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Fairfax, VA, United States

Colla S.,University of Houston | Ong D.S.T.,University of Houston | Ogoti Y.,University of Houston | Marchesini M.,University of Houston | And 40 more authors.
Cancer Cell | Year: 2015

Myelodysplastic syndrome (MDS) risk correlates with advancing age, therapy-induced DNA damage, and/or shorter telomeres, but whether telomere erosion directly induces MDS is unknown. Here, we provide the genetic evidence that telomere dysfunction-induced DNA damage drives classical MDS phenotypes and alters common myeloid progenitor (CMP) differentiation by repressing the expression of mRNA splicing/processing genes, including SRSF2. RNA-seq analyses of telomere dysfunctional CMP identified aberrantly spliced transcripts linked to pathways relevant to MDS pathogenesis such as genome stability, DNA repair, chromatin remodeling, and histone modification, which are also enriched in mouse CMP haploinsufficient for SRSF2 and in CD34+ CMML patient cells harboring SRSF2 mutation. Together, our studies establish an intimate link across telomere biology, aberrant RNA splicing, and myeloid progenitor differentiation. © 2015 Elsevier Inc.

Wong W.C.,Johns Hopkins University | Kim D.,Johns Hopkins University | Carter H.,Johns Hopkins University | Diekhans M.,University of California at Santa Cruz | And 2 more authors.
Bioinformatics | Year: 2011

Summary: Thousands of cancer exomes are currently being sequenced, yielding millions of non-synonymous single nucleotide variants (SNVs) of possible relevance to disease etiology. Here, we provide a software toolkit to prioritize SNVs based on their predicted contribution to tumorigenesis. It includes a database of precomputed, predictive features covering all positions in the annotated human exome and can be used either stand-alone or as part of a larger variant discovery pipeline. © The Author(s) 2011. Published by Oxford University Press.

Ryan M.C.,In Silico Solutions | Cleland J.,In Silico Solutions | Kim R.,In Silico Solutions | Wong W.C.,In Silico Solutions | Weinstein J.N.,University of Houston
Bioinformatics | Year: 2012

Summary: SpliceSeq is a resource for RNA-Seq data that provides a clear view of alternative splicing and identifies potential functional changes that result from splice variation. It displays intuitive visualizations and prioritized lists of results that highlight splicing events and their biological consequences. SpliceSeq unambiguously aligns reads to gene splice graphs, facilitating accurate analysis of large, complex transcript variants that cannot be adequately represented in other formats. © The Author 2012. Published by Oxford University Press. All rights reserved.

Douville C.,Johns Hopkins University | Carter H.,Johns Hopkins University | Kim R.,In Silico Solutions | Niknafs N.,Johns Hopkins University | And 5 more authors.
Bioinformatics | Year: 2013

Summary: Advances in sequencing technology have greatly reduced the costs incurred in collecting raw sequencing data. Academic laboratories and researchers therefore now have access to very large datasets of genomic alterations but limited time and computational resources to analyse their potential biological importance. Here, we provide a web-based application, Cancer-Related Analysis of Variants Toolkit, designed with an easy-to-use interface to facilitate the high-throughput assessment and prioritization of genes and missense alterations important for cancer tumorigenesis. Cancer-Related Analysis of Variants Toolkit provides predictive scores for germline variants, somatic mutations and relative gene importance, as well as annotations from published literature and databases. Results are emailed to users as MS Excel spreadsheets and/or tab-separated text files. © 2013 The Author 2013. Published by Oxford University Press.

Niknafs N.,Johns Hopkins University | Kim D.,Johns Hopkins University | Kim R.,In Silico Solutions | Diekhans M.,University of California at Santa Cruz | And 4 more authors.
Human Genetics | Year: 2013

Mutation position imaging toolbox (MuPIT) interactive is a browser-based application for single-nucleotide variants (SNVs), which automatically maps the genomic coordinates of SNVs onto the coordinates of available three-dimensional (3D) protein structures. The application is designed for interactive browser-based visualization of the putative functional relevance of SNVs by biologists who are not necessarily experts either in bioinformatics or protein structure. Users may submit batches of several thousand SNVs and review all protein structures that cover the SNVs, including available functional annotations such as binding sites, mutagenesis experiments, and common polymorphisms. Multiple SNVs may be mapped onto each structure, enabling 3D visualization of SNV clusters and their relationship to functionally annotated positions. We illustrate the utility of MuPIT interactive in rationalizing the impact of selected polymorphisms in the PharmGKB database, somatic mutations identified in the Cancer Genome Atlas study of invasive breast carcinomas, and rare variants identified in the exome sequencing project. MuPIT interactive is freely available for non-profit use at http://mupit.icm.jhu.edu. © 2013 Springer-Verlag Berlin Heidelberg.

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