DNA Motifs

Our goals were to produce a resource that (i) contains a comprehensive collection of relevant motifs for each factor; (ii) avoids repetitive, weakly enriched motifs that do not contribute to the in vivo specificity of the factor or its partners; and (iii) excludes variants of the same motif, particularly among the discovered motifs. With this in mind, we conducted motif discovery separately on each data set using five motif discovery tools and manually placed all its data sets into ‘factor groups’ on the basis of known motifs and homology (Figure 2). Known motifs from the literature and the top 10 most enriched discovered motifs (excluding duplicates) were collected for each factor group (see Supplementary Methods) and named as TF_known# for known motifs and TF_disc# for discovered motifs, where TF denotes the factor group (e.g. FOXA, CTCF, etc.). Known motifs were ordered arbitrarily, whereas the discovered motifs were ordered in descending order of the enrichment value that was used for their selection.
Figure 2.

Outline of motif discovery pipeline. Input regions for each data set are randomly partitioned into two groups. The top 250 regions of one of the partitions are scanned for motifs using five de novo motif discovery tools. These motifs are evaluated using the peaks from the other partitioned and pooled across data sets for a factor group to produce the final list of discovered motifs for each factor group.

The 427 ENCODE experiments analyzed correspond to 123 TFs, which we place into 84 factor groups (Figure 3a). We failed to discover an enriched motif for only 12 of the 84 factor groups, of which 9 lack DNA binding domains (BRF, CTBP2, HDAC8, KAT2A, NELFE, SUPT20H, SUZ12, WRNIP1 and XRCC4) as identified by UniProt (27 (link)), and 6 have all their data sets flagged as unreliable based on various quality metrics [BRF, KAT2A, NELFE, NR4A, SUPT20H and ZZZ3; see (A. Kundaje, L.Y. Jung, P.V. Kharchenko, B. Wold, A. Sidow, S. Batzoglou and P.J. Park, in preparation)]. Of these factor groups, only NR4A has a previously identified known motif.
Figure 3.

(a) Summary of input data used. The outside ring indicates the experimental data sets (one tick for each of 427), which are separated into 123 transcription factors (second ring). The TFs are further grouped into 84 factor groups (third ring). We are able to find a matching discovered motif for 41 of the 56 factor groups with a known motif; 29 of these 41 factor groups have additional discovered motifs that may be associated with cofactors. For all but 1 of the 15 factor groups where the known motif is not recovered we still find enriched discovered motifs. We also discovered enriched motifs for 17 of the 28 factor groups without a known motif. (b) Recovery of known motifs by each of the discovery tools. Performance of discovery in terms of number of factor groups for which the known motif was recovered. A motif is considered a match if it matches any of the known motifs for a factor group (see Supplementary Methods for details on how matches are computed). The number of additional factors that have a match is shown with each additional motif (only three motifs are taken from each individual method, whereas we have up to 10 for the pipeline). The number of factor groups with no motif match is shown in parenthesis. When multiple data sets exist for a factor group, the fraction that matches is used in computing its contribution for computing the performance of the individual tools.

We exclude from the discussion below motifs that we consider unlikely to be relevant to our analysis, while maintaining them as part of the overall resource where they may be useful. These include 46 discovered motifs that are either low-complexity (e.g. dinucleotide repeats) or consistently have weak enrichment (<2) and do not match known motifs (Supplementary Table S1). These are likely a consequence of slight biases in the discovery pipeline, or are due to real, but relatively weak, specificity for the factor. We also exclude an additional 36 motifs that have a weak similarity to the known motif for the factor but for which a better matching and enriched motif is also found (Supplementary Table S2). These are most frequently seen for longer motifs that can be broken up into recognizable, but globally dissimilar, patterns that are not captured by our automatic exclusion criteria (see Supplementary Methods). Together, these represent 28% of the 293 discovered motifs.

We searched for the short tandem repeat (STR)-signature of the employed cell product within isolated baboon DNA. Three SUR-sampled pieces of lung, liver, and spleen tissue per animal were obtained prior to isolation of genomic DNA using column-based techniques (Qiagen) and pooling of equal amounts DNA per animal. The same procedure was performed for frozen arterial blood pellets obtained during, and 24 or 72 hours after cell therapy and the administered cell product. We then ran 100 ng genomic DNA per animal and sample using a highly sensitive, 17 loci-extended forensic STR analysis kit (AmpFLSTR NGM SElect) on an Applied Biosystems 3500 forensic genetic analyzer. Data was analyzed utilizing the GeneMapper ID-X software package (all from Thermo Fisher). The STR-pattern of the employed cell product, as well as baboon-specific STR were identified and separated from the signatures of other human DNA (laboratory, medical and veterinarian staff) contaminating the samples.