Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.)

Dan Zhang; Hao Cheng; Hui Wang; Hengyou Zhang; Chunying Liu; Deyue Yu

doi:10.1016/S1673-8527(09)60074-6

Volume 37 Issue 8

Aug. 2010

Turn off MathJax

Article Contents

Abstract

References

Article Navigation > Journal of Genetics and Genomics > 2010 > 37(8): 545-556

PDF( 722 KB)

Identification of genomic regions determining flower and pod numbers development in soybean (Glycine max L.)

doi: 10.1016/S1673-8527(09)60074-6

National Center for Soybean Improvement, National Key Laboratory of Crop Genetics and Germplasm Enhancement, Nanjing Agricultural University, Nanjing 210095, China

More Information

Corresponding author: E-mail address: dyyu@njau.edu.cn (Deyue Yu)
Received Date: 2010-03-15
Accepted Date: 2010-06-10
Rev Recd Date: 2010-05-11

Available Online: 2010-09-01

Publish Date: 2010-08-20

Abstract

Abstract

Flower and pod numbers per plant are important agronomic traits underlying soybean yield. So far quantitative trait loci (QTL) detected for flower and pod-related traits have mainly focused on the final stage, and might therefore have ignored genetic effects expressed during a specific developmental stage. Here, dynamic expressions of QTL for flower and pod numbers were identified using 152 recombinant inbred lines (RILs) and a linkage map of 306 markers. Wide genetic variation was found among RILs; 17 unconditional and 18 conditional QTL were detected for the two traits at different developmental stages over two years. Some QTL were detected only at one stage and others across two or more stages, indicating that soybean flower and pod numbers development may be governed by time-dependent gene expression. Three main QTL (qfn-Chr18-2, qfn-Chr20-1, and qfn-Chr19) were detected for flower number, and two main QTL (qpn-Chr11 and qpn-Chr20) were detected for pod number. The phenotypic variation explained by them ranged from 6.1% to 34.7%. The markers linked to these QTL could be used in marker-assisted selection for increasing soybean flower and pod numbers, with the ultimate aim of increasing soybean yield. Comparison of the QTL regions for flower and pod numbers traits with the related genes reported previously showed that seven and four related genes were located in the QTL regions of qfn-Chr11 and qfn-Chr19, respectively. These results provide a basis for fine mapping and cloning of flower and pod development-related genes.
- conditional QTL,
- unconditional QTL,
- developmental quantitative genetics,
- flower number,
- pod number,
- soybean

FullText(HTML)

References(36)

