.00 531.80±148.51 571.00 733.20 780.99±183.28

Table 2

The χ2-test for drought-tolerance population"

ORS510 36.31 M53762 14.46 ORS883_1 24.15 M29997 11.78 M12324 20.64
ORS665 20.64 M63117 14.46 M26548 34.89 M29998 11.78 M26553 39.36
ORS331_3 56.38 M63118 14.46 M23014 9.38 M76524 14.46 M26549 30.70
ORS188_2 17.42 M47251 17.42 M23015 9.38 M158109 17.41 M32978 16.68
ORS1097_1 27.93 M47252 17.42 M60631 9.38 ORS749_3 50.95 M32979 16.68
M166096 14.37 M47253 17.42 M60632 9.38 M71304 70.86 M26753 27.93
M166095 9.83 M9848 17.42 M73785 9.38 M71305 70.86 M26754 31.98
M65009 9.68 M70258 18.46 M18564 14.46 M71306 54.41 M26755 31.98
M78469 9.38 M70259 18.46 M68521 14.46 ORS804 62.08 M41255 20.64
M42596 9.38 M70256 18.46 M68522 14.46 ORS710_2 24.15 M41256 20.64
M70648 9.38 M74282 21.17 M29444 20.64 ORS200_2 62.08 M44066 14.46
M13019 14.46 M92574 17.41 M29443 24.15 ORS502 45.79 M44065 14.46
M56579 11.78 M92575 23.14 M30447 24.15 M16656 11.78 M18546 17.42
M13018 11.78 M64800 27.93 M30448 24.15 M87334 15.43 M65260 14.46
M3679 11.78 M36341 18.46 M66317 24.15 M31406 20.64 M132062 10.73
M3680 11.78 M36342 19.08 M39702 31.98 M31407 20.64 M132063 8.50
M3681 11.78 M73285 17.42 M39703 31.98 M31408 20.64 M35489 11.78
M7600 11.78 M73284 11.78 M21816 31.98 M29706 9.38 M63604 14.46
M76785 9.76 M16682 9.38 M67939 31.98 ORS534_2 18.46 M64318 17.90
M62922 9.38 M16683 9.38 M67940 31.98 ORS1118 50.95 M73839 17.42
M17674 11.78 M16684 9.38 M91206 31.98 ORS761 45.79 M67864 17.90
M16151 11.78 M70270 9.76 M24719 27.93 ORS511 9.38 M43523 12.20
M82389 11.78 M70271 9.76 M20920 24.15 ORS1164 9.38 Ha494_2 31.98
M5389 11.78 M106626 8.81 M28413 24.15 M66318 17.42 M98429 14.56
M13708 14.46 M108409 8.31 M28414 24.15 M106782 14.46 M166171 19.08
M85412 11.78 ORS1143 17.42 M12140 27.93 M106783 14.46 M48356 52.54
M38509 11.78 ORS495 14.46 M12141 27.93 M17838 14.46 M48358 58.04
M45298 11.78 M55404 11.78 M1555 27.93 M17839 14.46 M48359 63.81
M19983 31.98 M17295 24.15 M72531 27.93 M17840 14.46 ORS12 27.93
M31217 31.98 Ha494_1 27.93 ORS604 56.38 M12322 20.64 ORS1143_1 14.46
M46874 31.98 Ha4057 20.64 M45299 11.78 M27515 20.64 ORS257_2 9.38
M46875 31.98 ORS1197_2 20.64 M87077 11.78 M39973 21.17 ORS1024 9.38
M66650 31.98 ORS516_3 20.64 M74063 9.38 M60579 17.42 ORS257_1 20.64
M66651 31.98 ORS769 20.64 M74064 9.38 M60580 17.42 ORS257_3 20.64
M66652 31.98 ORS1129_1 14.46 M74065 9.38 M93277 12.20 ORS525_1 9.38
M9089 31.98 ORS65_2 14.46 M31222 9.38 M10378 9.38 ORS965_4 14.46
M9090 31.98 M21636 9.38 M31223 9.38 M75855 8.01 M109397 24.15
