L3 Mutation and Mutation Rates Flashcards
Mutation
changes in DNA that have the potential to be propagated through DNA replication e.g. SNPs, indels, CNV
Polymorphism
- frequencies too high to be explained by mutation alone
- every variant site
Neutral theory of Evolution
Most common variation in gene sequences is neutral rather than adaptive
Neutralists arguments
See OneNote
Most molecular variation that is fixed:
- is neutral and therefore evolution is governed by genetic drift
Accepts that deleterious mutations are purged from the mutation, negative selection
Accepts that there is SOME positive selection
BUT of all the variation that gets fixed, MOST of the variation is neutral, has no consequences
Selectionist
Adaptive evolution explains much of the differences between species and much of the variation within species
MOST nucleotide variation is adaptive due to positive selection
MOST variation within population is affected by selection e.g. balancing selection - sickle cell anaemia
Null Hypothesis
the neutral model provides the framework for molecular evolutionary studies often treated as the null hypothesis
Neutral model
See OneNote
s = 0
probability of fixation = 1/(2N)
N = population size
fixation rate = mutation rate (at neutral sites)
Mutations arise by
- damage of molecular structure e.g. radiation, mutagenic compounds
- failure of repair mechanisms to restore DNA to original state
- misincorporation during DNA replication
- TE insertion
- unequal crossing over/segregation problems
How do you calculate the mutation rate?
See OneNote
- mutation accumulation experiment, direct calculation
- estimating mutation rate from divergence data (as neutral model says fixation rate = mutation rate)
How do you calculate the mutation rate - neutral model
See OneNote
- neutral model relates polymorphism to divergence
- as fixation rate = mutation rate, we can calculate mutation rate by looking at the divergence of neutral sites between species
- mutation rate can be estimated from divergence at a neutral locus
d = nd/n d = divergence nd = number of differences n = length of locus
rate = d/2T (as 2 lineages)
nd/n
See OneNote
becomes an underestimate of number of changes when there’s parallel changes or revertants
d = number of mutations observed k = number of mutations that actually occurred
if all bases occur at an equal frequency then d approaches 0.75
Jukes and Cantor Model
Assumes all changes are equally likely BUT there are more transitions than transversions
See FORMULA on OneNote
Kimura’s 2-parameter model
See OneNote diagram
Allows transversions and transitions to happen at different rates
- more sophisticated models could have 12 parameters
Drosophila parameters
See OneNote
- 6 parameters is appropriate
Mammalian Genomes CpG
See OneNote
- deficient in 5’ CpG 3’ di-nucleotides and are enriched for TpG (and their complement CpA)
Because…
- CpG often methylated, 5-methyl cytosine can be deaminated to get thymidine therefore CG => TG occurs often
Methylation effects mutational biases
Flanking sites affect mutation frequency