OMMA enables population-scale analysis of complex genomic features and phylogenomic relationships from nanochannel-based optical maps
| Autor: | Pui-Yan Kwok, Le Li, Melissa Chun-Jiao Liu, Yvonne Y. Y. Lai, Alden King-Yung Leung, Pak-Leung Ho, Ting-Fung Chan, Catherine J. Chu, Kevin Y. Yip |
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| Rok vydání: | 2018 |
| Předmět: |
haplotypes
Computer science Population Health Informatics Computational biology comparative genomics Genome Structural variation 03 medical and health sciences Genetic Genetics Technical Note Humans Copy-number variation Optical Restriction Mapping 1000 Genomes Project Polymorphism education single-molecule analysis Phylogeny 030304 developmental biology Comparative genomics 0303 health sciences education.field_of_study Polymorphism Genetic biology Contig Genome Human 030302 biochemistry & molecular biology Human Genome structural variation copy number variation DNA Genomics Sequence Analysis DNA biology.organism_classification Computer Science Applications optical mapping Omma Sequence Analysis Software Human |
| Zdroj: | GigaScience GigaScience, vol 8, iss 7 |
| ISSN: | 2047-217X |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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