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.     

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。     

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping.     

Genotype and SNP calling from next-generation sequencing data

Meaningful analysis of next-generation sequencing (NGS) data, which are produced extensively by genetics and genomics studies, relies crucially on the accurate calling of SNPs and genotypes. Recently developed statistical methods both improve and quantify the considerable uncertainty associated with genotype calling, and will especially benefit the growing number of studies using low- to medium-coverage data. We review these methods and provide a guide for their use in NGS studies.     

TILLING in extremis

Targeting induced local lesions in genomes (TILLING), initially a functional genomics tool in model plants, has been extended to many plant species and become of paramount importance to reverse genetics in crops species. Because it is readily applicable to most plants, it remains a dominant non-transgenic method for obtaining mutations in known genes. The process has seen many technological changes over the last 10 years; a major recent change has been the application of next-generation sequencing (NGS) to the process, which permits multiplexing of gene targets and genomes. NGS will ultimately lead to TILLING becoming an in silico procedure. We review here the history and technology in brief, but focus more importantly on recent developments in polyploids, vegetatively propagated crops and the future of TILLING for plant breeding.     

When to use next generation sequencing or diagnostic PCR in diet analyses

Next‐generation sequencing (NGS) is increasingly used for diet analyses; however, it may not always describe diet samples well. A reason for this is that diet samples contain mixtures of food DNA in different amounts as well as consumer DNA which can reduce the food DNA characterized. Because of this, detections will depend on the relative amount and identity of each type of DNA. For such samples, diagnostic PCR will most likely give more reliable results, as detection probability is only marginally dependent on other copresent DNA. We investigated the reliability of each method to test (a) whether predatory beetle regurgitates, supposed to be low in consumer DNA, allow to retrieve prey sequences using general barcoding primers that co‐amplify the consumer DNA, and (b) to assess the sequencing depth or replication needed for NGS and diagnostic PCR to give stable results. When consumer DNA is co‐amplified, NGS is better suited to discover the range of possible prey, than for comparing co‐occurrences of diet species between samples, as retested samples were repeatedly different in prey detections with this approach. This shows that samples were incompletely described, as prey detected by diagnostic PCR frequently were missed by NGS. As the sequencing depth needed to reliably describe the diet in such samples becomes very high, the cost‐efficiency and reliability of diagnostic PCR make diagnostic PCR better suited for testing large sample‐sets. Especially if the targeted prey taxa are thought to be of ecological importance, as diagnostic PCR gave more nested and consistent results in repeated testing of the same sample.     

Recent novel approaches for population genomics data analysis

Next‐generation sequencing (NGS) technology is revolutionizing the fields of population genetics, molecular ecology and conservation biology. But it can be challenging for researchers to learn the new and rapidly evolving techniques required to use NGS data. A recent workshop entitled ‘Population Genomic Data Analysis’ was held to provide training in conceptual and practical aspects of data production and analysis for population genomics, with an emphasis on NGS data analysis. This workshop brought together 16 instructors who were experts in the field of population genomics and 31 student participants. Instructors provided helpful and often entertaining advice regarding how to choose and use a NGS method for a given research question, and regarding critical aspects of NGS data production and analysis such as library preparation, filtering to remove sequencing errors and outlier loci, and genotype calling. In addition, instructors provided general advice about how to approach population genomics data analysis and how to build a career in science. The overarching messages of the workshop were that NGS data analysis should be approached with a keen understanding of the theoretical models underlying the analyses, and with analyses tailored to each research question and project. When analysed carefully, NGS data provide extremely powerful tools for answering crucial questions in disciplines ranging from evolution and ecology to conservation and agriculture, including questions that could not be answered prior to the development of NGS technology.     

Identification of Optimum Sequencing Depth Especially for De Novo Genome Assembly of Small Genomes Using Next Generation Sequencing Data

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C.elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6–40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.     

NGS Datenanalyse und Qualitätskontrolle

Next generation DNA sequencing (NGS) is rapidly becoming a pervasive technique within the human genetics community. The analysis of NGS data is however much more challenging than with previous genetic and genomics techniques. In this article, the basic data formats and analysis steps that are involved in any NGS DNA resequencing experiment are described. Special emphasis is placed on methods for quality control.     

Critical review of NGS analyses for de novo genotyping multigene families

The genotyping of highly polymorphic multigene families across many individuals used to be a particularly challenging task because of methodological limitations associated with traditional approaches. Next‐generation sequencing (NGS) can overcome most of these limitations, and it is increasingly being applied in population genetic studies of multigene families. Here, we critically review NGS bioinformatic approaches that have been used to genotype the major histocompatibility complex (MHC) immune genes, and we discuss how the significant advances made in this field are applicable to population genetic studies of gene families. Increasingly, approaches are introduced that apply thresholds of sequencing depth and sequence similarity to separate alleles from methodological artefacts. We explain why these approaches are particularly sensitive to methodological biases by violating fundamental genotyping assumptions. An alternative strategy that utilizes ultra‐deep sequencing (hundreds to thousands of sequences per amplicon) to reconstruct genotypes and applies statistical methods on the sequencing depth to separate alleles from artefacts appears to be more robust. Importantly, the ‘degree of change’ (DOC) method avoids using arbitrary cut‐off thresholds by looking for statistical boundaries between the sequencing depth for alleles and artefacts, and hence, it is entirely repeatable across studies. Although the advances made in generating NGS data are still far ahead of our ability to perform reliable processing, analysis and interpretation, the community is developing statistically rigorous protocols that will allow us to address novel questions in evolution, ecology and genetics of multigene families. Future developments in third‐generation single molecule sequencing may potentially help overcome problems that still persist in de novo multigene amplicon genotyping when using current second‐generation sequencing approaches.     

