基于系统基因组学分析揭示早期陆生植物的复杂网状进化关系

植物由水生走向陆生的进化过程中经历了非常复杂的演化,期间产生的大量基因的进化路线可能互不相同,因此仅仅使用系统发育树无法呈现真实的演化关系。系统发育网络图能够清楚地展示包括垂直演化和水平演化在内的复杂网状进化关系。本文选取莱茵衣藻(Chlamydomonas reinhardtii)和4种陆生植物,利用系统基因组学的方法,筛选得到1,668个一对一直系同源基因,重新构建了陆生植物的系统发育网状进化关系。结果发现,使用不同的分析策略所得到的系统发育树不同;对1,668个基因单独分析,发现存在15种不同的拓扑结构;对5个物种筛选得到的直系同源基因进行系统发育网络分析显示,在非常稳健的系统发育网络图中,仅仅5个物种就存在9个不同的分离支,暗示着非常复杂的网状进化关系;而且藻类植物与苔藓植物和石松类植物的分离支之间差异很小,这可能是产生系统发育树冲突的原因之一,也暗示着早期陆生植物发生了复杂的辐射演化。     

植物内生固氮菌系统发育进化新进展

在植物内生固氮菌系统发育进化关系研究中,常用的方法有形态学与蛋白质水平法、数值分类和自动化鉴定法、化学分类法、分子遗传学方法等。本文简要介绍了常用方法的关键技术,并归纳了它们的优缺点。生物学的研究进入基因组时代后,随着高通量DNA测序技术在微生物学领域应用的迅速发展,全基因组测序被应用到微生物系统发育进化研究中,然而目前并未发现对已测全基因组序列的植物内生固氮菌进行系统总结。本文在对已测序植物内生固氮菌进行归纳的基础上,又详细研究了基于基因组数据的几种具有代表性的新方法(ANI分析法、最大唯一匹配指数法、核心基因组分析、组分矢量法、基因流动性分析),并结合目前系统发育进化研究常用方法,对植物内生固氮菌系统发育进化研究趋势进行总结和展望,旨在使植物内生固氮菌的系统发育进化关系研究在精确度、可靠性等方面有所突破。     

基于Cytb和COⅠ基因部分序列的15种麻蝇之间的系统发育关系(双翅目:麻蝇科)(英文)

本研究通过测序Cytb基因和COⅠ基因的部分序列来推定15种麻蝇之间的系统发育关系。在世界麻蝇名录中,本研究的15种麻蝇能够代表麻蝇属Sarcophaga的6个亚属。连接序列(972bp)被用于系统发育分析;分析方法包括了了最大简约法、最大似然法以及贝叶斯法。我们的结果提示了亚麻蝇亚属Parasarcophaga、别麻蝇亚属Boettcherisca以及红麻蝇亚属Liopygia的单系性,同时也表明蛇麻蝇亚属Liosarcophaga和德麻蝇亚属Pandelleisca并不是单源的。不过,目前的研究并不能分辨野德麻蝇S.(Pandelleisca)similis和峨眉叉麻蝇S.(Robineauella)coei的系统发育位置。此外,最大简约分析和似然功能分析在scopariiformis-iwuensis进化枝和polystylata-hui进化枝的关系上产生了不一致的系统发育推断。因此,后续研究不仅需要其他的分子标记,也需要更多的分类取样。     

圆网蛛类系统发生与网型进化

本文从妖面蛛总科和园蛛总科系统发生关系、园蛛总科网型不同的蜘蛛间的系统发生关系及蛛网构建行为等几个方面着重介绍了圆网蛛类系统发生及网型进化的研究进展.圆网蛛类系统发生与其网型进化有效地结合、进行综合研究将有助于圆网蛛类的起源及网型多样性的研究.     

花楸(Sorbus pohuashanensis)导管分子穿孔板的类型及演化

对花楸茎次生木质部进行离析研究,发现其导管穿孔板有两种类型,即网状穿孔板和单穿孔板,并且还有5种过渡类型,具不同类型穿孔板的导管分子有3种类型,即两端均为网状穿孔板的导管分子;一端为网状穿孔板,另一端为单穿孔板的导管分子;两端的均为单穿孔板的导管分子,在花楸个体发育过程中穿孔板类型的演化重演了系统发育过程中导管网状穿孔板演化成单穿孔板的过程。     

