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。     

Understanding genetic variation and function- the applications of next generation sequencing

Next generation sequencing (NGS) technology has had a transformatory effect upon population-level studies linking genetic variation to gene function. In this review, I briefly describe recent studies that have used top-down genome scanning and population genetic approaches to identify loci under recent selection, as well as some examples of how large NGS datasets can be deployed to detect the total level of deleterious, neutral and advantageous variation present in standing genetic variation. I then explore studies that have used some of these approaches to study gene function along with advances in sequencing populations under selection, QTL mapping techniques and emerging methodologies utilising targeted capture and NGS.     

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.     

The status of AFLP in the genomics era and a pipeline for converting AFLPs into single-locus markers

Even though next-generation sequencing (NGS) has now become the predominant state-of-the-art technique for genotyping populations, amplified fragment length polymorphism (AFLP) DNA fingerprinting is still a relevant method, thanks to its versatility, cost-effectiveness, independence of prior sequence information and broad applicability. Even though the number of AFLP studies reached its peak in 2012, it is still applied extensively for phylogenetic analysis, genotyping or identifying non-model species, which often feature complex and large genomes. For these purposes, tools continue to be developed for designing AFLP studies, scoring AFLPs or handling AFLP data. Moreover, AFLP studies embrace the NGS technology; for example, the whole-genome sequence of model species is used to design more efficient AFLP studies for non-model species. Conversely, in complexity reduction of polymorphic sequences and restriction site-associated DNA sequencing studies, polymorphisms are often found to be present in many restriction sites, which can still be studied as AFLPs. We discuss the latest advances in AFLP-based studies in the era of NGS and anticipate that AFLP will remain a relevant method in the near future, even for species with a known genome, owing to its many promising new features such as methylation-sensitive-AFLP. Here, we also present an optimized pipeline for converting AFLP markers into single-locus markers, which can be applied in both traditional AFLP and NGS studies.     

Bacterial genome mapper: A comparative bacterial genome mapping tool

Recently, next generation sequencing (NGS) technologies have led to a revolutionary increase in sequencing speed and costefficacy. Consequently, a vast number of contigs from many recently sequenced bacterial genomes remain to be accurately mapped and annotated, requiring the development of more convenient bioinformatics programs. In this paper, we present a newly developed web-based bioinformatics program, Bacterial Genome Mapper, which is suitable for mapping and annotating contigs that have been assembled from bacterial genome sequence raw data. By constructing a multiple alignment map between target contig sequences and two reference bacterial genome sequences, this program also provides very useful comparative genomics analysis of draft bacterial genomes. AVAILABILITY: The database is available for free at http://mbgm.kribb.re.kr.     

Comparison of alignment software for genome-wide bisulphite sequence data

Recent advances in next generation sequencing (NGS) technology now provide the opportunity to rapidly interrogate the methylation status of the genome. However, there are challenges in handling and interpretation of the methylation sequence data because of its large volume and the consequences of bisulphite modification. We sequenced reduced representation human genomes on the Illumina platform and efficiently mapped and visualized the data with different pipelines and software packages. We examined three pipelines for aligning bisulphite converted sequencing reads and compared their performance. We also comment on pre-processing and quality control of Illumina data. This comparison highlights differences in methods for NGS data processing and provides guidance to advance sequence-based methylation data analysis for molecular biologists.     

Next-generation sequencing in the analysis of human microbiota: essential considerations for clinical application

The development of next-generation sequencing (NGS) presents an unprecedented opportunity to investigate the complex microbial communities that are associated with the human body. It offers for the first time a basis for detailed temporal and spatial analysis, with the potential to revolutionize our understanding of many clinically important systems. However, while advances continue to be made in areas such as PCR amplification for NGS, sequencing protocols, and data analysis, in many cases the quality of the data generated is undermined by a failure to address fundamental aspects of experimental design. While little is added in terms of time or cost by the analysis of repeat samples, the exclusion of DNA from dead bacterial cells and the extracellular matrix, the use of efficient nucleic acid extraction methodologies, and the implementation of safeguards to minimize the introduction of contaminating nucleic acids, such considerations are essential in achieving an accurate representation of the system being studied. In this review, the chronic bacterial infections that characterize lower respiratory tract infections in cystic fibrosis patients are used as an example system to examine the implications of a failure to address these issues when designing NGS-based analysis of human-associated microbiota. Further, ways in which the impact of these factors can be minimized are discussed.     

