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Life Sciences · Biochemistry, Genetics and Molecular Biology

Evolution and Genetic Dynamics
Research Guide

What is Evolution and Genetic Dynamics?

Evolution and Genetic Dynamics is the study of evolutionary processes driving genetic adaptation and mutation, encompassing experimental evolution, fitness landscapes, population genetics, microbial evolution, and host-parasite coevolution under selective pressures.

This field includes 73,543 works exploring mechanisms and consequences of genetic changes in response to selective pressures. Key tools like MEGA software enable comparative analysis of molecular sequence data for reconstructing evolutionary histories and inferring selective forces, as in "MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0" (2013) with 47,452 citations. Foundational methods such as bootstrapping provide confidence limits on phylogenies, introduced in "CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP" (1985) by Felsenstein with 40,908 citations.

Topic Hierarchy

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graph TD D["Life Sciences"] F["Biochemistry, Genetics and Molecular Biology"] S["Genetics"] T["Evolution and Genetic Dynamics"] D --> F F --> S S --> T style T fill:#DC5238,stroke:#c4452e,stroke-width:2px
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73.5K
Papers
N/A
5yr Growth
1.9M
Total Citations

Research Sub-Topics

Fitness Landscapes in Experimental Evolution

This sub-topic investigates the structure, ruggedness, and accessibility of fitness landscapes using microbial experimental evolution systems. Researchers map mutational effects, epistasis, and evolutionary trajectories through serial passaging and sequencing.

15 papers

Population Genetics of Adaptation

Researchers analyze genetic variation patterns, allele frequency trajectories, and selective sweeps during laboratory adaptation experiments. This includes hitchhiking effects, linkage disequilibrium, and coalescent-based inference of selection strengths.

15 papers

Microbial Experimental Evolution

This area employs bacteria, yeast, and viruses in controlled evolution experiments to study mutation rates, innovation, and parallel evolution under defined selective pressures. Studies track phenotypic and genomic changes over thousands of generations.

15 papers

Host-Parasite Coevolution Dynamics

Investigations explore Red Queen dynamics, arms-race coevolution, and specificity evolution in host-parasite systems using experimental microcosms. Researchers quantify coevolutionary rates, genetic correlations, and virulence-transmission tradeoffs.

15 papers

Mutation Supply and Evolutionary Innovation

This sub-topic examines how mutation rates, population size, and recombination influence evolutionary innovation and adaptation speed in asexual and sexual populations. Studies use fluctuation tests and directed evolution to quantify mutational input effects.

15 papers

Why It Matters

Evolution and Genetic Dynamics supports phylogenomics and phylomedicine through tools like MEGA X, which enables cross-platform analysis without virtualization for building timetrees of species, pathogens, and gene families, as detailed in "MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms" (2018) by Kumar et al. with 36,957 citations. Population genetic analyses of codominant, haploid, and binary data, including heterozygosity, F statistics, Nei's genetic distance, and population assignment, are facilitated by genalex 6 running in Microsoft Excel, per "<scp>genalex</scp> 6: genetic analysis in Excel. Population genetic software for teaching and research" (2005) by Peakall and Smouse with 16,482 citations. Model selection for DNA substitution, using log likelihood scores in MODELTEST, aids accurate evolutionary rate estimation, as in "MODELTEST: testing the model of DNA substitution" (1998) by Posada and Crandall with 20,036 citations.

Reading Guide

Where to Start

"MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0" by Tamura et al. (2013) because it provides a comprehensive entry to computational tools for molecular evolution analysis with broad applicability and 47,452 citations.

Key Papers Explained

Tamura et al. (2011) in "MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum Likelihood, Evolutionary Distance, and Maximum Parsimony Methods" established core methods for sequence analysis, which Tamura et al. (2013) advanced in "MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0" with timetree building, and Kumar et al. (2018) extended cross-platform in "MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms". Felsenstein (1985) laid statistical foundations in "CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP", complemented by Posada and Crandall (1998) model testing in "MODELTEST: testing the model of DNA substitution." Tamura et al. (2021) updated to MEGA11 for enhanced tools.

