MATLAB 7.X生物信息工具箱的应用--系统发生分析(五)

MATLAB 7.X生物信息工具箱为广大用户提供了一个用于系统发生分析的综合环境,它能利用数据库资源,方便获取DNA/蛋白质序列数据,所有操作简单高效,结果可视化程度高。在工具箱提供的开放环境里,用户还可以根据自己的目标来设计和利用分析工具。本文介绍MATLAB7.X生物信息工具箱在构建系统发生树方面的应用,以人科线粒体基因序列作为分子标记构建一株人科系统发生树为例,说明在MATLAB环境下对系统发生树的分析和处理。     

系统发育信息学及网络资源

系统发育信息学是近年来形成的新的学科方向,是系统学研究领域的一个新兴生长点。系统发育信息学是存贮、管理、注释、开发和加工系统树及其相关生物学信息的交叉学科。它的方法是基于计算机和网络技术,包括大型系统树及其相关生物学数据库的建立,系统树数据库网络的构架,系统树的可视化显示,小系统树的联合与超树的建立、用户查询、搜索和下载等,最终目的是要建立一个囊括地球上所有生物的系统树及其相关信息的数据库,将各种生物在树上精确定位,并进一步通过对系统发育信息的查询、搜索、联合与分析,从中获取生命进化的知识和进行生物学的预测。目前可用的系统发育网络资源主要有CIPRes和系统发育软件(PhylogenyPrograms)网站,已建立的系统发育信息学数据库包括TreeBASE,TreeofLife,Species2000,NCBITaxonomy数据库等。     

核糖体RNA二级结构对拓扑结构准确性的影响

探讨了核糖体小亚基二级结构对真菌系统发育分析的影响。对用不同方法构建的系统发育树进行比较,结果表明结合二级结构信息的分析方法较传统方法产生了更为合理的拓扑结构。二级结构信息除用于优化序列比对外,还需整合到核酸替代模型中;恰当的序列比对方法、进化模型和建树运算法则有助于更加准确地揭示类群之间的亲缘关系。     

基于保守序列挖掘的乙型肝炎病毒进化研究

乙型肝炎是一种十分严重的全球性传染疾病,乙型肝炎病毒(Hepatitis B virus,HBV)是导致乙型肝炎的直接原因。而HBV突变是乙肝病毒进化过程中的一个重要部分,近几年,国内外针对HBV突变进行了广泛研究。但是,对乙肝病毒序列中保守序列的研究为仍处于起步阶段。本文首先采用MEME(Multiple EM for motif elicitation)算法挖掘HBV基序(生物序列中的保守序列片段,即Motif),并提出了一种新的度量标准保守指数(Conserved index,CI),然后对HBV序列进行系统发育分析,最后对构建的系统发育树进行可靠性评价。结果表明,新的度量标准CI可以有效地利用MEME方法挖掘出多个保守序列,进行HBV序列的系统发育树构建,进而分析HBV序列之间的进化关系,并可以找出样本可能的祖先序列。本文的实验方法对HBV大数据集分析方法的研究有积极地启示作用。     

生物软件在序列分析过程中的运用

介绍了组合使用BLAST、FASTA/BLASTScan3.2,或用多序列比对软件,从数据库中快速提取大数量目标序列,最后用MEGA4快捷编辑整理大数量序列的方法。还介绍了一种生成核酸序列与其氨基酸序列相似性百分率整合表格的方法。简述了对引物设计的基本认识并介绍了多重引物兼容性筛选软件;对构建系统发育树的认识并引出分子进化树构建软件MEGA4的使用和PAUP 4.0常用建树命令模块。期望这些方法和软件的使用能解决生物序列分析过程的常见问题。     

