Recent Progress Using High-throughput Sequencing Technologies in Plant Molecular Breeding

High-throughput sequencing is a revolutionary technological innovation in DNA sequencing.This technology has an ultra-low cost per base of sequencing and an overwhelmingly high data output.High-throughput sequencing has brought novel research methods and solutions to the research fields of genomics and post-genomics.Furthermore,this technology is leading to a new molecular breeding revolution that has landmark significance for scientific research and enables us to launch multi-level,multi-faceted,and multi-extent studies in the fields of crop genetics,genomics,and crop breeding.In this paper,we review progress in the application of high-throughput sequencing technologies to plant molecular breeding studies.     

From bacterial genomics to metagenomics: concept,tools and recent advances

In the last 20 years, the applications of genomics tools have completely transformed the field of microbial research. This has primarily happened due to revolution in sequencing technologies that have become available today. This review therefore, first describes the discoveries, upgradation and automation of sequencing techniques in a chronological order, followed by a brief discussion on microbial genomics. Some of the recently sequenced bacterial genomes are described to explain how complete genome data is now being used to derive interesting findings. Apart from the genomics of individual microbes, the study of unculturable microbiota from different environments is increasingly gaining importance. The second section is thus dedicated to the concept of metagenomics describing environmental DNA isolation, metagenomic library construction and screening methods to look for novel and potentially important genes, enzymes and biomolecules. It also deals with the pioneering studies in the area of metagenomics that are offering new insights into the previously unappreciated microbial world. The authors have contributed equally to the work     

Perspectives of DNA microarray and next-generation DNA sequencing technologies

DNA microarray and next-generation DNA sequencing technologies are important tools for high-throughput genome research, in revealing both the structural and functional characteristics of genomes. In the past decade the DNA microarray technologies have been widely applied in the studies of functional genomics, systems biology and pharmacogenomics. The next-generation DNA sequencing method was first introduced by the 454 Company in 2003, immediately followed by the establishment of the Solexa and Solid techniques by other biotech companies. Though it has not been long since the first emergence of this technology, with the fast and impressive improvement, the application of this technology has extended to almost all fields of genomics research, as a rival challenging the existing DNA microarray technology. This paper briefly reviews the working principles of these two technologies as well as their application and perspectives in genome research. Supported by the National High-Tech Research Program of China (Grant No.2006AA020704) and Shanghai Science and Technology Commission (Grant No. 05DZ22201)     

纳米孔测序信号处理及其在DNA数据存储的应用

随着高通量测序技术的不断更新,可以在单个分子水平读取核苷酸序列的第三代测序技术迅速发展,纳米孔测序技术是其具有代表性的单分子测序技术,该技术通过检测DNA单链分子穿过纳米孔时引起的跨膜电流信号的变化,实现碱基识别.纳米孔测序仪在便携性、碱基读取速度、测序读段长度等方面较传统的第一代与第二代测序技术都有明显优势.随着纳米...     

Reconstruction of Microbial Haplotypes by Integration of Statistical and Physical Linkage in Scaffolding

DNA sequencing technologies provide unprecedented opportunities to analyze within-host evolution of microorganism populations. Often, within-host populations are analyzed via pooled sequencing of the population, which contains multiple individuals or “haplotypes.” However, current next-generation sequencing instruments, in conjunction with single-molecule barcoded linked-reads, cannot distinguish long haplotypes directly. Computational reconstruction of haplotypes from pooled sequencing has been attempted in virology, bacterial genomics, metagenomics, and human genetics, using algorithms based on either cross-host genetic sharing or within-host genomic reads. Here, we describe PoolHapX, a flexible computational approach that integrates information from both genetic sharing and genomic sequencing. We demonstrated that PoolHapX outperforms state-of-the-art tools tailored to specific organismal systems, and is robust to within-host evolution. Importantly, together with barcoded linked-reads, PoolHapX can infer whole-chromosome-scale haplotypes from 50 pools each containing 12 different haplotypes. By analyzing real data, we uncovered dynamic variations in the evolutionary processes of within-patient HIV populations previously unobserved in single position-based analysis.     

单分子测序技术及应用研究进展

从DNA双螺旋结构的发现开始,生命科学研究进入分子水平,在20世纪70年代出现的测序技术为破译遗传密码作出了巨大贡献.近几年出现的单分子测序技术,可以在单个分子水平读取核苷酸序列,也被称为第三代测序技术,主要代表有HeliScope、Nanopore和PacBio等.与传统的第一代和第二代测序技术相比,第三代测序能够产生更长的碱基读长,能直接对RNA进行测序,无需逆转录,测序速度极快,同时其中某些技术所涉及的设备可以小型化,可便携至野外现场测序.第三代测序技术在生命科学基础理论研究及生物医学临床实践中,具有广泛的应用.本文重点介绍了各种单分子测序技术的原理、优缺点,及其应用研究进展.     

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.     

