Facilitating population genomics of non-model organisms through optimized experimental design for reduced representation sequencing
Abstract 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...
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ftdatacite:10.6084/m9.figshare.c.5576202.v1 2023-05-15T13:57:17+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 https://dx.doi.org/10.6084/m9.figshare.c.5576202.v1 https://springernature.figshare.com/collections/Facilitating_population_genomics_of_non-model_organisms_through_optimized_experimental_design_for_reduced_representation_sequencing/5576202/1 unknown figshare https://dx.doi.org/10.1186/s12864-021-07917-3 https://dx.doi.org/10.6084/m9.figshare.c.5576202 Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 CC-BY Genetics FOS Biological sciences Collection article 2021 ftdatacite https://doi.org/10.6084/m9.figshare.c.5576202.v1 https://doi.org/10.1186/s12864-021-07917-3 https://doi.org/10.6084/m9.figshare.c.5576202 2021-11-05T12:55:41Z Abstract 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. Article in Journal/Newspaper Antarc* Antarctic DataCite Metadata Store (German National Library of Science and Technology) Antarctic |
institution |
Open Polar |
collection |
DataCite Metadata Store (German National Library of Science and Technology) |
op_collection_id |
ftdatacite |
language |
unknown |
topic |
Genetics FOS Biological sciences |
spellingShingle |
Genetics FOS Biological sciences 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 |
Genetics FOS Biological sciences |
description |
Abstract 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. |
format |
Article in Journal/Newspaper |
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 |
figshare |
publishDate |
2021 |
url |
https://dx.doi.org/10.6084/m9.figshare.c.5576202.v1 https://springernature.figshare.com/collections/Facilitating_population_genomics_of_non-model_organisms_through_optimized_experimental_design_for_reduced_representation_sequencing/5576202/1 |
geographic |
Antarctic |
geographic_facet |
Antarctic |
genre |
Antarc* Antarctic |
genre_facet |
Antarc* Antarctic |
op_relation |
https://dx.doi.org/10.1186/s12864-021-07917-3 https://dx.doi.org/10.6084/m9.figshare.c.5576202 |
op_rights |
Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode cc-by-4.0 |
op_rightsnorm |
CC-BY |
op_doi |
https://doi.org/10.6084/m9.figshare.c.5576202.v1 https://doi.org/10.1186/s12864-021-07917-3 https://doi.org/10.6084/m9.figshare.c.5576202 |
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1766264873076916224 |