M18321 31.98 M21637 9.38 M5387 9.38 M36906 11.78 M109396 27.93
M49169 32.61 M34808 9.38 M5388 9.38 M36907 11.78 M28142 20.64
M94707 32.61 M21634 9.38 M74062 9.38 M36908 11.78 M28141 24.15
M86618 31.98 M21635 9.38 M13016 11.78 M36909 11.78 M98430 22.41
M108153 32.61 M52731 9.38 M13017 11.78 ORS1040 11.78 M94939 28.52
M108154 32.61 M52732 9.38 M82388 9.38 M91533 13.24 M102100 17.41
M108155 32.61 M52733 9.38 M76708 29.90 ORS1242 9.38 ORS519 45.79
M115788 26.02 M52734 9.38 ORS418_2 45.79 ORS516_2 11.78 ORS575 14.46
M77329 21.75 M25595 11.78 M29707 11.78 M27654 27.93 M32713 22.41
M77330 21.75 M35009 9.38 M29708 11.78 M64799 24.15 ORS881_2 45.79
M49170 21.17 M31914 11.78 ORS1112 45.79 M67544 27.93 ORS315_4 20.64
M85256 21.17 M3202 11.78 ORS749_4 45.79 M22786 27.93 ORS486 56.38
M64415 21.17 M3203 11.78 ORS749_5 45.79 M22787 27.93 M19982 31.98
M65118 17.90 M33360 11.78 ORS1065_1 45.79 M86304 12.20 ORS881_3 45.79
M46192 17.42 M65122 11.78 M47014 9.38 M86305 12.20 ORS403_2 45.79
M46193 17.42 M70448 11.78 M47015 9.38 M82844 16.02 ORS380 27.93
M46191 17.42 M20592 9.38 M29995 11.78 M114875 17.42 ORS297 45.79
M64315 20.64 M17294 9.38 M29996 11.78 M12323 20.64


QTLs detectedl by one-way ANOVA of drought-tolerance popuaitipon"

[1] 王韵. 利用双向导入系解析水稻产量相关性状的遗传背景效应及环境互作效应. 沈阳农业大学博士学位论文, 辽宁沈阳, 2009
Wang Y.Genetic Background Effect and Environment Interaction Effect on QTL Expression of Yield Related Traits Revealed by Reciprocal Introgression Lines in Rice. PhD Dissertation of Shenyang Agricultural University, Shenyang,China, 2009 (in Chinese with English abstract)
[2] 王阳, 刘成, 王天宇, 石云素, 宋燕春, 黎裕. 干旱胁迫和正常灌溉条件下玉米产量性状的QTL分析. 植物遗传资源学报, 2007, 8: 179-183
Wang Y, Liu C, Wang T Y, Shi Y S, Song Y C, Li Y.QTL analysis of yield components in maize under different water regimes.J Plant Genet Resour, 2007, 8: 179-183 (in Chinese with English abstract)
[3] 赵秀琴, 徐建龙, 朱苓华, 黎志康. 利用高代回交导入系定位水、旱条件下影响水稻根系及产量的QTL. 中国农业科学, 2008, 41: 1887-1893
Zhao X Q, Xu J L, Zhu L H, Li Z K.QTL Mapping of yield and root traits under irrigation and drought conditions using advanced backcrossing introgression lines in rice.Sci Agric Sin, 2008, 41: 1887-1893 (in Chinese with English abstract)
[4] Adiredjo A L, Navaud O, Munos S, Langlade N B, Lamaze T, Grieu P.Genetic control of water use efficiency and leaf carbon isotope discrimination in sunflower (Helianthus annuu L.) subjected to two drought scenarios. PLoS One, 2014, 9: e101218
