Topic 12: Evolution at Multiple Loci

BS2470/BS5470 Evolution
Evolution at Multiple Loci

Key Questions

  1. What is linkage disequilibrium, how does it arise, and how does it change over evolutionary time?

  2. How do we use quantitative genetics to find the loci underlying polygenic traits?

LINKAGE DISEQUILIBRIUM

Importance of Linkage Disequilibrium

  • Understanding the population genetics of multiple loci requires tracking haplotype frequencies rather than just allele frequencies. This helps to understand how different alleles are inherited together and how they affect phenotypic traits in a population.

  • Allele frequency: Defined as the proportion of a specific allele within a population across all individuals, indicating genetic diversity and potential for evolution within that population.

  • Haplotype frequency: This refers to the frequency of a haplotype—a combination of alleles at multiple loci—within a population, crucial for understanding genetic linkage and evolutionary dynamics.

  • Haplotype: A set of closely linked alleles that tend to be inherited together. For instance, in a diploid organism with loci A, B, and C, possible haplotypes could include combinations like ABc or aBC, which provide insights into the genetic makeup of individuals beyond just single alleles.

Haplotype Frequencies

  • In examining two loci, A and B, each can have two alleles (A and a; B and b).

  • It is vital to analyze the association between alleles at these loci, as allele frequencies alone do not accurately depict haplotype frequencies. This association can reveal insights into evolutionary pressures and historical demographic changes in populations.

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LOCATION OF LOCI

Loci Placement

  • Loci can be either on different chromosomes, which allows independent assortment during meiosis, or on the same chromosome (physically linked), affecting the likelihood of recombination during meiosis.

  • Understanding their physical arrangement is essential when studying inheritance patterns, as proximity can lead to lower recombination rates and increased linkage disequilibrium.

Physically Linked Loci

  • The proximity of loci on the same chromosome influences how often recombination occurs during Prophase I of meiosis. When two loci are physically close, the likelihood of crossing over occurring between them decreases, which can maintain certain combinations of alleles in a population over generations.

LINKAGE DISEQUILIBRIUM

Definition of Linkage Disequilibrium

  • Linkage disequilibrium: It refers to the statistical association between alleles at two different loci. When the presence of one allele at the first locus influences the presence of an allele at the second locus, linkage disequilibrium is said to exist.

  • Example: If there are no ab haplotypes present in the population, it can be inferred that all b alleles are associated with A haplotypes (Ab). Therefore, knowing that an individual carries the b allele guarantees at least one A allele, giving valuable predictive power in population genetics.

Example of Linkage Disequilibrium

  • Consider two genes located on the same chromosome tracked for allele frequencies and haplotype frequencies. Potential haplotypes include combinations like AB, Ab, aB, and ab, highlighting how the configuration of alleles affects inheritance patterns.

ALLELE FREQUENCIES

Examples of Allele Frequencies

  • Population 1:

    • Frequency of A = 15/25 = 0.6

  • Population 2:

    • Frequency of A = 15/25 = 0.6

  • Tracking these frequencies across populations allows researchers to draw conclusions about genetic variation and selective pressures.

Population Analysis

  • Example for B allele:

    • Population 1: Frequency of B = 20/25 = 0.8

    • Population 2: Frequency of B = 20/25 = 0.8

  • Understanding allele frequencies serves as a foundational step in exploring population structure and dynamics as well as its evolutionary history.

HAPLOTYPE FREQUENCIES

Haplotype Frequency Analysis

  • For both populations, example frequencies were calculated for AB haplotypes:

    • Population 1: Frequency of AB = 12/25 = 0.48

    • Population 2: Frequency of AB = 11/25 = 0.44

  • Changes in haplotype frequencies over time can reflect underlying evolutionary trends, such as natural selection, where certain haplotypes provide a survival advantage.

Linkage Equilibrium Example

  • Population 1: Frequency of b on A = 3/15 = 0.2; b on a = 2/10 = 0.2. This illustrates linkage equilibrium, where the presence of one genotype does not provide predictive information about the other, indicating a random association between alleles.

LINKAGE DISEQUILIBRIUM DIAGRAMS

Population 2:

  • Frequency of b on A = 4/15 = 0.27; b on a = 1/10 = 0.1. This illustrates linkage disequilibrium, as knowing one genotype provides predictive information about the other, aiding in the study of genetic associations within populations.

