4.4 Molecular evolution and selection analysis
7 min read•july 30, 2024
and are crucial tools in comparative genomics. They help us understand how genes change over time and adapt to different environments. These methods reveal the forces shaping and species evolution.
Statistical tests like dN/dS ratios and McDonald-Kreitman tests detect selection at the molecular level. By comparing different types of genetic changes, scientists can infer positive, negative, or . This information provides insights into gene function and evolutionary history.
Detecting Selection at the Molecular Level
Statistical Methods for Detecting Selection
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- The ratio of nonsynonymous to rates (dN/dS or Ka/Ks) is a widely used method to detect selection at the molecular level
- A greater than 1 suggests , while a ratio less than 1 indicates negative (purifying) selection
- Example: A study of the primate FOXP2 gene, which is involved in speech and language development, found a dN/dS ratio of 2.4, indicating strong positive selection
- The compares the ratio of nonsynonymous to synonymous polymorphisms within a species to the ratio of nonsynonymous to synonymous fixed differences between species
- An excess of nonsynonymous fixed differences relative to polymorphisms suggests positive selection
- Example: A comparison of the Adh gene in Drosophila melanogaster and D. simulans revealed an excess of nonsynonymous fixed differences, suggesting positive selection on this gene
- compares the average number of pairwise differences between sequences to the number of segregating sites
- Negative values of Tajima's D suggest an excess of rare variants, which can be indicative of positive selection or population expansion
- Example: A study of the human lactase gene (LCT) found negative Tajima's D values in populations with a history of dairy farming, suggesting positive selection for lactase persistence
Additional Tests for Detecting Selection
- The Hudson-Kreitman-Aguadé (HKA) test compares the levels of and between two or more loci
- Deviation from the expected neutral pattern can suggest selection acting on one or more of the loci
- Example: An HKA test comparing the human ASPM gene, which is involved in brain development, to a neutral reference gene found evidence of positive selection on ASPM
- is sensitive to an excess of high-frequency derived alleles, which can be a signature of positive selection
- This test is particularly useful for detecting recent positive selection events
- Example: A study of the human G6PD gene, which is involved in malaria resistance, found a significant excess of high-frequency derived alleles in African populations, suggesting recent positive selection
Positive, Negative, and Balancing Selection
Types of Selection and Their Effects
- Positive selection occurs when an allele confers a fitness advantage and increases in frequency within a population over time
- This type of selection can lead to the fixation of beneficial alleles and drive
- Example: The sickle cell allele of the HBB gene provides resistance to malaria and has undergone positive selection in regions where malaria is endemic
- Negative (purifying) selection removes deleterious alleles from a population, preventing them from reaching high frequencies
- This type of selection maintains the functional integrity of genes and conserves amino acid sequences across species
- Example: The human BRCA1 gene, which is involved in DNA repair and tumor suppression, shows strong evidence of , with a low tolerance for amino acid-changing mutations
- Balancing selection maintains multiple alleles at a locus within a population
- This can occur through various mechanisms, such as heterozygote advantage (overdominance), frequency-dependent selection, or spatial and temporal variation in selection pressures
- Example: The human major histocompatibility complex (MHC) genes, which are involved in immune response, exhibit high levels of genetic diversity maintained by balancing selection
Evolutionary Consequences of Different Types of Selection
- Positive selection is often associated with rapid evolution and adaptation to new environments
- Genes under positive selection may show accelerated rates of amino acid change and divergence between species
- Example: The rhodopsin gene in deep-sea fishes has undergone positive selection, enabling adaptation to different light environments
- Negative selection is more common and helps to maintain the function of essential genes
- Genes under strong negative selection typically have low rates of amino acid change and high sequence conservation across species
- Example: The histone genes, which are involved in DNA packaging and regulation, are highly conserved across eukaryotes due to strong negative selection
- Balancing selection can lead to the maintenance of genetic diversity within populations and can result in the persistence of ancient polymorphisms
- Genes under balancing selection may show higher levels of polymorphism than expected under neutrality and may have polymorphisms that are shared between species
- Example: The ABO blood group system in humans is maintained by balancing selection, with the different blood types conferring resistance to various pathogens
Selection Analysis Results and Implications
Interpreting Selection Analysis Results
- A high dN/dS ratio (greater than 1) for a gene suggests that it has undergone positive selection, which may indicate adaptation to new environments or the evolution of new functions
