Lecture 18 Flashcards
'omics and next generation sequencing (30 cards)
Genome
all genes in an organism
does bigger genome mean more complex
No!
genomics
The study of an organism’s complete set of DNA (genome), including its structure, function, evolution, and mapping.
a cell’s “recipe book”
genome
contains coding and non-coding DNA
the language of cell’s genome
nucleotides
genome size range
viruses : tiny - small
prokaryotes : small
eukaryotes : small - gigantic
dinoflagellates genome
(single celled algae)
1-80 x larger than the human genome
complexity of genome
not directly correlated to size
Prokaryote and Viruses genomes (small)
huge collective metabolic diversity despite small individual genomes
genomes have high coding density (little to no “wasted space”)
eukaryotes genomes (small - huge)
high morphological diversity, but low metabolic diversity
huge euk genomes have low coding density (more DNA, but gene content does not increase proportionally)
DNA sequencing
reading the specific order of genes
PCR
polymerase chain reaction
(“photocopies” genes)
applications of DNA sequencing
enviro : study natural microbiomes
evolutionary : infer evolutionary relationships
applied : seek out biomolecules of interest (antibiotics, drugs, nutrition)
microbiome
community of microorganisms that inhabit a particular environment
NGS
next generation sequencing
first generation in the age of genomics
“sanger sequencing”
labour intensive but highly accurate
“next generation” sequencing technologies
no need for purified molecules - can now sequence directly
highly accurate - used for liquid biopsies
liquid biopsies
lab test that samples bodily fluid
3rd generation sequencing technologies
lower accuracy
immediate results possible
meta- prefix
when working with communities
The two main strategies for DNA sequencing
targeted approaches and untargeted approaches
targeted approaches examples
amplicon sequencing and barcoding
untargeted approach
shotgun genome sequencing
targeted approaches
use PCR to amplify a genetically conserved marker gene (e.g. rRNA)
- read DNA ‘barcodes’
- compare to database to classify
- cheap, reliable, simple but limited info