Effects of GC Bias in Next-Generation-Sequencing Data on De Novo Genome Assembly

Next-generation-sequencing (NGS) has revolutionized the field of genome assembly because of its much higher data throughput and much lower cost compared with traditional Sanger sequencing. However, NGS poses new computational challenges to de novo genome assembly. Among the challenges, GC bias in NGS data is known to aggravate genome assembly. However, it is not clear to what extent GC bias affects genome assembly in general. In this work, we conduct a systematic analysis on the effects of GC bias on genome assembly. Our analyses reveal that GC bias only lowers assembly completeness when the degree of GC bias is above a threshold. At a strong GC bias, the assembly fragmentation due to GC bias can be explained by the low coverage of reads in the GC-poor or GC-rich regions of a genome. This effect is observed for all the assemblers under study. Increasing the total amount of NGS data thus rescues the assembly fragmentation because of GC bias. However, the amount of data needed for a full rescue depends on the distribution of GC contents. Both low and high coverage depths due to GC bias lower the accuracy of assembly. These pieces of information provide guidance toward a better de novo genome assembly in the presence of GC bias.     

Genome complexity of harmful microalgae

During the past decade, next generation sequencing (NGS) technologies have provided new insights into the diversity, dynamics, and metabolic pathways of natural microbial communities. But, these new techniques face challenges related to the genome size and level of genome complexity of the species under investigation. Moreover, the coverage depth and the short-read length achieved by NGS based approaches also represent a major challenge for assembly. These factors could limit the use of these high-throughput sequencing methods for species lacking a reference genome and characterized by a high level of complexity. In the present work, the evolutionary history, mainly consisting of gene transfer events from bacteria and unicellular eukaryotes to microalgae, including harmful species, is discussed and reviewed as it relates to NGS application in microbial communities, with a particular focus on harmful algal bloom species and dinoflagellates. In the context of genetic population studies, genotyping-by-sequencing (GBS), an NGS based approach, could be used for the discovery and analysis of single nucleotide polymorphisms (SNPs). The NGS technologies are still relatively new and require further improvement. Specifically, there is a need to develop and standardize tools and approaches to handle large data sets, which have to be used for the majority of HAB species characterized by evolutionary highly dynamic genomes.     

A Microfluidic DNA Library Preparation Platform for Next-Generation Sequencing

Next-generation sequencing (NGS) is emerging as a powerful tool for elucidating genetic information for a wide range of applications. Unfortunately, the surging popularity of NGS has not yet been accompanied by an improvement in automated techniques for preparing formatted sequencing libraries. To address this challenge, we have developed a prototype microfluidic system for preparing sequencer-ready DNA libraries for analysis by Illumina sequencing. Our system combines droplet-based digital microfluidic (DMF) sample handling with peripheral modules to create a fully-integrated, sample-in library-out platform. In this report, we use our automated system to prepare NGS libraries from samples of human and bacterial genomic DNA. E. coli libraries prepared on-device from 5 ng of total DNA yielded excellent sequence coverage over the entire bacterial genome, with >99% alignment to the reference genome, even genome coverage, and good quality scores. Furthermore, we produced a de novo assembly on a previously unsequenced multi-drug resistant Klebsiella pneumoniae strain BAA-2146 (KpnNDM). The new method described here is fast, robust, scalable, and automated. Our device for library preparation will assist in the integration of NGS technology into a wide variety of laboratories, including small research laboratories and clinical laboratories.     

First insights into the metagenome of Egyptian mummies using next-generation sequencing

