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A targeted capture approach to generating reference sequence databases for chloroplast gene regions

Metabarcoding has improved the way we understand plants within our environment, from their ecology and conservation to invasive species management. The notion of identifying plant taxa within environmental samples relies on the ability to match unknown sequences to known reference libraries. Without...

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Autores principales: Foster, Nicole R., van Dijk, Kor‐jent, Biffin, Ed, Young, Jennifer M., Thomson, Vicki A., Gillanders, Bronwyn M., Jones, Alice R., Waycott, Michelle
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001157/
https://www.ncbi.nlm.nih.gov/pubmed/35432922
http://dx.doi.org/10.1002/ece3.8816
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author Foster, Nicole R.
van Dijk, Kor‐jent
Biffin, Ed
Young, Jennifer M.
Thomson, Vicki A.
Gillanders, Bronwyn M.
Jones, Alice R.
Waycott, Michelle
author_facet Foster, Nicole R.
van Dijk, Kor‐jent
Biffin, Ed
Young, Jennifer M.
Thomson, Vicki A.
Gillanders, Bronwyn M.
Jones, Alice R.
Waycott, Michelle
author_sort Foster, Nicole R.
collection PubMed
description Metabarcoding has improved the way we understand plants within our environment, from their ecology and conservation to invasive species management. The notion of identifying plant taxa within environmental samples relies on the ability to match unknown sequences to known reference libraries. Without comprehensive reference databases, species can go undetected or be incorrectly assigned, leading to false‐positive and false‐negative detections. To improve our ability to generate reference sequence databases, we developed a targeted capture approach using the OZBaits_CP V1.0 set, designed to capture chloroplast gene regions across the entirety of flowering plant diversity. We focused on generating a reference database for coastal temperate plant species given the lack of reference sequences for these taxa. Our approach was successful across all specimens with a target gene recovery rate of 92%, which was achieved in a single assay (i.e., samples were pooled), thus making this approach much faster and more efficient than standard barcoding. Further testing of this database highlighted 80% of all samples could be discriminated to family level across all gene regions with some genes achieving greater resolution than others—which was also dependent on the taxon of interest. Thus, we demonstrate the importance of generating reference sequences across multiple chloroplast gene regions as no single loci are sufficient to discriminate across all plant groups. The targeted capture approach outlined in this study provides a way forward to achieve this.
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spelling pubmed-90011572022-04-15 A targeted capture approach to generating reference sequence databases for chloroplast gene regions Foster, Nicole R. van Dijk, Kor‐jent Biffin, Ed Young, Jennifer M. Thomson, Vicki A. Gillanders, Bronwyn M. Jones, Alice R. Waycott, Michelle Ecol Evol Research Articles Metabarcoding has improved the way we understand plants within our environment, from their ecology and conservation to invasive species management. The notion of identifying plant taxa within environmental samples relies on the ability to match unknown sequences to known reference libraries. Without comprehensive reference databases, species can go undetected or be incorrectly assigned, leading to false‐positive and false‐negative detections. To improve our ability to generate reference sequence databases, we developed a targeted capture approach using the OZBaits_CP V1.0 set, designed to capture chloroplast gene regions across the entirety of flowering plant diversity. We focused on generating a reference database for coastal temperate plant species given the lack of reference sequences for these taxa. Our approach was successful across all specimens with a target gene recovery rate of 92%, which was achieved in a single assay (i.e., samples were pooled), thus making this approach much faster and more efficient than standard barcoding. Further testing of this database highlighted 80% of all samples could be discriminated to family level across all gene regions with some genes achieving greater resolution than others—which was also dependent on the taxon of interest. Thus, we demonstrate the importance of generating reference sequences across multiple chloroplast gene regions as no single loci are sufficient to discriminate across all plant groups. The targeted capture approach outlined in this study provides a way forward to achieve this. John Wiley and Sons Inc. 2022-04-11 /pmc/articles/PMC9001157/ /pubmed/35432922 http://dx.doi.org/10.1002/ece3.8816 Text en © 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Foster, Nicole R.
van Dijk, Kor‐jent
Biffin, Ed
Young, Jennifer M.
Thomson, Vicki A.
Gillanders, Bronwyn M.
Jones, Alice R.
Waycott, Michelle
A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title_full A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title_fullStr A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title_full_unstemmed A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title_short A targeted capture approach to generating reference sequence databases for chloroplast gene regions
title_sort targeted capture approach to generating reference sequence databases for chloroplast gene regions
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9001157/
https://www.ncbi.nlm.nih.gov/pubmed/35432922
http://dx.doi.org/10.1002/ece3.8816
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