Karyotype evolution and flexible (conventional versus inverted) meiosis in insects with holocentric chromosomes: a case study based on Polyommatus butterflies

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Abstract

The Polyommatus butterflies have holocentric chromosomes, which are characterized by kinetic activity distributed along the entire chromosome length, and the highest range of haploid chromosome numbers (n) known within a single eukaryotic genus (from n = 10 to n = 226). Previous analyses have shown that these numbers most likely evolved gradually from an ancestral karyotype, in accordance with the Brownian motion model of chromosome change accumulation. Here we studied chromosome sets within a monophyletic group of previously non-karyotyped Polyommatus species. We demonstrate that these species have a limited interspecific chromosome number variation from n = 16 to n = 25, which is consistent with the Brownian motion model prediction. We also found intra- and interpopulation variation in the chromosome numbers. These findings support the model of karyotype evolution through the gradual accumulation of neutral or weakly underdominant rearrangements that can persist in the heterozygous state within a population. For Polyommatus poseidonides we report the phenomenon of flexible meiosis in which the chromosome multivalents are able to undergo either conventional or inverted meiosis within the same individual. We hypothesise that the ability to invert the order of the meiotic events may be adaptive and can facilitate proper chromosome segregation in chromosomal heterozygotes, thus promoting rapid karyotype evolution.

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

Fredrik Ronquist, Maxim Teslenko, Paul van der Mark … (2012)

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.