QuBi/bio203

BIOL 203 Lab 4. Bioinformatics Exercises

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Research in modern molecular genetics increasingly rely on genomic information and computation. The following exercises will expose you to the field of bioinformatics, including the use of online databases and statistical analysis of genetic data.

Introduction

DNA and its organization into genes makes up an organism's genotype. The expression and presentation of those genes in the organism's development, physiology, and physical appearance (physical traits) make up the phenotype of the organism. Phenotypic variations among individuals of a species (e.g., humans) are caused by genotype variations, environmental factors, and interactions between genetic and environmental factors. In other words, phenotypic variations among individuals often have complex, unclear mechanisms and are not necessarily due entirely to genetic differences.

In this lab section, we will explore the concepts of phenotype and genotype by looking at the variations in the TAS2R38 gene, which is responsible for part of the sensation of taste. The taste receptor protein TAS2R38 (taste receptor 2, member 38) has been associated with the ability to taste the bitter compound phenylthiocarbamide (PTC) (Kim et al. 2003). Although most people can taste PTC ("tasters"), a centain percentage of people cannot ("nontasters"). In this experiment, you will test your Taster phenotype as well as determine your Taster genotype and correlate the phenotype with the genotype data. Your results and those of your classmates will be combined to statistically validate if there is such a phenotype-genotype association.

Learning goals and outcomes

• Understand phenotype, genotype, and their association
• Be able to use the NCBI online databases
• Be able to predict genotype frequencies using Hardy-Weinberg equilibrium
• Be able to use the contingency test of genotype-phenotype associations

Web Exercise 1. Search for gene information using NCBI online databases

1. Point your browser to the NCBI Human Genome Resource page
2. Type in the "Find A Gene" search box "TAS2R38" and select "Homo sapiens" from the pull-down menu. Click "Go"
3. Select the first link, which leads to an NCBI Gene Card page. Use the Gene Card to identify the following information on TAS2R38 gene:
   1. NCBI GeneID
   2. Chromosome location
   3. Click on "GenBank" and identify its gene structure, including the length of primary transcript, coding sequences, 5'-UTR and 3'-UTR. Does it have any introns?
   4. Zoom out the Sequence View to find its neighboring genes. Zoom out to read DNA sequences.
4. Click the link to OMIM (under Phenotype) and find phenotypes associated with TAS2R38 gene
   1. What does OMIM stand for?
   2. What are the expected "taster" and "nontaster" frequencies within human populations?
   3. If the ability to taste bitterness is evolutionary advantageous, how are alleles contributing to "nontaster" maintained in population?
   4. Is the correlation between TAS2R38 gene variations and the PTC phenotype variations 100%? If not, what could be the other causes?

Web Exercise 2. Predict results of PCR and restriction analysis

On a printout of the DNA sequence of TAS2R38 gene (from the GenBank link, see above),

1. Identify 5'-UTR, 3'-UTR, start codon, and stop codon.
2. Identify the regions your PCR primers should bind using the Primer3 web server
   1. Point your browser to Primer3 Web Server
   2. Select "check_primer" in the top box, and "HUMAN" in the 2nd box
   3. Paste the raw gene sequence into the 3rd box: Go to the GenBank page and click "FASTA" near the top of page
   4. Paste the two primer sequences into the 4th and 6th boxes
   5. Click "Pick Primers"
3. Identify the base location that contains 785 C/T SNP
4. Copy and paste the expected 302-bp section and locate the Fnu4H1 site using the NEBcutter website
5. What are the expected lengths for the C/C, C/T, and T/T genotypes?

Statistical Exercise 1. Test Hardy-Weinberg Equilibrium

The Hardy-Weinberg Equilibrium (HWE) predicts the genotype frequencies at a genetic locus in a random-mating population. If two alleles (e.g., C, T) are segregating in a diploid population with respective frequencies of p and q, if the mating is random, and if there is no fitness difference between the two alleles, then the genotypes frequencies (expected from random Mendelian segregation) are stably maintained throughout the generations with the following values: C/T (2pq), T/T (q²), and C/C (p²).

1. After PCR/sequencing experiments, collect genotype frequencies in your class as a group using the following table:

Table 1. Observed Genotype Frequencies

	C/C	C/T	T/T	Total
Count	NCC	NCT	NTT	N
Frequency	fCC	fCT	fTT	1

2. Calculate SNP allele frequencies using the following formula:

fC=(2NCC + NCT)/N

fT=(2NTT + NCT)/N

3. Predict expected genotype frequencies using HWE:

Table 2. Predicted Genotype Frequencies

	C/C	C/T	T/T	Total
Frequency	fC x fC	2 x fC x fT	fT x fT	1
Count	(multiply the above by N)	(multiply the above by N)	(multiply the above by N)	N

4. Test the goodness-of-fit between the observed (Table 1) and expected (Table 2) genotype frequencies using the Chi-Squared Test:

Χ² = ∑[(N_observed - N_expected)²/N_expected] (sum over all three genotypes)

5. Exit Questions:

1. Compare your Χ² value with the critical value of Χ² (with 2 degrees of freedom)=5.99. If your value is greater than 5.99, it is considered statistically significant at the level of p=0.05. It means that there is less than a 1 to 20 chance of getting a value equal or greater than your value. A significant Chi-squared value in this case would suggest a deviation from HWE.
2. What are the possible causes of deviation from HWE? Biological? Statistical?
3. However, if your result is not significant (i.e., < 5.99), the interpretations could be either (1) in support of HWE, or (more scientifically) (2) there is no evidence for deviation from HWE based on the sample of your class.

Statistical Exercise 2. Test phenotype-genotype association

Genome-Wide Association Study (GWAS) is a method for mapping phenotypes to genotypes. In a typical GWAS study, frequencies of alleles (e.g., C or T at position 785) are determined in a sample of affected individuals (the "cases") as well as in a sample of unaffected individuals (the "controls"). For example, the following table shows results of a case-control study at a locus segregating with two alleles (C and T):

Table 3. Sample Genotype Frequencies

	T/T	T/C	C/C	Total
Case	0	24	127	?
Control	9	68	114	?
Total	?	?	?	?

Association between the genotype and the phenotype could be assessed with a contingency table analysis (also using chi-square, as in the preceding exercise). In this case, Χ² = 26.4, p=0.0005, suggesting a significant association between genotypes and diseases. (In this case, the result suggests that C/C genotypes are over-represented in disease cases.)

1. Perform an online contingency table analysis using data in Table 3.

2. Based on Table 3, fill the following table with allele (not) counts and perform a 2-by-2 contingency table analysis using the link above. Is there a statistically significant association between alleles and disease phenotype? Which allele (C or T) is over-represented in disease cases?

Table 4. Sample Allele Frequencies

	T	C	Total
Case	?	?	?
Control	?	?	?
Total	?	?	?

3. Following the above two examples, perform both the genotype and allele association tests using the class data.

1. Draw a table for three genotypes
2. Draw a table for the two alleles

4. Exit Questions:

1. Is there a statistically significant association between the genotypes and the Taster phenotype?
2. Is there a statistically significant association between the alleles and the Taster phenotype?
3. Which allele (C or T) is over-represented in the Nontasters?
4. Is the association 100% (i.e., are there exceptions)?
5. What could be other causes if there are exceptions?