[5] Abdi1 N, Darvishzadeh R, Jafaril M, Pirzad A, Haddadi P. Genetic analysis and QTL mapping of agro-morphological traits in sunflower (Helianthus annuus L.) under two contrasting water treatment conditions. Plant Omics J, 2012, 5: 149-158
[6] Haddadi P, Yazdi-samadi B, Naghavi M R, Kalantari A, Maury P, Sarrafi A. QTL analysis of agronomic traits in recombinant inbred lines of sunflower under partial irrigation.Plant Biotechnol Rep, 2011, 5: 135-146
[7] 吕品, 于海峰, 于志贤, 张永虎, 张艳芳, 王婷婷, 侯建华. 向日葵高密度遗传连锁图谱构建及两种水分条件下芽期性状的QTL分析. 作物学报, 2017, 43: 19-30
Lyu P, Yu H F, Yu Z X, Zhang Y H, Zhang Y F, Wang T T, Hu J H.Construction of high-density genetic map and qtl mapping for seed germination traits in sunflower under two water conditions.Acta Agron Sin, 2017, 43: 19-30 (in Chinese with English abstract)
[8] Li Z K, Fu Z K, Gao Y M, Xu J L, Ali J, Lafittle H R, Jiang Y Z, Domingo R J, Vijayakumar C H M, Maghirang R, Zheng T Q, Zhu L H. Genome-wide introgression lines and their use in genetic and molecular dissection of complex phenotypes in rice (Oryza sativa L. ). Plant Mol Biol, 2005, 59: 33-52
[9] 刘海燕. 水稻高代回交导入系抗旱相关性状QTL定位研究. 中国农业科学院硕士学位论文, 北京, 2009
Liu H Y.QTL Mapping of Traits Related to Drought Tolerance of Advanced Backcrossing Introgression Lines in Rice. MS Thesis of Chinese Academy of Agricultural Sciences, Beijing,China, 2009 (in Chinese with English abstract)
[10] 黎志康. 我国水稻分子育种计划的策略. 分子植物育种, 2005, 3: 603-608
Li Z K.Strategies for molecular rice breeding in China.Mol Plant Breed, 2005, 3: 603-608
[11] 卓壮. 黄华占回交导入系抗旱筛选及QTL分析. 四川农业大学硕士学位论文, 四川雅安, 2013
Zhuo Z.Screening and QTL Mapping of Advanced Backcrossing Introgression Lines for Drought Tolerance in Huang Huazhan. MS Thesis of Sichuan Agricultural University, Sichuan Ya’an,China, 2013 (in Chinese with English abstract)
[12] 赵秀琴, 朱苓华, 徐建龙, 黎志康. 灌溉与自然降雨条件下水稻高代回交导入系产量QTL的定位. 作物学报, 2007, 33: 1536-1542
Zhao X Q, Zhu L H, Xu J L, Li Z K.QTL mapping of yield under irrigation and rainfed field conditions for advanced backcrossing introgression lines in rice.Acta Agron Sin. 2007, 33: 1536-1542 (in Chinese with English abstract)
[13] 王利锋, 郝宪彬, 何云霞, 华泽田, 高用明, 黎志康. 利用选择回交导入群体进行粳稻优良恢复系抗旱性改良与QTL定位. 安徽农业大学学报, 2007, 34: 311-319
Wang L F, Hao X B, He Y X, Hua Z T, Gao Y M, Li Z K.Improvement of drought tolerance for elite restorer ofjaponica rice (Oryza sativa L.) and identification of drought tolerant QTLs using selected introgression populations by backcross. J Anhui Agric Univ, 2007, 34: 311-319 (in Chinese with English abstract)
[14] 王英. 利用回交导入系筛选水稻高产、抗旱和耐盐株系及选择导入系相关性状的QTL定位. 中国农业科学院博士学位论文, 北京, 2013
