Comparative analysis using K-mer and K-flank patterns provides evidence for CpG island sequence evolution in mammalian genomes
Identifieur interne : 002033 ( Main/Exploration ); précédent : 002032; suivant : 002034Comparative analysis using K-mer and K-flank patterns provides evidence for CpG island sequence evolution in mammalian genomes
Auteurs : Heejoon Chae [États-Unis] ; Jinwoo Park [Corée du Sud] ; Seong-Whan Lee [Corée du Sud] ; Kenneth P. Nephew [États-Unis] ; Sun Kim [Corée du Sud]Source :
- Nucleic Acids Research [ 0305-1048 ] ; 2013.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- classification : Mammals.
- genetics : Mammals.
- methods : Genomics.
- Algorithms, Animals, Artificial Intelligence, CpG Islands, Evolution, Molecular, Humans, Phylogeny, Sequence Analysis, DNA.
Abstract
CpG islands are GC-rich regions often located in the 5′ end of genes and normally protected from cytosine methylation in mammals. The important role of CpG islands in gene transcription strongly suggests evolutionary conservation in the mammalian genome. However, as CpG dinucleotides are over-represented in CpG islands, comparative CpG island analysis using conventional sequence analysis techniques remains a major challenge in the epigenetics field. In this study, we conducted a comparative analysis of all CpG island sequences in 10 mammalian genomes. As sequence similarity methods and character composition techniques such as information theory are particularly difficult to conduct, we used exact patterns in CpG island sequences and single character discrepancies to identify differences in CpG island sequences. First, by calculating genome distance based on rank correlation tests, we show that k-mer and k-flank patterns around CpG sites can be used to correctly reconstruct the phylogeny of 10 mammalian genomes. Further, we used various machine learning algorithms to demonstrate that CpG islands sequences can be characterized using k-mers. In addition, by testing a human model on the nine different mammalian genomes, we provide the first evidence that k-mer signatures are consistent with evolutionary history.
Url:
DOI: 10.1093/nar/gkt144
PubMed: 23519616
PubMed Central: 3643570
Affiliations:
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Le document en format XML
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<front><div type="abstract" xml:lang="en"><p>CpG islands are GC-rich regions often located in the 5′ end of genes and normally protected from cytosine methylation in mammals. The important role of CpG islands in gene transcription strongly suggests evolutionary conservation in the mammalian genome. However, as CpG dinucleotides are over-represented in CpG islands, comparative CpG island analysis using conventional sequence analysis techniques remains a major challenge in the epigenetics field. In this study, we conducted a comparative analysis of all CpG island sequences in 10 mammalian genomes. As sequence similarity methods and character composition techniques such as information theory are particularly difficult to conduct, we used exact patterns in CpG island sequences and single character discrepancies to identify differences in CpG island sequences. First, by calculating genome distance based on rank correlation tests, we show that k-mer and k-flank patterns around CpG sites can be used to correctly reconstruct the phylogeny of 10 mammalian genomes. Further, we used various machine learning algorithms to demonstrate that CpG islands sequences can be characterized using k-mers. In addition, by testing a human model on the nine different mammalian genomes, we provide the first evidence that k-mer signatures are consistent with evolutionary history.</p>
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</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Kendall, Mg" uniqKey="Kendall M">MG Kendall</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Fredsiund, J" uniqKey="Fredsiund J">J Fredsiund</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Witten, Lh" uniqKey="Witten L">LH Witten</name>
</author>
<author><name sortKey="Frank, E" uniqKey="Frank E">E Frank</name>
</author>
</analytic>
</biblStruct>
<biblStruct><analytic><author><name sortKey="Miele, V" uniqKey="Miele V">V Miele</name>
</author>
<author><name sortKey="Bourguignon, Py" uniqKey="Bourguignon P">PY Bourguignon</name>
</author>
<author><name sortKey="Robelin, D" uniqKey="Robelin D">D Robelin</name>
</author>
<author><name sortKey="Nuel, G" uniqKey="Nuel G">G Nuel</name>
</author>
<author><name sortKey="Richard, H" uniqKey="Richard H">H Richard</name>
</author>
</analytic>
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</div1>
</back>
</TEI>
<affiliations><list><country><li>Corée du Sud</li>
<li>États-Unis</li>
</country>
<region><li>Indiana</li>
<li>Région capitale de Séoul</li>
</region>
<settlement><li>Séoul</li>
</settlement>
<orgName><li>Université nationale de Séoul</li>
</orgName>
</list>
<tree><country name="États-Unis"><region name="Indiana"><name sortKey="Chae, Heejoon" sort="Chae, Heejoon" uniqKey="Chae H" first="Heejoon" last="Chae">Heejoon Chae</name>
</region>
<name sortKey="Nephew, Kenneth P" sort="Nephew, Kenneth P" uniqKey="Nephew K" first="Kenneth P." last="Nephew">Kenneth P. Nephew</name>
</country>
<country name="Corée du Sud"><region name="Région capitale de Séoul"><name sortKey="Park, Jinwoo" sort="Park, Jinwoo" uniqKey="Park J" first="Jinwoo" last="Park">Jinwoo Park</name>
</region>
<name sortKey="Kim, Sun" sort="Kim, Sun" uniqKey="Kim S" first="Sun" last="Kim">Sun Kim</name>
<name sortKey="Kim, Sun" sort="Kim, Sun" uniqKey="Kim S" first="Sun" last="Kim">Sun Kim</name>
<name sortKey="Lee, Seong Whan" sort="Lee, Seong Whan" uniqKey="Lee S" first="Seong-Whan" last="Lee">Seong-Whan Lee</name>
<name sortKey="Park, Jinwoo" sort="Park, Jinwoo" uniqKey="Park J" first="Jinwoo" last="Park">Jinwoo Park</name>
</country>
</tree>
</affiliations>
</record>
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