阶段特异表达的胚胎抗原

本文介绍了阶段特异性胚胎抗原(stage specific embryonic antigen,SSEA)的发现、化学结构和在胚胎、成熟组织中的分布规律;SSEA通过参与细胞间的信息传递、细胞识别与粘附等过程在动物胚胎发育、组织分化、基因调控及肿瘤的发生、转移等方面发挥重要作用;SSEA作为细胞表面标志,在肿瘤患者确诊、预后监测及胚胎干细胞的分离纯化、鉴定等研究领域的重要应用价值;探讨了SSEA-1合成的关键酶——岩藻糖基转移酶基因表达与调控的研究进展。     

转基因植物中载体骨架序列的安全性隐患及解决方案

载体骨架序列等非目的基因外源DNA片段整合入植物染色体中有可能引发的安全性问题已成为近年来植物基因工程研究的热点之一。总结了载体骨架序列整合进植物染色体的现象、由此引发的安全性隐患和机理 ,以及解决该问题的研究思路和方法 ,并着重介绍了采用基本元件转化植物的研究进展。     

利用单克隆抗体可鉴定不同初级感觉神经元

背根神经节细胞具有将外周各种感觉信息传入脊髓的作用,不同信息通过不同的传入神经进入脊髓背角的不同区域。尽管这些区域的发生和发展还未有明确的报道,但目前认为,背根神经节和脊髓背角神经元表面分子之间的关系很可能和背角突触连结的发生有关,所以,通过表面抗原的识别有可能区别不同功能的感觉传入神经元。J.Dodd等用特定发育阶段的胚胎抗原(SSEA)制成单克隆抗体,鉴定SSEA在大鼠神经系统的分布,并确定了SSEA和初级感觉神经元的关系。首先用免疫荧光法发现部分初级传入神经元中有SSEA_3、SSEA_4免疫反应样物质,主要位于胞浆中,     

基因组规模代谢网络模型构建及其应用

微生物制造产业的发展迫切需要进一步提高认识、设计和改造微生物细胞代谢的能力,以推动工业生物技术快速发展。随着微生物全基因组序列等高通量数据的不断积聚和生物信息学策略的持续涌现,使全局性、系统化地解析、设计、调控微生物生理代谢功能成为可能。而基于基因组序列注释和详细生化信息整合的基因组规模代谢网络模型(GSMM)构建为全局理解和理性调控微生物生理代谢功能提供了最佳平台。以下在详述GSMM的应用基础上,描述了如何构建一个高精确度的GSMM,并展望了未来的发展方向。     

蛋白质基因组学：运用蛋白质组技术注释基因组

随着高通量DNA测序技术的飞速发展,越来越多的物种完成了基因组测序．定位编码基因、确定编码基因结构是基因组注释的基本任务,然而以往的基因组注释方法主要依赖于DNA及RNA序列信息．为了更加精确地解读完成测序的基因组,我们需要整合多种类型的组学数据进行基因组注释．近年来,基于串联质谱技术的蛋白质组学已经发展成熟,实现了对蛋白质组的高覆盖,使得利用串联质谱数据进行基因组注释成为可能．串联质谱数据一方面可以对已注释的基因进行表达验证,另一方面还可以校正原注释基因,进而发现新基因,实现对基因组序列的重新注释．这正是当前进展较快的蛋白质基因组学的研究内容．利用该方法系统地注释已完成测序的基因组已成为解读基因组的一个重要补充．本文综述了蛋白质基因组学的主要研究内容和研究方法,并展望了该研究方向未来的发展．     

应用反向PCR克隆慢病毒介导的转基因小鼠整合位点序列

目的：为分析慢病毒介导的转基因小鼠中外源基因整合位点的信息,应用反向PCR克隆整合位点序列。方法：小鼠基因组总DNA酶解和自连接后,针对慢病毒载体的特点在LTR附近设计一组特异的PCR引物,优化半巢式PCR的各种参数,提高整合位点序列克隆的效率。结果：克隆了分别携带绿色荧光蛋白（GFP）和转铁蛋白（TF）基因的慢病毒介导的转基因小鼠家系7只小鼠中10个外源基因整合位点序列。结论：本方法可用于慢病毒介导的转基因小鼠整合位点序列的克隆,为分析整合位点与外源基因表达之间的关系等提供了科学依据。     

