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Acta Agron Sin ›› 2016, Vol. 42 ›› Issue (11): 1620-1628.doi: 10.3724/SP.J.1006.2016.01620

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

Mapping QTL Protein and Oil Contents Using Population from Four-way Recombinant Inbred Lines for Soybean (Glycine max L. Merr.)

NING Hai-Long1,BAI Xue-Lian1,LI Wen-Bin1,XUE Hong1,ZHUANG Xu1,LI Wen-Xia1,*,LIU Chun-Yan2   

  1. 1 Key Laboratory of Soybean Biology, Ministry of Education / Key Laboratory of Soybean Biology and Breeding / Genetics, Ministry of Agriculture, Northeast Agricultural University, Harbin 150030, China; 2 Heilongjiang Province Compute Center, Harbin 150028, China
  • Received:2016-03-12 Revised:2016-07-11 Online:2016-11-12 Published:2016-08-11
  • Contact: LI Wenxia, E-mail: liwenxianeau@126.com E-mail:ninghailongneau@126.com
  • Supported by:

    This study was supported by Heilongjiang Province Natural Science Foundation Projects (C2015007), Heilongjiang Province Study Abroad Returnees Science Fund Project (LC2016010), Science and Technology Research Key Project of Heilongjiang Province Department of Education (12541z001), and Postdoctoral Research Start Fund in Heilongjiang Province (LBH-Q12152, LBH-Q09165).

Abstract:

Increasing protein content (PC) and oil content (OC) are main goals in soybean improvement, so mapping quantitative trait locus (QTL) and mining elite alleles underlying PC and OC are of importance for molecular design breeding in soybean. In this research a four-way recombinant inbred line population derived from double cross (Kenf 14 × Kenf 15) × (Hein 48 × Kenf 19) with 204 lines was used to analyze the data of PC and OC from the field experiments in eight environments across Harbin and Keshan in 2013, 2014, and 2015 by interval map method based on a linkage map constructed in previous research. The 29 PC QTLs and 39 OC QTLs were detected from eight planting environments. Among the twenty-nine PC QTLs, five were detected across over two environments, which distributed on six linkage groups, i.e. A1, D2, J, N and O, with explained phenotypic variation (PVE) ranging from 7.65% to 20.08%. Four of them, i.e. qPC-A1-1, qPC-D2-1, qPC-J-1, and qPC-O-2, showed PVE over 10%. Of the thirty-nine OC QTLs, ten were found in more than two environments, which were located on linkage groups A1, A2, B1, D1b, G, I, J, and N with PVE ranging from 7.30% to 25.68%. Four out of the ten QTLs that included qOC-A2-1, qOC-B1-1, qOC-G-1, and qOC-J-1 had PVE above 10%.

Key words: Soybean, Protein and oil content, QTL, Four-way recombinant inbred line, Elite allele

