1. Sequence based searches:
Genome
sequence
find
coding genes
Predicted
protein
coding genes
translation
RNA finding
(tRNAscan,
RFAM, homology
searches)
Collect any
literature for
the gene product
Sequence based searches:
Blast-type pairwise alignments;
HMM searches (Pfam, TIGRFAM, etc.);
InterPro; TMHMM; SignalP; TargetP;
COGs; Paralogous families; and more…..
predicted
RNA genes
Evaluate evidence
presented
in paper
Evaluation of evidence
pairwise alignments:
Visually inspect alignments, look for conserved
active sites, look for (generally) at least 35%
identity across the full lengths of both proteins.
If matches are not full length, look to see if there
are recognized functional domains in the area
where the match occurs.
Decide how much information can be transferred
from the match protein to the query. In order to
assert that the query has the exact same function
as the match protein, the match protein must
be experimentally characterized. If any doubt
about specificity of the function exists, back up to
a more general level of annotation.
family/domain based evidence:
Review search results (InterPro, HMM). Look to
see specificity of the family in question. Can a
specific function be assigned based on
membership in the family?, or is the family broad
in functional scope? If so, can a general function
such as “kinase” or “oxidoreductase” be given.
If not, can a name be given based on family
membership even if function is unknown?
motif predictors:
Look to see what the presence of membrane
spans, signal peptides, etc. is telling you about
the protein in light of other information coming
from other search results - is it all consistent,
does it add up to a particular cellular location
or function? If all you have is a motif, perhaps
you can still make some annotations (eg. “integral
membrane protein” based on for example
multiple TMHMM regions.
Get Candidate GO terms
-from match proteins
-from matching families/
domains/motifs
-from EC number mapping,
InterPro2GO, other mappings, etc.
Search for GO terms if no
candidates present themselves
-GO search/browse tool AmiGO
-many other tools (eg. Manatee,
QuickGO, etc.)
Evaluate GO terms:
Check that the quality of evidence
supports candidate GO terms at a
particular level of specificity. Read the
literature relevant to the experimental
characterization of any match proteins
used as evidence. Check that any GO
terms that may be assigned to the match
protein are correct. Check GO trees and
definitions to make sure the term makes
sense for your organism.
Generally it is safer to make function GO
annotations than process ones based on
sequence similarity t single proteins.
See IGC chart for more on process
annotatoins based on sequence.