motifml a novel ontology-based xml model for data-exchange of regulatory dna motif profiles
DESCRIPTION
MotifML A Novel Ontology-based XML Model for Data-Exchange of Regulatory DNA Motif Profiles Eric Neumann, Beyond Genomics Tian Niu, Harvard University Ken Baclawski, Northeastern University. Motifs. DNA Motifs. ========== = ============ === = ===== === = = ===== == ======= - PowerPoint PPT PresentationTRANSCRIPT
MotifMLA Novel Ontology-based XML Model for Data-
Exchange of Regulatory DNA Motif Profiles
Eric Neumann, Beyond Genomics
Tian Niu, Harvard University
Ken Baclawski, Northeastern University
MotifMLA Novel Ontology-based XML Model for Data-
Exchange of Regulatory DNA Motif Profiles
Eric Neumann, Beyond Genomics
Tian Niu, Harvard University
Ken Baclawski, Northeastern University
========== = ============ === = ===== === = = ===== == =======human GCTTGAATTAGACAGGATTAAAGGC TTACTGGAGCTGGAAGCCTTGCCCC -AACTCAGGAGTTTAGCCCCAbovine GCTTGAATTAAATAGGATTAAAGGC TTATCAGGGCTGGGAGCTACACCCC -AACTCCTGAGTTTAGCCCCAmouse GCTTGAATTAGACAGGATTAAAGGC TTAGCAGAGCTGGAAGCCTCACATC TAACTCCCACATTGAGCCCCA | | | | -70 -45 -20 +1
DNA Motifs
Alignment ProfileAlignment Profile
Functional Significance?
Motifs
Motif Finding ToolsMotif Finding Tools
AlignACE GIBBS Consensus Propsector
Information resides at multiple sources Data follow multiple Structures Multiple Interfaces
The Need for motifMLThe Need for motifML
BioProspector Gibbs AlignACEConsensus
MotifML
Integrated XML view
Gene expression regulation that is dependent on activated transcriptional factors
Key element of Gene Networks: Complex analysis of microarrays
Motif FunctionMotif Function
Cis-ElementsAssociated with a Gene
Transcriptional Factors
++ Regulated Gene Expression
motifML GoalsmotifML Goals
to allow the full specification of all experimental information known about motifs
to provide an extensible framework for this annotation and provide a common vehicle for exchanging the motif information
to provide a single document interface to integrate all project information, complete with protocols for network data retrieval.
motifML DesignmotifML Design
formal and concise- ontology based motifML documents easy to create clarity more important than brevity use both XML schema and XML DTD
motifML SemanticsmotifML Semantics
Annotation» The collection of features for a given set of
sequence(s) that have built in semantics Features
» Characteristics supported by analytic evidence Analyses
» Computational» Experimental
motifML SemanticsmotifML Semantics
Annotation
Features
MotifsResults
Property
Intentional Extraction
Semantically Definable & Searchable
Ontology
Pragmatic Objects
Analyses
<seq id=“demo_seq” name=“Human HAL Gene Exon 18”> <dbxref> <database>GenBank</database> <unique_id>14588658 </unique_id> </dbxref> <feature> <motif type=“cis-regulatory” name=“CBE” id=“dm312”/> <description> CRX Binding Element </description> <position start=“21” end=“32” /> <evidence> <reference paper=“Davies, J Mol Biol. 1993 296:1205-14”/> </evidence> </feature> <residues type=“dna”> ATAATGTCCAAGATCTTCTGGAGAGTGTATCCCATGCTGTGGAGCACTCTGTGGAAGCCACGGGTCCTTTAGACAGCTCATCCTATGAGGAGCACTTCTTAACTGGCACTGGTCTCTTGCAGTTTCTGAGAACAAGGCTCTGTGCCATCCCTCGTCTGTTGACTCCCTCTCCACCAGCGCAGCCACGGAGGACCACGTCTCCATGGGAGGATGGGCAGCAAGGAAAGCCCTCAGGGTCATCGAGCATGTGGAGCAAGGTAATGCTGATGAGTTCGGGGTGGCGGGCCTGCCTGATAGACCACTGTGCCTGTGGTTCTCAAGTGGGATCTCCCACCAGCAACATCAGCATC ACCTGGAAAC </residues></seq>
