Drought is one of the most severe abiotic factors restricting plant growth and yield. Numerous genes functioning in drought response are regulated by abscisic acid (ABA) dependent and independent pathways, but knowledge of interplay between the two pathways is still limited. Here, we integrated transcriptome sequencing and network analyses to explore interplays between ABA-dependent and ABA-independent pathways responding to drought stress in Arabidopsis thaliana. We identified 211 ABA-dependent differentially expressed genes (DEGs) and 1,118 ABA-independent DEGs under drought stress. Functional analysis showed that ABA-dependent DEGs were significantly enriched in expected biological processes in response to water deprivation and ABA stimulus, while ABA-independent DEGs were preferentially enriched in response to jasmonic acid (JA), salicylic acid (SA) and gibberellin (GA) stimuli. We found significantly enriched interactions between ABA-dependent and ABA-independent pathways with 94 genes acting as core interacting components by combining network analyses. A link between ABA and JA signaling mediated through a direct interaction of the ABA responsive elements-binding factor ABF3 with the basic helix-loop-helix transcription factor MYC2 was validated by yeast two-hybrid and bimolecular fluorescence complementation (BiFC) assays. Our study provides a systematic view of the interplay between ABA-dependent and ABA-independent pathways in response to drought stress.

Background: A new method for the prediction of protein structural classes is constructed based on Rough Sets algorithm, which is a rule-based data mining method. Amino acid compositions and 8 physicochemical properties data are used as conditional attributes for the construction of decision system. After reducing the decision system, decision rules are generated, which can be used to classify new objects. Results: In this study, self-consistency and jackknife tests on the datasets constructed by G.P. Zhou (Journal of Protein Chemistry, 1998, 17: 729–738) are used to verify the performance of this method, and are compared with some of prior works. The results showed that the rough sets approach is very promising and may play a complementary role to the existing powerful approaches, such as the component-coupled, neural network, SVM, and LogitBoost approaches. Conclusion: The results with high success rates indicate that the rough sets approach as proposed in this paper might hold a high potential to become a useful tool in bioinformatics.

Heat shock transcriptional factors (Hsfs) play important roles in the processes of biotic and abiotic stresses as well as in plant development. Cotton (Gossypium hirsutum, 2n = 4x = (AD)₂ = 52) is an important crop for natural fiber production. Due to continuous high temperature and intermittent drought, heat stress is becoming a handicap to improve cotton yield and lint quality. Recently, the related wild diploid species Gossypium raimondii genome (2n = 2x = (D₅)₂ = 26) has been fully sequenced. In order to analyze the functions of different Hsfs at the genome-wide level, detailed characterization and analysis of the Hsf gene family in G. hirsutum is indispensable. EST assembly and genome-wide analyses were applied to clone and identify heat shock transcription factor (Hsf) genes in Upland cotton (GhHsf). Forty GhHsf genes were cloned, identified and classified into three main classes (A, B and C) according to the characteristics of their domains. Analysis of gene duplications showed that GhHsfs have occurred more frequently than reported in plant genomes such as Arabidopsis and Populus. Quantitative real-time PCR (qRT-PCR) showed that all GhHsf transcripts are expressed in most cotton plant tissues including roots, stems, leaves and developing fibers, and abundantly in developing ovules. Three expression patterns were confirmed in GhHsfs when cotton plants were exposed to high temperature for 1 h. GhHsf39 exhibited the most immediate response to heat shock. Comparative analysis of Hsfs expression differences between the wild-type and fiberless mutant suggested that Hsfs are involved in fiber development. Comparative genome analysis showed that Upland cotton D-subgenome contains 40 Hsf members, and that the whole genome of Upland cotton contains more than 80 Hsf genes due to genome duplication. The expression patterns in different tissues in response to heat shock showed that GhHsfs are important for heat stress as well as fiber development. These results provide an improved understanding of the roles of the Hsf gene family during stress responses and fiber development.

Background: Microsatellites are extremely common in plant genomes, and in particular, they are significantly enriched in the 5' noncoding regions. Although some 5' noncoding microsatellites involved in gene regulation have been described, the general properties of microsatellites as regulatory elements are still unknown. To address the question of microsatellites associated with regulatory elements, we have analyzed the conserved noncoding microsatellite sequences (CNMSs) in the 5' noncoding regions by inter- and intragenomic phylogenetic footprinting in the Arabidopsis and Brassica genomes. Results: We identified 247 Arabidopsis-Brassica orthologous and 122 Arabidopsis paralogous CNMSs, representing 491 CT/GA and CTT/GAA repeats, which accounted for 10.6% of these types located in the 500-bp regions upstream of coding sequences in the Arabidopsis genome. Among these identified CNMSs, 18 microsatellites show high conservation in the regulatory regions of both orthologous and paralogous genes, and some of them also appear in the corresponding positions of more distant homologs in Arabidopsis, as well as in other plants. A computational scan of CNMSs for known cis-regulatory elements showed that light responsive elements were clustered in the region of CT/GA repeats, as well as salicylic acid responsive elements in the (CTT)_n/(GAA)_n sequences. Patterns of gene expression revealed that 70–80% of CNMS (CTT)_n/(GAA)_n associated genes were regulated by salicylic acid, which was consistent with the prediction of regulatory elements in silico. Conclusion: Our analyses showed that some noncoding microsatellites were conserved in plants and appeared to be ancient. These CNMSs served as regulatory elements involved in light and salicylic acid responses. Our findings might have implications in the common features of the over-represented microsatellites for gene regulation in plant-specific pathways.

Tomato (Solanum lycopersicum) self-compatibility (SC) is defined as self-pollen tubes that can penetrate their own stigma, elongate in the style and fertilize their own ovules. Self-incompatibility (SI) is defined as self-pollen tubes that are prevented from developing in the style. To determine the influence of gene expression on style self-pollination, a transcriptome-wide comparative analysis of SC and SI tomato unpollinated/pollinated styles was performed using RNA-sequencing (RNA-seq) data. Transcriptome profiles of 24-h unpollination (UP) and self-pollination (P) styles from SC and SI tomato species were generated using high-throughput next generation sequencing. From the comparison of SC self-pollinated and unpollinated styles, 1341 differentially expressed genes (DEGs) were identified, of which 753 were downregulated and 588 were upregulated. From the comparison of SI self-pollinated and unpollinated styles, 804 DEGs were identified, of which 215 were downregulated and 589 were upregulated. Nine gene ontology (GO) terms were enriched significantly in SC and 78 GO terms were enriched significantly in SI. A total of 105 enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were identified in SC and 80 enriched KEGG pathways were identified in SI, among which “Cysteine and methionine metabolism pathway” and “Plant hormone signal transduction pathway” were significantly enriched in SI. This study is the first global transcriptome-wide comparative analysis of SC and SI tomato unpollinated/pollinated styles. Advanced bioinformatic analysis of DEGs uncovered the pathways of “Cysteine and methionine metabolism” and “Plant hormone signal transduction”, which are likely to play important roles in the control of pollen tubes growth in SI species.