practical 4 Flashcards
(39 cards)
what is the law of segregation?
alleles on homologous chromosomes will segregate so each gamete carries one allele for each trait
what is the law of independent assortment
homologs will orient randomly during metaphase of meiosis I, these homologs will assort independently of one another in gametes
what are the requirements for genes to assort independently
if genes are located on different chromosomes
if the genes are located on the same chromosome but are far enough apart that the recombination frequency is 50%
what is the result of independent assortment?
it leads to different recombinations of maternal and paternal chromosomes depending on the orientation of homologous pairs in metaphase I
what is crossing over
nonsister chromatids in homologous pairs synapse in prophase I and exchange genes, the DNA from two parents is combined into a single chromosome
when can crossing over not occur
when genes are very close together they are less likely to recombine
what happens to assortment if the recombination frequency for genes is 50%?
they will assort independently as if they were located on different chromosomes
what is pure breeding
organisms bred are all homozygous at the traits of interest
what are the “tester” strains? what are they used for?
tester strains are homozygous recessive and are used to determine whether genes can assort independently or if they are linked
what are 100% linked genes? what are partially linked genes?
100% linked genes will not cross over
partially linked genes will have some crossing over
what is the recombinant frequency
the proportion of recombinant progeny can be used to estimate how far apart the two loci are from one another on the chromosome
if two loci are 100% linked (no crossing over) what will the results of a diheterozygote x tester cross be?
you will have equal proportions of the wildtype dominant and mutant
what is the sampling rule? when does it apply for events A and B
it is the probability of any chance of event A, it is equal to the amount of times A occured divided by the total number of events
what is the product rule, when does it apply for events A and B
the product rule describes the probability of events A and B occuring in that defined order. it is found by the product of the probability of Ax prob. B
for the probability of A and B occuring, are the events dependent on eachother?
no they are independent
what is the sum rule, how does it apply for events A or B
probability of either event occurring “A or B” it is found by adding prob. A + prob B.
how is the unordered sequence of events calculated?
this is for multiple events occurring in an undefined order. it is calcualted by the binomial expansion equation
using the binomial expansion equation. If you toss a coin 4 times, what is the probability you will get HTTT
What is n?
what is x
what is p
what is q?
n is the total number of events: 4
x: is the number of one particular event (getting heads) = 1
p is the probability of x=1/2
q is the probability of the other event: 1/2 (getting tails)n
what are the three main causes of a lack of a perfect match in an experiment between the expected and observed results?
1) experimental errors 2) incorrect hypothesis 3) sampling errors
how do sampling errors occur
they are errors made by a non representative sampling
what is the purpose of a chi-square test?
it is used to determine if there is a significant difference in the sampling differences or if the results are due to chance
when analyzing the differences between the expected and observed data, what is the null hypothesis?
there is no statistical difference between the observed data and the expected data
if the calculated X^2 value is less than or equal to the critical X^2 value, what can we do with the null?
we fail to reject the null hypothesis, this means there is no statistically significant difference between the observed and expected results
if the calculated X^2 value is greater than or equal to the critical X^2 value, what can we do with the null hypothesis
we can reject the null hypothesis, this means there is a significant difference between the observed and expected values that cannot simply be attributed to chance/sampling error