Small RNA Expression Profiling by High-Throughput Sequencing: Implications of Enzymatic Manipulation
Author(s) -
Fanglei Zhuang,
Ryan T. Fuchs,
G. Brett Robb
Publication year - 2012
Publication title -
journal of nucleic acids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.621
H-Index - 32
eISSN - 2090-021X
pISSN - 2090-0201
DOI - 10.1155/2012/360358
Subject(s) - profiling (computer programming) , computational biology , rna , gene expression profiling , computer science , biology , bioinformatics , gene expression , gene , genetics , operating system
Eukaryotic regulatory small RNAs (sRNAs) play significant roles in many fundamental cellular processes. As such, they have emerged as useful biomarkers for diseases and cell differentiation states. sRNA-based biomarkers outperform traditional messenger RNA-based biomarkers by testing fewer targets with greater accuracy and providing earlier detection for disease states. Therefore, expression profiling of sRNAs is fundamentally important to further advance the understanding of biological processes, as well as diagnosis and treatment of diseases. High-throughput sequencing (HTS) is a powerful approach for both sRNA discovery and expression profiling. Here, we discuss the general considerations for sRNA-based HTS profiling methods from RNA preparation to sequencing library construction, with a focus on the causes of systematic error. By examining the enzymatic manipulation steps of sRNA expression profiling, this paper aims to demystify current HTS-based sRNA profiling approaches and to aid researchers in the informed design and interpretation of profiling experiments.
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