Welcome to Acta Agronomica Sinica,

Acta Agron Sin ›› 2013, Vol. 39 ›› Issue (06): 1021-1029.doi: 10.3724/SP.J.1006.2013.01021

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

Analysis of Related Interactions and Mapping of QTLs for Seed Weight per Plant in Soybean in Different Years

FAN Dong-Mei1,MA Zhan-Zhou1,LIU Chun-Yan2,YANG Zhen1,ZENG Qing-Li1,XIN Da-Wei1,JIANG Hong-Wei2,QIU Peng-Cheng3,CHEN Qing-Shan1,4,*,HU Guo-Hua2,4,*   

  1. 1 College of Agriculture, Northeast Agricultural University, Harbin 150030, China; 2 The Crop Research and Breeding Center of Land-Reclamation, Harbin 150090, China; 3 Erdos Academy of Agriculture and Animal Husbandry Sciences, Inner Mongolia Erdos 017000, China; 4 The National Research Center of Soybean Engineering and Technology, Harbin 150050, China
  • Received:2012-08-13 Revised:2013-01-15 Online:2013-06-12 Published:2013-03-22
  • Contact: 胡国华, E-mail: hugh757@vip.163.com, Tel: 0451-55199475; 陈庆山, E-mail: qshchen@126.com, Tel: 0451-55191945

Abstract:

QTL analysis of seed weight per plant, epistatic effects and the QE interaction, have a great contribution tothe promote study of genetic for seed weight per plant in soybean. The objective of this study was to investigate the major QTLs, epistatic effects, and QE interaction effects of QTLs for seed weight per plant in soybean. To find out the steady and repeatable QTLs of this trait, we used F2:14–F2:18 RIL population containing 147 lines in this experiment in two sites in five years by CIM and MIM. Seventeen QTLs for seed weight per plant were detected by CIM and MIM in D1a, B1, B2, C2, F, G, and A1 linkage groups, respectively, accounting for 6.0–47.9% of the general phenotypic variation. Three QTLs for seed weight per plant could be detected simultaneously by CIM and MIM, accounting for 6.3%–38.3% of the general phenotypic variation. Four QTLs for seed weight per plant could be detected simultaneously in more than two years, accounting for 8.1–47.9% of the general phenotypic variation. Data from seven environments were used to detecte by QTLMapper for QE interaction effects and epistatic effects of QTLs in this study. One QE QTL and four pairs of QTLs with epistatic effects were detected, but the additive effects contribution rate and the general contribution of interaction were not significant, indicating that both major and minor QTLs with epistatic effects and QE should be considered in the improvement in soybean breeding.

Key words: Soybean, Seed weight per plant, QTL analysis, QTL×environment interaction, Epistatic effects

[1]Shan C-Y(单彩云), Wei Y-G(魏玉光), Zhang Y-J(张延军), Li X-H(李晓辉), Nie L(聂录), Dong X-L(董秀兰), Liu C(刘成). Grey correlation degree analysis on main traits of soybean varieties in HeiLongjiang Province. Soybean Sci (大豆科学), 2009, 28(5): 945–948 (in Chinese with English abstract)



[2]Hu Z-B(胡振帮), Zhu R-S(朱荣胜), Gao Y-L(高运来), Liu C-Y(刘春燕), Jiang H-W(蒋洪蔚), Han D-W(韩冬伟), Huo G-H(胡国华), Chen Q-S(陈庆山). Grey correlation degree analysis between seed weight per plant and other major agronomic traits with soybean varieties in Heilongjiang Province. J Northeast Agric Univ (东北农业大学学报), 42(11): 57–62 (in Chinese with English abstract)



[3]Xu Z-R(徐泽茹), Cao J-F(曹金锋), Wang R-F(王茹芳), Hu T-H(胡铁欢), Lu S-H(卢思慧), Gao G-J(高广居), Wu F-X(吴凤训). Grey relational grade analysis on yield and main agronomic characters of soybean. J Hebei Agric Sci (河北农业科学), 2010, 14(2): 1–2 (in Chinese with English abstract)



[4]Keim P, Diers B W, Olson T C, Shoemaker R C. RFLP mapping in soybean: association between marker loci and variation in quantitative traits. Genetics, 1990, 126: 735–742



