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PolymiRTS Database 3.0: linking polymorphisms in microRNAs and their target sites with human diseases and biological

Anindya Bhattacharya1, Jesse D Ziebarth, Yan Cui

  • 1Department of Microbiology, Immunology and Biochemistry, University of Tennessee Health Science Center, Memphis, TN 38163, USA and Center for Integrative and Translational Genomics, University of Tennessee Health Science Center, Memphis, TN 38163, USA.

Nucleic Acids Research
|October 29, 2013
PubMed

Insights

Genetic variations in microRNAs (miRNAs) and their targets can affect health and behavior. The updated PolymiRTS database now integrates CLASH data for more accurate analysis of these miRNA polymorphisms and their functional impacts.

Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Genetic variations in microRNAs (miRNAs) and their target sites, termed PolymiRTS, can alter miRNA functionality.
  • These alterations are linked to disease development and variations in physiological and behavioral traits.

Purpose of the Study:

  • To describe recent updates to the PolymiRTS database, an integrated platform for analyzing the functional impact of genetic polymorphisms in miRNA seed regions and target sites.
  • To incorporate new data and features for a more comprehensive analysis of PolymiRTS.

Main Methods:

  • Integration of data from cross-linking, ligation, and sequencing of hybrids (CLASH) experiments to identify direct miRNA-mRNA binding sites.
  • Inclusion of small insertions and deletions in miRNA seed regions and target sites.
  • Addition of TargetScan context + score differences and biological pathway information.

Main Results:

  • The updated PolymiRTS database provides more complete and accurate miRNA-mRNA interactions by integrating CLASH data.
  • New features allow for the assessment of the impact of polymorphic miRNA-mRNA interactions, including small indels and TargetScan context + scores.
  • The database facilitates exploration of relationships between PolymiRTSs and various biological traits and diseases.

Conclusions:

  • The enhanced PolymiRTS database serves as a valuable resource for researchers studying the functional consequences of genetic variations in miRNA pathways.
  • It enables a deeper understanding of how PolymiRTS contribute to phenotypic variation and disease etiology.

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