References

[1]	Atchley, W.R., Zhu, J. Developmental quantitative genetics, conditional epigenetic variability and growth in mice Genetics, 147 (1997),pp. 765-776
[2]	Board, J.E., Tan, Q. Assimilatory capacity effects on soybean yield components and pod number Crop Sci., 35 (1995),pp. 846-851
[3]	Brevedan, R., Egli, D., Leggett, J. Influence of N nutrition on flower and pod abortion and yield of soybeans Agron. J., 70 (1978),pp. 81-84
[4]	Chung, J., Babka, H., Graef, G. et al. The seed protein, oil, and yield QTL on soybean linkage group I Crop Sci., 43 (2003),pp. 1053-1067
[5]	Churchill, G.A., Doerge, R.W. Empirical threshold values for quantitative triat mapping Genetics, 138 (1994),pp. 963-971
[6]	Concibido, V.C., Denny, R.L., Boutin, S.R. et al. Crop Sci., 34 (1994),pp. 240-246
[7]	Fu, Y.H., Chen, Y.J. The relationship between flower pod abscission rate and growth stage of varieties Crop J., 5 (2002),pp. 12-13
[8]	Hepworth, S., Klenz, J., Haughn, G. Planta, 223 (2006),pp. 769-778
[9]	Keim, P., Diers, B.W., Olson, T.C. et al. RFLP mapping in soybean: association between marker loci and variation in quantitative traits Genetics, 126 (1990),pp. 735-742
[10]	Lee, S.H., Bailey, M.A., Mian, M.A.R. et al. Identification of quantitative trait loci for plant height, lodging, and maturity in a soybean population segregating for growth habit Theor. Appl. Genet., 92 (1996),pp. 516-523
[11]	Li, W., Sun, D., Du, Y. et al. Genome, 50 (2007),pp. 1067-1077
[12]	Lin, M., Belanger, H., Lee, Y. et al. FLOWERING LOCUS T protein may act as the long-distance florigenic signal in the cucurbits Plant Cell, 19 (2007),pp. 1488-1506
[13]	Liu, G., Zeng, R., Zhu, H. et al. Dynamic expression of nine QTL for tiller number detected with single segment substitution lines in rice Theor. Appl. Genet., 147 (2008),pp. 1432-2242
[14]	Mansur, L.M., Lark, K.G., Kross, H. et al. Theor. Appl. Genet., 86 (1993),pp. 907-913
[15]	Mo, P., Zhu, Y., Liu, X. et al. Plant Physiol., 164 (2007),pp. 478-486
[16]	Qiu, B.X., Arelli, P.R., Sleper, D.A. RFLP markers associated with soybean cyst nematode resistance and seed composition in a ‘Peking’ × ‘Essex’ population Theor. Appl. Genet., 98 (1999),pp. 356-364
[17]	Shaban, N. Analysis of the correlation and regression coefficients of the interaction between yield and some parameters of snap beans plants Trakia Journal of Sciences, 3 (2005),pp. 27-31
[18]	Sitaraman, J., Bui, M., Liu, Z. Plant Physiol., 147 (2008),pp. 672-681
[19]	Song, Q.J., Marek, L.F., Shoemaker, R.C. et al. A new integrated genetic linkage map of the soybean Theor. Appl. Genet., 109 (2004),pp. 122-128
[20]	Sun, D., Li, W., Zhang, Z. et al. Theor. Appl. Genet., 112 (2006),pp. 665-673
[21]	Sun, Q., Zhou, D. Proc. Natl. Acad. Sci. USA, 105 (2008),pp. 13679-13684
[22]	Teng, W., Han, Y., Du, Y. et al. Heredity, 102 (2008),pp. 372-380
[23]	Wang, D., Graef, G., Procopiuk, A. et al. Identification of putative QTL that underlie yield in interspecific soybean backcross populations Theor. Appl. Genet., 108 (2004),pp. 458-467
[24]	Wang, L., Wang, J.
[25]	Wang, S., Basten, C., and Zeng, Z. (2005). Windows QTL Cartographer 2.5. (Department of Statistics. North Carolina State University, Raleigh, NC).
[26]	Wang, S.Q., Gao, J.L., Liu, K.L. et al. Research on bean pod initiation and abscission in soja bean Inner Mongolia Agricultural Science and Technology, 2 (2006),p. 10
[27]	Webb, D., Baltazar, B., Rao-Arelli, A. et al. Genetic mapping of soybean cyst nematode race-3 resistance loci in the soybean PI 437.654 Theor. Appl. Genet., 91 (1995),pp. 574-581
[28]	Wu, W., Li, W., Tang, D. et al. Time-related mapping of quantitative trait loci underlying tiller number in rice Genetics, 151 (1999),pp. 297-303
[29]	Yan, J., Zhu, J., He, C. et al. Theor. Appl. Genet., 97 (1998),pp. 267-274
[30]	Yang, Q. Analysis on genetic variation in early generation of the cross materials for important agronomic traits Acta Genetica Sinica, 2 (1975),pp. 225-230
[31]	Yu, X., Li, L., Guo, M. et al. Proc. Natl. Acad. Sci. USA, 105 (2008),pp. 7618-7623
[32]	Yuan, J., Njiti, V., Meksem, K. et al. Quantitative trait loci in two soybean recombinant inbred line populations segregating for yield and disease resistance Crop Sci., 42 (2002),pp. 271-277
[33]	Zhang, D., Cheng, H., Geng, L. et al. Detection of quantitative trait loci for phosphorus deficiency tolerance at soybean seedling stage Euphytica, 167 (2009),pp. 313-322
[34]	Zhang, W.K., Wang, Y.J., Luo, G.Z. et al. Theor. Appl. Genet., 108 (2004),pp. 1131-1139
[35]	Zhu, J. Analysis of conditional genetic effects and variance components in developmental genetics Genetics, 141 (1995),pp. 1633-1639
[36]	Zhu, J. Mixed model approaches of mapping genes for complex quantitative traits Journal of Zhejiang University (Natural Sciences Edition), 33 (1999),pp. 327-335

