2021
DOI: 10.1002/tpg2.20109
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Sequencing the USDA core soybean collection reveals gene loss during domestication and breeding

Abstract: The gene content of plants varies between individuals of the same species due to gene presence/absence variation, and selection can alter the frequency of specific genes in a population. Selection during domestication and breeding will modify the genomic landscape, though the nature of these modifications is only understood for specific genes or on a more general level (e.g., by a loss of genetic diversity). Here we have assembled and analyzed a soybean (Glycine spp.) pangenome representing more than 1,000 soy… Show more

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Cited by 67 publications
(59 citation statements)
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“…The SNP matrix was generated from 985 of the soybean lines in the previous soybean pangenome study (Bayer et al 2021). Briefly, adapters of raw reads were removed using Trimmomatic v0.36 (Bolger et al 2014).…”
Section: Genotyping and Additional Genomic Resourcesmentioning
confidence: 99%
See 1 more Smart Citation
“…The SNP matrix was generated from 985 of the soybean lines in the previous soybean pangenome study (Bayer et al 2021). Briefly, adapters of raw reads were removed using Trimmomatic v0.36 (Bolger et al 2014).…”
Section: Genotyping and Additional Genomic Resourcesmentioning
confidence: 99%
“…Broad resequencing of soybean germplasm has provided a wealth of data for characterizing genetic diversity and for identifying genomic variation underlying agronomic traits (Fang et al 2017;Torkamaneh et al 2021a;Valliyodan et al 2021;Zhou et al 2015). In addition, the development of pangenomic datasets that increase variant and marker data accessibility across germplasm collections offers novel opportunities for plant breeding studies by providing the entire genetic content of soybean, including small and large structural variations, across global populations (Bayer et al 2021;Liu et al 2020;Torkamaneh et al 2021b). Several studies have mapped important major effect genomic loci; for example disease resistance (Chang et al 2016); SCN resistance (Patil et al 2019); mycorrhizal colonization (Pawlowski et al 2020); salt tolerance (Do et al 2019); seed composition (Patil et al 2018); and descriptive traits such as flower and pubescence colour (Bandillo et al 2017).…”
Section: Introductionmentioning
confidence: 99%
“…For this study and in accordance with our phenotyping capacities, 357 soybean PIs (Supplemental Table S1) were randomly selected from a larger group of 1,154 accessions on which WGS had been previously performed (Bayer et al., 2021). This collection comprised PIs from multiple countries on different continents (Asia, Europe, Africa, and South and North America) and belonging to different maturity groups (MG II, III, IV, and V).…”
Section: Methodsmentioning
confidence: 99%
“…Broad resequencing of soybean germplasm has provided a wealth of data for characterising genetic diversity and for identifying genomic variation underlying agronomic traits (Fang et al 2017;Torkamaneh et al 2021a;Valliyodan et al 2021;Zhou et al 2015). In addition, the development of pangenomic datasets that increase variant and marker data accessibility across germplasm collections offers novel opportunities for plant breeding studies by providing the entire genetic content of soybean, including small and large structural variations, across global populations (Bayer et al 2021;Liu et al 2020;Torkamaneh et al 2021b). Several studies have mapped important major effect genomic loci; for example disease resistance (Chang et al 2016), SCN resistance (Patil et al 2019); mycorrhizal colonization (Pawlowski et al 2020); salt tolerance (Do et al 2019); seed composition (Patil et al 2018); and descriptive traits such as flower and pubescence colour (Bandillo et al 2017).…”
Section: Introductionmentioning
confidence: 99%