QuBi/modules/biol203-geno-pheno-association: Difference between revisions

From QiuLab
Jump to navigation Jump to search
imported>Weigang
(Created page with "; <div style="font-size:180%">BIOL 203 Bioinformatics Exercises for Lab 13</div> ---- Research in modern molecular genetics increasingly relies on genomic information and comp...")
 
imported>Lab
No edit summary
 
(23 intermediate revisions by 2 users not shown)
Line 1: Line 1:
; <div style="font-size:180%">BIOL 203 Bioinformatics Exercises for Lab 13</div>
; <div style="font-size:180%">BIOL 203 Summer 2020 - Bioinformatics Exercises for Lab 11</div>
----
----
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: GWAS & 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" e.g. disease) 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):


==Introduction==
<center>
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.
Table 1. Sample Genotype Frequencies
{| class="wikitable"
|-
! !! T/T !! T/C !! C/C !! Total
|-
| Case || 0 || 24 || 127 || ?
|-
| Control || 9 || 68 || 114 || ?
|-
| Total || ? || ? || ? || ?
|}
</center>


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) [http://www.ncbi.nlm.nih.gov/pubmed/12595690 (Kim et al. 2003)]. Although most people can taste PTC ("tasters"), a certain percentage of people cannot ("nontasters"). In this experiment, you will test your Taster phenotype as well as determine your Taster genotype. Subsequently, your results and those of your classmates will be combined to statistically validate if there is an association between the Taster phenotype and TAS2R38 genotypes.
Association between the genotype and the phenotype could be assessed with a [http://en.wikipedia.org/wiki/Contingency_table contingency table analysis]. In this case, &Chi;<sup>2</sup> = 26.4, p<0.0005, suggesting a significant association between genotypes and diseases. (By comparing the expected and observed counts, one could conclude that the C/C genotypes are over-represented in disease cases.)


==Learning goals and outcomes==
1. Perform an [http://www.physics.csbsju.edu/stats/contingency.html online contingency table analysis] using the hypothetical data in Table 1. Click on "other contingency tables" and do a 2-rows and 3-columns test with the data above. Your &Chi;<sup>2</sup> should be 26.4.
* 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


==Web Exercise 1. Search for gene information using NCBI online databases==
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.
# Point your browser to the [http://www.ncbi.nlm.nih.gov/genome/guide/human/ NCBI Human Genome Resource] page
For example, in the controls, the number of T alleles is: 18 + 68 = 86 , because homozygotes have two alleles and heterozygotes have one.
# Type in the "Find A Gene" search box "TAS2R38" and select "Homo sapiens" from the pull-down menu. Click "Go"
# Select the first link, which leads to an NCBI Gene Card page. Use the Gene Card to identify the following information on TAS2R38 gene:
## NCBI GeneID
## Chromosome location
## 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?
## Zoom out the Sequence View to find its neighboring genes. Zoom in to read DNA sequences.
# Click the link to OMIM (under '''Phenotype''') and find phenotypes associated with TAS2R38 gene
## What does OMIM stand for?
## What are the expected "taster" and "nontaster" frequencies within human populations?
## If the ability to taste bitterness is evolutionary advantageous, how are alleles contributing to "nontaster" maintained in population?
## 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==
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?
# From the NCBI "TAS2R38" Gene page, click "HomoloGene" link under the "Related Information" (right-side navigation panel)
# 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'').
# Write down your expectations for the following species relationships:
## Is chimpanzee more closely related to macaque or to human?
## Is dog more related to mouse or to cow?
## Is rat and mouse more closely related than human and chimpanzee?
# 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.
<center>
<center>
Table 2. Sample Allele Frequencies
{| class="wikitable"
{| class="wikitable"
|-
|-
! Species pair !! % Protein Sequence Identity !! % DNA Seq Identity
! !! T !! C !! Total
|-
| Case || ? || ? || ?
|-
| Control || ? || ? || ?
|-
|-
| Chimp-Human || ? || ?
| Total || ? || ? || ?
|}
</center>
 
