基于第二代测序技术的细菌基因组与转录组研究策略简介

随着基于第二代测序技术的细菌基因组与转录组研究越来越广泛,选择合适的研究策略变得越来越重要.就基于第二代测序技术的细菌基因组和转录组研究策略进行综述,并简要介绍细菌基因组和转录组研究中的机遇和挑战.综述细菌基因组与转录组研究的常规方法及步骤,并简要地介绍存在的问题.细菌基因组和转录组研究策略为大多数细菌的研究提供了一个...     

真菌基因组de novo测序组装的方法与实践

真菌基因组较其他真核生物基因组结构简单,长度短,易于测序、组装与注释,因此真菌基因组是研究真核生物基因组的模型。为研究真菌基因组组装策略,本研究基于Illumina HiSeq测序平台对烟曲霉菌株An16007基因组测序,分别使用5种de novo组装软件ABySS、SOAP-denovo、Velvet、MaSuRCA和IDBA-UD组装基因组,然后通过Augustus软件进行基因预测,BUSCO软件评估组装结果。研究发现,5种组装软件对基因组组装结果不同,ABySS组装的基因组较其他4种组装软件具有更高的完整性和准确性,且预测的基因数量较高,因此,ABySS更适合本研究基因组的组装。本研究提供了真菌de novo测序、组装及组装质量评估的技术流程,为基因组<100 Mb的真菌或其他生物基因组的研究提供参考。     

水稻基因组测序的研究进展

水稻是最重要的粮食作物之一,世界上大约有一半的人口以水稻为主要粮食。作为基因组研究的模式植物,水稻基因组的测序工作已在世界范围内展开。此项研究工作不仅能破译水稻全基因组序列,还将有助于了解其他禾本科植物的基因组信息。本对水稻基因组测序工作进展作一综述。     

复杂基因组测序技术研究进展

复杂基因组指的是无法使用常规测序和组装手段直接解析的一类基因组,通常指包含高比例重复序列、高杂合度、极端GC含量、存在难消除异源DNA污染的基因组。为了解决复杂基因组的测序和组装问题,需要分别从基因组测序实验方法、测序技术平台、组装算法与策略3个方面进行深入研究。本文详细介绍了复杂基因组测序组装相关的现有技术与方法,并结合复杂基因组经典实例介绍了复杂基因组测序的技术解决途径和发展历程,可为制订合适的复杂基因组测序策略提供参考。     

微生物基因组的生物信息学研究平台的建立

随着人类基因组计划及其它测序工作顺利进行,人们已经得到了大量的基因序列。如何阐明这些序列的功能和意义,是功能基因组学的主要任务,生物信息学和比较基因组学为加速这一进程提供了有利的工具,该研究建立了对已经完成全基因组测序和部分测序的25种细菌的基因组的生物信息学研究平台,提供了WEB形式的服务（http://202.116.74.108)。25种细菌的全基因组蛋白质序列可以在NCBI的ftp://ftp.ncbi.nlm.nih.gov/genbank/genomes/bacteria下载,该系统可以按照基因序列号,功能和种属名查询基因序列。根据美国国家信息中心（NCBI）的功能代码表对每个基因进行了自动和手工分类,并可查询分类情况,在此基因上建立了几种亲缘关系相近的种属的同源基因相互注释功能的应用。     

高等植物基因组测序回顾与展望

全基因组序列测定为揭示植物重要性状形成的分子和遗传机制提供了强大工具,基因组学研究正开始指引着农作物新品种培育向定向化和精确化转变.在新一代测序技术的带动下,植物全基因组测序的热潮已经到来.对迄今开展的高等植物基因组测序工作进行简要回顾,并对未来的研究热点进行展望.     

全基因组测序与生物信息学分析在细菌耐药性研究中的应用

随着耐药细菌的大量出现及广泛传播,细菌耐药性成为全球备受关注的问题。耐药细菌的特征如耐药基因、毒力因子、质粒分型等以及不同菌株间亲缘关系对于细菌耐药性流行病学及分子生物学的研究有着十分重要的意义。但是传统的技术手段如聚合酶链式反应(Polymerase chain reaction,PCR)和脉冲场凝胶电泳(Pulsed field gel electrophoresis,PFGE)等得到的结果不够全面且精确度低,对于现有的研究存在很大的局限性。全基因组测序技术(Whole genome sequencing,WGS)和生物信息学分析(Bioinformatics analysis)由于能够快速详尽地得到耐药细菌的特征,也能更加精细地判断不同菌株间的进化关系,逐渐成为更加有效的技术手段,为耐药性研究提供了有效的帮助。因此,文中系统地介绍全基因组测序分析流程中的各个步骤,主要包括文库构建、平台测序以及后期数据分析三大方面的不同方法和其相应的特点,期望相关研究人员对此能够有更全面的了解,并得到一定的帮助。     

