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The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology

Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projec...

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Autores principales: Gardner, Eugene J., Lam, Vincent K., Harris, Daniel N., Chuang, Nelson T., Scott, Emma C., Pittard, W. Stephen, Mills, Ryan E., Devine, Scott E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668948/
https://www.ncbi.nlm.nih.gov/pubmed/28855259
http://dx.doi.org/10.1101/gr.218032.116
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author Gardner, Eugene J.
Lam, Vincent K.
Harris, Daniel N.
Chuang, Nelson T.
Scott, Emma C.
Pittard, W. Stephen
Mills, Ryan E.
Devine, Scott E.
author_facet Gardner, Eugene J.
Lam, Vincent K.
Harris, Daniel N.
Chuang, Nelson T.
Scott, Emma C.
Pittard, W. Stephen
Mills, Ryan E.
Devine, Scott E.
author_sort Gardner, Eugene J.
collection PubMed
description Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projects involving population genetics, human diseases, and clinical genomics. Here, we describe the Mobile Element Locator Tool (MELT), which was developed as part of the 1000 Genomes Project to perform MEI discovery on a population scale. Using both Illumina WGS data and simulations, we demonstrate that MELT outperforms existing MEI discovery tools in terms of speed, scalability, specificity, and sensitivity, while also detecting a broader spectrum of MEI-associated features. Several run modes were developed to perform MEI discovery on local and cloud systems. In addition to using MELT to discover MEIs in modern humans as part of the 1000 Genomes Project, we also used it to discover MEIs in chimpanzees and ancient (Neanderthal and Denisovan) hominids. We detected diverse patterns of MEI stratification across these populations that likely were caused by (1) diverse rates of MEI production from source elements, (2) diverse patterns of MEI inheritance, and (3) the introgression of ancient MEIs into modern human genomes. Overall, our study provides the most comprehensive map of MEIs to date spanning chimpanzees, ancient hominids, and modern humans and reveals new aspects of MEI biology in these lineages. We also demonstrate that MELT is a robust platform for MEI discovery and analysis in a variety of experimental settings.
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spelling pubmed-56689482017-11-13 The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology Gardner, Eugene J. Lam, Vincent K. Harris, Daniel N. Chuang, Nelson T. Scott, Emma C. Pittard, W. Stephen Mills, Ryan E. Devine, Scott E. Genome Res Method Mobile element insertions (MEIs) represent ∼25% of all structural variants in human genomes. Moreover, when they disrupt genes, MEIs can influence human traits and diseases. Therefore, MEIs should be fully discovered along with other forms of genetic variation in whole genome sequencing (WGS) projects involving population genetics, human diseases, and clinical genomics. Here, we describe the Mobile Element Locator Tool (MELT), which was developed as part of the 1000 Genomes Project to perform MEI discovery on a population scale. Using both Illumina WGS data and simulations, we demonstrate that MELT outperforms existing MEI discovery tools in terms of speed, scalability, specificity, and sensitivity, while also detecting a broader spectrum of MEI-associated features. Several run modes were developed to perform MEI discovery on local and cloud systems. In addition to using MELT to discover MEIs in modern humans as part of the 1000 Genomes Project, we also used it to discover MEIs in chimpanzees and ancient (Neanderthal and Denisovan) hominids. We detected diverse patterns of MEI stratification across these populations that likely were caused by (1) diverse rates of MEI production from source elements, (2) diverse patterns of MEI inheritance, and (3) the introgression of ancient MEIs into modern human genomes. Overall, our study provides the most comprehensive map of MEIs to date spanning chimpanzees, ancient hominids, and modern humans and reveals new aspects of MEI biology in these lineages. We also demonstrate that MELT is a robust platform for MEI discovery and analysis in a variety of experimental settings. Cold Spring Harbor Laboratory Press 2017-11 /pmc/articles/PMC5668948/ /pubmed/28855259 http://dx.doi.org/10.1101/gr.218032.116 Text en © 2017 Gardner et al.; Published by Cold Spring Harbor Laboratory Press http://creativecommons.org/licenses/by/4.0/ This article, published in Genome Research, is available under a Creative Commons License (Attribution 4.0 International), as described at http://creativecommons.org/licenses/by/4.0/.
spellingShingle Method
Gardner, Eugene J.
Lam, Vincent K.
Harris, Daniel N.
Chuang, Nelson T.
Scott, Emma C.
Pittard, W. Stephen
Mills, Ryan E.
Devine, Scott E.
The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title_full The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title_fullStr The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title_full_unstemmed The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title_short The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology
title_sort mobile element locator tool (melt): population-scale mobile element discovery and biology
topic Method
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5668948/
https://www.ncbi.nlm.nih.gov/pubmed/28855259
http://dx.doi.org/10.1101/gr.218032.116
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