Too many matches

1
Too many matches
2
Too many matches
What are the potential TF sites involved in
regulation of my gene of interest ?
Lets run MatInspector over the promoter region
of my gene
3
Too many matches
Where do I get my input promoter DNA sequence
from?
Lets extract from NCBI. 3kb upstream of TSS to
be sure to have the promoter
4
Too many matches
Which of those matches are relevant? How do I get
rid of all those false positives ?
5
TF binding sites
There is not a single false positive match
MatInspector gives you all physical TF binding
sites
A physical TFBS is found every 10 to 15 bps
throughout the genome
A single isolated TF binding site carries no
function
TFs work through complexes which are represented
on sequence level through sets of TF binding
sites in certain distance relationship and
orientation -gtpromoter frameworks
6
TF binding sites
Okay, what is now a physical TF binding site
? What is a functional TF binding site?
7
False positives?
8
Physical vs functional TFBS
...but binding proteins are present only in 2
cell types! -gt no functional binding site
in the other 3 cell types!
One binding site, five cell types...
...biological function may require additional
binding sites!
Even when binding proteins are present...
9
Transcriptional modules
Transcriptional modules integrate signals via the
interacting TFs
10
Why uses nature modules?
No common organization?
Common modules!
11
Transcriptional modules
Synergistic
Antagonistic
Synergistic
Composite elements
Short range module distance 50 bp
Looping module distance up to 300bp
Short range module distance 50 bp
or
or
Binding Affinity
High / Low Is possible
High / Low Is possible
High / Low Is possible
High / High only
12
Transcriptional modules
Induced by 2 pathways !
13
Transcriptional modules
14
Transcriptional modules
Gene A, transcript n
Protein complex
15
Transcriptional modules
16
Transcriptional modules
Experimentally verified evidence that TFBSs from
modules, which are crucial for regulation in one
biological context (cell type), are totally
irrelevant in another !
Fessele, S., Maier, H., Zischek, C., Nelson,
P.J., Werner, T. (2002) "Regulatory context is a
crucial part of gene function" Trends in
Genetics 18, 60-63 (MEDLINE 1181130)
17
Transcriptional modules
18
Promoter sequences
Very interesting but how does all this help me
with my original question ? The question still
is What are the potential TF sites involved in
regulation of my gene of interest ?
19
Promoter sequences
Where do I get my input promoter DNA sequence
from?
Lets extract from NCBI. 3kb upstream of TSS to
be sure to have the promoter
20
Promoter sequences
3 kb is too large for meaningful analysis
even going 10kb upstream of TSS is no guarantee
to have the relevant promoter sequence
multiple promoters are the rule, not an exeption
the non-coding first exon is always part of the
promoter
Huh? What does this mean ? Where do I get this
damn promoter now?
21
Alternative transcripts/promoters
22
Alternative transcripts/promoters
23
Alternative transcripts/promoters
Data from ElDorado
24
Alternative transcripts/promoters
Alternative promoter usage is often tied to
regulation of tissue specific gene expression
Alternative promoter usage is of very high
biological relevance. There are several examples
where aberrant regulation of the identical
primary transcript leads to severe biological
effects
25
Alternative transcripts/promoters
The gene product is absolutely identical. The
only difference is in the alternative promoter
usage. On transcript level this can be seen only
in the non-coding first exon.
26
Promoter Analysis
1. Identification of the promoter sequence
2. Prediction of physical transcription
factor binding sites
3. Functional context
4. Context dependent functional
transcription factor binding sites
27
ElDorado promoter sequence retrieval
Yes! I know all of this! I just wanted to know
from where I can get my promoter sequence(s)
easily!
