Coming of age: ten years of next-generation sequencing technologies.

Aquaculture is one of the fastest growing agro‐food industries in the world and Asia dominates the world's fish production (70% of total) with a high potential to ensure global food security. The leading aquaculture fish species in Asia show sexual dimorphism for traits such as growth, age at sexual maturity etc. in which one sex outperforms the other, increasing the need for controlling sex‐ratio in the farming system. Despite the huge contribution of Asian aquaculture to global fish production, the Asian aquaculture is facing a lot of challenges, for example, maintaining the genetic purity of the fish species and balancing the sex‐ratio in the culture system. Many of these difficulties arise due to a lack of deep understanding of fish genetics, or to the duplicated genome of cultured species, or to the unavailability of high‐quality reference genomes and information on sex determination mechanisms (crucial for monosex production and establishing appropriate breeding programme). This review has described the existing knowledge of the sex determination mechanisms in fish and genome architecture of four commercially important fish groups in Asia (carps, tilapias, catfishes and snakeheads). We also have outlined possible strategies for identifying sex‐determining gene/s using modern genome sequencing and computational technologies. Finally, we have highlighted the existing challenges and future prospects of Asian aquaculture. We anticipate that developments in genome sequencing technologies will help to address the biological complexities and challenges that exist in commercial aquaculture and will be of value for the future growth of the aquaculture industry in Asia.

Since the Arabidopsis genome was sequenced, hundreds of plant genomes have either been sequenced or are in sequencing progress. Reference genome sequences and large-scale genome sequencing technologies have initiated a new era in molecular breeding. The field of genomics is progressing rapidly and has already provided invaluable practical products for plant molecular breeding. Here, we review progress in genome sequencing technology and its application to plant breeding. We introduce various genomics tools and discuss how next-generation genome sequencing and genotyping technologies have been applied to high-throughput molecular breeding. We also describe the use of epigenome analysis to interpret phenotypic variations that cannot be explained by simple genetics based on the underlying DNA sequence alone, but rather by epigenetically-controlled mechanisms.

Many of the critical technologies in knowledge economy are undergoing an exponential rate of rapid improvement. The best known roadmap to guide exponential trend of improvement has been provided by Moore’s law.This paper will update the validity of Moore’s law by applying it to microprocessor technology. Using Moore’s law as the benchmark, then, we will examine how well the historical trends of performance improvement in speed for mobile cellular, genome sequencing, and microprocessor technologies have followed Moore’s law. We will also test whether the improvement rate have begun to slow down in recent years. Our finding indicates that Moore’s law remains valid over the last 40 years. However, improvement rate of speed measure varies for each technology.Another finding is that more recent improvement rate during the last 10 years again vary between different technologies. For example, a significant acceleration in the improvement rate for genome sequencing technology has occurred, while a marked slowdown has taken place to microprocessor’s clock speed.All of these variations, however, do not alter the fact that exponential trend indicated by Moore’s law remains valid to guide overall improvement of speed expected of these technologies.

Since the first plant genome of Arabidopsis thaliana has been sequenced and published, genome sequencing technologies have undergone significant changes. New algorithms, sequencing technologies and bioinformatic approaches were adopted to obtain genome, transcriptome and exome sequences for model and crop species, which have permitted deep inferences into plant biology. As a result of an improved genome assembly and analysis methods, genome sequencing costs plummeted and the number of high-quality plant genome sequences is constantly growing. Consequently, more than 300 plant genome sequences have been published over the past twenty years. Although many of the published genomes are considered incomplete, they proved to be a valuable tool for identifying genes involved in the formation of economically valuable plant traits, for marker-assisted and genomic selection and for comparative analysis of plant genomes in order to determine the basic patterns of origin of various plant species. Since a high coverage and resolution of a genome sequence is not enough to detect all changes in complex samples, targeted sequencing, which consists in the isolation and sequencing of a specific region of the genome, has begun to develop. Targeted sequencing has a higher detection power (the ability to identify new differences/variants) and resolution (up to one basis). In addition, exome sequencing (the method of sequencing only protein-coding genes regions) is actively developed, which allows for the sequencing of non-expressed alleles and genes that cannot be found with RNA-seq. In this review, an analysis of sequencing technologies development and the construction of “reference” genomes of plants is performed. A comparison of the methods of targeted sequencing based on the use of the reference DNA sequence is accomplished.

