MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods

Comparative analysis of molecular sequence data is essential for reconstructing the evolutionary histories of species and inferring the nature and extent of selective forces shaping the evolution of genes and species. Here, we announce the release of Molecular Evolutionary Genetics Analysis version 5 (MEGA5), which is a user-friendly software for mining online databases, building sequence alignments and phylogenetic trees, and using methods of evolutionary bioinformatics in basic biology, biomedicine, and evolution. The newest addition in MEGA5 is a collection of maximum likelihood (ML) analyses for inferring evolutionary trees, selecting best-fit substitution models (nucleotide or amino acid), inferring ancestral states and sequences (along with probabilities), and estimating evolutionary rates site-by-site. In computer simulation analyses, ML tree inference algorithms in MEGA5 compared favorably with other software packages in terms of computational efficiency and the accuracy of the estimates of phylogenetic trees, substitution parameters, and rate variation among sites. The MEGA user interface has now been enhanced to be activity driven to make it easier for the use of both beginners and experienced scientists. This version of MEGA is intended for the Windows platform, and it has been configured for effective use on Mac OS X and Linux desktops. It is available free of charge from http://www.megasoftware.net.     

MEGA: a biologist-centric software for evolutionary analysis of DNA and protein sequences

The Molecular Evolutionary Genetics Analysis (MEGA) software is a desktop application designed for comparative analysis of homologous gene sequences either from multigene families or from different species with a special emphasis on inferring evolutionary relationships and patterns of DNA and protein evolution. In addition to the tools for statistical analysis of data, MEGA provides many convenient facilities for the assembly of sequence data sets from files or web-based repositories, and it includes tools for visual presentation of the results obtained in the form of interactive phylogenetic trees and evolutionary distance matrices. Here we discuss the motivation, design principles and priorities that have shaped the development of MEGA. We also discuss how MEGA might evolve in the future to assist researchers in their growing need to analyze large data set using new computational methods.     

MEGA11: Molecular Evolutionary Genetics Analysis Version 11

The Molecular Evolutionary Genetics Analysis (MEGA) software has matured to contain a large collection of methods and tools of computational molecular evolution. Here, we describe new additions that make MEGA a more comprehensive tool for building timetrees of species, pathogens, and gene families using rapid relaxed-clock methods. Methods for estimating divergence times and confidence intervals are implemented to use probability densities for calibration constraints for node-dating and sequence sampling dates for tip-dating analyses. They are supported by new options for tagging sequences with spatiotemporal sampling information, an expanded interactive Node Calibrations Editor, and an extended Tree Explorer to display timetrees. Also added is a Bayesian method for estimating neutral evolutionary probabilities of alleles in a species using multispecies sequence alignments and a machine learning method to test for the autocorrelation of evolutionary rates in phylogenies. The computer memory requirements for the maximum likelihood analysis are reduced significantly through reprogramming, and the graphical user interface has been made more responsive and interactive for very big data sets. These enhancements will improve the user experience, quality of results, and the pace of biological discovery. Natively compiled graphical user interface and command-line versions of MEGA11 are available for Microsoft Windows, Linux, and macOS from www.megasoftware.net.     

DnaSP, DNA polymorphism analyses by the coalescent and other methods

SUMMARY: DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (approximately 5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. AVAILABILITY: The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp     

苔藓动物18S rRNA基因的分子系统发生初探

本文对我国沿海较为常见的8种唇口目苔藓动物的18SrRNA基因进行了PCR扩增和序列测定。结合已知的其它苔藓动物（包括内肛动物和外肛动物）以及腕足动物和帚虫的相应序列,运用分子系统学方法,研究苔藓动物门的系统发生关系,结果表明,外肛动物和内肛动物构成苔藓动物分子系统树中的二大平行支;本文测定的大室膜孔苔虫与Giribet等测定的膜孔苔虫在系统树中的位置间隔较远。结果也支持外肛动物包含被唇纲和裸唇纲两大类群的形态划分,而关于裸唇纲特别是唇口目内部的系统发生关系。分子数据的分析结果和形态分类之间的分歧有待于进一步研究。     