- Example: The PRNP gene, which encodes the prion protein, has a high dN/dS ratio in bats, suggesting adaptation to different ecological niches and possible resistance to prion diseases
- Genes with low dN/dS ratios (less than 1) are likely to be under strong negative selection, suggesting that they have essential functions and that their amino acid sequences are highly conserved across species
- Example: The cytochrome c oxidase genes, which are involved in cellular respiration, have very low dN/dS ratios across a wide range of species, indicating strong negative selection and functional constraint
- The identification of specific amino acid sites under positive selection within a gene can provide insights into the functional importance of those sites and the potential adaptive changes that have occurred
- Example: A study of the vertebrate rhodopsin gene identified several amino acid sites under positive selection, which were found to be involved in spectral tuning and adaptation to different light environments
Integrating Selection Analysis with Other Data
- Genes that show signatures of balancing selection may be involved in immune defense, as maintaining diversity at these loci can help populations defend against a wide range of pathogens
- Example: The human leukocyte antigen (HLA) genes, which are involved in antigen presentation, show evidence of balancing selection, likely due to their role in defending against diverse pathogens
- The results of selection analyses can be combined with functional studies and ecological data to gain a more comprehensive understanding of the evolutionary forces shaping gene evolution and adaptation
- Example: A study of the human EPAS1 gene, which is involved in high-altitude adaptation, integrated selection analysis results with functional assays and population genetic data to demonstrate the adaptive role of specific variants in Tibetan populations
Limitations and Biases in Selection Analysis
Data Quality and Assumptions
- Selection tests are sensitive to the quality and quantity of the sequence data used
- Small sample sizes, sequencing errors, and alignment issues can lead to false positives or false negatives
- Example: A study of the human MCPH1 gene, which is involved in brain development, initially suggested positive selection based on limited data, but this finding was not supported when a larger dataset was analyzed
- Selection tests assume a constant mutation rate across the genome, which may not always be the case
- Variation in mutation rates can lead to biases in the estimation of selection parameters
- Example: The human mitochondrial genome has a higher mutation rate than the nuclear genome, which can affect the interpretation of selection tests applied to mitochondrial genes
Demographic Effects and Statistical Power
- Demographic events, such as population bottlenecks or expansions, can mimic the signatures of selection and lead to false inferences
- It is important to consider the demographic history of the populations being studied when interpreting selection test results
- Example: A study of the human PDYN gene, which encodes an opioid peptide precursor, initially suggested positive selection, but this finding was later attributed to population bottlenecks rather than selection
- Selection tests may have limited power to detect selection in recently diverged species or populations, as there may not have been sufficient time for selection to leave a detectable signature in the genome
- Example: Many selection tests have limited power to detect selection in human populations that have diverged within the past 50,000 years, such as Europeans and Asians
Violations of Neutrality Assumptions
- Some selection tests, such as the McDonald-Kreitman test, assume that synonymous sites are neutral and not affected by selection
- However, selection on synonymous sites, such as codon usage bias, can violate this assumption and lead to biased results
- Example: In Drosophila, codon usage bias can affect the interpretation of the McDonald-Kreitman test, leading to overestimation of positive selection in some cases
- Selection tests that rely on the comparison of polymorphism and divergence, such as the HKA test, can be sensitive to violations of the assumptions of neutrality and constant population size
- Example: The presence of slightly deleterious mutations can lead to an excess of polymorphism relative to divergence, which can be misinterpreted as evidence of balancing selection in the HKA test
Key Terms to Review (28)
Adaptive evolution: Adaptive evolution is the process through which species evolve traits that enhance their survival and reproduction in specific environments. This mechanism involves natural selection acting on genetic variations, leading to the prevalence of advantageous traits over generations. Adaptive evolution can result from various factors, including gene duplication, loss, horizontal gene transfer, and the subsequent selection pressures in molecular evolution.
Adaptive Radiation: Adaptive radiation refers to the rapid evolution of diversely adapted species from a common ancestor in response to varying environmental conditions. This process often occurs when a species colonizes a new habitat or when ecological niches become available, leading to the development of different traits that enhance survival and reproduction in diverse environments. It highlights the interplay between genetic variation, environmental pressures, and natural selection in shaping biodiversity.