The advent and development of single-cell whole-genome sequencing (scWGS) technology has shed lights on the genomic heterogeneities within biosamples at the single-cell resolution. The technology is particularly well-established in the recent decade and witnesses a variety of clinical applications, such as circulating tumor cell (CTC) detection and preimplantation genetic diagnosis/screening (PGD/PGS). In this review, we summarize the latest practical breakthroughs of scWGS in the field of biomedicine, with the hope of providing a guideline to apply single-cell genomic sequencing in clinical researches.

Grappling With Genomic Incidental Findings in the Clinical Realm

Cereals are members of grass family and play an important role in providing food security to billions of people across the globe since the beginning of agriculture. Cereal crops differ considerably from each other in terms of morphology, adaptation and genetic architecture. This has motivated researchers across the world to study their evolution, genetics and development. During the last few decades, phenomenal progress in genomics research has paved the way for comparative genomic studies across crop species, especially the cereals due to their economic importance. These studies together have revealed a good level of conservation across cereals both at macro and micro level. However, most of the comparative studies in cereals prior to genome sequencing projects have been performed at genetic map level. Large-scale genome sequencing projects during the beginning of the twenty-first century, especially in rice, sorghum, maize, barley, wheat and foxtail millet, led to better understanding of the conservations of genes/genomic regions at sequence level. This chapter reviews the status of cereal comparative genomics prior to genome sequencing and progress post-genome sequencing of major cereals. The genomic organization of major cereals has been discussed in detail. The chapter also describes the distinguishing features and the mechanism of evolution of cereal genomes. The advancement in genome sequencing technologies, especially the next-generation sequencing technologies and its effectiveness in performing genomic studies across crops, is also discussed. The various genomic tools, databases and resources for performing comparative genomic studies are reviewed here. The chapter presents the opportunities on how the knowledge gained from comparative genomics of cereals can be used for gene discovery programmes, functional genomics and subsequently genetic improvement of cereal crops.

We, humans, have an ancient microscopic companion: yeasts. These microbial organisms have helped shape our evolution, our civilizations, and our sciences. The evolutionary event that enabled yeasts to produce alcohol more than 100 million years ago was followed with adaptations throughout the animal kingdom to tolerate it. Our realisation that yeast could be used to produce bread, beer, and wine quickly enabled us to fuel the high, caloric need of many civilizations. An international dispute nearly two centuries ago about the biological nature of yeast in alcohol production, ultimately led to the founding of microbiology and the various medicinal benefits from its practice. And today, yeasts are the ‘Swiss Army knives of biotechnology’, as they are often engineered to produced cheaper therapeutics and alternative energy sources.<br/><br/>Although an ancient companion, we have only begun to truly understand yeasts and their biotechnological capabilities, largely due to a new scientific instrument: genome sequencing technology. Analogous to an ‘algorithmic microscope’, genome sequencing technology is enabling us to generate large amounts of data about the genetic composition and diversity of yeasts. But it comes with a challenge: these (ever-growing) datasets are complex. So how do we properly analyse them? How do we consider the complex evolutionary histories encoded in the genomes of yeasts and other microbes alike? What new biology could we learn?

A Practical Guide to the Highly Dynamic Area of Massively Parallel Sequencing The development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphism, genome structure, and epigenomic abnormality. Next-Generation Sequencing Data Analysis shows how next-generation sequencing (NGS) technologies are applied to transform nearly all aspects of biological research. The book walks readers through the multiple stages of NGS data generation and analysis in an easy-to-follow fashion. It covers every step in each stage, from the planning stage of experimental design, sample processing, sequencing strategy formulation, the early stage of base calling, reads quality check and data preprocessing to the intermediate stage of mapping reads to a reference genome and normalization to more advanced stages specific to each application. All major applications of NGS are covered, including: RNA-seq: mRNA-seq and small RNA-seq Genotyping and variant discovery through genome re-sequencing De novo genome assembly ChIP-seq to study DNAprotein interaction Methylated DNA sequencing on epigenetic regulation Metagenome analysis through community genome shotgun sequencing Before detailing the analytic steps for each of these applications, the book presents the ins and outs of the most widely used NGS platforms, with side-by-side comparisons of key technical aspects. This helps practitioners decide which platform to use for a particular project. The book also offers a perspective on the development of DNA sequencing technologies, from Sanger to future-generation sequencing technologies. The book discusses concepts and principles that underlie each analytic step, along with software tools for implementation. It highlights key features of the tools while omitting tedious details to provide an easy-to-follow guide for practitioners in life sciences, bioinformatics, and biostatistics. In addition, references to detailed descriptions of the tools are given for further reading if needed. The accompanying website for the book provides step-by-step, real-world examples of how to apply the tools covered in the text to research projects. All the tools are freely available to academic users.