[5]Orf J H, Chase K, Jarvik T, Mansur L M, Cregan P B, Adler F R, Lark K G. Genetics of soybean agronomic traits: I. Comparison of three related recombinant inbred populations. Crop Sci, 1999, 39: 1642–1651



[6]Wang D, Graef G L, Procopiuk A M, Diers B W. Identification of putative QTL that underlie yield in interspecific soybean backcross populations. Theor Appl Genet, 2004, 108: 458–467



[7]Kabelka E A, Diers B W, Fehr W R, LeRoy A R, Baianu I C, You T, Neece D J, Nelson R L. Putative alleles for increased yield from soybean plant introductions. Crop Sci, 2004, 44: 784–791



[8]Li D D, Pfeiffer T W, Cornelius P L. Soybean QTL for yield and yield components associated with Glycine soja alleles. Crop Sci, 2008, 48: 571–581



[9]Huang Z-W(黄中文), Zhao T-J(赵团结), Yu D-Y(喻德跃), Chen S-Y(陈受宜), Gai J-Y(盖钧镒). Detection of QTLs of yield re-lated traits in soybean. Sci Agric Sin (中国农业科学), 2009, 42(12): 4155–4165 (in Chinese with English abstract)



[10]Sun Y N, Pan J B, Shi X L, Du X Y, Wu Q, Qi Z M, Jiang H W, Xin D W, Liu C Y, Hu G H, Chen Q S. Multi-environment mapping and meta-analysis of 100-seed weight in soybean. Mol Biol Rep, 2012, DOI 10.1007/s11033-012-1808-4



[11]Zhou R(周蓉), Wang X-Z (王贤智), Chen H-F(陈海峰), , Zhang X-J(张晓娟), Shan Z-H(单志慧), Wu X-J(吴学军), Cai S-P(蔡淑平), Qiu D-Z(邱德珍), Zhou X-A(周新安), Wu J-S(吴江生). QTL analysis of yield, yield components, and lodging in soybean. Acta Agron Sin (作物学报), 2009, 35(5): 821–830 (in Chinese with English abstract)



[12]Qi Z-M(齐照明), Sun Y-N(孙亚男), Chen L-J(陈立君), Guo Q(郭强), Liu C-Y(刘春燕), Hu G-H(胡国华), Chen Q-S(陈庆山). Meta-analysis of 100-seed weight QTLs in soybean. Sci Agric Sin (中国农业科学), 2009, 42(11): 3795–3803 (in Chinese with English abstract)



[13]Zhang W K, Wang Y J, Luo G Z, Zhang J S, He C Y, Wu X L, Gai J Y, Chen S Y. QTL mapping of ten agronomic traits on the soybean (Glycine max L. Merr.) genetic map and their association with EST markers. Theor Appl Genet, 2004, 108: 1131–1139



[14]Li W X, Zheng D H, Van K, Lee S H, QTL Mapping for major agronomic traits across two years in soybean (Glycine max L. Merr.). J Crop Sci Biotech , 2008, 11: 171–90



[15]Wang Z(王珍). Construction of Soybean SSR Based Map and QTL Analysis Important Agronomic Traits. MS Thesis of Guangxi University, 2004 (in Chinese with English abstract)



[16]Zhu X-L(朱晓丽). Constructing of Genetic Linkage Map and QTL Mapping of Important Agronomic Traits in Two Soybean Populations. MS Thesis of Northeast Agricultural University, 2006 (in Chinese with English abstract)



[17]Jing H-X(荆慧贤). QTL analysis of Quality and Yield related Traits in Soybean. MS Thesis of Hebei Normal Univerisity, 2008 (in Chinese with English abstract)



[18]Wang X(汪霞), Xu Y(徐宇), Li G-J(李广军), Li H-N(李河南), Gen W-Q(艮文全), Zhag Y-M(章元明). Mapping quantitative trait loci for 100-seed weight in soybean (Glycine max L. Merr.). Acta Agron Sin (作物学报), 2010, 36(10): 1674–1682 (in Chinese with English abstract)



[19]Yan Z-L(杨竹丽), Li G-Q(李贵全). The QTL analysis of important agronomic traits on a RIL population from a cross between Jinda 52 and Jinda 57. Acta Agric Boreali Sin (华北农学报), 2010, 25(2): 88–92 (in Chinese with English abstract)



