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PROB ABIL ITY IN GE NET ICS Independent events In meisois, which partner chromosome migrates to a specific pole is a random event. Thus alleles in a heterozygote always segregate to different gametes and genes on different chromosomes should always show independent assortment. Even gene on the same chromosome will show random assortment unless they are "linked". Unless evidence suggests otherwise, it is safe to assume genes are independent. The joint probability of two independent events happening together is the product of the individual probabilities. ie P(AB) = P(A) • P(B) Examples of use: gamete frequencies: given a genotype of Aa, Bb Cc dd, the probability of an (a,b,c,d) egg or sperm is 1/2 •1/2 • 1/2 • 1 = 1/8 phenotypic and genotypic frequencies in progeny: given the legends: De_ normal de/de endosperm lethal, no seed S_ starchy ss sugary D'D dwarf D'D short DD tall Hs_ hairy sheath hs/hs normal If a De/de, Ss, D'D Hs/hs plant is self fertilized, what fraction of the progeny will be a) De/De, Ss, D'D, hs/hs ? Taking one gene at a time in the order listed, the answer is: !/3 • 1/2 • 1/2 • 1/4 (the lethal de/de will not be a seed!) b) Normal endosperm, sugary, tall, normal sheath? 1 • 1/4 • 1/4 • 1/4 If the events are not independent, then the formula changes to P(AB) = P A • (B/A) or P(B) • P(A/B), where A/B the probability of event A given that event B has occurred, etc. These are conditional probabilities A common use of conditional probabilities occur in pedigrees. If two normal parents have a child with a recessive trait, we know that each parent is heterozygous. We also know that an u naffected brother or sister of the affected 'aa' child has a 2/3 chance of being heterozygous. given the fact he or she is normal so can't be ‘aa'. The probability that events A or B occur is P(A) + P(B) - P(AB) If A and B are mutually exclusive the P(AB) = 0 so drops out. Example: In humans the ability to taste PTC is dominant. A man and woman are tasters but each had a nontaster parent. What is the probability their first child will be a taster o r a son? P(taster) = 3/4 and P(son) = 1/2 and the probability of a taster son is 3/4 • 1/2 or 3/8, so the answer is 10/8 - 3/8 = 7/8 Binomial and Multinomial Di stributions Distributions of offspring in families generally deal with binomial or multinomial possible outcomes. The formula for the "general term" of a multinomial (trinomial shown) is: N! P (a )r P (b )s P (c)t r ! s! t ! where N is the total number of offspring, r is the number of one kind, s anther, t another and a is one possible outcome, b and c and the others (perhaps homozygous dominant, heterozygous, and homozygous recessive). N! = N•(N-1)•(N-2) ---•(1) ; so for example 5! = 5•4•3•2•1 = 120 0 By definition, 0! = 1 and (x) also = 1 Example problem: What fraction of families with 6 children will have 3 boys and 3 girls? Answer: 3 3 6!/3! 3! (1/2) (1/2) The second part of the equation shows the probability for one specific birth order that gives the projected outcome (3 boys then 3 girls for example) while the first part of the equation shows the number of birth orders that give the same overall outcome of 3 boys and 3 girls. Going back to the two heterozygous tasters, if they have 5 children, what is the probability that 4 will be tasters and 1 a nontaster? 4 1 5!/4! 1! (3/4) (1/4) If they have 4 children what is the probability they will all be tasters? 4 4!/4! 0! (3/4) (1/4) 0 A question that comes up in many situations is the probability of "at least one". The easiest way to solve this question is to use the formula: P(at least one) = 1-P(0) For the cross Tt by tt, what is the probability that at least 1 of 6 progeny will have the recessive phenotype? P(all dominant) = P(0 recessive) = 6 (1/2) = 1/64 or 0.0156; so P(at least one recessive) = 1-0.0156 = 0.9844 How many progeny should I examine if I want to be at least 99% certain that the dominant parent is heterozygous?