sequences, the expected and observed values were sub- jected to a Fisher’s exact test and false discovery rate (FDR; P-value < 0.05) correction for multiple testing (35). This way, we identiﬁed potential overlapping binding sites that were signiﬁcantly over-abundant or under-represented. Out of the 192 327 possible uniﬁcations of putative overlapping binding sites, we found 72 uniﬁed sequences that were signiﬁcantly over-abundant and 153 that were signiﬁcantly under-represented (see Supplementary Table S1 for the speciﬁc overlaps). Several SR protein-binding sites have a signiﬁcant tendency to overlap. However, this phenomenon may not be unique to splicing regulatory sequences. It may be that any similar subset of sequences would exhibit the same tendency to overlap, yielding similar numbers of over-abundant and under-represented overlaps. In order to address this issue, we generated 100 random subsets of sequences, which were not detected as splicing regulatory elements by any of the ESEﬁnder matrices (33,34) nor by other known bioinformatic detection methods (15,36,37). Each random subset was composed of the same number of hexamers, heptamers and octamers as the original dataset. Next, we performed the same statistical analyses to reveal signiﬁcant overlaps between the random sequences in each of the 100 random subsets. We found that the number of signiﬁcant over-abundant and under-represented SR-binding site overlaps was signiﬁcantly higher than the one observed for all 100 random datasets containing splicing inert sequences (P < 0.01 for both the over-abundant and under-represented sequences). We were also interested to examine whether the SR-binding sites that form the over-abundant and under-represented overlaps tend to appear in proximity, even if not in overlap. If so, their tendency to appear in overlap could be only a special case of their general tendency to be in proximity. We examined the average distance between every two SR-binding sites that formed an overlapping motif. This average distance was calculated for all SR-binding sites that formed a signiﬁcantly over-abundant or under-represented overlapping motif. As control, we calculated the average distance between every two SR-binding sites that did not form over-abundant or under-represented overlapping sites. We found that the average distance between the putative SR-binding sites that form an over-abundant or an under-represented overlapping motif did not signiﬁcantly diﬀer from the control dataset (see Supplementary Figure S1). This suggests that the overlapping motif itself is important and that the results we found could not be explained by mere proximity between SR-binding sites. Comparative analysis revealed high conservation of over-abundant motif overlaps We identiﬁed 72 signiﬁcantly over-abundant and 153 signiﬁcantly under-represented overlapping SR protein putative binding motifs. To shed light on the functionality of these motif overlaps, we employed a comparative genomics approach. The common premise underlying comparative genomic analyses is that selective pressure Nucleic Acids Research, 2010, Vol. 38, No. 10 3321 dictates that functional elements evolve at a slower rate than that of non-functional sequences. Indeed, splicing regulatory elements were shown to be highly conserved, indicative of their signiﬁcance in splicing regulation (38,39). To examine the conservation level of the signiﬁ- cant overlaps we identiﬁed, we extracted a dataset of human exons and their conserved orthologs (>75% nucleotide identity) in mouse (Mus musculus), rat (Rattus norvegicus), cow (Bos taurus), dog (Canis familiaris), chicken (Gallus gallus) and zebraﬁsh (Danio rerio). We then calculated the percentage of over-abundant and under-represented SR motif overlaps that were fully conserved (no mismatches allowed) between the human exons and their orthologous counterparts. As control for the signiﬁcantly over-abundant (or under-represented) motifs, we used all overlap motifs that appeared more (or less) than expected albeit not signiﬁcantly. As illustrated in Figure 2, compared to the non-signiﬁcant motifs, the 72 over-abundant overlapping motifs we identiﬁed are signiﬁcantly conserved between human exons and their orthologous counterparts in mouse (P = 4.77e 60), rat (P = 1.68e 32), cow (P = 4.72e 18), dog (P = 1.62e 04), chicken (P = 6.05e 07) and zebraﬁsh (P = 3.13e 03, 2 with df = 1 for all tests). Examination of the 153 under-represented motifs overlaps revealed insigniﬁcant results. We were concerned that some of the mismatches we identiﬁed do not actually change the ability of the sequence to function as a binding platform for the corre- sponding SR protein, i.e. the k-mer including the mismatch still belongs to the same SELEX matrix. We therefore repeated this analysis, this time considering mismatches that still preserve the ‘binding-type’ (giving ESEﬁnder motif score higher than the threshold) as conserved. However, this analysis yielded similar results (see Supplementary Data). We next employed another statistical approach to conﬁrm the validity of the conservation level of the over-represented motifs. Under the assumption that two adjacent N-mers are independent, the expected con- servation level of each overlapping SR-binding motifs could be calculated based on three observations: (i) the conservation level of the putative SR-binding site, Cons(SRbinding); (ii) the conservation level of the corre- sponding extension of N-mers, Cons(extension) and (iii) the number of times the corresponding overlap was detected in the dataset, Occurrence (SRbinding + extension), as follows: ConsðSRbindingÞ ConsðextensionÞ OccurenceðSRbinding þ extensionÞ: 2 ð Þ After calculating the expected conservation level of each overlapping sequence in the orthologous exons between human and each of the other examined species, we examined these exons to extract the actual conservation level of each of the overlapping motifs. For example, the overlap TGACTCCAG is comprised of the SRp40-binding site TGACTCC and of the extension AG, which is derived from the SR-binding site SC35 (G ACTCCAG). The expected conservation level of this