高等植物己糖激酶基因研究进展

己糖激酶(HXK)具有催化己糖磷酸化的作用,是植物体呼吸代谢过程中的关键酶之一。近十几年的研究发现,HXK在植物的糖感知和糖信号转导过程中扮演重要的角色。目前GenBank已登录28种高等植物的HXK同源基因,其在不同物种中均以多基因家族形式存在。HXK基因家族多数成员包括9个外显子,编码492-522个氨基酸。HXK亚细胞定位研究发现,植物HXK家族成员主要分布于线粒体,少数成员存在于细胞质、叶绿体和质体基质中。植物HXK基因家族大部分成员在不同器官或组织中均有表达,但是拟南芥(Arabidopsis thaliana)AtHKL3和水稻(Oryza sativa)OsHXK10仅在花中表达。高等植物部分HXK不仅影响植物生长发育,还调控植物激素信号转导以及调节植物花青素合成途径中相关基因表达。应用MEGA 4.0软件对18个物种HXK基因氨基酸序列构建系统进化树,HXK基因序列聚为7小支,聚类关系能反映不同基因结构和功能的差异。     

Recombination and Evolution of Duplicate Control Regions in the Mitochondrial Genome of the Asian Big-Headed Turtle,Platysternon megacephalum

Complete mitochondrial (mt) genome sequences with duplicate control regions (CRs) have been detected in various animal species. In Testudines, duplicate mtCRs have been reported in the mtDNA of the Asian big-headed turtle, Platysternon megacephalum, which has three living subspecies. However, the evolutionary pattern of these CRs remains unclear. In this study, we report the completed sequences of duplicate CRs from 20 individuals belonging to three subspecies of this turtle and discuss the micro-evolutionary analysis of the evolution of duplicate CRs. Genetic distances calculated with MEGA 4.1 using the complete duplicate CR sequences revealed that within turtle subspecies, genetic distances between orthologous copies from different individuals were 0.63% for CR1 and 1.2% for CR2app:addword:respectively, and the average distance between paralogous copies of CR1 and CR2 was 4.8%. Phylogenetic relationships were reconstructed from the CR sequences, excluding the variable number of tandem repeats (VNTRs) at the 3′ end using three methods: neighbor-joining, maximum likelihood algorithm, and Bayesian inference. These data show that any two CRs within individuals were more genetically distant from orthologous genes in different individuals within the same subspecies. This suggests independent evolution of the two mtCRs within each P. megacephalum subspecies. Reconstruction of separate phylogenetic trees using different CR components (TAS, CD, CSB, and VNTRs) suggested the role of recombination in the evolution of duplicate CRs. Consequently, recombination events were detected using RDP software with break points at ≈290 bp and ≈1,080 bp. Based on these results, we hypothesize that duplicate CRs in P. megacephalum originated from heterological ancestral recombination of mtDNA. Subsequent recombination could have resulted in homogenization during independent evolutionary events, thus maintaining the functions of duplicate CRs in the mtDNA of P. megacephalum.     

中国大头蛙属3个种线粒体ND1基因全序列分析与亲缘关系

测定了大头蛙和脆皮大头蛙线粒体ND1基因全序列长度分别为978 bp和958 bp,(对应编码325和319个氨基酸)。对所测基因序列组分进行了分析,并与福建大头蛙同源序列进行比较发现,978个核苷酸位点中,有664个保守位点和多变位点294个。同时发现福建大头蛙与大头蛙该基因序列的同源性最高(核苷酸序列同源性为78.77%,氨基酸序列为92.62%)。基于ND1基因全序列的氨基酸和核苷酸两种数据形式,选用M ega3.1软件中的NJ法对大头蛙属3个种、黑斑蛙、泽陆蛙及外群中国大鲵共6条基因序列进行系统树重建分析,结果表明:所得的2个NJ树均将大头蛙属3个种聚于一支,其中大头蛙与福建大头蛙为姐妹群关系(自检值均高度支持),从而证实了大头蛙与福建大头蛙亲缘关系较近的观点。     

