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University of Louisville Bioinformatics

Bioinformatics Research at the University of Louisville



CSI-UTR: Cleavage site intervals for analysis of 3'UTR differential Expression


Benjamin J. Harrison1,2,3, Juw Won Park3,4, Cynthia Gomes2,5>, Jeffrey C. Petruska2,6, Matthew R. Sapio7, Michael J. Iadarola7>, Eric C. Rouchka3,4

  1. Deparmtent of Biomedical Sciences, College of Osteopathic Medicine, Center for Excellence in Neurosciences, University of New England.
  2. Deparmtent of Anatomical Sciences and Neurobiology, University of Louisville.
  3. Kentucky Biomedical Research Infrastructure Network Bioinformatics Core.
  4. Department of Computer Engineering and Computer Science, University of Louisville.
  5. Kentucky Spinal Cord Research Center, University of Louisville..
  6. Deparmtent of Neurological Surgery, University of Louisville.
  7. Department of Perioperative Medicine, Clinical Center, National Institutes of Health.

Untranslated regions of the 3' end of transcripts (3'UTRs) are critical for controlling transcript abundance and location. 3'UTR configuration is highly regulated and provides functional diversity, similar to alternative splicing of exons. Detailed transcriptome-wide profiling of 3'UTR structures may help elucidate mechanisms regulating cellular functions. This profiling is more difficult than for coding sequences (CDS), where exon/intron boundaries are well-defined. To enable this we developed a new approach, CSI-UTR. Meaningful configurations of the 3'UTR are determined using cleavage site intervals (CSIs) that lie between functional alternative polyadenylation (APA) sites. The functional APAs are defined using publicly available polyA-seq datasets biased to the site of polyadenylation. CSI-UTR can be applied to any RNASeq dataset, regardless of the 3' bias.
Using CSI-UTR, we produced a pre-defined set of CSIs for human, mouse, and rat. Previous studies indicate 3'UTR structure is highly regulated during nervous system functions. We therefore assessed CSI-UTR using archived RNASeq datasets from the nervous system (SRP056604, SRP038707, and SRP055912) and a rat dataset of our own. In all three species, CSI-UTR identified differential expression (DE) events not detected by standard gene-based differential analyses. Many DE events were in transcripts in which the CDS was unchanged. Enrichment analyses determined these DE 3'UTRs are associated with genes with known roles in neural processes. CSI-UTR is a pow-erful new tool to uncover DE that is undetectable by standard pipelines, but can exert a major influence on cellular function.

Supported by the National Institutes of Health (NIH) grants P20GM103436, P20GM103643, R01NS094741, and P30GM103507 (supporting core facilities of the KSCIRC) and the Intramural Research Program, Clinical Center, NIH. The contents of this work are solely the responsibility of the developers and do not represent the official views of the funding organization.

CSI-UTR software
  • tarball (v1.1.0)
  • List of dependencies
    • BedTools (v2.24.0 or greater)
    • samtools
    • R
    • R libraries (and their dependencies -- note libcurl-devel and libxml2-devel are needed for R packages RCurl and XML)
      • DESeq2
      • DEXSeq
    • perl
    • perl CPAN modules
      • List::MoreUtils (>=0.33)
      • Getopt::Long (>=2.38)
      • MIME::Base64 (>= 3.08)
      • Statistics::TTest (>= 1.1)
      • Text::NSP::Measures::2D::Fisher::twotailed (>= 0.97)
      • Statistics::Multtest (>=0.13)
      • File::Which (>=1.09)
  • Instructions
Cleavage Site Interval (CSI) files
Please cite: Harrison BJ, Park JW, Gomes C, Petruska JC, Sapio MR, Iadarola MJ, Rouchka EC. (2017) Detection of significantly different expressed cleavage site intervals within 3' untranslated regions using CSI-UTR. Under review.

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