中华卵索线虫线粒体基因组多态性分析

为完善昆虫病原索科线虫线粒体基因组全序列数据库, 更系统地研究其基因组特征和系统演化规律, 进而为发挥该线虫生防潜力打下基础, 我们开展了中华卵索线虫Ovomermis sinensis线粒体全基因组的研究。该研究通过线粒体基因组滚环复制及酶切图谱, 揭示了中华卵索线虫线粒体基因组具有种内遗传多态性, 即群体中单体线虫具有独特的酶切条带, 且条带累加之和变化范围较大, 为16.5～24.5 kb。为进一步了解线粒体基因组多态性特征及产生的分子机制, 采用两步长PCR方法对2条代表性成虫线粒体基因组进行了测序及拼接, 得其全长分别为18 864和16 777 bp。对这2条序列的比对表明, 线粒体基因组中位于ND2和ND4之间的可变区域, 不仅基因排列顺序不同, 且存在ND3基因重复现象, 这是导致中华卵索线虫线粒体基因组呈现多态性的主要原因。通过对以上研究结果的分析及与GenBank中已有的6种索科线虫线粒体基因组序列进行比对, 概括出其线粒体基因组基本特点: ①线粒体基因排列顺序各不相同;②部分线虫线粒体基因存在重复现象, 且重复次数不同;③线粒体基因组大小存在很大差异。     

寄生于粘虫的卵索线虫属一新种——中华卵索线虫(线虫纲:索科)

本文报道从河南省驻马店地区和山东省临沂地区麦田内采集的粘虫幼虫的寄生线虫优势种卵索线虫属一新种,命名为中华卵索线虫,新种Ovomermis sinensis sp.nov.     

中华卵索线虫的体外培养

在研究中华卵索线虫的体外培养方法的同时,对其在不同培养基中的生长发育情况进行了观察。结果表明：以培养基TC－199加20％热灭活胎牛血清的培养效果较为理想,大多数线虫可存活3个月,最大虫体长55．1mm,宽204．13um,其发育程度大致与该种索线虫在宿主粘虫体内寄生8－9天的情况相近,培养期间观察到2次蜕皮;第一次蜕皮在卵内,第二次在培养6－8天之后,口针消失,虫体内滋养物体发育明显,尾部附器已经形成,没有观察到生殖原基的发育。     

中华卵索线虫雌雄成虫可溶性蛋白双向电泳分析

昆虫寄生线虫 (又称虫生线虫、昆虫病原线虫)是本世纪发展起来的一种有潜能的生物防治因子 ,它寄主范围广、能主动寻找寄主、对人畜及环境安全无毒。中华卵索线虫是昆虫寄生线虫的一种 ,由我国学者发现并命名的新种 (陈果等 ,1 9 91 ) ,具有广泛的寄主范围 ,可杀灭粘虫 (任慧芳等 ,1 989)、烟青虫、烟蚜 (侯茂林等 ,2 0 0 2 )及棉铃虫 (陈果 ,1 994)等危害十分严重的害虫 ,其寄生率等于宿主的死亡率。因此在生物防治手段日益突出的今天 ,中华卵索线虫无疑有着广泛的应用前景。然而 ,在线虫培养的过程中 ,无论是体内培养还是体外培养 ,我们发…     

五种索科线虫RAPD亲缘关系分析

采用RAPD技术构建了索科线虫4属5种的指纹图谱。从47个引物中筛选出12个稳定性好、多态性高的引物,共扩增出161条谱带,其中150条谱带具遗传多态性,占93·17%。所获片段长度大小为200~3200bp,单个引物扩增的条带数在11~16之间,平均为13·42条。采用RAPDistance软件及MEGA程序,计算Nei氏相似系数和遗传距离,建立UPGMA和NJ聚类图,两个聚类图拓扑结构相同,将5种索科线虫分为两大分支:同属于蚊幼寄生罗索属线虫的食蚊罗索线虫(Romanomermisculicivorax)与武昌罗索线虫(R.wuchangensis)亲缘关系最近,先聚在一起,再与同翅目(Homoptera)寄生长沙多索线虫(Agamermischang-shaensis)聚为一支;鳞翅目(Lepidoptera)寄生中华卵索线虫(Ovomermissinensis)和同翅目寄生两索属线虫(Amphimermissp·)亲缘关系较近,两者聚为一支。5种索线虫属内种间的遗传距离较小,食蚊罗索线虫与武昌罗索线虫之间遗传距离仅为0·1789;而属间遗传距离较大,在0·4471~0·5488之间。上述结果表明:RAPD技术可以应用于索科线虫亲缘关系的分析,能够反映出不同线虫间的遗传差距,从而成功地进行属、种的分类及进化问题研究。     

中华卵索线虫的性别分化分子机理研究进展

中华卵索线虫Ovomermis sinensis Chen et al.是一种宝贵的昆虫天敌资源,具有特殊的寄生期营养竞争压力决定其雌雄性别分化机制。本文重点概述了近年中华卵索线虫性别决定与分化、寄生期生理生化以及分子系统学研究等方面的进展,并对中华卵索线虫今后的研究方向提出了建议。     

索线虫寄生前期幼虫的分类研究

本文对六索属、罗索属和两索属3属6种索线虫的寄生前期幼虫进行了观察比较,对索线虫寄生前期幼虫作为索科线虫属、种鉴别的可能性、分类鉴别方法和主要鉴别特征值等问题作了初步研究。     

基因差异表达分析技术进展

比较了目前几种主要的基因差异表达分析技术并简要地归纳了各种基因差异表达分析方法的特点,重点介绍了经典的基因差异表达分析技术———差异显示技术及其改进与完善,最后根据差异显示技术在高等植物方面已取得的成就乐观地展现了该技术在园艺植物研究上的应用前景.     

