Flashcards: Linkage Analysis (Genomics)

Haplotypes are combinations of alleles at multiple loci that are inherited together from a single parent.

They are used in pedigree analysis to track the inheritance of genetic traits and help identify genetic markers associated with diseases.

Definition: Homologous recombination involves crossing over, which is the reciprocal breaking and re-joining of homologous chromosomes during meiosis.

Result: This process results in the exchange of chromosome segments between homologous chromosomes.

Significance: It leads to new allele combinations, increasing genetic diversity within a population and contributing to evolution.

Chromosome Pair: Homozygosity and heterozygosity refer to the alleles at the same loci on homologous chromosomes.

Homozygosity: If the alleles at a given locus are the same, the individual is homozygous for that trait.

Heterozygosity: If the alleles at a given locus are different, the individual is heterozygous for that trait.

Mendelian/Monogenic: Diseases caused by a single gene with little or no environmental influence (e.g., Polycystic Kidney Disease (PKD)).

Non-Mendelian/Polygenic/Complex: Diseases or traits resulting from the cumulative effect of many different genes, each contributing a small individual impact (e.g., psoriasis).

Multifactorial: Diseases or traits that arise from the interaction of multiple genes and often involve multiple environmental factors (e.g., heart disease).

Monogenic Diseases: Rare genetic diseases are typically monogenic, meaning they are caused by a single gene.

Single Gene Impact: In monogenic diseases, one gene corresponds to one disease, often due to a single rare variant with a significant effect on protein function.

Polygenic Diseases: Complex diseases, on the other hand, are polygenic, meaning they involve many genes contributing to one disease.

Common Variants: These complex diseases are caused by the cumulative impact of common variants, each exerting a small effect on the overall condition.

Physical Linkage: Linkage analysis assumes that genetic markers are physically linked to each other, similar to how a mobile phone is linked to its owner.

Tracking Location: Just as the location history of a mobile phone can be tracked based on its connection to the owner, genetic markers can track the location of a disease gene.

Proximity Utilization: By using genetic markers that are in close physical proximity to a disease gene, researchers can identify and map the gene's location within the genome.

Contextual Orientation: Maps provide context, helping individuals orient themselves within a space and understand their surroundings.

Distance Calculation: They allow users to calculate the distance between landmarks, facilitating efficient navigation.

Reference Points: For example, tube stations serve as reference points or ‘landmarks’ that aid in navigating through a city.

Genetic maps focus on information in blocks or regions, similar to zones on a tube map.

Physical maps provide information on the physical distances between landmarks, similar to stations on a tube map.

Genetic maps describe the relative position of genes, while physical maps provide precise location data.

Genetic linkage refers to the tendency for alleles at neighbouring loci to segregate together during meiosis.

Crossovers are more likely to occur between loci that are separated by some distance than between loci that are close together on the chromosome.

For two loci to be linked, they must lie very close together on the chromosome.

A haplotype defines multiple alleles at linked loci, and these chromosomal segments can be tracked through pedigrees and populations.

Scenario 1: Disease gene far from a genetic marker

Independent assortment occurs, leading to a high likelihood of recombination.

Scenario 2: Disease gene close to a genetic marker

Non-independent assortment occurs, resulting in a larger proportion of non-recombinants.

This leads to a greater likelihood of co-segregation of the marker with the gene.

Genotype multiple genetic markers across the entire genome.

Genotype family members, particularly those with the genetic trait or disease.

Identify which genetic markers co-segregate with the disease phenotype (i.e., markers that are inherited together with the disease in affected individuals).

Genetic markers that consistently co-segregate with the disease are considered linked to the disease-causing gene.

This linkage analysis helps pinpoint the general region of the genome where the disease gene is located, but further research is required to identify the specific gene and variant responsible.

DNA fingerprinting from very small amounts of material.

The standard test uses 13 core loci, making the likelihood of a chance match 1 in three trillion.

Paternity testing to confirm biological relationships.

Linkage analysis for disease gene identification.

Uses fluorescently-tagged PCR primers for DNA amplification.

Allows for multiplexing (multianalysis of dna samples simultaneously) of PCR products, using different colours and fragment lengths for analysis.

Fragment sizes are separated with 1bp resolution for precise identification.

Genotyping of microsatellites involves identifying which alleles the patient inherited from each parent by examining the fluorescent signals.

