Predicted world population growth will require more food, feed, and fiber production. Intermittent drought and shortages of water supply negatively impact crop productivity and are predicted to occur more frequently in future agricultural systems [1
]. In future agricultural systems, an increase in crop productivity must also be accompanied by a reduced environmental impact of production on natural resources [4
]. Therefore, to increase productivity while maintaining adequate water resources, it is necessary to understand the mechanisms plants use to cope with water deficit stress [5
]. There have been two general efforts towards more sustainable and water use efficient agricultural production. One effort is represented by breeding and genetic engineering [1
]. Another effort is focused on the improvement of agricultural practices such as tillage and irrigation systems [8
]. To successfully pursue the breeding and genetic engineering approach, it is fundamental to understand plant responses to drought stress at the molecular, cellular, and genetics levels. This understanding is critical, because drought tolerance is a quantitative trait influenced by a combination of regulatory pathways [5
Drought stress impacts a network of plant gene expression mechanisms that lead to the reprogramming of a variety of physiological and metabolic processes in accordance with stress response. Early studies primarily used model plant species to identify a wide spectrum of genes that are involved in different levels of metabolism, signal transduction, osmotic regulation, stress response, and gene regulation [12
]. More recently, many plant gene expression profiling experiments, using a range of technical approaches, have been conducted on economically important crop plants to determine stress related expression signatures. For example, next generation sequencing technology (NGS) has been applied to provide global gene expression profiles of whole transcriptomes [15
]. NGS expression studies are greatly facilitated by the availability of annotated genome sequence (reference or otherwise).
As an alternative to NGS, the cDNA-AFLP technique is a widely adopted gene expression profiling method. This is especially true for crop plants, such as cotton, that are awaiting whole genome- or whole transcriptome- sequence data. cDNA-AFLP profiling has proven to be a robust method to discover differentially expressed genes in a number of plant species [17
]. With the advantage of no prerequisite reference genome sequence requirement, cDNA-AFLP has been used to understand regulation mechanisms under various biotic and abiotic stress conditions that influence patterns of global gene expression in diverse crop species [20
Cotton, a warm climate crop of tremendous global economic importance, is known to contain intrinsic mechanisms that allow it to partially withstand water deficit- and heat-stresses by its deep and extensive root system and adaptive osmoregulation mechanisms [23
]. However, as water deficit stress progressively continues, development and reproduction of cotton is severely affected, and the quality and yield of cotton fiber production is significantly reduced [25
]. Therefore, for successful cotton fiber production, it is essential to understand proper management strategies between water demand, irrigation, and plant responses that are seasonally variable [27
In cotton, there are several reports on the molecular regulatory mechanisms that orchestrate drought resistance using quantitative trait loci (QTL) mapping or by developing drought stress induced cDNA libraries [28
]. In addition, microarray gene expression profiling has been used in cotton tissues exposed to variable water deficit stress in a controlled environment growth condition [31
]. However, microarray gene expression profiling is limited to ESTs or genes present on the microarray chip and may not provide a complete representation of differentially expressed genes.
Although genome sequencing data of many economically important crop species are widely available as full or high quality draft formats [32
], the progress of cotton genome sequencing has been slow. Genome sequencing of an ancestral diploid genome (D) is near completion [33
]. Once complete, the D-genome sequence will be useful as a platform for more comprehensive information on cultivated cotton’s tetraploid genome [35
In this study, our objective was to gain comprehensive insight into the water deficit stress-related gene expression profile in cotton grown under field conditions. To accomplish this, we used cDNA-AFLP to identify differentially expressed genes in the roots and leaves of a single cotton cultivar grown in a rain-fed, drought-prone field environment. From this large comparative analysis, fundamental experimental data illustrate complex mechanisms of gene expression in response to water deficit stress. This study should facilitate future efforts to improve the agricultural productivity of cotton and other crops under soil water deficit conditions.