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。     

MATLAB7．X生物信息工具箱的应用——基因序列分析（一）

MATLAB7．X生物信息工具箱为广大用户提供了一个用于基因组和蛋白质组分析的综合环境,它利用数据库资源,使科学研究事半功倍,在工具箱提供的开放环境里,用户甚至可以按照自己的目的来设计和利用分析工具。本文主要介绍了MATLAB7．X生物信息工具箱在基因序列分析中的应用,包括确定核苷酸组成,密码子组成,氨基酸转化和组成等,所有操作简便高效。结果可视化程度高。     

系统发育基因组学研究进展

系统发育基因组学是利用全基因组数据构建系统发育树的新领域。全基因组数据能有效消除横向基因转移和类群间基因进化速率差异等因素对系统发育树的影响。根据所使用的全基因组数据的类型, 可以将系统发育基因组学方法分为以下5类：多基因联合建树方法, 基于基因含量的方法, 基于基因排列信息的方法, 基于序列短串含量特征信息的方法及基于代谢途径的方法。文章系统地总结了每一类方法的原理、速度、准确性、适用范围及在各个生物类群中的应用, 并对系统发育基因组学的前景及面临的挑战进行了概述。     

MATLAB 7.X生物信息工具箱的应用——基因序列分析(一)

MATLAB 7.X生物信息工具箱为广大用户提供了一个用于基因组和蛋白质组分析的综合环境,它利用数据库资源,使科学研究事半功倍,在工具箱提供的开放环境里,用户甚至可以按照自己的目的来设计和利用分析工具.本文主要介绍了MATLAB7.X生物信息工具箱在基因序列分析中的应用,包括确定核苷酸组成,密码子组成,氨基酸转化和组成等,所有操作简便高效,结果可视化程度高.     

Chlorella sorokiniana rbcL基因的克隆与序列分析及其与18S rRNA基因在分类学上的比较

Rubisco大亚基基因(rbcL)广泛用于系统学分析中,在本文中以Chlorella sorokiniana CS-01叶绿体基因组DNA为模板,PCR扩增rbcL全长编码区序列,序列分析表明:该片段全长1428 bp,其中包括1425 bp的编码区序列,编码475个氨基酸,经BLAST比对发现同源性最高的为Chlorella sp.IFRPD 1018,同源性达到99.2%。同时构建系统发育树,结果显示Chlorellasorokiniana CS-01与Chlorella sp.IFRPD 1018在同一分支中。18S rDNA序列分析表明:该片段全长1740 bp,经BLAST比对发现同源性最高的为Chlorella sorokiniana,同源性达到99.7%,构建系统发育树显示Chlorella sorokiniana CS-01与两株Chlorellasorokiniana在同一分支中,支持率达到100%。但是18S rDNA序列构建的系统发育树鉴定的主要分支很少,即使鉴定出分支,该分支的支持率也比较弱,而rbcL基因序列构建的系统发育树则分支清晰且支持率较高。可见18S rDNA序列比rbcL...     

PhyloSuite: An integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies

Multigene and genomic data sets have become commonplace in the field of phylogenetics, but many existing tools are not designed for such data sets, which often makes the analysis time‐consuming and tedious. Here, we present PhyloSuite , a (cross‐platform, open‐source, stand‐alone Python graphical user interface) user‐friendly workflow desktop platform dedicated to streamlining molecular sequence data management and evolutionary phylogenetics studies. It uses a plugin‐based system that integrates several phylogenetic and bioinformatic tools, thereby streamlining the entire procedure, from data acquisition to phylogenetic tree annotation (in combination with iTOL). It has the following features: (a) point‐and‐click and drag‐and‐drop graphical user interface; (b) a workplace to manage and organize molecular sequence data and results of analyses; (c) GenBank entry extraction and comparative statistics; and (d) a phylogenetic workflow with batch processing capability, comprising sequence alignment (mafft and macse ), alignment optimization (trimAl, HmmCleaner and Gblocks), data set concatenation, best partitioning scheme and best evolutionary model selection (PartitionFinder and modelfinder ), and phylogenetic inference (MrBayes and iq‐tree ). PhyloSuite is designed for both beginners and experienced researchers, allowing the former to quick‐start their way into phylogenetic analysis, and the latter to conduct, store and manage their work in a streamlined way, and spend more time investigating scientific questions instead of wasting it on transferring files from one software program to another.     

