Table of Contents
International Journal of Plant Genomics
Volume 2015 (2015), Article ID 892716, 11 pages
http://dx.doi.org/10.1155/2015/892716
Research Article

Toward Coalescing Gene Expression and Function with QTLs of Water-Deficit Stress in Cotton

1USDA-ARS Crop Genetics Research Unit, Stoneville, MS 38776, USA
2USDA-ARS Cropping Systems Research Laboratory, Lubbock, TX 79415, USA
3Department of Plant and Soil Science, Texas Tech University, Lubbock, TX 79409, USA
4Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK 73401, USA

Received 21 January 2015; Revised 8 May 2015; Accepted 13 May 2015

Academic Editor: Ibrokhim Y. Abdurakhmonov

Copyright © 2015 Hirut Kebede et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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   × 10−15. These results suggest that the QTL regions have a higher propensity to contain stress genes.