Genetic and Genomic Resources for Soybean Breeding Research

被引:11
作者
Petereit, Jakob [1 ]
Marsh, Jacob, I [1 ]
Bayer, Philipp E. [1 ]
Danilevicz, Monica F. [1 ]
Thomas, William J. W. [1 ]
Batley, Jacqueline [1 ]
Edwards, David [1 ]
机构
[1] Univ Western Australia, Sch Biol Sci, Perth, WA 6009, Australia
来源
PLANTS-BASEL | 2022年 / 11卷 / 09期
基金
澳大利亚研究理事会;
关键词
soybean; germplasm; genomics; assemblies; pangenome; genetics; breeding; genetic variation; databases; WIDE ASSOCIATION; RESISTANCE; SELECTION; DATABASE; WILD; DOMESTICATION; ARCHITECTURE; ACCESSIONS; DIVERSITY; GERMPLASM;
D O I
10.3390/plants11091181
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Soybean (Glycine max) is a legume species of significant economic and nutritional value. The yield of soybean continues to increase with the breeding of improved varieties, and this is likely to continue with the application of advanced genetic and genomic approaches for breeding. Genome technologies continue to advance rapidly, with an increasing number of high-quality genome assemblies becoming available. With accumulating data from marker arrays and whole-genome resequencing, studying variations between individuals and populations is becoming increasingly accessible. Furthermore, the recent development of soybean pangenomes has highlighted the significant structural variation between individuals, together with knowledge of what has been selected for or lost during domestication and breeding, information that can be applied for the breeding of improved cultivars. Because of this, resources such as genome assemblies, SNP datasets, pangenomes and associated databases are becoming increasingly important for research underlying soybean crop improvement.
引用
收藏
页数:15
相关论文
共 125 条
[1]   SGMD: the soybean Genomics and Microarray database [J].
Alkharouf, NW ;
Matthews, BF .
NUCLEIC ACIDS RESEARCH, 2004, 32 :D398-D400
[2]  
Arumuganathan K., 1991, PLANT MOL BIOL REP, V9, P208, DOI DOI 10.1007/BF02672069
[3]   A Population Structure and Genome-Wide Association Analysis on the USDA Soybean Germplasm Collection [J].
Bandillo, Nonoy ;
Jarquin, Diego ;
Song, Qijian ;
Nelson, Randall ;
Cregan, Perry ;
Specht, Jim ;
Lorenz, Aaron .
PLANT GENOME, 2015, 8 (03)
[4]   Modelling of gene loss propensity in the pangenomes of three Brassica species suggests different mechanisms between polyploids and diploids [J].
Bayer, Philipp E. ;
Scheben, Armin ;
Golicz, Agnieszka A. ;
Yuan, Yuxuan ;
Faure, Sebastien ;
Lee, HueyTyng ;
Chawla, Harmeet Singh ;
Anderson, Robyn ;
Bancroft, Ian ;
Raman, Harsh ;
Lim, Yong Pyo ;
Robbens, Steven ;
Jiang, Lixi ;
Liu, Shengyi ;
Barker, Michael S. ;
Schranz, M. Eric ;
Wang, Xiaowu ;
King, Graham J. ;
Pires, J. Chris ;
Chalhoub, Boulos ;
Snowdon, Rod J. ;
Batley, Jacqueline ;
Edwards, David .
PLANT BIOTECHNOLOGY JOURNAL, 2021, 19 (12) :2488-2500
[5]   Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding [J].
Bayer, Philipp E. ;
Valliyodan, Babu ;
Hu, Haifei ;
Marsh, Jacob I. ;
Yuan, Yuxuan ;
Vuong, Tri D. ;
Patil, Gunvant ;
Song, Qijian ;
Batley, Jacqueline ;
Varshney, Rajeev K. ;
Lam, Hon-Ming ;
Edwards, David ;
Nguyen, Henry T. .
PLANT GENOME, 2022, 15 (01)
[6]   Plant pan-genomes are the new reference [J].
Bayer, Philipp E. ;
Golicz, Agnieszka A. ;
Scheben, Armin ;
Batley, Jacqueline ;
Edwards, David .
NATURE PLANTS, 2020, 6 (08) :914-920
[7]   Genomic prediction using training population design in interspecific soybean populations [J].
Beche, Eduardo ;
Gillman, Jason D. ;
Song, Qijian ;
Nelson, Randall ;
Beissinger, Tim ;
Decker, Jared ;
Shannon, Grover ;
Scaboo, Andrew M. .
MOLECULAR BREEDING, 2021, 41 (02)
[8]  
Bennett M., 2012, Angiosperm DNA C-values database (release 8.0
[9]  
Bhat JA., 2021, Legume Sci, V3, pe81, DOI [10.1002/leg3.81, DOI 10.1002/LEG3.81]
[10]   A new decade and new data at SoyBase, the USDA-ARS soybean genetics and genomics database [J].
Brown, Anne, V ;
Conners, Shawn, I ;
Huang, Wei ;
Wilkey, Andrew P. ;
Grant, David ;
Weeks, Nathan T. ;
Cannon, Steven B. ;
Graham, Michelle A. ;
Nelson, Rex T. .
NUCLEIC ACIDS RESEARCH, 2021, 49 (D1) :D1496-D1501