Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench ("wet bench") and data analyses conducted using bioinformatics pipelines ("dry bench"). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible "tag" PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.     

Using next-generation sequencing approaches to isolate simple sequence repeat (SSR) loci in the plant sciences

The application of next-generation sequencing (NGS) technologies for the development of simple sequence repeat (SSR) or microsatellite loci for genetic research in the botanical sciences is described. Microsatellite markers are one of the most informative and versatile DNA-based markers used in plant genetic research, but their development has traditionally been a difficult and costly process. NGS technologies allow the efficient identification of large numbers of microsatellites at a fraction of the cost and effort of traditional approaches. The major advantage of NGS methods is their ability to produce large amounts of sequence data from which to isolate and develop numerous genome-wide and gene-based microsatellite loci. The two major NGS technologies with emergent application in SSR isolation are 454 and Illumina. A review is provided of several recent studies demonstrating the efficient use of 454 and Illumina technologies for the discovery of microsatellites in plants. Additionally, important aspects during NGS isolation and development of microsatellites are discussed, including the use of computational tools and high-throughput genotyping methods. A data set of microsatellite loci in the plastome and mitochondriome of cranberry (Vaccinium macrocarpon Ait.) is provided to illustrate a successful application of 454 sequencing for SSR discovery. In the future, NGS technologies will massively increase the number of SSRs and other genetic markers available to conduct genetic research in understudied but economically important crops such as cranberry.     

Current challenges and solutions of de novo assembly

Background: Next-generation sequencing (NGS) technologies have fostered an unprecedented proliferation of high-throughput sequencing projects and a concomitant development of novel algorithms for the assembly of short reads. However, numerous technical or computational challenges in de novo assembly still remain, although many new ideas and solutions have been suggested to tackle the challenges in both experimental and computational settings.Results: In this review, we first briefly introduce some of the major challenges faced by NGS sequence assembly. Then, we analyze the characteristics of various sequencing platforms and their impact on assembly results. After that, we classify de novo assemblers according to their frameworks (overlap graph-based, de Bruijn graph-based and string graph-based), and introduce the characteristics of each assembly tool and their adaptation scene. Next, we introduce in detail the solutions to the main challenges of de novo assembly of next generation sequencing data, single-cell sequencing data and single molecule sequencing data. At last, we discuss the application of SMS long reads in solving problems encountered in NGS assembly.Conclusions: This review not only gives an overview of the latest methods and developments in assembly algorithms, but also provides guidelines to determine the optimal assembly algorithm for a given input sequencing data type.     

The impact of next-generation sequencing on genomics

This article reviews basic concepts,general applications,and the potential impact of next-generation sequencing(NGS)technologies on genomics,with particular reference to currently available and possible future platforms and bioinformatics.NGS technologies have demonstrated the capacity to sequence DNA at unprecedented speed,thereby enabling previously unimaginable scientific achievements and novel biological applications.But,the massive data produced by NGS also presents a significant challenge for data storage,analyses,and management solutions.Advanced bioinformatic tools are essential for the successful application of NGS technology.As evidenced throughout this review,NGS technologies will have a striking impact on genomic research and the entire biological field.With its ability to tackle the unsolved challenges unconquered by previous genomic technologies,NGS is likely to unravel the complexity of the human genome in terms of genetic variations,some of which may be confined to susceptible loci for some common human conditions.The impact of NGS technologies on genomics will be far reaching and likely change the field for years to come.     

Next-generation teaching: a template for bringing genomic and bioinformatic tools into the classroom

The recent increase in accessibility and scale of genetic data available through next-generation sequencing (NGS) technology has transformed biological inquiry. As a direct result, the application and analysis of NGS data has quickly become an important skill for future scientists. However, the steep learning curve for applying NGS technology to biological questions, including the complexity of sample preparation for sequencing and the analysis of large data sets, are deterrents to the integration of NGS into undergraduate education. Here, we present a course-based undergraduate research experience (CURE) designed to aid in overcoming these limitations through NGS investigations of prokaryotic diversity. Specifically, we use 16S rRNA sequencing to explore patterns of diversity stemming from student-directed hypothesis development. This CURE addresses three learning objectives: (1) it provides a forum for experimental design hypothesis generation, (2) it introduces modern genomic tools through a hands-on experience generating an NGS data-set, and (3) it provides students with an introductory experience in bioinformatics.     

