DNA拓扑异构酶Ⅱ的多态转换模型

DNA拓扑异构酶Ⅱ是一种分子马达,它利用ATP水解产生的化学能,切断一条双链DNA片段(G segment),并让另一条双链DNA片段(T segment)从缺口处通过.对DNA拓扑异构酶Ⅱ的工作循环研究将有助于阐明其工作机理.本文根据已有实验资料,利用主方程方法构建了DNA拓扑异构酶n状态转变的随机跃迁模型,求得系统...     

不同类型氨基酸网络参量与蛋白质折叠的关系

理论和实验研究表明,蛋白质天然拓扑结构对其折叠过程具有重要的影响．采用复杂网络的方法分析蛋白质天然结构的拓扑特征,并探索蛋白质结构特征与折叠速率之间的内在联系．分别构建了蛋白质氨基酸网络、疏水网、亲水网、亲水-疏水网以及相应的长程网络,研究了这些网络的匹配系数(assortativity coefficient)和聚集系数(clustering coefficient)的统计特性．结果表明,除了亲水-疏水网,上述各网络的匹配系数均为正值,并且氨基酸网和疏水网的匹配系数与折叠速率表现出明显的线性正相关,揭示了疏水残基间相互作用的协同性有助于蛋白质的快速折叠．同时,研究发现疏水网的聚集系数与折叠速率有明显的线性负相关关系,这表明疏水残基间三角结构(triangle construction)的形成不利于蛋白质快速折叠．还进一步构建了相应的长程网络,发现序列上间距较远的残基接触对的形成将使蛋白质折叠进程变慢．     

贵州3种车前草的随机扩增多态性DNA(RAPD)亲缘关系分析

利用随机扩增多态性DNA(RAPD)技术对贵州车前草的3个种进行了分析,建立了它们的指纹图谱.从60个随机引物中筛选出的9个引物共产生94条DNA片段,大小分布在0.1～0.2kb之间,其中71个条带具有遗传多态性,约占总数的75.53％.平均每个引物扩增的DNA带数为10.44条.应用NTSYSpc软件进行聚类,将聚类结果转化为3种车前草之间的遗传关系树形图.结果显示,车前和平车前首先聚类,其Dice相似性系数为0.76,在三者中它们的亲缘关系较近;而大车前与它们的遗传相似性系数为0.56,亲缘关系较远.     

DNA标记技术在螨类系统学研究中的应用

长期以来,螨类主要依靠其形态特征进行系统学研究。DNA标记是指能反映生物个体或物种间基因组中某种差异特征的DNA片段。近年来,DNA标记技术在螨类系统学研究中得到越来越广泛的应用。本文综述了随机扩增多态性RAPD、限制性内切酶片段长度多态性RFLP、微卫星SSR、核酸序列扩增、扩增片段长度多态性AFLP和直接扩增片段长度多态性DALP等6种DNA标记技术在螨类系统学研究中的应用现状及前景。     

猪肺炎支原体P97基因随机肽库的构建

目的:构建能用于抗原表位筛选的猪肺炎支原体(Mhp)P97基因C-端序列噬菌体随机肽库.方法: 以Mhp Z株(强毒)基因组DNA为模板,通过PCR扩增获得Mhp P97基因的C-端部分序列,扩增产物用DNaseⅠ消化并回收50 bp～100 bp的随机片段,将回收的随机片段插入pC89pⅧ型噬菌粒载体中,转化大肠杆菌XL1-Blue,辅助噬菌体VCSM13超感染,使P97基因随机片段以融合蛋白的形式展示于噬菌体表面, 从而成功构建了P97基因特异性噬菌体随机肽库.用PCR及DNA测序法鉴定所建文库的随机性和多样性,测定肽库的滴度并计算库容量.结果: 所建肽库的容量约为1.8×104,滴度约为1.3×1012 TU/mL,PCR检测及DNA测序结果显示插入片段具有随机性和多样性.结论: 所建随机肽库具有较好的随机性和多样性,能够满足后续的抗原表位筛选,为进一步的深入研究奠定了基础.     

