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 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

========== = ============ === = ===== === = = ===== == ======= human GCTTGAATTAGACAGGATTAAAGGC TTACTGGAGCTGGAAGCCTTGCCCC -AACTCAGGAGTTTAGCCCCA bovine GCTTGAATTAAATAGGATTAAAGGC TTATCAGGGCTGGGAGCTACACCCC -AACTCCTGAGTTTAGCCCCA mouse GCTTGAATTAGACAGGATTAAAGGC TTAGCAGAGCTGGAAGCCTCACATC TAACTCCCACATTGAGCCCCA | | | | DNA Motifs Alignment Profile Functional Significance? Motifs

Motif Finding Tools l AlignACE l GIBBS l Consensus l Propsector

l Information resides at multiple sources l Data follow multiple Structures l Multiple Interfaces The Need for motifML BioProspector Gibbs AlignACE Consensus MotifML Integrated XML view

l Gene expression regulation that is dependent on activated transcriptional factors l Key element of Gene Networks: Complex analysis of microarrays Motif Function Cis-Elements Associated with a Gene Transcriptional Factors + Regulated Gene Expression

motifML Goals l to allow the full specification of all experimental information known about motifs l to provide an extensible framework for this annotation and provide a common vehicle for exchanging the motif information l to provide a single document interface to integrate all project information, complete with protocols for network data retrieval.

motifML Design l formal and concise- ontology based l motifML documents easy to create l clarity more important than brevity l use both XML schema and XML DTD

motifML Semantics l Annotation »The collection of features for a given set of sequence(s) that have built in semantics l Features »Characteristics supported by analytic evidence l Analyses »Computational »Experimental

motifML Semantics Annotation Features Motifs Results Property Intentional Extraction Semantically Definable & Searchable Ontolog y Pragmatic Objects Analyse s

GenBank CRX Binding Element ATAATGTCCAAGATCTTCTGGAGAGTGTATCCCATGCTGTGGAGCACTCTGTGGAAGCCACGG GTCCTTTAGACAGCTCATCCTATGAGGAGCACTTCTTAACTGGCACTGGTCTCTTGCAGTTTCT GAGAACAAGGCTCTGTGCCATCCCTCGTCTGTTGACTCCCTCTCCACCAGCGCAGCCACGGA GGACCACGTCTCCATGGGAGGATGGGCAGCAAGGAAAGCCCTCAGGGTCATCGAGCATGTGG AGCAAGGTAATGCTGATGAGTTCGGGGTGGCGGGCCTGCCTGATAGACCACTGTGCCTGTGG TTCTCAAGTGGGATCTCCCACCAGCAACATCAGCATC ACCTGGAAAC motifML Sequence Item

Computational Analysis <!ELEMENT computational_analysis (date?, program, version?, parameter*, database?, result_set+)> <!ATTLIST seq_relationship seq IDREF #REQUIRED type (query | subject | peer ) #REQUIRED>

l 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. l 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. l Genes with an HSE at the upstream region may be co- regulated HSP and HSE

Dataset (Vertebrates)* l > gid , start=1, end=1027 l > gid , start=1, end=666 l > gid , start=1, end=1519 l > gid , start=1, end=800 l > gid 64795, start=1, end=487 l > gid 64791, start=1, end=614 l > gid 64789, start=1, end=1128 l > gid 64786, start=1, end=374 l > gid 32480, start=1, end=483 l > gid 32484, start=1, end=711 l > gid , start=1, end=424 l > gid , start=1, end=313 l > gid , start=1, end=760 l > gid , start=1, end=2179 l > gid , start=1, end=2634 l > gid , start=1, end=488 l > gid , start=1, end=959 l > gid , start=1, end=2631 l > gid , start=1, end=485 l > gid , start=1, end=489 l > gid , start=1, end=488 l > gid , start=1, end=391 l > gid 63508, start=1, end=1421 l > gid 63512, start=1, end=2300 l > gid , start=1, end=1231 l > gid , start=1, end=491 l > gid , start=1, end=426 *Data are from GenBank

l uses a Gibbs sampling strategy which is similar to that described by Neuwald et al., 1995 l An iterative masking procedure is used to allow multiple distinct motifs to be found within a single data set l Reference: Hughes et al., J Mol Biol : AlignACE program

AlignACE Results... Motif 1 GGGGAGGGGGTGGGGGGGC GGCGGGCGGGCGGCGGGGG GGACAGCGGCGGCTGGCTG GGGGTGCGGGGGCAGGCGC CCGCGGGGGCGGGCGGGGC ** * ***** ** *** * MAP Score: Motif 2 GGGGAGGGGGTGGGGGGGCGGGG GTGCGGGGGCAGGCGCGGAGAGC GCGGAGCGGGAGGGGGCGTGGCC GGGGTGCGGGAGGGCGGGCGGGC GGGCAGTGGGCGGCTGGCAGCTG

l Uses Stochastic Iterative Sampling l The Bernoulli motif sampler assumes that each sequence can contain zero or more ungapped motif elements of each motif type l Reference: »Lawrence et al., Science 1993;262(5131):208-14; »Neuwald et al., Protein Sci Aug;4(8): Gibbs Motif Sampler Program

