<html>
<font size=3>This sounds like mapping data to me...mapping phenotypes in
various organisms via shared genetic markers/polymorphisms. The
mapping data would have it's own representation and evidence in your
information system...maybe handled in some similar fashion as the GO,
maybe not. <br>
<br>
The association of the GO term with the gene product would be via a
separate set of experiments that measure function or some biological
process. Inferred from mutant phenotypes (IMP) is one of the
evidences that could be used there.<br>
<br>
I think, then, that the association of the GO term with the gene product
would be in the primary species. So, a rice gene product may be
shown to have an involvement in 'timing of seed set'. The location
of that gene in the other cereal genomes would be mapped using the
techniques below. Then the researcher might decide to transfer the
GO association with the rice gene product to the other cereal gene
product. Then the evidence for the association of the GO term in
the cereal species would perhaps be 'inferred from electronic annotation'
since you have 1) established the GO associations with the primary
species by whatever GO evidence code, 2) established a relationship
between the primary species and the secondary species by some other
experimental evidence, either by mapping phenotypes or sequence
similarity or other, and 3) transferred the GO information from the
primary species to the secondary species based on the identity
established between the two that is independent of the original GO
assignment. <br>
<br>
I remember working through this type of thing when we discuss the
transference of information from mouse to rat via orthology
determinations between the two species. <br>
<br>
Judy<br>
<br>
<br>
At 03:33 PM 11/8/01, Pankaj Jaiswal wrote:<br>
<br>
<blockquote type=cite class=cite cite>Dear GO Friends,<br>
<br>
<br>
In Gramene
(<a href="http://www.gramene.org/" eudora="autourl">www.gramene.org</a>),
we are presently curating rice mutants/phenotypes<br>
that have been characterized using<br>
one or more of the techniques outlined in the list of Evidence
codes. We are<br>
proposing the<br>
introduction of a new line of evidence called, "IAGP: Inferred from
Association<br>
between Genotype<br>
and Phenotype".<br>
<br>
We could have used the GO code, IGI (inferred from genetic interaction).
However<br>
after looking<br>
carefully at the description of IGI, we felt that by using it we might
not<br>
justify the evidence type. The<br>
reason we are proposing this new code of evidence is because many of
the<br>
phenotypes in crop plants<br>
(in general from cereal crops ) are characterized using genetic markers
and<br>
populations or genetic<br>
stocks that are well known to plant geneticists and breeders, and we felt
that<br>
listing them<br>
specifically will help us clarify the nature of evidence used to define
the<br>
relationships between<br>
the phenotypes and the genotypes, as defined by markers on the genetic
and<br>
physical maps.<br>
<br>
This is going to be very important while curating information
related to<br>
functional and comparative<br>
genomics. Entries in the rice Mutant database will use primarily
the GO terms<br>
and Trait terms (TO) for<br>
defining both the morphological and physiological
(Biochemical)<br>
mutants/phenotypes, and the<br>
Evidence code would include the following in addition to the
presently defined<br>
ones:<br>
<br>
<br>
PROPOSED NEW EVIDENCE CODE :<br>
<br>
IAGP (inferred from association between genotype and
phenotype)<br>
<br>
# Based on detection of
polymorphism or segregation of genetic markers<br>
e.g.. isozymes, RFLPs<br>
(Random Fragment Length Polymorphism), RAPDs (Random amplified
polymorphic<br>
DNA), AFLPs<br>
(Amplified Fragment Length Polymorphism), SNPs (Single
Nucleotide<br>
Polymorphisms), Microsatellite markers or SSR (Simple Sequence Repeats),
TD<br>
(Transposon Display).<br>
<br>
# Based on detection of
polymorphism or segregation of physical markers<br>
e.g.. FISH,<br>
centromeric,heterochromatic regions, chromosomal banding
patterns.<br>
<br>
# Based on detection of
polymorphisms in segregating plant material<br>
derived from bi-parental<br>
crosses e.g.. F2 lines, F3 families, Back cross populations, viz.,
BC1, BC2<br>
etc.; Doubled Haploid lines<br>
(DH), Recombinant Inbred Lines (RIL).<br>
<br>
# Based on detection of
polymorphisms in genetic stocks, e.g., Near<br>
Isogenic Lines (NIL),<br>
Introgression Lines (IL), Radiation Hybrids (RH), Cytogenetic
Stocks (CG),<br>
i.e., trisomics, aneuploids,<br>
etc.<br>
<br>
<br>
We look forward to getting your feedback on this proposal.<br>
<br>
Sincerely<br>
<br>
Pankaj<br>
<br>
<br>
**************************************************************<br>
Pankaj Jaiswal,
Ph.D.
<br>
Postdoctoral Associate<br>
Dept. of plant
Breeding
<br>
Cornell
University
<br>
Ithaca, NY-14853, USA <br>
<br>
Tel:+1-607-255-3103 / Fax:+1-607-255-6683<br>
E mail: pj37@cornell.edu<br>
<a href="http://www.gramene.org /" eudora="autourl">http://www.gramene.org
</a>
<a href="http://ars-genome.cornell.edu/rice" eudora="autourl">http://ars-genome.cornell.edu/rice</a><br>
**************************************************************</font></blockquote></html>