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Transcriptome Profiling in Human Diseases: New Advances and Perspectives.

作者信息

Casamassimi Amelia, Federico Antonio, Rienzo Monica, Esposito Sabrina, Ciccodicola Alfredo

机构信息

Department of Biochemistry, Biophysics and General Pathology, University of Campania "Luigi Vanvitelli", Via L. De Crecchio, 80138 Naples, Italy.

Institute of Genetics and Biophysics "Adriano Buzzati Traverso", CNR, 80131 Naples, Italy.

出版信息

Int J Mol Sci. 2017 Jul 29;18(8):1652. doi: 10.3390/ijms18081652.


DOI:10.3390/ijms18081652
PMID:28758927
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5578042/
Abstract

In the last decades, transcriptome profiling has been one of the most utilized approaches to investigate human diseases at the molecular level. Through expression studies, many molecular biomarkers and therapeutic targets have been found for several human pathologies. This number is continuously increasing thanks to total RNA sequencing. Indeed, this new technology has completely revolutionized transcriptome analysis allowing the quantification of gene expression levels and allele-specific expression in a single experiment, as well as to identify novel genes, splice isoforms, fusion transcripts, and to investigate the world of non-coding RNA at an unprecedented level. RNA sequencing has also been employed in important projects, like ENCODE (Encyclopedia of the regulatory elements) and TCGA (The Cancer Genome Atlas), to provide a snapshot of the transcriptome of dozens of cell lines and thousands of primary tumor specimens. Moreover, these studies have also paved the way to the development of data integration approaches in order to facilitate management and analysis of data and to identify novel disease markers and molecular targets to use in the clinics. In this scenario, several ongoing clinical trials utilize transcriptome profiling through RNA sequencing strategies as an important instrument in the diagnosis of numerous human pathologies.

摘要
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d29/5578042/584f515ba505/ijms-18-01652-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d29/5578042/584f515ba505/ijms-18-01652-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0d29/5578042/584f515ba505/ijms-18-01652-g001.jpg

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本文引用的文献

[1]
Differentially expressed genes from RNA-Seq and functional enrichment results are affected by the choice of single-end versus paired-end reads and stranded versus non-stranded protocols.

BMC Genomics. 2017-5-23

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Int J Mol Sci. 2017-4-29

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