PDF (2.2 MB)
Collect
Submit Manuscript
Show Outline
Outline
Abstract
Keywords
References
Show full outline
Hide outline
Research paper | Open Access

Genomic dissection of widely planted soybean cultivars leads to a new breeding strategy of crops in the post-genomic era

Xinpeng Qia,1Bingjun Jianga,b,1Tingting Wua,1Shi Suna,1Caijie WangaWenwen SongaCunxiang WuaWensheng HouaQijian SongcHon-Ming Lamb()Tianfu Hana()
MARA Key Laboratory of Soybean Biology (Beijing), Institute of Crop Sciences, Chinese Academy of Agricultural Sciences, Beijing 100081, China
Centre for Soybean Research of the State Key Laboratory of Agrobiotechnology and School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong, China
Soybean Genomics and Improvement Lab, USDA-ARS, Beltsville, MD 20705, USA

1 These authors contributed equally to this work.

Show Author Information

Abstract

Soybeans specially the widely planted cultivars have been dramatically improved in agronomic performance and is well adapted to local planting environments after long-time domestication and breeding. Uncovering the unique genomic features of popular cultivars will help to understand how soybean genomes have been modified through breeding. We re-sequenced 134 soybean cultivars that were released and most widely planted over the last century in China. Phylogenetic analyses established that these cultivars comprise two geographically distinct sub-populations: Northeast China (NE) versus the Huang-Huai-Hai River Valley and South China (HS). A total of 309 selective regions were identified as being impacted by geographical origins. The HS sub-population exhibited higher genetic diversity and linkage disequilibrium decayed more rapidly compared to the NE sub-population. To study the association between phenotypic differences and geographical origins, we recorded the vegetative period under different growing conditions for two years, and found that clustering based on the phenotypic data was closely correlated with cultivar geographical origin. By iteratively calculating accumulated genetic diversity, we established a platform panel of cultivars and have proposed a novel breeding strategy named “Potalaization” for selecting and utilizing the platform cultivars that represent the most genetically diversity and the highest available agronomic performance as the “plateau” for accumulating elite loci and traits, breeding novel widely adapted cultivars, and upgrading breeding technology. In addition to providing new genomic information for the soybean research community, the “Potalaization” strategy that we devised will also be practical for integrating the conventional and molecular breeding programs of crops in the post-genomic era.

References

[1]

T. Hymowitz, On the domestication of the soybean, Econ. Bot. 24 (1970) 408–421.

[2]
L. Wang, Soybean cultivar improvement and innovation, in: L. Wang, Q. Guo (Eds.), Contemporary Soybean Research in China, Jindun Press, Beijing, China, 2007, pp. 280–344 (in Chinese).
[3]

Z. Liu, H. Li, Z. Wen, X. Fan, Y. Li, R. Guan, Y. Guo, S. Wang, D. Wang, L. Qiu, Comparison of genetic diversity between Chinese and American soybean (Glycine max (L.)) accessions revealed by high-density SNPs, Front. Plant Sci. 8 (2017) 2014.

[4]

K. Rincker, R. Nelson, J. Specht, D. Sleper, T. Cary, S.R. Cianzio, S. Casteel, S. Conley, P. Chen, V. Davis, C. Fox, G. Graef, C. Godsey, D. Holshouser, G.-L. Jiang, S.K. Kantartzi, W. Kenworthy, C. Lee, R. Mian, L. McHale, S. Naeve, J. Orf, V. Poysa, W. Schapaugh, G. Shannon, R. Uniatowski, D. Wang, B. Diers, Genetic improvement of U.S. soybean in maturity groups Ⅱ, Ⅲ, and Ⅳ, Crop Sci. 54 (2014) 1419–1432.

[5]

Z. Cui, J. Gai, T. Carter, J. Qiu, T. Zhao, The Released Chinese Soybean Cultivars and Their Pedigree Analyses (1923–1995), China Agriculture Press, Beijing, China, 1998, pp. 23–31 (in Chinese).

[6]

C. Wang, T. Wu, S. Sun, R. Xu, J. Ren, C. Wu, B. Jiang, W. Hou, T. Han, Seventy-five years of improvement of yield and agronomic traits of soybean cultivars released in the Yellow-Huai-Hai river valley, Crop Sci. 56 (2016) 2354–2364.

[7]

T. Wu, X. Yang, S. Sun, C. Wang, Y. Wang, H. Jia, W. Man, L. Fu, W. Song, C. Wu, H. Yan, B. Jiang, W. Hou, G. Ren, T. Han, Temporal-spatial characterization of seed proteins and oil in widely grown soybean cultivars across a century of breeding in China, Crop Sci. 57 (2017) 748–759.

