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Identification of quantitative trait loci for flowering time by a combination of restriction site–associated DNA sequencing and bulked segregant analysis in soybean
Soybean (Glycine max) has a paleopolyploid genome, and many re-sequencing experiments to characterize soybean genotypes have been conducted using next-generation sequencing platforms. The accumulation of information about single nucleotide polymorphisms (SNPs) throughout the soybean genome has accel...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Japanese Society of Breeding
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5515319/ https://www.ncbi.nlm.nih.gov/pubmed/28744181 http://dx.doi.org/10.1270/jsbbs.17013 |
Sumario: | Soybean (Glycine max) has a paleopolyploid genome, and many re-sequencing experiments to characterize soybean genotypes have been conducted using next-generation sequencing platforms. The accumulation of information about single nucleotide polymorphisms (SNPs) throughout the soybean genome has accelerated identification of genomic regions related to agronomically important traits through association studies. However, although many efficient mapping techniques that use next-generation sequencing are available, the number of practical approaches to identify genes/loci is still limited. In this study, we used a combination of restriction site–associated DNA sequencing (RAD-seq) and bulk segregant analysis (BSA) to identify quantitative trait locus (QTLs) for flowering time in a segregating population derived from a cross between Japanese soybean cultivars. Despite the homogeneous genetic background of the parents, over 7000 SNPs were identified and can be used to detect QTLs by RAD-seq BSA analysis. By comparing genotype frequency between early and late-flowering bulks from the F(3) segregating population, we identified a QTL on Gm10, which corresponds to the previously identified E2 locus, and a QTL on Gm04, which is close to the E8 locus. Out of these SNPs, more than 2000 were easily converted to conventional DNA markers. Our approach would improve the efficiency of genetic mapping. |
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