Telescope: Characterization of the retrotranscriptome by accurate estimation of transposable element expression.
Matthew L Bendall, Miguel de Mulder, Luis Pedro I��iguez, Aar��n Lecanda-S��nchez, Marcos P��rez-Losada, Mario A Ostrowski, R Brad Jones, Lubbertus C F Mulder, Gustavo Reyes-Ter��n, Keith A Crandall, Christopher E Ormsby, Douglas F Nixon
Author Information
Matthew L Bendall: Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America. ORCID
Miguel de Mulder: Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America. ORCID
Luis Pedro I��iguez: Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America. ORCID
Aar��n Lecanda-S��nchez: Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Marcos P��rez-Losada: Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America.
Mario A Ostrowski: Department of Immunology, University of Toronto, Toronto, Ontario, Canada. ORCID
R Brad Jones: Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America.
Lubbertus C F Mulder: Department of Microbiology, Icahn School of Medicine at Mount Sinai, New York, New York, United States of America.
Gustavo Reyes-Ter��n: Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Keith A Crandall: Computational Biology Institute, Milken Institute School of Public Health, George Washington University, Washington, D.C., United States of America. ORCID
Christopher E Ormsby: Center for Research in Infectious Diseases (CIENI), Instituto Nacional de Enfermedades Respiratorias, Mexico City, Mexico.
Douglas F Nixon: Division of Infectious Diseases, Department of Medicine, Weill Cornell Medicine, New York, N.Y., United States of America. ORCID
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 tool that provides accurate estimation of transposable element expression (retrotranscriptome) 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 single locus analysis of HERV expression in 13 ENCODE cell types. When examined at this resolution, we find that the magnitude and breadth of the retrotranscriptome can be vastly different among cell types. Furthermore, our approach is robust to differences in sequencing technology and demonstrates that the retrotranscriptome has potential to be used for cell type identification. We compared our tool with other approaches for quantifying transposable element (TE) expression, and found that Telescope has the greatest resolution, as it estimates expression at specific TE insertions rather than at the TE subfamily level. Telescope performs highly accurate quantification of the retrotranscriptomic landscape in RNA-seq experiments, revealing a differential complexity in the transposable element biology of complex systems not previously observed. Telescope is available at https://github.com/mlbendall/telescope.
