ArticleMethods in molecular biology (Clifton, N.J.)2022
Dating Microbial Evolution with MCMCtree.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Article
- Complex multicellularity is linked with expanded specialized metabolite production in microorganisms.Nature microbiology · 2026Article
- Genomic landscape and genetic manipulation of an ectoparasitoid wasp, Gregopimpla kuwanae.Communications biology · 2026Article
- Phylogenetic reconciliation provides new insights into the evolutionary diversification of the glutamine synthetase gene family in seed plants.The FEBS journal · 2026Article
- Genome diversification of symbiotic fungi in beetle-fungus mutualistic symbioses.The ISME journal · 2026Article
- Phylogenomic, Morphological, and Phylogenetic Evidence Reveals Five New Species and Two New Host Records ofBiology · 2025Article
- Chromosome-scale genome assembly ofFrontiers in plant science · 2024Article
- Comparative analysis of organellar genomes between diploid and tetraploidFrontiers in plant science · 2023Article
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1 author.
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Abstract
This protocol explains how to use the program MCMCtree to estimate divergence times in microbial phylogenies. The main advantage of MCMCtree is the implementation of an approximation to the molecular data likelihood that dramatically speeds up computation during Bayesian MCMC sampling of divergence times and evolutionary rates. The approximation allows the analysis of large phylogenies with hundreds of taxa and molecular alignments with thousands or millions of sites. Two examples are used to illustrate Bayesian clock dating with MCMCtree. The first is a phylogeny of (mostly) microbial eukaryotes and prokaryotes encompassing the major groups of life on Earth, and for which fossil information, to calibrate the nodes of the phylogeny, is available. The second is a phylogeny of influenza viruses with known sampling times. An overview of Bayesian MCMC sampling is given as well as practical advice on issues such as construction of the time and rate prior and assessment of convergence of MCMC chains. Strategies for estimating times in microbial phylogenies for which neither fossil information nor sampling times are known are discussed.
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