Aberrant 3' splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization
Aberrant 3' splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization
The frequency distribution of mutation-induced aberrant 3' splice sites (3'ss) in exons and introns is more complex than for 5' splice sites, largely owing to sequence constraints upstream of intron/exon boundaries. As a result, prediction of their localization remains a challenging task. Here, nucleotide sequences of previously reported 218 aberrant 3'ss activated by disease-causing mutations in 131 human genes were compared with their authentic counterparts using currently available splice site prediction tools. Each tested algorithm distinguished authentic 3'ss from cryptic sites more effectively than from de novo sites. The best discrimination between aberrant and authentic 3'ss was achieved by the maximum entropy model. Almost one half of aberrant 3'ss was activated by AG-creating mutations and approximately 95% of the newly created AGs were selected in vivo. The overall nucleotide structure upstream of aberrant 3'ss was characterized by higher purine content than for authentic sites, particularly in position -3, that may be compensated by more stringent requirements for positive and negative nucleotide signatures centred around position -11. A newly developed online database of aberrant 3'ss will facilitate identification of splicing mutations in a gene or phenotype of interest and future optimization of splice site prediction tools
databases, comparative study, mutation, evaluation studies, genetics, algorithms, nucleic acid, nucleotides, genes, disease, humans, genetic diseases, research, rna splice sites, analysis, base composition, dna mutational analysis, rna, exons, utilization, internet, introns, research support, phenotype, human, methods, software, inborn, computational biology
4630-4641
Vorechovsky, Igor
7245de2f-8c9b-4034-8935-9a451d9b682e
September 2006
Vorechovsky, Igor
7245de2f-8c9b-4034-8935-9a451d9b682e
Vorechovsky, Igor
(2006)
Aberrant 3' splice sites in human disease genes: mutation pattern, nucleotide structure and comparison of computational tools that predict their utilization.
Nucleic Acids Research, 34 (16), .
(doi:10.1093/nar/gkl535).
Abstract
The frequency distribution of mutation-induced aberrant 3' splice sites (3'ss) in exons and introns is more complex than for 5' splice sites, largely owing to sequence constraints upstream of intron/exon boundaries. As a result, prediction of their localization remains a challenging task. Here, nucleotide sequences of previously reported 218 aberrant 3'ss activated by disease-causing mutations in 131 human genes were compared with their authentic counterparts using currently available splice site prediction tools. Each tested algorithm distinguished authentic 3'ss from cryptic sites more effectively than from de novo sites. The best discrimination between aberrant and authentic 3'ss was achieved by the maximum entropy model. Almost one half of aberrant 3'ss was activated by AG-creating mutations and approximately 95% of the newly created AGs were selected in vivo. The overall nucleotide structure upstream of aberrant 3'ss was characterized by higher purine content than for authentic sites, particularly in position -3, that may be compensated by more stringent requirements for positive and negative nucleotide signatures centred around position -11. A newly developed online database of aberrant 3'ss will facilitate identification of splicing mutations in a gene or phenotype of interest and future optimization of splice site prediction tools
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Published date: September 2006
Keywords:
databases, comparative study, mutation, evaluation studies, genetics, algorithms, nucleic acid, nucleotides, genes, disease, humans, genetic diseases, research, rna splice sites, analysis, base composition, dna mutational analysis, rna, exons, utilization, internet, introns, research support, phenotype, human, methods, software, inborn, computational biology
Identifiers
Local EPrints ID: 60372
URI: http://eprints.soton.ac.uk/id/eprint/60372
ISSN: 0305-1048
PURE UUID: 2562912d-821b-4b17-9a42-ee6aca0d84aa
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Date deposited: 08 Sep 2008
Last modified: 16 Mar 2024 03:32
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