基于SAFLP的我国常见索线虫科昆虫病原线虫亲缘关系分析

本研究建立并优化了索线虫科(Mermithidae)SAFLP体系,构建了我国常见索线虫科昆虫病原线虫6属11种/亚种的指纹图谱。采用EcoRⅠ和MseⅠ两种限制性内切酶单酶切,结果显示EcoRⅠ酶更适合作为索线虫科线虫SAFLP的内切酶。3个带有3个选择性碱基的EcoRⅠ引物进行扩增共得条带225个,片段大小为250～1 650 bp。通过NTsys-PC2.1软件计算了索线虫科6属11种/亚种的Nei-Li遗传距离(0.1980～034554)和相似系数,利用NTsys-PC2.1软件中的UPGMA方法构建其聚类图。索线虫科这6属11种/亚种从属级阶元可以分为两大类群：罗索属Romanomermis和八腱索属Octomyomermis聚为一支构成第一大类群;六索属Hexamermis与卵索属Ovomermis先聚在一起然后与多索属Agamermis聚在一起,再与两索属Amphimermis聚在一起构成第二大类群。在八腱索属和两索属中属内不同种/亚种间线虫采集地相距较近的其遗传距离较近。优化的索线虫科线虫SAFLP体系能够反映索线虫科线虫种属间的亲缘关系,并与形态学的研究结果基本相符,可以用于属种的分类和亲缘关系的研究。     

Selecting differentially expressed genes from microarray experiments

High throughput technologies, such as gene expression arrays and protein mass spectrometry, allow one to simultaneously evaluate thousands of potential biomarkers that could distinguish different tissue types. Of particular interest here is distinguishing between cancerous and normal organ tissues. We consider statistical methods to rank genes (or proteins) in regards to differential expression between tissues. Various statistical measures are considered, and we argue that two measures related to the Receiver Operating Characteristic Curve are particularly suitable for this purpose. We also propose that sampling variability in the gene rankings be quantified, and suggest using the "selection probability function," the probability distribution of rankings for each gene. This is estimated via the bootstrap. A real dataset, derived from gene expression arrays of 23 normal and 30 ovarian cancer tissues, is analyzed. Simulation studies are also used to assess the relative performance of different statistical gene ranking measures and our quantification of sampling variability. Our approach leads naturally to a procedure for sample-size calculations, appropriate for exploratory studies that seek to identify differentially expressed genes.     

Detecting multivariate differentially expressed genes

Background  

Gene expression is governed by complex networks, and differences in expression patterns between distinct biological conditions may therefore be complex and multivariate in nature. Yet, current statistical methods for detecting differential expression merely consider the univariate difference in expression level of each gene in isolation, thus potentially neglecting many genes of biological importance.     

Dolichol phosphate mannose synthase is differentially expressed in male and female worms of Schistosoma mansoni

The cDNA encoding the Schistosoma mansoni dolichol phosphate mannose synthase was completely sequenced, displaying the highest homology with Cricetulus griseus and Saccharomyces pombe genes. The Schistosome enzyme had a K(m) of 0.127 microM, a value that is within the range of those reported for several other species. Thin-layer chromatography of the radiolabelled schistosome lipid intermediate showed it was identical to dolichol-phosphate (C80-C105). Expression of dolichol phosphate mannose synthase of S. mansoni (SmDPMS) was analysed by Northern blot and quantified by semi-quantitative RT-PCR with cDNA from mature and immature male and female worms. Northern blot analysis revealed a single 1-kb band. Both approaches confirmed a higher level of expression in mature female worms, as compared to immature and male worms.     

In search of differentially expressed genes and proteins

A great challenge for modern cell biology is the successful examination of the co-expression of thousands of genes under physiological or pathological conditions and how the expression patterns define the different states of a single cell, tissue or a microorganism. Gene expression can be analyzed today on a large scale by advanced technical approaches for differential screening of proteins and mRNAs. The identification of differentially expressed mRNAs has been successfully applied to understand gene function and the underlying molecular mechanism(-s) of differentiation, development and disease state. Analysis of gene expression by the systematic mapping of thousands of proteins present in a cell or tissue can be achieved by the use of two-dimensional (2D) gel electrophoresis, quantitative computer image analysis, and protein identification techniques. In this article, we comment on some of these techniques and try to stress their advantages and drawbacks. We show how data from RNA/DNA mapping, sequence information from genome projects and protein pattern profiling can be linked with each other and annotated. These comprehensive approaches permit the study of differential gene and protein expressions in cells or tissues.     

Identifying differentially expressed genes from microarray experiments via statistic synthesis

MOTIVATION: A common objective of microarray experiments is the detection of differential gene expression between samples obtained under different conditions. The task of identifying differentially expressed genes consists of two aspects: ranking and selection. Numerous statistics have been proposed to rank genes in order of evidence for differential expression. However, no one statistic is universally optimal and there is seldom any basis or guidance that can direct toward a particular statistic of choice. RESULTS: Our new approach, which addresses both ranking and selection of differentially expressed genes, integrates differing statistics via a distance synthesis scheme. Using a set of (Affymetrix) spike-in datasets, in which differentially expressed genes are known, we demonstrate that our method compares favorably with the best individual statistics, while achieving robustness properties lacked by the individual statistics. We further evaluate performance on one other microarray study.     

差异表达基因的分离策略

生命活动的各个进程伴随着不同基因的选择性开启和关闭。如何有效地分离克隆各种差异表达的基因,成为分子生物学研究的一个努力方向,大量差异基因分离策略因之问世。本文扼要介绍了近年来发展的几种主要分离策略,并详细介绍一种新的差异基因分离方法--抑制差减杂交。