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 phylogeny of Isopoda, a speciose order of crustaceans, remains unresolved, with different data sets (morphological, nuclear, mitochondrial) often producing starkly incongruent phylogenetic hypotheses. We hypothesized that extreme diversity in their life histories might be causing compositional heterogeneity/heterotachy in their mitochondrial genomes, and compromising the phylogenetic reconstruction. We tested the effects of different data sets (mitochondrial, nuclear, nucleotides, amino acids, concatenated genes, individual genes, gene orders), phylogenetic algorithms (assuming data homogeneity, heterogeneity, and heterotachy), and partitioning; and found that almost all of them produced unique topologies. As we also found that mitogenomes of Asellota and two Cymothoida families (Cymothoidae and Corallanidae) possess inversed base (GC) skew patterns in comparison to other isopods, we concluded that inverted skews cause long-branch attraction phylogenetic artifacts between these taxa. These asymmetrical skews are most likely driven by multiple independent inversions of origin of replication (i.e., nonadaptive mutational pressures). Although the PhyloBayes CAT-GTR algorithm managed to attenuate some of these artifacts (and outperform partitioning), mitochondrial data have limited applicability for reconstructing the phylogeny of Isopoda. Regardless of this, our analyses allowed us to propose solutions to some unresolved phylogenetic debates, and support Asellota are the most likely candidate for the basal isopod branch. As our findings show that architectural rearrangements might produce major compositional biases even on relatively short evolutionary timescales, the implications are that proving the suitability of data via composition skew analyses should be a prerequisite for every study that aims to use mitochondrial data for phylogenetic reconstruction, even among closely related taxa.
BackgroundComplete mitochondrial genomes are much better suited for the taxonomic identification and phylogenetic studies of nematodes than morphology or traditionally-used molecular markers, but they remain unavailable for the entire Camallanidae family (Chromadorea). As the only published mitogenome in the Camallanina suborder (Dracunculoidea superfamily) exhibited a unique gene order, the other objective of this research was to study the evolution of mitochondrial architecture in the Spirurida order. Thus, we sequenced the complete mitogenome of the Camallanus cotti fish parasite and conducted structural and phylogenomic comparative analyses with all available Spirurida mitogenomes.ResultsThe mitogenome is exceptionally large (17,901 bp) among the Chromadorea and, with 46 (pseudo-) genes, exhibits a unique architecture among nematodes. Six protein-coding genes (PCGs) and six tRNAs are duplicated. An additional (seventh) tRNA (Trp) was probably duplicated by the remolding of tRNA-Ser2 (missing). Two pairs of these duplicated PCGs might be functional; three were incomplete and one contained stop codons. Apart from Ala and Asp, all other duplicated tRNAs are conserved and probably functional. Only 19 unique tRNAs were found. Phylogenomic analysis included Gnathostomatidae (Spirurina) in the Camallanina suborder.ConclusionsWithin the Nematoda, comparable PCG duplications were observed only in the enoplean Mermithidae family, but those result from mitochondrial recombination, whereas characteristics of the studied mitogenome suggest that likely rearrangement mechanisms are either a series of duplications, transpositions and random loss events, or duplication, fragmentation and subsequent reassembly of the mitogenome. We put forward a hypothesis that the evolution of mitogenomic architecture is extremely discontinuous, and that once a long period of stasis in gene order and content has been punctuated by a rearrangement event, such a destabilised mitogenome is much more likely to undergo subsequent rearrangement events, resulting in an exponentially accelerated evolutionary rate of mitogenomic rearrangements. Implications of this model are particularly important for the application of gene order similarity as an additive source of phylogenetic information. Chromadorean nematodes, and particularly Camallanina clade (with C. cotti as an example of extremely accelerated rate of rearrangements), might be a good model to further study this discontinuity in the dynamics of mitogenomic evolution.Electronic supplementary materialThe online version of this article (doi: 10.1186/s12864-017-4237-x) contains supplementary material, which is available to authorized users.
Diet is known to influence intestinal microbiota in fish, but the specifics of these impacts are still poorly understood. Different protein/fibre ratio diets may result in differing structures and activities of gut microbiota. We examined the hindgut
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.