11.4 Hardy-Wineberg Equilibrium

Equation - used to predict genotype frequencies in a population Predicted genotype frequencies are compared with Actual frequencies – used for traits in simple dominant-recessive systems "The Hardy-Weinberg equation is based on Mendelian genetics. It is derived from a simple Punnett square in which p is the frequency of the dominant allele and q is the frequency of the recessive allele." p 2 + 2pq + q 2 = Hardy-Weinberg Equilibrium

q 2 = # homozygous recessive/entire population p 2 = # homozygous dominant/entire population Take the square roots to find p & q If the predicted genotypes match the actual genotype frequencies than population is in equilibrium If it is not in equilibrium – it is changing - evolving 11.4 Hardy-Weinberg Equilibrium

Chi-Square Test Determines whether the experimental data fits the results expected For example – 290 purple flowers – 110 white flowers – Close to a 3 : 1 ratio – How do you know for sure?

Goodness of Fit The chi-square test is a “goodness of fit” test – Answers the question of how well do experimental data fit expectations Ex: self-pollination of a heterozygote – The null hypothesis is that the offspring will appear in a ratio of 3 dominant to 1 recessive.

Formula First determine the number of each phenotype that have been observed and how many would be expected “Χ” - Greek letter chi “∑” - sigma – Sum the following terms for all phenotypes “obs” is the number of individuals of the given phenotype observed “exp” is the number of that phenotype expected from the null hypothesis Must use the number of individuals and NOT proportions, ratios, or frequencies

Example F2 offspring – 290 purple and 110 white flowers – Total of 400 offspring We expect a 3 : 1 ratio. To calculate the expected numbers – Multiply the total offspring by the expected proportions – Expected Purple = 400 * 3/4 = 300 purple – Expected White = 400 * 1/4 = 100 white

Purple obs = 290 and exp = 300 White obs = 110 and exp = 100 Plug into the formula:  2 = ( ) 2 / ( ) 2 / 100 = (-10) 2 / (10) 2 / 100 = 100 / / 100 = = = chi-square value

Reasonable What is a “reasonable” result is subjective and arbitrary For most work a result is said to not differ significantly from expectations if it could happen at least 1 time in 20 That is, if the difference between the observed results and the expected results is small enough that it would be seen at least 1 time in 20 over thousands of experiments “1 time in 20” can be written as a probability value p = 1/20 = 0.05

Degrees of Freedom The number of independent random variables involved Simply the number of classes of offspring minus 1 Example: – 2 classes of offspring: purple and white – Degrees of freedom (d.f.) = 2 -1 = 1.

Critical Chi-Square Critical values for chi-square are found on tables, sorted by degrees of freedom and probability levels If your calculated chi-square value is greater than the critical value from the table, you “reject the null hypothesis” If your chi-square value is less than the critical value, you “fail to reject” the null hypothesis – Accept that your genetic theory about the expected ratio is correct

Chi-Square Table

Using the Table Example of 290 purple to 110 white Chi-square value of 1.333, with 1 degree of freedom 1 d.f. is the first row, and p = 0.05 is the sixth column Critical chi-square value = Calculated chi-square = – less than the critical value, – “fail to reject” the null hypothesis – An observed ratio of 290 purple to 110 white is a good fit to a 3 to 1 ratio

Another Example: from Mendel phenotypeobservedexpected proportion expected number round yellow 3159/ round green 1013/ wrinkled yellow 1083/ wrinkled green 321/ total5561

Finding the Expected Numbers Add up the observed offspring to get the total number of offspring Example: = 556 Multiply total offspring by the expected proportion --expected round yellow = 9/16 * 556 = expected round green = 3/16 * 556 = expected wrinkled yellow = 3/16 * 556 = expected wrinkled green = 1/16 * 556 = 34.75

Calculating the Chi-Square Value X 2 = ( )2 / ( )2 / ( )2 / ( )2 / = =

D.F. and Critical Value Degrees of freedom = 3 d.f. 3 d.f. and p = 0.05 – critical chi-square value = Observed chi-square (0.470) is less than the critical value – Fail to reject the null hypothesis – Accept Mendel’s conclusion that the observed results for a 9/16 : 3/16 : 3/16 : 1/16 ratio

Chi-Square Table

Mendel’s Yellow vs. Green Results