基因组二代测序数据的自动化分析流程

二代测序技术的发展对测序数据的处理分析提出了很高的要求。目前二代测序数据分析软件很多, 但是绝大多数软件仅能完成单一的分析功能(例如：仅进行序列比对或变异读取或功能注释等), 如何能正确高效地选择整合这些软件已成为迫切需求。文章设计了一套基于perl语言和SGE资源管理的自动化处理流程来分析Illumina平台基因组测序数据。该流程以测序原始序列数据作为输入, 调用业界标准的数据处理软件(如：BWA, Samtools, GATK, ANNOVAR等), 最终生成带有相应功能注释、便于研究者进一步分析的变异位点列表。该流程通过自动化并行脚本控制流程的高效运行, 一站式输出分析结果和报告, 简化了数据分析过程中的人工操作, 大大提高了运行效率。用户只需填写配置文件或使用图形界面输入即可完成全部操作。该工作为广大研究者分析二代测序数据提供了便利的途径。     

HIV整合位点的生物信息学分析

已有研究证明,HIV整合位点的选择,与宿主基因组功能和染色体结构特性之间存在着紧密的联系,但是具体的选择机制还不明确。使用聚类分析、特征提取、分类分析等生物信息学方法,对HIV整合位点序列进行分析和研究,挖掘HIV整合位点序列之间的关系,探索HIV整合位点的选择规律。通过实验和计算,从HIV整合位点集合中提取出了含有6个特征向量的向量集,该向量集与大部分整合位点的特征向量具有较高的相关性,从而提示了HIV整合位点选择中的规律性,即符合向量集的宿主DNA序列可为HIV的整合位点。研究结果为进一步揭示HIV整合位点的选择机制提供了可供参考的依据。     

GoPipe: 批量序列的Gene Ontology 注释和统计分析

随着后基因组时代的到来,批量的测序,特别是 EST 的测序,逐渐成为普通实验室的日常工作 . 这些新的序列往往需要进行批量的 Gene Ontology (GO) 的注释及随后的统计分析 . 但是目前除了 Goblet 以外,并没有软件适合对未知序列进行批量的 GO 注释,而 GoBlet 因为具有上载量的限制,以及仅仅利用 BLAST 作为预测工具,所以仍有许多不足之处 . 开发了一个软件包 GoPipe ,通过整合 BLAST 和 InterProScan 的结果来进行序列注释,并提供了进一步作统计比较的工具 . 主程序接收任意个 BLAST 和 InterProScan 的结果文件,并依次进行文本分析、数据整合、去除冗余、统计分析和显示等工作 . 还提供了统计的工具来比较不同输入对 GO 的分布来挖掘生物学意义 . 另外,在交集工作模式下,程序取 InterProScan 和 BLAST 结果的交集, 在测试数据集中,其精确度达到 99.1% ,这大大超过了 InterProScan 本身对 GO 预测的精确度,而敏感度只是稍微下降 . 较高的精确度、较快的速度和较大的灵活性使它成为对未知序列进行批量 Gene Ontology 注释的理想的工具 . 上述软件包可以在网站 (http://gopipe.fishgenome.org/ ) 免费获得或者与作者联系获取 .     

