scholarly journals Taking Advantage of the Genomics Revolution for Monitoring and Conservation of Chondrichthyan Populations

Diversity ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 49 ◽  
Author(s):  
Shaili Johri ◽  
Michael Doane ◽  
Lauren Allen ◽  
Elizabeth Dinsdale
Keyword(s):  
High Throughput Sequencing ◽  
Metagenomic Data ◽  
Vertebrate Species ◽  
Design And Implementation ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Population Structures ◽  
Genomic Studies ◽  
Species Groups ◽  
Data Deficient

Chondrichthyes (sharks, rays, skates and chimaeras) are among the oldest extant predators and are vital to top-down regulation of oceanic ecosystems. They are an ecologically diverse group occupying a wide range of habitats and are thus, exploited by coastal, pelagic and deep-water fishing industries. Chondrichthyes are among the most data deficient vertebrate species groups making design and implementation of regulatory and conservation measures challenging. High-throughput sequencing technologies have significantly propelled ecological investigations and understanding of marine and terrestrial species’ populations, but there remains a paucity of NGS based research on chondrichthyan populations. We present a brief review of current methods to access genomic and metagenomic data from Chondrichthyes and discuss applications of these datasets to increase our understanding of chondrichthyan taxonomy, evolution, ecology and population structures. Last, we consider opportunities and challenges offered by genomic studies for conservation and management of chondrichthyan populations.

scholarly journals Designing Efficient Spaced Seeds for SOLiD Read Mapping

2010 ◽  
Vol 2010 ◽  
pp. 1-12 ◽  
Author(s):  
Laurent Noé ◽  
Marta Gîrdea ◽  
Gregory Kucherov
Keyword(s):  
High Throughput Sequencing ◽  
Color Space ◽  
Major Advance ◽  
Read Mapping ◽  
Sequencing Technologies ◽  
Reading Errors ◽  
Spaced Seeds ◽  
Algorithmic Solution ◽  
Wide Range ◽  
Genomic Studies

The advent of high-throughput sequencing technologies constituted a major advance in genomic studies, offering new prospects in a wide range of applications.We propose a rigorous and flexible algorithmic solution to mapping SOLiD color-space reads to a reference genome. The solution relies on an advanced method of seed design that uses a faithful probabilistic model of read matches and, on the other hand, a novel seeding principle especially adapted to read mapping. Our method can handle both lossy and lossless frameworks and is able to distinguish, at the level of seed design, between SNPs and reading errors. We illustrate our approach by several seed designs and demonstrate their efficiency.

scholarly journals Utilizing the VirIdAl Pipeline to Search for Viruses in the Metagenomic Data of Bat Samples

Viruses ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2006
Author(s):  
Anna Y Budkina ◽  
Elena V Korneenko ◽  
Ivan A Kotov ◽  
Daniil A Kiselev ◽  
Ilya V Artyushin ◽  
...  
Keyword(s):  
Large Scale ◽  
High Throughput Sequencing ◽  
Metagenomic Data ◽  
Sequencing Data ◽  
Viral Pathogens ◽  
Genomic Databases ◽  
Bioinformatic Pipeline ◽  
Viral Genomes ◽  
Sequencing Technologies ◽  
Viral Screening

According to various estimates, only a small percentage of existing viruses have been discovered, naturally much less being represented in the genomic databases. High-throughput sequencing technologies develop rapidly, empowering large-scale screening of various biological samples for the presence of pathogen-associated nucleotide sequences, but many organisms are yet to be attributed specific loci for identification. This problem particularly impedes viral screening, due to vast heterogeneity in viral genomes. In this paper, we present a new bioinformatic pipeline, VirIdAl, for detecting and identifying viral pathogens in sequencing data. We also demonstrate the utility of the new software by applying it to viral screening of the feces of bats collected in the Moscow region, which revealed a significant variety of viruses associated with bats, insects, plants, and protozoa. The presence of alpha and beta coronavirus reads, including the MERS-like bat virus, deserves a special mention, as it once again indicates that bats are indeed reservoirs for many viral pathogens. In addition, it was shown that alignment-based methods were unable to identify the taxon for a large proportion of reads, and we additionally applied other approaches, showing that they can further reveal the presence of viral agents in sequencing data. However, the incompleteness of viral databases remains a significant problem in the studies of viral diversity, and therefore necessitates the use of combined approaches, including those based on machine learning methods.

