Location: Crop Germplasm ResearchTitle: A comparison of candidate gene-based and genotyping-by-sequencing (GBS) approaches to trait mapping in Gossypium barbadense L) Author
Submitted to: International Cotton Genome Initiative Workshop
Publication Type: Abstract Only
Publication Acceptance Date: 9/1/2012
Publication Date: N/A
Citation: N/A Interpretive Summary:
Technical Abstract: The genomes of cultivated cottons are large, complex, and incompletely characterized. The applications of single nucleotide polymorphisms (SNPs) for genetic analyses (e.g. QTL mapping, association mapping, etc.) are made problematic by the presence of multiple orthologs, homeologs, and paralogs. With the advent of next-generation sequencing (NGS) technologies (e.g. Roche 454, Illumina), it has become feasible to readily sort out SNPs present in various orthologs, homeologs and paralogs, thus facilitating the mapping of SNP alleles that are associated with traits of interest. In this study, we employed both a candidate gene (CG) approach and a genotyping-by-sequencing (GBS) approach to identify SNPs associated with a major locus that contributes to photoperiodic flowering in G. barbadense. Genetic stocks from 14 taxa were used in both approaches, including G. raimondii (D5), G. herbaceum (A2), G. barbadense (AD2), G. hirsutum (AD1), and an out-group G. incanum (E4). In the CG approach, Roche 454 amplicon sequencing was used to identify SNPs in 38 cotton orthologs of Arabidopsis thaliana genes in the floral regulatory pathway. Using this approach, we were able to parse out the 'A' and 'D' subgenome orthologs of candidate flowering genes, as well as intraspecific polymorphisms in AD allotetraploid taxa. In our GBS approach, we used a simplified restriction digestion protocol to achieve reduced representation for sequencing on the Illumina platform. In this approach, we were able to identify SNPs between cultivated AD2 cottons and wild AD2 relatives to map the floral regulatory locus to a genomic region. A comparison of the efficacy of these approaches, along with their potential applications to the analysis of other traits of interest, will be discussed.