Institute of Biomedical Sciences

Title

Single locus resolution of transposable element expression using RNA-seq

Poster Number

8

Document Type

Poster

Keywords

Transposable elements, Human Endogenous Retrovirus, Computational Biology, RNA-seq

Publication Date

4-2017

Abstract

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-Seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software pipeline, which provides accurate estimation of transposable element expression resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through differential analysis of HERV expression in primary CD4+ T cells infected with HIV-1, and found that HML2_1q22, was significantly up-regulated. Telescope performs robust analysis of the retrotranscriptomic landscape in RNA-Seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed.

Creative Commons License

Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Open Access

1

Comments

To be presented at GW Annual Research Days 2017.

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Single locus resolution of transposable element expression using RNA-seq

Characterization of Human Endogenous Retrovirus (HERV) expression within the transcriptomic landscape using RNA-Seq is complicated by uncertainty in fragment assignment because of sequence similarity. We present Telescope, a computational software pipeline, which provides accurate estimation of transposable element expression resolved to specific genomic locations. Telescope directly addresses uncertainty in fragment assignment by reassigning ambiguously mapped fragments to the most probable source transcript as determined within a Bayesian statistical model. We demonstrate the utility of our approach through differential analysis of HERV expression in primary CD4+ T cells infected with HIV-1, and found that HML2_1q22, was significantly up-regulated. Telescope performs robust analysis of the retrotranscriptomic landscape in RNA-Seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed.