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.

18Multi-gene and genomic datasets have become commonplace in the field of 19 phylogenetics, but many of the existing tools are not designed for such datasets, 20 which makes the analysis time-consuming and tedious. We therefore present 21 PhyloSuite, a user-friendly workflow desktop platform dedicated to streamlining 22 molecular sequence data management and evolutionary phylogenetics studies. It 23 employs a plugin-based system that integrates a number of useful phylogenetic and 24 bioinformatic tools, thereby streamlining the entire procedure, from data acquisition 25 to phylogenetic tree annotation, with the following features: (i) point-and-click and 26 drag-and-drop graphical user interface, (ii) a workspace to manage and organize 27 molecular sequence data and results of analyses, (iii) GenBank entries extraction and 28 comparative statistics, (iv) a phylogenetic workflow with batch processing capability, 29(v) elaborate bioinformatic analysis for mitochondrial genomes. The aim of 30 PhyloSuite is to enable researchers to spend more time playing with scientific 31 questions, instead of wasting it on conducting standard analyses. The compiled binary 32 of PhyloSuite is available under the GPL license at 33 https://github.com/dongzhang0725/PhyloSuite/releases, implemented in Python and 34 runs on Windows, Mac OSX and Linux. 35 36 37 Advancements in next-generation sequencing technologies (Metzker, 2009) have 38 resulted in a huge increase in the amount of genetic data available through public 39 databases. While this opens a multitude of research possibilities, retrieving and 40 managing such large amounts of data may be difficult and time-consuming for 41 researchers who are not computer-savvy. A standard analytical procedure for 42 phylogenetic analysis is: selecting and downloading GenBank entries, extracting 43 target genes (for multi-gene datasets, such as organelle genomes) and/or mining other 44 data, sequence alignment, alignment optimization, concatenation of alignments (for 45 multi-gene datasets), selection of best-fit partitioning schemes and evolutionary 46 models, phylogeny reconstruction, and finally visualization and annotation of the 47 phylogram. This can be very time-consuming if different programs have to be 48 employed for different steps, especially as they often have different input file format 49 requirements, and sometimes even require manual file tweaking. Therefore, 50 multifunctional, workflow-type software packages are becoming increasingly needed 51 by a broad range of evolutionary biologists (Smith, 2015). Specifically, as single-gene 52 datasets are rapidly being replaced by multi-gene or genomic datasets as a tool of 53 choice for phylogenetic reconstruction (Degnan and Rosenberg, 2009; Rivera-Rivera 54 and Montoya-Burgos, 2016), automated gene extraction from genomic data and batch 55 manipulation in some of the above steps, like alignment, are becoming a necessity. 56 Although there are several tools in existence, designed to streamline this process 57 by incorporat...

The genomic signatures of positive selection and evolutionary constraints can be detected by analyses of nucleotide sequences. One of the most widely used programs for this purpose is CodeML, part of the PAML package. Although a number of bioinformatics tools have been developed to facilitate the use of CodeML, these have various limitations. Here, we present a wrapper tool named EasyCodeML that provides a user‐friendly graphical interface for using CodeML. EasyCodeML has a custom running mode in which parameters can be adjusted to meet different requirements. It also offers a preset running mode in which an evolutionary analysis pipeline and publication‐quality tables can be exported by a single click. EasyCodeML allows visualized, interactive tree labelling, which greatly simplifies the use of the branch, branch‐site, and clade models of selection. The program allows comparison of major codon‐based models for analyses of selection. EasyCodeML is a stand‐alone package that is supported in Windows, Mac, and Linux operating systems, and is freely available at https://github.com/BioEasy/EasyCodeML .

Rice stripe virus (RSV) is one of the most economically important pathogens of rice and is repeatedly epidemic in China, Japan and Korea. The most recent outbreak of RSV in eastern China in 2000 caused significant losses and raised serious concerns. In this paper, we provide a genotyping profile of RSV field isolates and describe the population structure of RSV in China, based on the nucleotide sequences of isolates collected from different geographical regions during 1997-2004. RSV isolates could be divided into two or three subtypes, depending on which gene was analysed. The genetic distances between subtypes range from 0.050 to 0.067. The population from eastern China is composed only of subtype I/IB isolates. In contrast, the population from Yunnan province (southwest China) is composed mainly of subtype II isolates, but also contains a small proportion of subtype I/IB isolates and subtype IA isolates. However, subpopulations collected from different districts in eastern China or Yunnan province are not genetically differentiated and show frequent gene flow. RSV genes were found to be under strong negative selection. Our data suggest that the most recent outbreak of RSV in eastern China was not due to the invasion of new RSV subtype(s). The evolutionary processes contributing to the observed genetic diversity and population structure are discussed.