The chicken model organism for epigenomic research

Genome ◽  
2020 ◽  
Author(s):  
Tasnim H. BEACON ◽  
James R DAVIE
Keyword(s):  
High Throughput Sequencing ◽  
Chicken Genome ◽  
Regulation Of Gene Expression ◽  
Model Organism ◽  
Bioinformatic Tools ◽  
Sequencing Technologies ◽  
Trace Back ◽  
Human Orthologs ◽  
Genomic Studies ◽  
Chicken Model

The chicken model organism has advanced the areas of developmental biology, virology, immunology, oncology, epigenetic regulation of gene expression, conservation biology, and genomics of domestication. Further, the chicken model organism has aided in our understanding of human disease. Through the recent advances in high-throughput sequencing and bioinformatic tools, researchers have successfully identified sequences in the chicken genome that have human orthologs, improving mammalian genome annotation. In this review, we highlight the importance of chicken as an animal model in basic and pre-clinical research. We will present the importance of chicken in poultry epigenetics and in genomic studies that trace back to their ancestor, the last link between human and chicken tree of life. There are still many genes of unknown function in the chicken genome yet to be characterized. By taking advantage of recent sequencing technologies, it is possible to gain further insight into the chicken epigenome.

scholarly journals The ELIXIR Human Copy Number Variations Community: building bioinformatics infrastructure for research

F1000Research ◽  
2020 ◽  
Vol 9 ◽  
pp. 1229
Author(s):  
David Salgado ◽  
Irina M. Armean ◽  
Michael Baudis ◽  
Sergi Beltran ◽  
Salvador Capella-Gutierrez ◽  
...  
Keyword(s):  
Copy Number ◽  
High Throughput Sequencing ◽  
Population Genomics ◽  
Genetic Diseases ◽  
White Paper ◽  
Copy Number Variations ◽  
Direct Result ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Definition Of

Copy number variations (CNVs) are major causative contributors both in the genesis of genetic diseases and human neoplasias. While “High-Throughput” sequencing technologies are increasingly becoming the primary choice for genomic screening analysis, their ability to efficiently detect CNVs is still heterogeneous and remains to be developed. The aim of this white paper is to provide a guiding framework for the future contributions of ELIXIR’s recently established human CNV Community, with implications beyond human disease diagnostics and population genomics. This white paper is the direct result of a strategy meeting that took place in September 2018 in Hinxton (UK) and involved representatives of 11 ELIXIR Nodes. The meeting led to the definition of priority objectives and tasks, to address a wide range of CNV-related challenges ranging from detection and interpretation to sharing and training. Here, we provide suggestions on how to align these tasks within the ELIXIR Platforms strategy, and on how to frame the activities of this new ELIXIR Community in the international context.

scholarly journals Discovering the Unknown: Improving Detection of Novel Species and Genera from Short Reads

2011 ◽  
Vol 2011 ◽  
pp. 1-11 ◽  
Author(s):  
Gail L. Rosen ◽  
Robi Polikar ◽  
Diamantino A. Caseiro ◽  
Steven D. Essinger ◽  
Bahrad A. Sokhansanj
Keyword(s):  
High Throughput Sequencing ◽  
Mine Drainage ◽  
Novel Species ◽  
Classification Performance ◽  
Species Level ◽  
Metagenomic Data ◽  
Sequencing Technologies ◽  
Novel Taxa ◽  
New Algorithms ◽  
Better Than

High-throughput sequencing technologies enable metagenome profiling, simultaneous sequencing of multiple microbial species present within an environmental sample. Since metagenomic data includes sequence fragments (“reads”) from organisms that are absent from any database, new algorithms must be developed for the identification and annotation of novel sequence fragments. Homology-based techniques have been modified to detect novel species and genera, but, composition-based methods, have not been adapted. We develop a detection technique that can discriminate between “known” and “unknown” taxa, which can be used with composition-based methods, as well as a hybrid method. Unlike previous studies, we rigorously evaluate all algorithms for their ability to detect novel taxa. First, we show that the integration of a detector with a composition-based method performs significantly better than homology-based methods for the detection of novel species and genera, with best performance at finer taxonomic resolutions. Most importantly, we evaluate all the algorithms by introducing an “unknown” class and show that the modified version of PhymmBL has similar or better overall classification performance than the other modified algorithms, especially for the species-level and ultrashort reads. Finally, we evaluate theperformance of several algorithms on a real acid mine drainage dataset.

