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Abstract How the noncoding genome affects cellular functions is a key biological question. A particular challenge is to distinguish the effects of noncoding DNA elements from long noncoding RNAs (lncRNAs) that coincide at the same loci. Here, we identified the flowering‐associated intergenic lncRNA (FLAIL) inArabidopsisthrough early floweringflailmutants. Expression ofFLAILRNA from a different chromosomal location in combination with strand‐specific RNA knockdown characterizedFLAILas a trans‐acting RNA molecule.FLAILdirectly binds to differentially expressed target genes that control flowering via RNA–DNA interactions through conserved sequence motifs.FLAILinteracts with protein and RNA components of the spliceosome to affect target mRNA expression through co‐transcriptional alternative splicing (AS) and linked chromatin regulation. In the absence ofFLAIL, splicing defects at the direct FLAIL target flowering gene LACCASE 8 (LAC8) correlated with reduced mRNA expression. Double mutant analyses support a model whereFLAIL‐mediated splicing of LAC8 promotes its mRNA expression and represses flowering. Our study suggests lncRNAs as accessory components of the spliceosome that regulate AS and gene expression to impact organismal development.
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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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