With its theoretical basis firmly established in molecular evolutionary and population genetics, the comparative DNA and protein sequence analysis plays a central role in reconstructing the evolutionary histories of species and multigene families, estimating rates of molecular evolution, and inferring the nature and extent of selective forces shaping the evolution of genes and genomes. The scope of these investigations has now expanded greatly owing to the development of high-throughput sequencing techniques and novel statistical and computational methods. These methods require easy-to-use computer programs. One such effort has been to produce Molecular Evolutionary Genetics Analysis (MEGA) software, with its focus on facilitating the exploration and analysis of the DNA and protein sequence variation from an evolutionary perspective. Currently in its third major release, MEGA3 contains facilities for automatic and manual sequence alignment, web-based mining of databases, inference of the phylogenetic trees, estimation of evolutionary distances and testing evolutionary hypotheses. This paper provides an overview of the statistical methods, computational tools, and visual exploration modules for data input and the results obtainable in MEGA.

/pdf/mega3-integrated-software-for-molecular-evolutionary-1hk8vjhymf.pdf

MEGA3: Integrated software for Molecular Evolutionary Genetics Analysis and sequence alignment

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

PAML, currently in version 4, is a package of programs for phylogenetic analyses of DNA and protein sequences using maximum likelihood (ML). The programs may be used to compare and test phylogenetic trees, but their main strengths lie in the rich repertoire of evolutionary models implemented, which can be used to estimate parameters in models of sequence evolution and to test interesting biological hypotheses. Uses of the programs include estimation of synonymous and nonsynonymous rates (d(N) and d(S)) between two protein-coding DNA sequences, inference of positive Darwinian selection through phylogenetic comparison of protein-coding genes, reconstruction of ancestral genes and proteins for molecular restoration studies of extinct life forms, combined analysis of heterogeneous data sets from multiple gene loci, and estimation of species divergence times incorporating uncertainties in fossil calibrations. This note discusses some of the major applications of the package, which includes example data sets to demonstrate their use. The package is written in ANSI C, and runs under Windows, Mac OSX, and UNIX systems. It is available at -- (http://abacus.gene.ucl.ac.uk/software/paml.html).

/pdf/paml-4-phylogenetic-analysis-by-maximum-likelihood-2gg19rsgos.pdf

PAML 4: Phylogenetic Analysis by Maximum Likelihood

We have produced a draft sequence of the rice genome for the most widely cultivated subspecies in China, Oryza sativa L. ssp. indica, by whole-genome shotgun sequencing. The genome was 466 megabases in size, with an estimated 46,022 to 55,615 genes. Functional coverage in the assembled sequences was 92.0%. About 42.2% of the genome was in exact 20-nucleotide oligomer repeats, and most of the transposons were in the intergenic regions between genes. Although 80.6% of predicted Arabidopsis thaliana genes had a homolog in rice, only 49.4% of predicted rice genes had a homolog in A. thaliana. The large proportion of rice genes with no recognizable homologs is due to a gradient in the GC-content of rice coding sequences.

/pdf/a-draft-sequence-of-the-rice-genome-oryza-sativa-l-ssp-5212kgt1ff.pdf

A draft sequence of the rice genome (Oryza sativa L. ssp indica)

Evolution of Protein Molecules

Summary: PowerMarker delivers a data-driven, integrated analysis environment (IAE) for genetic data. The IAE integrates data management, analysis and visualization in a user-friendly graphical user interface. It accelerates the analysis lifecycle and enables users to maintain data integrity throughout the process. An ever-growing list of more than 50 different statistical analyses for genetic markers has been implemented in PowerMarker.

Availability: www.powermarker.net

Contact: powermarker@hotmail.com

PowerMarker: an integrated analysis environment for genetic marker analysis

Summary: The HyPhypackage is designed to provide a flexible and unified platform for carrying out likelihood-based analyses on multiple alignments of molecular sequence data, with the emphasis on studies of rates and patterns of sequence evolution.

