Field Of Next-generation Sequencing Research Articles

Elucidating Cancer Subtypes by Using the Relationship between DNA Methylation and Gene Expression.

Advancements in the field of next generation sequencing (NGS) have generated vast amounts of data for the same set of subjects. The challenge that arises is how to combine and reconcile results from different omics studies, such as epigenome and transcriptome, to improve the classification of disease subtypes. In this study, we introduce sCClust (sparse canonical correlation analysis with clustering), a technique to combine high-dimensional omics data using sparse canonical correlation analysis (sCCA), such that the correlation between datasets is maximized. This stage is followed by clustering the integrated data in a lower-dimensional space. We apply sCClust to gene expression and DNA methylation data for three cancer genomics datasets from the Cancer Genome Atlas (TCGA) to distinguish between underlying subtypes. We evaluate the identified subtypes using Kaplan-Meier plots and hazard ratio analysis on the three types of cancer-GBM (glioblastoma multiform), lung cancer and colon cancer. Comparison with subtypes identified by both single- and multi-omics studies implies improved clinical association. We also perform pathway over-representation analysis in order to identify up-regulated and down-regulated genes as tentative drug targets. The main goal of the paper is twofold: the integration of epigenomic and transcriptomic datasets followed by elucidating subtypes in the latent space. The significance of this study lies in the enhanced categorization of cancer data, which is crucial to precision medicine.

NEXT-GENERATION SEQUENCING IN CANCER: GENETIC DIAGNOSIS, RISK PREDICTION AND CLASSIFICATION

In recent years, developments in the field of next-generation sequencing have led to a decrease in prices, making NGS an essential tool in routine diagnosis. Targeted approaches such as gene panels and exome sequencing have provided many advantages in discovering somatic variants with the help of powerful computational algorithms. However, such targeted approaches fall short regarding the discovery of structural variants and regions of non-coding DNA such as introns, non-Coding RNAs, or regulatory elements. Today, the use of whole-genome sequencing is increasing; open-source databases are developing. However, the difficulty of functional studies related to non-coding regions slows down the development of knowledge on this subject and creates a bottleneck in cancer diagnosis and treatment processes. The combination of new generation technologies such as CRISPR-Cas9, Single-cell sequencing, and long-read sequencing provides excellent advantages in discovering and interpreting variants in non-coding regions but creates new generation problems. The ever-increasing need for computational power and the need for trained and highly qualified personnel make the institutionalization of NGS infrastructures rather difficult, which affects the diagnostic processes of patients at the end of the day. Within the scope of this talk, current developments and new generation approaches to these issues will be focused. 

Overview on Molecular Biomarkers for Laryngeal Cancer: Looking for New Answers to an Old Problem.

Simple SummaryLaryngeal cancer represents one of the most common head and neck cancers worldwide. It can arise in different larynx subsites, each associated with specific clinical-pathological characteristics and treatment options. Due to the nonspecific symptoms, laryngeal cancer diagnosis often occurs in a late phase, resulting in delayed treatment and worse prognosis. Therefore, successful clinical management is strictly linked to the identification of reliable diagnostic and prognostic biomarkers. Herein, we provide an overview of the most promising molecular factors to date identified for both detection and monitoring, focusing on mutated genes, non-coding RNAs, transforming epigenetic events, inflammatory mediators, and immune-related agents.Laryngeal squamous cell cancer (LSCC) accounts for almost 25–30% of all head and neck squamous cell cancers and is clustered according to the affected districts, as this determines distinct tendency to recur and metastasize. A major role for numerous genetic alterations in driving the onset and progression of this neoplasm is emerging. However, major efforts are still required for the identification of molecular markers useful for both early diagnosis and prognostic definition of LSCC that is still characterized by significant morbidity and mortality. Non-coding RNAs appear the most promising as they circulate in all the biological fluids allowing liquid biopsy determination, as well as due to their quick and characteristic modulation useful for non-invasive detection and monitoring of cancer. Other critical aspects are related to recent progress in circulating tumor cells and DNA detection, in metastatic status and chemo-refractoriness prediction, and in the functional interaction of LSCC with chronic inflammation and innate immunity. We review all these aspects taking into account the progress of the technologies in the field of next generation sequencing.