亚洲玉米螟不同地理种群基于COⅠ基因序列初步分析

本研究通过对我国亚洲玉米螟Ostrinia furnacalis(Guenée)6个地理种群的线粒体DNACOⅠ基因进行测序,运用分子进化遗传分析软件MEGA5对序列进行对比和同源性分析,并建立系统发育关系。结果表明,COⅠ基因在6个地理种群中进化具有一定的差异,平均遗传距离为0.013;进化树显示,亚洲玉米螟的三亚种群、广州种群与南昌种群聚为一支,然后与泰安种群聚为一支,再与哈尔滨种群聚为一支;而廊坊种群另聚成一支。遗传分歧度与系统发育进化关系均表明不同地理种群的遗传分化与地理距离之间具有一定的相关性。     

食肉目哺乳动物的系统发育学研究概述

追溯生物界不同生物类型的起源及进化关系,即重建生物类群的系统发育树是进化生物学领域中一个十分重要的内容。食肉目哺乳动物位于食物链顶端,很多成员不仅在我国野生动物保护工作中占有重要地位,而且还是研究动物适应性进化遗传机制的重要模式生物。因而,食肉目物种作为物种资源中的一个重要类群,其系统发育学一直是国内外研究的热门课题。构建可靠的食肉目分子系统树,无疑将具有重要的进化理论意义和保护生物学价值。鉴于目前食肉目各科间系统发育关系仍然处于“广泛争论”的状态,本文将针对食肉目科水平上的系统发育学研究进展,包括来自于形态学特征、细胞学及分子生物学方面的证据,做简要概述,并提出目前研究中存在的问题。这对今后食肉目系统发育方面的进一步研究工作具有指导意义,并为以该类群作为模式生物开展适应性进化研究奠定基础。     

常用系统发育树构建算法和软件鸟瞰

系统发育树又称进化树、生命树等,在达尔文的"进化论"一书中首次出现,之后系统发育树的重构被广大生物学家所接受。该文阐述了构建系统发育树的基本流程,对目前用于构建系统发育树的四类算法(距离法、最大简约法、最大似然法和贝叶斯法)进行了详细地分析和比较,并介绍了一些常用系统发育树构建和分析软件(PHYLIP、MEGA、MrBayes)的特点。     

基于Cytb和COⅡ基因序列的网翅蝗科(直翅目:蝗总科)部分种类的分子系统学研究

采用PCR产物直接测序法测定了2亚科31种网翅蝗科昆虫及1种癞蝗(外群)的线粒体基因Cyt b和COⅡ全序列,使用MEGA V4.1进行序列组成分析,对线粒体基因Cyt b、COⅡ数据集按照蛋白质基因密码子第一、二、三位点划分子集,并组成联合数据集COⅡ&Cyt b,对各数据集其子集进行了数据探索研究.在PAUP中应用NJ法、MP法、ML法以及在MrBayes V3.1中应用贝叶斯系统发育推论(BI)法进行系统发育关系重建,结果表明所研究的网翅蝗科部分种类的系统发育关系基本与中国的传统形态学分类体系没有差别,竹蝗亚科为较早分化出来的类群,其次为网翅蝗亚科;竹蝗新种和黄脊雷篦蝗聚为一支和其它竹蝗属类群形成姊妹群,因此建议将雷篾蝗属并入竹蝗属;隆额网翅蝗和宽翅曲背蝗聚为另一支,故建议将曲背蝗属并入网翅蝗属.雏蝗属的四个亚属中黑翅亚属、曲隆亚属和直隆亚属这三个亚属的单系性均得到稳健的支持,而短翅亚属的单系性在各种分析中皆得不到支持,它很可能是多系起源.     

基于18S rDNA与ITS-5.8S rDNA对 重庆地区网状车轮虫的种内分化研究

本研究基于形态和分子数据对采自重庆地区5个地理株系的网状车轮虫(Trichodina reticulata)进行了比较研究及重描述。研究结果表明,网状车轮虫不同株系表现出不同的表型分化,含形态略有不同的齿体及有或无中央颗粒,因而具有明显的种内形态多样性。不同地理株系网状车轮虫的18S rDNA序列相似度在99.0%~100%之间,遗传距离为0.000~0.008,并在三大变异区(V4、V5与V7)均具一致的二级结构,表明不同株系的18Sr DNA相似度与遗传距离均属种内水平。综合18SrDNA和ITS-5.8S rDNA的变异位点和系统发育对种内分歧的研究分析显示,来自不同地理分布和宿主的网状车轮虫株系皆因相同的变异位点而聚为一枝,以此推断网状车轮虫的种内分化主要受其基因的影响,地理分布与宿主差异等环境影响在目前的种群分化阶段暂未突显。此外,本研究进一步验证了中央颗粒不能作为网状车轮虫的主要鉴别性特征的观点。     

