Bioinformatics I (part 7)

–Variation in copy number (common in repetitive parts of the genome)

–Numbers of extra or missing bases (also common in repetitive regions

• –Base differences in the sequence
• Called Single Nucleotide Polymorphisms—SNP
• Relatively easy to detect and quantify

• Single Nucleotide Polymorphism
• 
• Different individuals in a species have a different base

–Any two genomes differ at (roughly) 1 base pair in 1000

Small populations have less variation than larger ones

Population size needs to be thought of as an average over time

• Many populations undergo bottlenecks
• –Large, rapid reduction in population size
• –Followed by population growth
• –Domestication

Linkage disequilibrium (LD) is a population-based parameter that describes the degree to which an allele of one genetic variant is inherited or correlated with an allele of a nearby genetic variant within a given population

Distribution of alleles follow the expected Hardy-weinburg equation

• Human species is young and small
• –LD blocks are large and strong

Many diseases have a heritable component

• We would like to find genome locations responsible
• –Treatment
• –Susceptibility

Most genetic diseases are poly-genic

• In other words, there are a number of variations that contribute to the disease
• –Your chance of contracting the disease might depend on how many of the disease alleles you inherit and on which particular alleles those are

The diseases have low penetrance: even you inherit the “bad” alleles, the probability of getting the disease might be low

Genome-wide association studies

uses recombinations to locate unknown genes with known ones

–We can locate disease genes by calculating the recombination fraction between the disease phenotype and known markers.

–In humans, this procedure is hampered by high degrees of homozygosity

–Instead, we calculated the likelihood of a gene of interest being at a particular location on the chromosome

Since speciation event

A) GenBank

• Markers can be looked up directly in GenBank then located on the Human Genome using Blast.
• Phylio creates trees

True

Rare to pinpoint 1 gene—most often find a region for further study

–Requires a known pedigree with the disease

–Requires genotyping many individuals in a single family

• –Is also computationally expensive
• and limited:
• –Only works if the disease can be localized in a family
• –Essentially works for mono-allelic diseases

We can take genetic data from a large number of unrelated individuals

Calculate the association between a bunch of SNPs and disease occurrence.

Works based on LD (linkage disequalibrium)

It is very unlikely that the causative genetic difference will be captured by the specific SNPs typed

However, because LD is common in the human genome, SNPs within ~50kb are close enough to show association with the disease

Points are SNPs

>1000 individuals

500K SNPS were typed—these are top hits

The y-axis gives the probability that this level association between the disease gene and SNP by chance

Calculated the probability of no association between a loci and the disease (P-value)

• Looking for cases where this value is small
• –Implies it is very unlikely that a given SNP and the disease would co-occur that often by chance

After Bonferroni correction, two SNPs showed association with AMD

One of the SNPs seems to have resulted from missing genotyping data—unclear how

• Second SNP was in a region with another nearly significant SNP
• -In an intron for Complement factor H
• -Part of the innate immune system
• -Responsible for rapid response to pathogens in the blood
• -Complement factor H can initiate this response
• -Hypothesis: Improper activation of the complement system is involved in damaging retinal cells

True

False

if there is no variation in the gene because it is essential, it will not be able to be located via SNPs in GWAS

A bottleneck

It is treating the alleles/traits as independent