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Day 3: Genetics Selcen Guzey and Tamara Moore

Day 3: Genetics Selcen Guzey and Tamara Moore. University of Minnesota. Agenda. Teaching Genetics- Challenges, misconceptions, strategies, and questions Content Assessment Genetic Variation Mutations Gene expression Lunch Integrating Genetic Engineering: Plasmids and C. elegans lab.

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Day 3: Genetics Selcen Guzey and Tamara Moore

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  1. Day 3: Genetics Selcen Guzey and Tamara Moore University of Minnesota

  2. Agenda • Teaching Genetics- Challenges, misconceptions, strategies, and questions • Content Assessment • Genetic Variation • Mutations • Gene expression • Lunch • Integrating Genetic Engineering: Plasmids and C. elegans lab

  3. Teaching Genetics-Challenges, misconceptions, strategies, and questions • Use the post-it notes to create a “Parking Lot Chart” to be addressed throughout the day. Challenge: integrating engineering Misconceptions: structure of DNA Strategies: how to include published scientific data into my genetics unit Question: What is a plasmid?

  4. Genetic Variation How much variation do you think exists among humans? How much variation do you think exists between a human and a chimp? How much variation do you think exists between a human and a Caenorhabditis elegans (C. elegans) (Nematode)?

  5. Genomes • Genomes vary in size, number of genes, and gene density! • What genetic attributions allow humans to get by with no more genes than nematodes? • What makes humans and chimps so different?

  6. Human Genome

  7. DNA is the genetic material! What piece of history is missing in this picture? OR If you would like to recreate this picture who would be in this picture?

  8. Rosalind Franklin

  9. The structure of DNA

  10. The Structure of a Gene Poly-A signal sequence TATA and CAAT boxes, CG sequences Enhancer Promoter Intron Exon Intron Exon Exon Transcription start site Downstream Upstream

  11. Beta Hemoglobin (HbB) • Gene loci: 11p 15.5. • 3 exons (coding regions) scattered over 1600 base pairs • Yields a 626-bp mRNA transcript • Translated into a 147 amino acid polypeptide

  12. Beta Hemoglobin Gene and Sickle Cell Anemia • SCA is an autosomal recessive disease caused by a point mutation in the hemoglobin beta gene (HBB). • The production of a structurally abnormal hemoglobin (Hb), called HbS. • It occurs in 1 in 500 individuals of African descent. http://www.hhmi.org/biointeractive/media/DNAi_sicklecell-lg.mov

  13. Beta-Globin Gene • In this activity, you will examine the DNA sequence of the beta-globin gene from five people. • The codes represent the “sense” for the DNA sequence- Sense strand looks like mRNA. • Examine the gene sequence of Person A and B and find the difference in gene sequences of Person A and B (Look at position 6) • Examine the gene sequence of Person C, D, E, and F. Changes shown in bold!

  14. From DNA to mRNA 3’- TTCAGTCGT - 5’ DNA template strand 5’- AAGTCAGCA- 3’ DNA sense strand Transcription 5’- AAGUCAGCA- 3’ mRNA codon Translation Lys Ser Ala Protein

  15. The codon table for mRNA

  16. Questions for Discussion • Would a person who has a sequence like person A’s and a second sequence like person B’s have SC anemia? • Assume that a person has one allele with the sequence shown for person B and a second allele with the sequence shown for person F. Would the person have SC anemia? • Would person D and E have SC anemia? • A person can have a mutation on beta-globin gene and do not have SC. Propose a hypothesis to explain this.

  17. HBB-mutations • 100 types of mutations affect HBB, and only one point mutation causes SC Anemia. (Person B) • Splice mutations and mutations that occur in the HBB gene promoter region tend to cause a reduction, rather than a complete absence of β-globin chains and so result in milder disease. • Nonsense mutations (Person D) and frameshift mutations (Person F) tend to not produce any β-globin chains leading to severe disease. • Silence mutations are rare (Person C and E).