Gibbs Results... 4, agtgc AGAGTCTGGAGAGC cgaat R gid , start=1, end=800 4, ggtat AGATGTCGGAGAGT cgttt R gid , start=1, end=800 4, atgga AGCCTCGGGAAACT tcggg F gid , start=1, end=800 5, atgga AGCCTCGGGAAACT tcggg F gid 64795, start=1, end=487 7, agtgt GGGTGCTGGAGGCT gacgg R gid 64789, start=1, end=1128 9, 1 26 ggagt GGCGGTGGGAAGGG tgttg R gid 32480, start=1, end= **************...

l Uses entropy-based scoring functions l References: »Stormo and Hartzell, PNAS 1989;86: »Hertz et al., 1990, CABIOS, 6:81-92 Consensus Program

Consensus Results MATRIX |23 : 1/593 TGCAAGATTTTTAA 2|9 : 2/8 TGGAGGCTTCCAGA 3|10 : 3/889 TGGAGGCTTCCAGA... MATRIX |23 : 1/593 TGCAAGATTTTTAA 2|9 : 2/8 TGGAGGCTTCCAGA 3|10 : 3/889 TGGAGGCTTCCAGA... MATRIX 3 1|23 : 1/593 TGCAAGATTTTTAA 2|9 : 2/8 TGGAGGCTTCCAGA 3|10 : 3/889 TGGAGGCTTCCAGA... MATRIX 4 1|21 : 1/38 GGGAAAGCTCGAGA 2|9 : 2/8 TGGAGGCTTCCAGA 3|10 : 3/889 TGGAGGCTTCCAGA...

l a program that examines the upstream region of genes in the same gene expression pattern group to search for regulatory sequence motifs. l uses zero to third-order Markov background models l allows for the searching of gapped motifs and motifs with palindromic patterns l Reference: Liu et al., Pac Symp Biocomput. 2001: BioProspector Program

BioProspector Results... Motif #1:... Seq #1 seg 1 r998 TCATCCAATCAGAG Seq #2 seg 1 f91 TCAACCGAACAGAA Seq #3 seg 1 r638 TCGACCAATCAAAA... Motif #2:... Seq #1 seg 1 f38 GGGAAAGCTCGAGA Seq #2 seg 1 r648 TGGAAGCCTCCAGT Seq #3 seg 1 r620 TGGAAGCCTCCAGT... Motif #3:... Seq #1 seg 1 r997 CTCATCCAATCAGA Seq #2 seg 1 f90 CTCAACCGAACAGA Seq #3 seg 1 r637 TTCGACCAATCAAA...

Conceptions and Interactions of the Underlying Statistical Algorithms Used by the Motif Searching Programs Gibbs AlignACE CONSENSUS Information Content BioProspector Gibbs Sampler; Iterative Updating Strategy Two Block Motif Model

Motif Data Representation l Common data representation for motif information. l Uses XML Schema to specify format. l Both human and machine readable. l Supports “knowledge mining”. l Statements can be asserted about a motif such as a role in gene regulation.

Example of a motif Blk1 A G C T

XML Schema l Extends the XML document type language: »Data format restrictions. »Data value (min and max) restrictions. »Element occurrence (min and max) restrictions. l No sophisticated restrictions: »Probability distribution.

XML Schema for MotifML <xsd:element name="block" minOccurs="0" maxOccurs="unbounded" type="BlockType"/>...

Statements about motifs <RDF xmlns=" xmlns:rdf=" xmlns:mml=" xmlns:bp="

l How do biologists learn the element structure of a document describing the heterogeneous sequence alignment output? l How do biologists share the structure and meta-data on motif profiles efficiently and unambiguously? The Need for Bio-Ontologies

========== = ============ === = ===== === = = ===== == ======= human GCTTGAATTAGACAGGATTAAAGGC TTACTGGAGCTGGAAGCCTTGCCCC -AACTCAGGAGTTTAGCCCCA bovine GCTTGAATTAAATAGGATTAAAGGC TTATCAGGGCTGGGAGCTACACCCC -AACTCCTGAGTTTAGCCCCA mouse GCTTGAATTAGACAGGATTAAAGGC TTAGCAGAGCTGGAAGCCTCACATC TAACTCCCACATTGAGCCCCA PCE-I -CBE-- AP cETS cETS | | | | 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)X53044M32733M32734 Alignment Profile

Transcriptional Factors Ontology Composite Element Site Transcriptional Motif Elements Transcriptional Factors ContextTranscript Tissue Stage Disease Env.Cond. Induced Kind of Part of Binds to Upstream to Within Found in produces Gene Observation contains

l Develop a data exchange format for DNA motif data l Handling output from motif analyses l Annotation and data mining of micro-array data l Important in modeling transcriptional regulatory networks in eukaryotes MotifML Applications

Future Directions l Distributed Annotation System – Lincoln Stein, Open-Bio l Exchange with Other XML Dialects l DAML development