Bioinformatics Unit 3: Exercise

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Unit 3: Molecular Genetics
Exercise

Pre-Exercise

Exercise

Part 1- Exploring approaches to genetic analysis

Part 2- Expression analysis using microarrays

Summary questions

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Exercise: Mapping disease genes & Analyzing microarray data


Objectives:

1. Develop an understanding of gene expression and the means of identification and analysis.

  • Review expression analysis, old and new
  • Understand the basics of microarray analysis
  • Appreciate different applications of microarrays

2. Understand polymorphisms.

  • Compare types of polymorphisms and their origins
  • Role of polymorphisms in health and disease
  • Utility of polymorphisms in different types of analysis

3. Understand the ethical issues related to bioinformatics.

Introduction:

In Unit 2, you found how the use of genetic markers is useful in comparative genomic mapping. Finding and using genetic markers has long been recognized as being extremely useful in a wide variety of applications. Examples include recognition of disease gene polymorphisms, use in studies of pathogens and epidemiology, selection of plants for desirable agricultural characteristics such as seed yield or height, and analysis of forensic evidence for civil and criminal court cases. The combination of more means of identification of polymorphisms along with the capability of genomic analysis has brought considerable improvements in these areas of inquiry. Additionally as a result of these advances, other areas are undergoing rapid expansion and development. Gene identification and association with function(s) in metabolism, development and cell differentiation, and various response systems are some examples. Means of identifying polymorphisms include restriction fragment length polymorphism [RFLP] and use of probes for specific gene markers, either as part of the gene in question or a closely linked marker to the gene of interest.

Until recently, expression analysis has been accomplished by studying one or a few genes at a time. With the advent of microarrays, expression analysis has taken giant leaps forward with the capability to screen in the range of 20,000 genes at a time. You will have the opportunity to become familiar with the foundation of this powerful methodology in preparation for the related project for this unit.

There are summary questions at the end of this section. Points = 10. Due 10/9 midnight or 10/14.

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Pre-Exercise:

1. Review the following in any recent molecular biology or genetics text.

  • Gene mapping
  • Genetic linkage
  • Polymorphisms
  • Acronyms to know
    • EST
    • RFLP
    • SNP
    • SSP
    • STP
    • VNTR

2. For an introduction to restriction enzymes, try:

http://www.accessexcellence.org/AE/AEC/CC/restriction.html

http://www.ultranet.com/~jkimball/BiologyPages/R/RestrictionEnzymes.html [This site also gives links to information on DNA sequencing and recombinant DNA.]

3. For an online review of Hardy-Weinburg and for the basics on human gene mapping, try Jacki Wicks and T. P. Speed's lecture notes for Week 5: Genetic epidemiology: Association and linkage:

http://oz.berkeley.edu/users/terry/Classes/s260.1998/Week5/week5/week5.html

4. For an introduction to the basics of microarray methods, try the following animated tutorial:

http://www.bio.davidson.edu/courses/genomics/chip/chip.html
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Exercise:

Part 1: Exploring approaches to genetic analysis

Tissue typing provides an excellent example of an activity which has been accomplished using a variety of methodologies over the years, including the development and use of probes. Screening for human major histocompatibility complex [MHC] antigens is required for tissue typing of possible donors for organ transplants and of the recipients. It is also useful in genetic linkage analysis for a variety of disease associations. Originally, screening was done using a cytotoxicity assay system for some of the loci, and a mixed lymphocyte response [MLR] assay for other loci. Use of RFLPs was introduced in the late 1980's followed by introduction of PCR methods in the 1990's. Microarrays are now being developed and introduced for HLA screening.

To become familiar with HLA and tissue typing, try the following tutorial which includes information on the different screening methods:

http://www.aseatta.org.au/educatio.htm

For cutting edge approaches, the following papers are of interest:

Feolo M, Fuller TC, Taylor M, Zone JJ, Neuhausen SL, 2001. A strategy for high throughput HLA-DQ typing. J Immunol Methods 2001 Dec 1;258(1-2):65-71 [Elsevier]

Cai H, White PS, Torney D, Deshpande A, Wang Z, Keller RA, Marrone B, Nolan JP., 2000. Flow cytometry-based minisequencing: a new platform for high-throughput single-nucleotide polymorphism scoring. Genomics 2000 Jun 1;66(2):135-43. Erratum in: Genomics 2000 Nov 1;69(3):395 [Elsevier]

If you are interested in more resources on HLA and typing, a worthy site to visit is the Anthony Nolan Bone Marrow Trust:

http://www.anthonynolan.org.uk/HIG.

For a different application using probes, check out the following site:

http://aem.asm.org/cgi/content/full/65/11/4775?view=full&pmid=10543785

The HLA allele with the strongest association with a disease is HLA B27. It has a strong association frequency with ankylosing spondylitis and one type of arthritis. Therefore it is of interest to screen for the presence of this particular allele. The complete mRNA sequence for B27 is in GenBank:

gi|187657|gb|M12678.1|HUMMHB27A

You may be interested in reading the following paper on HLA-B27, which combines two computational methods to identify peptide sequences from Chlamydia trachomatis predicted to be involved in binding B27 and which may be involved in the pathogenesis of B27 associated disease.

Kuon W, et al, 2001. Identification of HLA-B27-restricted peptides from the Chlamydia trachomatis proteome with possible relevance to HLA-B27-associated diseases. J Immunol Oct 15;167(8):4738-4746.
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Part 2- Expression analysis using microarrays

A. Explore microarrays. In the pre-exercise, you should have had some fun with the animated tutorial. If not, go back. For a more detailed exploration, try the following:

http://www.bio.davidson.edu/courses/genomics/chip/chipreal.html

http://www.bsi.vt.edu/ralscher/gridit/intro_ma.htm

Resource list for microarrays:

http://www.deathstarinc.com/science/biology/chips.html


B. Design a microarray.

Using the original methods, about 165 allelic differences were identified in the following loci of HLA: A, B, C, DR, DQ, and DP. At the sequence level, the number of allelic differences are far greater, and therefore an assay detecting them would be more sensitive. Design a microarray to rapidly screen for MHC antigens expressed on peripheral blood WBCs.

1. Outline what you would need to make the arrays, how you would design it to maximize data collection [including all accessory controls], and how you would intend to analyze the results.

2. To run the assay, let the following be standards: positive controls are labeled red; unknowns [samples] are labeled green. Give an example of some expected results, including the resulting color of the reactions.

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Summary Questions:

Try to limit your answers to 1-2 typed pages [12 pt font]. This length should be sufficient for your comments and any appropriate copy/pasted examples. [You need not retype or copy/paste the questions as part of your responses.]

1. Compare and contrast the following terms:

a. gene mapping vs. linkage analysis

b. RFLP vs. SNP analysis

2. Describe three approaches to analyzing disease association with genetic markers.

3. Give two reasons why there can be genetic marker-disease association but Hardy-Weinberg disequilibrium at a marker locus.

4. Designing a microarray:

a. Outline what you would need to make the arrays, how you would design it to maximize data collection [including all accessory controls], and how you would intend to analyze the results.

b. To run the assay, let the following be standards: positive controls are labeled red; unknowns [samples] are labeled green. Give an example of some expected results, including the resulting color of the reactions.

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Updated 10/9/03 by thatcher@sonoma.edu; bsc@classroomtools.com