Class 7 Quiz: Bold Or Underline The Correct Answer? ✓ Solved
Class 7 Quiz Bold Or Underline Correct Answerstarted Aug 17
What best describes the focus of population genetics?
What two genetically-determinable quantities does the Hardy Weinberg equilibrium relate?
If the frequency of alleles “a” and “A” within a population are 30% and 70% respectively, what are the expected Hardy Weinberg frequencies of various possible genotypes?
How might the Hardy Weinberg relationship be used to evaluate a new SNP genotyping technology using multiple individuals from a population?
What best describes the focus of Pharmacogenomics?
Why might a pharmaceutical company restrict the ethnicity of patients participating in a medical trial or require patient genotype data?
What best describes the "1000 genomes" project?
What is NOT true of "exome" sequencing as compared to whole genome sequencing?
What is meant by “$1000 genome” and “personalized medicine”; how might readily available genetic information be used to provide better medical diagnostics and treatment?
What are some current barriers slowing deployment of personalized medicine?
Paper For Above Instructions
Population Genetics Focus
Population genetics is a subfield of genetics that deals with the genetic composition of populations and how it changes over time due to evolutionary processes. It draws on principles from both Mendelian genetics and the theory of evolution, focusing primarily on allele frequencies and genotype distributions. Evolutionary changes in both population allele frequencies and genotype frequencies are essential aspects, but the more precise definition encompasses allele and genotype frequencies within populations.
Hardy-Weinberg Equilibrium
The Hardy-Weinberg equilibrium is a fundamental principle in population genetics that relates allele frequencies to genotype frequencies in a population at equilibrium. The two genetically-determinable quantities that this equilibrium relates are allele and genotype frequencies. Understanding these frequencies allows researchers to predict genetic variation and study the population's evolution over generations.
Hardy-Weinberg Frequencies Calculation
In a population where the allele frequencies of "a" and "A" are 30% and 70%, respectively, we can apply the Hardy-Weinberg principle to determine the expected frequencies of the genotypes. According to the Hardy-Weinberg equation, p^2 + 2pq + q^2 = 1, where p is the frequency of the dominant allele (A), and q is the frequency of the recessive allele (a), we can calculate the expected frequencies as follows:
Let p = 0.7 (A) and q = 0.3 (a). Then:
- AA (p^2) = 0.7^2 = 0.49 or 49%
- Aa (2pq) = 2 0.7 0.3 = 0.42 or 42%
- aa (q^2) = 0.3^2 = 0.09 or 9%
This suggests that the expected Hardy-Weinberg frequencies of the genotypes are aa = 9%, AA = 49%, and aA = 42%.
Evaluating SNP Genotyping Technology
The Hardy-Weinberg relationship can be pivotal in evaluating new SNP genotyping technologies. If the observed genotype and allele frequencies fit the Hardy-Weinberg expectations, we can conclude that the technology is sound, as it accurately reflects genetic variation in the population. Conversely, discrepancies may indicate that the technology struggles with accurately calling SNPs, necessitating further scrutiny and potential refinements.
Focus of Pharmacogenomics
Pharmacogenomics is a burgeoning field at the intersection of pharmacology and genomics, aiming to understand how an individual's genetic makeup influences their response to drugs. The focus here is on the relationships between the metabolism of pharmaceuticals and the genetic pathways involved. By analyzing genetic variants, researchers can customize medication plans, leading to more effective treatment protocols tailored to the individual's genetic profile.
Patient Demographics in Medical Trials
Pharmaceutical companies often restrict trial participant ethnicity or require genotype data to sample genetic variation effectively. This approach allows for a clearer understanding of genetic influences on drug metabolism and responses, eventually reducing adverse drug reactions and optimizing therapeutic outcomes. The goal is to minimize potential genetic variation that may cloud the results and yield more conclusive evidence on drug effectiveness.
The "1000 Genomes" Project
The "1000 Genomes" project is an ambitious endeavor aimed at cataloging human genetic variation comprehensively. The initiative seeks to create a deep catalog of human genetic variation that represents ethnic and geographic diversity, rather than just focusing on a specified number of individual genomes. This diversity is crucial in understanding complex traits and diseases, making it a cornerstone for future medical genomics research.
Exome Sequencing vs. Whole Genome Sequencing
Exome sequencing is a cost-effective method focusing on sequencing only the protein-coding regions of the genome, which constitutes about 1-2% of the total DNA. This approach allows for cheaper and faster genetic analysis. However, it can miss crucial genomic features, such as non-coding regulatory regions and RNA genes, potentially leading to incomplete genetic assessments as compared to whole genome sequencing, which covers the entire genome.
$1000 Genome and Personalized Medicine
The term "$1000 genome" refers to the significant drop in the cost of sequencing an individual's entire genome, bringing it to a price point where personal genomics could become widely accessible. Personalized medicine is the application of genetic information to provide tailored medical diagnostics and treatments. Accessible genetic data can enhance disease prevention strategies, guide therapeutic interventions more precisely, and ensure a more personalized approach to health care.
Barriers to Personalized Medicine Deployment
Despite major advancements, several barriers impede the widespread deployment of personalized medicine. One of the primary obstacles is the integration of genetic data into existing health care systems, which can be costly and complex. Furthermore, concerns regarding patient privacy, ethical dilemmas surrounding genetic data, and the need for updated regulatory frameworks present significant challenges. Additionally, the lack of education among healthcare professionals about genetics can hinder the adoption of personalized strategies in patient care.
References
- Hartl, D. L., & Clark, A. G. (2007). Principles of Population Genetics. Sinauer Associates.
- Mammen, A. L., & Kaczanowska, K. (2019). The role of allele and genotype frequencies in population genetics studies. Genetics and Molecular Biology, 42(3), 487-499.
- Devlin, B., & Risch, N. (1995). A comparison of linkage disequilibrium in genetic mapping of human populations. Human Heredity, 45(5), 273-284.
- McCarthy, M. I. (2010). Genomics, Type 2 Diabetes, and Obesity. New England Journal of Medicine, 363(24), 2371-2380.
- Collins, F. S., Morgan, M., & Patrinos, A. (2003). The Human Genome Project: Lessons from the Past and Plans for the Future. The 2003 National Human Genome Research Institute Report.
- Mardis, E. R. (2008). Next-Generation DNA Sequencing Methods. Annual Review of Analytical Chemistry, 1(1), 387-404.
- Flint, J., & Mott, R. (2001). Finding the Key to Human Disease. Nature, 414(6863), 704-709.
- Schwartz, M. K., & Kohn, L. M. (2009). The role of exome sequencing in the clinical diagnosis of genetic disorders. Nature Reviews Genetics, 10(9), 649-657.
- Wetterstrand, K. (2021). DNA Sequencing Costs: Data from the NHGRI Genomic Sequencing and Monitoring Center. National Human Genome Research Institute.
- Ginsburg, G. S., & Phillips, K. A. (2018). Precision medicine: From science to value. Health Affairs, 37(5), 768-775.