scholarly journals Nanopore sequencing in non-human forensic genetics

2021 ◽  
Author(s):  
Rob Ogden ◽  
Nina Vasiljevic ◽  
Stefan Prost
Keyword(s):  
Massively Parallel Sequencing ◽  
Forensic Genetics ◽  
Consensus Sequence ◽  
Rapid Expansion ◽  
Nanopore Sequencing ◽  
Wildlife Forensics ◽  
Forensic Casework ◽  
Sequencing Technologies ◽  
Sequence Production ◽  
Sequencing Platforms

The past decade has seen a rapid expansion of non-human forensic genetics coinciding with the development of 2nd and 3rd generation DNA sequencing technologies. Nanopore sequencing is one such technology that offers massively parallel sequencing at a fraction of the capital cost of other sequencing platforms. The application of nanopore sequencing to species identification has already been widely demonstrated in biomonitoring studies and has significant potential for non-human forensic casework, particularly in the area of wildlife forensics. This review examines nanopore sequencing technology and assesses its potential applications, advantages and drawbacks for use in non-human forensics, alongside other next-generation sequencing platforms and as a possible replacement to Sanger sequencing. We assess the specific challenges of sequence error rate and the standardisation of consensus sequence production, before discussing recent progress in the validation of nanopore sequencing for use in forensic casework. We conclude that nanopore sequencing may be able to play a considerable role in the future of non-human forensic genetics, especially for applications to wildlife law enforcement within emerging forensic laboratories.

Molecular Genetics of Early- and Late-Onset Alzheimer’s Disease

2020 ◽  
Vol 20 ◽  
Author(s):  
Md. Sahab Uddin ◽  
Sharifa Hasana ◽  
Md. Farhad Hossain ◽  
Md. Siddiqul Islam ◽  
Tapan Behl ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Massively Parallel Sequencing ◽  
Late Onset ◽  
Current Knowledge ◽  
The Elderly ◽  
Apoe Ε4 ◽  
Sequencing Technologies ◽  
Genetic Components ◽  
Ε4 Allele

: Alzheimer’s disease (AD) is the most common form of dementia in the elderly and this complex disorder is associated with environmental as well as genetic components. Early-onset AD (EOAD) and late-onset AD (LOAD, more common) are major identified types of AD. The genetics of EOAD is extensively understood with three genes variants such as APP, PSEN1, and PSEN2 leading to disease. On the other hand, some common alleles including APOE are effectively associated with LOAD identified but the genetics of LOAD is not clear to date. It has been accounted that about 5% to 10% of EOAD patients can be explained through mutations in the three familiar genes of EOAD. The APOE ε4 allele augmented the severity of EOAD risk in carriers, and APOE ε4 allele was considered as a hallmark of EOAD. A great number of EOAD patients, who are not genetically explained, indicate that it is not possible to identify disease- triggering genes yet. Although several genes have been identified through using the technology of next-generation sequencing in EOAD families including SORL1, TYROBP, and NOTCH3. A number of TYROBP variants were identified through exome sequencing in EOAD patients and these TYROBP variants may increase the pathogenesis of EOAD. The existence of ε4 allele is responsible for increasing the severity of EOAD. However, several ε4 allele carriers live into their 90s that propose the presence of other LOAD genetic as well as environmental risk factors that are not identified yet. It is urgent to find out missing genetics of EOAD and LOAD etiology to discover new potential genetics facets which will assist to understand the pathological mechanism of AD. These investigations should contribute to developing a new therapeutic candidate for alleviating, reversing and preventing AD. This article based on current knowledge represents the overview of the susceptible genes of EOAD, and LOAD. Next, we represent the probable molecular mechanism which might elucidate the genetic etiology of AD and highlight the role of massively parallel sequencing technologies for novel gene discoveries.

scholarly journals Sequoia: an interactive visual analytics platform for interpretation and feature extraction from nanopore sequencing datasets

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ratanond Koonchanok ◽  
Swapna Vidhur Daulatabad ◽  
Quoseena Mir ◽  
Khairi Reda ◽  
Sarath Chandra Janga
Keyword(s):  
Single Molecule ◽  
Visual Analytics ◽  
Visual Analysis ◽  
Direct Sequencing ◽  
Visual Exploration ◽  
Nanopore Sequencing ◽  
Sequencing Data ◽  
Rna Sequences ◽  
Sequencing Technologies ◽  
Signal Features

