A survey on identification and quantification of alternative polyadenylation sites from RNA-seq data.
Brief Bioinform
; 21(4): 1261-1276, 2020 07 15.
Article
em En
| MEDLINE
| ID: mdl-31267126
ABSTRACT
Alternative polyadenylation (APA) has been implicated to play an important role in post-transcriptional regulation by regulating mRNA abundance, stability, localization and translation, which contributes considerably to transcriptome diversity and gene expression regulation. RNA-seq has become a routine approach for transcriptome profiling, generating unprecedented data that could be used to identify and quantify APA site usage. A number of computational approaches for identifying APA sites and/or dynamic APA events from RNA-seq data have emerged in the literature, which provide valuable yet preliminary results that should be refined to yield credible guidelines for the scientific community. In this review, we provided a comprehensive overview of the status of currently available computational approaches. We also conducted objective benchmarking analysis using RNA-seq data sets from different species (human, mouse and Arabidopsis) and simulated data sets to present a systematic evaluation of 11 representative methods. Our benchmarking study showed that the overall performance of all tools investigated is moderate, reflecting that there is still lot of scope to improve the prediction of APA site or dynamic APA events from RNA-seq data. Particularly, prediction results from individual tools differ considerably, and only a limited number of predicted APA sites or genes are common among different tools. Accordingly, we attempted to give some advice on how to assess the reliability of the obtained results. We also proposed practical recommendations on the appropriate method applicable to diverse scenarios and discussed implications and future directions relevant to profiling APA from RNA-seq data.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise de Sequência de RNA
Tipo de estudo:
Diagnostic_studies
/
Guideline
/
Prognostic_studies
Limite:
Animals
/
Humans
Idioma:
En
Revista:
Brief Bioinform
Assunto da revista:
BIOLOGIA
/
INFORMATICA MEDICA
Ano de publicação:
2020
Tipo de documento:
Article
País de afiliação:
China