Kitty Genetics
How Well Does a Punnett Square Predict the Actual Ratios?
In this lab you will make predictions using Punnett Squares and then use data from the cat slides produced as
a class to simulate the genetic crosses. You will then use a statistical test to compare the actual results with
the predicted results.
The trait you are looking at is the gene that codes for two different cat traits. Specifically, white fur (WW, Ww)
or non-white fur (ww), and Agouti hair (AA, Aa) or solid hair (aa).
● W allele – codes for white fur
● w allele – codes for non-white fur
● A allele – codes for agouti hair
● a allele – codes for solid hair
Predicted Ratio
Open a google doc and type, or use paper and draw a Punnett Square to show the cross between two
carriers of non-white fur. The Punnett Square depicted the ratio of theoretically predicted genotypes based
on the rules of probability.
Actual Ratio
Now we will collect data using the cats the whole class found the genetic traits for.
Record the genotypes of your offspring in your lab book. Repeat the coin flip to determine the genotype of a
second offspring.
Class Data
You will tally and analyze data from the class slides. Create a table like this: (Example below)
Example:
Genotype
Observed
Expected
FF
6
=.25(27)=6.75
Ff
16
=0.5(27)=13.5
ff
5
=.25(27)=6.75
27
27
Observed
Expected
TOTAL
White / Non-White
Genotype
TOTAL
Agouti / Non-Agouti
Genotype
Observed
Expected
TOTAL
Qualitative Analysis (answer in complete sentences below):
● In the table, how do you determine the expected number of each genotype?
●
Would you consider the observed and expected results to be the same, close to the same or not close
at all?
●
What do the letters in the genotype represent?
●
Why are there two?
●
When finding the genotype of the cats, why did we write the first letter and then a blank? i.e. B__,
Quantitative Analysis
You will perform a Chi-Square Goodness of Fit test to determine if there is a significant difference between
what was observed and what was expected. Answer the following in complete sentences.
1. What is the null hypothesis for this test?
2. What is the alternative hypothesis for this test?
3. Complete a Chi-Square table to show your work for the Chi-Square test. Include the Chi-Square
formula and at least one example calculation.
4. Determine the DF for the test.
5. Determine the critical Chi-square value using a table of significance.
6. Interpret your statistical test to determine if there is a significant difference between what was observed
and what was expected.