Reproducible and accessible analysis of transposon insertion sequencing in Galaxy for qualitative essentiality analyses

BackgroundSignificant progress has been made in advancing and standardizing tools for human genomic and biomedical research. Yet, the field of next-generation sequencing (NGS) analysis for microorganisms (including multiple pathogens) remains fragmented, lacks accessible and reusable tools, is hindered by local computational resource limitations, and does not offer widely accepted standards. One such “problem areas” is the analysis of Transposon Insertion Sequencing (TIS) data. TIS allows probing of almost the entire genome of a microorganism by introducing random insertions of transposon-derived constructs. The impact of the insertions on the survival and growth under specific conditions provides precise information about genes affecting specific phenotypic characteristics. A wide array of tools has been developed to analyze TIS data. Among the variety of options available, it is often difficult to identify which one can provide a reliable and reproducible analysis.ResultsHere we sought to understand the challenges and propose reliable practices for the analysis of TIS experiments. Using data from two recent TIS studies, we have developed a series of workflows that include multiple tools for data de-multiplexing, promoter sequence identification, transposon flank alignment, and read count repartition across the genome. Particular attention was paid to quality control procedures, such as determining the optimal tool parameters for the analysis and removal of contamination.ConclusionsOur work provides an assessment of the currently available tools for TIS data analysis. It offers ready to use workflows that can be invoked by anyone in the world using our public Galaxy platform (https://usegalaxy.org). To lower the entry barriers, we have also developed interactive tutorials explaining details of TIS data analysis procedures at https://bit.ly/gxy-tis.

MITGARD: an automated pipeline for mitochondrial genome assembly in eukaryotic species using RNA-seq data.

Over the past decade, the field of next-generation sequencing (NGS) has seen dramatic advances in methods and a decrease in costs. Consequently, a large expansion of data has been generated by NGS, most of which have originated from RNA-sequencing (RNA-seq) experiments. Because mitochondrial genes are expressed in most eukaryotic cells, mitochondrial mRNA sequences are usually co-sequenced within the target transcriptome, generating data that are commonly underused or discarded. Here, we present MITGARD, an automated pipeline that reliably recovers the mitochondrial genome from RNA-seq data from various sources. The pipeline identifies mitochondrial sequence reads based on a phylogenetically related reference, assembles them into contigs, and extracts a complete mtDNA for the target species. We demonstrate that MITGARD can reconstruct the mitochondrial genomes of several species throughout the tree of life. We noticed that MITGARD can recover the mitogenomes in different sequencing schemes and even in a scenario of low-sequencing depth. Moreover, we showed that the use of references from congeneric species diverging up to 30 million years ago (MYA) from the target species is sufficient to recover the entire mitogenome, whereas the use of species diverging between 30 and 60 MYA allows the recovery of most mitochondrial genes. Additionally, we provide a case study with original data in which we estimate a phylogenetic tree of snakes from the genus Bothrops, further demonstrating that MITGARD is suitable for use on biodiversity projects. MITGARD is then a valuable tool to obtain high-quality information for studies focusing on the phylogenetic and evolutionary aspects of eukaryotes and provides data for easily identifying a sample using barcoding, and to check for cross-contamination using third-party tools.

Sequencing Strategies for Fusion Gene Detection.

Fusion genes formed by chromosomal rearrangements are common drivers of cancer. Recent innovations in the field of next-generation sequencing (NGS) have seen a dynamic shift from traditional fusion detection approaches, such as visual characterization by fluorescence, to more precise multiplexed methods. There are many different NGS-based approaches to fusion gene detection and deciding on the most appropriate method can be difficult. Beyond the experimental approach, consideration needs to be given to factors such as the ease of implementation, processing time, associated costs, and the level of expertise required for data analysis. Here, the different NGS-based methods for fusion gene detection, the basic principles underlying the techniques, and the benefits and limitations of each approach are reviewed. This article concludes with a discussion of how NGS will impact fusion gene detection in a clinical context and from where the next innovations are evolving.

Clinical Applications of Next-Generation Sequencing

The significant drop in sequencing costs boosted by chemistries optimization and sample multiplexation has resulted in an immense growth within the field of next-generation sequencing (NGS) in the last decade. This has allowed a diversification of techniques, promoting a rapid advance in knowledge on the molecular basis of human disease. Due to the applicability and importance of this technology in basic research, it has quickly migrated to the clinical setting. NGS enables clinicians to make improved diagnostic and treatment decisions, which ultimately may influence precision medicine.

