Genetics Challenge Set II --- Fall 2013
N.B. I encourage you to consult outside references as you work on these questions! Please
provide reference information for each article/book/webpage that you find to be helpful.
1. You are charged with sequencing the matK gene from Rosa rubus, a local species for which
several sequences are already available on boldsystems.org
a. Locate relevant sequence data. Note: more than one sequence may be available. If so,
use a unique identifier from the website to indicate which sequence you plan to investigate,
e.g. "GBVJ2345=11".
b. Choose a string of 20 nucleotides from anywhere within the recorded sequence data. Be
sure to indicate the positions of these two nucleotides within the sequence of interest. For
example, you might write, " I am focusing on nucleotides 70 through 89 in of the recorded
sequence data: ATCAGTCAGCTAGCGACAAT."
c. Draw a gel that could have been used to ascertain the sequence of this 20-nucleotide
region using Sanger sequencing with fluorescent nucleotides.
d. In no more than one paragraph, describe, in general, a procedure that could have been
used to produce this gel.
2. New methods for sequencing ancient DNAs are increasing opportunities for biologists to
deextinct species. As we've discussed in class, there are strong arguments both for and against
these efforts.
Imagine that you are a member of a group of scientists charged with bringing back Mammut
americanum, a long-extinct mastodon that once roamed North America.
a. In no more than one paragraph, describe a strategy you might use to approach this
challenge.
b. List three genetic/molecular challenges that you might encounter in this work, and
propose a strategy to address each of them.
c. In no more than one sentence, provide an argument either for or against de-extinction
of M. americanum.
3. In class, we discussed cases of gyandromorphy in a chicken (Gallus gallus domesticus) and in
the northern cardinal (Cardinalis cardinalis). Draw a diagram to show one mechanism
where by a gyandromorphic individual might arise in a species for which the female is the
heterogametic sex.
4. In lab earlier this semester, we considered allele frequencies at a biallelic locus under various
assumptions about the relative fitnesses of homozygous and heterozygous genotypes.
a. Using the R code provided for that lab (and included, again, below), find a set of
relative fitness values that would yield non-zero, unequal genotype frequencies for the two
homozygous genotypes at a locus that illustrates simple dominance. As you will recall, that R is a
freeware program, and so can be downloaded onto your home computer (see http://www.rproject.org). The program is also available on the desktop Macs and PCs in Wilson 214.
b. Please make a plot of the change in the frequency of the recessive allele over 1000
generations, print your plot, and include it with the rest of your challenge set. You are also
welcome to sketch the plot by hand, if you prefer.
c. In no more than one paragraph, describe the strategy you used to select this particular
set of relative fitness values.
d. Next, find a set of relative fitness values, with heterozygote fitness of greater than 0,
that would result in fixation of the dominant allele.
e. In no more than one paragraph, describe the strategy that you used to select this
particular set of fitness values.
5. You are talking with a friend in introductory biology who is struggling with the concept of
genetic drift. Draw (by hand or by computer, as you prefer) and annotate a diagram that could be
helpful as you help to explain this concept.
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#R CODE FOR MODELING INFINITE POPULATION SIZE AND HARDY WEINBERG EQUILIBRIUM
#These lines give the frequencies of the A (given by p) and a (given by q) alleles at the start of
the simulation. The default setting is for the "a" allele to be a new mutation -- that is, it is
present at very low frequency at the start of the simulation.
q=.0001
p=1-q
#These lines give the fitness values for three different genotypes at this locus.
wAA=1
wAa=1
waa=1
qlist<-c()
#This line stores the value of q (the frequency of the a allele) for each generation.
qlisttenpercent<-c(q)
#The function uses current allele frequencies to calculate the frequency of the a allele in the next
generation. The default setting is to collect frequency data for 100 generations.
for(i in 1:1000)
{
q=(p*(1-p)*wAa+(1-p)*(1-p)*waa)/(2*p*(1-p)*wAa+(1-p)*(1-p)*waa+p*p*wAA);
qlist<-c(qlist,q); p<-(1-q)}
plot(qlist, ylab="frequency of a", xlab="generation number")