scholarly journals Fast sequence-based microsatellite genotyping development workflow

2019 ◽  
Author(s):  
Olivier Lepais ◽  
Emilie Chancerel ◽  
Christophe Boury ◽  
Franck Salin ◽  
Aurélie Manicki ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Ad Hoc ◽  
De Novo ◽  
Microsatellite Genotyping ◽  
Sequencing Technologies ◽  
Wide Range ◽  
Genetic Diversity And Structure ◽  
Genomic Resource ◽  
Analytical Frameworks ◽  
Different Levels

AbstractApplication of high-throughput sequencing technologies to microsatellite genotyping (SSRseq) has been shown to remove many of the limitations of electrophoresis-based methods and to refine inference of population genetic diversity and structure. We present here a streamlined SSRseq development workflow that includes microsatellite development, multiplexed marker amplification and sequencing, and automated bioinformatics data analysis. We illustrate its application to five groups of species across phyla (fungi, plant, insect and fish) with different levels of genomic resource availability. We found that relying on previously developed microsatellite assay is not optimal and leads to a resulting low number of reliable locus being genotyped. In contrast, de novo ad hoc primer designs gives highly multiplexed microsatellite assays that can be sequenced to produce high quality genotypes for 20 to 40 loci. We highlight critical upfront development factors to consider for effective SSRseq setup in a wide range of situations. Sequence analysis accounting for all linked polymorphisms along the sequence, quickly generates a powerful multi-allelic haplotype-based genotypic dataset, calling to new theoretical and analytical frameworks to extract more information from multi-nucleotide polymorphism marker systems.

scholarly journals Deep embeddings to comprehend and visualize microbiome protein space

2021 ◽  
Author(s):  
Krzysztof Odrzywolek ◽  
Zuzanna Karwowska ◽  
Jan Majta ◽  
Aleksander Byrski ◽  
Kaja Milanowska-Zabel ◽  
...  
Keyword(s):  
High Throughput Sequencing ◽  
Language Model ◽  
Structure And Function ◽  
Metagenomic Data ◽  
Use Case ◽  
Sequencing Technologies ◽  
Alignment Free ◽  
And Function ◽  
Clinical Potential ◽  
Protein Space

Understanding the function of microbial proteins is essential to reveal the clinical potential of the microbiome. The application of high-throughput sequencing technologies allows for fast and increasingly cheaper acquisition of data from microbial communities. However, many of the inferred protein sequences are novel and not catalogued, hence the possibility of predicting their function through conventional homology-based approaches is limited. Here, we leverage a deep-learning-based representation of proteins to assess its utility in alignment-free analysis of microbial proteins. We trained a language model on the Unified Human Gastrointestinal Protein catalogue and validated the resulting protein representation on the bacterial part of the SwissProt database. Finally, we present a use case on proteins involved in SCFA metabolism. Results indicate that our model (ArdiMiPE) manages to accurately represent features related to protein structure and function, allowing for alignment-free protein analyses. Technologies such as ArdiMiPE that contextualize metagenomic data are a promising direction to deeply understand the microbiome.

scholarly journals Asymmetric Inheritance of Cell Fate Determinants: Focus on RNA

2019 ◽  
Vol 5 (2) ◽  
pp. 38 ◽  
Author(s):  
Yelyzaveta Shlyakhtina ◽  
Katherine L. Moran ◽  
Maximiliano M. Portal
Keyword(s):  
Cell Fate ◽  
Mammalian Cells ◽  
High Throughput Sequencing ◽  
General Pattern ◽  
Nuclear Architecture ◽  
Biological Information ◽  
Current Evidence ◽  
Rna Molecules ◽  
Sequencing Technologies ◽  
Wide Range

