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September 22, 2019  |  

Next-generation sequencing for pathogen detection and identification

Over the past decade, the field of genomics has seen such drastic improvements in sequencing chemistries that high-throughput sequencing, or next-generation sequencing (NGS), is being applied to generate data across many disciplines. NGS instruments are becoming less expensive, faster, and smaller, and therefore are being adopted in an increasing number of laboratories, including clinical laboratories. Thus far, clinical use of NGS has been mostly focused on the human genome, for purposes such as characterizing the molecular basis of cancer or for diagnosing and understanding the basis of rare genetic disorders. There are, however, an increasing number of examples whereby NGS is employed to discover novel pathogens, and these cases provide precedent for the use of NGS in microbial diagnostics. NGS has many advantages over traditional microbial diagnostic methods, such as unbiased rather than pathogen-specific protocols, ability to detect fastidious or non-culturable organisms, and ability to detect co-infections. One of the most impressive advantages of NGS is that it requires little or no prior knowledge of the pathogen, unlike many other diagnostic assays; therefore for pathogen discovery, NGS is very valuable. However, despite these advantages, there are challenges involved in implementing NGS for routine clinical microbiological diagnosis. We discuss these advantages and challenges in the context of recently described research studies.


September 22, 2019  |  

The new world of isoform sequencing

Not too long ago, the life sciences community was still debating whether sequencers would ever overtake microarrays as the preferred means of measuring gene expression. Today, not only have sequencers become the standard workhorse for gene expression studies, but newer sequencing technology has delivered the ability to generate novel expression data even in the most well-characterized cells or organisms. Truly, it is a remarkable time for comprehensive studies of which genes are being transcribed, with the goal of providing functional insight into various biological processes. The key advantage sequencing holds over microarrays is its ability to deeply survey an entire transcriptome, while microarrays are limited to interrogating known genes using probes designed from a reference genome assembly. As next-generation sequencing became more affordable, scientists were eager to switch to this approach, which became known as RNA sequencing or simply RNA-seq. © Mary Ann Liebert, Inc.


September 22, 2019  |  

Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics.

Short read massive parallel sequencing has emerged as a standard diagnostic tool in the medical setting. However, short read technologies have inherent limitations such as GC bias, difficulties mapping to repetitive elements, trouble discriminating paralogous sequences, and difficulties in phasing alleles. Long read single molecule sequencers resolve these obstacles. Moreover, they offer higher consensus accuracies and can detect epigenetic modifications from native DNA. The first commercially available long read single molecule platform was the RS system based on PacBio’s single molecule real-time (SMRT) sequencing technology, which has since evolved into their RSII and Sequel systems. Here we capsulize how SMRT sequencing is revolutionizing constitutional, reproductive, cancer, microbial and viral genetic testing.© The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research.


September 22, 2019  |  

Computational analysis of alternative splicing in plant genomes.

Computational analyses play crucial roles in characterizing splicing isoforms in plant genomes. In this review, we provide a survey of computational tools used in recently published, genome-scale splicing analyses in plants. We summarize the commonly used software and pipelines for read mapping, isoform reconstruction, isoform quantification, and differential expression analysis. We also discuss methods for analyzing long reads and the strategies to combine long and short reads in identifying splicing isoforms. We review several tools for characterizing local splicing events, splicing graphs, coding potential, and visualizing splicing isoforms. We further discuss the procedures for identifying conserved splicing isoforms across plant species. Finally, we discuss the outlook of integrating other genomic data with splicing analyses to identify regulatory mechanisms of AS on genome-wide scale. Copyright © 2018 Elsevier B.V. All rights reserved.


September 22, 2019  |  

Next generation sequencing technology: Advances and applications.

