Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing
BACKGROUND: Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density...
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BioMed Central
2021
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Online Access: | http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380342/ http://www.ncbi.nlm.nih.gov/pubmed/34418978 https://doi.org/10.1186/s12864-021-07917-3 |
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Research Christiansen, Henrik Heindler, Franz M. Hellemans, Bart Jossart, Quentin Pasotti, Francesca Robert, Henri Verheye, Marie Danis, Bruno Kochzius, Marc Leliaert, Frederik Moreau, Camille Patel, Tasnim Van de Putte, Anton P. Vanreusel, Ann Volckaert, Filip A. M. Schön, Isa Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
topic_facet |
Research |
description |
BACKGROUND: Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. RESULTS: In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. CONCLUSIONS: Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07917-3. |
format |
Text |
author |
Christiansen, Henrik Heindler, Franz M. Hellemans, Bart Jossart, Quentin Pasotti, Francesca Robert, Henri Verheye, Marie Danis, Bruno Kochzius, Marc Leliaert, Frederik Moreau, Camille Patel, Tasnim Van de Putte, Anton P. Vanreusel, Ann Volckaert, Filip A. M. Schön, Isa |
author_facet |
Christiansen, Henrik Heindler, Franz M. Hellemans, Bart Jossart, Quentin Pasotti, Francesca Robert, Henri Verheye, Marie Danis, Bruno Kochzius, Marc Leliaert, Frederik Moreau, Camille Patel, Tasnim Van de Putte, Anton P. Vanreusel, Ann Volckaert, Filip A. M. Schön, Isa |
author_sort |
Christiansen, Henrik |
title |
Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
title_short |
Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
title_full |
Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
title_fullStr |
Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
title_full_unstemmed |
Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
title_sort |
facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing |
publisher |
BioMed Central |
publishDate |
2021 |
url |
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380342/ http://www.ncbi.nlm.nih.gov/pubmed/34418978 https://doi.org/10.1186/s12864-021-07917-3 |
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Antarctic |
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Antarc* Antarctic |
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Antarc* Antarctic |
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BMC Genomics |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380342/ http://www.ncbi.nlm.nih.gov/pubmed/34418978 http://dx.doi.org/10.1186/s12864-021-07917-3 |
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© The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
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https://doi.org/10.1186/s12864-021-07917-3 |
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BMC Genomics |
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22 |
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ftpubmed:oai:pubmedcentral.nih.gov:8380342 2023-05-15T13:33:11+02:00 Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing Christiansen, Henrik Heindler, Franz M. Hellemans, Bart Jossart, Quentin Pasotti, Francesca Robert, Henri Verheye, Marie Danis, Bruno Kochzius, Marc Leliaert, Frederik Moreau, Camille Patel, Tasnim Van de Putte, Anton P. Vanreusel, Ann Volckaert, Filip A. M. Schön, Isa 2021-08-21 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380342/ http://www.ncbi.nlm.nih.gov/pubmed/34418978 https://doi.org/10.1186/s12864-021-07917-3 en eng BioMed Central http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8380342/ http://www.ncbi.nlm.nih.gov/pubmed/34418978 http://dx.doi.org/10.1186/s12864-021-07917-3 © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. CC0 PDM CC-BY BMC Genomics Research Text 2021 ftpubmed https://doi.org/10.1186/s12864-021-07917-3 2021-08-29T00:38:46Z BACKGROUND: Genome-wide data are invaluable to characterize differentiation and adaptation of natural populations. Reduced representation sequencing (RRS) subsamples a genome repeatedly across many individuals. However, RRS requires careful optimization and fine-tuning to deliver high marker density while being cost-efficient. The number of genomic fragments created through restriction enzyme digestion and the sequencing library setup must match to achieve sufficient sequencing coverage per locus. Here, we present a workflow based on published information and computational and experimental procedures to investigate and streamline the applicability of RRS. RESULTS: In an iterative process genome size estimates, restriction enzymes and size selection windows were tested and scaled in six classes of Antarctic animals (Ostracoda, Malacostraca, Bivalvia, Asteroidea, Actinopterygii, Aves). Achieving high marker density would be expensive in amphipods, the malacostracan target taxon, due to the large genome size. We propose alternative approaches such as mitogenome or target capture sequencing for this group. Pilot libraries were sequenced for all other target taxa. Ostracods, bivalves, sea stars, and fish showed overall good coverage and marker numbers for downstream population genomic analyses. In contrast, the bird test library produced low coverage and few polymorphic loci, likely due to degraded DNA. CONCLUSIONS: Prior testing and optimization are important to identify which groups are amenable for RRS and where alternative methods may currently offer better cost-benefit ratios. The steps outlined here are easy to follow for other non-model taxa with little genomic resources, thus stimulating efficient resource use for the many pressing research questions in molecular ecology. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12864-021-07917-3. Text Antarc* Antarctic PubMed Central (PMC) Antarctic BMC Genomics 22 1 |