Application of phylogenetic networks in evolutionary studies

The evolutionary history of a set of taxa is usually represented by a phylogenetic tree, and this model has greatly facilitated the discussion and testing of hypotheses. However, it is well known that more complex evolutionary scenarios are poorly described by such models. Further, even when evolution proceeds in a tree-like manner, analysis of the data may not be best served by using methods that enforce a tree structure but rather by a richer visualization of the data to evaluate its properties, at least as an essential first step. Thus, phylogenetic networks should be employed when reticulate events such as hybridization, horizontal gene transfer, recombination, or gene duplication and loss are believed to be involved, and, even in the absence of such events, phylogenetic networks have a useful role to play. This article reviews the terminology used for phylogenetic networks and covers both split networks and reticulate networks, how they are defined, and how they can be interpreted. Additionally, the article outlines the beginnings of a comprehensive statistical framework for applying split network methods. We show how split networks can represent confidence sets of trees and introduce a conservative statistical test for whether the conflicting signal in a network is treelike. Finally, this article describes a new program, SplitsTree4, an interactive and comprehensive tool for inferring different types of phylogenetic networks from sequences, distances, and trees.     

Tripartitions do not always discriminate phylogenetic networks

Phylogenetic networks are a generalization of phylogenetic trees that allow for the representation of non-treelike evolutionary events, like recombination, hybridization, or lateral gene transfer. In a recent series of papers devoted to the study of reconstructibility of phylogenetic networks, Moret, Nakhleh, Warnow and collaborators introduced the so-called tripartition metric for phylogenetic networks. In this paper we show that, in fact, this tripartition metric does not satisfy the separation axiom of distances (zero distance means isomorphism, or, in a more relaxed version, zero distance means indistinguishability in some specific sense) in any of the subclasses of phylogenetic networks where it is claimed to do so. We also present a subclass of phylogenetic networks whose members can be singled out by means of their sets of tripartitions (or even clusters), and hence where the latter can be used to define a meaningful metric.     

Trees and/or networks to display intraspecific DNA sequence variation?

Phylogenetic trees and networks are both used in the scientific literature to display DNA sequence variation at the intraspecific level. Should we rather use trees or networks? I argue that the process of inferring the most parsimonious genealogical relationships among a set of DNA sequences should be dissociated from the problem of displaying this information in a graph. A network graph is probably more appropriate than a strict consensus tree if many alternative, equally most parsimonious, genealogies are to be included. Within the maximum parsimony framework, current phylogenetic inference and network‐building algorithms are both unable to guarantee the finding of all most parsimonious (MP) connections. In fact, each approach can find MP connections that the other does not. Although it should be possible to improve at least the maximum parsimony approach, current implementations of these algorithms are such that it is advisable to use both approaches to increase the probability of finding all possible MP connections among a set of DNA sequences.     

Networks in phylogenetic analysis: new tools for population biology

Phylogenetic analysis has changed greatly in the past decade, including the more widespread appreciation of the idea that evolutionary histories are not always tree-like, and may, thus, be best represented as reticulated networks rather than as strictly dichotomous trees. Reconstructing such histories in the absence of a bifurcating speciation process is even more difficult than the usual procedure, and a range of alternative strategies have been developed. There seem to be two basic uses for a network model of evolution: the display of real but unobservable evolutionary events (i.e. a hypothesis of the true phylogenetic history), and the display of character conflict within the data itself (i.e. a summary of the data). These two general approaches are briefly reviewed here, and the strengths and weaknesses of the different implementations are compared and contrasted. Each network methodology seems to have limitations in terms of how it responds to increasing complexity (e.g. conflict) in the data, and therefore each is likely to be more appropriate for one of the two uses than for the other. Several examples using parasitological data sets illustrate the uses of networks within the context of population biology.     

Global patterns in anuran–prey networks: structure mediated by latitude

Life on Earth is supported by an infinite number of interactions among organisms. Species interactions in these networks are influenced by latitude, evolutionary history and species traits. We performed a global‐scale literature analysis to build up a database of interactions between anuran communities and their preys, from a wide range of geographical areas, using a network approach. For this purpose, we compiled a total of 55 weighted anuran–prey interaction networks, 39 located in the tropics and 16 in temperate areas. We tested the influence of latitude, as well as anuran taxonomic, functional and phylogenetic richness on network metrics. We found that anuran–prey networks are not nested, exhibit low complementary specialization and modularity and high connectance when compared to other types of networks. The main effects on network metrics were related to latitude, followed by anuran taxonomic, functional and phylogenetic richness, a pattern similar to the emerging in mutualistic networks. Our study is the first integrated analysis of the structural patterns in anuran–prey antagonistic interaction networks in different parts of the world. We suggest that different processes, mediated mainly by latitude, are modeling the architecture of anuran–prey networks across the globe.     

