Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.

High throughput sequencing technologies are revolutionizing genetic research. With this "rise of the machines", genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored...

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Autores principales:	Florian Leese, Philipp Brand, Andrey Rozenberg, Christoph Mayer, Shobhit Agrawal, Johannes Dambach, Lars Dietz, Jana S Doemel, William P Goodall-Copstake, Christoph Held, Jennifer A Jackson, Kathrin P Lampert, Katrin Linse, Jan N Macher, Jennifer Nolzen, Michael J Raupach, Nicole T Rivera, Christoph D Schubart, Sebastian Striewski, Ralph Tollrian, Chester J Sands
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e4fbd7d257b44d0395e95b9e28f54023
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spelling	oai:doaj.org-article:e4fbd7d257b44d0395e95b9e28f540232021-11-18T08:08:01ZExploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.1932-620310.1371/journal.pone.0049202https://doaj.org/article/e4fbd7d257b44d0395e95b9e28f540232012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23185309/?tool=EBIhttps://doaj.org/toc/1932-6203High throughput sequencing technologies are revolutionizing genetic research. With this "rise of the machines", genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02-25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers.Florian LeesePhilipp BrandAndrey RozenbergChristoph MayerShobhit AgrawalJohannes DambachLars DietzJana S DoemelWilliam P Goodall-CopstakeChristoph HeldJennifer A JacksonKathrin P LampertKatrin LinseJan N MacherJennifer NolzenMichael J RaupachNicole T RiveraChristoph D SchubartSebastian StriewskiRalph TollrianChester J SandsPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 11, p e49202 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Florian Leese Philipp Brand Andrey Rozenberg Christoph Mayer Shobhit Agrawal Johannes Dambach Lars Dietz Jana S Doemel William P Goodall-Copstake Christoph Held Jennifer A Jackson Kathrin P Lampert Katrin Linse Jan N Macher Jennifer Nolzen Michael J Raupach Nicole T Rivera Christoph D Schubart Sebastian Striewski Ralph Tollrian Chester J Sands Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
description	High throughput sequencing technologies are revolutionizing genetic research. With this "rise of the machines", genomic sequences can be obtained even for unknown genomes within a short time and for reasonable costs. This has enabled evolutionary biologists studying genetically unexplored species to identify molecular markers or genomic regions of interest (e.g. micro- and minisatellites, mitochondrial and nuclear genes) by sequencing only a fraction of the genome. However, when using such datasets from non-model species, it is possible that DNA from non-target contaminant species such as bacteria, viruses, fungi, or other eukaryotic organisms may complicate the interpretation of the results. In this study we analysed 14 genomic pyrosequencing libraries of aquatic non-model taxa from four major evolutionary lineages. We quantified the amount of suitable micro- and minisatellites, mitochondrial genomes, known nuclear genes and transposable elements and searched for contamination from various sources using bioinformatic approaches. Our results show that in all sequence libraries with estimated coverage of about 0.02-25%, many appropriate micro- and minisatellites, mitochondrial gene sequences and nuclear genes from different KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways could be identified and characterized. These can serve as markers for phylogenetic and population genetic analyses. A central finding of our study is that several genomic libraries suffered from different biases owing to non-target DNA or mobile elements. In particular, viruses, bacteria or eukaryote endosymbionts contributed significantly (up to 10%) to some of the libraries analysed. If not identified as such, genetic markers developed from high-throughput sequencing data for non-model organisms may bias evolutionary studies or fail completely in experimental tests. In conclusion, our study demonstrates the enormous potential of low-coverage genome survey sequences and suggests bioinformatic analysis workflows. The results also advise a more sophisticated filtering for problematic sequences and non-target genome sequences prior to developing markers.
format	article
author	Florian Leese Philipp Brand Andrey Rozenberg Christoph Mayer Shobhit Agrawal Johannes Dambach Lars Dietz Jana S Doemel William P Goodall-Copstake Christoph Held Jennifer A Jackson Kathrin P Lampert Katrin Linse Jan N Macher Jennifer Nolzen Michael J Raupach Nicole T Rivera Christoph D Schubart Sebastian Striewski Ralph Tollrian Chester J Sands
author_facet	Florian Leese Philipp Brand Andrey Rozenberg Christoph Mayer Shobhit Agrawal Johannes Dambach Lars Dietz Jana S Doemel William P Goodall-Copstake Christoph Held Jennifer A Jackson Kathrin P Lampert Katrin Linse Jan N Macher Jennifer Nolzen Michael J Raupach Nicole T Rivera Christoph D Schubart Sebastian Striewski Ralph Tollrian Chester J Sands
author_sort	Florian Leese
title	Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
title_short	Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
title_full	Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
title_fullStr	Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
title_full_unstemmed	Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
title_sort	exploring pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/e4fbd7d257b44d0395e95b9e28f54023
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Exploring Pandora's box: potential and pitfalls of low coverage genome surveys for evolutionary biology.

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