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      Extreme genetic diversity among springtails (Collembola) in subterranean calcretes of arid Australia

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          Abstract

          The subterranean islands hypothesis for calcretes of the Yilgarn region in Western Australia applies to many stygobitic (subterranean–aquatic) species that are “trapped” evolutionarily within isolated aquifers due to their aquatic lifestyles. In contrast, little is known about the distribution of terrestrial–subterranean invertebrates associated with the calcretes. We used subterranean Collembola from the Yilgarn calcretes to test the hypothesis that troglobitic species, those inhabiting the subterranean unsaturated (non-aquatic) zone of calcretes, are also restricted in their distribution and represent reciprocally monophyletic and endemic lineages. We used the barcoding fragment of the mtDNA cytochrome c oxidase subunit 1 (COI) gene from 183 individuals to reconstruct the phylogenetic history of the genus Pseudosinella Schäffer (Collembola, Lepidocyrtidae) from 10 calcretes in the Yilgarn. These calcretes represent less than 5% of the total possible calcretes in this region, yet we show that their diversity for subterranean Collembola comprises a minimum of 25 new species. Regionally, multiple levels of diversity exist in Pseudosinella, indicative of a complex evolutionary history for this genus in the Yilgarn. These species have probably been impacted by climatic oscillations, facilitating their dispersal across the landscape. The results represent a small proportion of the undiscovered diversity in Australia’s arid zone.

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          MrBayes 3.2: Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space

          Since its introduction in 2001, MrBayes has grown in popularity as a software package for Bayesian phylogenetic inference using Markov chain Monte Carlo (MCMC) methods. With this note, we announce the release of version 3.2, a major upgrade to the latest official release presented in 2003. The new version provides convergence diagnostics and allows multiple analyses to be run in parallel with convergence progress monitored on the fly. The introduction of new proposals and automatic optimization of tuning parameters has improved convergence for many problems. The new version also sports significantly faster likelihood calculations through streaming single-instruction-multiple-data extensions (SSE) and support of the BEAGLE library, allowing likelihood calculations to be delegated to graphics processing units (GPUs) on compatible hardware. Speedup factors range from around 2 with SSE code to more than 50 with BEAGLE for codon problems. Checkpointing across all models allows long runs to be completed even when an analysis is prematurely terminated. New models include relaxed clocks, dating, model averaging across time-reversible substitution models, and support for hard, negative, and partial (backbone) tree constraints. Inference of species trees from gene trees is supported by full incorporation of the Bayesian estimation of species trees (BEST) algorithms. Marginal model likelihoods for Bayes factor tests can be estimated accurately across the entire model space using the stepping stone method. The new version provides more output options than previously, including samples of ancestral states, site rates, site d N /d S rations, branch rates, and node dates. A wide range of statistics on tree parameters can also be output for visualization in FigTree and compatible software.
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            MEGA6: Molecular Evolutionary Genetics Analysis version 6.0.

            We announce the release of an advanced version of the Molecular Evolutionary Genetics Analysis (MEGA) software, which currently contains facilities for building sequence alignments, inferring phylogenetic histories, and conducting molecular evolutionary analysis. In version 6.0, MEGA now enables the inference of timetrees, as it implements the RelTime method for estimating divergence times for all branching points in a phylogeny. A new Timetree Wizard in MEGA6 facilitates this timetree inference by providing a graphical user interface (GUI) to specify the phylogeny and calibration constraints step-by-step. This version also contains enhanced algorithms to search for the optimal trees under evolutionary criteria and implements a more advanced memory management that can double the size of sequence data sets to which MEGA can be applied. Both GUI and command-line versions of MEGA6 can be downloaded from www.megasoftware.net free of charge.
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              A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences.

              Some simple formulae were obtained which enable us to estimate evolutionary distances in terms of the number of nucleotide substitutions (and, also, the evolutionary rates when the divergence times are known). In comparing a pair of nucleotide sequences, we distinguish two types of differences; if homologous sites are occupied by different nucleotide bases but both are purines or both pyrimidines, the difference is called type I (or "transition" type), while, if one of the two is a purine and the other is a pyrimidine, the difference is called type II (or "transversion" type). Letting P and Q be respectively the fractions of nucleotide sites showing type I and type II differences between two sequences compared, then the evolutionary distance per site is K = -(1/2) ln [(1-2P-Q) square root of 1-2Q]. The evolutionary rate per year is then given by k = K/(2T), where T is the time since the divergence of the two sequences. If only the third codon positions are compared, the synonymous component of the evolutionary base substitutions per site is estimated by K'S = -(1/2) ln (1-2P-Q). Also, formulae for standard errors were obtained. Some examples were worked out using reported globin sequences to show that synonymous substitutions occur at much higher rates than amino acid-altering substitutions in evolution.
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                Author and article information

                Journal
                Genome
                Genome
                Canadian Science Publishing
                0831-2796
                1480-3321
                March 2021
                March 2021
                : 64
                : 3
                : 181-195
                Affiliations
                [1 ]Australian Centre for Evolutionary Biology and Biodiversity, School of Biological Sciences, the University of Adelaide, SA 5005, Australia.
                [2 ]Biological and Earth Sciences, South Australian Museum, SA 5000, Australia.
                [3 ]University of South Australia, Clinical and Health Sciences, SA 5000, Australia.
                [4 ]South Australian Museum, North Terrace, Adelaide, SA 5000, Australia.
                [5 ]Department of Terrestrial Zoology, Western Australian Museum, Locked Bag 49, Welshpool DC, Western Australia 6986, Australia, Affiliate.
                [6 ]School of Biological Sciences, University of Western Australia, Crawley, WA 6009, Australia.
                Article
                10.1139/gen-2019-0199
                2b8304f4-50fe-4cd3-9d28-27cc8b8d3507
                © 2021

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