[20]Chen Q-S(陈庆山), Zhang Z-C(张忠臣), Liu C-Y(刘春燕), Xin D-W(辛大伟), Shan D-P(单大鹏), Qiu H-M(邱红梅), Shan C-Y(单彩云). QTL analysis of major agronomic traits in soybean. Sci Agric Sin (中国农业科学), 2007, 6(4): 399–405 (in Chinese with English abstract)



[21]Jiang C-Z(蒋春志), Pei C-J(裴翠娟), Jing H-X(荆慧贤), Zhang M-C(张孟臣), Wang T(王涛), Di R(邸锐), Liu B-Q(刘兵强), Yan L(闫龙). QTL analysis of soybean Quality and Related character. Acta Agric Boreali Sin (华北农学报), 2011, 26(5): 127–130 (in Chinese with English abstract)



[22]Mian M A R, Bailey M A, Tamulonis J P, Shipe E R, Carter T E Jr, Parrott W A, Ashley D A, Hussey R S, Boerma H R. Molecular markers associated with seed weight in two soybean populations. Theor Appl Genet, 1996, 93: 1011–1016



[23]Campbell B T, Baenziger P S, Gill K S, Eskridge K M, Budak H, Erayman M, Dweikat I, Yen Y. Identification of QTLs and Environmental interactions associated with agronomic traits on chromosome 3A of wheat. Crop Sci, 2003,  43:1493–1505



[24]Hu X(胡霞), Shi Y-M(石瑜敏), Jia Q(贾倩), Xu QQ(徐琴), Wang Y(王韵), Chen K(陈凯), Sun R(孙勇), Zhu L-H(朱苓华), Xu J-L(徐建龙), Li Z-K(黎志康). Analyses of QTLs for rice panicle and milling quality traits and their interaction with environment. Acta Agron Sin (作物学报). 2011, 37(7): 1175−1185 (in Chinese with English abstract)



[25]Bateson W. Mendel's Principles of Heredity. Cambridge: Cambirdge University Press.1909



[26]Eshed Y, Zamir D. Less-than-additive epistatic interactions of quantitative trait loci in tomato. Genetics, 1996, 143: 1807−1817



[27]Yu S B, Li J X, Xu C G, Tan Y F, Gao Y J, Li X H, Zhang Q. Importance of epistasis as the genetic basis of heterosis in anelite rice hybrid. Proc Natl Acad Sci USA, 1997, 94: 9226–9231



[28]Wang D L, Zhu J, Li Z K, Paterson A H. Mapping QTLs with epistatic effects and QTL-environment interactions by mixed linear model approaches. Theor Appl Genet, 1999, 99: 1255−1264



[29]Jansen R C, Van Ooijien J M, Stam P. Genotype-by-environment interaction in genetic mapping of multiple quantitative trait loci. Theor Appl Genet, 1995, 91: 33−37



[30]Veronica C, Pablo F R, Valeria B, Gerardo L. Cervigni, Ruben M, Carlos A J, Viviana C E. Mapping of main and epistatic effect QTLs associated to grain protein and gluten strength using a RIL population of durum wheat. J Appl Genet, 2011, 52: 287–298



[31]Gao Y-M(高用明), Zhu J(朱军), Song Y-S(宋佑胜), He C-X(何慈信), Shi C-H(石春海), Xing Y-Z(邢永忠). Use of permanent F2 population to analyze epistasis and their inter-action effects with environments for QTLs controlling heading date in rice. Acta Agron Sin (作物学报), 2004, 30(9): 849−854 (in Chinese with English abstract)



[32]Shan Q-P(单大鹏), Qi Z-M(齐照明), Qiu H-M(邱红梅), Shan C-Y(单彩云), Liu C-Y(刘春燕), Hu G-H(胡国华), Chen Q-S(陈庆山). Epistatic effects of QTLs and QE interaction effects on oil content in soybean. Acta Agron Sin (作物学报), 2008, 34(6): 952–957 (in Chinese with English abstract)



[33]Zhao Z-M(赵芳明), Zhang G-Q(张桂权), Zeng R-Z(曾瑞珍), Yang Z-L(杨正林), Ling Y-H(凌英华), Sang X-C(桑贤春), He G-H(何光华). Analysis of epistatic and additive effects of QTLs for grain shape using single segment substitution lines in rice (Oryza sativa L.) Acta Agron Sin (作物学报), 2011, 37(3): 469–476 (in Chinese with English abstract)