[8]

C. Wang, T. Wu, C. Wu, B. Jiang, S. Sun, W. Hou, T. Han, R. Singh, Changes in photo-thermal sensitivity of widely grown Chinese soybean cultivars due to a century of genetic improvement, Plant Breed. 134 (2015) 94–104.

[9]

J. Schmutz, S.B. Cannon, J. Schlueter, J. Ma, T. Mitros, W. Nelson, D.L. Hyten, Q. Song, J.J. Thelen, J. Cheng, D. Xu, U. Hellsten, G.D. May, Y. Yu, T. Sakurai, T. Umezawa, M.K. Bhattacharyya, D. Sandhu, B. Valliyodan, E. Lindquist, M. Peto, D. Grant, S. Shu, D. Goodstein, K. Barry, M. Futrell-Griggs, B. Abernathy, J. Du, Z. Tian, L. Zhu, N. Gill, T. Joshi, M. Libault, A. Sethuraman, X.C. Zhang, K. Shinozaki, H.T. Nguyen, R.A. Wing, P. Cregan, J. Specht, J. Grimwood, D. Rokhsar, G. Stacey, R.C. Shoemaker, S.A. Jackson, Genome sequence of the palaeopolyploid soybean, Nature 463 (2010) 178–183.

[10]

H.M. Lam, X. Xu, X. Liu, W. Chen, G. Yang, F.L. Wong, M.W. Li, W. He, N. Qin, B.o. Wang, J. Li, M. Jian, J. Wang, G. Shao, J. Wang, S.M. Sun, G. Zhang, Resequencing of 31 wild and cultivated soybean genomes identifies patterns of genetic diversity and selection, Nat. Genet. 42 (2010) 1053–1059.

[11]

Y. Li, S. Zhao, J. Ma, D. Li, L. Yan, J. Li, X. Qi, X. Guo, L. Zhang, W. He, R. Chang, Q. Liang, Y. Guo, C. Ye, X. Wang, Y. Tao, R. Guan, J. Wang, Y. Liu, L. Jin, X. Zhang, Z. Liu, L. Zhang, J. Chen, K. Wang, R. Nielsen, R. Li, P. Chen, W. Li, J. Reif, M. Purugganan, J. Wang, M. Zhang, J. Wang, L. Qiu, Molecular footprints of domestication and improvement in soybean revealed by whole genome re-sequencing, BMC Genomics 14 (2013) 579.

[12]

Z. Zhou, Y.U. Jiang, Z. Wang, Z. Gou, J. Lyu, W. Li, Y. Yu, L. Shu, Y. Zhao, Y. Ma, C. Fang, Y. Shen, T. Liu, C. Li, Q. Li, M. Wu, M. Wang, Y. Wu, Y. Dong, W. Wan, X. Wang, Z. Ding, Y. Gao, H. Xiang, B. Zhu, S.H. Lee, W. Wang, Z. Tian, Resequencing 302 wild and cultivated accessions identifies genes related to domestication and improvement in soybean, Nat. Biotechnol. 33 (2015) 408–414.

[13]

Y. Han, X. Zhao, D. Liu, Y. Li, D.A. Lightfoot, Z. Yang, L. Zhao, G. Zhou, Z. Wang, L. Huang, Z. Zhang, L. Qiu, H. Zheng, W. Li, Domestication footprints anchor genomic regions of agronomic importance in soybeans, New Phytol. 209 (2016) 871–884.

[14]

J.Y. Kim, S. Jeong, K.H. Kim, W.J. Lim, H.Y. Lee, N. Jeong, J.K. Moon, N. Kim, Dissection of soybean populations according to selection signatures based on whole-genome sequences, Gigascience 8 (2019) giz151.

[15]

E.Y. Hwang, Q. Song, G. Jia, J.E. Specht, D.L. Hyten, J. Costa, P.B. Cregan, A genome-wide association study of seed protein and oil content in soybean, BMC Genomics 15 (2014) 1.

[16]

J. Zhang, Q. Song, P.B. Cregan, R.L. Nelson, X. Wang, J. Wu, G.L. Jiang, Genome-wide association study for flowering time, maturity dates and plant height in early maturing soybean (Glycine max) germplasm, BMC Genomics 16 (2015) 217.

[17]

C. Fang, Y. Ma, S. Wu, Z. Liu, Z. Wang, R. Yang, G. Hu, Z. Zhou, H. Yu, M. Zhang, Y. Pan, G. Zhou, H. Ren, W. Du, H. Yan, Y. Wang, D. Han, Y. Shen, S. Liu, T. Liu, J. Zhang, H. Qin, J. Yuan, X. Yuan, F. Kong, B. Liu, J. Li, Z. Zhang, G. Wang, B. Zhu, Z. Tian, Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean, Genome Biol. 18 (2017) 161.

