Abscisic acid and jasmonic acid are involved in drought priming-induced tolerance to drought in wheat

Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene. Conclusions RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.

The level of abscisic acid (ABA) in any particular tissue in a plant is determined by the rate of biosynthesis and catabolism of the hormone. Therefore, identifying all the genes involved in the metabolism is essential for a complete understanding of how this hormone directs plant growth and development. To date, almost all the biosynthetic genes have been identified through the isolation of auxotrophic mutants. On the other hand, among several ABA catabolic pathways, current genomic approaches revealed that Arabidopsis CYP707A genes encode ABA 8'-hydroxylases, which catalyze the first committed step in the predominant ABA catabolic pathway. Identification of ABA metabolic genes has revealed that multiple metabolic steps are differentially regulated to fine-tune the ABA level at both transcriptional and post-transcriptional levels. Furthermore, recent ongoing studies have given new insights into the regulation and site of ABA metabolism in relation to its physiological roles.

Jasmonates (JAs) and ethylene (ET), often acting cooperatively, play essential roles in regulating plant defense against pests and pathogens. Recent research reviewed here has revealed mechanistic new insights into the mode of action of these hormones in plant abiotic stress tolerance. During cold stress, JAs and ET differentially regulate the C-repeat binding factor (CBF) pathway. Major JA and ET signaling hubs such as JAZ proteins, CTR1, MYC2, components of the mediator complex, EIN2, EIN3, and several members of the AP2/ERF transcription factor gene family all have complex regulatory roles during abiotic stress adaptation. Better understanding the roles of these phytohormones in plant abiotic stress tolerance will contribute to the development of crop plants tolerant to a wide range of stressful environments.