motifML Sequence Item
motifML Sequence Item
Computational Analysis
Computational Analysis
<!ELEMENT computational_analysis (date?, program, version?, parameter*, database?, result_set+)> <!ATTLIST computational_analysis seq IDREF #REQUIRED>
<!ELEMENT program (#PCDATA)>
<!ELEMENT result_set (score?, output*, result*)>
<!ELEMENT result (score, type, subtype?, seq_relationship+, output*)> <!ATTLIST result id ID #IMPLIED>
<!ELEMENT seq_relationship (location, alignment?)> <!ATTLIST seq_relationship seq IDREF #REQUIRED type (query | subject | peer ) #REQUIRED>
<!ELEMENT alignment (#PCDATA)><!ELEMENT type (#PCDATA)><!ELEMENT value (#PCDATA)><!ELEMENT parameter (type, value)><!ELEMENT output (type, value)><!ELEMENT database (name, date?, version?)><!ELEMENT version (#PCDATA)><!ELEMENT score (#PCDATA)>
Heat shock and other environmental and pathophysiologic stresses stimulate synthesis of heat shock proteins (Hsps). These proteins enable the cell to survive and recover from stressful conditions by as yet incompletely understood mechanisms.
A conserved 14 base pair regulatory sequence, referred to as the heat shock element (HSE), is found in multiple imperfect copies
upstream of the TATA box of all heat shock genes. Genes with an HSE at the upstream region may be co-regulated
HSP and HSEHSP and HSE
Dataset (Vertebrates)*Dataset (Vertebrates)*
> gid 3004462, start=1, end=1027 > gid 7861931, start=1, end=666 > gid 7108904, start=1, end=1519 > gid 7739662, start=1, end=800 > gid 64795, start=1, end=487 > gid 64791, start=1, end=614 > gid 64789, start=1, end=1128 > gid 64786, start=1, end=374 > gid 32480, start=1, end=483 > gid 32484, start=1, end=711 > gid 7669470, start=1, end=424 > gid 5729878, start=1, end=313 > gid 5031770, start=1, end=760
> gid 1816451, start=1, end=2179
> gid 184422, start=1, end=2634 > gid 184416, start=1, end=488 > gid 188491, start=1, end=959 > gid 4691417, start=1, end=2631 > gid 188489, start=1, end=485 > gid 188487, start=1, end=489 > gid 184416, start=1, end=488 > gid 211940, start=1, end=391 > gid 63508, start=1, end=1421 > gid 63512, start=1, end=2300 > gid 409185, start=1, end=1231 > gid 163160, start=1, end=491 > gid 414974, start=1, end=426*Data are from GenBank
uses a Gibbs sampling strategy which is similar to that described by Neuwald et al., 1995
An iterative masking procedure is used to allow multiple distinct motifs to be found within a single data set
Reference: Hughes et al., J Mol Biol. 2000 296:1205-14
AlignACE programAlignACE program
AlignACE ResultsAlignACE Results
...Motif 1GGGGAGGGGGTGGGGGGGC 23 788 0GGCGGGCGGGCGGCGGGGG 23 867 1GGACAGCGGCGGCTGGCTG 11 107 0GGGGTGCGGGGGCAGGCGC 23 1417 1CCGCGGGGGCGGGCGGGGC 13 2034 1...** * ***** ** *** *MAP Score: 794.004
Motif 2GGGGAGGGGGTGGGGGGGCGGGG 23 784 0GTGCGGGGGCAGGCGCGGAGAGC 23 1420 1GCGGAGCGGGAGGGGGCGTGGCC 13 1932 1GGGGTGCGGGAGGGCGGGCGGGC 23 1448 1GGGCAGTGGGCGGCTGGCAGCTG 14 1452 1 ...
Uses Stochastic Iterative Sampling The Bernoulli motif sampler assumes that each
sequence can contain zero or more ungapped motif elements of each motif type
Reference: » Lawrence et al., Science 1993;262(5131):208-14; » Neuwald et al., Protein Sci. 1995 Aug;4(8):1618-32.
Gibbs Motif Sampler Program
Gibbs Motif Sampler Program
Gibbs ResultsGibbs Results
...