Compositional Bias May Affect Both DNA-Based and Protein-Based Phylogenetic Reconstructions

It is now well-established that compositional bias in DNA sequences can adversely affect phylogenetic analysis based on those sequences. Phylogenetic analyses based on protein sequences are generally considered to be more reliable than those derived from the corresponding DNA sequences because it is believed that the use of encoded protein sequences circumvents the problems caused by nucleotide compositional biases in the DNA sequences. There exists, however, a correlation between AT/GC bias at the nucleotide level and content of AT- and GC-rich codons and their corresponding amino acids. Consequently, protein sequences can also be affected secondarily by nucleotide compositional bias. Here, we report that DNA bias not only may affect phylogenetic analysis based on DNA sequences, but also drives a protein bias which may affect analyses based on protein sequences. We present a striking example where common phylogenetic tools fail to recover the correct tree from complete animal mitochondrial protein-coding sequences. The data set is very extensive, containing several thousand sites per sequence, and the incorrect phylogenetic trees are statistically very well supported. Additionally, neither the use of the LogDet/paralinear transform nor removal of positions in the protein alignment with AT- or GC-rich codons allowed recovery of the correct tree. Two taxa with a large compositional bias continually group together in these analyses, despite a lack of close biological relatedness. We conclude that even protein-based phylogenetic trees may be misleading, and we advise caution in phylogenetic reconstruction using protein sequences, especially those that are compositionally biased. Received: 19 February 1998 / Accepted: 28 August 1998     

A format for phylogenetic placements

We have developed a unified format for phylogenetic placements, that is, mappings of environmental sequence data (e.g., short reads) into a phylogenetic tree. We are motivated to do so by the growing number of tools for computing and post-processing phylogenetic placements, and the lack of an established standard for storing them. The format is lightweight, versatile, extensible, and is based on the JSON format, which can be parsed by most modern programming languages. Our format is already implemented in several tools for computing and post-processing parsimony- and likelihood-based phylogenetic placements and has worked well in practice. We believe that establishing a standard format for analyzing read placements at this early stage will lead to a more efficient development of powerful and portable post-analysis tools for the growing applications of phylogenetic placement.     

Gene's Functional Arrangement as a Measure of thePhylogenetic Relationships of Microorganisms

With the development of genome sequencing more whole genomes of microorganisms were completed, many methods wereintroduced to reconstruct the phylogenetic tree of those microorganismswith the information extracted from the whole genomes through variousways of transforming or mapping the whole genome sequences into otherforms which can describe the evolutionary distance in a new way. We thinkit might be possible that there exists information buried in the wholegenome transferred along lineage, which remains stable and is moreessential than sequence conservation of individual genes or the arrangementof some genes of a selected set. We need to find one measurement that caninvolve as many phylogenetic features as possible that are beyond thegenome sequence itself. We converted each genome sequence of themicroorganisms into another linear sequence to represent the functionalstructure of the sequence, and we used a new information function tocalculate the discrepancy of sequences and to get one distance matrix of thegenomes, and built one phylogenetic tree with a neighbor joining method.The resulting tree shows that the major lineages are consistent with theresult based on their 16srRNA sequences. Our method discovered onephylogenetic feature derived from the genome sequences and the encodedgenes that can rebuild the phylogenetic tree correctly. The mapping of onegenome sequence to its new form representing the relative positions of thefunctional genes provides a new way to measure the phylogeneticrelationships, and with the more specific classification of gene functions theresult could be more sensitive.     