If you dont have one already, sign up for a free
evaluation account. first... ... then login here!
www.genomatix.de
28
ElDorado promoter sequence retrieval
29
ElDorado promoter sequence retrieval
30
ElDorado promoter sequence retrieval
IMPORTANT! Affymetrix probe-set-ID input Our
annotation is NOT based on the Affymetrix NetAffx
assignment!It is rather based on genomic mapping
of each single probe. A transcript will be
retrieved if at least one probe of the set
(usually 11 probes) matches. For mixed probe
sets (cross-hybridisation), all relevant
transcripts will be retrieved, which might lead
to a result with transcripts from different loci.
Input in this section delivers results based on
gene name or keyword search. Over a million of
names, synonyms and gene IDs help to find what
you want - fast!
HMGCS1 ( for example)
Input in this section delivers results based on
ultra fast sequence mapping. Copy and paste raw
sequence data here (min.15 nucleotides) or enter
an accession number. In contrast to the entry of
an accession number above, here the sequence is
actually retrived from data base and mapped onto
the genome(s). NOTE many EST based accession
numbers have poor sequence homology and deliver
no result.
31
ElDorado promoter sequence retrieval
32
ElDorado promoter sequence retrieval
This gives you an interactive graphical
representation of the genomic context of your
gene
33
ElDorado promoter sequence retrieval
mapping positions of Affymetrix single probes !
switch display of components on and off
scale/slide the retrieved genomic "window"
select regions of the graphics and safe them into
a file
Orange indicates your input. In this case a gene
name. It is very informative when your query is
based on sequence data. Then you see the mapping
positions.
Everything is clickable just play around !
Here you can scale the view
34
ElDorado promoter sequence retrieval
Clicking on this trancriptional start region
(TSR)...
...displays this hyperlink to ...
Now we have zoomed into the promoter region
35
ElDorado promoter sequence retrieval
...this profile of the different experimentally
verified TSS (CAGE tags) in the different tissue
types.
36
ElDorado promoter sequence retrieval
This is a table-like representation of all
annotated elements. It is especially useful for
quick and easy retrieval of the dna sequence(s)
of interest.
37
ElDorado promoter sequence retrieval
Tick/un-tick the boxes of what you would like to
see, and then...
38
ElDorado promoter sequence retrieval
This for instance...
...tells you that this SNP deletes three
potential TF binding sites and creates a new one.
A potential regulatory active SNP...
39
ElDorado promoter sequence retrieval
from here you can directly run a MatInspector
analysis for this promoter...
...again,play around with the interactive
graphics... Click the symbols and jump right
into MatBase, the TF knowledge base..
40
ElDorado promoter sequence retrieval
now, finally the first way to extract a promoter
sequence ... ...and/or any other element
displayed in the list below.
Choose your desired length. Unless you have good
reason to change the length of the proximal
promoter, leave the defaults!
41
ElDorado promoter sequence retrieval
This shows you all annotated alternative
transcripts plus all Affymetrix probe set single
probe mappings plus
another way to extract your promoter
sequence(s)
42
ElDorado promoter sequence retrieval
You know this already... Three different known
transcripts for this locus...
... and four distinct promoters ! How this
comes, Ill tell you in a minute
43
ElDorado promoter sequence retrieval
Tick the promoter of your interest...
Or submit the promoter directly to
MatInspector for graphical analysis. It works on
a single sequence, too.
Or submit sequences directly to one of those
tasks. But they make sense only with multiple
sequences. More on that later!
...choose format...
...and extract the sequence.
44
ElDorado promoter sequence retrieval
But why do I have four promoters here? And two
even dont have a transcript assigned, as it is
written here! And whats all that CompGen thing
about?
The multiple promoter thing I showed you before.
Remember the GCK example, liver and
pancreas? Now to the CompGen promoters. They are
derived by a proprietary comparative genomics
approach.
45
ElDorado promoter sequence retrieval
46
ElDorado promoter sequence retrieval
The tick-boxes you know already... We need them
for later promoter retrieval.
For our example we have an homologous locus
assigned in chimp, macaca, human, rat, dog, cow,
opossum, chicken, and zebrafish.
Note the Promoter Set number !
