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QTL mapping for the number of branches and pods using wild chromosome segment substitution lines in soybean [Glycine max (L.) Merr.]

Published online by Cambridge University Press:  16 July 2014

Qingyuan He
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China Life Science College of Anhui Science and Technology University, Fengyang, Auhui233100, People's Republic of China
Hongyan Yang
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
Shihua Xiang
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
Wubing Wang
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
Guangnan Xing
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
Tuanjie Zhao*
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
Junyi Gai*
Affiliation:
Soybean Research Institute, National Center for Soybean Improvement, MOA Key Laboratory for Biology and Genetic Improvement of Soybean (General), National Key Laboratory for Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing, Jiangsu210095, People's Republic of China
*
* Corresponding authors. E-mail: tjzhao@njau.edu.cn; sri@njau.edu.cn
* Corresponding authors. E-mail: tjzhao@njau.edu.cn; sri@njau.edu.cn

Abstract

Annual wild soybean characterized with more number of branches and pods may contain favourable exotic genes/alleles for improving the yield potential of cultivated soybeans. To evaluate the wild alleles/segments, the chromosome segment substitution line population SojaCSSLP3 comprising 158 lines with N24852 (wild) as the donor and NN1138-2 (cultivated) as the recurrent parent was tested under three environments. The phenotypic data along with 198 simple sequence repeat markers were analysed for qualitative trait loci (QTL)/segments associated with the number of branches on the main stem (BN) and number of pods per plant (PN) using the inclusive composite interval mapping procedure (RSTEP-LRT-ADD model) of ICIM version 3.0. The analysis was carried out for individual environments due to a significant G × E interaction. A total of eight QTL/segments associated with BN and eight QTL/segments associated with PN were detected under the three environments, with all the wild segments having positive effects. Among these, two QTL/segments for each of the two traits could be detected under two or three environments and three QTL/segments could be detected for both traits. Four QTL/segments associated with BN and one QTL/segment associated with PN were identified only in SojaCSSLP3, not reported for cultivated crosses in the literature. The detected wild segments may provide materials for further characterization, cloning and pyramiding of the alleles conferring the two traits.