植物中转基因的整合机制

转基因在植物基因组中的整合分两步:在整合前阶段,转化的完整质粒及转基因片段经重组连接形成转基因串联子(transgenearray),其中不含任何植物基因组序列,连接反应由植物细胞本身的酶催化,仅依赖于游离的DNA末端,CaMV35S启动子和TDNA边界序列中的特定序列可能充当重组热点;在整合阶段,转基因DNA通过微同源介导的异常重组整合到植物基因组中,最初的整合位点作为整合热点,引导随后的转基因分子在该位点附近整合,不同转基因位点可被1～10kb植物DNA隔开,形成转基因簇(transgenecluster)。     

Hypotheses for testing deviations from random integration: evidence for nonrandom retroviral integration

The use of a recently developed in vitro model for retroviral integration provides a means of statistically testing hypotheses concerning the distribution of integration sites and hypotheses about the sequence of proviral orientations. In this study, three null hypotheses are formulated and applied to previously published data. Statistical analyses of these data suggest that the distribution of integration sites may not be uniform, and the sequence of proviral orientations is not random. On the basis of these results and the observed clustering of orientations, it was postulated that if a DNA sequence was involved in nonrandom proviral integration, that sequence would be found in the regions where the orientations change direction with respect to the target DNA ("I" regions). Computer analyses for homologous and complementary DNA sequences were performed on all possible pairs of identifiable "I" regions. A common sequence (at least 8 bp in size) was found in three out of four regions and that sequence was absent elsewhere in the target DNA. A model, with features of recombination reminiscent of chi sequences in bacteria, is proposed that may account for these results.     

Large-scale prediction of drug-target relationships

The rapidly increasing amount of publicly available knowledge in biology and chemistry enables scientists to revisit many open problems by the systematic integration and analysis of heterogeneous novel data. The integration of relevant data does not only allow analyses at the network level, but also provides a more global view on drug-target relations. Here we review recent attempts to apply large-scale computational analyses to predict novel interactions of drugs and targets from molecular and cellular features. In this context, we quantify the family-dependent probability of two proteins to bind the same ligand as function of their sequence similarity. We finally discuss how phenotypic data could help to expand our understanding of the complex mechanisms of drug action.     

Information Integration in Molecular Bioscience

Integrating information in the molecular biosciences involves more than the cross-referencing of sequences or structures. Experimental protocols, results of computational analyses, annotations and links to relevant literature form integral parts of this information, and impart meaning to sequence or structure. In this review, we examine some existing approaches to integrating information in the molecular biosciences. We consider not only technical issues concerning the integration of heterogeneous data sources and the corresponding semantic implications, but also the integration of analytical results. Within the broad range of strategies for integration of data and information, we distinguish between platforms and developments. We discuss two current platforms and six current developments, and identify what we believe to be their strengths and limitations. We identify key unsolved problems in integrating information in the molecular biosciences, and discuss possible strategies for addressing them including semantic integration using ontologies, XML as a data model, and graphical user interfaces as integrative environments.     

Signal sequences influence membrane integration of the prion protein

Biosynthesis of the prion protein at the endoplasmic reticulum generates multiple topological forms. The topology of an individual chain is determined first by the localization of the N terminus and then by potential integration of the transmembrane domain into the lipid bilayer. Here, we provide the first evidence that signal sequences affect the latter of these events by demonstrating that some but not other signal sequences and signal sequence mutations result in significant increases in the fraction of prion protein nascent chains that integrate into the lipid bilayer. Through analysis of the prolactin signal sequence, an especially poor integration effector, we find that the N terminal and hydrophobic regions of the signal sequence affect integration most significantly. Mutations in either region result in a considerable increase in the number of chains that integrate. The effect of the signal sequence cannot be attributed to timing of signal cleavage or the state of the ribosome membrane junction, parameters previously found to affect protein biogenesis. We also present evidence that signal sequences that are poor integration effectors can promote integration under experimental conditions that allow the nascent chain more time to integrate. These findings reveal a previously unappreciated relationship between signal sequences and transmembrane integration.     

