Literature DB >> 21922594

SpliceAid 2: a database of human splicing factors expression data and RNA target motifs.

Francesco Piva1, Matteo Giulietti, Alessandra Ballone Burini, Giovanni Principato.   

Abstract

Splicing is the most frequently altered biological process by mutations within gene regions. Information for splicing is recognized by several factors that bind pre-mRNA sequence and, through coordinated interaction, yield mature transcripts. Some in silico methods have been developed to predict if a mutation leads to aberrant splicing patterns. We previously created SpliceAid tool that is able to minimize false positive predictions because it adopts strictly experimental RNA target motifs bound by splicing proteins in humans. In order to improve prediction accuracy and better understand the splicing outcome, the tissue specificity of each splicing regulatory factor has to be taken into account. Here, we have developed SpliceAid 2 by adding the expression data related to the splicing factors extracted from the main proteomic and transcriptomic databases, true 5' and 3' splice sites, polypyrimidine tracts, and branch point sequences. The new version collects 2,220 target sites of 62 human splicing proteins and their expression data in 320 tissues per cell. SpliceAid 2 can be useful to foresee the splicing pattern alteration, to guide the identification of the molecular effect due to the mutations and to understand the tissue-specific alternative splicing. SpliceAid 2 is freely accessible at www.introni.it/spliceaid.html.
© 2011 Wiley Periodicals, Inc.

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Year:  2011        PMID: 21922594     DOI: 10.1002/humu.21609

Source DB:  PubMed          Journal:  Hum Mutat        ISSN: 1059-7794            Impact factor:   4.878


  116 in total

1.  Algorithm to identify frequent coupled modules from two-layered network series: application to study transcription and splicing coupling.

Authors:  Wenyuan Li; Chao Dai; Chun-Chi Liu; Xianghong Jasmine Zhou
Journal:  J Comput Biol       Date:  2012-06       Impact factor: 1.479

2.  In silico to in vivo splicing analysis using splicing code models.

Authors:  Matthew R Gazzara; Jorge Vaquero-Garcia; Kristen W Lynch; Yoseph Barash
Journal:  Methods       Date:  2013-12-07       Impact factor: 3.608

3.  BRCA1 exon 11 a model of long exon splicing regulation.

Authors:  Michela Raponi; Lindsay D Smith; Marco Silipo; Cristiana Stuani; Emanuele Buratti; Diana Baralle
Journal:  RNA Biol       Date:  2014-03-18       Impact factor: 4.652

4.  SNPlice: variants that modulate Intron retention from RNA-sequencing data.

Authors:  Prakriti Mudvari; Mercedeh Movassagh; Kamran Kowsari; Ali Seyfi; Maria Kokkinaki; Nathan J Edwards; Nady Golestaneh; Anelia Horvath
Journal:  Bioinformatics       Date:  2014-12-06       Impact factor: 6.937

5.  High-throughput analysis revealed mutations' diverging effects on SMN1 exon 7 splicing.

Authors:  Přemysl Souček; Kamila Réblová; Michal Kramárek; Lenka Radová; Tereza Grymová; Pavla Hujová; Tatiana Kováčová; Matej Lexa; Lucie Grodecká; Tomáš Freiberger
Journal:  RNA Biol       Date:  2019-06-19       Impact factor: 4.652

6.  C3a and suPAR drive versican V1 expression in tubular cells of focal segmental glomerulosclerosis.

Authors:  Runhong Han; Shuai Hu; Weisong Qin; Jinsong Shi; Qin Hou; Xia Wang; Xiaodong Xu; Minchao Zhang; Caihong Zeng; Zhihong Liu; Hao Bao
Journal:  JCI Insight       Date:  2019-04-04

7.  A germline missense mutation in exon 3 of the MSH2 gene in a Lynch syndrome family: correlation with phenotype and localization assay.

Authors:  Francesca Bianchi; Elena Maccaroni; Laura Belvederesi; Cristiana Brugiati; Riccardo Giampieri; Federica Bini; Raffaella Bracci; Silvia Pagliaretta; Michela Del Prete; Francesco Piva; Alessandra Mandolesi; Marina Scarpelli; Rossana Berardi
Journal:  Fam Cancer       Date:  2018-04       Impact factor: 2.375

8.  Protein Sam68 regulates the alternative splicing of survivin DEx3.

Authors:  Javier Gaytan-Cervantes; Carolina Gonzalez-Torres; Vilma Maldonado; Cecilia Zampedri; Gisela Ceballos-Cancino; Jorge Melendez-Zajgla
Journal:  J Biol Chem       Date:  2017-06-27       Impact factor: 5.157

9.  Integrative analysis of many RNA-seq datasets to study alternative splicing.

Authors:  Wenyuan Li; Chao Dai; Shuli Kang; Xianghong Jasmine Zhou
Journal:  Methods       Date:  2014-02-28       Impact factor: 3.608

10.  Mathematical modeling identifies potential gene structure determinants of co-transcriptional control of alternative pre-mRNA splicing.

Authors:  Jeremy Davis-Turak; Tracy L Johnson; Alexander Hoffmann
Journal:  Nucleic Acids Res       Date:  2018-11-16       Impact factor: 16.971

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