Abstract Background Direct-sequencing technologies, such as Oxford Nanopore’s, are delivering long RNA reads with great efficacy and convenience. These technologies afford an ability to detect post-transcriptional modifications at a single-molecule resolution, promising new insights into the functional roles of RNA. However, realizing this potential requires new tools to analyze and explore this type of data. Result Here, we present Sequoia, a visual analytics tool that allows users to interactively explore nanopore sequences. Sequoia combines a Python-based backend with a multi-view visualization interface, enabling users to import raw nanopore sequencing data in a Fast5 format, cluster sequences based on electric-current similarities, and drill-down onto signals to identify properties of interest. We demonstrate the application of Sequoia by generating and analyzing ~ 500k reads from direct RNA sequencing data of human HeLa cell line. We focus on comparing signal features from m6A and m5C RNA modifications as the first step towards building automated classifiers. We show how, through iterative visual exploration and tuning of dimensionality reduction parameters, we can separate modified RNA sequences from their unmodified counterparts. We also document new, qualitative signal signatures that characterize these modifications from otherwise normal RNA bases, which we were able to discover from the visualization. Conclusions Sequoia’s interactive features complement existing computational approaches in nanopore-based RNA workflows. The insights gleaned through visual analysis should help users in developing rationales, hypotheses, and insights into the dynamic nature of RNA. Sequoia is available at https://github.com/dnonatar/Sequoia.

scholarly journals Assessing genotyping errors in mammalian museum study skins using high-throughput genotyping-by-sequencing

2021 ◽  
Author(s):  
Stella C. Yuan ◽  
Eric Malekos ◽  
Melissa T. R. Hawkins
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Massively Parallel Sequencing ◽  
Massively Parallel ◽  
Museum Specimens ◽  
Museum Specimen ◽  
Genotyping Errors ◽  
Allelic Dropout ◽  
Parallel Sequencing ◽  
Sequencing Technologies

AbstractThe use of museum specimens held in natural history repositories for population and conservation genetic research is increasing in tandem with the use of massively parallel sequencing technologies. Short Tandem Repeats (STRs), or microsatellite loci, are commonly used genetic markers in wildlife and population genetic studies. However, they traditionally suffered from a host of issues including length homoplasy, high costs, low throughput, and difficulties in reproducibility across laboratories. Massively parallel sequencing technologies can address these problems, but the incorporation of museum specimen derived DNA suffers from significant fragmentation and exogenous DNA contamination. Combatting these issues requires extra measures of stringency in the lab and during data analysis, yet there have not been any high-throughput sequencing studies evaluating microsatellite allelic dropout from museum specimen extracted DNA. In this study, we evaluate genotyping errors derived from mammalian museum skin DNA extracts for previously characterized microsatellites across PCR replicates utilizing high-throughput sequencing. We found it useful to classify samples based on DNA concentration, which determined the rate by which genotypes were accurately recovered. Longer microsatellites performed worse in all museum specimens. Allelic dropout rates across loci were dependent on sample quantity, with high concentration museum specimens performing as well and recovering quality metrics nearly as high as the frozen tissue sample. Based on our results, we provide a set of best practices for quality assurance and incorporation of reliable genotypes from museum specimens.

scholarly journals Sequencing and Computational Approaches to Identification and Characterization of Microbial Organisms

2013 ◽  
Vol 5 ◽  
pp. BECB.S10886 ◽  
Author(s):  
Brijesh Singh Yadav ◽  
Venkateswarlu Ronda ◽  
Dinesh P. Vashista ◽  
Bhaskar Sharma
Keyword(s):  
Sequence Data ◽  
Microbial Interactions ◽  
Microbial Pathogens ◽  
Nucleotide Sequence Data ◽  
Computational Approaches ◽  
Microbial Detection ◽  
Sequencing Technologies ◽  
Sequencing Platforms ◽  
Identification And Characterization

