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NIH Research Festival

September 14 – 16, 2016

Incorporating variant analysis in microRNA coding genes and microRNA target sites into the standard exome analysis pipeline

Friday, September 16, 2016 – Poster Session IV
12:00 – 1:30 p.m.

FAES Terrace

NHGRI

COMPBIO-9

Authors

  • TS Frisby
  • CC Lau
  • CJ Adams
  • MJ Warburton
  • NI Balanda
  • BN Pusey
  • WA Gahl
  • DR Adams

Abstract

Exome sequencing has become a routine assessment for patients in the NIH Undiagnosed Diseases Program. Currently, several hundred patients and their nuclear families have been sequenced. Our current exome analysis methods, which attempt to expand on standard-of-care clinical exome analysis, nonetheless focus largely on variants in and around the coding regions of the genome. In order to elucidate novel causes of rare diseases, we are extending our analytic pipeline to incorporate an expanding set of non-coding DNA variation. Areas of interest include microRNA (miRNA) coding genes and miRNA target sites within the 3’-UTR of protein coding genes, both which are regions implicated in human diseases. As part of a pilot analysis, we have investigated variants within these elements by extending our exome analysis pipeline. In 5 nuclear families, we found a range of 70 – 323 variants (mean 220, median 278) rare in the general population that segregated with the diseases within the families that were previously excluded from our exome analysis. By annotating miRNA target sites using target binding prediction tools (miRanda-mirSVR, TargetScan), we were able to prioritize variants that fell into predicted or conserved miRNA target sites. Additionally, we prioritized variants that fell within the 95th percentile of miRNA target predictions. Finally, we computed the effect of the variants to the binding prediction, to find biologically and clinically significant examples. Further work needs to be done to validate these findings, but this represents the first step in the analysis and interpretation of variants that had been previously overlooked.

Scientific Focus Area: Computational Biology

This page was last updated on Friday, March 26, 2021

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