4, 1 284 agtgc AGAGTCTGGAGAGC cgaat 271 0.87 R gid 7739662, start=1, end=800
4, 2 425 ggtat AGATGTCGGAGAGT cgttt 412 0.79 R gid 7739662, start=1, end=800
4, 3 643 atgga AGCCTCGGGAAACT tcggg 656 0.86 F gid 7739662, start=1, end=800
5, 1 239 atgga AGCCTCGGGAAACT tcggg 252 0.86 F gid 64795, start=1, end=487
7, 1 401 agtgt GGGTGCTGGAGGCT gacgg 388 0.99 R gid 64789, start=1, end=1128
9, 1 26 ggagt GGCGGTGGGAAGGG tgttg 13 0.99 R gid 32480, start=1, end=483... ************** ...
Uses entropy-based scoring functions References:
» Stormo and Hartzell, PNAS 1989;86:1183-1187» Hertz et al., 1990, CABIOS, 6:81-92
Consensus ProgramConsensus Program
Consensus ResultsConsensus Results
MATRIX 1...1|23 : 1/593 TGCAAGATTTTTAA2|9 : 2/8 TGGAGGCTTCCAGA3|10 : 3/889 TGGAGGCTTCCAGA...MATRIX 2...1|23 : 1/593 TGCAAGATTTTTAA2|9 : 2/8 TGGAGGCTTCCAGA3|10 : 3/889 TGGAGGCTTCCAGA...MATRIX 31|23 : 1/593 TGCAAGATTTTTAA2|9 : 2/8 TGGAGGCTTCCAGA3|10 : 3/889 TGGAGGCTTCCAGA...MATRIX 41|21 : 1/38 GGGAAAGCTCGAGA2|9 : 2/8 TGGAGGCTTCCAGA3|10 : 3/889 TGGAGGCTTCCAGA...
a program that examines the upstream region of genes in the same gene expression pattern group to search for regulatory sequence motifs.
uses zero to third-order Markov background models allows for the searching of gapped motifs and motifs
with palindromic patterns Reference: Liu et al., Pac Symp Biocomput. 2001:127-38
BioProspector ProgramBioProspector Program
BioProspector ResultsBioProspector Results
...Motif #1:... Seq #1 seg 1 r998 TCATCCAATCAGAGSeq #2 seg 1 f91 TCAACCGAACAGAASeq #3 seg 1 r638 TCGACCAATCAAAA...Motif #2:...Seq #1 seg 1 f38 GGGAAAGCTCGAGASeq #2 seg 1 r648 TGGAAGCCTCCAGTSeq #3 seg 1 r620 TGGAAGCCTCCAGT...Motif #3:...Seq #1 seg 1 r997 CTCATCCAATCAGASeq #2 seg 1 f90 CTCAACCGAACAGASeq #3 seg 1 r637 TTCGACCAATCAAA...
Conceptions and Interactions of the Underlying Statistical Algorithms
Used by the Motif Searching Programs
Conceptions and Interactions of the Underlying Statistical Algorithms
Used by the Motif Searching Programs
GibbsAlignACE
CONSENSUS T
Abbbseq pffI )/(log2
Information Content
BioProspector
Gibbs Sampler; Iterative Updating Strategy
Two Block Motif Model
Motif Data Representation
Motif Data Representation
Common data representation for motif information.
Uses XML Schema to specify format. Both human and machine readable. Supports “knowledge mining”. Statements can be asserted about a
motif such as a role in gene regulation.
Example of a motif<motif id="GXY1"> <block> <base type="G">0.21</base> <base type="C">0.21</base> <base type="T">0.59</base> </block> <block> <base type="G">0.44</base> <base type="C">0.50</base> <base type="T">0.06</base> </block> <block> <base type="A">0.70</base> <base type="G">0.29</base> </block> ...</motif>
Blk1 A G C T
1 0.00 0.21 0.21 0.59
2 0.00 0.44 0.50 0.06
3 0.70 0.29 0.00 0.00
4 0.32 0.62 0.00 0.06
5 0.03 0.00 0.97 0.00
6 0.00 0.00 1.00 0.00
7 0.85 0.09 0.03 0.03
8 0.88 0.12 0.00 0.00
9 0.03 0.00 0.03 0.94
10 0.03 0.09 0.88 0.00
11 0.70 0.12 0.18 0.00
...
