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The soybean is self-pollinated plant, the genetic diversity is lower, that made the soybean genetic research was to drag behind, especially the genetic mapping.To develop the new molecular markers and construct high-density soybean genetic map, the soybean EST data and the soybean genome sequences were downloaded, and the bioinformatics method were token to mine the potential SNP mutation from the soybean genes re-sequences data, and the SNP mutations were transform to the CAPS markers.The soybean genome sequences were analyzed, and the length DNA sequences insertion mutation of the soybean gene intron were discovered.PCR primers were designed to the flanking regions of the insertion mutation, and the SCAR markers were developed after verified the polymorphism.By re-sequencing the SCAR markers, the novel retroposon GmAu1 was identified and characterized.The retroposon GmAu1 insertion sites were identified genome-widely by BLAST against the soybean genome, and the GmAu1 insertion mutation sites were converted into SCAR markers.The SCAR markers and CAPS markers were selected for genotyped the soybean core varieties, and identified markers associated with hundred-seed weight (HSW).Then, the best linear unbiased predictor and Bayesian liner regression methods were used to construct GS models to predict the HSW trait based upon genotype information for trait selection.Both GS models showed good prediction performance in soybean, as the correlation coefficient between genomic estimated breeding values and true breeding values was as high as 0.904.This indicated that GS was performed effectively based on dozens of SCAR markers in soybean, which were of low density but easily detectable.Therefore, the combination of GS modeling and highly-effective molecular marker technology, SCAR and CAPS markers, can facilitate genetic breeding in soybean.