A Practical Guide to the Highly Dynamic Area of Massively Parallel Sequencing The development of genome and transcriptome sequencing technologies has led to a paradigm shift in life science research and disease diagnosis and prevention. Scientists are now able to see how human diseases and phenotypic changes are connected to DNA mutation, polymorphism, genome structure, and epigenomic abnormality. Next-Generation Sequencing Data Analysis shows how next-generation sequencing (NGS) technologies are applied to transform nearly all aspects of biological research. The book walks readers through the multiple stages of NGS data generation and analysis in an easy-to-follow fashion. It covers every step in each stage, from the planning stage of experimental design, sample processing, sequencing strategy formulation, the early stage of base calling, reads quality check and data preprocessing to the intermediate stage of mapping reads to a reference genome and normalization to more advanced stages specific to each application. All major applications of NGS are covered, including: RNA-seq: mRNA-seq and small RNA-seq Genotyping and variant discovery through genome re-sequencing De novo genome assembly ChIP-seq to study DNAprotein interaction Methylated DNA sequencing on epigenetic regulation Metagenome analysis through community genome shotgun sequencing Before detailing the analytic steps for each of these applications, the book presents the ins and outs of the most widely used NGS platforms, with side-by-side comparisons of key technical aspects. This helps practitioners decide which platform to use for a particular project. The book also offers a perspective on the development of DNA sequencing technologies, from Sanger to future-generation sequencing technologies. The book discusses concepts and principles that underlie each analytic step, along with software tools for implementation. It highlights key features of the tools while omitting tedious details to provide an easy-to-follow guide for practitioners in life sciences, bioinformatics, and biostatistics. In addition, references to detailed descriptions of the tools are given for further reading if needed. The accompanying website for the book provides step-by-step, real-world examples of how to apply the tools covered in the text to research projects. All the tools are freely available to academic users.

The advances in next generation sequencing (NGS) technologies have tremendous impacts on the studies of structural and functional genomics. Sequencing‐based approaches like ChIP‐Seq and RNA‐Seq have started taking the place of microarray experiments to study protein–DNA ( deoxyribonucleic acid ) interactions and transcriptomic profiling, respectively. The arrival of NGS technologies has also enabled several whole human genome resequencing studies to be completed efficiently at an affordable price. The major strengths of NGS technologies are their ultra high‐throughput production, characterized by their ability to generate several hundred megabases to tens of gigabases of sequencing data per instrument run, and more importantly, the steep reduction in cost compared to the traditional Sanger sequencing method. Hence, NGS technologies have rapidly become the primary choice for large scale as well as genome‐wide sequencing studies. The new sequencing‐based approaches to explore structural and functional genomics have produced important information and significantly expanded our knowledge in these areas. Key concepts The rapid developments in sequencing technologies have transformed the approaches in the studies of structural and functional genomics. The arrival of next generation sequencing (NGS) technologies has started substituting traditional Sanger sequencing method in many large‐scale or genome‐wide sequencing studies. Shortly after the first next generation sequencer was introduced by Roche® 454 Life Science, the Genome Sequencer 20 (GS 20) System (it was subsequently replaced by GS FLX System), another two biotechnology companies also marketed their sequencing platforms: Illumina® Genome Analyzer (GA) and Applied Biosystems® (ABI) Supported Oligonucleotide Ligation Detection System (SOLiD). The major attractions of NGS technologies are their ultra high‐throughput production, characterized by their ability to produce gigabases of sequencing data per instrument run, and more importantly, the steep reduction in cost compared to the traditional sequencing method. Previously, the molecular genomics studies mainly relied on microarray technologies such as gene expression microarrays and the ChIP‐chip method (i.e. chromatin immunoprecipitation coupled with microarray) for genome‐wide interrogation. The NGS technologies have been used in various research areas besides the standard sequencing applications such as whole genome sequencing; they have also been increasingly applied in detecting structural variations (paired‐end mapping), studies of protein–DNA interactions and histone modifications (ChIP‐Seq) and transcriptomic profiling of messenger RNAs (mRNAs) and noncoding RNAs (RNA‐Seq). Sequencing‐based approaches have already yielded numerous novel and important findings in research areas like genome‐wide mapping of histone modifications and protein–DNA interactions, discovery of genetic variations and transcriptomics studies even though the approaches are still new and maturing. The NGS technologies have shown their potential of being dominant in future genomics studies. This is evident from several international projects using NGS technologies like the ENCODE Project, 1000 Genomes Project and cancers sequencing project by the International Cancer Genome Consortium. It is only a matter of time before achieving the goal of $1000 per whole genome sequencing. This should not be too far from now given the progresses in the development of third generation sequencing technologies. Although the $1000 genome will technically make sequencing of thousands of human genomes a reality, the substantial cost that will be incurred for data storage, powerful computational packages and analytical softwares has to be borne in mind. However, beyond affordability, what are left behind are the bioinformatics challenges in processing and analysing the huge amount of sequencing data.