Plant genomics in Africa: present and prospects

Plants are the world’s most consumed goods. They are of high economic value and bring many health benefits. In most countries in Africa, the supply and quality of food will rise to meet the growing population’s increasing demand. Genomics and other biotechnology tools offer the opportunity to improve subsistence crops and medicinal herbs in the continent. Significant advances have been made in plant genomics, which have enhanced our knowledge of the molecular processes underlying both plant quality and yield. The sequencing of complex genomes of African plant species, facilitated by the continuously evolving next-generation sequencing technologies and advanced bioinformatics approaches, has provided new opportunities for crop improvement. This review summarizes the achievements of genome sequencing projects of endemic African plants in the last two decades. We also present perspectives and challenges for future plant genomic studies that will accelerate important plant breeding programs for African communities. These challenges include a lack of basic facilities, a lack of sequencing and bioinformatics facilities, and a lack of skills to design genomics studies. However, it is imperative to state that African countries have become key players in the plant genome revolution and genome derived-biotechnology. Therefore, African governments should invest in public plant genomics research and applications, establish bioinformatics platforms and training programs, and stimulate university and industry partnerships to fully deploy plant genomics, particularly in the fields of agriculture and medicine.     

Advantages of Single-Molecule Real-Time Sequencing in High-GC Content Genomes

Next-generation sequencing has become the most widely used sequencing technology in genomics research, but it has inherent drawbacks when dealing with high-GC content genomes. Recently, single-molecule real-time sequencing technology (SMRT) was introduced as a third-generation sequencing strategy to compensate for this drawback. Here, we report that the unbiased and longer read length of SMRT sequencing markedly improved genome assembly with high GC content via gap filling and repeat resolution.     

Turning quantity into quality: novel quality assurance strategies for data produced by high-throughput genomics technologies

The pharmaceutical industry is facing the challenge of managing the exponential increase in volume, diversity and complexity of data generated by high-throughput technologies such as genome sequencing, gene-expression profiling, protein-expression profiling, metabolic profiling and high-throughput screening. These novel ‘genomics’ technologies are expected to reshape the approach of life science companies to research. Unfortunately, in many cases genomics technologies have been used uncritically, and some preliminary results have been disappointing. The lack of standardized data validation and quality assurance processes is recognized as one of the major hurdles for successfully implementing genomics technologies. This is particularly important for industrialized drug discovery processes, because more and more key conclusions and far-reaching decisions in the pharmaceutical industry are based on data that is generated automatically. Therefore, automated, specialized quality-control systems that can spot erroneous data that might obscure important biological effects are needed urgently. In this article, special emphasis is placed on DNA microarray technologies, a key genomics technology that suffers from severe problems with data quality. A generic, automatable data-quality-assurance workflow is discussed that will ultimately improve the quality of the drug candidates and, at the same time, reduce overall drug-development costs.     

From Pasteur to genomics: progress and challenges in infectious diseases

Over the past decade, microbiology and infectious disease research have undergone the most profound revolution since the times of Pasteur. Genomic sequencing has revealed the much-awaited blueprint of most pathogens. Screening blood for the nucleic acids of infectious agents has blunted the spread of pathogens by transfusion, the field of antiviral therapeutics has exploded and technologies for the development of novel and safer vaccines have become available. The quantum jump in our ability to detect, prevent and treat infectious diseases resulting from improved technologies and genomics was moderated during this period by the greatest emergence of new infectious agents ever recorded and a worrisome increase in resistance to existing therapies. Dozens of new infectious diseases are expected to emerge in the coming decades. Controlling these diseases will require a better understanding of the worldwide threat and economic burden of infectious diseases and a global agenda.     

Automation of Molecular-Based Analyses: A Primer on Massively Parallel Sequencing

Recent advances in genetics have been enabled by new genetic sequencing techniques called massively parallel sequencing (MPS) or next-generation sequencing. Through the ability to sequence in parallel hundreds of thousands to millions of DNA fragments, the cost and time required for sequencing has dramatically decreased. There are a number of different MPS platforms currently available and being used in Australia. Although they differ in the underlying technology involved, their overall processes are very similar: DNA fragmentation, adaptor ligation, immobilisation, amplification, sequencing reaction and data analysis. MPS is being used in research, translational and increasingly now also in clinical settings. Common applications include sequencing of whole genomes, whole exomes or targeted genes for disease-causing gene discovery, genetic diagnosis and targeted cancer therapy. Even though the revolution that is occurring with MPS is exciting due to its increasing use, improving and emerging technologies and new applications, significant challenges still exist. Particularly challenging issues are the bioinformatics required for data analysis, interpretation of results and the ethical dilemma of ‘incidental findings’.     

Lessons learnt on the analysis of large sequence data in animal genomics

The ’omics revolution has made a large amount of sequence data available to researchers and the industry. This has had a profound impact in the field of bioinformatics, stimulating unprecedented advancements in this discipline. Mostly, this is usually looked at from the perspective of human ’omics, in particular human genomics. Plant and animal genomics, however, have also been deeply influenced by next‐generation sequencing technologies, with several genomics applications now popular among researchers and the breeding industry. Genomics tends to generate huge amounts of data, and genomic sequence data account for an increasing proportion of big data in biological sciences, due largely to decreasing sequencing and genotyping costs and to large‐scale sequencing and resequencing projects. The analysis of big data poses a challenge to scientists, as data gathering currently takes place at a faster pace than does data processing and analysis, and the associated computational burden is increasingly taxing, making even simple manipulation, visualization and transferring of data a cumbersome operation. The time consumed by the processing and analysing of huge data sets may be at the expense of data quality assessment and critical interpretation. Additionally, when analysing lots of data, something is likely to go awry—the software may crash or stop—and it can be very frustrating to track the error. We herein review the most relevant issues related to tackling these challenges and problems, from the perspective of animal genomics, and provide researchers that lack extensive computing experience with guidelines that will help when processing large genomic data sets.     

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。