Value of a newly sequenced bacterial genome

Next-generation sequencing(NGS) technologies have made high-throughput sequencing available to medium- and small-size laboratories, culminating in a tidal wave of genomic information. The quantity of sequenced bacterial genomes has not only brought excitement to the field of genomics but also heightened expectations that NGS would boost antibacterial discovery and vaccine development. Although many possible drug and vaccine targets have been discovered, the success rate of genome-based analysis has remained below expectations. Furthermore, NGS has had consequences for genome quality, resulting in an exponential increase in draft(partial data) genome deposits in public databases. If no further interests are expressed for a particular bacterial genome, it is more likely that the sequencing of its genome will be limited to a draft stage, and the painstaking tasks of completing the sequencing of its genome and annotation will not be undertaken. It is important to know what is lost when we settle for a draft genome and to determine the "scientific value" of a newly sequenced genome. This review addresses the expected impact of newly sequenced genomes on antibacterial discovery and vaccinology. Also, it discusses the factors that could be leading to the increase in the number of draft deposits and the consequent loss of relevant biological information.     

基于新一代测序技术的昆虫转录组学研究进展

新一代测序技术具有快速、 高通量和低成本的特点, 为“组学”研究带来了新方法、 新方案, 正在深刻地改变着当前生物学的研究模式。近年来, 新一代测序技术极大促进了昆虫特别是无参考基因组信息昆虫的转录组学研究。自2008年至今, 采用新一代测序技术已对7个目的68种昆虫进行了转录组测序, 其中由我国学者完成了6个目的22种昆虫的转录组测序。目前, 昆虫转录组学研究主要集中在基因挖掘、 分子标记开发、 基因表达分析等方面, 为全面揭示昆虫生命活动中相关基因功能、 系统发生与进化以及昆虫与其他生物相互作用等奠定了基础。本文总结了当前昆虫转录组学研究的已有成果, 分析了其今后的发展趋势, 讨论了采用新一代测序技术开展昆虫转录组学研究中存在的诸如研究对象相对局限、 测序准确性不够高等不足, 并指出开展昆虫转录组学研究时需充分思考所要回答的科学问题, 选择合适的研究策略, 评估性价比, 以及开发转录组信息高效利用的方法等。作者建议未来的研究方向侧重于： （1）大规模开展基于新一代测序技术的昆虫转录组学研究, 特别是对其他目以及独特生态环境中的代表性昆虫应予以重点关注; （2）开发昆虫转录组数据存储及分析的软硬件; （3）合理利用新一代测序技术研究昆虫转录组并充分挖掘已测昆虫转录组中的遗传信息。     

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。     

Application of Next-generation Sequencing Technology in Forensic Science

Next-generation sequencing （NGS） technology, with its high-throughput capacity and low cost, has developed rapidly in recent years and become an important analytical tool for many genomics researchers. New opportunities in the research domain of the forensic studies emerge by harnessing the power of NGS technology, which can be applied to simultaneously analyzing multi- ple loci of forensic interest in different genetic contexts, such as autosomes, mitochondrial and sex chromosomes. Furthermore, NGS technology can also have potential applications in many other aspects of research. These include DNA database construction, ancestry and phenotypic inference, monozygotic twin studies, body fluid and species identification, and forensic animal, plant and microbiological analyses. Here we review the application of NGS technology in the field of forensic science with the aim of providing a reference for future forensics studies and practice.     

Next Generation Sequencing in der diagnostischen Praxis

Next generation sequencing (NGS) allows whole exome or whole genome sequencing for a given patient to be performed timely and at reasonable cost. This diagnostic quantum leap not only has various legal, ethical and economical aspects but will naturally also impact upon patient care. Currently, however, the wide-spread introduction of NGS into routine diagnostics is facing many obstacles. In particular, it is to be expected that NGS will identify a large number of rare variants in a given patient that are of (yet) unknown clinical significance. As a first step towards solving this problem, we introduce the concept of a database that will systematically integrate genotypic and phenotypic information from the German health care context. Not only will this resource be of great scientific value, but the database shall also provide human geneticists with the evidence base necessary for the reliable evaluation of their patient-related sequencing data.     

Next generation sequencing in cardiomyopathy: towards personalized genomics and medicine

Next generation sequencing (NGS) is perhaps one of the most exciting advances in the field of life sciences and biomedical research in the last decade. With the availability of massive parallel sequencing, human DNA blueprint can be decoded to explore the hidden information with reduced time and cost. This technology has been used to understand the genetic aspects of various diseases including cardiomyopathies. Mutations for different cardiomyopathies have been identified and cataloging mutations on phenotypic basis are underway and are expected to lead to new discoveries that may translate to novel diagnostic, prognostic and therapeutic targets. With ease in handling NGS, cost effectiveness and fast data output, NGS is now considered as a diagnostic tool for cardiomyopathy by providing targeted gene sequencing. In addition to the number of genetic variants that are identified in cardiomyopathies, there is a need of quicker and easy way to screen multiple genes associated with the disease. In this review, an attempt has been made to explain the NGS technology, methods and applications in cardiomyopathies and their perspective in clinical practice and challenges which are to be addressed.