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Images were processed using the ZEN software Zeiss. Expression of GFP from transgenic lines and the expression of mRNA in wild-type fish were compared manually using neuroanatomical landmarks and immunohistochemical labels. Samples were split into two sets. These neuroanatomical markers provide well characterized neuroanatomical landmarks to interpret the location of GFP expression. The protocol followed was the same as that employed to prepare samples for zebrafishbrain.

The second set called in situ test was used to perform wholemount fluorescent in situ hybridization using DIG-labelled probes and tyramide detection according to the protocol of Lauter et al. Both the sets of samples were examined using confocal microscopy from a dorsal and lateral aspect eye removed. Stacks were examined in 3D using Fiji software for neuroanatomical location and overlap between native gene expression and GFP expression.

Frequently the in situ test set showed poor expression data for the in situ hybridization channel. For these sets, in situ hybridization was carried out on wild-type AB embryos using chromogenic detection of DIG-labelled probes according the standard protocol of the Thisse laboratory Expression could then be compared between this sample and the neuroanatomical test sample.

Output data took the form of text annotations of the neuroanatomical locations of GFP expression and its comparison with native zebrafish gene expression. Only sets comprising at least 10 CNEs sets in total were searched for possible motif enrichment. Motifs were detected using MEME3 ref. A threshold score characterizing each motif is then defined as the lowest weight obtained while matching the motif against each of its constitutive sequences, using the matrix-scan program of the RSATools suite This score will be used to seek the motif in other control CNE sets.

This program thus determined the frequencies of every possible dinucleotide in the total set of CNEs, and used these as background frequencies to compute the significance of observed motifs. Two statistical tests are further applied to eliminate motifs that may be due to chance occurrence. The first test consists in calculating a P value associated to the number of motif hits observed in the CNE set, by searching the motif in 1, random sets comprising the same number of CNEs, using matrix-scan and the weight threshold value previously computed.

This P value reflects the number of times an equal or higher number of motif occurrences are found by chance, compared with the set of CNEs predicted to target the same gene. The second test consists in the search for motifs in the same CNE set but using shuffled motifs. We computed the proportion of CNEs that match known motifs, as a function of increasing evolutionary linkage score to a neighbouring gene similar to Fig.

Matches between CNEs and matrices of known motifs were identified using the matrix-scan program from RSAT 36 , with the background as described above and with the following parameters: -1str —lth score 5. A full description of motifs shown in Fig. How to cite this article: Naville, M.


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