Paper Timeline

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graph LR P0["A simple method for estimating e...
1980 · 29.3K cites"] P1["CONFIDENCE LIMITS ON PHYLOGENIES...
1985 · 40.9K cites"] P2["MODELTEST: testing the model of ...
1998 · 20.0K cites"] P3["MEGA5: Molecular Evolutionary Ge...
2011 · 40.1K cites"] P4["MEGA6: Molecular Evolutionary Ge...
2013 · 47.5K cites"] P5["MEGA X: Molecular Evolutionary G...
2018 · 37.0K cites"] P6["MEGA11: Molecular Evolutionary G...
2021 · 20.0K cites"] P0 --> P1 P1 --> P2 P2 --> P3 P3 --> P4 P4 --> P5 P5 --> P6 style P4 fill:#DC5238,stroke:#c4452e,stroke-width:2px
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Most-cited paper highlighted in red. Papers ordered chronologically.

Advanced Directions

Recent versions like MEGA11 by Tamura et al. (2021) expand timetree capabilities for pathogens and gene families, building on prior MEGA iterations without new preprints or news indicating shifts.

Papers at a Glance

# Paper Year Venue Citations Open Access
1 MEGA6: Molecular Evolutionary Genetics Analysis Version 6.0 2013 Molecular Biology and ... 47.5K
2 CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP 1985 Evolution 40.9K
3 MEGA5: Molecular Evolutionary Genetics Analysis Using Maximum ... 2011 Molecular Biology and ... 40.1K
4 MEGA X: Molecular Evolutionary Genetics Analysis across Comput... 2018 Molecular Biology and ... 37.0K
5 A simple method for estimating evolutionary rates of base subs... 1980 Journal of Molecular E... 29.3K
6 MEGA11: Molecular Evolutionary Genetics Analysis Version 11 2021 Molecular Biology and ... 20.0K
7 MODELTEST: testing the model of DNA substitution. 1998 Bioinformatics 20.0K
8 Confidence Limits on Phylogenies: An Approach Using the Bootstrap 1985 Evolution 19.2K
9 The genetical theory of natural selection 1930 Clarendon Press eBooks 17.6K
10 <scp>genalex</scp> 6: genetic analysis in Excel. Population ge... 2005 Molecular Ecology Notes 16.5K

Frequently Asked Questions

What is MEGA software?

MEGA is computational software for molecular evolutionary genetics analysis, implementing methods for phylogenomics, timetrees of species and pathogens, and inference of selective forces. Versions like MEGA6 (Tamura et al., 2013) and MEGA X (Kumar et al., 2018) support maximum likelihood, evolutionary distance, and maximum parsimony methods across platforms.

How does the bootstrap method work for phylogenies?

The bootstrap method resamples data points with replacement to create replicate samples, analyzes each for phylogenies, and places confidence intervals on branches. Felsenstein (1985) introduced this in "CONFIDENCE LIMITS ON PHYLOGENIES: AN APPROACH USING THE BOOTSTRAP", enabling statistical assessment of tree reliability.

What does MODELTEST do?

MODELTEST uses log likelihood scores to select the best-fitting model of DNA substitution for phylogenetic analysis. Posada and Crandall (1998) developed it to improve accuracy in evolutionary studies.

How are evolutionary rates of base substitutions estimated?

Evolutionary rates are estimated through comparative studies of nucleotide sequences using simple methods. Kimura (1980) provided such a method in "A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences".

What analyses does genalex 6 perform?

genalex 6 conducts population genetic analyses including allele frequencies, heterozygosity, F statistics, Nei's genetic distance, and population assignment for codominant, haploid, and binary data in Excel. Peakall and Smouse (2005) designed it for teaching and research.

Open Research Questions

  • ? How can fitness landscapes be accurately mapped in microbial evolution under varying selective pressures?
  • ? What are the precise dynamics of host-parasite coevolution at the genetic level?
  • ? How do mutation rates interact with population genetics to drive adaptation in experimental evolution?
  • ? What improvements are needed in timetree construction for gene families and pathogens?
  • ? How can experimental evolution reveal consequences of genetic changes beyond current models?

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