Lecture 6
Gene expression is determined by: genetic code, histone code, nucleosome code,
DNA methylation (= genome + epigenome)
Complexity due to: - folding of large genome
- regulation of expression in many cell types
- memory/imprinting
- fine tuning expression and robustness (stability through
disturbance)
What is the additional value of proteomics compared to
transcriptomics? Also study protein content to find out about: posttranslational
modification of the protein (methylation, glycation, etc); interaction between
proteins; subcellular localization of the protein; movement of the protein (they
can move from one cell to another)
How can you determine the location of proteins in the cell? Use fusion
proteins with tags, like GFP. Also proteomics can help. A cell is never static, it
changes (gene expression, proteome, etc.)
Questions art 1
- Briefly describe the experimental approach. Use MS to determine
which proteins are in the cell. They used the organs (mitochondria, chloroplast,
etc), not the whole plant.
- How many proteins were detected? 13.000 proteins, so not all genes are
detected (there are more genes known than 13.000)
- Which type of proteins are underrepresented in this proteome
analysis? Low abundant genes, transcription factors (because they are
only produced in certain cells), small proteins (bigger protein has more change
to be charged, only charged proteins are detected by MS)
--> we don’t need to know how Mass Spectrometry works.
--> table on page 4: not all spectra are usable, so less peptides than spectra.
More peptides form one protein, so less proteins than peptides.
- How many acetylated peptides were detected? Why is this relevant?
Total amount of peptides 195. You won’t know acetylation by just studying
RNA.
- What is meant with 57 new gene models and describe a few examples
(Fig1)? Examples of new gene models: They found peptides that didn’t map
the predicted ORF, in the DNA they did map, so there was a new gene
discovered. Also, there were proteins found from pseudogenes, that may be
worth to study it. There were regions that were annotated as introns, but there
were peptides found that came from that region, so there is an additional exon
found. You can also find additional exons in the 5’- or 3’-end.
--> 2nd dia on page 4: compare found peptides with genome --> novel hits -->
update the genome. Types of novel hits: proteins from pseudogenes, totally
new (no gene model), novel exon, exon skipping (an intermediate exon was
spliced out), boundary change (new exons at 5’-end). More examples on 1 st dia
on page 5
- What is GO annotation? (fig 2) GO = Gene Ontology, quite complete
description about the protein: molecular function, biological process, cellular
component (see 1st slide page 6) Helps to find out differences between
proteins.
- Why are proteins in the GO category RNA metabolism
overrepresented in the proteome of cultured cells? In cultured cells,
there are cell divisions
, - Why are in a pairwise comparison the proteomes of flowers and
leaves highly correlated (Fig 2B)? There is similarity in protein
content in flowers and leaves, possibly because flowers are mutated leaves,
they have the same origin.
- What is the major conclusion from fig 2C? The proteins of genes which
have more transcripts are detected more often. Lower number of transcripts
--> less detected proteins.
Gene expression is determined by: genetic code, histone code, nucleosome code,
DNA methylation (= genome + epigenome)
Complexity due to: - folding of large genome
- regulation of expression in many cell types
- memory/imprinting
- fine tuning expression and robustness (stability through
disturbance)
What is the additional value of proteomics compared to
transcriptomics? Also study protein content to find out about: posttranslational
modification of the protein (methylation, glycation, etc); interaction between
proteins; subcellular localization of the protein; movement of the protein (they
can move from one cell to another)
How can you determine the location of proteins in the cell? Use fusion
proteins with tags, like GFP. Also proteomics can help. A cell is never static, it
changes (gene expression, proteome, etc.)
Questions art 1
- Briefly describe the experimental approach. Use MS to determine
which proteins are in the cell. They used the organs (mitochondria, chloroplast,
etc), not the whole plant.
- How many proteins were detected? 13.000 proteins, so not all genes are
detected (there are more genes known than 13.000)
- Which type of proteins are underrepresented in this proteome
analysis? Low abundant genes, transcription factors (because they are
only produced in certain cells), small proteins (bigger protein has more change
to be charged, only charged proteins are detected by MS)
--> we don’t need to know how Mass Spectrometry works.
--> table on page 4: not all spectra are usable, so less peptides than spectra.
More peptides form one protein, so less proteins than peptides.
- How many acetylated peptides were detected? Why is this relevant?
Total amount of peptides 195. You won’t know acetylation by just studying
RNA.
- What is meant with 57 new gene models and describe a few examples
(Fig1)? Examples of new gene models: They found peptides that didn’t map
the predicted ORF, in the DNA they did map, so there was a new gene
discovered. Also, there were proteins found from pseudogenes, that may be
worth to study it. There were regions that were annotated as introns, but there
were peptides found that came from that region, so there is an additional exon
found. You can also find additional exons in the 5’- or 3’-end.
--> 2nd dia on page 4: compare found peptides with genome --> novel hits -->
update the genome. Types of novel hits: proteins from pseudogenes, totally
new (no gene model), novel exon, exon skipping (an intermediate exon was
spliced out), boundary change (new exons at 5’-end). More examples on 1 st dia
on page 5
- What is GO annotation? (fig 2) GO = Gene Ontology, quite complete
description about the protein: molecular function, biological process, cellular
component (see 1st slide page 6) Helps to find out differences between
proteins.
- Why are proteins in the GO category RNA metabolism
overrepresented in the proteome of cultured cells? In cultured cells,
there are cell divisions
, - Why are in a pairwise comparison the proteomes of flowers and
leaves highly correlated (Fig 2B)? There is similarity in protein
content in flowers and leaves, possibly because flowers are mutated leaves,
they have the same origin.
- What is the major conclusion from fig 2C? The proteins of genes which
have more transcripts are detected more often. Lower number of transcripts
--> less detected proteins.
