title: Model-based method for transcription factor target identification with limited data.
abstract: We present a computational method for identifying potential targets of a transcription factor (TF) using wild-type gene expression time series data. For each putative target gene we fit a simple differential equation model of transcriptional regulation, and the model likelihood serves as a score to rank targets. The expression profile of the TF is modeled as a sample from a Gaussian process prior distribution that is integrated out using a nonparametric Bayesian procedure. This results in a parsimonious model with relatively few parameters that can be applied to short time series datasets without noticeable overfitting. We assess our method using genome-wide chromatin immunoprecipitation (ChIP-chip) and loss-of-function mutant expression data for two TFs, Twist, and Mef2, controlling mesoderm development in Drosophila. Lists of top-ranked genes identified by our method are significantly enriched for genes close to bound regions identified in the ChIP-chip data and for genes that are differentially expressed in loss-of-function mutants. Targets of Twist display diverse expression profiles, and in this case a model-based approach performs significantly better than scoring based on correlation with TF expression. Our approach is found to be comparable or superior to ranking based on mutant differential expression scores. Also, we show how integrating complementary wild-type spatial expression data can further improve target ranking performance.
authors.affiliation: Department of Information and Computer Science, Aalto University School of Science and Technology, Helsinki, Finland. antti.honkela@tkk.fi
authors.forename: Antti
authors.initials: A
authors.lastname: Honkela
authors.forename: Charles
authors.initials: C
authors.lastname: Girardot
authors.forename: E Hilary
authors.initials: EH
authors.lastname: Gustafson
authors.forename: Ya-Hsin
authors.initials: YH
authors.lastname: Liu
authors.forename: Eileen E M
authors.initials: EE
authors.lastname: Furlong
authors.forename: Neil D
authors.initials: ND
authors.lastname: Lawrence
authors.forename: Magnus
authors.initials: M
authors.lastname: Rattray
mesh_terms: D001499:Bayes Theorem; D047369:Chromatin Immunoprecipitation; D029721:Drosophila Proteins / Q000378:metabolism*; D005786:Gene Expression Regulation / Q000235:genetics* / Q000502:physiology; D053263:Gene Regulatory Networks / Q000235:genetics*; D016013:Likelihood Functions; D008957:Models, Genetic; D009154:Mutation / Q000235:genetics; D018006:Myogenic Regulatory Factors / Q000378:metabolism*; D049490:Systems Biology / Q000379:methods*; D051879:Twist-Related Protein 1 / Q000378:metabolism*
chemical_list: D029721:Drosophila Proteins; C499409:Mef2 protein, Drosophila; D018006:Myogenic Regulatory Factors; D051879:Twist-Related Protein 1
references.citation: Bioinformatics. 2009 Feb 1;25(3):419-20
references.pmid: 19074958
references.citation: Genes Dev. 2007 Feb 15;21(4):436-49
references.pmid: 17322403
references.citation: Genome Res. 2008 Jun;18(6):939-48
references.pmid: 18441228
references.citation: Ann N Y Acad Sci. 2007 Dec;1115:1-22
references.pmid: 17925349
references.citation: Biotechniques. 2003 Feb;34(2):374-8
references.pmid: 12613259
references.citation: Genome Biol. 2006;7(3):R25
references.pmid: 16584535
references.citation: Dev Cell. 2006 Jun;10(6):797-807
references.pmid: 16740481
references.citation: Nature. 2009 Nov 5;462(7269):65-70
references.pmid: 19890324
references.citation: Proc Natl Acad Sci U S A. 2001 Apr 24;98(9):5116-21
references.pmid: 11309499
references.citation: Bioinformatics. 2005 Sep 15;21(18):3637-44
references.pmid: 16020470
references.citation: Genome Biol. 2009;10(7):R80
references.pmid: 19627575
references.citation: Science. 2001 Aug 31;293(5535):1629-33
references.pmid: 11486054
references.citation: Genome Biol. 2002;3(12):RESEARCH0088
references.pmid: 12537577
references.citation: Bioinformatics. 2005 Jun;21 Suppl 1:i159-68
references.pmid: 15961453
references.citation: Proc Natl Acad Sci U S A. 2006 Dec 5;103(49):18592-6
references.pmid: 17121995
references.citation: Nature. 2001 Jan 25;409(6819):533-8
references.pmid: 11206552
references.citation: Science. 2000 Dec 22;290(5500):2306-9
references.pmid: 11125145
references.citation: Bioinformatics. 2008 Aug 15;24(16):i70-5
references.pmid: 18689843
references.citation: BMC Bioinformatics. 2009 Jul 09;10:211
references.pmid: 19589155
references.citation: PLoS Biol. 2008 Feb;6(2):e27
references.pmid: 18271625
references.citation: Mol Syst Biol. 2007;3:78
references.pmid: 17299415
references.citation: Mol Syst Biol. 2009;5:276
references.pmid: 19536199