Welcome to Acta Agronomica Sinica，

Acta Agron Sin ›› 2011, Vol. 37 ›› Issue (02): 235-248.doi: 10.3724/SP.J.1006.2011.00235

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

QTL Mapping of Ear Traits of Maize under Different Water Regimes

TAN Wei-Wei1,2,WANG Yang2,LI Yong-Xiang2,LIU Cheng3,LIU Zhi-Zhai2,4,PENG Bo2,WANG Di2,ZHANG Yan2,SUN Bao-Cheng3,SHI Yun-Su2,SONG Yan-Chun2,YANG De-Guang1,*,WANG Tian-Yu2, and LI Yu2,*   

  1. 1 College of Agronomy, Northeast Agricultural University, Harbin 150030, China; 2 Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China; 3Institute of Food Crops, Xinjiang Academy of Agricultural Sciences, Urumqi 830000, China; 4 Southwest University, Chongqing 400716, China
  • Received:2010-06-13 Revised:2010-09-25 Online:2011-02-12 Published:2010-12-12
  • Contact: 杨德光, E-mail: ydgl@tom.com; 黎裕, E-mail: yuli@mail.caas.net.cn, Tel: 010-62131196

PDF

2750

Cited

14

Abstract: Ear traits are closely associated with maize yield. Therefore, genetic dissection of ear traits can provide clues to maize high-yield breeding and is especially important in breeding for drought tolerance. In this study, seven ear related traits including ear length (EL), ear diameter (ED), row number (KRN), kernel number per row (KRE), grain yield per ear (GW), cob diameter (AD) and weight per ear (EW), were investigated using two sets of F2:3 populations, which were derived from crosses of Ye478×Huangzaosi (Y/H) and Qi319×Huangzaosi (Q/H), respectively. The two populations were evaluated under different water conditions in Xinjiang in 2007 and 2008. The results showed that those ear traits under drought were phenotypically lower than those under normal water regime and ear length, ear diameter, weight per ear had positive correlation with GW. A total of 75 QTL were identified under different water regimes using mixed linear model with two methods of single-experiment analysis and water regime joint analysis, including 20 QTL detected under normal water regime and 55 QTL detected under drought stress. The QTL detected in Y/H were located on chromosome 1, 2, 5, 6, 7, and 10, and the QTL detected in Q/H were distributed on chromosome 2, 3, 4, 5, 6, 7, 9, and 10. However, only four and nineteen QTL was identified in the two populations under drought stress respectively, significantly lower than that detected under normal water regime. Meanwhile, in the joint analysis, only three QTL had significant interaction with environments and six QTL had epistatic interaction, showing that the genetic feature of ear traits was complex. In Y/H, two congruent QTL, qKRE1-5-1 and qKRE1-7-1, were detected under different water levels, with the phenotypic contribution from 6.15% to 19.48%, while in Q/H, three congruent QTL, qKRE2-5-1, qGW2-10-1, and qKRE2-3-1, were detected under different water levels, with the phenotypic contribution from 7.14% to 16.65%. These results implied that these QTL were little influenced by environment and could stably expressed, which can be used in marker-assisted selection.