Impressive progress has been made in the field of Next Generation Sequencing (NGS). Through advancements in the fields of molecular biology and technical engineering, parallelization of the sequencing reaction has profoundly increased the total number of produced sequence reads per run. Current sequencing platforms allow for a previously unprecedented view into complex mixtures of RNA and DNA samples. NGS is currently evolving into a molecular microscope finding its way into virtually every fields of biomedical research. In this chapter we review the technical background of the different commercially available NGS platforms with respect to template generation and the sequencing reaction and take a small step towards what the upcoming NGS technologies will bring. We close with an overview of different implementations of NGS into biomedical research. This article is part of a Special Issue entitled: From Genome to Function. Copyright © 2014 Elsevier B.V. All rights reserved.


September 22, 2019  |  

Defining cell identity with single cell omics.

Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation-most notably in the emergence and evolution of tumors. Recent technical advances in single-cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.© 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.


September 22, 2019  |  

Avian transcriptomics: opportunities and challenges

Recent developments in next-generation sequencing technologies have greatly facilitated the study of whole transcriptomes in model and non-model species. Studying the transcriptome and how it changes across a variety of biological conditions has had major implications for our understanding of how the genome is regulated in different contexts, and how to interpret adaptations and the phenotype of an organism. The aim of this review is to highlight the potential of these new technologies for the study of avian transcriptomics, and to summarise how transcriptomics has been applied in ornithology. A total of 81 peer-reviewed scientific articles that used transcriptomics to answer questions within a broad range of study areas in birds are used as examples throughout the review. We further provide a quick guide to highlight the most important points which need to be take into account when planning a transcriptomic study in birds, and discuss how researchers with little background in molecular biology can avoid potential pitfalls. Suggestions for further reading are supplied throughout. We also discuss possible future developments in the technology platforms used for ribonucleic acid sequencing. By summarising how these novel technologies can be used to answer questions that have long been asked by ornithologists, we hope to bridge the gap between traditional ornithology and genomics, and to stimulate more interdisciplinary research.


September 22, 2019  |  

Current progress in EBV-associated B-cell lymphomas.

Epstein-Barr virus (EBV) was the first human tumor virus discovered more than 50 years ago. EBV-associated lymphomagenesis is still a significant viral-associated disease as it involves a diverse range of pathologies, especially B-cell lymphomas. Recent development of high-throughput next-generation sequencing technologies and in vivo mouse models have significantly promoted our understanding of the fundamental molecular mechanisms which drive these cancers and allowed for the development of therapeutic intervention strategies. This review will highlight the current advances in EBV-associated B-cell lymphomas, focusing on transcriptional regulation, chromosome aberrations, in vivo studies of EBV-mediated lymphomagenesis, as well as the treatment strategies to target viral-associated lymphomas.


September 22, 2019  |  

Accurate determination of bacterial abundances in human metagenomes using full-length 16S sequencing reads

DNA sequencing of PCR-amplified marker genes, especially but not limited to the 16S rRNA gene, is perhaps the most common approach for profiling microbial communities. Due to technological constraints of commonly available DNA sequencing, these approaches usually take the form of short reads sequenced from a narrow, targeted variable region, with a corresponding loss of taxonomic resolution relative to the full length marker gene. We use Pacific Biosciences single-molecule, real-time circular consensus sequencing to sequence amplicons spanning the entire length of the 16S rRNA gene. However, this sequencing technology suffers from high sequencing error rate that needs to be addressed in order to take full advantage of the longer sequence. Here, we present a method to model the sequencing error process using a generalized pair hidden Markov chain model and estimate bacterial abundances in microbial samples. We demonstrate, with simulated and real data, that our model and its associated estimation procedure are able to give accurate estimates at the species (or subspecies) level, and is more flexible than existing methods like SImple Non-Bayesian TAXonomy (SINTAX).


September 22, 2019  |  

The state of play in higher eukaryote gene annotation.

A genome sequence is worthless if it cannot be deciphered; therefore, efforts to describe – or ‘annotate’ – genes began as soon as DNA sequences became available. Whereas early work focused on individual protein-coding genes, the modern genomic ocean is a complex maelstrom of alternative splicing, non-coding transcription and pseudogenes. Scientists – from clinicians to evolutionary biologists – need to navigate these waters, and this has led to the design of high-throughput, computationally driven annotation projects. The catalogues that are being produced are key resources for genome exploration, especially as they become integrated with expression, epigenomic and variation data sets. Their creation, however, remains challenging.


