DNA barcoding the native flowering plants and conifers of Wales.

We present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the nati...

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Main Authors: Natasha de Vere, Tim C G Rich, Col R Ford, Sarah A Trinder, Charlotte Long, Chris W Moore, Danielle Satterthwaite, Helena Davies, Joel Allainguillaume, Sandra Ronca, Tatiana Tatarinova, Hannah Garbett, Kevin Walker, Mike J Wilkinson
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2012-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22701588/pdf/?tool=EBI
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author Natasha de Vere
Tim C G Rich
Col R Ford
Sarah A Trinder
Charlotte Long
Chris W Moore
Danielle Satterthwaite
Helena Davies
Joel Allainguillaume
Sandra Ronca
Tatiana Tatarinova
Hannah Garbett
Kevin Walker
Mike J Wilkinson
author_facet Natasha de Vere
Tim C G Rich
Col R Ford
Sarah A Trinder
Charlotte Long
Chris W Moore
Danielle Satterthwaite
Helena Davies
Joel Allainguillaume
Sandra Ronca
Tatiana Tatarinova
Hannah Garbett
Kevin Walker
Mike J Wilkinson
author_sort Natasha de Vere
collection DOAJ
description We present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the native Welsh flora. We have sampled multiple individuals for each species, resulting in 3304 rbcL and 2419 matK sequences. The majority of our samples (85%) are from DNA extracted from herbarium specimens. Recoverability of DNA barcodes is lower using herbarium specimens, compared to freshly collected material, mostly due to lower amplification success, but this is balanced by the increased efficiency of sampling species that have already been collected, identified, and verified by taxonomic experts. The effectiveness of the DNA barcodes for identification (level of discrimination) is assessed using four approaches: the presence of a barcode gap (using pairwise and multiple alignments), formation of monophyletic groups using Neighbour-Joining trees, and sequence similarity in BLASTn searches. These approaches yield similar results, providing relative discrimination levels of 69.4 to 74.9% of all species and 98.6 to 99.8% of genera using both markers. Species discrimination can be further improved using spatially explicit sampling. Mean species discrimination using barcode gap analysis (with a multiple alignment) is 81.6% within 10×10 km squares and 93.3% for 2×2 km squares. Our database of DNA barcodes for Welsh native flowering plants and conifers represents the most complete coverage of any national flora, and offers a valuable platform for a wide range of applications that require accurate species identification.
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spelling doaj.art-207b3391e21049a3bddb94d64c196cbd2022-12-21T22:57:57ZengPublic Library of Science (PLoS)PLoS ONE1932-62032012-01-0176e3794510.1371/journal.pone.0037945DNA barcoding the native flowering plants and conifers of Wales.Natasha de VereTim C G RichCol R FordSarah A TrinderCharlotte LongChris W MooreDanielle SatterthwaiteHelena DaviesJoel AllainguillaumeSandra RoncaTatiana TatarinovaHannah GarbettKevin WalkerMike J WilkinsonWe present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the native Welsh flora. We have sampled multiple individuals for each species, resulting in 3304 rbcL and 2419 matK sequences. The majority of our samples (85%) are from DNA extracted from herbarium specimens. Recoverability of DNA barcodes is lower using herbarium specimens, compared to freshly collected material, mostly due to lower amplification success, but this is balanced by the increased efficiency of sampling species that have already been collected, identified, and verified by taxonomic experts. The effectiveness of the DNA barcodes for identification (level of discrimination) is assessed using four approaches: the presence of a barcode gap (using pairwise and multiple alignments), formation of monophyletic groups using Neighbour-Joining trees, and sequence similarity in BLASTn searches. These approaches yield similar results, providing relative discrimination levels of 69.4 to 74.9% of all species and 98.6 to 99.8% of genera using both markers. Species discrimination can be further improved using spatially explicit sampling. Mean species discrimination using barcode gap analysis (with a multiple alignment) is 81.6% within 10×10 km squares and 93.3% for 2×2 km squares. Our database of DNA barcodes for Welsh native flowering plants and conifers represents the most complete coverage of any national flora, and offers a valuable platform for a wide range of applications that require accurate species identification.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22701588/pdf/?tool=EBI
spellingShingle Natasha de Vere
Tim C G Rich
Col R Ford
Sarah A Trinder
Charlotte Long
Chris W Moore
Danielle Satterthwaite
Helena Davies
Joel Allainguillaume
Sandra Ronca
Tatiana Tatarinova
Hannah Garbett
Kevin Walker
Mike J Wilkinson
DNA barcoding the native flowering plants and conifers of Wales.
PLoS ONE
title DNA barcoding the native flowering plants and conifers of Wales.
title_full DNA barcoding the native flowering plants and conifers of Wales.
title_fullStr DNA barcoding the native flowering plants and conifers of Wales.
title_full_unstemmed DNA barcoding the native flowering plants and conifers of Wales.
title_short DNA barcoding the native flowering plants and conifers of Wales.
title_sort dna barcoding the native flowering plants and conifers of wales
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22701588/pdf/?tool=EBI
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