A genotype network reveals homoplastic cycles of convergent evolution in influenza A (H3N2) haemagglutinin

Networks of evolving genotypes can be constructed from the worldwide time-resolved genotyping of pathogens like influenza viruses. Such genotype networks are graphs where neighbouring vertices (viral strains) differ in a single nucleotide or amino acid. A rich trove of network analysis methods can help understand the evolutionary dynamics reflected in the structure of these networks. Here, I analyse a genotype network comprising hundreds of influenza A (H3N2) haemagglutinin genes. The network is rife with cycles that reflect non-random parallel or convergent (homoplastic) evolution. These cycles also show patterns of sequence change characteristic for strong and local evolutionary constraints, positive selection and mutation-limited evolution. Such cycles would not be visible on a phylogenetic tree, illustrating that genotype network analysis can complement phylogenetic analyses. The network also shows a distinct modular or community structure that reflects temporal more than spatial proximity of viral strains, where lowly connected bridge strains connect different modules. These and other organizational patterns illustrate that genotype networks can help us study evolution in action at an unprecedented level of resolution.     

Biological solutions to transport network design

Transport networks are vital components of multicellular organisms, distributing nutrients and removing waste products. Animal and plant transport systems are branching trees whose architecture is linked to universal scaling laws in these organisms. In contrast, many fungi form reticulated mycelia via the branching and fusion of thread-like hyphae that continuously adapt to the environment. Fungal networks have evolved to explore and exploit a patchy environment, rather than ramify through a three-dimensional organism. However, there has been no explicit analysis of the network structures formed, their dynamic behaviour nor how either impact on their ecological function. Using the woodland saprotroph Phanerochaete velutina, we show that fungal networks can display both high transport capacity and robustness to damage. These properties are enhanced as the network grows, while the relative cost of building the network decreases. Thus, mycelia achieve the seemingly competing goals of efficient transport and robustness, with decreasing relative investment, by selective reinforcement and recycling of transport pathways. Fungal networks demonstrate that indeterminate, decentralized systems can yield highly adaptive networks. Understanding how these relatively simple organisms have found effective transport networks through a process of natural selection may inform the design of man-made networks.     

Ecological,historical and evolutionary determinants of modularity in weighted seed‐dispersal networks

Modularity is a recurrent and important property of bipartite ecological networks. Although well‐resolved ecological networks describe interaction frequencies between species pairs, modularity of bipartite networks has been analysed only on the basis of binary presence–absence data. We employ a new algorithm to detect modularity in weighted bipartite networks in a global analysis of avian seed‐dispersal networks. We define roles of species, such as connector values, for weighted and binary networks and associate them with avian species traits and phylogeny. The weighted, but not binary, analysis identified a positive relationship between climatic seasonality and modularity, whereas past climate stability and phylogenetic signal were only weakly related to modularity. Connector values were associated with foraging behaviour and were phylogenetically conserved. The weighted modularity analysis demonstrates the dominating impact of ecological factors on the structure of seed‐dispersal networks, but also underscores the relevance of evolutionary history in shaping species roles in ecological communities.     

Comparative protein analysis of the chitin metabolic pathway in extant organisms: A complex network approach

Chitin is a structural endogenous carbohydrate, which is a major component of fungal cell walls and arthropod exoskeletons. A renewable resource and the second most abundant polysaccharide in nature after cellulose, chitin is currently used for waste water clearing, cosmetics, medical, and veterinary applications. This work comprises data mining of protein sequences related to the chitin metabolic pathway of completely sequenced genomes of extant organisms pertaining to the three life domains, followed by meta-analysis using traditional sequence similarity comparison and complex network approaches. Complex networks involving proteins of the chitin metabolic pathway in extant organisms were constructed based on protein sequence similarity. Several usual network indices were estimated in order to obtain information on the topology of these networks, including those related to higher order neighborhood properties. Due to the assumed evolutionary character of the system, we also discuss issues related to modularity properties, with the concept of edge betweenness playing a particularly important role in our analysis. Complex network approach correctly identifies clusters of organisms that belong to phylogenetic groups without any a priori knowledge about the biological features of the investigated protein sequences. We envisage the prospect of using such a complex network approach as a high-throughput phylogenetic method.