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Shape-based alignment of genomic landscapes in multi-scale resolution

Due to dramatic advances in DNA technology, quantitative measures of annotation data can now be obtained in continuous coordinates across the entire genome, allowing various heterogeneous ‘genomic landscapes’ to emerge. Although much effort has been devoted to comparing DNA sequences, not much atten...

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Detalles Bibliográficos
Autores principales: Ashida, Hiroki, Asai, Kiyoshi, Hamada, Michiaki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3413149/
https://www.ncbi.nlm.nih.gov/pubmed/22561376
http://dx.doi.org/10.1093/nar/gks354
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author Ashida, Hiroki
Asai, Kiyoshi
Hamada, Michiaki
author_facet Ashida, Hiroki
Asai, Kiyoshi
Hamada, Michiaki
author_sort Ashida, Hiroki
collection PubMed
description Due to dramatic advances in DNA technology, quantitative measures of annotation data can now be obtained in continuous coordinates across the entire genome, allowing various heterogeneous ‘genomic landscapes’ to emerge. Although much effort has been devoted to comparing DNA sequences, not much attention has been given to comparing these large quantities of data comprehensively. In this article, we introduce a method for rapidly detecting local regions that show high correlations between genomic landscapes. We overcame the size problem for genome-wide data by converting the data into series of symbols and then carrying out sequence alignment. We also decomposed the oscillation of the landscape data into different frequency bands before analysis, since the real genomic landscape is a mixture of embedded and confounded biological processes working at different scales in the cell nucleus. To verify the usefulness and generality of our method, we applied our approach to well investigated landscapes from the human genome, including several histone modifications. Furthermore, by applying our method to over 20 genomic landscapes in human and 12 in mouse, we found that DNA replication timing and the density of Alu insertions are highly correlated genome-wide in both species, even though the Alu elements have amplified independently in the two genomes. To our knowledge, this is the first method to align genomic landscapes at multiple scales according to their shape.
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spelling pubmed-34131492012-08-07 Shape-based alignment of genomic landscapes in multi-scale resolution Ashida, Hiroki Asai, Kiyoshi Hamada, Michiaki Nucleic Acids Res Computational Biology Due to dramatic advances in DNA technology, quantitative measures of annotation data can now be obtained in continuous coordinates across the entire genome, allowing various heterogeneous ‘genomic landscapes’ to emerge. Although much effort has been devoted to comparing DNA sequences, not much attention has been given to comparing these large quantities of data comprehensively. In this article, we introduce a method for rapidly detecting local regions that show high correlations between genomic landscapes. We overcame the size problem for genome-wide data by converting the data into series of symbols and then carrying out sequence alignment. We also decomposed the oscillation of the landscape data into different frequency bands before analysis, since the real genomic landscape is a mixture of embedded and confounded biological processes working at different scales in the cell nucleus. To verify the usefulness and generality of our method, we applied our approach to well investigated landscapes from the human genome, including several histone modifications. Furthermore, by applying our method to over 20 genomic landscapes in human and 12 in mouse, we found that DNA replication timing and the density of Alu insertions are highly correlated genome-wide in both species, even though the Alu elements have amplified independently in the two genomes. To our knowledge, this is the first method to align genomic landscapes at multiple scales according to their shape. Oxford University Press 2012-08 2012-05-04 /pmc/articles/PMC3413149/ /pubmed/22561376 http://dx.doi.org/10.1093/nar/gks354 Text en © The Author(s) 2012. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Ashida, Hiroki
Asai, Kiyoshi
Hamada, Michiaki
Shape-based alignment of genomic landscapes in multi-scale resolution
title Shape-based alignment of genomic landscapes in multi-scale resolution
title_full Shape-based alignment of genomic landscapes in multi-scale resolution
title_fullStr Shape-based alignment of genomic landscapes in multi-scale resolution
title_full_unstemmed Shape-based alignment of genomic landscapes in multi-scale resolution
title_short Shape-based alignment of genomic landscapes in multi-scale resolution
title_sort shape-based alignment of genomic landscapes in multi-scale resolution
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3413149/
https://www.ncbi.nlm.nih.gov/pubmed/22561376
http://dx.doi.org/10.1093/nar/gks354
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