[1] Mehrzad E, Elroy R, Istvan R. Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents. Theor Appl Genet, 2013, 126: 403–495 [2] Pandurangan S, Pajak A, Molnar S J. Cober Elroy R, Dhaubhadel S, Hernndez-Sebasti Cinta K, Werner M, Nelson Randall L, Huber Steven C, Marsolais F. Relationship between asparagine metabolism and protein concentration in soybean seed. J Exp Bot, 2012, 63: 3173–3184 [3] 葛振宇, 刘晓冰, 刘宝辉, 阿部纯, 马凤鸣, 孔凡江. 大豆种子蛋白质和油分性状的QTL定位. 大豆科学, 2011, 30: 901–905 Ge Z Y, Liu X B, Liu B H, Abe J, Ma F M, Kong F J. QTL mapping of protein and oil content in soybean. Soybean Sci, 2011, 30: 901–905 [4] 林延慧, 张丽娟, 李伟, 张礼凤, 徐冉. 大豆蛋白质含量的QTL定位. 大豆科学, 2010, 29: 207–209 Lin Y H, Zhang L J, Li W, Zhang L F, Xu R. QTLs mapping related to protein content of soybeans. Soybean Sci, 2010, 29: 207–209 [5] Fasoula V, Harris A. Validation and designation of quantitative trait loci for seed protein, seed oil, and seed weight from two soybean populations. Crop Sci, 2004, 4: 1218–1225 [6] Lee S H, Bailey M A, M. Mian A R, CarterJr T E, Shipe E R, Ashley D A, Parrott W A, Hussey R S, Boerma H R.. RFLP loci associated with soybean seed protein and oil content across populations and locations. Theor Appl Genet, 1996, 93: 649–657 [7] Panthee D R, Pantalone V R, West D R, Saxton A M, Sans C E. Quantitative trait loci for seed protein and oil concentration, and seed size in soybean. Crop Sci, 2005, 45: 2015–2022 [8] Maria E R, James O, Liu L J, Dong Z M, Rajcan I. Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian x Chinese crosses. Theor Appl Genet, 2013, 126: 1809–1823 [9] Shen Y R, Liu C Y, Jiang Z F, Wang L L, Ma Z Z, Yang Z, Xin D W, Jiang H W, Hu G H, Chen S H. QTL Analysis of stability for oil content in soybean. Mol Plant Breed, 2014, 12: 251–261 [10] Qi Z M, Wu Q, Han X, Sun Y N, Du X Y, Liu C Y, Jiang H W, Hu G H , Chen Q S. Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes. Euphytica, 2011, 179: 499–514 [11] Li H W, Zhao T J, Wang Y F, Yu D Y, Chen S Y, Zhou R B, Gai J Y. Genetic structure composed of additive QTL, epistatic QTL pairs and collective unmapped minor QTL conferring oil content and fatty acid components of soybeans. Euphytica, 2011, 182: 117–132. [12] Moongkanna J, Nakasathien S, Novitzky W. SSR markers linking to seed traits and total oil content in soybean. Thai J Agric Sci, 2011, 44: 233–241 [13] Lu W G, Wen Z X, Li H C, Yuan D H, Li J Y, Zhang H, Huang Z W, Cui S Y, Du W J. Identification of the quantitative trait loci (QTL) underlying water soluble protein content in soybean. Theor Appl Genet, 2013, 126:425–433 [14] Wang X Z, Jiang G L, Green M, Roy A S, David L, Hyten B. Cregan. Quantitative trait locus analysis of saturated fatty acids in a population of recombinant inbred lines of soybean. Mol Breed, 2012, 30: 1163–1179 [15] Liang H Z, Xu Y L, Yang H Q Zhang H Y, Dong W, Li C Y, Gong P Z, Liu X Y, Fang X J. Epistatic effects and QTL×environment interaction effects of QTLs for yield and agronomic traits in soybean. Acta Agron Sin, 2014, 40: 37–44 [16] Chen Q S, Zhang Z C, Liu C Y, Xin D W, Qiu H M, Shan D P. QTL analysis of major agronomic traits in soybean. Agric Sci China, 2007, 6: 399–405 [17] Vieira A, Oliveira D, Soares D, Schuster I, Piovesan N, Martinez C A, Barros E G, Moreira M A. Use of the QTL approach to the study of soybean trait relationships in two populations of recombinant inbred lines at the F7 and F8 generations. J Plant Physiol, 2006, 18: 281–290 [18] Tajuddin, W S, Yamanaka N, Harda K. Analysis of quantitative trait loci for protein and lipid contents in soybean seeds using recombinant inbred lines. Breed Sci, 2003, 3: 133–140 [19] Gai J Y, Wang Y J, Wu X L, Chen S Y. A comparative study on segregation analysis and QTL mapping of quantitative traits in plants-with a case in soybean. Front Agric China, 2007, 1: 1–7 [20] Csanadi G, Vollmann J, Stift G, Lelley T. Seed quality QTLs identified in a molecular map of early maturing soybean. Theor Appl Genet, 2001, 103: 912–919 [21] Qi Z, Han X, Hou M, Xin D, Wang Z, Zhu R, Hu Z, Jiang H, Li C, Liu C, Hu G, Chen Q. QTL analysis of soybean oil content under 17 environments. Can J Plant Sci, 2014, 94: 245–261 [22] Xu S. Mapping quantitative trait loci using four-way crosses. Genet Res, 1996, 68: 175–181 [23] 宁海龙, 李柏云, 何月鹏, 吴昊, 白雪莲, 司敬博, 庄煦, 李文霞. 大豆四向重组自交群体单株产量QTL单标记分析.大豆科学, 2016, 35: 160–164 Ning H L, Li B Y, He Y P, Wu H, Bai X L, Si J B, Zhuang X, Li W X. Single marker analysis on QTL conditioning yield per plant in soybean by four-way recombinant inbred lines population. Soybean Sci, 2016, 35: 160–164 [24] 宁海龙, 吴昊, 李文滨, 薛红, 李柏云, 李琦, 白雪莲, 李文霞. 