4.3 Article

High-Resolution Genotyping of Wild Barley Introgression Lines and Fine-Mapping of the Threshability Locus thresh-1 Using the Illumina GoldenGate Assay

期刊

G3-GENES GENOMES GENETICS
卷 1, 期 3, 页码 187-196

出版社

GENETICS SOCIETY AMERICA
DOI: 10.1534/g3.111.000182

关键词

wild barley introgression lines; Illumina GoldenGate assay; high-resolution mapping populations; threshability locus thresh-1

资金

  1. German Plant Genome Research Initiative (GABI) of the Federal Ministry of Education and Research [0313125B, 0315041B]
  2. Ministry of Education of the State of Saxony-Anhalt

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Genetically well-characterized mapping populations are a key tool for rapid and precise localization of quantitative trait loci (QTL) and subsequent identification of the underlying genes. In this study, a set of 73 introgression lines (S42ILs) originating from a cross between the spring barley cultivar Scarlett (Hordeum vulgare ssp. vulgare) and the wild barley accession ISR42-8 (H. v. ssp. spontaneum) was subjected to high-resolution genotyping with an Illumina 1536-SNP array. The array enabled a precise localization of the wild barley introgressions in the elite barley background. Based on 636 informative SNPs, the S42IL set represents 87.3% of the wild barley genome, where each line contains on average 3.3% of the donor genome. Furthermore, segregating high-resolution mapping populations (S42IL-HRs) were developed for 70 S42ILs in order to facilitate QTL fine-mapping and cloning. As a case study, we used the developed genetic resources to rapidly identify and fine-map the novel locus thresh-1 on chromosome 1H that controls grain threshability. Here, the recessive wild barley allele confers a difficult to thresh phenotype, suggesting that thresh-1 played an important role during barley domestication. Using a S42IL-HR population, thresh-1 was fine-mapped within a 4.3cM interval that was predicted to contain candidate genes involved in regulation of plant cell wall composition. The set of wild barley introgression lines and derived high-resolution populations are ideal tools to speed up the process of mapping and further dissecting QTL, which ultimately clears the way for isolating the genes behind QTL effects.

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