scholarly journals High throughput shotgun sequencing of eRNA reveals taxonomic and derived functional shifts across a benthic productivity gradient

2020 ◽  
Author(s):  
Elias Broman ◽  
Stefano Bonaglia ◽  
Alf Norkko ◽  
Simon Creer ◽  
Francisco J.A. Nascimento
Keyword(s):  
High Throughput ◽  
Shotgun Sequencing ◽  
Productivity Gradient ◽  
Benthic Productivity

scholarly journals Metagenomic analysis and functional characterization of the biogas microbiome using high throughput shotgun sequencing and a novel binning strategy

2016 ◽  
Vol 9 (1) ◽  
Author(s):  
Stefano Campanaro ◽  
Laura Treu ◽  
Panagiotis G. Kougias ◽  
Davide De Francisci ◽  
Giorgio Valle ◽  
...  
Keyword(s):  
High Throughput ◽  
Functional Characterization ◽  
Shotgun Sequencing ◽  
Metagenomic Analysis

scholarly journals Shotgun sequencing decades-old lichen specimens to resolve phylogenomic placement of type material

2019 ◽  
Vol 64 (2) ◽  
pp. 237-247 ◽  
Author(s):  
Steven D. Leavitt ◽  
Rachel Keuler ◽  
Clayton C. Newberry ◽  
Roger Rosentreter ◽  
Larry L. St. Clair
Keyword(s):  
High Throughput ◽  
Nuclear Gene ◽  
Genetic Data ◽  
Single Copy ◽  
Fungal Species ◽  
Shotgun Sequencing ◽  
Phylogenetic Position ◽  
Herbarium Specimens ◽  
Type Specimens ◽  
Single Copy Nuclear Gene

AbstractNatural history collections, including name-bearing type specimens, are an important source of genetic information. These data can be critical for appropriate taxonomic revisions in cases where the phylogenetic position of name-bearing type specimens needs to be identified, including morphologically cryptic lichen-forming fungal species. Here, we use high-throughput metagenomic shotgun sequencing to generate genome-scale data from decades-old (i.e., more than 30 years old) isotype specimens representing three vagrant taxa in the lichen-forming fungal genus Rhizoplaca, including one species and two subspecies. We also use data from high-throughput metagenomic shotgun sequencing to infer the phylogenetic position of an enigmatic collection, originally identified as R. haydenii, that failed to yield genetic data via Sanger sequencing. We were able to construct a 1.64 Mb alignment from over 1200 single-copy nuclear gene regions for the Rhizoplaca specimens. Phylogenomic reconstructions recovered an isotype representing Rhizoplaca haydenii subsp. arbuscula within a clade comprising other specimens identified as Rhizoplaca haydenii subsp. arbuscula, while an isotype of R. idahoensis was recovered within a clade with substantial phylogenetic substructure comprising Rhizoplaca haydenii subsp. haydenii and other specimens. Based on these data and morphological differences, Rhizoplaca haydenii subsp. arbuscula is elevated to specific rank as Rhizoplaca arbuscula. For the enigmatic collection, we were able to assemble the nearly complete nrDNA cistron and over 50 Mb of the mitochondrial genome. Using these data, we identified this specimen as a morphologically deviant form representing Xanthoparmelia aff. subcumberlandia. This study highlights the power of high-throughput metagenomic shotgun sequencing in generating larger and more comprehensive genetic data from taxonomically important herbarium specimens.

scholarly journals Binnacle: Using Scaffolds to Improve the Contiguity and Quality of Metagenomic Bins

2021 ◽  
Vol 12 ◽  
Author(s):  
Harihara Subrahmaniam Muralidharan ◽  
Nidhi Shah ◽  
Jacquelyn S. Meisel ◽  
Mihai Pop
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Mobile Elements ◽  
Shotgun Sequencing ◽  
Strain Level ◽  
Level Variation ◽  
Sequencing Data ◽  
Sequencing Errors ◽  
Complete Genomes

