Table of contents
- 1. Introduction to Genetics51m
- 2. Mendel's Laws of Inheritance3h 37m
- 3. Extensions to Mendelian Inheritance2h 41m
- 4. Genetic Mapping and Linkage2h 28m
- 5. Genetics of Bacteria and Viruses1h 21m
- 6. Chromosomal Variation1h 48m
- 7. DNA and Chromosome Structure56m
- 8. DNA Replication1h 10m
- 9. Mitosis and Meiosis1h 34m
- 10. Transcription1h 0m
- 11. Translation58m
- 12. Gene Regulation in Prokaryotes1h 19m
- 13. Gene Regulation in Eukaryotes44m
- 14. Genetic Control of Development44m
- 15. Genomes and Genomics1h 50m
- 16. Transposable Elements47m
- 17. Mutation, Repair, and Recombination1h 6m
- 18. Molecular Genetic Tools19m
- 19. Cancer Genetics29m
- 20. Quantitative Genetics1h 26m
- 21. Population Genetics50m
- 22. Evolutionary Genetics29m
15. Genomes and Genomics
Comparative Genomics
1:26 minutes
Problem 23c
Textbook Question
Textbook QuestionYeager, M., et al. [(2007) Nature Genetics 39:645–649] and Sladek, R., et al. [(2007) Nature 445:881–885] have used single-nucleotide polymorphisms (SNPs) in genome-wide association studies (GWAS) to identify novel risk loci for prostate cancer and Type 2 diabetes, respectively. Each study suggests that disease-risk genes can be identified that significantly contribute to the disease state. Given your understanding of such complex diseases, what would you determine as reasonable factors to consider when interpreting the results of GWAS?
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Key Concepts
Here are the essential concepts you must grasp in order to answer the question correctly.
Single-Nucleotide Polymorphisms (SNPs)
Single-nucleotide polymorphisms (SNPs) are the most common type of genetic variation among people, where a single nucleotide in the genome is altered. These variations can influence how individuals respond to diseases, medications, and environmental factors. In genome-wide association studies (GWAS), SNPs are used as markers to identify genetic loci associated with complex diseases, helping researchers pinpoint potential risk factors.
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Genome-Wide Association Studies (GWAS)
Genome-wide association studies (GWAS) are research methods used to identify genetic variants associated with specific diseases by scanning the genomes of many individuals. By comparing the frequency of SNPs in affected versus unaffected individuals, researchers can identify loci that may contribute to disease risk. GWAS have been instrumental in uncovering genetic factors for complex diseases like prostate cancer and Type 2 diabetes.
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Complex Diseases
Complex diseases, such as prostate cancer and Type 2 diabetes, are influenced by multiple genetic and environmental factors rather than a single gene mutation. These diseases often exhibit polygenic inheritance, where many genes contribute to the risk and severity of the condition. Understanding the multifactorial nature of these diseases is crucial when interpreting GWAS results, as it highlights the need to consider gene-environment interactions and the cumulative effect of multiple risk alleles.
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