scholarly journals Advances in Metagenomics and Its Application in Environmental Microorganisms

2021 ◽  
Vol 12 ◽  
Author(s):  
Lu Zhang ◽  
FengXin Chen ◽  
Zhan Zeng ◽  
Mengjiao Xu ◽  
Fangfang Sun ◽  
...  
Keyword(s):  
Gene Prediction ◽  
Sequencing Analysis ◽  
Bioactive Substances ◽  
New Approach ◽  
Functional Activities ◽  
Taxonomic Profiling ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing

Metagenomics is a new approach to study microorganisms obtained from a specific environment by functional gene screening or sequencing analysis. Metagenomics studies focus on microbial diversity, community constitute, genetic and evolutionary relationships, functional activities, and interactions and relationships with the environment. Sequencing technologies have evolved from shotgun sequencing to high-throughput, next-generation sequencing (NGS), and third-generation sequencing (TGS). NGS and TGS have shown the advantage of rapid detection of pathogenic microorganisms. With the help of new algorithms, we can better perform the taxonomic profiling and gene prediction of microbial species. Functional metagenomics is helpful to screen new bioactive substances and new functional genes from microorganisms and microbial metabolites. In this article, basic steps, classification, and applications of metagenomics are reviewed.

scholarly journals Novel NGS Pipeline for Virus Discovery from a Wide Spectrum of Hosts and Sample Types

2020 ◽  
Author(s):  
Ilya Plyusnin ◽  
Ravi Kant ◽  
Anne J. Jääskeläinen ◽  
Tarja Sironen ◽  
Liisa Holm ◽  
...  
Keyword(s):  
Wide Spectrum ◽  
Domestic Animals ◽  
Metagenomic Data ◽  
Virus Discovery ◽  
Taxonomic Profiling ◽  
Sequencing Technologies ◽  
Living Organisms ◽  
Next Generation Sequencing Ngs ◽  
Microbiome Data ◽  
Generation Sequencing

ABSTRACTThe study of the microbiome data holds great potential for elucidating the biological and metabolic functioning of living organisms and their role in the environment. Metagenomic analyses have shown that humans, along with e.g. domestic animals, wildlife and arthropods, are colonized by an immense community of viruses. The current Coronavirus pandemic (COVID-19) heightens the need to rapidly detect previously unknown viruses in an unbiased way. The increasing availability of metagenomic data in this era of next-generation sequencing (NGS), along with increasingly affordable sequencing technologies, highlight the need for reliable and comprehensive methods to manage such data. In this article, we present a novel stand-alone pipeline called LAZYPIPE for identifying both previously known and novel viruses in host-associated or environmental samples and give examples of virus discovery based on it. LAZYPIPE is a Unix-based pipeline for automated assembling and taxonomic profiling of NGS libraries implemented as a collection of C++, Perl, and R scripts.

scholarly journals Novel NGS pipeline for virus discovery from a wide spectrum of hosts and sample types

2020 ◽  
Vol 6 (2) ◽  
Author(s):  
Ilya Plyusnin ◽  
Ravi Kant ◽  
Anne J Jääskeläinen ◽  
Tarja Sironen ◽  
Liisa Holm ◽  
...  
Keyword(s):  
Wide Spectrum ◽  
Metagenomic Data ◽  
Virus Discovery ◽  
Bioinformatics Pipeline ◽  
Taxonomic Profiling ◽  
Sequencing Technologies ◽  
Living Organisms ◽  
Next Generation Sequencing Ngs ◽  
Microbiome Data ◽  
Generation Sequencing

Abstract The study of the microbiome data holds great potential for elucidating the biological and metabolic functioning of living organisms and their role in the environment. Metagenomic analyses have shown that humans, along with for example, domestic animals, wildlife and arthropods, are colonized by an immense community of viruses. The current Coronavirus pandemic (COVID-19) heightens the need to rapidly detect previously unknown viruses in an unbiased way. The increasing availability of metagenomic data in this era of next-generation sequencing (NGS), along with increasingly affordable sequencing technologies, highlight the need for reliable and comprehensive methods to manage such data. In this article, we present a novel bioinformatics pipeline called LAZYPIPE for identifying both previously known and novel viruses in host associated or environmental samples and give examples of virus discovery based on it. LAZYPIPE is a Unix-based pipeline for automated assembling and taxonomic profiling of NGS libraries implemented as a collection of C++, Perl, and R scripts.