大豆四向重组自交系群体全生育期QTL的单标记分析. 大豆科学, 2016, 34: 1081–1084 Ning H L, Wu H, Li W B, Xue H, Li B Y, Li Q, Bai X L, Li W X. Single marker analysis on QTLs controlling maturity period in soybean using a four-way recombinant inbred lines population. Soybean Sci, 2016, 34: 1081–1084 [25] 宁海龙, 梁世鑫, 蒋红鑫, 李文霞, 薛红, 李琦, 吴昊, 李文滨, 王德亮. 应用极大似然法分析大豆四向重组自交系群体株高与主茎节数的主基因遗传效应. 大豆科学, 2013, 32: 438–444 Ning H L, Liang S X, Jiang H X, Li W X, Xue H, Li Q, Wu H, Li W B, Wang D L. Genetic effects analysis of major genes underlying plant height and main stem nodes in a soybean four- way recombinant inbred lines population through maximum likelihood method. Soybean Sci, 2013, 32: 438–444 [26] 宁海龙, 李琦, 李文滨, 薛红, 李柏云, 白雪莲, 庄煦, 李文霞. 大豆四向重组自交系群体遗传图谱的构建. 大豆科学, 2015, 34: 776–781 Ning H L, Li Q, Li W B, Xue H, Li B Y, Bai X L, Zhuang X, Li W X. Construction of linkage map based on a four-way recombinant inbred lines population. Soybean Sci, 2015, 34: 776–781 [27] Cregan P B, Jarvik T, Bush A L, Lark G K. An integrated genetic linkage map of the soybean genome. Crop Sci, 1999, 39: 1464–1490 [28] Tong C F, Zhang B, Shi J S. A hidden Markov model approach to multilocus linkage analysis in a full-sib family. Tree Genet Genom, 2010, 6: 651–662 [29] Jiang B B, Yu S Z, Xiao B G, Lou X Y, Xu H M. Constructing linkage map based on a four-way cross population. J Zhejiang Univ (Agric & Life Sci), 2014, 40: 387–396 [30] Song Q J, Marek? L F, Shoemaker R C, Lark K G, Concibido V C, Delannay X, Specht J E, Cregan P B. A new integrated genetic linkage map of the soybean. Theor Appl Genet, 2004, 109: 122–128 [31] Mansur L M, Orf J H, Chase K, Jarvik T, Cregan P B, Lark K G. Genetic mapping of agronomic traits using recombinant inbred lines of soybean. Crop Sci, 1996, 36: 1327–1336 [32] 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 [33] Panthee D, Pantalone V, Saxton A, West D, Sams C. Genomic regions associated with amino acid composition in soybean. Mol Breed, 2006, 17: 79–89 [34] Reinprecht Y, Poysa V, Yu K, Rajcan I., Ablett G., Pauls K. Seed and agronomic QTL in low linolenic acid, lipoxygenase-free soybean (Glycine max L. Merrill) germplasm. Genome, 2006, 49: 1510–1527 [35] Qi Z, Wu Q, Han X, Sun Y, Du X, Liu C, Jiang H, Hu G, Chen Q. Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes. Euphytica, 2011, 179: 499–514 [36] Brummer E C, Graef G L, Orf J H, Wilcox J R, Shoemaker R C. Mapping QTL for seed protein and oil content in eight soybean populations. Crop Sci, 1997, 37: 370–378 [37] Kim H, Kim Y, Kim S, Son B, Choi Y, Kang J, Park Y, Cho Y, Choi I. Analysis of quantitative trait loci (QTLs) for seed size and fatty acid composition using recombinant inbred lines in soybean. J Life Sci, 2010, 20: 1186–1192 [38] Diers BW, Keim P, Shoemaker R C, Fehr W R. RFLP analysis of soybean seed protein and oil content. Theor Appl Genet, 1992, 83: 608–612 [39] Sebolt A M, Shoemaker R C, Diers B W. Analysis of a quantitative trait locus allele from wild soybean that increases seed protein concentration in soybean. Crop Sci, 2000, 40: 1438–1444 [40] Specht J E, Chase K, Macrander M, Graef G L, Chung J, Markwell J P, Germann M, Orf J H, Lark K G. Soybean response to water: A QTL analysis of drought tolerance. Crop Sci, 2001, 41: 493–509 [41] Chung J, Babka H L, Graef G L, Staswick P E, Lee D J, Cregan P B, Shoemaker R C, Specht J E. The seed protein, oil, and yield QTL on soybean linkage group I. Crop Sci, 2003, 43: 1053–1067 [42] Shibata M, Takayama K, Ujiie A, Yamada T, Abe J, Kitamura K. Genetic relationship between lipid content and linolenic acid concentration in soybean seeds. Breed Sci, 2008, 58: 361–366 [43] Palomeque L, Li-Jun L, Li W, Hedges B, Cober E, Rajcan I. QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted x high-yielding exotic soybean lines. Theor Appl Genet, 2009, 119: 429–436 [44] Tajuddin T, Watanabe S, Yamanaka N, Harada K. Analysis of quantitative trait loci for protein and lipid contents in soybean seeds using recombinant inbred lines. Breed Sci, 2003, 53: 133–140 [45] Bachlava E, Dewey R, Burton J, Cardinal A. Mapping and comparison of quantitative trait loci for oleic acid seed content in two segregating soybean populations. Crop Sci, 2009, 49: 433–442 [46] Rossi M, Orf J, Liu L, Dong Z, Rajcan I. Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses. Theor Appl Genet, 2013, 126: 1809–1823 [47] Panthee D, Pantalone V, Saxton A. Modifier QTL for fatty acid composition in soybean oil. Euphytica, 2006, 152: 67–73

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