Balancing selection: Balancing selection is a form of natural selection that maintains multiple alleles in a population, allowing for genetic diversity. This process can occur through mechanisms like heterozygote advantage, where individuals with two different alleles at a locus have a higher fitness than those with two identical alleles, or frequency-dependent selection, where the fitness of an allele depends on its frequency in the population. Balancing selection plays a crucial role in molecular evolution and helps shape the genetic structure of populations over time.
Beast: In the context of molecular evolution and selection analysis, 'beast' refers to a software platform used for Bayesian analysis of molecular sequences. This tool helps researchers estimate phylogenetic trees, understand evolutionary relationships, and analyze the effects of selection on genetic data. The use of Bayesian statistics allows for the incorporation of prior information and provides a robust framework for assessing evolutionary processes.
Convergent Evolution: Convergent evolution is the process where organisms from different evolutionary backgrounds develop similar traits or adaptations in response to similar environmental challenges or ecological niches. This phenomenon highlights how natural selection can shape unrelated species in similar ways, leading to analogous structures and functions despite their distinct genetic lineages.
Divergence: Divergence refers to the process through which two or more related biological species or lineages evolve different traits and characteristics over time, leading to increased differences between them. This concept is central to understanding how species adapt to their environments, as well as the mechanisms of molecular evolution and natural selection that drive these changes.
Dn/ds ratio: The dn/ds ratio, also known as the nonsynonymous to synonymous substitution ratio, is a metric used in molecular evolution to assess the strength of natural selection acting on a protein-coding gene. It compares the rate of nonsynonymous substitutions (which change amino acids) to synonymous substitutions (which do not change amino acids). A dn/ds ratio greater than 1 suggests positive selection, a ratio equal to 1 indicates neutral evolution, and a ratio less than 1 implies purifying selection.
Fay and Wu's H Test: Fay and Wu's H Test is a statistical method used to detect the presence of natural selection in DNA sequences by comparing the levels of polymorphism within a species to the divergence from a closely related species. This test helps identify whether certain alleles are maintained or favored due to selection, providing insights into molecular evolution. By analyzing the ratio of polymorphism to divergence, this test can indicate if a region of DNA is under positive selection, balancing selection, or neutrality.
Fisher's geometric model: Fisher's geometric model is a theoretical framework that describes how phenotypic traits evolve under natural selection by considering the relationship between genotype and phenotype in a multidimensional space. It suggests that the fitness of an organism is influenced by how close its traits are to an optimum point in this space, where even small mutations can have varying effects on fitness depending on their proximity to this optimal point. This model emphasizes the complexities of adaptation and how it can be affected by multiple traits interacting simultaneously.
Genetic diversity: Genetic diversity refers to the variety of genes within a population, which is crucial for the adaptability and survival of species. This variation among individuals allows populations to withstand environmental changes, resist diseases, and thrive in different habitats. High genetic diversity is a key factor in evolutionary processes and is essential for conservation efforts aimed at maintaining biodiversity.
Genetic Drift: Genetic drift is a mechanism of evolution that refers to random changes in allele frequencies within a population over time, particularly in small populations. It occurs due to chance events that can lead to certain alleles becoming more or less common, regardless of their impact on survival and reproduction. This randomness can significantly influence the genetic makeup of populations and can lead to reduced genetic variation, making it an important factor in understanding evolutionary dynamics.
Heterozygosity: Heterozygosity refers to the presence of different alleles at a specific locus on homologous chromosomes in an organism. This genetic variability is crucial for understanding evolutionary processes, population dynamics, and conservation efforts, as it can influence an organism's adaptability to environmental changes and the overall health of populations.
Homology: Homology refers to the existence of shared ancestry between a pair of structures, or genes, in different taxa. This concept is central to understanding molecular evolution and selection analysis because homologous traits indicate a common evolutionary origin, which helps scientists trace the lineage of species and understand the evolutionary pressures that have shaped their development over time.
Hudson-Kreitman-Aguadé Test: The Hudson-Kreitman-Aguadé test is a statistical method used to assess the role of natural selection in molecular evolution by comparing polymorphism within species to divergence between species. This test helps to identify whether observed genetic variations are due to neutral processes or adaptive evolution, linking molecular data to evolutionary theory.
Kimura's Neutral Theory: Kimura's Neutral Theory proposes that most evolutionary changes at the molecular level are the result of random drift of neutral mutations rather than natural selection. This theory emphasizes that a significant proportion of genetic variation observed within populations is due to mutations that do not confer any selective advantage or disadvantage, suggesting that genetic drift plays a critical role in shaping molecular evolution.
