Unit 3 Flashcards
Chain termination (Sanger) method
a. Introduce florescent terminator bases to end the sequence on a specific base
b. Different sized DNA fragments are made, ending with the color representing the base it ended with.
Problems with the Chain termination (Sanger) method
Requires a sequence-specific primer, poor sequence near the primer, only good form 100-1000 base pairs of sequence
De novo sequencing
For only completely unknown sequences where you can’t generate a primer.
Chromosome/Primer Walking
Use previously generated sequence to design a primer for the next piece
a. Takes time – you can;t start sequencing the next piece until you’ve finished the first
b. You have to start from a known sequence (for the first primer)
Shotgun sequencing
Good for longer stretches.
- Break the genome into smaller, random pieces
- Clone those pieces into plasmids
- Sequence the pieces
- Use computers to identify overlapping regions and put the sequences together
Shotgun sequencing problems
Repeated regions make the assembly of the fragments difficult
How does knowing genetic sequences help you?
- Genetic diseases
- Genetic susceptibilities
- Reactions to certain medications
What are some concerns about using genetic information in disease treatment?
a. Tailor-made medicines might be more expensive
b. Not everyone might have access to new treatments
c. Keeping genetic information private
d. Possible discrimination at work and from health insurance companies
e. Need for more information about this type of medicine
Two main types of Research
A. Application of Data to Biology (NHGRI: National Human Genome Research Institute)
B. Bioinformatics methods (NHGRI: Genome Tech Branch)
Epigenitics
Heritable changes in gene activity that are not caused by the DNA sequence
Sequence mining: How do variations in human DNA lead to differences in our phenotypes?
Humans differ by ~1/1000 base pairs, most sequence variations are in non-coding regions
Sequence mining: How do we assess significant differences?
- Multifactor Dimensionality Reduction – looks for patterns in a set of data, cross-validate by comparing with other data sets. (Ex: Study of Susceptibility to Pulmonary Tuberculosis)
- P value analysis determines if a correlation is significant (0-1, small p value <0.05 (marginal) and large >0.05 (random)
SNP
Regions in the genome where single-base mutations are common
- SNPs can be in coding regions of the DNA but most are not
- most SNPs have only 2 alleles
- SNPs that change the amino acids of a protein are called non synonymous
- SNPs that do not affect the protein sequence are synonymous
How can I use SNPs to more easily compare people’s genomes?
a. Make a chip containing the DNAs with the SNPs
b. Hybridize with DNA from the person of interest
c. If the patient has the same allele as the chip, there will be a strong hybridization
d. Allows you to only look at regions that will have a difference in the sequence
e. You can see the COMBINATION of SNPs that are associated with the individual.
The HapMap
A catalog of the most common genetic variants in humans