Exhaustive cross-mapping of all transcripts to
all genomes of all organisms in ElDorado
generates our homology groups.
47
ElDorado promoter sequence retrieval
Get a feeling for the degree of phylogenetic
conservation of the resp. promoter. See how
much experimental evidence supports this promoter
48
ElDorado promoter sequence retrieval
A Promoter Set represents phylogenetically
conserved promoters
You should be familiar with this view,
now. Here the orange indicates a promoter
belonging to a promoter set.
With these tick-boxes you can switch on and off
the display of the different Promoter Sets
49
ElDorado promoter sequence retrieval
Dont waste my time here! How do I get my
promoter sequence now? And which one of all
those promoters should I take ?
Well, which one? If you do not have any other
information (experimental or from literature), I
would recommend that you consider all available
alternative promoters for further analysis
50
ElDorado promoter sequence retrieval
Dont waste my time here! How do I get my
promoter sequence now? And which one of all
those promoters should I take ?
Two easy ways of promoter sequence retrieval by
two mouse clicks I showed you some minutes
ago. There are more...
oh... you cannot access these options?
51
ElDorado promoter sequence retrieval
Otherwise it is slightly more cumbersome...
... and use that for sequence retrieval from your
second to Genomatix favorite system, e.g. NCBI
Use one of the options I showed you before and
get Contig and positional information...
Hint If you are interested in the TF results
rather than the sequence, use the search for
common transcription factor binding sites option
as shown before.
52
From physical to functional TF site
Quite interesting But I am not a single step
closer to the answer of my real question What
are the potential TF sites involved in regulation
of my gene of interest ?
Well, I think you are. Essential first step is to
analyze the right sequence in a length that
allows for meaningful results. Now that you have
the real promoter sequence(s), lets see how to
go on from here...
53
From physical to functional TF site
Then we have to look for additional evidence that
some of the physical TF sites might be functional
ones. Best would be to go for a ChromatinIP
experiment. However, for such you would need some
hints for which TF to make or buy antibodies.
Further computer analysis is required
anyhow! There are three different roads to go...
The ideal situation for determining potential
functional binding sites would be to have a set
of genes apparently being co-regulated in the
given cellular and experimental context, f.i.
from a microarray experiment. A comparative
promoter analysis with FrameWorker would very
likely give you a pattern of involved TFs, as
shown in numerous publications (see our web site
at About us -gt Publications).
But I have only a single gene. And thats the
one I am interested in!
54
From physical to functional TF site
We talked about promoter modules before. Search
your sequence for promoter modules with
ModelInspector. Our Promoter Module Library
contains over 550 promoter modules, each of them
experimentally verified to carry transcriptional
regulatory activity. A module match increases
probability that an involved TF site is
functional.
Okay, how do I do this? Lets go !
Look for phylogenetically conserved patterns of
TF sites in a comparative genomics promoter set
with FrameWorker. TFs being part of such
phylogenetically conserved frameworks carry
higher probability for being functional.
Do extensive literature data mining with
BiblioSpherePE for known TF correlations, pathway
analysis and gene set creation for comparative
promoter analysis. TFs showing biological
activity in another experimental context are
functional (at least in that context).
55
ElDorado promoter sequence retrieval
Lets start with an analysis for promoter
modules...
56
Search for promoter modules
If you are licensed, you can have a quick look
at the promoter module library. Each module is
experimentally verified to carry regulatory
activity.
57
Search for promoter modules
Choose a sequence file from your directory
Or copy paste a raw sequence here. or you know
the rest !
Dont click anything below, unless you want to
scan an entire data base !
58
Search for promoter modules
59
Search for promoter modules
60
Search for promoter modules
61
Search for promoter modules
Now we have focused down to 21 very interesting
positions in this promoter with modules that are
composed of a total of 11 different transcription
factor binding sites. Our arbitrary chosen
example HMGCS1 belongs to the cholesterol
biosynthesis pathway. Some of the found promoter
modules do have proven function in sterol
regulation!
