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Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation
A significant number of human X-linked genes escape X chromosome inactivation and are thus expressed from both the active and inactive X chromosomes. The basis for escape from inactivation and the potential role of the X chromosome primary DNA sequence in determining a gene's X inactivation sta...
Autores principales: | , , , |
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Formato: | Texto |
Lenguaje: | English |
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Public Library of Science
2006
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557588/ https://www.ncbi.nlm.nih.gov/pubmed/16948528 http://dx.doi.org/10.1371/journal.pcbi.0020113 |
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author | Wang, Zhong Willard, Huntington F Mukherjee, Sayan Furey, Terrence S |
author_facet | Wang, Zhong Willard, Huntington F Mukherjee, Sayan Furey, Terrence S |
author_sort | Wang, Zhong |
collection | PubMed |
description | A significant number of human X-linked genes escape X chromosome inactivation and are thus expressed from both the active and inactive X chromosomes. The basis for escape from inactivation and the potential role of the X chromosome primary DNA sequence in determining a gene's X inactivation status is unclear. Using a combination of the X chromosome sequence and a comprehensive X inactivation profile of more than 600 genes, two independent yet complementary approaches were used to systematically investigate the relationship between X inactivation and DNA sequence features. First, statistical analyses revealed that a number of repeat features, including long interspersed nuclear element (LINE) and mammalian-wide interspersed repeat repetitive elements, are significantly enriched in regions surrounding transcription start sites of genes that are subject to inactivation, while Alu repetitive elements and short motifs containing ACG/CGT are significantly enriched in those that escape inactivation. Second, linear support vector machine classifiers constructed using primary DNA sequence features were used to correctly predict the X inactivation status for >80% of all X-linked genes. We further identified a small set of features that are important for accurate classification, among which LINE-1 and LINE-2 content show the greatest individual discriminatory power. Finally, as few as 12 features can be used for accurate support vector machine classification. Taken together, these results suggest that features of the underlying primary DNA sequence of the human X chromosome may influence the spreading and/or maintenance of X inactivation. |
format | Text |
id | pubmed-1557588 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2006 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-15575882006-10-02 Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation Wang, Zhong Willard, Huntington F Mukherjee, Sayan Furey, Terrence S PLoS Comput Biol Research Article A significant number of human X-linked genes escape X chromosome inactivation and are thus expressed from both the active and inactive X chromosomes. The basis for escape from inactivation and the potential role of the X chromosome primary DNA sequence in determining a gene's X inactivation status is unclear. Using a combination of the X chromosome sequence and a comprehensive X inactivation profile of more than 600 genes, two independent yet complementary approaches were used to systematically investigate the relationship between X inactivation and DNA sequence features. First, statistical analyses revealed that a number of repeat features, including long interspersed nuclear element (LINE) and mammalian-wide interspersed repeat repetitive elements, are significantly enriched in regions surrounding transcription start sites of genes that are subject to inactivation, while Alu repetitive elements and short motifs containing ACG/CGT are significantly enriched in those that escape inactivation. Second, linear support vector machine classifiers constructed using primary DNA sequence features were used to correctly predict the X inactivation status for >80% of all X-linked genes. We further identified a small set of features that are important for accurate classification, among which LINE-1 and LINE-2 content show the greatest individual discriminatory power. Finally, as few as 12 features can be used for accurate support vector machine classification. Taken together, these results suggest that features of the underlying primary DNA sequence of the human X chromosome may influence the spreading and/or maintenance of X inactivation. Public Library of Science 2006-09 2006-09-01 /pmc/articles/PMC1557588/ /pubmed/16948528 http://dx.doi.org/10.1371/journal.pcbi.0020113 Text en © 2006 Wang et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Wang, Zhong Willard, Huntington F Mukherjee, Sayan Furey, Terrence S Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title | Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title_full | Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title_fullStr | Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title_full_unstemmed | Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title_short | Evidence of Influence of Genomic DNA Sequence on Human X Chromosome Inactivation |
title_sort | evidence of influence of genomic dna sequence on human x chromosome inactivation |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1557588/ https://www.ncbi.nlm.nih.gov/pubmed/16948528 http://dx.doi.org/10.1371/journal.pcbi.0020113 |
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