Wang Y.Screening of High Yield, Drought and Salt Tolerant Plants from Backcross Introgression Lines and QTL Detection for Related Traits in Rice. PhD Dissertation of Chinese Academy of Agricultural Sciences, Beijing,China, 2013 (in Chinese with English abstract)
[15] 任洁, 赵秀琴, 丁在松, 项超, 张晶, 王超, 张俊巍, Joseph C A, 张强, 庞昀龙, 高用明, 石英尧. 利用选择导入系进行水稻耐低磷鉴定与QTL定位分析. 中国水稻科学, 2015, 29: 1-13
Ren J, Zhao X Q, Ding Z S, Xiang C, Zhang J, Wang C, Zhang J W, Joseph C A, Zhang Q, PongY L, Gao Y M, Shi Y Y. Dissection and QTL mapping of low-phosphorus tolerance using selected introgression lines in rice.Chin J Rice Sci, 2015, 29: 1-13 (in Chinese with English abstract)
[16] 李芳, 程立锐, 许美容, 周政, 张帆, 孙勇, 周永力, 朱苓华, 徐建龙, 黎志康. 利用品质性状的回交选择导入系挖掘水稻抗纹枯病 QTL. 作物学报, 2009, 35: 1729-1737
Li F, Cheng L R, Xu M R, Zhou Z, Zhang F, Sun Y, Zhou Y L, Zhu L H, Xu J L, Li Z K.QTL mining for sheath blight resistance using the backcross selected introgression lines for grain quality in rice.Acta Agron Sin, 2009, 35: 1729-1737 (in Chinese with English abstract)
[17] 李灿东, 蒋洪蔚, 刘春燕, 邱鹏程, 张闻博, 李文福, 高运来, 陈庆山, 胡国华. 大豆定向选择群体耐旱性位点基因型分析及QTL定位. 中国油料作物学报, 2009, 31: 285-292
Li C D, Jiang H W, Liu C Y, Qiu P C, Zhang W B, Li T F, Gao Y L, Chen Q S.Genotype and QTL analysis of drought tolerance loci for directional population in soybean.Chin J Oil Crop Sci, 2009, 31: 285-292 (in Chinese with English abstract)
[18] 张金巍, 韩粉霞, 陈明阳, 孙君明, 韩广振, 闫淑荣, 杨华. 利用选择回交导入群体定位大豆蛋白质含量 QTL. 中国油料作物学报, 2015, 37: 433-442
Zhang J W, Han F X, Chen M Y, Sun J M, Han G Z, Yan S R, Yang H.Detection of protein content QTL with random and extremely selected BC2F2 populations in soybean. Chin J Oil Crop Sci, 2015, 37: 433-442 (in Chinese with English abstract)
[19] 房冬梅, 吕品, 侯建华. 油葵SSR-PCR反应体系的优化及引物筛选. 中国农学通报, 2015, 31(12): 205-209
Fang D M, Lyu P, Hou J H.Optimization of SSR-PCR reaction system and primer screening in oil sunflower.Chin Agric Sci Bull, 2015, 31(12): 205-209 (in Chinese with English abstract)
[20] Schlotterer C.Hitchhiking mapping-functional genomics from the population genetics perspective.Trends Genet, 2003, 19: 32-38
[21] 邱鹏程, 张闻博, 李灿东, 蒋洪蔚, 刘春燕, 范冬梅, 曾庆力, 胡国华, 陈庆山. 利用选择导入系分析大豆芽期和苗期耐旱性的遗传重叠. 作物学报, 2011, 37: 477-483
Qiu P C, Zhang W B, Li C D, Jiang H W, Liu C Y, Fan D M, Zeng Q L, Hu G H, Chen Q S.Genetic overlap of drought- tolerance loci between germination stage and seedling stage analyzed using introgression lines in soybean. Acta Agron Sin, 2011, 37: 477-483 (in Chinese with English abstract)
