NDLI: Studying alternative splicing regulatory networks through partial correlation analysis

Content Provider	Springer Nature : BioMed Central
Author	Chen, Liang Zheng, Sika
Abstract	Background Alternative pre-mRNA splicing is an important gene regulation mechanism for expanding proteomic diversity in higher eukaryotes. Each splicing regulator can potentially influence a large group of alternative exons. Meanwhile, each alternative exon is controlled by multiple splicing regulators. The rapid accumulation of high-throughput data provides us with a unique opportunity to study the complicated alternative splicing regulatory network. Results We propose the use of partial correlation analysis to identify association links between exons and their upstream regulators or their downstream target genes (exon-gene links) and links between co-spliced exons (exon-exon links). The partial correlation analysis avoids taking the ratio of two noisy random variables, exon expression level and gene expression level, so that it achieves a higher statistical power. We named this analysis procedure pCastNet (partial Correlation analysis of splicing transcriptome Network). Through studies of known alternative exons, conservation patterns, relative positions, functional annotations, and RT-PCR experiments, we concluded that pCastNet can effectively identify exon-gene or exon-exon links. We further found that gene pairs with exon-gene or exon-exon links tend to have similar functions or are present in the same pathways. More interestingly, gene pairs with exon-gene or exon-exon links tend to share cis-elements in promoter regions and microRNA binding elements in 3' untranslated regions, which suggests the coupling of co-alternative-splicing, co-transcription-factor-binding, and co-microRNA-binding. Conclusions Alternative splicing regulatory networks reconstructed by pCastNet can help us better understand the coordinate and combinatorial nature of alternative splicing regulation. The proposed tool can be readily applied to other high-throughput data such as transcriptome sequencing data.
Related Links	https://genomebiology.biomedcentral.com/counter/pdf/10.1186/gb-2009-10-1-r3.pdf
Ending Page	20
Page Count	20
Starting Page	1
File Format	HTM / HTML
DOI	10.1186/gb-2009-10-1-r3
Journal	Genome Biology
Issue Number	1
Volume Number	10
Language	English
Publisher	BioMed Central
Publisher Date	2009-01-09
Access Restriction	Open
Subject Keyword	Animal Genetics and Genomics Human Genetics Plant Genetics and Genomics Microbial Genetics and Genomics Bioinformatics Evolutionary Biology Alternative Splice Additional Data File Partial Correlation Analysis Alternative Exon Exon Array
Content Type	Text
Resource Type	Article
Subject	Biotechnology Genetics
Journal Impact Factor	10.1/2023
5-Year Journal Impact Factor	16.5/2023

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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