Machine Learning Transcriptional Regulators Figure 6. The wild-type activities of FC enhancers require input from classifier-defined Myb and POUHD TF binding motifs. (A) TRANSFAC position weight matrices for Myb (V$MYB_Q6) and POUHD (V$POU1F1_Q6) enriched motifs identified by the classifier. (B) Binding site sequences in the Ndg enhancer for Myb and POUHD and versions in which those sites are selectively mutated. Motifs were defined by searching for matches to the vertebrate homologues in the UniPROBE database [99]. The identification of these binding sites and the designs of the mutant versions are described in Table S4. (C) GFP (green) and b-Gal (magenta) are co-expressed when driven by the wild-type (WT) Ndg enhancer (NdgWT- GFP and NdgWT-lacZ, respectively). (D) GFP (green) expression driven by a version of the Ndg enhancer in which POUHD sites are selectively inactivated (NdgPOUHD-GFP) is significantly reduced compared to b-Gal (magenta) driven by NdgWT-lacZ. (E) b-Gal driven by a version of the Ndg enhancer in which Myb binding sites are selectively inactivated (NdgMyb-lacZ) is de-repressed into additional somatic mesodermal cells compared to GFP driven by a WT version of the Ndg enhancer (NdgWT-GFP). doi:10.1371/journal.pgen.1002531.g006 interested in determining the distribution of all known regulatory motifs in enhancers of this class. We reasoned that such a survey might reveal whether TF combinatorics contribute to FC enhancer specificity. Thus, we analyzed all 18 D. melanogaster FC enhancers (16 from the original training set plus 2 more enhancer predictions whose activities were validated in the current study) for the presence of a total of 11 types of TFBSs that are known to contribute to FC activity. For this purpose, we added 7 motifs from prior studies of FC enhancers to the 4 new motifs discovered here. We had previously constructed and validated a regulatory model of FC enhancer activity which reflected the coordinated input of Tcf, Mad, Pnt, Twi and Tin [28,29]. Subsequently, combining the clustering of FC genes based on genetic perturbation responses with a systematic in silico evaluation of candidate transcriptional regulatory models, we demonstrated that Pnt, Twi and Tin alone target a subset of highly Ras-responsive FC genes [5]. In addition to these 5 motifs, we included 2 other previously characterized myogenic regulatory sequences that are bound by Mef2 [66] and homeodomain (HD) TFs ([35,67] and B. W. Busser, L. Shokri, S. A. Jaeger, S. S. Gisselbrecht, A. Singhania, M. F. Berger, B. Zhou, M. L. Bulyk and A. M. Michelson, unpublished data). Using position weight matrices (PWMs) for 3 signal-activated TFs (Tcf, Mad and Pnt), the ubiquitously expressed Myb, 4 tissue- restricted TFs (Twi, Tin, Mef2 and HD, where HD in this case represents Hox factors that are widely expressed throughout the somatic mesoderm [59]), plus 4 cell type-specific TF classes (POUHD, Fkh, T-box and HD, where in this case HD refers to muscle identity TFs such as Slou, Ap, and Muscle Segment Homeobox that are expressed in various subsets of FCs [54,68,69]), we scanned and scored all 18 FC enhancers for at least one occurrence of each of these 11 binding site motifs (Figure 8, Figure S9 and Table S6). Interestingly, this analysis revealed that each FC enhancer has a unique combination of predicted binding sites for all 11 of these TF classes. On the other hand, the FC enhancers exhibited various overlapping TFBS combinations when subsets of the 11 motifs were considered (Figure S9 and Table S6). Of note, the only motif that is present in all 18 FC enhancers binds the MAPK-activated TF Pnt, a result that is consistent with prior evidence demonstrating that the receptor tyrosine kinase/Ras pathway is the major inductive signal for establishing all FC fates [49,70]. A number of caveats must be considered in interpreting the above analysis of motif distributions within FC enhancers. First, PLoS Genetics | www.plosgenetics.org 11 March 2012 | Volume 8 | Issue 3 | e1002531