Genomic alterations and precise medicine of esophageal squamous cell carcinoma

Abstract Human cancer is a complex disease caused by the interaction of multiple genes and environmental factors. It is known that environmental factors such as smoking, drinking, and food carcinogens are implicated in the development of certain types of cancer including esophageal squamous cell carcinoma (ESCC). However, only a small portion of exposed individuals finally developed cancer, indicating that genetic makeup also plays an important role in the tumorigenesis. Genome-wide association studies (GWAS) have found numerous susceptible genes or loci for cancers, providing new ideas and directions for precision prevention and treatment of cancers. With the advances in the field of next-generation sequencing (NGS), the genomic landscapes of many types of human cancer have comprehensively been characterized. Here, we review the progresses of GWAS and NGS in revealing genomic variations of ESCC, one of the most common cancers in China, and discuss the potential applications of these results in precision medicine of ESCC.

The pyrosequencing protocol for bacterial genomes.

The pyrosequencing methodology was applied in 2005 by 454 Lifesciences to the emerging field of next generation sequencing (NGS), revolutionizing the way of DNA sequencing. In the last years the same strategy grew up and was technologically updated, reaching a high throughput in terms of amount of generated sequences (reads) per run and in terms of length of sequence up to values of 800-1,000 bases. These features of pyrosequencing perfectly fit to bacterial genome sequencing for the de novo assemblies and resequencing as well. The approaches of shotgun and paired ends sequencing allow the bacterial genome finishing providing a high-quality data in few days with unprecedented results.

Sequence Of Events

Roche has acquired Genia Technologies, a privately held gene-sequencing company based in Mountain View, Calif. The Swiss drug and diagnostics company is looking to bolster its standing in the next-generation sequencing field after recent setbacks. Roche sees its purchase as a step toward introducing “a potentially disruptive technology to the market,” says Roland Diggelmann, chief operating officer of Roche Diagnostics. To do so, Roche is willing to pay Genia’s shareholders $125 million in cash and up to $225 million in milestone payments. Founded in 2009, Genia is developing a semiconductor-based system using nanopore technology for massively parallel, single-molecule DNA sequencing. Much of the core technology came from work with professors Jingyue Ju at Columbia University and George Church at Harvard University. Genia’s approach uses an assembly of protein pores in a lipid bilayer. Single nucleotides are identified through base-specific tags that are cleaved from the sequence and detected electrically...

An empirical study of choosing efficient discriminative seeds for oligonucleotide design

BackgroundOligonucleotide design is known as a time-consuming work in bioinformatics. In order to accelerate and be efficient the oligonucleotide design process, one of widely used approach is the prescreening unreliable regions using a hashing (or seeding) algorithm. Since the seeding algorithm is originally proposed to increase sensitivity for local alignment, the specificity should be considered as well as the sensitivity for the oligonucleotide design problem. However, a measure of evaluating the seeds regarding how adequate and efficient they are in the oligo design is not yet proposed. Here, we propose novel measures of evaluating the seeding algorithms based on the discriminability and the efficiency.ResultsTo evaluate the proposed measures, we examine five seeding algorithms in oligonucleotide design. We carried out a series of experiments to compare the seeding algorithms. As the result, the spaced seed is recorded as the most efficient discriminative seed for oligo design. The performance of transition-constrained seed is slightly lower than the spaced seed. Because BLAT seeding algorithm and Vector seeding algorithm give poor scores in specificity and efficiency, we conclude that these algorithms are not adequate to design oligos.Consequently, we recommend spaced seeds or transition-constrained seeds with 15~18 weight in order to design oligos with the length of 50 mer. The empirical experiments in real biological data reveal that the recommended seeds show consequently good performance. We also propose a software package which enables the users to get the adequate seeds under their own experimental conditions.ConclusionOur study is valuable to the two points. One is that our study can be applied to the oligo design programs in order to improve the performance by suggesting the experiment-specific seeds. The other is that our study is useful to improve the performance of the mapping assembly in the field of Next-Generation Sequencing. Our proposed measures are originally designed to be used for oligo design but we expect that our study will be helpful to the other genomic tasks.