===Test association with locus A===
Following the above two examples, perform both the genotype and allele association tests using the class data.
<center>
Table 3a. Genotype counts at Locus A
{| class="wikitable"
|-
|-
| Chimp-Macaque || ? || ?
!  !! A1/A1 !! A1/A2 !! A2/A2 !! Row Sum
|-
|-
| Dog-Cow || ? || ?
| Taster || ? || ? || ? || ?
|-
|-
| Dog-Mouse || ? || ?
| Non-Taster || ? || ? || ? || ?
|-
|-
| Rat-Mouse || ? || ?
| Column Sum || ? || ? || ? || ?
|}
|}
</center>
</center>
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 [http://www.phylogeny.fr the phylogeny.fr web]
# Click "Show Multiple Alignment"
# Click "Download" and, when the page uploads, click "download" again
# Go to the [http://www.phylogeny.fr the phylogeny.fr web] and select "Phylogenetic Analysis" and then "One Click" analysis
# Copy and paste your downloaded sequences into the text box and click on "Submit"
# When analysis is finished, you should see a phylogenetic tree. Answer the following questions:
## Define "orthologous genes"
## What do tree nodes represent?
## What do tree branches and branch length represent?
## How do you determine species relatedness based on a phylogenetic tree?
([http://evolution.berkeley.edu/evolibrary/article/evo_05 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),
# Identify 5'-UTR, 3'-UTR, start codon, and stop codon.
# Identify the regions your PCR primers should bind using the Primer3 web server
## Point your browser to [http://primer3.ut.ee/ Primer3 Web Server]
## Select "check_primer" in the top box, and "HUMAN" in the 2nd box
## Paste the raw gene sequence into the 3rd box from the [http://www.ncbi.nlm.nih.gov/nuccore/NC_000007.13?report=fasta&from=141672259&to=141673743&strand=true GenBank page]
## Paste the two primer sequences (use only the sequences within {}) into the 4th and 6th boxes: <pre>(p2283) ttttggatccAACTGGCAGAa{TAAAGATCTCAATTTAT}; (p2285) ttttggatcc{AACACAAACCATCACCCCTATTTT}</pre>
## Click "Pick Primers"
# Identify the base location that contains 785 C/T SNP
# Copy and paste the expected 303-bp section and locate the Fnu4H1 site using the [http://tools.neb.com/NEBcutter2/ NEBcutter website]
# What are the expected lengths for the C/C, C/T, and T/T genotypes?
==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):


Calculate allele counts & then test for association
<center>
<center>
Table 3. Sample Genotype Frequencies
Table 3b. Allele counts at Locus A
{| class="wikitable"
{| class="wikitable"
|-
|-
! !! T/T !! T/C !! C/C !! Total
! !! A1 !! A2 !! Row Sum
|-
|-
| Case || 0 || 24 || 127 || ?
| Taster || ? || ? || ?
|-
|-
| Control || 9 || 68 || 114 || ?
| Non-Taster || ? || ? || ?
|-
|-
| Total || ? || ? || ? || ?
| Column Sum || ? || ? || ?
|}
|}
</center>
</center>


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.)
===Test association with Locus B===
 
Table 4a. Genotype counts at Locus B for each phenotype
1. Perform an [http://www.physics.csbsju.edu/stats/contingency.html online contingency table analysis] using the hypothetical data in Table 3.
 
2. Deriving from Table 3, 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?
<center>
<center>
Table 4. Sample Allele Frequencies
{| class="wikitable"
{| class="wikitable"
|-
|-
! !! T !! C !! Total
! !! B1/B1 !! B1/B2 !! B1/B3 !! B2/B2 !! B2/B3 !! B3/B3!! Row Sum
|-
|-
| Case || ? || ? || ?
| Taster || ? || ? || ? || ? || ? || ? || ?
|-
|-
| Control || ? || ? || ?
| Non-Taster || ? || ? || ? || ? || ? || ? || ?
|-
|-
| Total || ? || ? || ?
| Column Sum || ? || ? || ? || ? || ? || ? || ?
|}
|}
</center>
</center>
 
Calculate allele counts & then test for association
3. Following the above two examples, perform both the genotype and allele association tests using the class data.
Table 4b. Allele counts at Locus A
# Design a 2-by-3 contingency table for three genotypes
# Design a 2-by-2 contingency table for the C/T alleles
# Negative control: Instead of testing the association of the Taster/Non-taster phenotype with the C/T alleles, test the association of the same phenotype with another genetic factor, e.g., the gene determining the eye color (assuming that it is determined by a single gene with two allele Blue & Brown, with the Brown gene as dominant). Your contingency table would look like the one in the following table:
<center>
<center>
Table 5. Association of Taster/Non-taster with eye color
{| class="wikitable"
{| class="wikitable"
|-
|-
! !! Blue Eye !! Brown Eye !! Total
! !! B1 !! B2 !! B3 !! Row Sum
|-
|-
| Taster || ? || ? || ?
| Taster || ? || ? || ? || ?
|-
|-
| Non-Taster || ? || ? || ?
| Non-Taster || ? || ? || ? || ?
|-
|-
| Total || ? || ? || ?
| Column Sum || ? || ? || ? || ?
|}
|}
</center>
</center>