Wow! Thats impressive! But that example is a
mock-up, isnt it?
Not really. It is a nice example to show this
approach. Very frequently one finds functionally
related modules. However, there is no
guarantee It adds just another line of evidence.
62
Phylogenetically conserved frameworks
Thats right. For this approach you first need a
set of phylogenetically conserved promoters.
Remember several slides before ?
Okay, how does the other thing help? How did you
call it, phylogenetically conserved frameworks?
Not really. It is a nice example to show this
approach. Very frequently one finds functionally
related modules. However, there is no
guarantee It adds just another line of evidence.
63
ElDorado promoter sequence retrieval
and tick the promoters of one set.
In this example I choose Promoter Set 3 for
human, rat, dog and cow.
...scroll to the top of the page...
Inspect and choose your Promoter Set...
64
Phylogenetically conserved frameworks
...scroll down...
Great ! That is what I really want to know
Which TF sites do they have in common?
From here you can have a look at TF binding sites
which are common to the input promoters
65
Phylogenetically conserved frameworks
Great ! That is what I really want to know
Which TF sites do they have in common?
This is not more than a tiny hint! I can show you
many cases where totally unrelated exons do have
more TF sites in common than closely co-regulated
promoters. What you are really looking for is a
conserved pattern of TF sites. And we are going
to do so. But first lets have a look on the
nucleotide sequence level...
Be careful !!
66
Phylogenetically conserved frameworks
DiAlign TF gives an overlay of a true multiple
sequence alignment (not pairwise) and common TF
sites. Check DiAlign for other sequences
(including amino acids)! It is extremely fast
and especially powerful for finding short
homologies in largely unrelated sequences.
67
Phylogenetically conserved frameworks
The parameters should be self explanatory.
You can always click for help
68
Phylogenetically conserved frameworks
Here an output example.
69
Phylogenetically conserved frameworks
Why did you do this? What does it tell me?
It is pretty informative to get a feeling for the
degree of homology, which parts are more
conserved than others and which TF binding sites
reside in the homologous parts. Then, it is of
interest to see where the evolutionary pressure
was rather on functional conservation (TFBS) than
on sequence conservation.
70
Phylogenetically conserved frameworks
Why did you do this? What does it tell me?
Then, if you do a framework analysis on two
highly homologous sequences we run into a
combinatorial explosion. FrameWorker checks for
it and might give you a warning. However, in this
case everything is fine...
71
Phylogenetically conserved frameworks
Why did you do this? What does it tell me?
If you do a framework analysis on two highly
homologous sequences we run into a combinatorial
explosion. FrameWorker checks for it and might
give you a warning. However, in this case
everything is fine...
Now, we finally go to the FrameWorker analysis!
72
Phylogenetically conserved frameworks
This filter is a positive filter! Only TFs known
to be associated with a tissue are listed here. A
TF not listed in a certain tissue does NOT mean
that it is not expressed there! It just has not
been reported, yet.
Here you can choose the matrix library
Here you can select for TFs only, known to be
associated with certain tissues.
73
Phylogenetically conserved frameworks
More options gives you...
...well, more options !
Dont change those parameters unless you know
exactly what you are doing !
74
Phylogenetically conserved frameworks
If you know that a certain TF is involved in the
regulation of your gene, make it a mandatory
element and search only for frameworks containing
such. Mandatory elements are most helpful in
focusing your analysis. If you dont know one a
priory, Ill show you later in BiblioSpherePE how
to get to those. Toggle multiple choices by
holding the "Ctrl" key when clicking!
This decides the number of input sequences which
have to show a common pattern of TF sites
One word on this parameter. It decides the
minimum/maximum number of TF sites being allowed
in one framework. In this case I increased the
default value from 6 up to 10 since we want to
identify the largest conserved pattern in this
phylogenetic promoter set. We might lower this
later.
This sets the distance constraints between two
adjacent TF sites. More important than the
absolute distance is the distance variance.