McDonald-Kreitman Test: The McDonald-Kreitman test is a statistical method used to assess the effects of natural selection on protein-coding genes by comparing the rates of synonymous and nonsynonymous mutations. This test provides insights into whether a gene has undergone adaptive evolution, as it evaluates the differences in mutation rates in both conserved and variable regions of a gene, which can indicate the strength of selection acting on it.
Mega: In the context of genomics, 'mega' is a prefix denoting a factor of one million (10^6) and is often used to describe large-scale genomic data or sequences. It emphasizes the vast quantities of data generated in genomic research and analysis, as well as the comprehensive resources available for studying molecular evolution and selection processes.
Molecular evolution: Molecular evolution refers to the process by which genetic material and the molecular structures of organisms change over time through mechanisms such as mutation, selection, and genetic drift. This field helps in understanding how these changes at the molecular level contribute to the diversity of life and evolutionary relationships among species. The study of molecular evolution often involves the analysis of DNA, RNA, and protein sequences to trace evolutionary paths and mechanisms of natural selection.
Negative Selection: Negative selection is a process in evolutionary biology where deleterious alleles or mutations are removed from a population, enhancing the overall fitness of the organism. This mechanism is crucial in maintaining genetic stability, as harmful genetic variations are less likely to be passed on to future generations. By favoring individuals with advantageous traits, negative selection plays a vital role in shaping the genetic landscape of populations over time.
Nonsynonymous substitution: A nonsynonymous substitution is a type of mutation that results in a change to the amino acid sequence of a protein. This change can alter the function, structure, or stability of the resulting protein, impacting the organism's traits and fitness. These substitutions are significant in molecular evolution as they can be subject to natural selection, influencing evolutionary processes.
Nucleotide diversity: Nucleotide diversity is a measure of the variation in nucleotide sequences within a population or species, often expressed as the average number of nucleotide differences per site between two randomly chosen DNA sequences. This concept is crucial for understanding genetic variation, evolutionary dynamics, and the overall health of populations, influencing how species adapt to environmental changes and how conservation efforts are directed.
Orthology: Orthology refers to genes in different species that evolved from a common ancestral gene through speciation events. These genes retain similar functions across species, which makes them important for studying evolutionary relationships and functional genomics. Understanding orthologs can provide insights into how specific traits or functions are conserved or adapted over time, linking molecular evolution to selection analysis.
Polymorphism: Polymorphism refers to the occurrence of two or more different alleles at a specific locus within a population, leading to variations in the genetic makeup of individuals. This genetic variation is crucial for understanding evolutionary processes and natural selection, as it provides the raw material for adaptation and contributes to the diversity within populations over time.
Positive Selection: Positive selection is a process in evolutionary biology where specific genetic variants increase in frequency within a population due to providing some advantage to individuals carrying them. This mechanism plays a crucial role in shaping the genetic makeup of populations, as advantageous traits become more common over generations, leading to adaptation and evolutionary change.
Purifying selection: Purifying selection is a type of natural selection that acts to remove deleterious mutations from a population, maintaining the integrity of essential genes and functions. This process ensures that harmful genetic changes are less likely to be passed on, thus preserving the adaptive traits of a species. It plays a crucial role in molecular evolution by favoring the survival and reproduction of individuals with beneficial or neutral alleles over those with detrimental ones.
Selection Analysis: Selection analysis is a method used to understand how natural selection affects the genetic variation in populations over time. It helps identify which genes or traits are favored in a particular environment, providing insights into evolutionary processes. By analyzing genetic data, researchers can determine whether observed changes in allele frequencies are due to selection, genetic drift, or other factors.
Synonymous substitution: A synonymous substitution is a type of genetic mutation where a nucleotide change in the DNA sequence does not alter the amino acid sequence of the resulting protein. This kind of mutation is significant because it indicates that some genetic changes can occur without affecting the overall function of proteins, suggesting a level of redundancy in the genetic code. Understanding synonymous substitutions is crucial for studying molecular evolution and selection analysis, as they can provide insights into evolutionary pressures and genetic diversity.
Tajima's D Test: Tajima's D Test is a statistical method used to detect natural selection in genetic data by comparing the number of segregating sites to the average number of nucleotide differences in a sample. This test helps identify deviations from neutrality, indicating whether a population has experienced expansion, contraction, or selection pressures. Understanding Tajima's D is crucial for interpreting molecular evolution and the effects of selection on genetic variation.