High-throughput sequencing has revolutionized the field of microbiology, however, reconstructing complete genomes of organisms from whole metagenomic shotgun sequencing data remains a challenge. Recovered genomes are often highly fragmented, due to uneven abundances of organisms, repeats within and across genomes, sequencing errors, and strain-level variation. To address the fragmented nature of metagenomic assemblies, scientists rely on a process called binning, which clusters together contigs inferred to originate from the same organism. Existing binning algorithms use oligonucleotide frequencies and contig abundance (coverage) within and across samples to group together contigs from the same organism. However, these algorithms often miss short contigs and contigs from regions with unusual coverage or DNA composition characteristics, such as mobile elements. Here, we propose that information from assembly graphs can assist current strategies for metagenomic binning. We use MetaCarvel, a metagenomic scaffolding tool, to construct assembly graphs where contigs are nodes and edges are inferred based on paired-end reads. We developed a tool, Binnacle, that extracts information from the assembly graphs and clusters scaffolds into comprehensive bins. Binnacle also provides wrapper scripts to integrate with existing binning methods. The Binnacle pipeline can be found on GitHub (https://github.com/marbl/binnacle). We show that binning graph-based scaffolds, rather than contigs, improves the contiguity and quality of the resulting bins, and captures a broader set of the genes of the organisms being reconstructed.

scholarly journals Molecular Characterization of Microbiota in Cerebrospinal Fluid From Patients With CSF Shunt Infections Using Whole Genome Amplification Followed by Shotgun Sequencing

2021 ◽  
Vol 11 ◽  
Author(s):  
Paul Hodor ◽  
Christopher E. Pope ◽  
Kathryn B. Whitlock ◽  
Lucas R. Hoffman ◽  
David L. Limbrick ◽  
...  
Keyword(s):  
Cerebrospinal Fluid ◽  
16S Rrna ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Whole Genome Amplification ◽  
Shotgun Sequencing ◽  
Csf Shunt ◽  
Whole Genome ◽  
Shunt Infections

Understanding the etiology of cerebrospinal fluid (CSF) shunt infections and reinfections requires detailed characterization of associated microorganisms. Traditionally, identification of bacteria present in the CSF has relied on culture methods, but recent studies have used high throughput sequencing of 16S rRNA genes. Here we evaluated the method of shotgun DNA sequencing for its potential to provide additional genomic information. CSF samples were collected from 3 patients near the beginning and end of each of 2 infection episodes. Extracted total DNA was sequenced by: (1) whole genome amplification followed by shotgun sequencing (WGA) and (2) high-throughput sequencing of the 16S rRNA V4 region (16S). Taxonomic assignments of sequences from WGA and 16S were compared with one another and with conventional microbiological cultures. While classification of bacteria was consistent among the 3 approaches, WGA provided additional insights into sample microbiological composition, such as showing relative abundances of microbial versus human DNA, identifying samples of questionable quality, and detecting significant viral load in some samples. One sample yielded sufficient non-human reads to allow assembly of a high-quality Staphylococcus epidermidis genome, denoted CLIMB1, which we characterized in terms of its MLST profile, gene complement (including putative antimicrobial resistance genes), and similarity to other annotated S. epidermidis genomes. Our results demonstrate that WGA directly applied to CSF is a valuable tool for the identification and genomic characterization of dominant microorganisms in CSF shunt infections, which can facilitate molecular approaches for the development of better diagnostic and treatment methods.

scholarly journals False positives complicate ancient pathogen identifications using high-throughput shotgun sequencing

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Michael G Campana ◽  
Nelly Robles García ◽  
Frank J Rühli ◽  
Noreen Tuross
Keyword(s):  
High Throughput ◽  
False Positives ◽  
Shotgun Sequencing

scholarly journals Optimal assembly for high throughput shotgun sequencing

2013 ◽  
Vol 14 (S5) ◽  
Author(s):  
Guy Bresler ◽  
Ma'ayan Bresler ◽  
David Tse
Keyword(s):  
High Throughput ◽  
Shotgun Sequencing ◽  
Optimal Assembly

154: Integration of TPSA and High-Throughput Mass Spectrometry Data Improves Prostate Cancer Prediction

2007 ◽  
Vol 177 (4S) ◽  
pp. 52-53
Author(s):  
Stefano Ongarello ◽  
Eberhard Steiner ◽  
Regina Achleitner ◽  
Isabel Feuerstein ◽  
Birgit Stenzel ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Mass Spectrometry ◽  
High Throughput ◽  
Mass Spectrometry Data ◽  
Cancer Prediction
Sign in / Sign up

Export Citation Format

Share Document