Always start at default values (unless you know
already better) and relax gradually if nothing
meaningful is found.
And always think about the HELP pages !
This option gives you an idea of the specificity
of the found frameworks. It checks how often a
framework would be found in a background of 5.000
random human promoter sequences.
Use it with care! It slows down FrameWorker
considerably!
75
Phylogenetically conserved frameworks
The longest frameworks contain 8 TF sites. There
are 4 different frameworks. If you click the
link, you jump direct to the graphical
representation
All four promoters have 18 TF sites in common.
This number might differ from the search for
common TF job earlier, since now we take strand
specificity into account.
76
Phylogenetically conserved frameworks
Here you see the detailed description of the
framework. It is perfectly conserved throughout
the species
You can save this framework in your personal
directory for subsequent sequence or database
scans
Here you have a graphical representation. You
already know how this works...
Scroll down to the bottom of the page...
77
Phylogenetically conserved frameworks
At the bottom of the output you find this list.
Now we not only have identified the TFs but also
the exact positions which are worth a closer
look. You can scan with your saved frameworks all
of our promoter databases for promoters with
similar organization.
Why should I do this? Would this give me
additional information ?
78
Phylogenetically conserved frameworks
In this example with an 8 element framework and
almost no distance variation between the TF
sites, you will find exactly 1 match in over
56.000 human promoters the input gene. How to
use this approach with less selective frameworks
for identification of similarly organized
promoters? I'll show you later
79
Knowledge based analysis
Yes. The third is knowledge driven and bases on a
combination of literature data mining, sequence
analysis and pathway/network analysis. For this
you need first to download and install the Java
client of BiblioSpherePE
Fine! I think I have seen now two strategies.
You mentioned three?
80
Knowledge based analysis
81
Knowledge based analysis
For more detailed introduction to BiblioSpherePE
please have a look at http//www.genomatix.de/pr
oducts/BiblioSphere/BiblioSpherePE5.html
82
Knowledge based analysis
...un-tick this box... We are interested in the
full network around our gene, not only the
connected transcription factors
Choose "single gene" here...
HMGCS1
83
Knowledge based analysis
84
Knowledge based analysis
This sets the context sensitive filter
stringency. The most stringent including
computer based semantic analysis is an ordered
Gene1 function word Gene2 level (B3). (B4)
shows expert curated gene-gene relationships
only. Expert knowledge is derived by different
sources, like Genomatix experts, Molecular
Connections NetPro data base, STKE, etc...
Here you have a list of all other genes, being
connected to your input gene by at least one
co-citation in entire PubMed on abstract level
Click around, and see what happens !
85
Knowledge based analysis
This filters the co-citation frequency
I have intentionally chosen an example with no
expert curation available, since I want to
demonstrate how to generate new knowledge!
86
Knowledge based analysis
Here you see the network around HGMCS1, all other
genes connected on GFG level
87
Knowledge based analysis
Here connected transcription factors only on GFG
level.
88
Knowledge based analysis
Now all connected transcription factors.
89
Knowledge based analysis
A connection line between two genes means that
there is a bibliographic connection on abstract
level (BO)...
90
Knowledge based analysis
"Mouse over" and clicking gives you more
information...
91
Knowledge based analysis
The green indicates that there is a binding site
for SREBF1 (VSREB) in at least one of the
promoters of HMGCS1
92
Knowledge based analysis
There is more encoded in the connection
lines...
93
Knowledge based analysis
The little symbols give you some information
about the gene and its association with pathways
94
Knowledge based analysis
The tagged text tells us that the TF SREBF1 is
involved in regulation of HMGCS1
Some more helpful options from this page...
95
Knowledge based analysis
This you know already...
You can get all info about any gene you click up
there...
over here...
96
Knowledge based analysis
..as well as this.
97
Knowledge based analysis
Hey, hey hey ! Stop it ! I want to know about
the regulation of my gene, not to play around
with your Biblio...thing!