Advances in DNA sequencing technology have resulted in an abundance of personalized data with challenging clinical utility and meaning for clinicians. This wealth of data has potential to dramatically impact the quality of healthcare. Nurses are at the focal point in educating patients regarding relevant healthcare needs; therefore, an understanding of sequencing technology and utilizing these data are critical. The objective of this study was to explicate the role of nurses and nurse scientists as integral members of healthcare teams in improving understanding of DNA sequencing data and translational genomics for patients. A history of the nurse role in newborn screening is used as an exemplar. This study serves as an exemplar on how genome sequencing has been utilized in nursing science and incorporates linkages of other omics approaches used by nurses that are included in this special issue. This special issue showcased nurse scientists conducting multi-omic research from various methods, including targeted candidate genes, pharmacogenomics, proteomics, epigenomics, and the microbiome. From this vantage point, we provide an overview of the roles of nurse scientists in genome sequencing research and provide recommendations for the best utilization of nurses and nurse scientists related to genome sequencing.

We are in the midst of a time of great change in genetics that may dramatically impact human biology and medicine. The completion of the human genome project,1,2 the development of low cost, high-throughput parallel sequencing technology, and large-scale studies of genetic variation3 have provided a rich set of techniques and data for the study of genetic disease risk, treatment response, population diversity, and human evolution. Newly-developed sequencing instruments now generate hundreds of millions to billions of short sequences per run, allowing for rapid complete sequencing of human genomes. These technological advances have facilitated a precipitous drop (Figure 1) in the cost per base pair of DNA sequenced. To capitalize on the potential of these technologies for research and clinical applications, translational scientists and clinicians must become familiar with a continuously evolving field. In this review we will provide a historical perspective on human genome sequencing, summarize current and future sequencing technologies, highlight issues related to data management and interpretation, and finally consider research and clinical applications of high-throughput sequencing, with specific emphasis on cardiovascular disease. Open in a separate window Figure 1 Sequencing milestones, costs, and output since completion of the human genome project. Note logarithmic scale for sequencing costs and bases produced per sequence run.

Over the past decade, single-cell omics sequencing technologies have revolutionized biological and medical research and deepened our knowledge of cellular heterogeneities in life activities at the genomic, epigenomic, and transcriptomic levels. Concurrently, single-molecule long-read sequencing (SMS) technologies have also made amazingly rapid progress. In recent years, the convergence of these two exciting fields has injected new vitality into the generation of novel insights in genomics (repetitive elements, structural variations), epigenomics (allele-specific epigenetic modifications), and transcriptomics (alternative splicing) at the single-cell level, providing powerful new tools and opening new opportunities for biomedical fields. In this review, we introduce SMS platform-based single-cell genome, epigenome, and transcriptome sequencing technologies - the current situation and future perspectives.

The Need for Speed and Energy Efficiency in Genome Analysis