XML Schema
Extends the XML document type language:» Data format restrictions.» Data value (min and max) restrictions.» Element occurrence (min and max)
restrictions. No sophisticated restrictions:
» Probability distribution.
XML Schema for MotifML<xsd:schema xmlns:xsd="http://www.w3.org/2001/XMLSchema"><xsd:element name="motif" type="MotifType"/><!-- A motif consists of a sequence of blocks. --><xsd:complexType name="MotifType"> <xsd:sequence> <xsd:element name="block" minOccurs="0" maxOccurs="unbounded" type="BlockType"/> </xsd:sequence></xsd:complexType><!-- A block specifies a probability for each DNA base type. --><xsd:complexType name="BlockType"> <xsd:sequence> <xsd:element name="base" minOccurs="1" maxOccurs="4">...
Statements about motifs
<?xml version="1.0"?>
<RDF xmlns="http://www.w3.org/1999/02/22-rdf-syntax-ns#”
xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#”
xmlns:mml="http://www.beyondgenomics.com/2001/07/motifml#"
xmlns:bp="http://www.beyondgenomics.com/2001/07/biopathway#"/>
<Description about="http://www.beyondgenomics.com/motifdb/gxy1">
<bp:upregulate rdf:resource="http://www.beyondgenomics.com/motifdb/awy5"/>
<bp:upregulate rdf:resource="http://www.beyondgenomics.com/motifdb/ftg6"/>
<bp:downregulate rdf:resource="http://www.beyondgenomics.com/motifdb/bgt3"/>
</Description>
</RDF>
How do biologists learn the element structure of a document describing the heterogeneous sequence alignment output?
How do biologists share the structure and meta-data on motif profiles efficiently and unambiguously?
The Need for Bio-Ontologies
The Need for Bio-Ontologies
========== = ============ === = ===== === = = ===== == =======human GCTTGAATTAGACAGGATTAAAGGC TTACTGGAGCTGGAAGCCTTGCCCC -AACTCAGGAGTTTAGCCCCAbovine GCTTGAATTAAATAGGATTAAAGGC TTATCAGGGCTGGGAGCTACACCCC -AACTCCTGAGTTTAGCCCCAmouse GCTTGAATTAGACAGGATTAAAGGC TTAGCAGAGCTGGAAGCCTCACATC TAACTCCCACATTGAGCCCCA PCE-I -CBE-- AP-4 8888 cETS cETS | | | | -70 -45 -20 +1
A multiple sequence alignment linked with TRANSFAC/TRANSPATH
Shown here is the alignment from -70 to +1. The numbering shown corresponds to the mouse sequence. Identical bases are shown by the = above each nucleotide. Consensus sequence matches conserved among all three species are: the Ret-1/PCE-I element at -65 to -60, the CRX-binding element (CBE) at -55 to -50, an AP-4 consensus core sequence at -37 to -34, a cETS consensus core at -35 to -31 and another at positions -57 to -54, and an S8 homeodomain is shown by "8888" at -64 to -61. Only the core bases are marked. The criteria for searching the TRANSFAC Database by MatInspector were a match to the core sequence of at least 80% and to the entire consensus sequence of at least 85%. The Genbank entries for human, bovine, and mouse are X53044, M32733, and M32734, respectively. (Boatright, Mol Vis 1997; 3:15)
Alignment ProfileAlignment Profile
Transcriptional Factors Ontology
Composite Element
Site
Transcriptional Motif Elements
Transcriptional Factors
Context Transcript
•Tissue
•Stage
•Disease
•Env.Cond.
•Induced
Kind of
Part of
Binds to
Upstream to
Within
Found in
produces
Gene
Observation
contains
Develop a data exchange format for DNA motif data
Handling output from motif analyses Annotation and data mining of micro-array
data Important in modeling transcriptional
regulatory networks in eukaryotes
MotifML ApplicationsMotifML Applications
Future DirectionsFuture Directions
Distributed Annotation System –Lincoln Stein, Open-Bio
Exchange with Other XML Dialects DAML development