Abstract

Cotton exhibits moderately high vegetative tolerance to water-deficit stress but lint production is restricted by the available rainfed and irrigation capacity. We have described the impact of water-deficit stress on the genetic and metabolic control of fiber quality and production. Here we examine the association of tentative consensus sequences (TCs) derived from various cotton tissues under irrigated and water-limited conditions with stress-responsive QTLs. Three thousand sixteen mapped sequence-tagged-sites were used as anchored targets to examine sequence homology with 15,784 TCs to test the hypothesis that putative stress-responsive genes will map within QTLs associated with stress-related phenotypic variation more frequently than with other genomic regions not associated with these QTLs. Approximately 1,906 of 15,784 TCs were mapped to the consensus map. About 35% of the annotated TCs that mapped within QTL regions were genes involved in an abiotic stress response. By comparison, only 14.5% of the annotated TCs mapped outside these QTLs were classified as abiotic stress genes. A simple binomial probability calculation of this degree of bias being observed if QTL and non-QTL regions are equally likely to contain stress genes was P (x ≥ 85) = 7.99 × 10−15. These results suggest that the QTL regions have a higher propensity to contain stress genes.

Highlights

  • Cotton (Gossypium spp.) exhibits moderately high tolerance during vegetative development, water-deficit stress is one of the major limiting factors in its production

  • Advancements in genome mapping and functional genomics provide a powerful resource for the genetic dissection of abiotic stress tolerance in crop plants [1]

  • Comparisons of expression data with mapped Quantitative Trait Locus (QTL) were carried out using a subset of stress responsive Expressed Sequence Tags (ESTs)

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Summary

Introduction

Cotton (Gossypium spp.) exhibits moderately high tolerance during vegetative development, water-deficit stress is one of the major limiting factors in its production. Advancements in genome mapping and functional genomics provide a powerful resource for the genetic dissection of abiotic stress tolerance in crop plants [1]. Searchable databases and analytic tools available to the research community offer the capacity to query these data. These comparative tools from related fields enable the identification of genes and gene products and may reveal functional relationships between a genotype and observed phenotype [3, 4]. There is an opportunity to make direct and meaningful comparisons from data generated by quantitative trait loci (QTLs) mapping and genome-wide expression analysis to provide solutions for crop improvement

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