amplisas: a web server for multilocus genotyping using next‐generation amplicon sequencing data

Next‐generation sequencing (NGS) technologies are revolutionizing the fields of biology and medicine as powerful tools for amplicon sequencing (AS). Using combinations of primers and barcodes, it is possible to sequence targeted genomic regions with deep coverage for hundreds, even thousands, of individuals in a single experiment. This is extremely valuable for the genotyping of gene families in which locus‐specific primers are often difficult to design, such as the major histocompatibility complex (MHC). The utility of AS is, however, limited by the high intrinsic sequencing error rates of NGS technologies and other sources of error such as polymerase amplification or chimera formation. Correcting these errors requires extensive bioinformatic post‐processing of NGS data. Amplicon Sequence Assignment (amplisas ) is a tool that performs analysis of AS results in a simple and efficient way, while offering customization options for advanced users. amplisas is designed as a three‐step pipeline consisting of (i) read demultiplexing, (ii) unique sequence clustering and (iii) erroneous sequence filtering. Allele sequences and frequencies are retrieved in excel spreadsheet format, making them easy to interpret. amplisas performance has been successfully benchmarked against previously published genotyped MHC data sets obtained with various NGS technologies.     

Discovering and sequencing new plant viral genomes by next‐generation sequencing: description of a practical pipeline

Small‐scale sequencing has improved substantially in recent decades, culminating in the development of next‐generation sequencing (NGS) technologies. Modern NGS methods have helped the discovery of many new plant viruses. Nevertheless, there is still a need to establish solid assembly pipelines targeting small genomes characterised by low identities to known viral sequences. Here, we describe and discuss the fundamental steps required for discovering and sequencing new plant viral genomes by NGS. A practical pipeline and standard alternative tools used in NGS analysis are presented.     

Library preparation methods for next-generation sequencing: Tone down the bias

Next-generation sequencing (NGS) has caused a revolution in biology. NGS requires the preparation of libraries in which (fragments of) DNA or RNA molecules are fused with adapters followed by PCR amplification and sequencing. It is evident that robust library preparation methods that produce a representative, non-biased source of nucleic acid material from the genome under investigation are of crucial importance. Nevertheless, it has become clear that NGS libraries for all types of applications contain biases that compromise the quality of NGS datasets and can lead to their erroneous interpretation. A detailed knowledge of the nature of these biases will be essential for a careful interpretation of NGS data on the one hand and will help to find ways to improve library quality or to develop bioinformatics tools to compensate for the bias on the other hand. In this review we discuss the literature on bias in the most common NGS library preparation protocols, both for DNA sequencing (DNA-seq) as well as for RNA sequencing (RNA-seq). Strikingly, almost all steps of the various protocols have been reported to introduce bias, especially in the case of RNA-seq, which is technically more challenging than DNA-seq. For each type of bias we discuss methods for improvement with a view to providing some useful advice to the researcher who wishes to convert any kind of raw nucleic acid into an NGS library.     

Multilocus sequence typing of Salmonella strains by high-throughput sequencing of selectively amplified target genes

Rapid development of next generation sequencing (NGS) technologies in recent years has made whole genome sequencing of bacterial genomes widely accessible. However, it is often unnecessary or not feasible to sequence the whole genome for most applications of genetic analyses in bacteria. Selectively capturing defined genomic regions followed by NGS analysis could be a promising approach for high-resolution molecular typing of a large set of strains. In this study, we describe a novel and straightforward PCR-based target-capturing method, hairpin-primed multiplex amplification (HPMA), which allows for simultaneous amplification of numerous target genes. To test the feasibility of NGS-based strain typing using HPMA, 20 target gene sequences were simultaneously amplified with barcode tagging in each of 41 Salmonella strains. The amplicons were then pooled and analyzed by 454 pyrosequencing. Analysis of the sequence data, as an extension of multilocus sequence typing (MLST), demonstrated the utility and potential of this novel typing method, MLST-seq, as a high-resolution strain typing method. With the rapidly increasing sequencing capacity of NGS, MLST-seq or its variations using different target enrichment methods can be expected to become a high-resolution typing method in the near future for high-throughput analysis of a large collection of bacterial strains.     