重庆市26个南亚果实蝇种群mtDNA 16S rRNA基因部分序列及其系统进化

对重庆市26个南亚果实蝇Bactrocera(Zeugodacus)tau(Walker)种群线粒体16S rRNA基因进行测序,获得长约350bp片段的序列。对获得的序列分析表明,A,T,C,G平均含量分别为35·0%,41·3%,7·2%,16·5%,其中保守位点数342个,变异位点数5个,简约信息位点2个,自裔位点2个,所有碱基转换总数为136,替换总数为50。利用MEGA2·1软件重建系统发生树,发现其中21个南亚果实蝇种群未出现分化,另外有5个南亚果实蝇种群出现了分化,但遗传分化程度小。     

Divergent evolution of the chloroplast small heat shock protein gene in the genera Rhododendron (Ericaceae) and Machilus (Lauraceae)

BACKGROUND AND AIMS: Evolutionary and ecological roles of the chloroplast small heat shock protein (CPsHSP) have been emphasized based on variations in protein contents; however, DNA sequence variations related to the evolutionary and ecological roles of this gene have not been investigated. In the present study, a basal angiosperm, Machilus, together with the eudicot Rhododendron were used to illustrate the evolutionary dynamics of gene divergence in CPsHSPs. METHODS: Degenerate primers were used to amplify CPsHSP-related sequences from 16 Rhododendron and eight Machilus species that occur in Taiwan. Manual DNA sequence alignment was carried out according to the deduced amino acid sequence alignment performed by CLUSTAL X. A neighbour-joining tree was generated in MEGA using conceptual translated amino acid sequences from consensus sequences of cloned CPsHSP genes from eight Machilus and 16 Rhododendron species as well as amino acid sequences of CPsHSPs from five monocots and seven other eudicots acquired from GenBank. CPsHSP amino acid sequences of Funaria hygrometrica were used as the outgroups. The aligned DNA and amino acid sequences were used to estimate several parameters of sequence divergence using the MEGA program. Separate Bayesian inference of DNA sequences of Rhododendron and Machilus species was analysed and the resulting gene trees were used for detection of putative positively selected amino acid sites by the Codeml program implemented in the PAML package. Mean hydrophobicity profile analysis was performed with representative amino acid sequences for both Rhododendron and Machilus species by the Bioedit program. The computer program SplitTester was used to examine whether CPsHSPs of Rhododendron lineages and duplicate copies of the Machilus CPsHSPs have evolved functional divergence based on the hydrophobicity distance matrix. KEY RESULTS: Only one copy of the CPsHSP was found in Rhododendron. However, a higher evolutionary rate of amino acid substitutions in the Hymenanthes lineage of Rhododendron was inferred. Two positively selected amino acid sites may have resulted in higher hydrophobicity in the region of the alpha-crystallin domain (ACD) of the CPsHSP. By contrast, the basal angiosperm, Machilus, possessed duplicate copies of the CPsHSP, which also differed in their evolutionary rates of amino acid substitutions. However, no apparent relationship of ecological relevance toward the positively selected amino acid sites was found in Machilus. CONCLUSIONS: Divergent evolution was found for both Rhododendron lineages and the paralogues of CPsHSP in Machilus that were directed to the shift in hydrophobicity in the ACD and/or methionine-rich region, which might have played important roles in molecular chaperone activity.     