Importance of Linkage Disequilibrium

  • Linkage disequilibrium is instrumental in tracking changes in allele or haplotype frequencies over time caused by evolutionary processes such as mutation, selection, nonrandom mating, migration, and drift. By identifying patterns of linkage disequilibrium, scientists can infer the evolutionary history and demographic events that shaped the genetic makeup of populations.

EVOLUTIONARY PROCESSES CREATING LINKAGE DISEQUILIBRIUM

Five Processes of Linkage Disequilibrium Creation

  1. Mutation: New mutations can introduce novel alleles, impacting haplotype composition.

  2. Selection on polygenic traits: Differential survival and reproduction can alter allele frequencies and increase associations between beneficial alleles.

  3. Non-random mating (sexual selection): Mate preferences can lead to associations between certain alleles and phenotypic traits.

  4. Migration (gene flow): The introduction of new alleles through migration can disrupt linkage disequilibrium in recipient populations.

  5. Genetic drift: Random changes in allele frequencies, particularly in small populations, can lead to the loss of haplotypes and the renaturation of linkage disequilibrium.

Linkage Disequilibrium via Mutation

  • Prior to mutation: Only AB and aB haplotypes are present. The introduction of new alleles through mutation may create new haplotypes that can foster statistical associations between previously unlinked alleles.

  • Post-mutation: The emergence of an ab haplotype creates a statistical association between the alleles, where the b allele at the B locus guarantees the presence of the a allele at the A locus, indicating new patterns of inheritance.

LINKAGE DISEQUILIBRIUM VIA SELECTION

Impact of Selection

  • Selection primarily creates linkage disequilibrium between alleles exhibiting epistatic interactions—a phenomenon where the effect of one gene is influenced by the presence of one or more other genes.

  • Additionally, it may indirectly affect nearby non-selected loci through genetic hitchhiking, where alleles that are physically linked to beneficial alleles are swept along by selection, increasing their frequency in the population.

Genetic Hitchhiking Example

  • In scenarios with strong selective pressure against non-functional alleles (e.g., disease alleles like a and b), linkage disequilibrium arises when such alleles are encapsulated in a haplotype that contains beneficial alleles, leading to their co-inheritance and persistence.

LINKAGE DISEQUILIBRIUM VIA STRONG SELECTION

Strong Selection & Genetic Hitchhiking

  • Strong selection can leave a distinctive linkage disequilibrium fingerprint through genetic hitchhiking (selective sweep), which provides insight into the historical adaptation of populations.

  • For example, lactase enzyme production is preserved into adulthood in certain human populations as an adaptation resulting from the historic domestication of cattle, showcasing how selection pressures can shape allele frequencies.

Geography & Selection

  • Patterns of lactase persistence correlate significantly with the geography of cattle domestication, indicating how human cultural practices can influence genetic variation. Approximately 30% of global human populations display this trait, with notable distributions in regions of East and West Africa and Northwest Europe, reinforcing the connection between environment and evolutionary outcomes.

LINKAGE DISEQUILIBRIUM VIA NONRANDOM MATING

Nonrandom Mating Effects

  • Nonrandom mating can enhance linkage disequilibrium, particularly when mate preferences are involved. For instance, if females exhibit a preference for long-tailed males (represented by a preference locus P) in a population of wrens, there will be a noticeable association between the P alleles and the T alleles (associated with tail size).

  • Such preferences can create nonrandom associations that lead to increased frequencies of certain haplotypes, impacting the genetic structure of the population.

LINKAGE DISEQUILIBRIUM VIA MIGRATION

Impact of Migration

  • Migration has the potential to create linkage disequilibrium within populations, particularly when individuals from different genetic backgrounds interbreed. For example, if a population of mainland lizards (with haplotypes ab|ab) migrates to a new island environment, statistical associations will emerge between the alleles at A and B loci in the newly established population.

  • Such gene flow can introduce new alleles, thereby altering the existing genetic landscape and influencing evolutionary processes.

LINKAGE DISEQUILIBRIUM VIA GENETIC DRIFT

Linkage Disequilibrium through Drift

  • Genetic drift can lead to the loss of haplotypes and the redundancy of linkage disequilibrium. In smaller populations, the random loss of a haplotype (e.g., ab) can yield nonrandom associations between alleles at loci A and B, thereby dampening the genetic diversity and creating shifts in allele frequencies over generations.

DISSOLUTION OF LINKAGE DISEQUILIBRIUM

Mechanism of Breakdown

  • Linkage disequilibrium diminishes over time primarily due to recombination during meiosis and independent assortment when loci are unlinked. Over successive generations, this association will gradually dissipate as alleles segregate independently or recombine into new formations, leading to a reversion to linkage equilibrium.

