| 2. |
- Rands, Chris M., et al.
(författare)
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Insights into the evolution of Darwin's finches from comparative analysis of the Geospiza magnirostris genome sequence
- 2013
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Ingår i: BMC Genomics. - : Springer Science and Business Media LLC. - 1471-2164. ; 14, s. 95-
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Tidskriftsartikel (refereegranskat)abstract
- Background: A classical example of repeated speciation coupled with ecological diversification is the evolution of 14 closely related species of Darwin's (Galapagos) finches (Thraupidae, Passeriformes). Their adaptive radiation in the Galapagos archipelago took place in the last 2-3 million years and some of the molecular mechanisms that led to their diversification are now being elucidated. Here we report evolutionary analyses of genome of the large ground finch, Geospiza magnirostris. Results: 13,291 protein-coding genes were predicted from a 991.0 Mb G. magnirostris genome assembly. We then defined gene orthology relationships and constructed whole genome alignments between the G. magnirostris and other vertebrate genomes. We estimate that 15% of genomic sequence is functionally constrained between G. magnirostris and zebra finch. Genic evolutionary rate comparisons indicate that similar selective pressures acted along the G. magnirostris and zebra finch lineages suggesting that historical effective population size values have been similar in both lineages. 21 otherwise highly conserved genes were identified that each show evidence for positive selection on amino acid changes in the Darwin's finch lineage. Two of these genes (Igf2r and Pou1f1) have been implicated in beak morphology changes in Darwin's finches. Five of 47 genes showing evidence of positive selection in early passerine evolution have cilia related functions, and may be examples of adaptively evolving reproductive proteins. Conclusions: These results provide insights into past evolutionary processes that have shaped G. magnirostris genes and its genome, and provide the necessary foundation upon which to build population genomics resources that will shed light on more contemporaneous adaptive and non-adaptive processes that have contributed to the evolution of the Darwin's finches.
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| 3. |
- Ronquist, Fredrik, et al.
(författare)
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MrBayes 3.2 : Efficient Bayesian Phylogenetic Inference and Model Choice Across a Large Model Space
- 2012
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Ingår i: Systematic Biology. - : Oxford University Press (OUP). - 1063-5157 .- 1076-836X. ; 61:3, s. 539-542
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Tidskriftsartikel (refereegranskat)abstract
- 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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