  18. More on Mutations • Gene mutation- Point mutations/single base substitutions • Substitutions CCC CCA • Frameshift mutations: insertions and deletions 5’ CCC CCA GGG 3’ 5’CCC CCA AGA GGG 3’ • Chromosomal Mutations • Deletion • Duplication • Inversion • Translocation Point mutations can be also categorized as: nonsense mutations, missense mutations, and silent mutations

  19. Testing for Sickle Cell Anemia Mst II recognizes the sequence CCTNAGG and cut the DNA where N is. DNA from normal homozygous individuals (AA), heterozygous carriers of the trait (AS), and homozygous sickle cell patients (SS) produces different sizes of restriction fragments. When the fragments are separated by gel electrophoresis the patterns result on the gel can be used to identify people with sickle cell anemia. • Which family members have the sickle cell genotype (SS), carrier genotype (AS), or the normal genotype (AA)? • Draw a pedigree showing inheritance of sickle cell anemia in the family. • Make a Punnett Square and explain the probabilities of various genotypes and phenotypes for offspring of 2 carrier parents.

  20. Mst II recognizes the sequence CCTNAGG

  21. Gene Expression: Switching genes on and off • Gene expression in humans is controlled by a variety of mechanisms: Transcriptional control that prevents mRNA from being synthesized: Heterochromatin vs. Euchromatin, acetylation/deacetylation of DNA, DNA methylation, transcription factors (activators and inhibators) Posttranscriptional control: Alternative mRNA splicing Transitional control: Initiation factors Posttransitional control: Protein activation Cancer results from genes that do not turn off properly. Cancer cells have lost their ability to regulate mitosis, resulting in uncontrolled cell division!

  22. Transcriptional Post transcriptional Transitional Post transitional

  23. Analyzing gene expressionCase Study - What’s wrong with Raymond? Presentation: Raymond, a 43-year-old man, was admitted to the hospital with a rapidly growing, painless mass in his armpit. He reports that he has been experiencing fever, weight loss, and night sweats during the past four months.

  24. Case Study - What’s wrong with Raymond? Tests: Enlarged lymph nodes were removed and the histology of the cells was examined, revealing abnormal B cells. A bone marrow biopsy was done, along with additional blood tests, X-rays, and CT scans. Diagnosis: Raymond has lymphoma.

  25. What is lymphoma? • http://video.about.com/lymphoma/Non-Hodgkin-s-Lymphoma.htm

  26. Case Study - What’s wrong with Raymond? Tests: Enlarged lymph nodes were removed and the histology of the cells was examined, revealing abnormal B cells. A bone marrow biopsy was done, along with additional blood tests, X-rays, and CT scans. Diagnosis: Raymond has diffuse large B-cell lymphoma (DLBCL).

  27. Diffuse large B-cell lymphoma What is it? What is the prognosis? Lymphoma = tumor of white blood cells type A # survivors type B 1 2 3 4 5 6 7 8 9 time (yrs)

  28. Does Raymond have Type A or Type B? http://emedicine.medscape.com/article/202677-media

  29. Challenge • Since there is no observable difference in Type A and Type B tumors, how could you determine which type of DLBCL your patient has? • Type A (GCB): good prognosis with chemotherapy • Type B (ABC): poor prognosis with chemotherapy http://emedicine.medscape.com/article/202677-media

  30. Proteins! • How could you find the protein differences between cells of Type A and Type B DLBCL?

  31. Differences in protein… Surrogate: differences in mRNA Stephen Friend et al. 2002 Sci. Am. 286:44-49 http://bcs.whfreeman.com/lodish6e Chapter 5 animation http://www.bio.davidson.edu/courses/genomics/chip.chip.html

  32. DNA microarray http://www.genome.gov/10000533

  33. DNA microarray analysis Analyze genes expressed in tumors Decreased mRNA in lymphoma Elevated mRNA in lymphoma Similar levels of mRNA http://llmpp.nih.gov/ http://lymphochip.nih.gov/signaturedb/ http://llmpp.nih.gov/lymphoma/explore_figure1.html

  34. How do we organize microarray data? • Compare your gene expression profile to others within your group, to identify those whose cancer cells share the most similarity to yours. • Organize all of the strips into a single panel, and stick them to a piece of paper using double-sided tape. • Can you classify the patients in your group into categories based on gene expression? If so, how many categories?

  35. Tumor Sample Gene

  36. Raymond type A # survivors type B Subgroup A Subgroup B 1 2 3 4 5 6 7 8 9 time (yrs) Lymphoma Case Study Prognosis: On the basis of gene expression patterns what is Raymond’s prognosis?

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