Key words: Maize, Ear traits, Drought stress, Quantitative trait loci

[1]Qi W(齐伟), Zhang J-W(张吉旺), Wang K-J(王空军), Liu P(刘鹏), Dong S-T(董树亭). Effects of drought stress on the grain yield and root physiological traits of maize varieties with different drought tolerance. Chin J Appl Ecol (应用生态学报), 2010, 21(1): 48-52 (in Chinese with English abstract)
[2]Xiao J-F(肖俊夫), Liu Z-D(刘战东), Liu Z-G(刘祖贵), Chen Y-M(陈玉民), Liu X-F(刘小飞). Analysis on irrigation input problems and drought in growth period of maize in China. J Irrigation & Drainage (灌溉排水学报), 2009, 5: 21-24 (in Chinese with English abstract)
[3]Liu Z-H(刘宗华), Tang J-H(汤继华), Wei X-Y(卫晓轶), Wang C-L(王春丽), Tian G-W(田国伟), Hu Y-M(胡彦民), Chen W-C(陈伟程). QTL mapping of ear traits under low and high nitrogen conditions in maize. Sci Agric Sin (中国农业科学), 2007, 40(11): 2409-2417 (in Chinese with English abstract)
[4]Blum A. Plant Breeding for Stress Environments. In: Boca Raton, USA: FL, CRC Press, 1988
[5]Tang H (汤华), Huang Y-Q(黄益勤), Yan J-B(严建兵), Liu Z-H(刘宗华), Tang J-H(汤继华), Zheng Y-L(郑用琏), Li J-S(李建生). Genetic analysis of yield traits with elite maize hybrid—Yuyu 22. Acta Agron Sin (作物学报), 2004, 30(9): 922-926 (in Chinese with English abstract)
[6]Cui Z-H(崔震海), Zhang L-J(张立军), Fan J-J(樊金娟), Ruan Y-Y(阮燕晔), Ma X-L(马兴林). Correlation analysis of grain yield and ear characters of maize during seedling stage with different water supply. Acta Agric Boreali-Sin (华北农学报), 2008, 23(1): 123-127 (in Chinese with English abstract)
[7]Frova C, Krajewski P, N di Fonzo, Villa M, Sari-Gorla M. Genetic analysis of drought tolerance in maize by molecular markers: I. Yield components. Theor Appl Genet, 1999, 99: 280-288
[8]Guo J F, Su G Q, Zhang J P, Wang GY. Genetic analysis and QTL mapping of maize yield and associate agronomic traits under semi-arid land condition. African J Biotech, 2008, 12: 1829-1838
[9]Lu G H, Tang J H, Yan J B, Ma X Q, Li J S, Chen S J, Ma J C, Liu Z X, E L Z, Zhang Y R, Dai J R. Quantitative trait loci mapping of maize yield and its components under different water treatments at flowering time. J Integr Plant Biol, 2006, 48:1233-1243
[10]Shi Y-S石云素), Li Y(黎裕), Wang T-Y(王天宇), Song Y-C(宋燕春). Standard of Description for Maize Germplasm and Data. Beijing: China Agriculture Press, 2006. pp 1-98 (in Chinese)
[11]Knapp S J, Stroup W W, Ross W M. Exact confidence intervals for heritability on a progeny mean basis. Crop Sci, 1985, 25: 192-194
[12]Lander E S, Green P, Abrahanson J, Barlow A, Daly M J, Lincoln S E, Newberg L A. MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations. Genomics, 1987, 1: 174-181
[13]Yang J, Zhu J, Williams R W. Mapping the genetic architecture of complex traits in experimental populations. Bioinformatics, 2007, 23: 1527-1536
[14]Wang C S, Rutledge J J, Gianola D. Bayesian analysis of mixed linear models via Gibbs sampling with an application to little size in Iberian pigs. J Genet Sel Evol, 1994, 26: 91-115
[15]Stuber C W, Edwards M D, Wendel J F. Molecular marker facilitated investigations of quantitative trait loci in maize: II. Factors influencing yield and its component traits. Crop Sci, 1987, 27: 639-648
[16]McCouch S R, Cho Y G, Yano M, Paul E, Blinstrub M, Morishima H, Kinoshita T. Report on QTL nomenclature. Rice Genet Newsl, 1997, 14: 11-13
[17]Yan J B, Tang H, Huang Y Q, Zheng Y L, Li J S. Quantitative trait loci mapping and epistatic analysis for grain yield and yield components using molecular markers with an elite maize hybrid. Euphytica, 2006, 149: 121-131
[18]Messmer R, Fracheboud Y, Bänziger M, Vargas M, Stamp P, Ribaut J M. Drought stress and tropical maize: QTL-by-environment interactions and stability of QTL across environments for yield components and secondary traits. Theor Appl Genet, 2009, 119: 913-930
[19]Sabadin P K, de Souza C L J, de Souza A P, Franco A A G. QTL mapping for yield components in a tropical maize population using microsatellite markers. Hereditas, 2008, 145: 194-203
