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; <div style="font-size:180%">BIOL 203 Bioinformatics Exercises for Lab 13</div>
; <div style="font-size:180%">BIOL 203 Bioinformatics Exercises for Lab 13</div>
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Research in modern molecular genetics increasingly relies 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.
==Test phenotype-genotype association==
 
===Introduction: Contingency Test===
==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 identify sequence variations at which of the two loci are associated with the ability to taste the bitter compound phenylthiocarbamide (PTC). We will use a statistical test called "Contingency Analysis" to analyze the genotypic and phenotypic data collected from the class.
 
==Learning goals and outcomes==
* Be able to use the NCBI online databases
* Be able to compare genes among species using phylogeny
* Be able to perform the contingency-table test of genotype-phenotype associations
 
==Statistical Exercise. 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 hypothetical case-control study at a locus segregating with two alleles (C and T):
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 hypothetical case-control study at a locus segregating with two alleles (C and T):


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Association between the genotype and the phenotype could be assessed with a [http://en.wikipedia.org/wiki/Contingency_table contingency table analysis] (also using chi-square, as in the preceding exercise). In this case, &Chi;<sup>2</sup> = 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.)
Association between the genotype and the phenotype could be assessed with a [http://en.wikipedia.org/wiki/Contingency_table contingency table analysis] (also using chi-square, as in the preceding exercise). In this case, &Chi;<sup>2</sup> = 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 [http://www.physics.csbsju.edu/stats/contingency.html online contingency table analysis] using the hypothetical data in Table 1.
# Perform an [http://www.physics.csbsju.edu/stats/contingency.html online contingency table analysis] using the hypothetical data in Table 1.


2. Deriving from Table 1, fill the following table with allele counts. Then 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 (i.e., statistically associated with) disease cases?
# Deriving from Table 1, fill the following table with allele counts. Then 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 (i.e., statistically associated with) disease cases?
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Table 2. Sample Allele Frequencies
Table 2. Sample Allele Frequencies
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3. Following the above two examples, perform both the genotype and allele association tests using the class data.
===Test genotype/allele association at locus A===
Following the above two examples, perform both the genotype and allele association tests using the class data.
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Table 3a. Genotype counts at Locus A
Table 3a. Genotype counts at Locus A
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===Test association at Locus B===
Table 4a. Genotype counts at Locus B for each phenotype
Table 4a. Genotype counts at Locus B for each phenotype
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4. Exit Questions:
===Exit Questions===
# Which of the two genes shows significant ''genotype'' association with the PTC Taster/Non-Taster phenotype?
# Which of the two genes shows significant ''genotype'' association with the PTC Taster/Non-Taster phenotype?
# Is there a statistically significant association between the ''alleles'' and the Taster phenotype?  
# Is there a statistically significant association between the ''alleles'' and the Taster phenotype?  

Revision as of 02:31, 2 April 2016

BIOL 203 Bioinformatics Exercises for Lab 13

Test phenotype-genotype association

Introduction: Contingency Test

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 hypothetical case-control study at a locus segregating with two alleles (C and T):

Table 1. 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 the hypothetical data in Table 1.
  1. Deriving from Table 1, fill the following table with allele counts. Then 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 (i.e., statistically associated with) disease cases?

Table 2. Sample Allele Frequencies

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

Test genotype/allele association at locus A

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

Table 3a. Genotype counts at Locus A

A1/A1 A1/A2 A2/A2 Row Sum
Taster ? ? ? ?
Non-Taster ? ? ? ?
Column Sum ? ? ? ?

Calculate allele counts & then test for association

Table 3b. Allele counts at Locus A

A1 A2 Row Sum
Taster ? ? ?
Non-Taster ? ? ?
Column Sum ? ? ?

Test association at Locus B

Table 4a. Genotype counts at Locus B for each phenotype

B1/B1 B1/B2 B1/B3 B2/B2 B2/B3 B3/B3 Row Sum
Taster ? ? ? ? ? ? ?
Non-Taster ? ? ? ? ? ? ?
Column Sum ? ? ? ? ? ? ?

Calculate allele counts & then test for association Table 4b. Allele counts at Locus A

B1 B2 B3 Row Sum
Taster ? ? ? ?
Non-Taster ? ? ? ?
Column Sum ? ? ? ?

Exit Questions

  1. Which of the two genes shows significant genotype association with the PTC Taster/Non-Taster phenotype?
  2. Is there a statistically significant association between the alleles and the Taster phenotype?
  3. Which genotype is over-represented in the Non-Tasters?
  4. Which allele is over-represented in the Non-Tasters?
  5. Are there exceptions? What are possible causes for exceptions?

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 in 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. Cross-species comparisons with HomoloGene

  1. From the NCBI "TAS2R38" Gene page, click "HomoloGene" link under the "Related Information" (right-side navigation panel)
  2. You should see a page listing TAS2R38 orthologous (i.e., same gene in different species) genes from 7 mammalian species, including human (Homo sapiens), chimpanzee (Pan troglodytes), macaque (Macaca mulatta), dog (Canis lupus familiaris), cow (Bos taurus), rat (Rattus norvegicus), and mouse (Mus musculus).
  3. Write down your expectations for the following species relationships:
    1. Is chimpanzee more closely related to macaque or to human?
    2. Is dog more related to mouse or to cow?
    3. Is rat and mouse more closely related than human and chimpanzee?
  4. Click on the link "Show Pairwise Alignment Scores" under "Protein Alignments" and fill in the following table when the page loads. Do these sequence-comparison results change your expectations in the above? Explain.
Species pair % Protein Sequence Identity % DNA Seq Identity
Chimp-Human ? ?
Chimp-Macaque ? ?
Dog-Cow ? ?
Dog-Mouse ? ?
Rat-Mouse ? ?

You can find exact differences by clicking on "Blast" for each pairwise comparisons. Lastly, obtain a phylogenetic tree of TAS2R38 protein sequences from these 7 species using the phylogeny.fr web

  1. Click "Show Multiple Alignment"
  2. Click "Download" and, when the page uploads, click "download" again
  3. Go to the the phylogeny.fr web and select "Phylogenetic Analysis" and then "One Click" analysis
  4. Copy and paste your downloaded sequences into the text box and click on "Submit"
  5. When analysis is finished, you should see a phylogenetic tree. Answer the following questions:
    1. Define "orthologous genes"
    2. What do tree nodes represent?
    3. What do tree branches and branch length represent?
    4. How do you determine species relatedness based on a phylogenetic tree?

(This short tutorial on phylogenetic tree may help).

Web Exercise 3. 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 from the GenBank page
    4. Paste the two primer sequences (use only the sequences within {}) into the 4th and 6th boxes: 
      (p2283) ttttggatccAACTGGCAGAa{TAAAGATCTCAATTTAT}; (p2285) ttttggatcc{AACACAAACCATCACCCCTATTTT}
    5. Click "Pick Primers"
  3. Identify the base location that contains 785 C/T SNP
  4. Copy and paste the expected 303-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?
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