The recent advances in sequencing technologies and computational approaches are propelling scientists ever closer towards complete understanding of human-microbial interactions. The powerful sequencing platforms are rapidly producing huge amounts of nucleotide sequence data which are compiled into huge databases. This sequence data can be retrieved, assembled, and analyzed for identification of microbial pathogens and diagnosis of diseases. In this article, we present a commentary on how the metagenomics incorporated with microarray and new sequencing techniques are helping microbial detection and characterization.

scholarly journals Splicing Express: a software suite for alternative splicing analysis using next-generation sequencing data

PeerJ ◽  
2015 ◽  
Vol 3 ◽  
pp. e1419 ◽  
Author(s):  
Jose E. Kroll ◽  
Jihoon Kim ◽  
Lucila Ohno-Machado ◽  
Sandro J. de Souza
Keyword(s):  
Alternative Splicing ◽  
Dna Sequencing ◽  
Next Generation Sequencing Data ◽  
Next Generation ◽  
Sequencing Data ◽  
Software Suite ◽  
Next Generation Dna Sequencing ◽  
Sequencing Technologies ◽  
Body Map ◽  
Sequencing Platforms

Motivation.Alternative splicing events (ASEs) are prevalent in the transcriptome of eukaryotic species and are known to influence many biological phenomena. The identification and quantification of these events are crucial for a better understanding of biological processes. Next-generation DNA sequencing technologies have allowed deep characterization of transcriptomes and made it possible to address these issues. ASEs analysis, however, represents a challenging task especially when many different samples need to be compared. Some popular tools for the analysis of ASEs are known to report thousands of events without annotations and/or graphical representations. A new tool for the identification and visualization of ASEs is here described, which can be used by biologists without a solid bioinformatics background.Results.A software suite namedSplicing Expresswas created to perform ASEs analysis from transcriptome sequencing data derived from next-generation DNA sequencing platforms. Its major goal is to serve the needs of biomedical researchers who do not have bioinformatics skills.Splicing Expressperforms automatic annotation of transcriptome data (GTF files) using gene coordinates available from the UCSC genome browser and allows the analysis of data from all available species. The identification of ASEs is done by a known algorithm previously implemented in another tool namedSplooce. As a final result,Splicing Expresscreates a set of HTML files composed of graphics and tables designed to describe the expression profile of ASEs among all analyzed samples. By using RNA-Seq data from the Illumina Human Body Map and the Rat Body Map, we show thatSplicing Expressis able to perform all tasks in a straightforward way, identifying well-known specific events.Availability and Implementation.Splicing Expressis written in Perl and is suitable to run only in UNIX-like systems. More details can be found at:http://www.bioinformatics-brazil.org/splicingexpress.

scholarly journals Nanopore sequencing provides rapid and reliable insight into microbial profiles of Intensive Care Units

2021 ◽  
Author(s):  
Guilherme Marcelino Viana de Siqueira ◽  
Felipe Marcelo Pereira-dos-Santos ◽  
Rafael Silva-Rocha ◽  
Maria-Eugenia Guazzaroni
Keyword(s):  
Intensive Care ◽  
Intensive Care Units ◽  
Nanopore Sequencing ◽  
Accurate Identification ◽  
Complex Samples ◽  
Healthcare Settings ◽  
Long Read ◽  
Single Use ◽  
Sequencing Platforms ◽  
Insight Into

Fast and accurate identification of pathogens is an essential task in healthcare settings. Next generation sequencing platforms such as Illumina have greatly expanded the capacity with which different organisms can be detected in hospital samples, and third-generation nanopore-driven sequencing devices such as Oxford Nanopore's minION have recently emerged as ideal sequencing platforms for routine healthcare surveillance due to their long-read capacity and high portability. Despite its great potential, protocols and analysis pipelines for nanopore sequencing are still being extensively validated. In this work, we assess the ability of nanopore sequencing to provide reliable community profiles based on 16S rRNA sequencing in comparison to traditional Illumina platforms using samples collected from Intensive Care Units from a hospital in Brazil. While our results point that lower throughputs may be a shortcoming of the method in more complex samples, we show that the use of single-use Flongle flowcells in nanopore sequencing runs can provide insightful information on the community composition in healthcare settings.

scholarly journals Nanopore Sequencing of a Forensic STR Multiplex Reveals Loci Suitable for Single-Contributor STR Profiling