scholarly journals Apollo: a sequencing-technology-independent, scalable and accurate assembly polishing algorithm

2020 ◽  
Vol 36 (12) ◽  
pp. 3669-3679 ◽  
Author(s):  
Can Firtina ◽  
Jeremie S Kim ◽  
Mohammed Alser ◽  
Damla Senol Cali ◽  
A Ercument Cicek ◽  
...  
Keyword(s):  
Genome Analysis ◽  
Supplementary Information ◽  
Third Generation ◽  
Sequencing Technology ◽  
Base Pairs ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Long Reads ◽  
Generation Sequencing ◽  
Large Genomes

Abstract Motivation Third-generation sequencing technologies can sequence long reads that contain as many as 2 million base pairs. These long reads are used to construct an assembly (i.e. the subject’s genome), which is further used in downstream genome analysis. Unfortunately, third-generation sequencing technologies have high sequencing error rates and a large proportion of base pairs in these long reads is incorrectly identified. These errors propagate to the assembly and affect the accuracy of genome analysis. Assembly polishing algorithms minimize such error propagation by polishing or fixing errors in the assembly by using information from alignments between reads and the assembly (i.e. read-to-assembly alignment information). However, current assembly polishing algorithms can only polish an assembly using reads from either a certain sequencing technology or a small assembly. Such technology-dependency and assembly-size dependency require researchers to (i) run multiple polishing algorithms and (ii) use small chunks of a large genome to use all available readsets and polish large genomes, respectively. Results We introduce Apollo, a universal assembly polishing algorithm that scales well to polish an assembly of any size (i.e. both large and small genomes) using reads from all sequencing technologies (i.e. second- and third-generation). Our goal is to provide a single algorithm that uses read sets from all available sequencing technologies to improve the accuracy of assembly polishing and that can polish large genomes. Apollo (i) models an assembly as a profile hidden Markov model (pHMM), (ii) uses read-to-assembly alignment to train the pHMM with the Forward–Backward algorithm and (iii) decodes the trained model with the Viterbi algorithm to produce a polished assembly. Our experiments with real readsets demonstrate that Apollo is the only algorithm that (i) uses reads from any sequencing technology within a single run and (ii) scales well to polish large assemblies without splitting the assembly into multiple parts. Availability and implementation Source code is available at https://github.com/CMU-SAFARI/Apollo. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Diagnosis of Severe Tetanus Assisted by Next-Generation Sequencing Analysis of Etiology: A Case Report

2020 ◽  
Author(s):  
Yuling An ◽  
Mingming Fan ◽  
Ziyu Li ◽  
You Peng ◽  
Xiaomeng Yi ◽  
...  
Keyword(s):  
Next Generation Sequencing ◽  
Comprehensive Treatment ◽  
Sequencing Analysis ◽  
Next Generation ◽  
Next Generation Sequencing Analysis ◽  
Autonomic Instability ◽  
The Right ◽  
Next Generation Sequencing Ngs ◽  
Generation Sequencing ◽  
Severe Tetanus

Abstract We shared our successful treatment experience of a severe tetanus patient in China. A 50 year old male patient was admitted to our hospital 10 days after the right arm injury due to pain and masticatory weakness. The pathogen of wound secretion was confirmed to be clostridium tetanus by next-generation sequencing (NGS).The patient's condition rapidly progressed to a severe state with autonomic instability. After debridement and comprehensive treatment in ICU, including deep analgesia and sedation with dexmedetomidine, ventilator support and anti-infection treatment, the patient finally recovered and discharged. This case suggested that early diagnosis and reasonable intervention of severe tetanus could reduce mortality.

scholarly journals ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Michael T. Wolfinger ◽  
Jörg Fallmann ◽  
Florian Eggenhofer ◽  
Fabian Amman
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Motif ◽  
Software Components ◽  
Sequencing Analysis ◽  
Next Generation ◽  
File Formats ◽  
Next Generation Sequencing Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

scholarly journals Telomere Length De Novo Assembly of all 7 Chromosomes and Mitogenome Sequencing of the Model Entomopathogenic Fungus, Metarhizium Brunneum, by Means of a Novel Assembly Pipeline

2020 ◽  
Author(s):  
Zack Saud ◽  
Alexandra M. Kortsinoglou ◽  
Vassili N. Kouvelis ◽  
Tariq M. Butt
Keyword(s):  
Entomopathogenic Fungus ◽  
De Novo ◽  
Gene Prediction ◽  
Fungal Species ◽  
Orthologous Protein ◽  
Metarhizium Brunneum ◽  
Sequencing Technologies ◽  
Protein Clusters ◽  
Assembly Pipeline ◽  
Generation Sequencing

