Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors

Jianbo Wang, Zhenqing Ye, Tim H. Huang, Huidong Shi, Victor X. Jin

Research output: Chapter in Book/Report/Conference proceedingChapter

3 Citations (Scopus)

Abstract

Alternative splicing is widely recognized for playing roles in regulating genes and creating gene diversity. Consequently the identification and quantification of differentially spliced transcripts are pivotal for transcriptome analysis. However, how these diversified isoforms are spliced during genomic transcription and protein expression and what biological factors might influence the regulation of this are still required for further exploration. The advances in next-generation sequencing of messenger RNA (RNA-seq) have enabled us to survey gene expression and splicing more accurately. We have introduced a novel computational method, graph-based exon-skipping scanner (GESS), for de novo detection of skipping event sites from raw RNA-seq reads without prior knowledge of gene annotations, as well as for determining the dominant isoform generated from such sites. We have applied our method to publicly available RNA-seq data in GM12878 and K562 cells from the ENCODE consortium, and integrated other sequencing-based genomic data to investigate the impact of splicing activities, transcription factors (TFs) and epigenetic histone modifications on splicing outcomes. In a separate study, we also apply this algorithm in prostate cancer in The Cancer Genomics Atlas (TCGA) for de novo skipping event discovery to the understanding of abnormal splicing in each patient and to identify potential markers for prediction and progression of diseases.

Original languageEnglish (US)
Title of host publicationMethods in Molecular Biology
PublisherHumana Press Inc.
Pages163-170
Number of pages8
DOIs
StatePublished - Jan 1 2017

Publication series

NameMethods in Molecular Biology
Volume1513
ISSN (Print)1064-3745

Fingerprint

Epigenomics
Exons
Transcription Factors
RNA
Protein Isoforms
Histone Code
Molecular Sequence Annotation
K562 Cells
Atlases
Alternative Splicing
Biological Factors
Gene Expression Profiling
Genomics
Genes
Disease Progression
Prostatic Neoplasms
Gene Expression
Messenger RNA
Neoplasms
Proteins

Keywords

  • Alternative splicing (AS)
  • Epigenetic
  • Graph-based exon-skipping scanner (GESS)
  • RNA-sequencing

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics

Cite this

Wang, J., Ye, Z., Huang, T. H., Shi, H., & Jin, V. X. (2017). Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors. In Methods in Molecular Biology (pp. 163-170). (Methods in Molecular Biology; Vol. 1513). Humana Press Inc.. https://doi.org/10.1007/978-1-4939-6539-7_11

Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors. / Wang, Jianbo; Ye, Zhenqing; Huang, Tim H.; Shi, Huidong; Jin, Victor X.

Methods in Molecular Biology. Humana Press Inc., 2017. p. 163-170 (Methods in Molecular Biology; Vol. 1513).

Research output: Chapter in Book/Report/Conference proceedingChapter

Wang, J, Ye, Z, Huang, TH, Shi, H & Jin, VX 2017, Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors. in Methods in Molecular Biology. Methods in Molecular Biology, vol. 1513, Humana Press Inc., pp. 163-170. https://doi.org/10.1007/978-1-4939-6539-7_11
Wang J, Ye Z, Huang TH, Shi H, Jin VX. Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors. In Methods in Molecular Biology. Humana Press Inc. 2017. p. 163-170. (Methods in Molecular Biology). https://doi.org/10.1007/978-1-4939-6539-7_11
Wang, Jianbo ; Ye, Zhenqing ; Huang, Tim H. ; Shi, Huidong ; Jin, Victor X. / Computational methods and correlation of Exon-skipping events with splicing, transcription, and epigenetic factors. Methods in Molecular Biology. Humana Press Inc., 2017. pp. 163-170 (Methods in Molecular Biology).
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