September 22, 2019  |  

Analyses of intestinal microbiota: culture versus sequencing.

Analyzing human as well as animal microbiota composition has gained growing interest because structural components and metabolites of microorganisms fundamentally influence all aspects of host physiology. Originally dominated by culture-dependent methods for exploring these ecosystems, the development of molecular techniques such as high throughput sequencing has dramatically increased our knowledge. Because many studies of the microbiota are based on the bacterial 16S ribosomal RNA (rRNA) gene targets, they can, at least in principle, be compared to determine the role of the microbiome composition for developmental processes, host metabolism, and physiology as well as different diseases. In our review, we will summarize differences and pitfalls in current experimental protocols, including all steps from nucleic acid extraction to bioinformatical analysis which may produce variation that outweighs subtle biological differences. Future developments, such as integration of metabolomic, transcriptomic, and metagenomic data sets and standardization of the procedures, will be discussed. © The Author 2015. Published by Oxford University Press on behalf of the Institute for Laboratory Animal Research. All rights reserved. For permissions, please email: journals.permissions@oup.com.


September 22, 2019  |  

The human microbiome and understanding the 16S rRNA gene in translational nursing science.

As more is understood regarding the human microbiome, it is increasingly important for nurse scientists and healthcare practitioners to analyze these microbial communities and their role in health and disease. 16S rRNA sequencing is a key methodology in identifying these bacterial populations that has recently transitioned from use primarily in research to having increased utility in clinical settings.The objectives of this review are to (a) describe 16S rRNA sequencing and its role in answering research questions important to nursing science; (b) provide an overview of the oral, lung, and gut microbiomes and relevant research; and (c) identify future implications for microbiome research and 16S sequencing in translational nursing science.Sequencing using the 16S rRNA gene has revolutionized research and allowed scientists to easily and reliably characterize complex bacterial communities. This type of research has recently entered the clinical setting, one of the best examples involving the use of 16S sequencing to identify resistant pathogens, thereby improving the accuracy of bacterial identification in infection control. Clinical microbiota research and related requisite methods are of particular relevance to nurse scientists-individuals uniquely positioned to utilize these techniques in future studies in clinical settings.


September 22, 2019  |  

MEGAN-LR: new algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs.

There are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing, and there is a need to adapt short read tools to long read datasets.We describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.All presented methods are implemented in the open source edition of MEGAN, and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.This article was reviewed by Nicola Segata together with Moreno Zolfo, Pete James Lockhart and Serghei Mangul.This work extends the applicability of the widely-used metagenomic analysis software MEGAN to long reads. Our study suggests that the presented LAST+MEGAN-LR pipeline is sufficiently fast and accurate.


September 22, 2019  |  

How far can mitochondrial DNA drive the disease?

Mitochondria are one of the dominant drivers for producing cellular energy to meet a large number of biological functions, of which the mitochondrial DNA (mtDNA) is the control center of energetic driving force and the dominant driver of mitochondrial molecular diversification. mtDNA transcription generates the necessary RNAs to regulate the extent and nature of mtRNA post-transcriptional modifications and the activity of nucleus-encoded enzymes. With a special focus on mtDNA, the current volume aims to overview the biology and structures of mtDNA, regulatory roles of mtDNA in lung diseases, or involvement of mtDNA in metabolism. We explore the significance of mtDNA sequencing, methylation, stability, and mutation in the pathogenesis of the diseases. Molecular mechanisms by which mtDNA contribute to the regulation of mitochondrial homeostasis and drug resistance are also discussed. We also point out the importance of mitochondrial ribosome, single cell biology, and gene editing in the understanding of the development of mitochondrial dysfunction in lung disease.


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