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 381 ◽  
Author(s):  
Olivier Tytgat ◽  
Yannick Gansemans ◽  
Jana Weymaere ◽  
Kaat Rubben ◽  
Dieter Deforce ◽  
...  
Keyword(s):  
Tandem Repeats ◽  
Massively Parallel Sequencing ◽  
Flow Cell ◽  
Nanopore Sequencing ◽  
Flow Cells ◽  
Pattern Complexity ◽  
Str Loci ◽  
Oxford Nanopore ◽  
Oxford Nanopore Technologies ◽  
Short Tandem

Nanopore sequencing for forensic short tandem repeats (STR) genotyping comes with the advantages associated with massively parallel sequencing (MPS) without the need for a high up-front device cost, but genotyping is inaccurate, partially due to the occurrence of homopolymers in STR loci. The goal of this study was to apply the latest progress in nanopore sequencing by Oxford Nanopore Technologies in the field of STR genotyping. The experiments were performed using the state of the art R9.4 flow cell and the most recent R10 flow cell, which was specifically designed to improve consensus accuracy of homopolymers. Two single-contributor samples and one mixture sample were genotyped using Illumina sequencing, Nanopore R9.4 sequencing, and Nanopore R10 sequencing. The accuracy of genotyping was comparable for both types of flow cells, although the R10 flow cell provided improved data quality for loci characterized by the presence of homopolymers. We identify locus-dependent characteristics hindering accurate STR genotyping, providing insights for the design of a panel of STR loci suited for nanopore sequencing. Repeat number, the number of different reference alleles for the locus, repeat pattern complexity, flanking region complexity, and the presence of homopolymers are identified as unfavorable locus characteristics. For single-contributor samples and for a limited set of the commonly used STR loci, nanopore sequencing could be applied. However, the technology is not mature enough yet for implementation in routine forensic workflows.

scholarly journals Clinical Genetic Screening in Adult Patients with Kidney Disease

2020 ◽  
Vol 15 (10) ◽  
pp. 1497-1510 ◽  
Author(s):  
Enrico Cocchi ◽  
Jordan Gabriela Nestor ◽  
Ali G. Gharavi
Keyword(s):  
Genetic Testing ◽  
Kidney Disease ◽  
Massively Parallel Sequencing ◽  
Kidney Diseases ◽  
Chromosomal Microarray ◽  
Ethical Considerations ◽  
Clinical Genetic ◽  
Genetic Sequencing ◽  
Sequencing Technologies ◽  
Potential Benefits

Expanded accessibility of genetic sequencing technologies, such as chromosomal microarray and massively parallel sequencing approaches, is changing the management of hereditary kidney diseases. Genetic causes account for a substantial proportion of pediatric kidney disease cases, and with increased utilization of diagnostic genetic testing in nephrology, they are now also detected at appreciable frequencies in adult populations. Establishing a molecular diagnosis can have many potential benefits for patient care, such as guiding treatment, familial testing, and providing deeper insights on the molecular pathogenesis of kidney diseases. Today, with wider clinical use of genetic testing as part of the diagnostic evaluation, nephrologists have the challenging task of selecting the most suitable genetic test for each patient, and then applying the results into the appropriate clinical contexts. This review is intended to familiarize nephrologists with the various technical, logistical, and ethical considerations accompanying the increasing utilization of genetic testing in nephrology care.

scholarly journals Recent advances in functional genome analysis

F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1968 ◽  
Author(s):  
Roderic Guigo ◽  
Michiel de Hoon
Keyword(s):  
Functional Genomics ◽  
Human Genome ◽  
Large Scale ◽  
Massively Parallel Sequencing ◽  
Genome Project ◽  
Biological Traits ◽  
Cellular Behavior ◽  
Sequencing Technologies ◽  
Recent Advances ◽  
The Human Genome Project

At the beginning of this century, the Human Genome Project produced the first drafts of the human genome sequence. Following this, large-scale functional genomics studies were initiated to understand the molecular basis underlying the translation of the instructions encoded in the genome into the biological traits of organisms. Instrumental in the ensuing revolution in functional genomics were the rapid advances in massively parallel sequencing technologies as well as the development of a wide diversity of protocols that make use of these technologies to understand cellular behavior at the molecular level. Here, we review recent advances in functional genomic methods, discuss some of their current capabilities and limitations, and briefly sketch future directions within the field.

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