Topic 1 - General Approaches Flashcards
what could be molecules of interest in molecular bio?
DNA, RNA, proteins, metabolites
what could “gene expression” mean?
- transcription
- transcript processing
- translation
- protein processing
- protein modification
- protein localization, interactions, modifications
targeted vs untargeted
target studies:
- examine one or a few specific molecules
untargeted studies
- try to examine all molecules of one type (global changes in gene changes, transcripts, or proteins)
- often called PROFILING because trying to document entire collection
example hypotheses for targeted vs untargeted experiments
targeted: “gene x transcript abundance will decrease in the mutant”
untargeted: maybe more vague/weak
“different transcripts will vary in abundance between wt and mutant”
“we expect to see more genes associated with __ function in x env compared to y env”
genomics, transcriptomics, proteomics, metabolomics meaning
genomics - studying all DNA of an organism
transcriptomics - studying all transcripts of an organism
proteomics - studying all proteins within an organism
metabolomics - studying all metabolites present within an organism
what does “meta” prefix and “omics” suffix mean together?
same as -omics words but:
- it’s total DNA/transcript/proteins in a sample/environment, NOT just one organism!!!
untargeted experiments often lead to __________
identification of target molecules in later experiments
what source of biological variation can contribute to “noise” in measuring molecular changes? (for genes, transcripts, proteins)
genes
- DNA modifications can vary between tissues, etc.
- genotypes differ between individuals
transcripts and proteins
- so many factors!!! e.g., cell type, time of day, diet, genotype, age, etc. etc.
how to minimize biological variation for your data (so it reflects only factor of interest)?
- for euk: use a consistent, homozygous WT background line for exp -> only mutation of interest should affect resutls
- keep uninterested variables consistent
how can we be more sure of measurement validity? types of this?
REPLICATES!
- repeat experiments multiple times
- technical replicate
- biological replicate
technical replicate vs biological replicate?
technical - repeating same system (sample) multiple times, looking for variation in technique
biological - testing different systems (similar conditions), NOT same sample!
ex. You work at a wastewater treatment plant and want to know how many E. coli cells there are per L of water (you use qPCR to achieve this). Which below is a biological replicate?
a) You take three separate 1 L bottles of water and conduct the measurement on each.
b) From a single sample of water, you repeat the measurement three times.
a) because it is with different samples
importance of controls
- help evaluate whether an exp’s output is valid/meaningful
- prevents hidden factors that could go undetected
what are controls?
samples done at same time as experimental samples to help identify errors in judgement
- positive and negative controls
how to design controls?
anticipate what your test will show, and think of how positive and negative results could occur or be misinterpreted!
- design a sample that would test for this error
- know how biological and technical variation can impact your data
- know method well (to know possible errors)
model organisms! what are they, main goal for using them?
model organism - non-human species that are commonly used to study biological traits, with the goal of applying discoveries made in model organisms to other organisms
why do we usually not want to use euks (and use model organisms instead)?
- genome size highly variable
- most of euks’ genome = non-coding
- challenging to include in ex
note: Organisms size/type/complexity = poor predictor of genome size
traits of model organisms (~6)
- small genome size
- low amt of repetitive DNA
- usu. diploid
- short life cycle
- small, cheap to maintain
- transformable
other benefits of model organisms! (~6)
(other than model organism traits)
- focus resources on a few, rather than many, organisms
- collaboration! share data, resources, protocols
- research moves faster (alr familiar with model organism)
- validate results by replication by others
- aids large scale exp that benefit whole community
- develop integrate datasets that aid mathematical modeling
what are some widely used euk model organisms? (just general, don’t memorize too well)
yeast, worm, fly, fish, plant, mouse, frog
(good variety! :o)
drawbacks of model organisms
- differences between model organisms and actual systems of interest
- used in lab env with controlled conditions that cannot perfectly mimic a natural condition
– exacerbated by gen upon gen grown in lab
pyrimidines and purines?
purines = AG
pyrimidines = CUT
where do ssDNA and dsRNA exist in nature?
viruses!
T/F introns are in mRNA?
F - only exons (ORF)
transcription in euk vs prok
prok: transcription and translation happen at the same time
euks: cant do that - transcription (nucleus) & translation (cytoplasm)
group sense/antisense, coding/non-coding, and template/non-template
antisense = non-coding = template
- transcribed to make pre-mRNA, complementary to pre-mRNA
sense = coding = non-template
- same seq as pre-mRNA, not transcribed
insert size limits for plasmids, phages, cosmids, and BAC/YAC/MAC
plasmids - <= 10kb
phage - 5-20 kb
cosmid - 35-45 kb
BAC/YAC/MAC - a lot more
