3.8 Article

Paleo-diatom composition from Santa Barbara Basin deep-sea sediments: a comparison of 18S-V9 and diat-rbcL metabarcoding vs shotgun metagenomics

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ISME COMMUNICATIONS
卷 1, 期 1, 页码 -

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DOI: 10.1038/s43705-021-00070-8

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  1. PSU Faculty Development Grant [NSF-OCE1851412, NSF-OCE 1851537, 1737364]

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This study compared the application of metabarcoding and metagenomic shotgun approaches in reconstructing marine ecosystems, revealing significant differences in eukaryote and diatom compositions between the two methods, with overamplification of short reads in metabarcoding data. Diatom composition was also influenced by reference bias and showed increased representation in metabarcoding data.
Sedimentary ancient DNA (sedaDNA) analyses are increasingly used to reconstruct marine ecosystems. The majority of marine sedaDNA studies use a metabarcoding approach (extraction and analysis of specific DNA fragments of a defined length), targeting short taxonomic marker genes. Promising examples are 18S-V9 rRNA (similar to 121-130 base pairs, bp) and diat-rbcL (76 bp), targeting eukaryotes and diatoms, respectively. However, it remains unknown how 18S-V9 and diat-rbcL derived compositional profiles compare to metagenomic shotgun data, the preferred method for ancient DNA analyses as amplification biases are minimised. We extracted DNA from five Santa Barbara Basin sediment samples (up to similar to 11 000 years old) and applied both a metabarcoding (18S-V9 rRNA, diat-rbcL) and a metagenomic shotgun approach to (i) compare eukaryote, especially diatom, composition, and (ii) assess sequence length and database related biases. Eukaryote composition differed considerably between shotgun and metabarcoding data, which was related to differences in read lengths (similar to 112 and similar to 161 bp, respectively), and overamplification of short reads in metabarcoding data. Diatom composition was influenced by reference bias that was exacerbated in metabarcoding data and characterised by increased representation of Chaetoceros, Thalassiosira and Pseudo-nitzschia. Our results are relevant to sedaDNA studies aiming to accurately characterise paleo-ecosystems from either metabarcoding or metagenomic data.

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