98
Knowledge based analysis
Hey, hey hey ! Stop it ! I want to know about
the regulation of my gene, not to play around
with your Biblio...thing!
BiblioSphere PathwayEdition ! We already found
TFs of interest, known to be involved in
regulation of our gene. Now lets see the
biological environment of our gene and find a
group of related genes which might share some
regulatory motifs. Lets go back and display all
genes contained in this network...
99
Knowledge based analysis
Lets load the GO-Filter "biological process"...
100
Knowledge based analysis
Go to the table view by this tab...
Here you see the tree for the selected filter.
Expand and collapse by clicking on the /-
101
Knowledge based analysis
The Z-Score gives you a measure whether certain
categories are significantly over- or
under-represented by the displayed gene set.
Top scoring is sterol and cholesterol
metabolism... Everything above 3 is
statistically significant!
Clicking here opens the tree on the left and
highlights the category as well as the resp.
genes in the pathway view.
102
Knowledge based analysis
This finally applies the filter to your gene
set. Superimpose as many filters as youd like !
103
Knowledge based analysis
We see two TFs in here, SREBF1 and SREBF2, both
Sterol Regulatory Element Binding Protein
factors.
The "redraw" button
Double-click on SREBF1 in order to see all
connections to that TF
104
Knowledge based analysis
Another table view...
105
Knowledge based analysis
...the colors encode for...
Highlight those genes with your mouse, and copy
them...
106
Knowledge based analysis
Now we have expanded our single input gene with a
set of seven additional genes! And we know
already quite a lot about them!
They all are connected with my original gene in
PubMed
All genes, with very high high statistical
significance, belong to the GO-category
"Cholesterol Metabolic Process"
SREB transcription factors seem to play a role in
the regulation of those genes
Now lets check whether the promoters of
those genes share a complex framework. For such
we first need to export those genes into
GenomatixSuites Gene2Promoter
107
Back to sequence level
Oh my god... more... Where do I find this now
?
Relax ! Its easy and not far away...
108
Back to sequence level
APOA1, LDLR, SREBF2, VLDLR, FDFT1, FDPS, MVK,
HMGCS1
Paste here the gene symbols which we just copied
in BiblioSpherePE
Dont forget this ! Otherwise you will be asked
for all findings in all organisms.
109
Back to sequence level
110
Back to sequence level
Hey stop ! Havent I seen this before ?
You are right! It pretty much is the same display
as the comparative genomics page which we have
generated earlier. The difference in this case
is that we now compare promoters of different
genes within one organism
111
Back to sequence level
Eight loci with 26 different unique promoters !
9.216 combinations possible for exhaustive
analysis! Combinatorial explosion !
How should I know which ones? How do I do this
?
Since we are concentrating on SREB TF-sites,
lets concentrate on those promoters which
contain an VSREB binding site.
We have to find a way to circumvent this
Very easy! Just scroll down to the bottom of the
page...
112
Back to sequence level
Select the desired TF-matrix family here
113
Back to sequence level
...and all relevant promoters are checked already
for you
Now we have reduced to 12 different promoters
from 8 different loci, each containing at least
one SREB site.
114
Back to sequence level
Scroll to the bottom of the Gene2Promoter result
page...
We have done this before...
115
Back to sequence level
You see? Now we have tolerable combinatorics and
can perform an exhaustive promoter analysis.
116
Back to sequence level
...but now we choose VSREB as a mandatory
element for our framework. Hint you can select
multiple elements by holding the "Ctrl" key
while clicking.
...and with these parameters you have to play
around a little bit. Start at default. Gradually
relax stringency. Go down in Quorum Constraint
step by step, or allow for higher distance
variance (e.g. 20, 30, 40, 50, usw...) The lower
the distance variance and the more elements per
model, the higher is the resulting model
selectivity.
Remember? We have been here before, too...