FINDING GENES UNDERLYING QUANTITATIVE TRAITS

Quantitative Trait Loci (QTL)

  • QTL: These are regions of the genome that contribute to complex or quantitative traits, typically encoding genes for enzymes, proteins, or transcription factors that exert small effects on the resulting phenotype, influencing traits like height, yield, or disease resistance.

  • Identifying QTLs is key to understanding the genetic basis of complex traits and involves scanning the genome for associations between genetic markers and phenotypic variation.

Statistical Tools Required

  • Specialized statistical methods are essential for determining the count, location, and effects of QTLs on trait variation. These tools facilitate the interpretation of complex datasets and help in identifying significant genetic markers linked to particular traits.

METHODS TO IDENTIFY QTLS

Comparison of Two Mapping Techniques

  • QTL Mapping utilizes known pedigrees for tracking traits through generations, which allows for a greater understanding of genetic inheritance patterns.

  • Association Mapping employs natural populations (Genome Wide Association Studies - GWAS) and can assess variations across diverse alleles simultaneously.

  • Both methods require quantitative phenotypes, genetic markers, and appropriate mapping frameworks to draw valid conclusions about genetic associations.

QTL Mapping Steps

  1. Measure quantitative traits for many individuals in the population in order to capture the phenotypic variation present.

  2. Assess each individual for numerous genetic markers to identify potential associations between genotypes and observed traits.

  3. Analyze allele-phenotype associations using statistical methods (e.g., Lod scores) to determine which alleles significantly correlate with the traits.

  4. Plot Lod scores along chromosomes to visualize the strength and location of associations.

  5. Establish significance against a threshold (commonly Lod score > 3) to identify QTLs confidently.

EXAMPLE: QTL MAPPING FOR TOMATO FRUIT WEIGHT

Analysis of Tomato Genotype

  • An example with parent strains and backcross (BC) offspring reveals how specific genotype combinations can influence fruit weight through various genetic markers (denoted M1-M5).

  • Observing differences between various genotypes at specific markers helps in pinpointing the QTL responsible for trait variation.

Genotype Analysis

  • At Marker 1: B/B and B/S show similar phenotypes, suggesting the absence of a nearby QTL affecting weight at this position.

  • At Marker 3: Significant differences in the phenotypes between B/B and B/S hint at the presence of a QTL influencing fruit weight.

LINKAGE GROUP AND QTL SIGNIFICANCE THRESHOLD

Odds and Lod Scores

  • The significance threshold for QTL detection is generally set at Lod score >3, reflecting significantly higher odds of observing data given the presence of a QTL compared to its absence. This threshold underscores the importance of robust statistical analysis in genetic mapping.

EXAMPLES OF QTL MAPPING IN VARIOUS ORGANISMS

Genetic Analysis in Different Species

  • Some Genes and Their Associated Traits:

    • Yeast: RHO2 for high-temperature growth

    • Arabidopsis: CRY2 for flowering time

    • Maize: Tb1 for branching, Vgt for flowering time

    • Rice: Hd1 for photoperiod sensitivity

    • Tomato: Fw2.2 for fruit weight

    • Drosophila: scabrous for bristle number

    • Cattle: DGAT1 for milk yield

    • Mice: Genes related to type 1 diabetes and colon cancer.

ASSOCIATION MAPPING

Benefits of Association Mapping

  • Association mapping is advantageous because it can identify genetic associations without necessitating specific breeding designs. It allows researchers to survey numerous alleles at once due to the widespread availability of SNPs distributed across the entire genome, enhancing the power and efficiency of genetic studies.

Steps in Association Mapping

  1. Measure numerous individuals for a complex phenotype (e.g., disease susceptibility) to capture a broad dataset.

  2. Assess individuals across various genetic markers (e.g., SNPs) to find relevant genetic information.

  3. Analyze SNP-trait associations statistically, with the null hypothesis generally stating there is no association.

  4. Plot significant P-values (using methods like the Manhattan plot) to visually identify associated SNPs, simplifying the interpretation of results within the context of genetic variation.

MANHATTAN PLOT EXAMPLES

GWAS Outcomes

  • Notable studies have illustrated the associations between genetic markers and traits in both dogs and humans, often aiming to establish stringent significance thresholds (e.g., critical P-value lower than 0.05) to bolster the reliability of findings.