Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets

Simple nucleotide matching identification methods are not as accurate as once thought at identifying environmental fungal sequences. This is largely because of incorrect naming and the underrepresentation of various fungal groups in reference datasets. Here, we explore these issues by examining an e...

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Autores principales:	Lauren E. Eldred, R. Greg Thorn, David Roy Smith
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	Basidiomycota metabarcoding misidentification SILVA sequence identification Genetics QH426-470
Acceso en línea:	https://doaj.org/article/002db7b74a6c4e318b298f4ab786579f
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spelling	oai:doaj.org-article:002db7b74a6c4e318b298f4ab786579f2021-12-01T07:49:13ZSimple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets1664-802110.3389/fgene.2021.768473https://doaj.org/article/002db7b74a6c4e318b298f4ab786579f2021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fgene.2021.768473/fullhttps://doaj.org/toc/1664-8021Simple nucleotide matching identification methods are not as accurate as once thought at identifying environmental fungal sequences. This is largely because of incorrect naming and the underrepresentation of various fungal groups in reference datasets. Here, we explore these issues by examining an environmental metabarcoding dataset of partial large subunit rRNA sequences of Basidiomycota and basal fungi. We employed the simple matching method using the QIIME 2 classifier and the RDP Classifier in conjunction with the latest releases of the SILVA (138.1, 2020) and RDP (11, 2014) reference datasets and then compared the results with a manual phylogenetic binning approach. Of the 71 query sequences tested, 21 and 42% were misidentified using QIIME 2 and the RDP Classifier, respectively. Of these simple matching misidentifications, more than half resulted from the underrepresentation of various groups of fungi in the SILVA and RDP reference datasets. More comprehensive reference datasets with fewer misidentified sequences will increase the accuracy of simple matching identifications. However, we argue that the phylogenetic binning approach is a better alternative to simple matching since, in addition to better accuracy, it provides evolutionary information about query sequences.Lauren E. EldredR. Greg ThornDavid Roy SmithFrontiers Media S.A.articleBasidiomycotametabarcodingmisidentificationSILVAsequence identificationGeneticsQH426-470ENFrontiers in Genetics, Vol 12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Basidiomycota metabarcoding misidentification SILVA sequence identification Genetics QH426-470
spellingShingle	Basidiomycota metabarcoding misidentification SILVA sequence identification Genetics QH426-470 Lauren E. Eldred R. Greg Thorn David Roy Smith Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
description	Simple nucleotide matching identification methods are not as accurate as once thought at identifying environmental fungal sequences. This is largely because of incorrect naming and the underrepresentation of various fungal groups in reference datasets. Here, we explore these issues by examining an environmental metabarcoding dataset of partial large subunit rRNA sequences of Basidiomycota and basal fungi. We employed the simple matching method using the QIIME 2 classifier and the RDP Classifier in conjunction with the latest releases of the SILVA (138.1, 2020) and RDP (11, 2014) reference datasets and then compared the results with a manual phylogenetic binning approach. Of the 71 query sequences tested, 21 and 42% were misidentified using QIIME 2 and the RDP Classifier, respectively. Of these simple matching misidentifications, more than half resulted from the underrepresentation of various groups of fungi in the SILVA and RDP reference datasets. More comprehensive reference datasets with fewer misidentified sequences will increase the accuracy of simple matching identifications. However, we argue that the phylogenetic binning approach is a better alternative to simple matching since, in addition to better accuracy, it provides evolutionary information about query sequences.
format	article
author	Lauren E. Eldred R. Greg Thorn David Roy Smith
author_facet	Lauren E. Eldred R. Greg Thorn David Roy Smith
author_sort	Lauren E. Eldred
title	Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
title_short	Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
title_full	Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
title_fullStr	Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
title_full_unstemmed	Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets
title_sort	simple matching using qiime 2 and rdp reveals misidentified sequences and an underrepresentation of fungi in reference datasets
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/002db7b74a6c4e318b298f4ab786579f
work_keys_str_mv	AT laureneeldred simplematchingusingqiime2andrdprevealsmisidentifiedsequencesandanunderrepresentationoffungiinreferencedatasets AT rgregthorn simplematchingusingqiime2andrdprevealsmisidentifiedsequencesandanunderrepresentationoffungiinreferencedatasets AT davidroysmith simplematchingusingqiime2andrdprevealsmisidentifiedsequencesandanunderrepresentationoffungiinreferencedatasets
_version_	1718405393687773184

Simple Matching Using QIIME 2 and RDP Reveals Misidentified Sequences and an Underrepresentation of Fungi in Reference Datasets

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