PhyloSuite: an integrated and scalable desktop platform for streamlined molecular sequence data management and evolutionary phylogenetics studies

Abstract

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...

Mitochondrial architecture rearrangements produce asymmetrical nonadaptive mutational pressures that subvert the phylogenetic reconstruction in Isopoda

“…PhyloSuite (Zhang et al, 2018) was used to batch-download all selected mitogenomes from the GenBank, extract genomic features, translate genes into amino acid sequences, semi-automatically re-annotate ambiguously annotated tRNA genes with the help of the ARWEN (Laslett & Canbäck, 2008) output, automatically replace the GenBank taxonomy with the WoRMS database taxonomy, as the latter tends to be more up to date (Costello et al, 2013), generate comparative genome statistics tables, and conduct phylogenetic analyses (Flowchart mode) using a number of incorporated plug-in programs. Nucleotide and amino acid sequences of protein-coding genes (PCGs) were aligned in batches (using codon and normal-alignment modes respectively) with ‘--auto’ strategy, whereas rRNA genes (including the nuclear 18S ) were aligned using Q-INS-i algorithm, which takes secondary structure information into account, all implemented in MAFFT (Katoh & Standley, 2013; Katoh & Toh, 2008).…”

The complete mitochondrial genome of Eysarcoris guttigerus (Hemiptera: Pentatomidae)

“…tRNAs were identified with MITOS2 (Bernt et al 2013), rRNAs and A þ T-rich region were determined by the bound- ary of tRNAs. Phylogenetic tree was constructed with whole mitogenome sequences of Pentatomidae using PhyloSuite (Zhang et al 2019). The mitogenomic size of E. guttigerus (MN831205) is 15,368 bp.…”

Complete mitochondrial genome of the Endangered long-armed scarab Cheirotonus gestroi (Coleoptera: Euchiridae)

“…In order to validate the phylogenetic position of C. gestroi, the mitogenomes of 15 species in superfamily Scarabaeoidea and the outgroup Euspilotus scissus (Coleoptera: Histeridae) were used to construct the maximum likelihood (ML) tree. The ML inference was performed using IQ-TREE (Nguyen et al 2015) in PhyloSuite (Zhang et al 2020) with 10,000 ultrafast bootstrap replicates. The result indicates that C. gestroi has the closest evolutionary relationship with the same genus species C. jansoni.…”