[18]

D.B. Egli, Soybean yield trends from to 2003 in mid-western USA, Field Crops Res. 106 (1972) 53–59.

[19]

M. Bu, T. Pan, A study on the regionalization of soybean producing area in China, Soybean Sci. 1 (1982) 105-121 (in Chinese with English abstract).

[20]

C. Wang, S. Sun, B. Wu, R. Chang, T. Han, Pedigree analysis of the most planted soybean cultivars in China since 1940s, Chin. J. Oil Crop Sci. 35 (2013) 246-252 (in Chinese with English abstract).

[21]

A.M. Bolger, M. Lohse, B. Usadel, Trimmomatic: a flexible trimmer for Illumina sequence data, Bioinformatics 30 (2014) 2114–2120.

[22]

H. Li, R. Durbin, Fast and accurate short read alignment with Burrows-Wheeler transform, Bioinformatics 25 (2009) 1754–1760.

[23]

A. McKenna, M. Hanna, E. Banks, A. Sivachenko, K. Cibulskis, A. Kernytsky, K. Garimella, D. Altshuler, S. Gabriel, M. Daly, M.A. DePristo, The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data, Genome Res. 20 (2010) 1297–1303.

[24]

M. Krzywinski, J. Schein, İ. Birol, J. Connors, R. Gascoyne, D. Horsman, S.J. Jones, M.A. Marra, Circos: an information aesthetic for comparative genomics, Genome Res. 19 (2009) 1639–1645.

[25]

Tao Lin, Guangtao Zhu, Junhong Zhang, Xiangyang Xu, Qinghui Yu, Zheng Zheng, Zhonghua Zhang, Yaoyao Lun, Shuai Li, Xiaoxuan Wang, Zejun Huang, Junming Li, Chunzhi Zhang, Taotao Wang, Yuyang Zhang, Aoxue Wang, Yancong Zhang, Kui Lin, Chuanyou Li, Guosheng Xiong, Yongbiao Xue, Andrea Mazzucato, Mathilde Causse, Zhangjun Fei, James J Giovannoni, Roger T Chetelat, Dani Zamir, Thomas Städler, Jingfu Li, Zhibiao Ye, Yongchen Du, Sanwen Huang, Genomic analyses provide insights into the history of tomato breeding, Nat. Genet. 46 (2014) 1220–1226.

[26]

S. Purcell, B. Neale, K. Todd-Brown, L. Thomas, M.A.R. Ferreira, D. Bender, J. Maller, P. Sklar, P.I.W. de Bakker, M.J. Daly, P.C. Sham, PLINK: a tool set for whole-genome association and population-based linkage analyses, Am. J. Hum. Genet. 81 (2007) 559–575.

[27]

J. Felsenstein, PHYLIP-phylogeny inference package (Version 3.2), Cladistics 5 (1989) 164–166.

[28]

X. Zheng, D. Levine, J. Shen, S.M. Gogarten, C. Laurie, B.S. Weir, A high-performance computing toolset for relatedness and principal component analysis of SNP data, Bioinformatics 28 (2012) 3326–3328.

[29]

J.K. Pritchard, M. Stephens, P. Donnelly, Inference of population structure using multilocus genotype data, Genetics 155 (2000) 945–959.

[30]

J.C. Barrett, B. Fry, J. Maller, M.J. Daly, Haploview: analysis and visualization of LD and haplotype maps, Bioinformatics 21 (2005) 263–265.

[31]

P. Danecek, A. Auton, G. Abecasis, C.A. Albers, E. Banks, M.A. DePristo, R.E. Handsaker, G. Lunter, G.T. Marth, S.T. Sherry, G. McVean, R. Durbin, G.P.A. Group, The variant call format and VCFtools, Bioinformatics 27 (2011) 2156–2158.

[32]

C. Xie, M. Tammi, CNV-seq, a new method to detect copy number variation using high-throughput sequencing, BMC Bioinformatics 10 (2009) 80.

[33]

H. Chen, N. Patterson, D. Reich, Population differentiation as a test for selective sweeps, Genome Res. 20 (2010) 393–402.

[34]

D. Grant, R.T. Nelson, S.B. Cannon, R.C. Shoemaker, SoyBase, the USDA-ARS soybean genetics and genomics database, Nucleic Acids Res. 38 (2009) D843-D846.

[35]

W. Xie, G. Wang, M. Yuan, W. Yao, K. Lyu, H. Zhao, M. Yang, P. Li, X. Zhang, J. Yuan, Q. Wang, F. Liu, H. Dong, L. Zhang, X. Li, X. Meng, W. Zhang, L. Xiong, Y. He, S. Wang, S. Yu, C. Xu, J. Luo, X. Li, J. Xiao, X. Lian, Q. Zhang, Breeding signatures of rice improvement revealed by a genomic variation map from a large germplasm collection, Proc. Natl. Acad. Sci. U. S. A. 112 (2015) e5411-e5419.