Relative Articles

[1]	Yifeng Huang, Kaixuan Cui, Zhen Zhang, Rongyao Chai, Hongguang Xie, Jianyao Shou, Junru Fu, Guolin Li, Jiyun Liu, Shuangqing Wu, Guochang Sun, Jianfu Zhang, Yiwen Deng, Zuhua He. Identification and fine-mapping of quantitative trait loci (QTL) conferring rice false smut resistance in rice[J]. Journal of Genetics and Genomics, 2023, 50(4): 276-279. doi: 10.1016/j.jgg.2022.11.010
[2]	Chao Fang, Haiping Du, Lingshuang Wang, Baohui Liu, Fanjiang Kong. Mechanisms underlying key agronomic traits and implications for molecular breeding in soybean[J]. Journal of Genetics and Genomics. doi: 10.1016/j.jgg.2023.09.004
[3]	Yu Luo, Wei Liu, Juan Sun, Zheng-Rong Zhang, Wei-Cai Yang. Quantitative proteomics reveals key pathways in the symbiotic interface and the likely extracellular property of soybean symbiosome[J]. Journal of Genetics and Genomics, 2023, 50(1): 7-19. doi: 10.1016/j.jgg.2022.04.004
[4]	Hua Yuan, Peng Qin, Li Hu, Shijie Zhan, Shifu Wang, Peng Gao, Jing Li, Mengya Jin, Zhengyan Xu, Qiang Gao, Anping Du, Bin Tu, Weilan Chen, Bingtian Ma, Yuping Wang, Shigui Li. OsSPL18 controls grain weight and grain number in rice[J]. Journal of Genetics and Genomics, 2019, 46(1): 41-51. doi: 10.1016/j.jgg.2019.01.003
[5]	Liwen Hu, Xinyue Yao, Hairong Huang, Zhong Guo, Xi Cheng, Yang Xu, Yi Shen, Biao Xu, Demin Li. Clinical significance of germline copy number variation in susceptibility of human diseases[J]. Journal of Genetics and Genomics, 2018, 45(1): 3-12. doi: 10.1016/j.jgg.2018.01.001
[6]	Jinsong Xu, Xi Song, Yong Cheng, Xiling Zou, Liu Zeng, Xing Qiao, Guangyuan Lu, Guiping Fu, Zhen Qu, Xuekun Zhang. Identification of QTLs for Branch Number in Oilseed Rape (Brassica napus L.)[J]. Journal of Genetics and Genomics, 2014, 41(10): 557-559. doi: 10.1016/j.jgg.2014.06.006
[7]	Cong Tan, Zhongmin Han, Huihui Yu, Wei Zhan, Weibo Xie, Xun Chen, Hu Zhao, Fasong Zhou, Yongzhong Xing. QTL Scanning for Rice Yield Using a Whole Genome SNP Array[J]. Journal of Genetics and Genomics, 2013, 40(12): 629-638. doi: 10.1016/j.jgg.2013.06.009
[8]	Ching Chan, Xinpeng Qi, Man-Wah Li, Fuk-Ling Wong, Hon-Ming Lam. Recent Developments of Genomic Research in Soybean[J]. Journal of Genetics and Genomics, 2012, 39(7): 317-324. doi: 10.1016/j.jgg.2012.02.002
[9]	Junzhou Li, Yan Xie, Anyong Dai, Lifeng Liu, Zichao Li. Root and shoot traits responses to phosphorus deficiency and QTL analysis at seedling stage using introgression lines of rice[J]. Journal of Genetics and Genomics, 2009, 36(3): 173-183. doi: 10.1016/S1673-8527(08)60104-6
[10]	Laura L. Clay Montier, Janice J. Deng, Yidong Bai. Number matters: control of mammalian mitochondrial DNA copy number[J]. Journal of Genetics and Genomics, 2009, 36(3): 125-131. doi: 10.1016/S1673-8527(08)60099-5