An SNP involves a single base change, such as CCT → CTT (Proline to Leucine).

It is the most common type of genetic variation.

SNPs are thought to occur approximately 1 per 1,000 bases in the genome.

The human genome consists of 3 billion base pairs (2 x 3,000 Mb).

SNP genotyping arrays provide genome-wide coverage of SNP markers.

SNPs are proxy markers, meaning they are not the causal disease variants but are used to track disease-associated genes.

These arrays can amplify thousands of markers in a single experiment.

Alleles are identified by relative fluorescence:

Homozygous for allele 1 = green signal.

Homozygous for allele 2 = red signal.

Heterozygous (1/2) = yellow signal.

Linkage analysis in families (affected vs unaffected relatives).

Homozygosity mapping for autosomal recessive diseases and mapping of Mendelian traits.

GWAS (Genome-Wide Association Studies) in populations (unrelated cases vs matched controls).

Analysis of non-Mendelian disorders and multifactorial traits.

Example of microsatellite coverage: A panel developed by the Centre for Inherited Disease Research (CIDR).

Microsatellites help analyze specific regions of the genome, but gaps exist, particularly in centromeres and telomeres (represented by black areas).

Example of SNP coverage: A 10k SNP mapping array developed by Affymetrix.

The array provides coverage of specific regions across the genome, but gaps still exist, primarily in the centromeres and telomeres (represented by black areas).

These SNP arrays help analyze genetic variation across different individuals.

Linkage mapping uses an observed locus (genetic marker) to draw inferences about an unobserved locus (such as a disease gene).

This method helps identify the location of disease genes by analyzing their relationship with known genetic markers.

If a marker is linked to a disease locus (e.g. M3 and M4), the same marker alleles will be inherited by two affected relatives more often than expected by chance.

If the marker and disease locus are unlinked (e.g. M5 and M8), the affected relatives in a family are less likely to inherit the same marker alleles.

Linkage regions are identified based on the inheritance patterns of markers in families with the disease.

This method helps narrow down the location of the disease gene by tracking marker inheritance.

Determine which allele is inherited from each parent.

Paternal haplotype is drawn on the left.

Maternal haplotype is drawn on the right.

A LOD score (logarithm of the odds score) is used to evaluate the likelihood that two loci are linked.

It compares the probability of the observed data if the loci are linked to the probability of the data if there is no linkage (independent assortment, θ = 0.5).

The LOD score is calculated as the logarithm of the likelihood ratio: observed data under linkage vs. expected data under no linkage.

The recombination fraction (θ) represents the proportion of recombinant offspring, calculated as θ=RNR+R\theta = \frac{R}{NR + R}θ=NR+RR​, where R = recombinants and NR = non-recombinants.

When θ = 0.5, it indicates independent assortment (maximum recombination). Lower θ values suggest tighter linkage.

A higher LOD score indicates stronger evidence for linkage, typically considered significant if it exceeds 3.

LOD scores can be calculated across the whole genome using genotype data for many genetic markers in multiple family members.

Parametric analysis specifies the pedigree structure and inheritance pattern (model).

Non-parametric analysis detects allele sharing between affected individuals.

LOD scores are additive: Different families linked to the same disease locus will increase the overall score.

A LOD score ≥ 3 is considered evidence for linkage.

A LOD score of 3 is equivalent to odds of 1000:1 that the observed linkage occurred by chance.

A LOD score ≤ -2 is considered evidence against linkage.

Linkage software options include: Vitesse, PLINK, MERLIN, Alohomora, Fastlink, and others.

Parametric analysis in these programs specifies analysis parameters, such as:

Inheritance pattern

Disease allele frequency

Penetrance

Non-parametric analysis:

No parameters are specified.

Focuses on allele sharing between affected individuals.

Adams-Oliver syndrome involves autosomal dominant inheritance.

Terminal transverse limb defects (TTLD) and scalp aplasia cutis congenita (ACC) are characteristic features.

Associated features include:

Neurological anomalies

Cardiac malformations

Vascular defects (e.g., cutis marmorata telangiectatica congenita, dilated veins)

Refinement of the minimal linkage interval using microsatellite and SNP markers across the region.

Heterozygous mutations of the ARHGAP31 gene detected in two unrelated probands.

Both mutations are predicted to result in premature protein truncation.