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.     

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。     

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     

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.     

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。     

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。