[11]	Weijun Du, Min Wang, Sanxiong Fu, Deyue Yu. Mapping QTLs for seed yield and drought susceptibility index in soybean (Glycine max L.) across different environments[J]. Journal of Genetics and Genomics, 2009, 36(12): 721-731. doi: 10.1016/S1673-8527(08)60165-4
[12]	Peng Liu, Wei Wei, Shouqiang Ouyang, Jin-Song Zhang, Shou-Yi Chen, Wan-Ke Zhang. Analysis of expressed receptor-like kinases (RLKs) in soybean[J]. Journal of Genetics and Genomics, 2009, 36(10): 611-619. doi: 10.1016/S1673-8527(08)60153-8
[13]	Shimin Zuo, Li Zhang, Hui Wang, Yuejun Yin, Yafang Zhang, Zongxiang Chen, Yuyin Ma, Xuebiao Pan. Prospect of the QTL-qSB-9Tq utilized in molecular breeding program of japonica rice against sheath blight[J]. Journal of Genetics and Genomics, 2008, 35(8): 499-505. doi: 10.1016/S1673-8527(08)60068-5
[14]	Yang Xiang, Yumei Li, Zaiming Liu, Zhenqiu Sun. The application of the entropy-based statistic for genomic association study of QTL[J]. Journal of Genetics and Genomics, 2008, 35(3): 183-188. doi: 10.1016/S1673-8527(08)60025-9
[15]	Jun Liu, Da Ha, Zongming Xie, Chunmei Wang, Huiwen Wang, Wanke Zhang, Jinsong Zhang, Shouyi Chen. Ectopic expression of soybean GmKNT1 in Arabidopsis results in altered leaf morphology and flower identity[J]. Journal of Genetics and Genomics, 2008, 35(7): 441-449. doi: 10.1016/S1673-8527(08)60061-2
[16]	Guifu Liu, Jian Yang, Haiming Xu, Jun Zhu. Influence of Epistasis and QTL × Environment Interaction on Heading Date of Rice (Oryza sativa L.)[J]. Journal of Genetics and Genomics, 2007, 34(7): 608-615. doi: 10.1016/S1673-8527(07)60069-1
[17]	Yang Xiang, Yumei Li, Zaiming Liu, Zhenqiu Sun. An Entropy-based Index for Fine-scale Mapping of QTL[J]. Journal of Genetics and Genomics, 2007, 34(4): 373-380. doi: 10.1016/S1673-8527(07)60040-X
[18]	Jinghu Zhang, Yuanzhu Xiong, Bo Zuo, Minggang Lei, Siwen Jiang, Feng'e Li, Rong Zheng, Jialian Li, Dequan Xu. Detection of Quantitative Trait Loci Associated with Several Internal Organ Traits and Teat Number Trait in a Pig Population[J]. Journal of Genetics and Genomics, 2007, 34(4): 307-314. doi: 10.1016/S1673-8527(07)60032-0
[19]	Pengfei Xu, Yingpeng Han, Junjiang Wu, Huiying Lv, Lijuan Qiu, Ruzhen Chang, Limei Jin, Jinsheng Wang, Anliang Yu, Chen Chen, Haiyang Nan, Xiuhong Xu, Ping Wang, Dayong Zhang, Shuzhen Zhang, Wenbin Li, Weiyuan Chen. Phylogenetic Analysis of the Sequences of rDNA Internal Transcribed Spacer (ITS) of Phytophthora sojae[J]. Journal of Genetics and Genomics, 2007, 34(2): 180-188. doi: 10.1016/S1673-8527(07)60019-8
[20]	Rengao Xue, Biao Zhang. Increased Endogenous Methyl Jasmonate Altered Leaf and Root Development in Transgenic Soybean Plants[J]. Journal of Genetics and Genomics, 2007, 34(4): 339-346. doi: 10.1016/S1673-8527(07)60036-8