During the last decade, and mainly primed by major developments in high-throughput sequencing technologies, the catalogue of RNA molecules harbouring regulatory functions has increased at a steady pace. Current evidence indicates that hundreds of mammalian RNAs have regulatory roles at several levels, including transcription, translation/post-translation, chromatin structure, and nuclear architecture, thus suggesting that RNA molecules are indeed mighty controllers in the flow of biological information. Therefore, it is logical to suggest that there must exist a series of molecular systems that safeguard the faithful inheritance of RNA content throughout cell division and that those mechanisms must be tightly controlled to ensure the successful segregation of key molecules to the progeny. Interestingly, whilst a handful of integral components of mammalian cells seem to follow a general pattern of asymmetric inheritance throughout division, the fate of RNA molecules largely remains a mystery. Herein, we will discuss current concepts of asymmetric inheritance in a wide range of systems, including prions, proteins, and finally RNA molecules, to assess overall the biological impact of RNA inheritance in cellular plasticity and evolutionary fitness.

scholarly journals Metagenomic Approaches to Analyze Antimicrobial Resistance: An Overview

2021 ◽  
Vol 11 ◽  
Author(s):  
Vinicius A. C. de Abreu ◽  
José Perdigão ◽  
Sintia Almeida
Keyword(s):  
Antimicrobial Resistance ◽  
High Throughput Sequencing ◽  
Genetic Recombination ◽  
Public Health Problem ◽  
Metagenomic Data ◽  
Global Public Health ◽  
Community Based ◽  
Sequencing Technologies ◽  
Antimicrobial Resistance Genes ◽  
Functional Gene Analysis

Antimicrobial resistance is a major global public health problem, which develops when pathogens acquire antimicrobial resistance genes (ARGs), primarily through genetic recombination between commensal and pathogenic microbes. The resistome is a collection of all ARGs. In microorganisms, the primary method of ARG acquisition is horizontal gene transfer (HGT). Thus, understanding and identifying HGTs, can provide insight into the mechanisms of antimicrobial resistance transmission and dissemination. The use of high-throughput sequencing technologies has made the analysis of ARG sequences feasible and accessible. In particular, the metagenomic approach has facilitated the identification of community-based antimicrobial resistance. This approach is useful, as it allows access to the genomic data in an environmental sample without the need to isolate and culture microorganisms prior to analysis. Here, we aimed to reflect on the challenges of analyzing metagenomic data in the three main approaches for studying antimicrobial resistance: (i) analysis of microbial diversity, (ii) functional gene analysis, and (iii) searching the most complete and pertinent resistome databases.

Integrating independent microbial studies to build predictive models of anaerobic digestion inhibition by ammonia and phenol

2020 ◽  
Author(s):  
Simon Poirier ◽  
Sébastien Déjean ◽  
Cédric Midoux ◽  
Kim-Anh Lê Cao ◽  
Olivier Chapleur
Keyword(s):  
Anaerobic Digestion ◽  
High Throughput Sequencing ◽  
Economic Losses ◽  
List Type ◽  
Community Patterns ◽  
Microbial Indicators ◽  
Sequencing Technologies ◽  
External Data ◽  
Wide Range ◽  
Process Failure

AbstractAnaerobic digestion (AD) is a microbial process that can efficiently degrade organic waste into renewable energies such as methane-rich biogas. However, the underpinning microbial mechanisms are highly vulnerable to a wide range of inhibitory compounds, leading to process failure and economic losses. High-throughput sequencing technologies enable the identification of microbial indicators of digesters inhibition and can provide new insights into the key phylotypes at stake during AD process. But yet, current studies have used different inocula, substrates, geographical sites and types of reactors, resulting in indicators that are not robust or reproducible across independent studies. In addition, such studies focus on the identification of a single microbial indicator that is not reflective of the complexity of AD. Our study proposes the first analysis of its kind that seeks for a robust signature of microbial indicators of phenol and ammonia inhibitions, whilst leveraging on 4 independent in-house and external AD microbial studies. We applied a recent multivariate integrative method on two-in-house studies to identify such signature, then predicted the inhibitory status of samples from two datasets with more than 90% accuracy. Our study demonstrates how we can efficiently analyze existing studies to extract robust microbial community patterns, predict AD inhibition, and deepen our understanding of AD towards better AD microbial management.HighlightsRobust biomarkers of AD inhibition were tagged by integrating independent 16S studiesIncrease of the Clostridiales relative abundance is an early warning of AD inhibitionCloacimonetes is associated with good performance of biomethane productionMultivariate model predicts ammonia inhibition with 90% accuracy in external data

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