Five new species of the long-legged sac spider genus Cheiracanthium C.L. Koch, 1839 (Araneae: Cheiracanthiidae) from China

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Abstract

Five species of the cheiracanthiid spider genus Cheiracanthium C.L. Koch, 1839 collected from China are diagnosed and described as new to science based on morphological characters: Cheiracanthium arcilongum sp. nov. (♂♀) from Yunnan, C. circulum sp. nov. (♂♀) from Yunnan, C. digitatum sp. nov. (♂♀) from Anhui, C. jiuquan sp. nov. (♂♀) from Guangxi and C. xinjiangense sp. nov. (♂♀) from Xinjiang. In addition, the photos of the habitus, copulatory organs and distribution map are provided for all species. However, DNA barcodes information is only provided for four species.

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MAFFT Multiple Sequence Alignment Software Version 7: Improvements in Performance and Usability

Kazutaka Katoh, Daron Standley (2013)

We report a major update of the MAFFT multiple sequence alignment program. This version has several new features, including options for adding unaligned sequences into an existing alignment, adjustment of direction in nucleotide alignment, constrained alignment and parallel processing, which were implemented after the previous major update. This report shows actual examples to explain how these features work, alone and in combination. Some examples incorrectly aligned by MAFFT are also shown to clarify its limitations. We discuss how to avoid misalignments, and our ongoing efforts to overcome such limitations.

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trimAl: a tool for automated alignment trimming in large-scale phylogenetic analyses

Salvador Capella-Gutiérrez, José Silla-Martínez, Toni Gabaldón (2009)

Summary: Multiple sequence alignments are central to many areas of bioinformatics. It has been shown that the removal of poorly aligned regions from an alignment increases the quality of subsequent analyses. Such an alignment trimming phase is complicated in large-scale phylogenetic analyses that deal with thousands of alignments. Here, we present trimAl, a tool for automated alignment trimming, which is especially suited for large-scale phylogenetic analyses. trimAl can consider several parameters, alone or in multiple combinations, for selecting the most reliable positions in the alignment. These include the proportion of sequences with a gap, the level of amino acid similarity and, if several alignments for the same set of sequences are provided, the level of consistency across different alignments. Moreover, trimAl can automatically select the parameters to be used in each specific alignment so that the signal-to-noise ratio is optimized. Availability: trimAl has been written in C++, it is portable to all platforms. trimAl is freely available for download (http://trimal.cgenomics.org) and can be used online through the Phylemon web server (http://phylemon2.bioinfo.cipf.es/). Supplementary Material is available at http://trimal.cgenomics.org/publications. Contact: tgabaldon@crg.es

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MEGA11: Molecular Evolutionary Genetics Analysis Version 11

Koichiro Tamura, Glen Stecher, Sudhir Kumar (2021)

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 .