一株辛德毕斯病毒的基因组序列测定及分析

目的：对引进的一株辛德毕斯病毒的基因组序列进行测定,阐明其与已报道毒株序列的关系。方法：对辛德毕斯病毒基因组编码区进行分段RT-PCR扩增,对非编码区采用RACE法进行扩增,将扩增产物直接进行测序,应用DNAStar软件将测序结果拼接得到基因组序列,采用MEGA3.1软件对9株辛德毕斯病毒基因组序列进行系统进化发生树的构建。结果与结论：此株辛德毕斯病毒基因组共11663nt,编码3745个氨基酸残基,其中5＇端的2/3基因组编码4种非结构蛋白NSp1、NSp2、NSp3和NSp4,3＇端的1/3基因组编码5种结构蛋白E1、E2、E3、6K和C;结构基因和非结构基因之间有48nt的连接区为非翻译区;病毒基因组5＇末端和3＇末端分别有59、318nt的非编码区;序列同源性分析结果表明,此株病毒与S.A.AR86株的同源性最高,两者核苷酸序列的同源性为99.7%,氨基酸序列的同源性为99.6%,而与本室保存的另一辛德毕斯病毒MEI株的遗传进化关系稍远,系统进化发生树处于不同分支上。     

ORTHOSCOPE*: A Phylogenetic Pipeline to Infer Gene Histories from Genome-Wide Data

Comparative genome-scale analyses of protein-coding gene sequences are employed to examine evidence for whole-genome duplication and horizontal gene transfer. For this purpose, an orthogroup should be delineated to infer evolutionary history regarding each gene, and results of all orthogroup analyses need to be integrated to infer a genome-scale history. An orthogroup is a set of genes descended from a single gene in the last common ancestor of all species under consideration. However, such analyses confront several problems: 1) Analytical pipelines to infer all gene histories with methods comparing species and gene trees are not fully developed, and 2) without detailed analyses within orthogroups, evolutionary events of paralogous genes in the same orthogroup cannot be distinguished for genome-wide integration of results derived from multiple orthogroup analyses. Here I present an analytical pipeline, ORTHOSCOPE* (star), to infer evolutionary histories of animal/plant genes from genome-scale data. ORTHOSCOPE* estimates a tree for a specified gene, detects speciation/gene duplication events that occurred at nodes belonging to only one lineage leading to a species of interest, and then integrates results derived from gene trees estimated for all query genes in genome-wide data. Thus, ORTHOSCOPE* can be used to detect species nodes just after whole-genome duplications as a first step of comparative genomic analyses. Moreover, by examining the presence or absence of genes belonging to species lineages with dense taxon sampling available from the ORTHOSCOPE web version, ORTHOSCOPE* can detect genes lost in specific lineages and horizontal gene transfers. This pipeline is available at https://github.com/jun-inoue/ORTHOSCOPE_STAR.     

In silico evolutionary analysis of Helicobacter pylori outer membrane phospholipase A (OMPLA)

ABSTRACT: BACKGROUND: In the past decade, researchers have proposed that the pldA gene for outer membrane phospholipase A (OMPLA) is important for bacterial colonization of the human gastric ventricle. Several conserved Helicobacter pylori genes have distinct genotypes in different parts of the world, biogeographic patterns that can be analyzed through phylogenetic trees. The current study will shed light on the importance of the pldA gene in H. pylori. In silico sequence analysis will be used to investigate whether the bacteria are in the process of preserving, optimizing, or rejecting the pldA gene. The pldA gene will be phylogenetically compared to other housekeeping (HK) gene, and a possible origin via horizontal gene transfer (HGT) will be evaluated through both at intra- and inter-species evolutionary analyses. RESULTS: In this study, pldA gene sequences were phylogenetically analyzed and compared with a large reference set of concatenated HK gene sequences. A total of 246 pldA nucleotide sequences were used; 207 were from Norwegian isolates, 20 were from Korean isolates, and 19 were from the NCBI database. Best-fit evolutionary models were determined with MEGA5 ModelTest for the pldA (K80 + I + G) and HK (GTR + I + G) sequences, and maximum likelihood trees were constructed. Both HK and pldA genes showed biogeographic clustering. Horizontal gene transfer was inferred based on significantly different GC contents, the codon adaptation index, and a phylogenetic conflict between a tree of OMPLA protein sequences representing 171 species and a tree of the AtpA HK protein for 169 species. Although a vast majority of the residues in OMPLA were predicted to be under purifying selection, sites undergoing positive selection were also found. CONCLUSIONS: Our findings indicate that the pldA gene could have been more recently acquired than seven of the HK genes found in H. pylori. However, the common biogeographic patterns of both the HK and pldA sequences indicated that the transfer occurred long ago. Our results indicate that the bacterium is preserving the function of OMPLA, although some sites are still being evolutionarily optimized.     