毛木耳种质资源的RAPD分析

利用22个随机引物对来源不同的56个木耳菌株进行了RAPD分析。结果表明,所有引物的扩增产物DNA片段均表现出明显的多态性,供试菌株总共扩增出164条多态性片段,占总扩增片段的99%;供试菌株两两间的遗传相似系数变化较大(平均GS值0.2143￣0.8764)。采用系统聚类法中的类平均法,对供试的所有菌株两两间相似系数进行聚类,可将它们分为四大类,各大类的类间和类内菌株的遗传变异程度较大,以IV类内各菌株间的最高(平均GS值0.3891),II和III类间的最低(平均GS值0.5887),表明遗传变异也较丰富(总平均GS值0.4918)。将RAPD技术应用于不同菌株间遗传差异的研究,具有反应迅速、不受外界环境条件影响、能从DNA分子水平上揭示菌株间遗传差异等优点,是一种快速准确评估木耳种质资源的有效方法。     

10种帘蛤科贝类COI基因序列分析及系统发育研究

应用通用引物扩增了凸加夫蛤(Gafrarium tumidum)、锯齿巴非蛤(Paphiagallus)、细纹卵蛤(Pitar striatum)、钝缀锦蛤(Tapes dorsatus)、裂纹格特蛤(Marcia hiantina)5种帘蛤科贝类COI基因片段,并与GenBank数据库收录的加夫蛤(Gafrarium pectinatum)、沟纹巴非蛤(Paphia exarata)、日本卵蛤(Pitar japonicum)、日本格特蛤(Marcia japonica)、四射缀锦蛤(Tapes belcheri)5种帘蛤科贝类的同源序列进行比对分析.结果表明:所有物种扩增片段长度均为616 bp,序列A+T平均含量(62.9％)明显高于G+C含量.在616个位点中,保守位点数为282个,变异位点数为334个,其中简约信息位点数为283个.以COI基因片段序列为标记,以海螂科砂海螂(Mya arenaria)作外群,构建了帘蛤科贝类的系统进化树,其拓扑结构显示:细纹卵蛤和日本卵蛤聚为一枝,凸加夫蛤和加夫蛤聚为一枝,锯齿巴非蛤和沟纹巴非蛤聚为一枝,四射缀锦蛤单独聚为一枝,钝缀锦蛤、裂纹格特蛤和日本格特蛤聚为一枝,最后所有帘蛤科物种聚为一枝,与外群相区别,其结果与传统形态分类基本一致.研究表明,线粒体COI基因作为帘蛤科贝类DNA条形码在物种鉴定方面具有可靠性,可以作为物种分类的重要辅助手段.     

嗜水气单胞菌气溶素基因的克隆与序列分析

以嗜水气单胞菌BZ和NK分离株的DNA为模板, 采用PCR技术, 扩增气溶素基因(aerA)的DNA片段, 将其克隆到pMD18-T载体上。通过序列测定, 分析结果表明：所克隆的1393 bp片段为aerA部分序列, 编码产生464个氨基酸。BZ与NK之间aerA核苷酸同源性为97.6%, 氨基酸同源性为98.3%, 与其它分离物核苷酸同源性为71.6%~97.5%, 氨基酸同源性为68.0%~98.9%。利用邻接法构建了aerA分子树状图, 树状图分析表明：气单胞菌属各分离物聚为三支, 其中嗜水气单胞菌各菌株之间关系密切, 被聚类为同一支。     

云南腾冲热泉土壤微生物基因组文库的构建与分析

采用冻融、蛋白酶K、SDS-高盐-加热处理法联合的方法,直接从云南腾冲地区的一个弱碱性高温热泉沉积样品中提取和分离环境混合基因组DNA,产量为每克样品1~2μg DNA,用Promega试剂盒纯化后进行PstⅠ部分酶切处理,电泳回收3~8kb的片段后,构建了pSK( )为载体的基因组文库,共获得25000个阳性克隆,平均插入片段长度为4.6kb。通过随机DNA序列测定和基因注释,发现外源插入片段含有未见报道的序列。     