癌症基因组测序方案制定的研究进展

癌症的基因组测序对于癌症的预防、诊断、预后、治疗以及基础生物学研究都有巨大的潜在的应用价值,正是由于其方向广泛,所以基因组测序的方案制定对于实现特定的研究目标,就显得尤为重要。同时,了解了基因组测序方案制定的规则,也有助于评估如今快速增长的发表文献的正确性和重要性。主要论述高通量测序技术在癌症基因组测序中的实际应用,并讨论癌症基因组测序在方案设计和方法学上如何调整,才能更好地实现特定的研究目的。     

植物基因组测序的研究进展

近年来,随着测序技术的不断发展,基因组测序技术渐趋成熟并在动物和植物基因组上获得了越来越多的成功,大量植物的基因组的草图和精细图不断地被公布出来。比较和分析了三代测序技术各自的特点,对测序前的准备、基因组组装、注释和比较基因组学等方面的研究进展进行了详细的评述,阐明了植物基因组研究的特点和难点。通过植物的全基因组测序,研究者不仅可以获得该植物基因组和重要功能基因的序列信息,为从分子水平研究植物的分子进化、基因组成和基因调控等提供了一定的依据,而且还对即将测序的植物基因组研究具有重要的借鉴意义。     

木本植物全基因组测序研究进展

近年来,植物全基因组测序的结果正如雨后春笋般涌现,木本植物全基因组测序也在紧锣密鼓地展开。但由于木本植物通常基因组较大,基因组结构较为复杂,在测序、测序后的组装、注释、功能分析等均存在较大的困难。在基因组测序分析的经费预算方面也存在着较大的压力。因此,有必要对这方面的研究进展及其存在问题进行分析比较,以提高林木全基因组研究方面的效率。文章在比较分析已经发展起来的3代基因测序技术(Sanger测序法、合成测序法和单分子测序法)的基础上,选择4种已经公布的木本植物(杨树、葡萄、番木瓜、苹果),从全基因组测序的研究背景、测序结果及应用的研究进展和存在问题等方面进行了述评,对未来要开展的木本植物全基因组测序前的准备工作(材料选择、遗传图谱和连锁图谱的构建、测序技术的选择),全基因组测序结果的生物信息学分析和应用进行了讨论。     

Identification of de novo germline mutations and causal genes for sporadic diseases using trio‐based whole‐exome/genome sequencing

Whole‐genome or whole‐exome sequencing (WGS/WES) of the affected proband together with normal parents (trio) is commonly adopted to identify de novo germline mutations (DNMs) underlying sporadic cases of various genetic disorders. However, our current knowledge of the occurrence and functional effects of DNMs remains limited and accurately identifying the disease‐causing DNM from a group of irrelevant DNMs is complicated. Herein, we provide a general‐purpose discussion of important issues related to pathogenic gene identification based on trio‐based WGS/WES data. Specifically, the relevance of DNMs to human sporadic diseases, current knowledge of DNM biogenesis mechanisms, and common strategies or software tools used for DNM detection are reviewed, followed by a discussion of pathogenic gene prioritization. In addition, several key factors that may affect DNM identification accuracy and causal gene prioritization are reviewed. Based on recent major advances, this review both sheds light on how trio‐based WGS/WES technologies can play a significant role in the identification of DNMs and causal genes for sporadic diseases, and also discusses existing challenges.     

On peptide de novo sequencing: a new approach.

A procedure is presented for the automatic determination of the amino acid sequence of peptides by processing data obtained from mass spectrometry analysis. This is a basic and relevant problem in the field of proteomics. Furthermore, it has an even higher conceptual and applicative interest in peptide research, as well as in other connected fields. The analysis does not rely on known protein databases, but on the computation of all amino acid sequences compatible with the given spectral data. By formulating a mathematical model for such combinatorial problems, the structural limitations of known methods are overcome, and efficient solution algorithms can be developed. The results are very encouraging both from the accuracy and computational points of view.     

Taxonomy becoming a driving force in genome sequencing projects

We studied the possible impact of genomic projects by comparing the number of published articles before and after the completion of the project. We found that for most species, there is no significant change in the number of citations. Also our study remarks the growing importance of taxonomy as main motivation for the sequencing of genomes.     