Targeted assembly of short sequence reads

As next-generation sequence (NGS) production continues to increase, analysis is becoming a significant bottleneck. However, in situations where information is required only for specific sequence variants, it is not necessary to assemble or align whole genome data sets in their entirety. Rather, NGS data sets can be mined for the presence of sequence variants of interest by localized assembly, which is a faster, easier, and more accurate approach. We present TASR, a streamlined assembler that interrogates very large NGS data sets for the presence of specific variants by only considering reads within the sequence space of input target sequences provided by the user. The NGS data set is searched for reads with an exact match to all possible short words within the target sequence, and these reads are then assembled stringently to generate a consensus of the target and flanking sequence. Typically, variants of a particular locus are provided as different target sequences, and the presence of the variant in the data set being interrogated is revealed by a successful assembly outcome. However, TASR can also be used to find unknown sequences that flank a given target. We demonstrate that TASR has utility in finding or confirming genomic mutations, polymorphisms, fusions and integration events. Targeted assembly is a powerful method for interrogating large data sets for the presence of sequence variants of interest. TASR is a fast, flexible and easy to use tool for targeted assembly.     

VISA - Vector Integration Site Analysis server: a web-based server to rapidly identify retroviral integration sites from next-generation sequencing

Background

Analyzing the integration profile of retroviral vectors is a vital step in determining their potential genotoxic effects and developing safer vectors for therapeutic use. Identifying retroviral vector integration sites is also important for retroviral mutagenesis screens.

Results

We developed VISA, a vector integration site analysis server, to analyze next-generation sequencing data for retroviral vector integration sites. Sequence reads that contain a provirus are mapped to the human genome, sequence reads that cannot be localized to a unique location in the genome are filtered out, and then unique retroviral vector integration sites are determined based on the alignment scores of the remaining sequence reads.

Conclusions

VISA offers a simple web interface to upload sequence files and results are returned in a concise tabular format to allow rapid analysis of retroviral vector integration sites.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0653-6) contains supplementary material, which is available to authorized users.     

The palindromic LTR-LTR junction of Moloney murine leukemia virus is not an efficient substrate for proviral integration.

We generated viral constructs to test the hypothesis that the major substrate on retroviral DNA that is utilized for proviral DNA integration is the palindromic sequence, termed the LTR-LTR junction, normally present in circular molecules formed by joining the two termini of linear proviral DNA. Recombinant viral genomes were built which carried a selectable marker and an extra copy of the LTR-LTR junction from a cloned circular provirus. The junction sequence in each case was positioned such that its use during integration would lead to an easily detected, aberrantly integrated proviral DNA. Analysis of DNA from cells infected with the virus constructs showed that the introduced junction sequence is used at least 1,000-fold less efficiently than the natural sequences at the ends of the genome. This suggests that a linear or more exotic DNA intermediate is most likely the true precursor for the integration reaction.     

PCR检定OSM cDNA转染细胞中基因组整合与转录

用PCR和RT-PCR方法对人OSM cDNA转染的小鼠黑色素瘤细胞进行基因组整合和mRNA转录的检定.基因组整合检定时,采用与调控序列和cDNA序列相对应的上、下游引物,以连续的转录单位进行扩增,能够更准确地反映整合与表达的关系;mRNA检定时,采用与cDNA序列和质粒克隆位点与加polyA信号之间序列相对应的上、下游引物,可以区分宿主细胞中内源性与外源性基因的转录.     

MetaFam: a unified classification of protein families. II. Schema and query capabilities

MOTIVATION: Protein sequence and family data is accumulating at such a rapid rate that state-of-the-art databases and interface tools are required to aid curators with their classifications. We have designed such a system, MetaFam, to facilitate the comparison and integration of public protein sequence and family data. This paper presents the global schema, integration issues, and query capabilities of MetaFam. RESULTS: MetaFam is an integrated data warehouse of information about protein families and their sequences. This data has been collected into a consistent global schema, and stored in an Oracle relational database. The warehouse implementation allows for quick removal of outdated data sets. In addition to the relational implementation of the primary schema, we have developed several derived tables that enable efficient access from data visualization and exploration tools. Through a series of straightforward SQL queries, we demonstrate the usefulness of this data warehouse for comparing protein family classifications and for functional assignment of new sequences.