运用线粒体COⅠ基因分析深圳海域石珊瑚系统发育关系

通过COⅠ基因特异扩增测序,对深圳东部海域45种石珊瑚COⅠ基因片段序列进行了比较分析。结果表明,该片段序列的平均(A+T)含量为61.2%,所有物种的序列碱基(A+T)含量大于(G+C)含量,与其它无脊椎动物线粒体DNA序列基本一致,序列都处于高度饱和的状态。45种造礁珊瑚的平均遗传距离为0.126。采用邻位连接(NJ)、最大似然(ML)和最小进化(ME)法对本研究中45种石珊瑚COⅠ基因片段构建了系统发育树。结果显示45个石珊瑚品种分别聚为两个大的分支,木珊瑚科、滨珊瑚科、菌珊瑚科、枇杷珊瑚科、鹿角珊瑚科的18个品种聚为分支Ⅰ,蜂巢珊瑚科、铁星珊瑚科、梳状珊瑚科、裸肋珊瑚科、褶叶珊瑚科的27个品种聚为分支Ⅱ,处于进化树基部。分支Ⅱ的聚类结果与传统形态学分类存在巨大差异,提示石珊瑚表型的变异性可能对传统分类存在影响。     

Characteristics of Venture Capital Network and Its Correlation with Regional Economy: Evidence from China

Financial networks have been extensively studied as examples of real world complex networks. In this paper, we establish and study the network of venture capital (VC) firms in China. We compute and analyze the statistical properties of the network, including parameters such as degrees, mean lengths of the shortest paths, clustering coefficient and robustness. We further study the topology of the network and find that it has small-world behavior. A multiple linear regression model is introduced to study the relation between network parameters and major regional economic indices in China. From the result of regression, we find that, economic aggregate (including the total GDP, investment, consumption and net export), upgrade of industrial structure, employment and remuneration of a region are all positively correlated with the degree and the clustering coefficient of the VC sub-network of the region, which suggests that the development of the VC industry has substantial effects on regional economy in China.     

Topological features of cancer proteins in the human NR-RTK interaction network

Protein-protein interaction (PPI) network analysis has been considered as a useful approach to explore the mechanisms of complex diseases, such as cancer. To date, many proteins have been reported to involve in the development of cancer. Exploration of cancer proteins in the human PPI network may provide important biological information to uncover molecular mechanisms of cancer. Here, we have explored network characteristics (including degree, betweenness, clustering coefficient and shortest-path distance) of cancer proteins of the human nuclear and tyrosine kinases receptors network (NR-RTK) constructed in our earlier work. We found that the network topology of cancer proteins in this network have some specific features. Relative to the non-cancer proteins, the cancer proteins have likely higher degree, higher betweenness, similar clustering coefficient and similar shortest-path distance. Finally, we found that the cancer proteins were involved mainly in signalling pathways which dysfunction is directly related to cancer onset. These findings are helpful for cancer candidate protein prioritization and verification, and identification of key pathways involved in cancer disease.     

The dichotomy in degree correlation of biological networks

Most complex networks from different areas such as biology, sociology or technology, show a correlation on node degree where the possibility of a link between two nodes depends on their connectivity. It is widely believed that complex networks are either disassortative (links between hubs are systematically suppressed) or assortative (links between hubs are enhanced). In this paper, we analyze a variety of biological networks and find that they generally show a dichotomous degree correlation. We find that many properties of biological networks can be explained by this dichotomy in degree correlation, including the neighborhood connectivity, the sickle-shaped clustering coefficient distribution and the modularity structure. This dichotomy distinguishes biological networks from real disassortative networks or assortative networks such as the Internet and social networks. We suggest that the modular structure of networks accounts for the dichotomy in degree correlation and vice versa, shedding light on the source of modularity in biological networks. We further show that a robust and well connected network necessitates the dichotomy of degree correlation, suggestive of an evolutionary motivation for its existence. Finally, we suggest that a dichotomous degree correlation favors a centrally connected modular network, by which the integrity of network and specificity of modules might be reconciled.     