[34]Chen Q-S(陈庆山), Zhang Z-C(张忠臣), Liu C-Y(刘春燕), Wang W-Q(王伟权), Li W-B(李文滨). Construction and analysis of soybean genetic map using recombinant inbred line of Charleston × Dongnong 594. Sci Agric Sin (中国农业科学), 2005, 38(7): 1312–1316 (in Chinese with English abstract)



[35]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



[36]Li J-Q(李杰勤), Zhang Q-J(张启军), Ye S-P(叶少平), Zhao B(赵兵), Liang Y-S(梁永书), Peng Y(彭勇), Wu F-Q(吴发强), Wang S-Q(王世全), Li P(李平). Comparative research on four mapping methods of QTLs. Acta Agron Sin (作物学报), 2005, 11: 1473–1477



[37]Kao C H, Zeng Z B, Teasdaler R D. Multiple interval mapping for quantitative trait loci. 1999, 152: 203–216



[38]Fulton T M, Beck-Bunn T, Emmatty D, Eshed Y, Lopez J, Petiard V, Uhlig J, Zamir D, Tanksley S D. QTL analysis of an advanced backcross of Lycopersicon peruvianum to the cultivated tomato and comparisons with QTLs found in other wild species. Theor Appl Genet, 1997, 95: 5–6, 881–894



[39]Guzman P S, Diers B W, Neece D J, Martin S K St, LeRoy A R, Grau C R, Hughes T J, Nelson R L. QTL associated with yield in three backcross-derived populations of soybean. Crop Sci, 2007, 47: 111–122



[40]Liao C Y, Wu P, Hu B, Yi K K. Effects of genetic background and environment on QTL and epistasis for rice (Oryza sativa L.) panicle number. Theor Appl Genet, 2001, 103: 104–111



[41]Jiang L-R(江良荣), Wang W(王伟), Huang J-X(黄建勋), Hang R-Y(黄荣裕), Zheng J-S(郑景生), Huang Y-M(黄育民), Wang H-C(王侯聪). Analysis of epistatic and QE interaction effects of QTLs for gain shape in rice. Mol Plant Breed (分子植物育种). 2009, 7(4): 690–698 (in Chinese with English abstract)



[42]Chase K, Adler F R, Lark K G. Epistat: A computer program for identifying and testing interactions between pairs of quantitative trait loci. Theor Appl Genet, 94: 724–730



[43]Liu G F, Yang J, Xu H M, Zhu J. Influence of epistasis and QTL × environment interaction on heading date of rice (Oryza sativa L.). J Genet Genom, 2007, 34: 608–615



[44]Li Z, Pinson S R, Park W D, Paterson A H, Stansel J W. Epistasis for three grain yield components in rice (Oryza sativa L.). Genetics, 1997, 145: 453–465

