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Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.

Identifieur interne : 001447 ( PubMed/Corpus ); précédent : 001446; suivant : 001448

Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.

Auteurs : Ezzeddin Kamil Mohamed Hashim ; Rosni Abdullah

Source :

Journal of theoretical biology [ 1095-8541 ] ; 2015.

RBID : pubmed:26427337

English descriptors

KwdEn :
- Animals, Birds (genetics), Chromosomes, Human, Pair 21 (chemistry), Computational Biology, CpG Islands (genetics), DNA (genetics), Databases, Genetic, Fishes (genetics), Humans, Mammals (genetics), Nucleotide Motifs (genetics), Promoter Regions, Genetic.
MESH :
- chemical , genetics : DNA.
- chemistry : Chromosomes, Human, Pair 21.
- genetics : Birds, CpG Islands, Fishes, Mammals, Nucleotide Motifs.
- Animals, Computational Biology, Databases, Genetic, Humans, Promoter Regions, Genetic.

Abstract

Empirical analysis on k-mer DNA has been proven as an effective tool in finding unique patterns in DNA sequences which can lead to the discovery of potential sequence motifs. In an extensive study of empirical k-mer DNA on hundreds of organisms, the researchers found unique multi-modal k-mer spectra occur in the genomes of organisms from the tetrapod clade only which includes all mammals. The multi-modality is caused by the formation of the two lowest modes where k-mers under them are referred as the rare k-mers. The suppression of the two lowest modes (or the rare k-mers) can be attributed to the CG dinucleotide inclusions in them. Apart from that, the rare k-mers are selectively distributed in certain genomic features of CpG Island (CGI), promoter, 5' UTR, and exon. We correlated the rare k-mers with hundreds of annotated features using several bioinformatic tools, performed further intrinsic rare k-mer analyses within the correlated features, and modeled the elucidated rare k-mer clustering feature into a classifier to predict the correlated CGI and promoter features. Our correlation results show that rare k-mers are highly associated with several annotated features of CGI, promoter, 5' UTR, and open chromatin regions. Our intrinsic results show that rare k-mers have several unique topological, compositional, and clustering properties in CGI and promoter features. Finally, the performances of our RWC (rare-word clustering) method in predicting the CGI and promoter features are ranked among the top three, in eight of the CGI and promoter evaluations, among eight of the benchmarked datasets.