Effects of heterogeneous and clustered contact patterns on infectious disease dynamics

The spread of infectious diseases fundamentally depends on the pattern of contacts between individuals. Although studies of contact networks have shown that heterogeneity in the number of contacts and the duration of contacts can have far-reaching epidemiological consequences, models often assume that contacts are chosen at random and thereby ignore the sociological, temporal and/or spatial clustering of contacts. Here we investigate the simultaneous effects of heterogeneous and clustered contact patterns on epidemic dynamics. To model population structure, we generalize the configuration model which has a tunable degree distribution (number of contacts per node) and level of clustering (number of three cliques). To model epidemic dynamics for this class of random graph, we derive a tractable, low-dimensional system of ordinary differential equations that accounts for the effects of network structure on the course of the epidemic. We find that the interaction between clustering and the degree distribution is complex. Clustering always slows an epidemic, but simultaneously increasing clustering and the variance of the degree distribution can increase final epidemic size. We also show that bond percolation-based approximations can be highly biased if one incorrectly assumes that infectious periods are homogeneous, and the magnitude of this bias increases with the amount of clustering in the network. We apply this approach to model the high clustering of contacts within households, using contact parameters estimated from survey data of social interactions, and we identify conditions under which network models that do not account for household structure will be biased.     

蛋白质氨基酸网络研究进展

氨基酸网络是运用复杂网络工具对蛋白质结构-功能关系研究的新方法。本文回顾了氨基酸网络中常用网络参量的计算方法,如:度分布,聚集系数,平均最短路径等。结合本研究小组的工作,介绍了常用的网络构建和分析方法,并总结了氨基酸网络在蛋白质折叠以及蛋白质分子对接问题中的应用。最后,分析了氨基酸网络研究目前存在的主要问题,并对未来的工作进行了展望。     

Visualization and analysis of the complexome network of Saccharomyces cerevisiae

Most processes in the cell are delivered by protein complexes, rather than individual proteins. While the association of proteins has been studied extensively in protein-protein interaction networks (the interactome), an intuitive and effective representation of complex-complex connections (the complexome) is not yet available. Here, we describe a new representation of the complexome of Saccharomyces cerevisiae. Using the core-module-attachment data of Gavin et al. ( Nature 2006 , 440 , 631 - 6 ), protein complexes in the network are represented as nodes; these are connected by edges that represent shared core and/or module protein subunits. To validate this network, we examined the network topology and its distribution of biological processes. The complexome network showed scale-free characteristics, with a power law-like node degree distribution and clustering coefficient independent of node degree. Connected complexes in the network showed similarities in biological process that were nonrandom. Furthermore, clusters of interacting complexes reflected a higher-level organization of many cellular functions. The strong functional relationships seen in these clusters, along with literature evidence, allowed 44 uncharacterized complexes to be assigned putative functions using guilt-by-association. We demonstrate our network model using the GEOMI visualization platform, on which we have developed capabilities to integrate and visualize complexome data.     

蛋白质氨基酸网络研究进展

氨基酸网络是运用复杂网络工具对蛋白质结构-功能关系研究的新方法。本文回顾了氨基酸网络中常用网络参量的计算方法,如：度分布,聚集系数,平均最短路径等。结合本研究小组的工作,介绍了常用的网络构建和分析方法,并总结了氨基酸网络在蛋白质折叠以及蛋白质分子对接问题中的应用。最后,分析了氨基酸网络研究目前存在的主要问题,并对未来的工作进行了展望。     

Mitochondrial DNA diversity and origins of South and Central American goats

We have analysed the genetic diversity of South and Central American (SCA) goats by partially sequencing the mitochondrial control region of 93 individuals with a wide geographical distribution. Nucleotide and haplotype diversities reached values of 0.020 ± 0.00081 and 0.963 ± 0.0012 respectively. We have also observed a rather weak phylogeographic structure, with almost 69% of genetic variation included in the within-breed variance component. The topology of a median-joining network analysis including 286 European, Iberian, Atlantic and SCA mitochondrial sequences was very complex, with most of the haplotypes forming part of independent small clusters. SCA sequences showed a scattered distribution throughout the network, and clustering with Spanish and Portuguese sequences occurred only occasionally, not allowing the distinguishing of a clear Iberian signature. Conversely, we found a prominent cluster including Canarian, Chilean, Argentinian and Bolivian mitochondrial haplotypes. This result was independently confirmed by constructing a Bayesian phylogenetic tree (posterior probability of 0.97). Sharing of mitochondrial haplotypes by SCA and Canarian goats suggests that goat populations from the Atlantic archipelagos, where Spanish and Portuguese ships en route to the New World used to stow food and supplies, participated in the foundation of SCA caprine breeds.