Availability: http://www.hyphy.org

Contact: muse@stat.ncsu.edu

Supplementary information:HyPhydocumentation and tutorials are available at http://www.hyphy.org

/pdf/hyphy-hypothesis-testing-using-phylogenies-4wgvy3cz0b.pdf

HyPhy: hypothesis testing using phylogenies

A model of DNA sequence evolution applicable to coding regions is presented. This represents the first evolutionary model that accounts for dependencies among nucleotides within a codon. The model uses the codon, as opposed to the nucleotide, as the unit of evolution, and is parameterized in terms of synonymous and nonsynonymous nucleotide substitution rates. One of the model's advantages over those used in methods for estimating synonymous and nonsynonymous substitution rates is that it completely corrects for multiple hits at a codon, rather than taking a parsimony approach and considering only pathways of minimum change between homologous codons. Likelihood-ratio versions of the relative-rate test are constructed and applied to data from the complete chloroplast DNA sequences of Oryza sativa, Nicotiana tabacum, and Marchantia polymorpha. Results of these tests confirm previous findings that substitution rates in the chloroplast genome are subject to both lineage-specific and locus-specific effects. Additionally, the new tests suggest tha the rate heterogeneity is due primarily to differences in nonsynonymous substitution rates. Simulations help confirm previous suggestions that silent sites are saturated, leaving no evidence of heterogeneity in synonymous substitution rates.

/pdf/a-likelihood-approach-for-comparing-synonymous-and-3nxu4s0nho.pdf

A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome.

Two hundred and sixty maize inbred lines, representative of the genetic diversity among essentially all public lines of importance to temperate breeding and many important tropical and subtropical lines, were assayed for polymorphism at 94 microsatellite loci. The 2039 alleles identified served as raw data for estimating genetic structure and diversity. A model-based clustering analysis placed the inbred lines in five clusters that correspond to major breeding groups plus a set of lines showing evidence of mixed origins. A "phylogenetic" tree was constructed to further assess the genetic structure of maize inbreds, showing good agreement with the pedigree information and the cluster analysis. Tropical and subtropical inbreds possess a greater number of alleles and greater gene diversity than their temperate counterparts. The temperate Stiff Stalk lines are on average the most divergent from all other inbred groups. Comparison of diversity in equivalent samples of inbreds and open-pollinated landraces revealed that maize inbreds capture <80% of the alleles in the landraces, suggesting that landraces can provide additional genetic diversity for maize breeding. The contributions of four different segments of the landrace gene pool to each inbred group's gene pool were estimated using a novel likelihood-based model. The estimates are largely consistent with known histories of the inbreds and indicate that tropical highland germplasm is poorly represented in maize inbreds. Core sets of inbreds that capture maximal allelic richness were defined. These or similar core sets can be used for a variety of genetic applications in maize.

https://www.genetics.org/content/genetics/165/4/2117.full.pdf

Genetic Structure and Diversity Among Maize Inbred Lines as Inferred From DNA Microsatellites

Inference of how evolutionary forces have shaped extant genetic diversity is a cornerstone of modern comparative sequence analysis. Advances in sequence generation and increased statistical sophistication of relevant methods now allow researchers to extract ever more evolutionary signal from the data, albeit at an increased computational cost. Here, we announce the release of Datamonkey 2.0, a completely re-engineered version of the Datamonkey web-server for analyzing evolutionary signatures in sequence data. For this endeavor, we leveraged recent developments in open-source libraries that facilitate interactive, robust, and scalable web application development. Datamonkey 2.0 provides a carefully curated collection of methods for interrogating coding-sequence alignments for imprints of natural selection, packaged as a responsive (i.e. can be viewed on tablet and mobile devices), fully interactive, and API-enabled web application. To complement Datamonkey 2.0, we additionally release HyPhy Vision, an accompanying JavaScript application for visualizing analysis results. HyPhy Vision can also be used separately from Datamonkey 2.0 to visualize locally executed HyPhy analyses. Together, Datamonkey 2.0 and HyPhy Vision showcase how scientific software development can benefit from general-purpose open-source frameworks. Datamonkey 2.0 is freely and publicly available at http://www.datamonkey.org, and the underlying codebase is available from https://github.com/veg/datamonkey-js.

/pdf/datamonkey-2-0-a-modern-web-application-for-characterizing-1nuq81zn18.pdf

Spencer V. Muse

Papers

PowerMarker: an integrated analysis environment for genetic marker analysis

HyPhy: hypothesis testing using phylogenies

A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome.

Genetic Structure and Diversity Among Maize Inbred Lines as Inferred From DNA Microsatellites

Datamonkey 2.0: A Modern Web Application for Characterizing Selective and Other Evolutionary Processes.