Genetics and Allele Frequencies Quiz

Pharmacogenomics Goals

• Pharmacogenomics aims to classify individuals based on genetic variation to determine the best drug and dosage.
• Genetic variations influence how individuals respond differently to drugs.
• PGx testing can help tailor treatment plans.

DNA Variation in Populations

• DNA variation arises from DNA combination in germ cells.
• Crossover and recombination during meiosis contribute to variation.
• Mutations and recombination within genes introduce variations that are passed to next generations.
• Variations in genes can lead to differences in individual traits.

DNA Origination

• Genetic variations originate in germ cells of the father.
• Mutations in somatic cells do not typically affect future generations.
• Thirty mutations are estimated per human sperm.

First Level DNA Variation

• Germline mutations cause variations in offspring compared to parents.
• Mutations in genes lead to alleles, variations within a gene.
• Alleles' location in the DNA is denoted as loci.
• Not all mutations spread equally in the population.

Major and Minor Alleles

• A major allele is the most common allele in a population.
• A minor allele refers to other alleles in the population.
• The frequency of an allele provides information on its prevalence.
• Allele frequencies can vary between populations.

What Determines Allele Spread?

• Natural selection favors alleles that improve survival and reproduction.
• Genetic drift leads to random changes in allele frequencies.
• Genetic variation mixes alleles between populations, transferring them between populations.

DNA Variation Population Differences

• Individuals may differ in genetic variation between populations.
• Genetic variations within populations are significant compared to between populations.
• Variations in skin pigmentation are relatively high within continents and low between continents.

Allele Frequency

• Allele frequencies are used to characterize populations.
• Allele frequencies in different populations are distinct.
• Understanding the geographic ancestry is more helpful than simply race when examining differences.

DNA Variants in Humans

• The human genome is approximately 3 billion base pairs.
• Approximately 1-2% of the genome codes for proteins (exomes).
• The majority (~98-99%) of the genome is non-coding DNA.
• Many functional RNA molecules reside in the non-coding region.

DNA Variations and Medicine

• DNA variations affect the entire genome, but only a small fraction are located in genes.
• Mapping variations helps identify genes related to diseases and drug responses.
• Variations can help categorize patients based on their drug responses.

Types of DNA Variations (SNVs)

• Single Nucleotide Variants (SNVs): the most common type of genetic variation.
• SNVs are also known as single nucleotide polymorphisms (SNPs).
• SNVs are preferred over SNPs when the frequency exceeds 1%.

Minor Allele Frequency (MAF)

• MAF: represents the frequency of the less common allele in a population.
• Common MAF is defined as greater than 5%.
• Low MAF ranges from 1% to 5%.
• Rare MAF is less than 1%.
• Very rare MAF is less than 0.1%.

SNVs and Gene Function

• SNVs in exons (coding regions) can disrupt gene function.
• SNVs in introns or intergenic regions might not directly affect the adjacent gene.
• Different types of SNVs (e.g., synonymous, missense, nonsense) can lead to different effects on proteins.

How SNVs Disrupt Gene Function (Specific Examples)

• Sickle cell disease results when a gene mutation leads to a missense mutation change.
• Specific mutations, such as nonsense mutations, can lead to protein production problems.
• Other mutations may cause a silent mutation, with no changes in the protein.

SNV Variations (Short Indels)

• Short Indels are the second most common genetic variant.
• These variants introduce insertions or deletions of small segments (typically 1-6 basepairs).
• Frameshift mutations occur due to insertion and deletion.

SNV Variations (Structural)

• Copy number variations (CNVs) involve variations in the number of gene copies.
• Inversions, translocations, and duplications represent structural changes in DNA sequence.

Identifying Genes of Interest

• Variations can be used as landmarks to identify genes linked to diseases or drug responses.
• This involves comparing DNA variation in populations with and without the disease.
• Finding associated genes can involve using large-scale studies like GWAS.

GWAS (Genome-Wide Association Studies)

• GWAS is a strategy to identify genetic variations associated with diseases or drug responses.
• It screens numerous SNPs across the genome.
• GWAS relies on statistical differences and the presence of linkage disequilibrium.

GWAS Results Interpretation

• Manhattan plots are used to visualize the results of GWAS.
• Significance (p-value) helps determine the impact of genetic variants.
• SNPs with lower p-values show stronger associations.

Pharmacogenomics Success Stories

• Success stories show the practical use of pharmacogenomics in medicine.
• Understanding and knowing variations in genes in drug response can tailor treatment plans based on needs.

Pharmacodynamic/Pharmacokinetic Factors

• Pharmacodynamics and pharmacokinetics determine drug efficacy.
• Pharmacodynamics involve changes in the target cell/organ.
• Pharmacogenetics determine variation in response due to genetic variations.

Challenges in Detecting DNA Variations

• Variation detection using arrays has limitations.
• Cost and time can be a factor in genome-wide studies.
• Sequencing has various challenges, including data handling issues, and gaps.

Pharmacogenomics Applications

• Genetic variations are related to specific traits, diseases, or drug response.
• Pharmacogenomics strategies help to personalize treatment to individual needs.
• Specific considerations are important with rare genetic variants.