高通量测序技术在细菌耐药中的应用

细菌耐药已成为威胁全球人类公共健康的重要因素之一,快速、准确明确细菌耐药的特性、机制及传播特征对疾病治疗及控制耐药菌的传播具有重要意义。高通量测序技术可以同时平行检测多个基因序列的状态,已广泛应用于细菌耐药检测。目前高通量测序技术在细菌耐药领域的应用主要有:全基因组测序技术、目标区域测序技术和宏基因组测序技术。所采用的测序平台主要为Illumina、Ion Torrent、BGI等二代测序和Pacific Biosciences、Oxford Nonopore 等三代测序平台。通过细菌耐药基因预测细菌耐药表型的准确性在很大程度上依赖于成熟的专业耐药基因数据库,各种通用型、特异型及隐马尔可夫模型耐药基因数据库的建立和完善,为高通量测序技术在细菌耐药领域的应用提供了坚实的基础。本文简要介绍了高通量测序技术、数据分析方法及相应测序平台在细菌耐药领域中的应用进展,并同时介绍了细菌耐药数据库的现状。     

单分子实时测序技术的原理与应用

单分子DNA测序技术是近10年发展起来的新一代测序技术,也称为第三代测序技术,包括单分子实时测序、真正单分子测序、单分子纳米孔测序等技术。文章介绍了单分子实时(Single-molecule real-time,SMRT)测序技术的基本原理、性能以及应用。与Sanger测序法和下一代测序技术相比,SMRT测序具有超长读长、测序周期短、无需模板扩增和直接检测表观修饰位点等特点,为研究人员提供了新选择。同时,SMRT测序的低准确率备受争议(约85%),其中约93%的错误是插入缺失,因此,其数据应用于基因组组装前需先对数据进行纠错处理。目前,SMRT测序在小型基因组从头测序和完整组装中已有良好应用,并且已经或将在表观遗传学、转录组学、大型基因组组装等领域发挥其优势,促进基因组学的研究。     

Identification of an EMS-induced causal mutation in a gene required for boron-mediated root development by low-coverage genome re-sequencing in Arabidopsis

Next-generation sequencing (NGS) technologies enable the rapid production of an enormous quantity of sequence data. These powerful new technologies allow the identification of mutations by whole-genome sequencing. However, most reported NGS-based mapping methods, which are based on bulked segregant analysis, are costly and laborious. To address these limitations, we designed a versatile NGS-based mapping method that consists of a combination of low- to medium-coverage multiplex SOLiD (Sequencing by Oligonucleotide Ligation and Detection) and classical genetic rough mapping. Using only low to medium coverage reduces the SOLiD sequencing costs and, since just 10 to 20 mutant F₂ plants are required for rough mapping, the operation is simple enough to handle in a laboratory with limited space and funding. As a proof of principle, we successfully applied this method to identify the CTR1, which is involved in boron-mediated root development, from among a population of high boron requiring Arabidopsis thaliana mutants. Our work demonstrates that this NGS-based mapping method is a moderately priced and versatile method that can readily be applied to other model organisms.     

Efficient genome-wide genotyping strategies and data integration in crop plants

Key message

Next-generation sequencing (NGS) has revolutionized plant and animal research by providing powerful genotyping methods. This review describes and discusses the advantages, challenges and, most importantly, solutions to facilitate data processing, the handling of missing data, and cross-platform data integration.

Abstract

Next-generation sequencing technologies provide powerful and flexible genotyping methods to plant breeders and researchers. These methods offer a wide range of applications from genome-wide analysis to routine screening with a high level of accuracy and reproducibility. Furthermore, they provide a straightforward workflow to identify, validate, and screen genetic variants in a short time with a low cost. NGS-based genotyping methods include whole-genome re-sequencing, SNP arrays, and reduced representation sequencing, which are widely applied in crops. The main challenges facing breeders and geneticists today is how to choose an appropriate genotyping method and how to integrate genotyping data sets obtained from various sources. Here, we review and discuss the advantages and challenges of several NGS methods for genome-wide genetic marker development and genotyping in crop plants. We also discuss how imputation methods can be used to both fill in missing data in genotypic data sets and to integrate data sets obtained using different genotyping tools. It is our hope that this synthetic view of genotyping methods will help geneticists and breeders to integrate these NGS-based methods in crop plant breeding and research.

