SummaryWRKY transcription factors (TFs) are key regulators of many plant processes, including the responses to biotic and abiotic stresses, senescence, seed dormancy and seed germination. For over 15 years, limited evidence has been available suggesting that WRKY TFs may play roles in regulating plant responses to the phytohormone abscisic acid (ABA), notably some WRKY TFs are ABA-inducible repressors of seed germination. However, the roles of WRKY TFs in other aspects of ABA signalling, and the mechanisms involved, have remained unclear. Recent significant progress in ABA research has now placed specific WRKY TFs firmly in ABA-responsive signalling pathways, where they act at multiple levels. In Arabidopsis, WRKY TFs appear to act downstream of at least two ABA receptors: the cytoplasmic PYR ⁄ PYL ⁄ RCARprotein phosphatase 2C-ABA complex and the chloroplast envelope-located ABAR-ABA complex. In vivo and in vitro promoter-binding studies show that the target genes for WRKY TFs that are involved in ABA signalling include well-known ABA-responsive genes such as ABF2, ABF4, ABI4, ABI5, MYB2, DREB1a, DREB2a and RAB18. Additional well-characterized stressinducible genes such as RD29A and COR47 are also found in signalling pathways downstream of WRKY TFs. These new insights also reveal that some WRKY TFs are positive regulators of ABA-mediated stomatal closure and hence drought responses. Conversely, many WRKY TFs are negative regulators of seed germination, and controlling seed germination appears a common function of a subset of WRKY TFs in flowering plants. Taken together, these new data demonstrate that WRKY TFs are key nodes in ABA-responsive signalling networks.
The rice genome annotation has been greatly improved in recent years, largely due to the availability of full length cDNA sequences derived from many tissues. Among those yet to be studied is the aleurone layer, which produces hydrolases for mobilization of seed storage reserves during seed germination and post germination growth. Herein, we report transcriptomes of aleurone cells treated with the hormones abscisic acid, gibberellic acid, or both. Using a comprehensive approach, we identified hundreds of novel genes. To minimize the number of false positives, only transcripts that did not overlap with existing annotations, had a high level of expression, and showed a high level of uniqueness within the rice genome were considered to be novel genes. This approach led to the identification of 553 novel genes that encode proteins and/or microRNAs. The transcriptome data reported here will help to further improve the annotation of the rice genome.
Annotation of the rice (Oryza sativa) genome has evolved significantly since release of its draft sequence, but it is far from complete. Several published transcript assembly programmes were tested on RNA-sequencing (RNA-seq) data to determine their effectiveness in identifying novel genes to improve the rice genome annotation. Cufflinks, a popular assembly software, did not identify all transcripts suggested by the RNA-seq data. Other assembly software was CPU intensive, lacked documentation, or lacked software updates. To overcome these shortcomings, a heuristic ab initio transcript assembly algorithm, Tiling Assembly, was developed to identify genes based on short read and junction alignment. Tiling Assembly was compared with Cufflinks to evaluate its gene-finding capabilities. Additionally, a pipeline was developed to eliminate false-positive gene identification due to noise or repetitive regions in the genome. By combining Tiling Assembly and Cufflinks, 767 unannotated genes were identified in the rice genome, demonstrating that combining both programmes proved highly efficient for novel gene identification. We also demonstrated that Tiling Assembly can accurately determine transcription start sites by comparing the Tiling Assembly genes with their corresponding full-length cDNA. We applied our pipeline to additional organisms and identified numerous unannotated genes, demonstrating that Tiling Assembly is an organism-independent tool for genome annotation.
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