genetic variation and analysis Flashcards
population genetics
investigates genetic variation among individuals within and between groups
genetic basis for evolutionary change
how patterns vary geographically over time
applicable to all kinds of populations
human populations
demographic structure
genetic structure- genes that we possess
constitution- how many alleles are in the population + how the genes are passed on
continuing entity
genomic variation
mutations are pimary source- dna sequence/genes/repeat size/chromosome numbers
genetic variability is the raw material upon which natural selection operates
can occur at all levels- from micro- change in one letter of dna sequence
locus- location of dna sequence/ gene in genome
allele- different forms of same gene or dna sequence
specific loci
ABO locus- A, B, O alleles- has 4 phenotypes and 6 genotypes
A,B codominant, O is recessive
beta hb locus- S,C,C
SNP locus- A + G or C+T - or any combination
repeat loci-2-2 or 3-4 repeats- alu, II,ID,DD
insertion deletion
genetic constitutions
a pool of genes/alleles at any one time
can be specified in the form of allele frequencies
allows comparison- uni dimensional (one population), multidimensional (different population groups/ethnicities)
admixture- when 2 populations mix, offspring will have genetic makeup of mixture of migrating and receiving populations
genetic structure
the way alleles are distributed and combined with populations
human populations are heterogenerous
barriers to breeding/mating- cultural, religion or social
subdivisions affect distribution of genes within populations, lead to consequences –> divergence, fixation of genes at a locus, increased homozygosity
maintenance of genetic variation
errors in dna replicationa are not always repaired by the mechanisms - leads to mutations
some alleles may not be independently assorted
haploid gametes- crossing over (variation)
allele frequency calcs
SNPs, alu, STRs
eg 2 alleles I and D
homozygotes and heterozygotes
- I allele = (2 Homozygotes) + Heterozygotes/ 2*N
*1st allele = p, 2nd allele= q
if there are 2 alleles then p+q=1
any numbers of alleles, formula should work and still add up to 1)
polymorphisms will usually have 2 polymorphisms- insertion and deletion allele
SE of allele frequency
allows evaluation of range and calculation of CI
SE and SD are the same for allele frequencies
√p x(1-p) / 2xN
p= allele of interest
N= no. of individuals in study
small samples have larger SE
for 2 allele systems (alu/snps)- SE same for both alleles
STRs- multialleic systems- each allele has separate SE
SE low is good
heterozygosity
how many heterozygotes are in a population
observed heterozygosisy- frequency of the heterozygotes - h=nh/N
Where nh is the number of heterozygote individuals and N is the total number of individuals studied/analysed
expected heterozygosity= H=1-sum of p^2
p= allele freqency,
1- exp homozygosity= expected heterozygosity
HWE
in a large random mating population, allele and genotype frequencies do not change from 1 generation to next
assumptions
- random mating
- infinite population size
- no mutation or selection
- no migration
cant be used for humans
formula- (p+q)2 = p2+2pq+q2
how and why do we test hwe
tested within the population
null hyp= there is no difference between observed and expected genotype frequencies
population maintains hwe or population does not show departure/deviation from hwe
- calculate allele frequencies
- work out expected genotype frequencies
- work out expected genotype numbers
- use chi2 to test null hypothesis
HWE explained
HWE is calculated for each locus and each population
if not maintained, assumptions causing changes to allele frequencies need evaluation
could be due to selection, gene flow + migration, inbreeding, genetic drift and founder effect, mutation
genetic differences between populations
multiple usages (group comparisons/case control disease analyses)
categorical data
simple solution- compare genotype and allele frequencies using descriptive methods
statistical comparisons
using rxc contigency chi square methods (multidimensional chi square)
organise data into columns + rows, work out totals
work out expected numbers from observed data and work out chi2 for whole table
- expected number = (row totoal * column total)/grand total
- work out expected values for each cell – work it out individually
- degrees of Freedom = (Number of Columns -1) * (No of Rows -1)