Type
Research Article
Copyright
Copyright © NIAB 2014 

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References

Ao, X, Zhao, MH, Zhu, Q, Li, J, Zhang, HJ, Wang, HY, Yu, CM, Li, CH, Yao, XD, Xie, FT and Han, XR (2013) Study on plant morphological traits and production characteristics of super high-yielding soybean. Journal of Integrative Agriculture 12: 11731182.CrossRefGoogle Scholar
Asanome, N and Ikeda, T (1998) Effect of branch direction's arrangement on soybean yield and yield components. Journal of Agronomy and Crop Science 181: 95102.Google Scholar
Chen, QS, Zhang, ZC, Liu, CY, Xin, DW, Shan, DP, Qiu, HM, Shan, CY and Hu, GH (2007) QTL analysis of major agronomic traits in soybean. Agricultural Sciences in China 6: 399405 (in Chinese).Google Scholar
Concibido, VC, La Vallee, B, Mclaird, P, Pineda, N, Meyer, J, Hummel, L, Yang, J, Wu, K and Delannay, X (2003) Introgression of a quantitative trait locus for yield from Glycine soja into commercial soybean cultivars. Theoretical and Applied Genetics 106: 575582.Google Scholar
Eshed, Y and Zamir, D (1994) A genomic library of Lycopersicon pennellii in L. esculentum: A tool for fine mapping of genes. Euphytica 79: 175179.Google Scholar
Foroutan-pour, K, Dutilleul, P and Smith, DL (1999) Soybean canopy development as affected by population density and intercropping with corn: fractal analysis in comparison with other quantitative approaches. Crop Science 39: 17841791.CrossRefGoogle Scholar
Hao, DR, Cheng, H, Yin, ZT, Cui, SY, Zhang, D, Wang, H and Yu, DY (2012) Identification of single nucleotide polymorphisms and haplotypes associated with yield and yield components in soybean (Glycine max) landraces across multiple environments. Theoretical and Applied Genetics 124: 447458.Google Scholar
Jiang, CZ, Pei, CJ, Jiang, HX, Zhang, MC, Wang, T, Di, R, Liu, BQ and Yan, L (2011) QTL analysis of soybean quality and yield related characters. Acta Agriculturae Boreali-Sinica 26: 127130 (in Chinese).Google Scholar
Kan, GZ, Tong, ZF, Hu, ZB, Zhang, D, Zhang, GZ and Yu, DY (2012) Mapping QTLs for yield related traits in wild soybean (Glycine soja sieb. and Zucc.). Soybean Science 31: 333340 (in Chinese).Google Scholar
Li, HH, Ye, GY and Wang, JK (2007) A modified algorithm for the improvement of composite interval mapping. Genetics 175: 361374.Google Scholar
Li, D, Pfeiffer, TW and Cornelius, PL (2008a) Soybean QTL for yield and yield components associated with Glycine soja alleles. Crop Science 48: 571581.CrossRefGoogle Scholar
Li, WX, Zheng, DH, Van, KJ and Lee, SH (2008b) QTL mapping for major agronomic traits across two years in soybean (Glycine max L. Merr.). Journal of Crop Science and Biotechnology 11: 171176.Google Scholar
Liu, CY, Luan, HH, Pei, YF, Zhang, WY, Liu, YL, He, L, Chen, QS and Hu, GH (2007) QTL analysis of morphologic traits in soybean. Journal of Hunan Agricultural University (Natural Sciences) 33: 127133 (in Chinese).Google Scholar
Qin, J, Yang, RQ, Liu, ZX, Zhang, YF, Jiang, CX, Li, WB, Li, YH, Guan, RX, Chang, RZ and Qiu, LJ (2010) Location and transmission of QTL for multiple traits in the pedigree of soybean cultivars. Euphytica 173: 377386.Google Scholar
Sayama, T, Hwang, TY, Hiroyuki, Y, Naoya, Y, Kunihiko, K, Masakazu, T, Chika, S, Tomoaki, M, Yoshinori, T, Xia, ZJ, Yasutaka, T, Satoshi, W, Kyuya, H, Hideyuki, F and Masao, I (2010) Mapping and comparison of quantitative trait loci for soybean branching phenotype in two locations. Breeding science 60: 380389.CrossRefGoogle Scholar
Song, QJ, Marek, LF, Shoemaker, RC, Lark, KG, Concibido, VC, Delannay, X, Specht, JE and Cregan, PB (2004) A new integrated genetic linkage map of the soybean. Theoretical and Applied Genetics 109: 122128.Google Scholar
Tan, B, Guo, Y and Qiu, LJ (2013) Whole genome discovery of genes related to branching and co-localization with QTLs in soybean. Hereditas (Beijing) 35: 793804 (in Chinese).Google Scholar
Tanksley, SD and McCouch, SR (1997) Seed banks and molecular maps: unlocking genetic potential from the wild. Science 277: 10631066.CrossRefGoogle ScholarPubMed
Vieira, AJD, Oliveira, DAD, Soares, TCB, Schuster, I, Piovesan, ND, Martinez, CA, Barros, EG and Moreira, MA (2006) 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. Brazil Journal of Plant Physiology 18: 281290.Google Scholar
Wang, D, Graef, GL, Procopiuk, AM and Diers, BW (2004) Identification of putative QTL that underline yield in interspecific soybean backcross populations. Theoretical and Applied Genetics 108: 458467.Google Scholar
Wang, XZ, Zhang, XJ, Zhou, R, Sha, AH, Wu, XJ, Cai, SP, Qiu, DZ and Zhou, XA (2007) QTL analysis of seed and pod traits in soybean RIL population. Acta Agronomica Sinica 33: 441448 (in Chinese).Google Scholar
Wang, WB, He, QY, Yang, HY, Xiang, SH, Zhao, TJ, Xing, GN and Gai, JY (2012) Detection of wild segments associated with number of branches on main stem and leafstalk angle in soybean. Scientia Agricultura Sinica 45: 47494758 (in Chinese).Google Scholar
Wang, WB, He, QY, Yang, HY, Xiang, SH, Zhao, TJ and Gai, JY (2013) Development of a chromosome segment substitution line population with wild soybean (Glycine soja SiebEt Zucc.) as donor parent. Euphytica 189: 293307.CrossRefGoogle Scholar
Yang, ZL and Li, GQ (2010) The QTL analysis of important agronomic traits on a RIL population from a cross between Jinda52 and Jinda57. Acta Agriculturae Boreali-Sinica 25: 8892 (in Chinese).Google Scholar
Zhang, D, Cheng, H, Wang, H, Zhang, HY, Liu, CY and Yu, DY (2010) Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.). Journal of Genetics and Genomics 37: 545556.CrossRefGoogle ScholarPubMed
Zhou, B, Xing, H, Chen, SY and Gai, JY (2010) Density-enhanced genetic linkage map of RIL population NJRIKY and its impacts on mapping genes and QTLs in soybean. Acta Agronomica Sinica 36: 3646 (in Chinese).Google Scholar
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