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

AbstractSedimentary 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 (~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 ~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 (~112 and ~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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Evaluating and Improving SSU rRNA PCR Primer Coverage via Metagenomes from Global Ocean Surveys

10.1101/2020.11.09.375543 ◽

2020 ◽

Author(s):

Jesse McNichol ◽

Paul M. Berube ◽

Steven J. Biller ◽

Jed A. Fuhrman

Keyword(s):

Rational Design ◽

Pcr Primers ◽

Global Ocean ◽

Metagenomic Data ◽

Marker Genes ◽

Ssu Rrna ◽

Shotgun Metagenomics ◽

Field Samples ◽

Globally Distributed ◽

Pcr Primer

AbstractSmall subunit ribosomal RNA (SSU rRNA) amplicon sequencing comprehensively profiles microbiomes, but results will only be accurate if PCR primers perfectly match environmental sequences. To evaluate whether primers commonly used in microbial oceanography match naturally-occurring organisms, we compared primers with > 300 million rRNA sequences retrieved from globally-distributed metagenomes. The best-performing 16S primers were 515Y/926R and 515Y/806RB which perfectly matched most sequences (~0.95). Considering Cyanobacteria/Chloroplast 16S, 515Y/926R had the highest coverage (0.99), making it ideal for quantifying phytoplankton. For 18S sequences, 515Y/926R performed best (0.88), followed by V4R/V4RB (18S-specific; 0.82). Using Atlantic and Pacific BioGEOTRACES field samples, we demonstrate high correspondence between 515Y/926R amplicons (generated as part of this study) and metagenomic 16S rRNA (median R2=0.98, n=272), indicating amplicons can produce equally accurate community composition data versus shotgun metagenomics. Since our pipeline identifies missed taxa, we suggest modifications to improve coverage of biogeochemically-important oceanic microorganisms - a strategy applicable to any environment with metagenomic data.Significance StatementQuantification of taxonomically-informative marker genes using PCR amplification and high-throughput sequencing is a low-cost technique for monitoring distributions and changes of microbial communities across space and time. In order to maximize this procedure’s effectiveness, it is essential that environmental organisms match PCR primer sequences exactly. In this study, we developed a software pipeline to evaluate how well commonly-used primers match primer-binding regions from globally-distributed short-read oceanic metagenomes. Our results demonstrate common primer sets vary widely in performance, and that including additional degenerate bases is a simple strategy to maximize environmental coverage. Written in the reproducible snakemake workflow language and publicly accessible, our pipeline provides a general-purpose tool to guide rational design of PCR primers for any environment with metagenomic data.

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SANTA BARBARA BASIN, CALIFORNIA FLOOD LAYER PROVENANCE: MAPPING FLOODING HAZARD BY SEDIMENT SOURCE REGION

10.1130/abs/2016am-285044 ◽

2016 ◽

Author(s):

Tiffany J. Napier ◽

◽

Ingrid Hendy ◽

Julia G. Bryce

Keyword(s):

Source Region ◽

Sediment Source ◽

Santa Barbara ◽

Santa Barbara Basin ◽

Flooding Hazard

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Systematic benchmark of ancient DNA read mapping

Briefings in Bioinformatics ◽

10.1093/bib/bbab076 ◽

2021 ◽

Author(s):

Adrien Oliva ◽

Raymond Tobler ◽

Alan Cooper ◽

Bastien Llamas ◽

Yassine Souilmi

Keyword(s):

Ancient Dna ◽

Dna Sequences ◽

Population Genetic ◽

Reference Genome ◽

Population Data ◽

Human Populations ◽

Current Standard ◽

Read Mapping ◽

Reference Bias ◽

The Impact

Abstract The current standard practice for assembling individual genomes involves mapping millions of short DNA sequences (also known as DNA ‘reads’) against a pre-constructed reference genome. Mapping vast amounts of short reads in a timely manner is a computationally challenging task that inevitably produces artefacts, including biases against alleles not found in the reference genome. This reference bias and other mapping artefacts are expected to be exacerbated in ancient DNA (aDNA) studies, which rely on the analysis of low quantities of damaged and very short DNA fragments (~30–80 bp). Nevertheless, the current gold-standard mapping strategies for aDNA studies have effectively remained unchanged for nearly a decade, during which time new software has emerged. In this study, we used simulated aDNA reads from three different human populations to benchmark the performance of 30 distinct mapping strategies implemented across four different read mapping software—BWA-aln, BWA-mem, NovoAlign and Bowtie2—and quantified the impact of reference bias in downstream population genetic analyses. We show that specific NovoAlign, BWA-aln and BWA-mem parameterizations achieve high mapping precision with low levels of reference bias, particularly after filtering out reads with low mapping qualities. However, unbiased NovoAlign results required the use of an IUPAC reference genome. While relevant only to aDNA projects where reference population data are available, the benefit of using an IUPAC reference demonstrates the value of incorporating population genetic information into the aDNA mapping process, echoing recent results based on graph genome representations.

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Development of a time-series shotgun metagenomics database for monitoring microbial communities at the Pacific coast of Japan

Scientific Reports ◽

10.1038/s41598-021-91615-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Kazutoshi Yoshitake ◽

Gaku Kimura ◽

Tomoko Sakami ◽

Tsuyoshi Watanabe ◽

Yukiko Taniuchi ◽

...

Keyword(s):

Time Series ◽

Microbial Communities ◽

Pacific Coast ◽

Three Dimensional ◽

Amplicon Sequencing ◽

Metagenomic Data ◽

Shotgun Metagenomics ◽

Functional Features ◽

Pacific Coast Of Japan ◽

Marine Microbial Communities

AbstractAlthough numerous metagenome, amplicon sequencing-based studies have been conducted to date to characterize marine microbial communities, relatively few have employed full metagenome shotgun sequencing to obtain a broader picture of the functional features of these marine microbial communities. Moreover, most of these studies only performed sporadic sampling, which is insufficient to understand an ecosystem comprehensively. In this study, we regularly conducted seawater sampling along the northeastern Pacific coast of Japan between March 2012 and May 2016. We collected 213 seawater samples and prepared size-based fractions to generate 454 subsets of samples for shotgun metagenome sequencing and analysis. We also determined the sequences of 16S rRNA (n = 111) and 18S rRNA (n = 47) gene amplicons from smaller sample subsets. We thereafter developed the Ocean Monitoring Database for time-series metagenomic data (http://marine-meta.healthscience.sci.waseda.ac.jp/omd/), which provides a three-dimensional bird’s-eye view of the data. This database includes results of digital DNA chip analysis, a novel method for estimating ocean characteristics such as water temperature from metagenomic data. Furthermore, we developed a novel classification method that includes more information about viruses than that acquired using BLAST. We further report the discovery of a large number of previously overlooked (TAG)n repeat sequences in the genomes of marine microbes. We predict that the availability of this time-series database will lead to major discoveries in marine microbiome research.

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