Reconsideration of systematic relationships within the order Euplotida (Protista, Ciliophora) using new sequences of the gene coding for small-subunit rRNA and testing the use of combined data sets to construct phylogenies of the Diophrys-complex

Comprehensive molecular analyses of phylogenetic relationships within euplotid ciliates are relatively rare, and the relationships among some families remain questionable. We performed phylogenetic analyses of the order Euplotida based on new sequences of the gene coding for small-subunit RNA (SSrRNA) from a variety of taxa across the entire order as well as sequences from some of these taxa of other genes (ITS1-5.8S-ITS2 region and histone H4) that have not been included in previous analyses. Phylogenetic trees based on SSrRNA gene sequences constructed with four different methods had a consistent branching pattern that included the following features: (1) the “typical” euplotids comprised a paraphyletic assemblage composed of two divergent clades (family Uronychiidae and families Euplotidae–Certesiidae–Aspidiscidae–Gastrocirrhidae), (2) in the family Uronychiidae, the genera Uronychia and Paradiophrys formed a clearly outlined, well-supported clade that seemed to be rather divergent from Diophrys and Diophryopsis, suggesting that the Diophrys-complex may have had a longer and more separate evolutionary history than previously supposed, (3) inclusion of 12 new SSrRNA sequences in analyses of Euplotidae revealed two new clades of species within the family and cast additional doubt on the present classification of genera within the family, and (4) the intraspecific divergence among five species of Aspidisca was far greater than those of closely related genera. The ITS1-5.8S-ITS2 coding regions and partial histone H4 genes of six morphospecies in the Diophrys-complex were sequenced along with their SSrRNA genes and used to compare phylogenies constructed from single data sets to those constructed from combined sets. Results indicated that combined analyses could be used to construct more reliable, less ambiguous phylogenies of complex groups like the order Euplotida, because they provide a greater amount and diversity of information.     

Performance of an iterated T-HMM for homology detection

MOTIVATION: Much information about new protein sequences is derived from identifying homologous proteins. Such tasks are difficult when the evolutionary relationships are distant. Some modern methods achieve better results by building a model of a set of related sequences, and then identifying new proteins that fit the model. A further advance was the development of iterative methods that refine the model as more homologs are discovered. These methods are generally limited by ad hoc methods of sequence weighting, neglect of underlying evolutionary relationships and the representation of the set with a single one-size-fits-all model. These limitations are avoided through the use of a Tree hidden Markov model (T-HMM) approach. Our previous work described how a non-iterative version of the T-HMM method could identify distant homologs with superior performance compared with other non-iterated approaches, and described how this method was particularly appropriate for being implemented as an iterative algorithm. RESULTS: We describe an iterative version of the T-HMM algorithm, and evaluate its performance for the detection of distant homologs. Significant improvement over other commonly used methods is found. AVAILABILITY: The software (C++, Perl) is available from the corresponding author.     

节肢动物α-淀粉酶系统进化树构建及分析

目的:构建节肢动物α-淀粉酶的系统进化树,探讨其进化关系,找出进化树中聚类在一起的α-淀粉酶的特异性序列。方法:在美国国立生物技术信息中心(National Center for Biotechnology Information,NCBI)数据库中选取了56个节肢动物的α-淀粉酶氨基酸序列,利用CLUSTALX2.0进行序列比对、MEGA6.0建立进化树,通过BOXSHADE找到聚类的α-淀粉酶特异性序列。结果:56个α-淀粉酶聚类成A、B、C、D四大簇,A簇特异性序列为"VD NHD NQ",B簇特异性序列为"ID NHD NX",C簇特异性序列为"ID NHD NQ",D簇特异性序列为"XGN NHD X"。A、B、C、D四簇都含有保守的NHD(天冬酰胺-组氨酸-天冬氨酸)序列,但序列两端氨基酸种类不同。结论:56个节肢动物α-淀粉酶分为4簇,每簇都有其特异性序列,但都含有保守序列NHD。     