     

Genome Wide Sampling Sequencing for SNP Genotyping: Methods,Challenges and Future Development

Genetic polymorphisms, particularly single nucleotide polymorphisms (SNPs), have been widely used to advance quantitative, functional and evolutionary genomics. Ideally, all genetic variants among individuals should be discovered when next generation sequencing (NGS) technologies and platforms are used for whole genome sequencing or resequencing. In order to improve the cost-effectiveness of the process, however, the research community has mainly focused on developing genome-wide sampling sequencing (GWSS) methods, a collection of reduced genome complexity sequencing, reduced genome representation sequencing and selective genome target sequencing. Here we review the major steps involved in library preparation, the types of adapters used for ligation and the primers designed for amplification of ligated products for sequencing. Unfortunately, currently available GWSS methods have their drawbacks, such as inconsistency in the number of reads per sample library, the number of sites/targets per individual, and the number of reads per site/target, all of which result in missing data. Suggestions are proposed here to improve library construction, genotype calling accuracy, genome-wide marker density and read mapping rate. In brief, optimized GWSS library preparation should generate a unique set of target sites with dense distribution along chromosomes and even coverage per site across all individuals.     

新一代测序技术应用于microRNA检测

MicroRNAs(miRNAs)是一类在进化上高度保守的非编码小分子单链RNA(~22nt),在基因转录后调控中发挥至关重要的作用。越来越多的证据表明,miRNAs参与很多重要的生理和病理过程,例如发育、器官形成、调亡、细胞增殖、肿瘤发生等。近年来飞速发展的新一代测序技术在miRNA检测方面具有重要的应用。文章简要介绍了新一代测序技术3大平台的基本步骤和原理,测序数据的生物信息学分析方法以及新一代测序技术在miRNA方向的主要应用。相比于传统的miRNA检测方法,新一代测序技术具有通量高、对遗传物质检测完全且准确度高,可重复性好等优点,在探索新miRNA、miRNA互补链、miRNA编辑、miRNA异构体检测以及miRNA靶基因检测等方面具有巨大优势。随着新一代测序技术的不断发展,测序成本不断降低,在未来几年,新一代测序技术的使用率或将大大增加。新一代测序技术的不断应用将进一步促进人类对于miRNA在各种生理病理过程中的功能和调控的认识。     

高通量测序技术在农作物全基因组序列测定中的应用概览

近几年飞速发展的高通量测序技术(next generation sequencing,NGS)在生命科学研究的各个领域充分展现了其低成本、高通量和应用面广等优势。在现代农业生物技术领域,利用高通量测序技术,科学家们不仅能更经济而高效对农作物、模式植物或不同栽培品种进行深入的全基因组测序、重测序,也可以对成百上千的栽培品种进行高效而准确的遗传差异分析、分子标记分析、连锁图谱分析、表观遗传学分析、转录组分析,进而改进农作物的育种技术,加快新品种的育种研究。其中,获得农作物的全基因组序列是其他研究和分析的基础。本文通过介绍近年来发表的一些利用高通量测序技术进行的农作物全基因组测定和组装的工作,展示高通量测序技术在现代农业生物技术领域的广泛前景以及其建立起来的研究基础。     

Impact of Next Generation Sequencing Techniques in Food Microbiology

Understanding the Maxam-Gilbert and Sanger sequencing as the first generation, in recent years there has been an explosion of newly-developed sequencing strategies, which are usually referred to as next generation sequencing (NGS) techniques. NGS techniques have high-throughputs and produce thousands or even millions of sequences at the same time. These sequences allow for the accurate identification of microbial taxa, including uncultivable organisms and those present in small numbers. In specific applications, NGS provides a complete inventory of all microbial operons and genes present or being expressed under different study conditions. NGS techniques are revolutionizing the field of microbial ecology and have recently been used to examine several food ecosystems. After a short introduction to the most common NGS systems and platforms, this review addresses how NGS techniques have been employed in the study of food microbiota and food fermentations, and discusses their limits and perspectives. The most important findings are reviewed, including those made in the study of the microbiota of milk, fermented dairy products, and plant-, meat- and fish-derived fermented foods. The knowledge that can be gained on microbial diversity, population structure and population dynamics via the use of these technologies could be vital in improving the monitoring and manipulation of foods and fermented food products. They should also improve their safety.