Island length distribution in genome sequencing

 We consider the general problem of constructing a physical map of a genome by welding islands of overlapping clones. Both distribution of clone length and non-uniform probability of overlap detection are taken into account, the latter restricted to the Markov case in which only the location of the end of the developing island is required. Exact results for the distribution of island length are obtained in the special cases of fixed clone length or rigid overlap criterion, and mean and variance for the general situation. Determination of ocean length distribution permits island number and contig number distributions to be found as well. Received: 21 December 1998     

C-terminal de novo sequencing of peptides using oxazolone-based derivatization with bromine signature

Due to almost identical chemical properties of C-terminal and side-chain carboxylic groups, selective C-terminal derivatization has been difficult. Although oxazolone-based C-terminal derivatization is the only selective C-terminal modification available, it has not been used widely because of its low derivatization efficiency. In this paper, an improved oxazolone chemistry for incorporation of Br signature to C-terminus is reported. MS/MS analysis of the brominated peptides led to a series of y ions with Br signature, facilitating de novo C-terminal sequencing.     

蛋白质全新设计的现状和展望

对蛋白质全新设计的方法、设计原则、迄今为止取得的成就和存在的问题及目前面临的困难进行了综述.     

RADProc: A computationally efficient de novo locus assembler for population studies using RADseq data

Restriction site‐associated DNA sequencing (RADseq) is a powerful tool for genotyping of individuals, but the identification of loci and assignment of sequence reads is a crucial and often challenging step. The optimal parameter settings for a given de novo RADseq assembly vary between data sets and can be difficult and computationally expensive to determine. Here, we introduce RADProc, a software package that uses a graph data structure to represent all sequence reads and their similarity relationships. Storing sequence–comparison results in a graph eliminates unnecessary and redundant sequence similarity calculations. De novo locus formation for a given parameter set can be performed on the precomputed graph, making parameter sweeps far more efficient. RADProc also uses a clustering approach for faster nucleotide‐distance calculation. The performance of RADProc compares favourably with that of the widely used Stacks software. The run‐time comparisons between RADProc and Stacks for 32 different parameter settings using 20 green‐crab (Carcinus maenas) samples showed that RADProc took as little as 2 hr 40 min compared to 78 hr by Stacks, while 16 brown trout (Salmo trutta L.) samples were processed by RADProc and Stacks in 23 and 263 hr, respectively. Comparisons of the de novo loci formed, and catalog built using both the methods demonstrate that the improvement in processing speeds achieved by RADProc does not affect much the actual loci formed and the results of downstream analyses based on those loci.     

Using Illumina next generation sequencing technologies to sequence multigene families in de novo species

The advent of Next Generation Sequencing Technology (NGST) has revolutionized molecular biology research, allowing for rapid gene/genome sequencing from a multitude of diverse species. As high throughput sequencing becomes more accessible, more efficient workflows must be developed to deal with the amounts of data produced and better assemble the genomes of de novo lineages. We combine traditional laboratory methods with Illumina NGST to amplify and sequence the largest mammalian multigene family, the Olfactory Receptor gene family, for species with and without a reference genome. We develop novel assembly methods to annotate and filter these data, which can be utilized for any gene family or any species. We find no significant difference between the ratio of genes within their respective gene families of our data compared with available genomic data. Using simulated data we explore the limitations of short‐read sequence data and our assembly in recovering this gene family. We highlight the benefits and shortcomings of these methods. Compared with data generated from traditional polymerase chain reaction, cloning and Sanger sequencing methodologies, sequence data generated using our pipeline increases yield and sequencing efficiency without reducing the number of unique genes amplified. A cloning step is not required, therefore shortening data generation time. The novel downstream methodologies and workflows described provide a tool to be utilized by many fields of biology, to access and analyze the vast quantities of data generated. By combining laboratory and in silico methods, we provide a means of extracting genomic information for multigene families without complete genome sequencing.     

Algorithms for the de novo sequencing of peptides from tandem mass spectra

Proteomics is the study of proteins, their time- and location-dependent expression profiles, as well as their modifications and interactions. Mass spectrometry is useful to investigate many of the questions asked in proteomics. Database search methods are typically employed to identify proteins from complex mixtures. However, databases are not often available or, despite their availability, some sequences are not readily found therein. To overcome this problem, de novo sequencing can be used to directly assign a peptide sequence to a tandem mass spectrometry spectrum. Many algorithms have been proposed for de novo sequencing and a selection of them are detailed in this article. Although a standard accuracy measure has not been agreed upon in the field, relative algorithm performance is discussed. The current state of the de novo sequencing is assessed thereafter and, finally, examples are used to construct possible future perspectives of the field.