[22] 彭勃, 王阳, 李永祥, 刘成, 刘志斋, 王迪, 谭巍巍, 张岩, 孙宝成, 石云素, 宋燕春, 王天宇, 黎裕. 不同水分环境下玉米产量构成因子及籽粒相关性状的QTL分析. 作物学报, 2010, 36: 1832-1842
Peng B, Wang Y, Li Y X, Liu C, Liu Z Z, Wang D, Tan W W, Zhang Y, Sun B C, Shi Y S, Song Y C, Wang T Y, Li Y.QTL analysis for yield components and kernel-related traits in maize under different water regimes.Acta Agron Sin, 2010, 36: 1832-1842 (in Chinese with English abstract)
[23] 谭巍巍, 李永祥, 王阳, 刘成, 刘志斋, 彭勃, 王迪, 张岩, 孙宝成, 石云素, 宋燕春, 杨德光, 王天宇, 黎裕. 在干旱和正常水分条件下玉米穗部性状QTL分析. 作物学报, 2011, 37: 235-248
Tan W W, Li Y X, Wang Y, Liu C, Liu Z Z, Peng B, Wang D, Zhang Y, Sun B C, Shi Y S, Song Y C, Yang D G, Wang T Y, Li Y.QTL mapping of ear traits of maize under different water regimes.Acta Agron Sin, 2011, 37: 235-248 (in Chinese with English abstract)
[24] 郑天清, 徐建龙, 傅彬英, 高用明, Veruka S, Lafitte R, 翟虎渠, 万建民, 朱苓华, 黎志康. 遗传搭车与方差分析在水稻定向选择群体的抗旱性位点分析中的初步应用. 作物学报, 2007, 33: 799-804
Zheng T Q, Xu J L, Fu B Y, Gao Y M, Veruka S, Lafitte R, Zhai H Q, Wan J M, Zhu L H, Li Z K. application of genetic hitch-hiking and ANOVA in identification of loci for drought tolerance in populations of rice from directional selection.Acta Agron Sin, 2007, 33: 779-804 (in Chinese with English abstract)
[25] 何云霞. 应用回交育种和QTL聚合改良粳稻抗旱性. 沈阳农业大学硕士学位论文, 辽宁沈阳, 2009
He Y X.Improving Drought Tolerance of Japonica Rice by BC Breeding and QTL Pyramiding. MS Thesis of Shenyang Agricultural University, Shenyang, China, 2009 (in Chinese with English abstract)
[26] 石英尧. 水稻选择导入系产量和抗倒伏性状改良及QTL定位.安徽农业大学硕士学位论文, 安徽合肥, 2013
Shi Y R.Improvement and QTL Mapping for Yield and Loding Resistance Using Selected Backcrossing Introgression Lines in Rice. MS Thesis of Anhui Agricultural University, Hefei,China, 2013 (in Chinese with English abstract)
[27] 李灿东, 蒋洪蔚, 刘春燕, 郭泰, 王志新, 吴秀红, 郑伟, 邱鹏程, 张闻博, 宋英博, 栾奕娜, 陈庆山, 胡国华. 大豆耐旱选择群体QTL定位. 作物学报, 2011, 37: 603-611
Li C D, Jiang H W, Liu C Y, Guo T, Wang Z X, Wu X H, Zheng W, Qiu P C, Zhang W B, Song Y B, Luan Y N, Chen Q S, Hu G H.QTL identification of drought tolerance to soybean in selection population. Acta Agron Sin, 2011, 37: 603-611 (in Chinese with English abstract)
[28] Sharma R, Xia X, Cano L M, Evangelisti E, Kemen E, Judelson H, Oome S, Sambles C, van den Hoogen D J, Kitner M, Klein J, Meijer H J G, Spring O, Win J, Zipper R, Bode H B, Govers F, Kamoun S, Schornack S, Studholme D J, Van den Ackerveken G, Thines M. Genome analyses of the sunflower pathogen Plasmopara halstedii provide insights into effector evolution in downy mildews and phytophthora. Genomics, 2015, 16: 2-23
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