裸盖菇属的真菌鉴定及分子系统学初探

裸盖菇属(Psilocybe)的许多真菌含有神经致幻型毒素,这些毒素被中国卫生部列为A类管制药品。在药检时,这些真菌样品通常是粉末。因此,仅依靠形态分类鉴定该类真菌非常困难。研究采用ITS序列分析的方法鉴定该类真菌并初步探讨了该属种间的系统发育关系。由系统发育树推断Psilocybe属可能是多源进化的。通过序列分析可以鉴定真菌样品为Psilocybe属。     

A novel feature-based method for whole genome phylogenetic analysis without alignment: application to HEV genotyping and subtyping

Traditional phylogenetic analysis is based on multiple sequence alignment. With the development of worldwide genome sequencing project, more and more completely sequenced genomes become available. However, traditional sequence alignment tools are impossible to deal with large-scale genome sequence. So, the development of new algorithms to infer phylogenetic relationship without alignment from whole genome information represents a new direction of phylogenetic study in the post-genome era. In the present study, a novel algorithm based on BBC (base-base correlation) is proposed to analyze the phylogenetic relationships of HEV (Hepatitis E virus). When 48 HEV genome sequences are analyzed, the phylogenetic tree that is constructed based on BBC algorithm is well consistent with that of previous study. When compared with methods of sequence alignment, the merit of BBC algorithm appears to be more rapid in calculating evolutionary distances of whole genome sequence and not requires any human intervention, such as gene identification, parameter selection. BBC algorithm can serve as an alternative to rapidly construct phylogenetic trees and infer evolutionary relationships.     

Phylogenetic uncertainty revisited: Implications for ecological analyses

Ecologists and biogeographers usually rely on a single phylogenetic tree to study evolutionary processes that affect macroecological patterns. This approach ignores the fact that each phylogenetic tree is a hypothesis about the evolutionary history of a clade, and cannot be directly observed in nature. Also, trees often leave out many extant species, or include missing species as polytomies because of a lack of information on the relationship among taxa. Still, researchers usually do not quantify the effects of phylogenetic uncertainty in ecological analyses. We propose here a novel analytical strategy to maximize the use of incomplete phylogenetic information, while simultaneously accounting for several sources of phylogenetic uncertainty that may distort statistical inferences about evolutionary processes. We illustrate the approach using a clade‐wide analysis of the hummingbirds, evaluating how different sources of uncertainty affect several phylogenetic comparative analyses of trait evolution and biogeographic patterns. Although no statistical approximation can fully substitute for a complete and robust phylogeny, the method we describe and illustrate enables researchers to broaden the number of clades for which studies informed by evolutionary relationships are possible, while allowing the estimation and control of statistical error that arises from phylogenetic uncertainty. Software tools to carry out the necessary computations are offered.     

Treeness triangles: visualizing the loss of phylogenetic signal

It is well known that molecular data "saturates" with increasing sequence divergence (thereby losing phylogenetic information) and that in addition the accumulation of misleading information due to chance similarities or to systematic bias may accompany saturation as well. Exploratory data analysis methods that can quantify the extent of signal loss or convergence for a given data set are scarce. Such methods are needed because genomics delivers very long sequence alignments spanning substantial phylogenetic depth, where site saturation may be compounded by systematic biases or other alternative signals. Here we introduce the Treeness Triangle (TT) graph, in which signals detectable by Hadamard (spectral) analysis are summed into 3 categories--those supporting 1) external and 2) internal branches in the optimal tree, in addition to 3) the residuals (potential internal branches not present in the optimal tree). These 3 values are plotted in a standard ternary coordinate system. The approach is illustrated with simulated and real data sets, the latter from complete chloroplast genomes, where potential problems of paralogy or lateral gene acquisition can be excluded. The TT uncovers the divergence-dependent loss of phylogenetic signal as subsets of chloroplast genomes are investigated that span increasingly deeper evolutionary timescales. The rate of signal loss (or signal retention) varies with the gene and/or the method of analysis.