DOI: 10.1016/j.jtbi.2015.09.014
PubMed: 26427337

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pubmed:26427337

Le document en format XML

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<author><name sortKey="Mohamed Hashim, Ezzeddin Kamil" sort="Mohamed Hashim, Ezzeddin Kamil" uniqKey="Mohamed Hashim E" first="Ezzeddin Kamil" last="Mohamed Hashim">Ezzeddin Kamil Mohamed Hashim</name>
<affiliation><nlm:affiliation>School of Computer Sciences, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia. Electronic address: ezzeddin@usm.my.</nlm:affiliation>
</affiliation>
</author>
<author><name sortKey="Abdullah, Rosni" sort="Abdullah, Rosni" uniqKey="Abdullah R" first="Rosni" last="Abdullah">Rosni Abdullah</name>
<affiliation><nlm:affiliation>School of Computer Sciences, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia; National Advanced IPv6 Centre of Excellence (NAv6), School of Computer Sciences Building, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia.</nlm:affiliation>
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<sourceDesc><biblStruct><analytic><title xml:lang="en">Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.</title>
<author><name sortKey="Mohamed Hashim, Ezzeddin Kamil" sort="Mohamed Hashim, Ezzeddin Kamil" uniqKey="Mohamed Hashim E" first="Ezzeddin Kamil" last="Mohamed Hashim">Ezzeddin Kamil Mohamed Hashim</name>
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<author><name sortKey="Abdullah, Rosni" sort="Abdullah, Rosni" uniqKey="Abdullah R" first="Rosni" last="Abdullah">Rosni Abdullah</name>
<affiliation><nlm:affiliation>School of Computer Sciences, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia; National Advanced IPv6 Centre of Excellence (NAv6), School of Computer Sciences Building, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia.</nlm:affiliation>
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<term>Chromosomes, Human, Pair 21 (chemistry)</term>
<term>Computational Biology</term>
<term>CpG Islands (genetics)</term>
<term>DNA (genetics)</term>
<term>Databases, Genetic</term>
<term>Fishes (genetics)</term>
<term>Humans</term>
<term>Mammals (genetics)</term>
<term>Nucleotide Motifs (genetics)</term>
<term>Promoter Regions, Genetic</term>
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<front><div type="abstract" xml:lang="en">Empirical analysis on k-mer DNA has been proven as an effective tool in finding unique patterns in DNA sequences which can lead to the discovery of potential sequence motifs. In an extensive study of empirical k-mer DNA on hundreds of organisms, the researchers found unique multi-modal k-mer spectra occur in the genomes of organisms from the tetrapod clade only which includes all mammals. The multi-modality is caused by the formation of the two lowest modes where k-mers under them are referred as the rare k-mers. The suppression of the two lowest modes (or the rare k-mers) can be attributed to the CG dinucleotide inclusions in them. Apart from that, the rare k-mers are selectively distributed in certain genomic features of CpG Island (CGI), promoter, 5' UTR, and exon. We correlated the rare k-mers with hundreds of annotated features using several bioinformatic tools, performed further intrinsic rare k-mer analyses within the correlated features, and modeled the elucidated rare k-mer clustering feature into a classifier to predict the correlated CGI and promoter features. Our correlation results show that rare k-mers are highly associated with several annotated features of CGI, promoter, 5' UTR, and open chromatin regions. Our intrinsic results show that rare k-mers have several unique topological, compositional, and clustering properties in CGI and promoter features. Finally, the performances of our RWC (rare-word clustering) method in predicting the CGI and promoter features are ranked among the top three, in eight of the CGI and promoter evaluations, among eight of the benchmarked datasets. </div>
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<DateRevised><Year>2015</Year>
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<JournalIssue CitedMedium="Internet"><Volume>387</Volume>
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<Title>Journal of theoretical biology</Title>
<ISOAbbreviation>J. Theor. Biol.</ISOAbbreviation>
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<ArticleTitle>Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.</ArticleTitle>
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<Abstract><AbstractText>Empirical analysis on k-mer DNA has been proven as an effective tool in finding unique patterns in DNA sequences which can lead to the discovery of potential sequence motifs. In an extensive study of empirical k-mer DNA on hundreds of organisms, the researchers found unique multi-modal k-mer spectra occur in the genomes of organisms from the tetrapod clade only which includes all mammals. The multi-modality is caused by the formation of the two lowest modes where k-mers under them are referred as the rare k-mers. The suppression of the two lowest modes (or the rare k-mers) can be attributed to the CG dinucleotide inclusions in them. Apart from that, the rare k-mers are selectively distributed in certain genomic features of CpG Island (CGI), promoter, 5' UTR, and exon. We correlated the rare k-mers with hundreds of annotated features using several bioinformatic tools, performed further intrinsic rare k-mer analyses within the correlated features, and modeled the elucidated rare k-mer clustering feature into a classifier to predict the correlated CGI and promoter features. Our correlation results show that rare k-mers are highly associated with several annotated features of CGI, promoter, 5' UTR, and open chromatin regions. Our intrinsic results show that rare k-mers have several unique topological, compositional, and clustering properties in CGI and promoter features. Finally, the performances of our RWC (rare-word clustering) method in predicting the CGI and promoter features are ranked among the top three, in eight of the CGI and promoter evaluations, among eight of the benchmarked datasets. </AbstractText>
<CopyrightInformation>Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.</CopyrightInformation>
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<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Mohamed Hashim</LastName>
<ForeName>Ezzeddin Kamil</ForeName>
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<Author ValidYN="Y"><LastName>Abdullah</LastName>
<ForeName>Rosni</ForeName>
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<AffiliationInfo><Affiliation>School of Computer Sciences, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia; National Advanced IPv6 Centre of Excellence (NAv6), School of Computer Sciences Building, Universiti Sains Malaysia, 11800 Gelugor, Penang, Malaysia.</Affiliation>
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<Keyword MajorTopicYN="N">Genome</Keyword>
<Keyword MajorTopicYN="N">Rare-word</Keyword>
<Keyword MajorTopicYN="N">k-tuple</Keyword>
<Keyword MajorTopicYN="N">n-mer</Keyword>
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Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.

Rare k-mer DNA: Identification of sequence motifs and prediction of CpG island and promoter.

Source :

English descriptors

Abstract

Links to Exploration step

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