[36]

S. Zhao, F. Zheng, W. He, H. Wu, S. Pan, H.M. Lam, Impacts of nucleotide fixation during soybean domestication and improvement, BMC Plant Biol. 15 (2015) 81.

[37]

J. Ye, L. Fang, H. Zheng, Y. Zhang, J. Chen, Z. Zhang, J. Wang, S. Li, R. Li, L. Bolund, J. Wang, WEGO: a web tool for plotting GO annotations, Nucleic Acids Res. 34 (2006) W293-W297.

[38]

B.L. Browning, S.R. Browning, Detecting identity by descent and estimating genotype error rates in sequence data, Am. J. Hum. Genet. 93 (2013) 840–851.

[39]

T. Tian, Y. Liu, H. Yan, Q. You, X. Yi, Z. Du, W. Xu, Z. Su, agriGO v2.0: a GO analysis toolkit for the agricultural community, 2017 update, Nucleic Acids Res. 45 (2017) W122-W129.

[40]

G. Yu, L. Wang, Y. Han, Q. He, clusterProfiler: an R package for comparing biological themes among gene clusters, OMICS 16 (2012) 284–287.

[41]
W.R. Fehr, C.E. Caviness, Stages of Soybean Development, Iowa State University of Science and Technology, Iowa (1977).
[42]

Y. Wang, L. Cheng, J. Leng, C. Wu, G. Shao, W. Hou, T. Han, Genetic analysis and quantitative trait locus identification of the reproductive to vegetative growth period ratio in soybean (Glycine max (L.) Merr.), Euphytica 201 (2015) 275–284.

[43]

W. Liu, B. Jiang, L. Ma, S. Zhang, H. Zhai, X. Xu, W. Hou, Z. Xia, C. Wu, S. Sun, T. Wu, L. Chen, T. Han, Functional diversification of Flowering Locus T homologs in soybean: GmFT1a and GmFT2a/5a have opposite roles in controlling flowering and maturation, New Phytol. 217 (2018) 1335–1345.

[44]

Q. Li, C. Fan, X. Zhang, X. Wang, F. Wu, R. Hu, Y. Fu, Identification of a soybean MOTHER OF FT AND TFL1 homolog involved in regulation of seed germination, PLoS ONE 9 (2014) e99642.

[45]

H. Nan, D. Cao, D. Zhang, Y. Li, S. Lu, L. Tang, X. Yuan, B. Liu, F. Kong, GmFT2a and GmFT5a redundantly and differentially regulate flowering through interaction with and upregulation of the bZIP transcription factor GmFDL19 in soybean, PLoS ONE 9 (2014) e97669.

[46]

H. Sun, Z. Jia, D. Cao, B. Jiang, C. Wu, W. Hou, Y. Liu, Z. Fei, D. Zhao, T. Han, GmFT2a, a soybean homolog of FLOWERING LOCUS T, is involved in flowering transition and maintenance, PLoS ONE 6 (2011) e29238.

[47]

J. Li, X. Wang, W. Song, X. Huang, J. Zhou, H. Zeng, S. Sun, H. Jia, W. Li, X. Zhou, S. Li, P. Chen, C. Wu, Y. Guo, T. Han, L. Qiu, Genetic variation of maturity groups and four E genes in the Chinese soybean mini core collection, PLoS ONE 12 (2017) e0172106.

[48]

T. Wu, S. Sun, C. Wang, W. Lu, B. Sun, X. Song, X. Han, T. Guo, W. Man, Y. Cheng, J. Niu, L. Fu, W. Song, B. Jiang, W. Hou, C. Wu, T. Han, Characterizing changes from a century of genetic improvement of soybean cultivars in Northeast China, Crop Sci. 55 (2015) 2056–2067.

[49]

C. Hao, C. Jiao, J. Hou, T. Li, H. Liu, Y. Wang, J. Zheng, H. Liu, Z. Bi, F. Xu, J. Zhao, L. Ma, Y. Wang, U. Majeed, X. Liu, R. Appels, M. Maccaferri, R. Tuberosa, H. Lu, X. Zhang, Resequencing of 145 landmark cultivars reveals asymmetric sub–genome selection and strong founder genotype effects on wheat breeding in China, Mol. Plant 13 (2020) 1733–1751.

The Crop Journal
Pages 1079-1087
Cite this article:
Qi X, Jiang B, Wu T, et al. Genomic dissection of widely planted soybean cultivars leads to a new breeding strategy of crops in the post-genomic era. The Crop Journal, 2021, 9(5): 1079-1087. https://doi.org/10.1016/j.cj.2021.01.001
Metrics & Citations  
Article History
Copyright
Rights and Permissions
Return