Unboxing mutations: Connecting mutation types with evolutionary consequences

Autor: Alexander Suh, Alexandre Blanckaert, Inês Fragata, Anja M. Westram, Tanja Slotte, Emma L. Berdan
Přispěvatelé: Repositório da Universidade de Lisboa
Rok vydání: 2021
Předmět:
0106 biological sciences
0301 basic medicine
Mutation rate
mutation rate
Population
Population genetics
Single-nucleotide polymorphism
adaptation
Computational biology
Biology
010603 evolutionary biology
01 natural sciences
Evolutionsbiologi
03 medical and health sciences
structural variant
Mutation Rate
Genetic algorithm
Matematikk og Naturvitenskap: 400::Basale biofag: 470::Biokjemi: 476 [VDP]
Genetics
Selection
Genetic
education
Ecology
Evolution
Behavior and Systematics
Population Density
Evolutionary Biology
education.field_of_study
Models
Genetic
Evolutionary significance
population genetics
Matematikk og Naturvitenskap: 400::Basale biofag: 470::Molekylærbiologi: 473 [VDP]
Other Quantitative Biology (q-bio.OT)
Adaptation
Physiological
Biological Evolution
Quantitative Biology - Other Quantitative Biology
recombination
030104 developmental biology
Genetics
Population
speciation
Conceptual framework
Evolutionary biology
FOS: Biological sciences
Matematikk og Naturvitenskap: 400::Basale biofag: 470::Genetikk og genomikk: 474 [VDP]
Mutation (genetic algorithm)
Chromosome Inversion
Mutation
Key (cryptography)
mutation
Adaptation
distribution of fitness effects
Zdroj: Molecular Ecology
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
ISSN: 1365-294X
Popis: A key step in understanding the genetic basis of different evolutionary outcomes (e.g., adaptation) is to determine the roles played by different mutation types (e.g., SNPs, translocations and inversions). To do this we must simultaneously consider different mutation types in an evolutionary framework. Here, we propose a research framework that directly utilizes the most important characteristics of mutations, their population genetic effects, to determine their relative evolutionary significance in a given scenario. We review known population genetic effects of different mutation types and show how these may be connected to different evolutionary outcomes. We provide examples of how to implement this framework and pinpoint areas where more data, theory and synthesis are needed. Linking experimental and theoretical approaches to examine different mutation types simultaneously is a critical step towards understanding their evolutionary significance.
Databáze: OpenAIRE
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