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Mutations

Mutations

Mutations

Mutations

Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
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Viral Mutations

Viral Mutations

A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...

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Mutation, Gene Flow, and Genetic Drift

Mutation, Gene Flow, and Genetic Drift

In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).

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Predicting mutational routes to new adaptive phenotypes.

Peter A Lind^1,2, Eric Libby^1,3,4, Jenny Herzog¹

¹New Zealand Institute for Advanced Study, Massey University at Albany, Auckland, New Zealand.

|January 9, 2019

Summary

This summary is machine-generated.

Predicting bacterial evolution is complex. This study models evolutionary pathways in Pseudomonas fluorescens, revealing mutation hotspots and fitness effects that challenge current predictive models.

Keywords:

Pseudomonas fluorescens c-di-GMP evolutionary biology evolutionary forecasting experimental evolution genetic architecture genetics genomics wrinkly spreader

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Area of Science:

Evolutionary biology
Microbial genetics
Systems biology

Background:

Predicting evolutionary trajectories remains a significant challenge in biology.
The model bacterium *Pseudomonas fluorescens* offers a known genotype-to-phenotype map for studying adaptive evolution.
Understanding the genetic basis of adaptation is crucial for forecasting evolutionary change.

Purpose of the Study:

To develop and test mechanistic models for predicting evolutionary rates and mutational targets.
To investigate the regulatory pathways governing the evolution of the 'wrinkly spreader' (WS) phenotype in *P. fluorescens*.
To identify discrepancies between predicted and observed mutational patterns and their underlying causes.

Main Methods:

Mathematical modeling of three key regulatory pathways involved in WS evolution.
Experimental determination of mutation rates and targets within these pathways.
Comparative analysis of mutation spectra with and without selection to assess fitness effects.

Main Results:

Mathematical models predicted mutation rates and targets for WS evolution.
Unanticipated mutational hotspots led to deviations from initial predictions.
Refined models incorporating additional data better explained experimental observations.
A mismatch in mutation spectra under selection versus no selection was observed due to previously unknown low-fitness mutations.

Conclusions:

Mechanistic models can aid in forecasting evolutionary processes, but limitations exist.
Predicting locus-specific mutational biases and fitness effects presents significant challenges.
Further research is needed to refine models for accurate evolutionary prediction, especially considering fitness landscapes.