[20]Li Y L, Li X H, Li J Z, Fu J F, Wang Y Z, Wei M G. Dent corn genetic background influences QTL detection for grain yield and yield components in high-oil maize. Euphytica, 2009, 169: 273-284
[21]Beavis W D, Smith O S, Grant D, Fincher R. Identification of quantitative trait loci using a small sample of topcrosses and F4 progeny from maize. Crop Sci, 1994, 34: 882-896
[22]Ribaut J M, Jiang C, Gonzalez-de-Leon D, Edmeades G O, Hoisington D A. Identification of quantitative trait loci under drought conditions in tropical maize: 2. Yield components and marker-assisted selection strategies. Theor Appl Genet, 1997, 94: 887-896
[23]Ajmone-Marsan P, Monfredini G, Ludwig W F, Melchinger A E, Franceschini P, Pagnotto G, Motto M. In an elite cross of maize a major quantitative trait locus controls one-fourth of the genetic variation for grain yield. Theor Appl Genet, 1995, 90: 415-424
[24]Mihaljevic R, Utz H F, Melchinger A E. Congruency of quantitative trait loci detected for agronomic traits in testcrosses of five populations of European maize. Crop Sci, 2004, 44: 114-124
[25]Upadyayula N, da Silva H S, Bohn M O, Rocheford T R. Genetic and QTL analysis of maize tassel and ear inflorescence architecture. Theor Appl Genet, 2006, 112: 592-606
[26]Li Y-X(李永祥), Wang Y(王阳), Shi Y-S(石云素), Song Y-C(宋燕春), Wang T-Y(王天宇), Li Y(黎裕). Correlation analysis and QTL mapping for traits of kernel structure and yield components in maize. Sci Agric Sin (中国农业科学), 2009, 42(2): 408-418 (in Chinese with English abstract)
[27]Tuberosa R, Salvi S, Sanguineti M C, Landi P, Maccaferri M. Conti S. Mapping QTL regulating morpho-physiological traits and yield: case studies, shortcomings and perspectives in drought-stress maize. Annu Bot, 2002, 89: 941-963
[28]Moreau L, Charcosset A, Gallais A. Use of trial clustering to study QTL × environment effects for grain yield and related traits in maize. Theor Appl Genet, 2004, 110: 92-10
[29]Cockerham C C, Zeng Z B. Design III with marker loci. Genetics, 1996, 143: 1437-1456
[30]Luo L J, Li Z K, Mei H W, Shu Q Y, Tabien R, Zhong D B, Ying C S, Stansel J W, Khush G S, Paterson A H. Overdominant epistatic loci are the primary genetic basis of inbreeding depression and heterosis in rice: II. Grain yield components. Genetics, 2001, 158: 1755-1771
[31]Johnson W C, Gepts P. The role of epistasis in controlling seed yield and other agronomic traits in an Andean×Mesoamerican cross of common bean (Phaseolus vulgrais L.). Euphytica, 2004, 125: 69-79
[32]Wang J, van Ginkel M, Trethowan R, Ye G, Delacy I, Podlich D, Cooper M. Simulating the effects of dominance and epistasis on selection response in the CIMMYT wheat breeding program using QuCim. Crop Sci, 2004, 44: 1889-1892
[33]Doebley J, Stec A, Gustus C. Teosinte branched-1 and the origin of maize: evidence for epistasis and the evolution of dominance. Genetics, 1995, 141: 333-346
[34]Eta-Ndu J T, Openshaw S J. Epistasis for grain yield in two F2 populations of maize. Crop Sci, 1999, 39: 346-352
[35]Ma X Q, Tang J H, Teng W T, Yan J B, Meng Y J, Li J S. Epistatic interaction is an important genetic basis of grain yield and its components in maize. Mol Breed, 2007, 20: 41-51
[36]Xiang D-Q(向道权), Cao H-H(曹海河), Cao Y-G(曹永国), Yang J-P(杨俊品), Huang L-J(黄烈健), Wang S-C(王守才) , Dai J-R(戴景瑞). Constructure of SSR genetic linkage map and mapping of maize yield. Acta Genet Sin (遗传学报), 2001, 28(8): 778-784 (in Chinese with English abstract)
[37]Albler B S B, Edwards M D, Stuber C W. Isoenzymatic identification of quantitative trait loci in across of elite maize inbreds. Crop Sci, 1991, 31: 267-274
[1] Liang Jin-Yu, Yin Jia-De, Wang Hong-Li, Zhang Guo-Ping, Hou Hui-Zhi, Dong Bo, Ma Ming-Sheng. Estimation of leaf nitrogen content in dryland forage maize using UAV-based hyperspectral imaging and machine learning [J]. Acta Agronomica Sinica, 2026, 52(6): 1788-1801.
[2] Yang Yang, Chang Shi-Hui, Tian Hong-Li, Yi Hong-Mei, Wang Lu, Ren Jie, Fan Ya-Ming, Liu Ya-Wei, Wang Feng-Ge, Zhao Jiu-Ran. Genetic diversity analysis of nationally approved maize varieties in different ecological regions [J]. Acta Agronomica Sinica, 2026, 52(5): 1352-1364.
