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OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps

BACKGROUND: Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping...

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Autores principales: Leung, Alden King-Yung, Liu, Melissa Chun-Jiao, Li, Le, Lai, Yvonne Yuk-Yin, Chu, Catherine, Kwok, Pui-Yan, Ho, Pak-Leung, Yip, Kevin Y, Chan, Ting-Fung
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615982/
https://www.ncbi.nlm.nih.gov/pubmed/31289833
http://dx.doi.org/10.1093/gigascience/giz079
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author Leung, Alden King-Yung
Liu, Melissa Chun-Jiao
Li, Le
Lai, Yvonne Yuk-Yin
Chu, Catherine
Kwok, Pui-Yan
Ho, Pak-Leung
Yip, Kevin Y
Chan, Ting-Fung
author_facet Leung, Alden King-Yung
Liu, Melissa Chun-Jiao
Li, Le
Lai, Yvonne Yuk-Yin
Chu, Catherine
Kwok, Pui-Yan
Ho, Pak-Leung
Yip, Kevin Y
Chan, Ting-Fung
author_sort Leung, Alden King-Yung
collection PubMed
description BACKGROUND: Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples. FINDINGS: We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains. CONCLUSIONS: With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools.
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spelling pubmed-66159822019-07-15 OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps Leung, Alden King-Yung Liu, Melissa Chun-Jiao Li, Le Lai, Yvonne Yuk-Yin Chu, Catherine Kwok, Pui-Yan Ho, Pak-Leung Yip, Kevin Y Chan, Ting-Fung Gigascience Technical Note BACKGROUND: Optical mapping is an emerging technology that complements sequencing-based methods in genome analysis. It is widely used in improving genome assemblies and detecting structural variations by providing information over much longer (up to 1 Mb) reads. Current standards in optical mapping analysis involve assembling optical maps into contigs and aligning them to a reference, which is limited to pairwise comparison and becomes bias-prone when analyzing multiple samples. FINDINGS: We present a new method, OMMA, that extends optical mapping to the study of complex genomic features by simultaneously interrogating optical maps across many samples in a reference-independent manner. OMMA captures and characterizes complex genomic features, e.g., multiple haplotypes, copy number variations, and subtelomeric structures when applied to 154 human samples across the 26 populations sequenced in the 1000 Genomes Project. For small genomes such as pathogenic bacteria, OMMA accurately reconstructs the phylogenomic relationships and identifies functional elements across 21 Acinetobacter baumannii strains. CONCLUSIONS: With the increasing data throughput of optical mapping system, the use of this technology in comparative genome analysis across many samples will become feasible. OMMA is a timely solution that can address such computational need. The OMMA software is available at https://github.com/TF-Chan-Lab/OMTools. Oxford University Press 2019-07-09 /pmc/articles/PMC6615982/ /pubmed/31289833 http://dx.doi.org/10.1093/gigascience/giz079 Text en © The Author(s) 2019. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Technical Note
Leung, Alden King-Yung
Liu, Melissa Chun-Jiao
Li, Le
Lai, Yvonne Yuk-Yin
Chu, Catherine
Kwok, Pui-Yan
Ho, Pak-Leung
Yip, Kevin Y
Chan, Ting-Fung
OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title_full OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title_fullStr OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title_full_unstemmed OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title_short OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
title_sort omma enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
topic Technical Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6615982/
https://www.ncbi.nlm.nih.gov/pubmed/31289833
http://dx.doi.org/10.1093/gigascience/giz079
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