| Literature DB >> 28760689 |
Jin Zhang1, Malachi Griffith2, Christopher A Miller3, Obi L Griffith4, David H Spencer5, Jason R Walker6, Vincent Magrini7, Sean D McGrath7, Amy Ly6, Nichole M Helton5, Maria Trissal5, Daniel C Link5, Ha X Dang1, David E Larson8, Shashikant Kulkarni9, Matthew G Cordes6, Catrina C Fronick6, Robert S Fulton6, Jeffery M Klco10, Elaine R Mardis7, Timothy J Ley4, Richard K Wilson7, Christopher A Maher11.
Abstract
To detect diverse and novel RNA species comprehensively, we compared deep small RNA and RNA sequencing (RNA-seq) methods applied to a primary acute myeloid leukemia (AML) sample. We were able to discover previously unannotated small RNAs using deep sequencing of a library method using broader insert size selection. We analyzed the long noncoding RNA (lncRNA) landscape in AML by comparing deep sequencing from multiple RNA-seq library construction methods for the sample that we studied and then integrating RNA-seq data from 179 AML cases. This identified lncRNAs that are completely novel, differentially expressed, and associated with specific AML subtypes. Our study revealed the complexity of the noncoding RNA transcriptome through a combined strategy of strand-specific small RNA and total RNA-seq. This dataset will serve as an invaluable resource for future RNA-based analyses.Entities:
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Year: 2017 PMID： 28760689 PMCID： PMC5772960 DOI： 10.1016/j.exphem.2017.07.008
Source DB: PubMed Journal: Exp Hematol ISSN： 0301-472X Impact factor: 3.084