[3] Yang Xin-Yu, Cui Wen-Tao, Dilinigeer Alimu, Wang Kai-Xiang, Wu Peng-Hao, Ren Jiao-Jiao. Genome-wide association and genomic selection analysis of the number of leaves above the ear in maize [J]. Acta Agronomica Sinica, 2026, 52(5): 1573-1590.
[4] Han Ya-Xin, He Guan-Hua, Zhang Xiao-Qiong, Zhang Deng-Feng, Li Yong-Xiang, Liu Xu-Yang, Wang Tian-Yu, Li Yu, Zou Hua-Wen, Li Chun-Hui. Identification of maize lateral root density genes resources through integrated RNA-seq and BSA-seq analyses [J]. Acta Agronomica Sinica, 2026, 52(5): 1341-1352.
[5] Sun Shu-Feng, Xu Zhen-Nan, Huang Jia-Xin, Weng Jian-Feng, Li Xin-Hai. Genome-wide identification of the maize MAPK gene family and its response to Fusarium verticillioides infection [J]. Acta Agronomica Sinica, 2026, 52(5): 1291-1308.
[6] Zhang Ning-Ning, Teng Yu-Fei, Ren Na-Na, Wei Xing-Zhuo, Yan Shu-Hao, Fan Ke-Xin, Wang Yong-Hong, Chen Wen-Kang, Zhang Xing-Hua, Zhu Wan-Chao, Xu Shu-Tu, Xue Ji-Quan. Phenotypic evaluation and plasticity analysis of drought resistance in 201 maize inbred lines [J]. Acta Agronomica Sinica, 2026, 52(5): 1309-1325.
[7] Zhang Hong-Rong, Wang Fei-Er, Li Pan, Qiu Hai-Long, Zhu Jing, Zhao Lian-Hao, Nan Yun-You, He Wei, Fan Zhi-Long, Hu Fa-Long, Chai Qiang, Yin Wen. Photosynthetic characteristics of 20% reduced irrigation combined with 25% organic substitution for chemical fertilizer in increasing silage maize yield [J]. Acta Agronomica Sinica, 2026, 52(5): 1487-1500.
[8] Cai Hong-Wei, Yu Ai-Zhong, Jiang Ke-Qiang, Wang Peng-Fei, Wang Yu-Long, Huo Jian-Zhe, Pang Xiao-Neng, Yin Bo, Shang Yong-Pan. Key mechanisms underlying the enhancement of sweet maize yield through partial substitution of chemical fertilizers with organic manure in arid irrigation districts [J]. Acta Agronomica Sinica, 2026, 52(4): 1166-1180.
[9] Tian Hong-Li, Yang Yang, Fan Ya-Ming, Yi Hong-Mei, Guo Dan-Dan, Wang Feng-Ge, Zhao Jiu-Ran. A novel set of tri-allelic variant SNP loci suitable for maize variety identification [J]. Acta Agronomica Sinica, 2026, 52(4): 993-1005.
[10] Guo Xiang-Yang, Tu Liang, Wang Dong, Liu Peng-Fei, Wang An-Gui, Yi Qiang, Ren Hong, Li Gang, Zhu Yun-Fang, Wu Xun, Jiang Yu-Lin, Tian Feng, Chen Ze-Hui. Application and prospects of Suwan germplasm in maize breeding in China [J]. Acta Agronomica Sinica, 2026, 52(3): 655-664.
[11] Meng Cheng, Wang Zhe. Genome-wide identification and expression analysis of the ZmPFK gene family under biotic and abiotic stresses in maize [J]. Acta Agronomica Sinica, 2026, 52(3): 764-779.
[12] Li Xin-Hao, Xing Meng-Ke, Zhou Zi-Hui, Li Si-Ye, Ren Hao, Wang Hong-Zhang, Lai Hua-Jiang. Exogenous melatonin enhances heat tolerance of maize at the seedling stage by coordinating light and dark reactions [J]. Acta Agronomica Sinica, 2026, 52(3): 839-856.
[13] Ma Liang, Ma Lu, Zhang Shu-Yu, Zhang Hui-Min, Wang Ren-Ming, Song Xu-Dong, Zhang Zhen-Liang, Mao Yu-Xiang, Lu Hu-Hua, Chen Guo-Qing, Hao De-Rong, Zhou Guang-Fei. Transcriptome analysis and identification of candidate genes associated with husk number in maize [J]. Acta Agronomica Sinica, 2026, 52(3): 790-801.
[14] Liu Ji-Chang, Li Si-Ye, Li Xue-Ting, Wang Hong-Zhang, Liu Peng, Zhang Ji-Wang, Zhao Bin, Ren Bai-Zhao, Ren Hao. Effects of salt stress on root growth and nutrient absorption efficiency of different salt-tolerant summer maize varieties [J]. Acta Agronomica Sinica, 2026, 52(2): 565-577.
[15] Lin Zi-Qing, Zhong Xing-Yu, Liu Fan, Ren Zi-Ao, Ma Rui, Deng Xiu-Feng, Wang Dong-Wei, Liu Shao-Peng, Chen Kang, Zhang Ming-Cai, Li Zhao-Hu, Zhou Yu-Yi, Duan Liu-Sheng. Development of ultra-high-yield technology for a wheat-maize double cropping system achieving a 2-ton annual grain yield per mu in the coastal plain of Northern Shandong peninsula, China [J]. Acta Agronomica Sinica, 2026, 52(2): 631-643.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Add: No. 80 Xueyuan South Rd, Beijing 100081, P. R. China E-mail: zwxb301@caas.cn
Supported by Beijing Magtech Co.Ltd