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Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers

BACKGROUND: Duchenne muscular dystrophy, a fatal muscle-wasting disease, is characterized by dystrophin deficiency caused by mutations in the dystrophin gene. Skipping of a target dystrophin exon during splicing with antisense oligonucleotides is attracting much attention as the most plausible way t...

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Autores principales: Malueka, Rusdy Ghazali, Takaoka, Yutaka, Yagi, Mariko, Awano, Hiroyuki, Lee, Tomoko, Dwianingsih, Ery Kus, Nishida, Atsushi, Takeshima, Yasuhiro, Matsuo, Masafumi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2012
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Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3350383/
https://www.ncbi.nlm.nih.gov/pubmed/22462762
http://dx.doi.org/10.1186/1471-2156-13-23
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author Malueka, Rusdy Ghazali
Takaoka, Yutaka
Yagi, Mariko
Awano, Hiroyuki
Lee, Tomoko
Dwianingsih, Ery Kus
Nishida, Atsushi
Takeshima, Yasuhiro
Matsuo, Masafumi
author_facet Malueka, Rusdy Ghazali
Takaoka, Yutaka
Yagi, Mariko
Awano, Hiroyuki
Lee, Tomoko
Dwianingsih, Ery Kus
Nishida, Atsushi
Takeshima, Yasuhiro
Matsuo, Masafumi
author_sort Malueka, Rusdy Ghazali
collection PubMed
description BACKGROUND: Duchenne muscular dystrophy, a fatal muscle-wasting disease, is characterized by dystrophin deficiency caused by mutations in the dystrophin gene. Skipping of a target dystrophin exon during splicing with antisense oligonucleotides is attracting much attention as the most plausible way to express dystrophin in DMD. Antisense oligonucleotides have been designed against splicing regulatory sequences such as splicing enhancer sequences of target exons. Recently, we reported that a chemical kinase inhibitor specifically enhances the skipping of mutated dystrophin exon 31, indicating the existence of exon-specific splicing regulatory systems. However, the basis for such individual regulatory systems is largely unknown. Here, we categorized the dystrophin exons in terms of their splicing regulatory factors. RESULTS: Using a computer-based machine learning system, we first constructed a decision tree separating 77 authentic from 14 known cryptic exons using 25 indexes of splicing regulatory factors as decision markers. We evaluated the classification accuracy of a novel cryptic exon (exon 11a) identified in this study. However, the tree mislabeled exon 11a as a true exon. Therefore, we re-constructed the decision tree to separate all 15 cryptic exons. The revised decision tree categorized the 77 authentic exons into five groups. Furthermore, all nine disease-associated novel exons were successfully categorized as exons, validating the decision tree. One group, consisting of 30 exons, was characterized by a high density of exonic splicing enhancer sequences. This suggests that AOs targeting splicing enhancer sequences would efficiently induce skipping of exons belonging to this group. CONCLUSIONS: The decision tree categorized the 77 authentic exons into five groups. Our classification may help to establish the strategy for exon skipping therapy for Duchenne muscular dystrophy.
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spelling pubmed-33503832012-05-12 Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers Malueka, Rusdy Ghazali Takaoka, Yutaka Yagi, Mariko Awano, Hiroyuki Lee, Tomoko Dwianingsih, Ery Kus Nishida, Atsushi Takeshima, Yasuhiro Matsuo, Masafumi BMC Genet Research Article BACKGROUND: Duchenne muscular dystrophy, a fatal muscle-wasting disease, is characterized by dystrophin deficiency caused by mutations in the dystrophin gene. Skipping of a target dystrophin exon during splicing with antisense oligonucleotides is attracting much attention as the most plausible way to express dystrophin in DMD. Antisense oligonucleotides have been designed against splicing regulatory sequences such as splicing enhancer sequences of target exons. Recently, we reported that a chemical kinase inhibitor specifically enhances the skipping of mutated dystrophin exon 31, indicating the existence of exon-specific splicing regulatory systems. However, the basis for such individual regulatory systems is largely unknown. Here, we categorized the dystrophin exons in terms of their splicing regulatory factors. RESULTS: Using a computer-based machine learning system, we first constructed a decision tree separating 77 authentic from 14 known cryptic exons using 25 indexes of splicing regulatory factors as decision markers. We evaluated the classification accuracy of a novel cryptic exon (exon 11a) identified in this study. However, the tree mislabeled exon 11a as a true exon. Therefore, we re-constructed the decision tree to separate all 15 cryptic exons. The revised decision tree categorized the 77 authentic exons into five groups. Furthermore, all nine disease-associated novel exons were successfully categorized as exons, validating the decision tree. One group, consisting of 30 exons, was characterized by a high density of exonic splicing enhancer sequences. This suggests that AOs targeting splicing enhancer sequences would efficiently induce skipping of exons belonging to this group. CONCLUSIONS: The decision tree categorized the 77 authentic exons into five groups. Our classification may help to establish the strategy for exon skipping therapy for Duchenne muscular dystrophy. BioMed Central 2012-03-31 /pmc/articles/PMC3350383/ /pubmed/22462762 http://dx.doi.org/10.1186/1471-2156-13-23 Text en Copyright ©2012 Malueka et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Malueka, Rusdy Ghazali
Takaoka, Yutaka
Yagi, Mariko
Awano, Hiroyuki
Lee, Tomoko
Dwianingsih, Ery Kus
Nishida, Atsushi
Takeshima, Yasuhiro
Matsuo, Masafumi
Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title_full Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title_fullStr Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title_full_unstemmed Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title_short Categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
title_sort categorization of 77 dystrophin exons into 5 groups by a decision tree using indexes of splicing regulatory factors as decision markers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3350383/
https://www.ncbi.nlm.nih.gov/pubmed/22462762
http://dx.doi.org/10.1186/1471-2156-13-23
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