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Abstract BackgroundAlternative splicing of precursor mRNAs serves as a crucial mechanism to enhance gene expression plasticity for organismal adaptation. However, the precise regulation and function of alternative splicing in plant immune gene regulation remain elusive. ResultsHere, by deploying in-depth transcriptome profiling with deep genome coverage coupled with differential expression, differential alternative splicing, and differential transcript usage analysis, we reveal profound and dynamic changes in alternative splicing following treatment with microbial pattern flg22 peptides inArabidopsis. Our findings highlight RNA polymerase II C-terminal domain phosphatase-like 3 (CPL3) as a key regulator of alternative splicing, preferentially influencing the splicing patterns of defense genes rather than their expression levels. CPL3 mediates the production of a flg22-induced alternative splicing variant, diacylglycerol kinase 5α (DGK5α), which differs from the canonical DGK5β in its interaction with the upstream kinase BIK1 and subsequent phosphorylation, resulting in reduced flg22-triggered production of phosphatidic acid and reactive oxygen species. Furthermore, our functional analysis suggests that DGK5β, but not DGK5α, contributes to plant resistance against virulent and avirulent bacterial infections. ConclusionsThese findings underscore the role of CPL3 in modulating alternative splicing dynamics of defense genes and DGK5 isoform-mediated phosphatidic acid homeostasis, shedding light on the intricate mechanisms underlying plant immune gene regulation.
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High-dimension to high-dimension screening for detecting genome-wide epigenetic and noncoding RNA regulators of gene expression
Abstract MotivationThe advancement of high-throughput technology characterizes a wide variety of epigenetic modifications and noncoding RNAs across the genome involved in disease pathogenesis via regulating gene expression. The high dimensionality of both epigenetic/noncoding RNA and gene expression data make it challenging to identify the important regulators of genes. Conducting univariate test for each possible regulator–gene pair is subject to serious multiple comparison burden, and direct application of regularization methods to select regulator–gene pairs is computationally infeasible. Applying fast screening to reduce dimension first before regularization is more efficient and stable than applying regularization methods alone. ResultsWe propose a novel screening method based on robust partial correlation to detect epigenetic and noncoding RNA regulators of gene expression over the whole genome, a problem that includes both high-dimensional predictors and high-dimensional responses. Compared to existing screening methods, our method is conceptually innovative that it reduces the dimension of both predictor and response, and screens at both node (regulators or genes) and edge (regulator–gene pairs) levels. We develop data-driven procedures to determine the conditional sets and the optimal screening threshold, and implement a fast iterative algorithm. Simulations and applications to long noncoding RNA and microRNA regulation in Kidney cancer and DNA methylation regulation in Glioblastoma Multiforme illustrate the validity and advantage of our method. Availability and implementationThe R package, related source codes and real datasets used in this article are provided at https://github.com/kehongjie/rPCor. Supplementary informationSupplementary data are available at Bioinformatics online.
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- Award ID(s):
- 2113568
- PAR ID:
- 10370494
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Bioinformatics
- Volume:
- 38
- Issue:
- 17
- ISSN:
- 1367-4803
- Format(s):
- Medium: X Size: p. 4078-4087
- Size(s):
- p. 4078-4087
- Sponsoring Org:
- National Science Foundation
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