Morphology and angiosperm systematics in the molecular era

Several ways in which morphology is used in systematic and evolutionary research in angiosperms are shown and illustrated with examples: 1) searches for special structural similarities, which can be used to find hints for hitherto unrecognized relationships in groups with unresolved phylogenetic position; 2) cladistic studies based on morphology and combined morphological and molecular analyses; 3) comparative morphological studies in new, morphologically puzzling clades derived from molecular studies; 4) studies of morphological character evolution, unusual evolutionary directions, and evolutionary lability based on molecular studies; and 5) studies of organ evolution. Conclusions: Goals of comparative morphology have shifted in the present molecular era. Morphology no longer plays the primary role in phylogenetic studies. However, new opportunities for morphology are opening up that were not present in the premolecular era: 1) phylogenetic studies with combined molecular and morphological analyses; 2) reconstruction of the evolution of morphological features based on molecularly derived cladograms; 3) refined analysis of morphological features induced by inconsistencies of previous molecular and molecular phylogenetic analyses; 4) better understanding of morphological features by judgment in a wider biological context; 5) increased potential for including fossils in morphological analyses; and 6) exploration of the evolution of morphological traits by integration of comparative structural and molecular developmental genetic aspects (Evo-Devo); this field is still in its infancy in botany; its advancement is one of the major goals of evolutionary botany.     

GO4genome: A Prokaryotic Phylogeny Based on Genome Organization

Determining the phylogeny of closely related prokaryotes may fail in an analysis of rRNA or a small set of sequences. Whole-genome phylogeny utilizes the maximally available sample space. For a precise determination of genome similarity, two aspects have to be considered when developing an algorithm of whole-genome phylogeny: (1) gene order conservation is a more precise signal than gene content; and (2) when using sequence similarity, failures in identifying orthologues or the in situ replacement of genes via horizontal gene transfer may give misleading results. GO4genome is a new paradigm, which is based on a detailed analysis of gene function and the location of the respective genes. For characterization of genes, the algorithm uses gene ontology enabling a comparison of function independent of evolutionary relationship. After the identification of locally optimal series of gene functions, their length distribution is utilized to compute a phylogenetic distance. The outcome is a classification of genomes based on metabolic capabilities and their organization. Thus, the impact of effects on genome organization that are not covered by methods of molecular phylogeny can be studied. Genomes of strains belonging to Escherichia coli, Shigella, Streptococcus, Methanosarcina, and Yersinia were analyzed. Differences from the findings of classical methods are discussed. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Jerarca: Efficient Analysis of Complex Networks Using Hierarchical Clustering

Background

How to extract useful information from complex biological networks is a major goal in many fields, especially in genomics and proteomics. We have shown in several works that iterative hierarchical clustering, as implemented in the UVCluster program, is a powerful tool to analyze many of those networks. However, the amount of computation time required to perform UVCluster analyses imposed significant limitations to its use.

Methodology/Principal Findings

We describe the suite Jerarca, designed to efficiently convert networks of interacting units into dendrograms by means of iterative hierarchical clustering. Jerarca is divided into three main sections. First, weighted distances among units are computed using up to three different approaches: a more efficient version of UVCluster and two new, related algorithms called RCluster and SCluster. Second, Jerarca builds dendrograms based on those distances, using well-known phylogenetic algorithms, such as UPGMA or Neighbor-Joining. Finally, Jerarca provides optimal partitions of the trees using statistical criteria based on the distribution of intra- and intercluster connections. Outputs compatible with the phylogenetic software MEGA and the Cytoscape package are generated, allowing the results to be easily visualized.

Conclusions/Significance

The four main advantages of Jerarca in respect to UVCluster are: 1) Improved speed of a novel UVCluster algorithm; 2) Additional, alternative strategies to perform iterative hierarchical clustering; 3) Automatic evaluation of the hierarchical trees to obtain optimal partitions; and, 4) Outputs compatible with popular software such as MEGA and Cytoscape.