We applied, for the first time, next-generation sequencing (NGS) technology on Egyptian mummies. Seven NGS datasets obtained from five randomly selected Third Intermediate to Graeco-Roman Egyptian mummies (806 BC–124AD) and two unearthed pre-contact Bolivian lowland skeletons were generated and characterised. The datasets were contrasted to three recently published NGS datasets obtained from cold-climate regions, i.e. the Saqqaq, the Denisova hominid and the Alpine Iceman. Analysis was done using one million reads of each newly generated or published dataset. Blastn and megablast results were analysed using MEGAN software. Distinct NGS results were replicated by specific and sensitive polymerase chain reaction (PCR) protocols in ancient DNA dedicated laboratories. Here, we provide unambiguous identification of authentic DNA in Egyptian mummies. The NGS datasets showed variable contents of endogenous DNA harboured in tissues. Three of five mummies displayed a human DNA proportion comparable to the human read count of the Saqqaq permafrost-preserved specimen. Furthermore, a metagenomic signature unique to mummies was displayed. By applying a “bacterial fingerprint”, discrimination among mummies and other remains from warm areas outside Egypt was possible. Due to the absence of an adequate environment monitoring, a bacterial bloom was identified when analysing different biopsies from the same mummies taken after a lapse of time of 1.5 years. Plant kingdom representation in all mummy datasets was unique and could be partially associated with their use in embalming materials. Finally, NGS data showed the presence of Plasmodium falciparum and Toxoplasma gondii DNA sequences, indicating malaria and toxoplasmosis in these mummies. We demonstrate that endogenous ancient DNA can be extracted from mummies and serve as a proper template for the NGS technique, thus, opening new pathways of investigation for future genome sequencing of ancient Egyptian individuals.     

Comparison of Hepatocellular Carcinoma miRNA Expression Profiling as Evaluated by Next Generation Sequencing and Microarray

MicroRNA (miRNA) expression profiling has proven useful in diagnosing and understanding the development and progression of several diseases. Microarray is the standard method for analyzing miRNA expression profiles; however, it has several disadvantages, including its limited detection of miRNAs. In recent years, advances in genome sequencing have led to the development of next-generation sequencing (NGS) technologies, which significantly advance genome sequencing speed and discovery. In this study, we compared the expression profiles obtained by next generation sequencing (NGS) with the profiles created using microarray to assess if NGS could produce a more accurate and complete miRNA profile. Total RNA from 14 hepatocellular carcinoma tumors (HCC) and 6 matched non-tumor control tissues were sequenced with Illumina MiSeq 50-bp single-end reads. Micro RNA expression profiles were estimated using miRDeep2 software. As a comparison, miRNA expression profiles for 11 out of 14 HCCs were also established by microarray (Agilent human microRNA microarray). The average total sequencing exceeded 2.2 million reads per sample and of those reads, approximately 57% mapped to the human genome. The average correlation for miRNA expression between microarray and NGS and subtraction were 0.613 and 0.587, respectively, while miRNA expression between technical replicates was 0.976. The diagnostic accuracy of HCC, p-value, and AUC were 90.0%, 7.22×10⁻⁴, and 0.92, respectively. In summary, NGS created an miRNA expression profile that was reproducible and comparable to that produced by microarray. Moreover, NGS discovered novel miRNAs that were otherwise undetectable by microarray. We believe that miRNA expression profiling by NGS can be a useful diagnostic tool applicable to multiple fields of medicine.     

Sequence deeper without sequencing more: Bayesian resolution of ambiguously mapped reads

Next-generation sequencing (NGS) has transformed molecular biology and contributed to many seminal insights into genomic regulation and function. Apart from whole-genome sequencing, an NGS workflow involves alignment of the sequencing reads to the genome of study, after which the resulting alignments can be used for downstream analyses. However, alignment is complicated by the repetitive sequences; many reads align to more than one genomic locus, with 15–30% of the genome not being uniquely mappable by short-read NGS. This problem is typically addressed by discarding reads that do not uniquely map to the genome, but this practice can lead to systematic distortion of the data. Previous studies that developed methods for handling ambiguously mapped reads were often of limited applicability or were computationally intensive, hindering their broader usage. In this work, we present SmartMap: an algorithm that augments industry-standard aligners to enable usage of ambiguously mapped reads by assigning weights to each alignment with Bayesian analysis of the read distribution and alignment quality. SmartMap is computationally efficient, utilizing far fewer weighting iterations than previously thought necessary to process alignments and, as such, analyzing more than a billion alignments of NGS reads in approximately one hour on a desktop PC. By applying SmartMap to peak-type NGS data, including MNase-seq, ChIP-seq, and ATAC-seq in three organisms, we can increase read depth by up to 53% and increase the mapped proportion of the genome by up to 18% compared to analyses utilizing only uniquely mapped reads. We further show that SmartMap enables the analysis of more than 140,000 repetitive elements that could not be analyzed by traditional ChIP-seq workflows, and we utilize this method to gain insight into the epigenetic regulation of different classes of repetitive elements. These data emphasize both the dangers of discarding ambiguously mapped reads and their power for driving biological discovery.