# Science of Opioid Dependence

LAB 10 Science of Opioid Dependence Homework In lab you learned about how scientists are studying possible genetic links to opioid dependence. Some of the genes being studied are related to reward pathways in the brain. Using the information you learned in lab, answer the following questions. Type your answers to the following questions and submit it through Turnitin links on eCampus by the due date. Use complete sentences and consider your writing style. Well written answers will convey your message better. 1. During the online session you were asked to write down a possible question. What was the question you wrote for this research study? (3 pts.) 2. What particular region of DNA was isolated and amplified for this study? Why was it selected? What was unique about this region? (4 pts.) 3. Briefly describe the steps or methods for studying genes. Start with targeting a gene region and end with gel electrophoresis. (4 pts.) Β© WVU Biology 2020 4. How does using gel electrophoresis help to determine the genotypes of individuals? Incorporate and explanation of how gel electrophoresis works in your answer. (4 pts.) 5. Students in previous sessions analyzed gel images and collected data for one class section and compared them to with numbers collected across lab sections in the course. Use the number provided by your TA to do calculations and comparisons. Below are formulas you will need for the calculations. πΊππππ‘π¦ππ πππππ’ππππ¦ = β πππππ£πππ’πππ π€ππ‘β πππππ‘π¦ππ (πΆπΆ, πΆπ, ππ ππ) π‘ππ‘ππ # πππππ£πππ’πππ # π΄ππππππ = (2 Γ # πππππ£πππ’πππ π€ππ‘β βππππ§π¦πππ’π πππππ‘π¦ππ (πΆπΆ ππ ππ)) + (# πππππ£πππ’πππ π€ππ‘β βππ‘ππππ§π¦πππ’π πππππ‘π¦ππ (πΆπ) (2 Γ β πππππ£πππ’πππ π€ππ‘β βππππ§π¦πππ’π πππππ‘π¦ππ (πΆπΆ ππ ππ)) + ( β πππππ£πππ’πππ π€ππ‘β βππ‘ππππ§π¦πππ’π πππππ‘π¦ππ (πΆπ)) π΄πππππ πππππ’ππππ¦ = 2 Γ π‘ππ‘ππ β πππππ£πππ’πππ a. Calculate genotype and allele frequencies for one lab section and across lab sections in the course. (3 pts.) One lab section: Genotypes of Individuals Genotype CC CT TT Total: Β© WVU Biology 2020 Number in Control Population Number in Case Population Genotype Frequencies Genotype Frequency in Control Population Frequency in Case Population # in Control Population # in Case Population Frequency in Control Population Frequency in Case Population Number in Control Population Number in Case Population Frequency in Control Population Frequency in Case Population # in Control Population # in Case Population CC CT TT Numbers of Alleles Alelles C T Allele Frequencies Alelles C T Combined Lab sections: Genotypes of Individuals Genotype CC CT TT Total: Genotype Frequencies Genotype CC CT TT Numbers of Alleles Alelles C T Β© WVU Biology 2020 Allele Frequencies Alelles Frequency in Control Population Frequency in Case Population C T b. Explain how one lab section compares to combined lab sections. (3 pts.) Statistical analyses, such as a chi square test, could help you determine if any differences you observe between control and case populations are real (significant) or occurring by chance. One output of chi square analysis is a probability value, or p-value. These p-values are a measure of how likely it is the differences happened by chance. A p-value of less than 0.05 is usually considered significant and means that 19 times out of 20 the difference or relationship between the identified data points are real and only one time out of 20 would the difference occur by chance. Also, while a p-value of 0.05 or less is considered significant, p-values can go much lower, indicating higher significance the lower they go. So a p-value 0.0001 is much more significant than 0.05 and offers stronger evidence that the difference is real. There are online calculators available for performing chi square tests. Go to https://www.socscistatistics.com/tests/ and select the chi square calculator for 5 ο΄ 5 (or less) contingency table to perform analyses for genotype and allele frequencies by entering categories (genotypes or alleles) and groups (control and case populations), and numbers of individuals in the calculator. Use the results to determine if there are significant differences between control and case populations. c. Do chi square analyses to determine if there are significant differences between control and case populations with regard to genotype and allele frequencies for your lab section and combined lab sections. (3 pts.) One lab section: p-values From Chi Square Analyses p-value from chi square analysis Genotype frequencies Allele frequencies Β© WVU Biology 2020 Significant difference? Combined Lab sections: p-values From Chi Square Analyses p-value from chi square analysis Significant difference? Genotype frequencies Allele frequencies d. Explain how your lab section compares to combined lab sections in the course. (3 pts.) e. What could account for differences between your lab section and across lab sections in course? Do you think one data set is more reliable than the other? Explain. (3 pts.) 6. What conclusions can you make about the case and control populations. Is there a genetic association to opioid dependence? (4 pts.) 7. Why is it inaccurate to say that if someone has a T or C allele for the rs1800497 SNP will become dependent on opioids? (4 pts.) Β© WVU Biology 2020 8. Current published research on the ANKK1 gene and the SNP rs1800497 showed that the frequency of the T allele was 38% in a control group and 44% in a group of opioid dependent participants in a study (Zhang et al. 2018). Chi square analysis resulted in a p-value of 0.04. Do your results align with published data? Explain. (4 pts.) 9. How do you think the methods for this lab (i.e. studying genes and DNA) could be used to address the opioid epidemic? (4 pts.) 10. Thinking more broadly than in the last question, what do you think could be done to address the opioid crisis? List at least two ideas you have. Explain why you think your suggestions would be effective. (4 pts.) Β© WVU Biology 2020 …

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