Abstract More accurate and complete reference genomes have improved understanding of gene function, biology, and evolutionary mechanisms. Hybrid genome assembly approaches leverage benefits of both long, relatively error-prone reads from third-generation sequencing technologies and short, accurate reads from second-generation sequencing technologies, to produce more accurate and contiguous de novo genome assemblies in comparison to using either technology independently. In this study, we present a novel hybrid assembly pipeline that allowed for both mitogenome de novo assembly and telomere length de novo assembly of all 7 chromosomes of the model entomopathogenic fungus, Metarhizium brunneum. The improved assembly allowed for better ab initio gene prediction and a more BUSCO complete proteome set has been generated in comparison to the eight current NCBI reference Metarhizium spp. genomes. Remarkably, we note that including the mitogenome in ab initio gene prediction training improved overall gene prediction. The assembly was further validated by comparing contig assembly agreement across various assemblers, assessing the assembly performance of each tool. Genomic synteny and orthologous protein clusters were compared between Metarhizium brunneum and three other Hypocreales species with complete genomes, identifying core proteins, and listing orthologous protein clusters shared uniquely between the two entomopathogenic fungal species, so as to further facilitate the understanding of molecular mechanisms underpinning fungal-insect pathogenesis. The novel assembly pipeline may be used for other haploid fungal species, facilitating the need to produce high-quality reference fungal genomes, leading to better understanding of fungal genomic evolution, chromosome structuring and gene regulation.

scholarly journals ViennaNGS: A toolbox for building efficient next- generation sequencing analysis pipelines

F1000Research ◽  
2015 ◽  
Vol 4 ◽  
pp. 50 ◽  
Author(s):  
Michael T. Wolfinger ◽  
Jörg Fallmann ◽  
Florian Eggenhofer ◽  
Fabian Amman
Keyword(s):  
Next Generation Sequencing ◽  
Sequence Motif ◽  
Software Components ◽  
Sequencing Analysis ◽  
Next Generation ◽  
File Formats ◽  
Next Generation Sequencing Analysis ◽  
Next Generation Sequencing Ngs ◽  
Ngs Data ◽  
Generation Sequencing

Recent achievements in next-generation sequencing (NGS) technologies lead to a high demand for reuseable software components to easily compile customized analysis workflows for big genomics data. We present ViennaNGS, an integrated collection of Perl modules focused on building efficient pipelines for NGS data processing. It comes with functionality for extracting and converting features from common NGS file formats, computation and evaluation of read mapping statistics, as well as normalization of RNA abundance. Moreover, ViennaNGS provides software components for identification and characterization of splice junctions from RNA-seq data, parsing and condensing sequence motif data, automated construction of Assembly and Track Hubs for the UCSC genome browser, as well as wrapper routines for a set of commonly used NGS command line tools.

scholarly journals RNA Transcriptome Mapping with GraphMap

2017 ◽  
Author(s):  
Krešimir Križanović ◽  
Ivan Sović ◽  
Ivan Krpelnik ◽  
Mile Šikić
Keyword(s):  
Third Generation ◽  
Sequencing Data ◽  
Mapping Algorithm ◽  
Gene Annotations ◽  
Sequencing Technologies ◽  
Third Generation Sequencing ◽  
Oxford Nanopore ◽  
Rna Mapping ◽  
Synthetic Datasets ◽  
Generation Sequencing

AbstractNext generation sequencing technologies have made RNA sequencing widely accessible and applicable in many areas of research. In recent years, 3rd generation sequencing technologies have matured and are slowly replacing NGS for DNA sequencing. This paper presents a novel tool for RNA mapping guided by gene annotations. The tool is an adapted version of a previously developed DNA mapper – GraphMap, tailored for third generation sequencing data, such as those produced by Pacific Biosciences or Oxford Nanopore Technologies devices. It uses gene annotations to generate a transcriptome, uses a DNA mapping algorithm to map reads to the transcriptome, and finally transforms the mappings back to genome coordinates. Modified version of GraphMap is compared on several synthetic datasets to the state-of-the-art RNAseq mappers enabled to work with third generation sequencing data. The results show that our tool outperforms other tools in general mapping quality.

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