2014
DOI: 10.1111/pbi.12249
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Identification of loci governing eight agronomic traits using a GBSGWAS approach and validation by QTL mapping in soya bean

Abstract: Summary Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome‐wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping‐by‐sequencing (GBS) approach was used to provide dense genome‐wide marker coverage (>47 000 SNPs) for a pane… Show more

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Cited by 311 publications
(307 citation statements)
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References 50 publications
(81 reference statements)
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“…Note that LD decay varies across different chromosomes and even within heterochromatic and euchromatic chromosome regions. Sonah et al (2015) has shown LD for each of the chromosomes separately and observed range from 250 kb to 2.5 Mb. Hwang et al (2014) identified that the LD decay rate in heterochromatic and euchromatic chromosome regions was 360 and 9600 kb, respectively.…”
Section: Discussionmentioning
confidence: 99%
“…Note that LD decay varies across different chromosomes and even within heterochromatic and euchromatic chromosome regions. Sonah et al (2015) has shown LD for each of the chromosomes separately and observed range from 250 kb to 2.5 Mb. Hwang et al (2014) identified that the LD decay rate in heterochromatic and euchromatic chromosome regions was 360 and 9600 kb, respectively.…”
Section: Discussionmentioning
confidence: 99%
“…Conceptually, an increase in the compositional value of soybeans via altered carbon partitioning seems feasible, because a considerable portion of the soybean dry weight is composed of less valuable fiber and the poorly digestible oligosaccharides raffinose and stachyose (Padgette et al, 1996). However, neither conventional breeding nor quantitative trait locus mapping approaches for increasing soybean oil, while maintaining protein content, has been very successful, because increases in one of these components is usually associated with decreases in the other (Smith and Weber, 1968;Burton and Brim, 1981;Feng et al, 2004;Eskandari et al, 2013;Sonah et al, 2015). Consequently, the oil and protein contents of about 20% and 40% for commodity soybeans have changed little in the last several decades.…”
mentioning
confidence: 99%
“…Significant natural variation for seed carotenoids also is present in diversity panels of maize (Zea mays), wheat (Triticum aestivum), Citrus spp., chickpea (Cicer arietinum), carrot (Daucus carota), pea (Pisum sativum), cassava (Manihot esculenta), and Arabidopsis (Abbo et al, 2010;Arango et al, 2010;Welsch et al, 2010;Yan et al, 2010;Blanco et al, 2011;Cook et al, 2012;Gonzalez-Jorge et al, 2013;Kandianis et al, 2013;Owens et al, 2014;Jourdan et al, 2015;Suwarno et al, 2015). Advances in high-throughput phenotyping and genotyping are allowing some of the genes underlying this natural variation to be identified through genome-wide association studies (GWAS; Harjes et al, 2008;Zhou et al, 2012;Gonzalez-Jorge et al, 2013;Owens et al, 2014;Wen et al, 2014;Sonah et al, 2015). In this study, we integrate GWAS, QTL analysis, and reverse genetics in the model plant Arabidopsis to functionally define the loci contributing to natural variation in seed carotenoid levels.…”
mentioning
confidence: 99%