[1] Tang Kuan-Qiang, Li Gong-Yun, Song Mei-Yi, Zhao Xue, Chang Chun-Ling. Genome-wide association analysis and prediction model construction for soybean plant height [J]. Acta Agronomica Sinica, 2026, 52(6): 1743-1756.
[2] Yao Shu, Guo Kai-Yue, Zhai Hui-Hui, Yao Jia-Hui, Deng Wen-Qi, Yan Ling, Huang Chi, Gao Yang, Yu Yan-Ran, Zhao Zhen-Bang, Li Ying-Hui, Wang Xiao-Bo, Li Jia-Jia. Comprehensive evaluation of low-iron tolerance and screening of elite germplasm at the soybean seedling stage [J]. Acta Agronomica Sinica, 2026, 52(5): 1373-1387.
[3] Zhang Qing, Yang Yu, Guo Qian, Yue Pei-Yao, Yin Cong-Cong, Niu Jing-Ping, Zhao Jin-Zhong, Du Wei-Jun, Yue Ai-Qin. Cloning and functional analysis of the soybean GmARA6a gene in response to salt stress [J]. Acta Agronomica Sinica, 2026, 52(2): 480-493.
[4] WANG Ke-Jing, LI Xiang-Hua. Endangerment assessment of the perennial species G. tabacina and G. tomentella of the genus Glycine Willd. in China [J]. Acta Agronomica Sinica, 2025, 51(8): 2009-2019.
[5] MENG Ran, LI Zhao-Jia, FENG Wei, CHEN Yue, LIU Lu-Ping, YANG Chun-Yan, LU Xue-Lin, WANG Xiu-Ping. Comprehensive evaluation of salt tolerance at different growth stages of soybean and screening of salt-tolerant germplasm [J]. Acta Agronomica Sinica, 2025, 51(8): 1991-2008.
[6] HE Hong-Li, ZHANG Yu-Han, YANG Jing, CHENG Yun-Qing, ZHAO Yang, LI Xing-Nuo, SI Hong-Liang, ZHANG Xing-Zheng, YANG Xiang-Dong. Creation and physiological analysis of an e1-as gene mutant in soybean [J]. Acta Agronomica Sinica, 2025, 51(8): 2228-2239.
[7] HU Meng, SHA Dan, ZHANG Sheng-Rui, GU Yong-Zhe, ZHANG Shi-Bi, LI Jing, SUN Jun-Ming, QIU Li-Juan, LI Bin. QTL mapping and candidate gene screening for branch number in soybean [J]. Acta Agronomica Sinica, 2025, 51(7): 1747-1756.
[8] WANG Qiong, ZOU Dan-Xia, CHEN Xing-Yun, ZHANG Wei, ZHANG Hong-Mei, LIU Xiao-Qing, JIA Qian-Ru, WEI Li-Bin, CUI Xiao-Yan, CHEN Xin, WANG Xue-Jun, CHEN Hua-Tao. Genome-wide association analysis and candidate genes prediction of flowering time and maturity date traits in soybean (Glycine max L.) [J]. Acta Agronomica Sinica, 2025, 51(6): 1558-1568.
[9] YIN Cong-Cong, LI Rui-Qi, YUE Pei-Yao, LI Chen, NIU Jing-Ping, ZHAO Jin-Zhong, DU Wei-Jun, YUE Ai-Qin. Establishment and application of a visual detection method for soybean mosaic virus SC15 based on closed dumbbell mediated isothermal amplification [J]. Acta Agronomica Sinica, 2025, 51(5): 1248-1260.
[10] XU Rui, HE Miao-Hua, WANG Hao, LI Wei, REN Jie, XIA Zhi-Qiang. Spatial transcriptomic analysis of soybean embryonic responses to X-ray irradiation [J]. Acta Agronomica Sinica, 2025, 51(12): 3121-3132.
[11] LIN Yang, SHI Xiao-Lei, CHEN Qiang, LIU Bing-Qiang, YANG Qing, YU Hui-Juan, YAN Long, WU Xiao-Xia, YANG Chun-Yan. QTL mapping of soybean protein, oil, and fatty acid components [J]. Acta Agronomica Sinica, 2025, 51(11): 2899-2910.
[12] LI Wei, ZHU Yu-Peng, SUN Bin-Cheng, WEN You-Xiang, WU Zong-Sheng, XU Yi-Fan, SONG Wen-Wen, XU Cai-Long, WU Cun-Xiang. Transgenic soybean combined with no-tillage flat planting promotes the simplification of soybean production in Northeast China [J]. Acta Agronomica Sinica, 2025, 51(10): 2738-2749.
[13] CHEN Min, JIA Rong, ZHANG Jin-Chuan, ZHANG Chen-Yu, CHU Jun-Cong, YAO Wei, GE Jun-Yong, WANG Xing-Yu, YANG Ya-Dong, ZENG Zhao-Hai, ZANG Hua-Dong. Yield advantages and nitrogen utilization characteristics of oat and legume strip intercropping in semi-arid zones [J]. Acta Agronomica Sinica, 2025, 51(10): 2727-2737.
[14] QIAN Yu-Ping, SU Bing-Bing, GAO Ji-Xing, RUAN Fen-Hua, LI Ya-Wei, MAO Lin-Chun. Effects of maize and soybean intercropping on soil physicochemical properties and microbial carbon metabolism in karst region [J]. Acta Agronomica Sinica, 2025, 51(1): 273-284.
[15] DING Shu-Qi, CHENG Tong, WANG Bi-Kun, YU De-Bin, RAO De-Min, MENG Fan-Gang, ZHAO Yin-Kai, WANG Xiao-Hui, ZHANG Wei. Effects of planting density on photosynthetic production and yield formation of soybean varieties from different eras [J]. Acta Agronomica Sinica, 2025, 51(1): 161-173.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!