117
Back to sequence level
Tick the boxes of the models for subsequent
database search for other promoters with similar
organization. With 6 elements I expect to find
the 3 genes from which this models were derived
only SREBF2, HMGCS1, and MVK
There are frameworks with 6 elements! This is
quite significant and expected to be extremely
selective.
For example, at quorum of 30, allowed distance
range of 5 to 200 bp, distance variance of 50 bp
maximum elements allowed 10 we find quite a lot
of frameworks in the different promoter
combinations.
118
Back to sequence level
Now lets see how selective this model is...
Scroll all the way down...
This list is quite interesting! Here we have the
differents TF sites in this set of
frameworks. This list represents those TFs which
we should concentrate on, when analyzing the
regulation of the original input gene. It is
pretty comparable to the list from our
phylogenetic approach before. There is now good
evidence that those factors play a role in
regulation in the biological context of
cholesterol metabolism.
119
Back to sequence level
It is just one click away...
120
Back to sequence level
This should look familiar to you ! But now we
are going for the database section...
Unless you have a good reason to do so, always go
for the database of promoters of annotated genes.
This allows for GO-group Z-scoring of the
database hits later on...
121
Back to sequence level
This is a termination parameter. If this number
of hits is reached before the end of the
database, the search is terminated
Careful! Some browsers crash with too many hits
to display in HTML ! (gt10.000)
A database search usually takes several minutes.
In order to avoid a server time-out go for the
e-mail option. Youll receive a mail with a
direct link to your result file ( it will be kept
in your "Results Directory", too)
122
Back to sequence level
Eight matches!
In four sequences. Each model matches exactly
once per sequence...
The three genes of our "training set"...
...out of a total of 56.193 different promoters
Wow !
123
Back to sequence level
...plus one additional "new" gene! This one was
not in our input list and is identified only by
common promoter organization!
124
Back to sequence level
Those four genes now are extremely likely to
share common regulation in the given biological
context! The TFs in the framework now are the top
candidates for further inspection.
125
Back to sequence level
Those four genes now are extremely likely to
share common regulation in the given biological
context! The TFs in the framework now are the top
candidates for further inspection.
126
New Knowledge
I am terribly sorry for that! However,
eukaryotic transcriptional regulation is pretty
complex. Our group of researchers works in this
field since more than two decades. As you have
seen, our tools - though pretty easy to use -
require some explanations and sometimes a
slightly different mind-setting, going beyond
looking at single, isolated TF binding sites. I
hope I was able to show you some basic strategies
to follow. Nevertheless, lets have a final look
at the additional gene which we have found with
the database search in our example...
127
New Knowledge
128
New Knowledge
129
New Knowledge
MMAB is a transferase involved in vitamin B(12)
activation and linked to a disease methylmalonyl
aciduria
130
New Knowledge
Feeding all 4 genes from ModelInspector into
BiblioSpherePE shows that they are all connected
plus...
131
In our example, we started with a single gene (
HMGCS1), ElDorado put it into biological context
in and concentrated on an potential regulator (
SREB), BiblioSpherePE identified common promoter
organization (TF-Framework) GEMS Launcher ,
FrameWorker searched for additional genes with
similar promoter organization and GEMS Launcher ,
ModelInspector put the genes back into
biological context. BiblioSpherePE Literature
confirmed that we indeed found a co-regulated
network and identified the molecular basis for
such. This could NEVER be achieved by
statistical analysis of isolated TFBS
132
. There is so much more in GenomatixSuite PE I
did neither say a word to matrix generation, nor
to direct experimental planning for
knock-out/knock-in experiments with
SequenceShaper Expand the hit-list by shortening
the framework, etc... etc... Get in touch with
us via support_at_genomatix.de and we will give you
a tour through the entire system at a
web-meeting. Some informative links http//www.
genomatix.de/company/publications1.html http//ww
w.genomatix.de/training/tasks.html http//www.gen
omatix.de/download/download4.html http//www.geno
matix.de/cgi-bin/UMapps/register.pl