4. Exit Questions:
==Web Exercise. Search for gene information using NCBI online databases==
# Is there a statistically significant association between the ''genotypes'' and the Taster phenotype?
# Point your browser to the [http://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastSearch&BLAST_SPEC=OGP__9606__9558&LINK_LOC=blasthome NCBI Human Genome Resource] page
# Is there a statistically significant association between the ''alleles'' and the Taster phenotype?  
# Copy and paste sequence provided on Blackboard- this is the sequence of the gene associated with the taster phenotype
# Which allele (C or T) is over-represented in the Nontasters?
# Expand the "Algorithm parameters" tab and change "Expect threshold" to 0.00001 (10e-5). Define "expect value" in your owns words after watching the linked Youtube video.
# Is the association 100% (i.e., are there exceptions)?
# Press "BLAST". Copy & Paste the top hit in your final lab report.
# What could be other causes if there are exceptions?
# Briefly describe the function of the gene based on information gathered on the locus page
 
==Lab Report IV==
# Your report should include the following results:
## A printout of contingency test for Locus A, including expected counts, observed counts, chi-square statistic, degree of freedom, and p values
## Same as above for Locus B
## A printout of alignment for the top BLAST hits for the sequence provided
Additional questions to include in your report:
## State what is the ''null hypothesis'' in a chi-square test & what is the ''alternative hypothesis''
## Explain what probability is represented by the p-value.
## What can you conclude when p-value is '''below''' the threshold of significance (e.g., p = 0.05)?
## What would you conclude when p-value is '''above''' the critical value?
## Is there a statistically significant association between one of the alleles tested and the Taster phenotype?  
## Which genotype is over-represented in the Non-Tasters?
## Which allele is over-represented in the Non-Tasters?
## Are there exceptions? What are possible causes for exceptions?
## Define e-value in a BLAST search

Latest revision as of 02:16, 24 July 2020

BIOL 203 Summer 2020 - Bioinformatics Exercises for Lab 11

Test phenotype-genotype association

Introduction: GWAS & 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" e.g. disease) 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. In this case, Χ2 = 26.4, p<0.0005, suggesting a significant association between genotypes and diseases. (By comparing the expected and observed counts, one could conclude that the C/C genotypes are over-represented in disease cases.)

1. Perform an online contingency table analysis using the hypothetical data in Table 1. Click on "other contingency tables" and do a 2-rows and 3-columns test with the data above. Your Χ2 should be 26.4.

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. For example, in the controls, the number of T alleles is: 18 + 68 = 86 , because homozygotes have two alleles and heterozygotes have one.

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 association with 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 with 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 ? ? ? ?

Web Exercise. Search for gene information using NCBI online databases

  1. Point your browser to the NCBI Human Genome Resource page
  2. Copy and paste sequence provided on Blackboard- this is the sequence of the gene associated with the taster phenotype
  3. Expand the "Algorithm parameters" tab and change "Expect threshold" to 0.00001 (10e-5). Define "expect value" in your owns words after watching the linked Youtube video.
  4. Press "BLAST". Copy & Paste the top hit in your final lab report.
  5. Briefly describe the function of the gene based on information gathered on the locus page

Lab Report IV

  1. Your report should include the following results:
    1. A printout of contingency test for Locus A, including expected counts, observed counts, chi-square statistic, degree of freedom, and p values
    2. Same as above for Locus B
    3. A printout of alignment for the top BLAST hits for the sequence provided

Additional questions to include in your report:

    1. State what is the null hypothesis in a chi-square test & what is the alternative hypothesis
    2. Explain what probability is represented by the p-value.
    3. What can you conclude when p-value is below the threshold of significance (e.g., p = 0.05)?
    4. What would you conclude when p-value is above the critical value?
    5. Is there a statistically significant association between one of the alleles tested and the Taster phenotype?
    6. Which genotype is over-represented in the Non-Tasters?
    7. Which allele is over-represented in the Non-Tasters?
    8. Are there exceptions? What are possible causes for exceptions?
    9. Define e-value in a BLAST search
Retrieved from "https://wiki.genometracker.org/index.php?title=QuBi/modules/biol203-geno-pheno-association&oldid=3991"