GC content or sequences that are only overrepresented in certain
gene regions.
Often motif enrichment tools will detect more than one
enriched sequence and users have to identify the relevant motifs
of interest. To that end, both MEME and HOMER supply a
statistical p-value, which can be used as a criterium to select
enriched motifs. Additional considerations could include the number of times a sequence has been detected, which mRNAs contain
the motif, the degeneracy of the sequence, as well as any other
biological context. While http://homer.ucsd.edu/homer/
AUUUGCU
AUUUGCA
CCCAUAAUCCUA
CCCAUAAUCCUA
UUUUGCA
AUUUGCU
MOTIF ENRICHMENT ANALYSIS
AUUUGCU
AUUUGCU
UUUUGCA
AUUUGCA
CCCAUAAUCCUA
CCCAUAAUCCUA
CCCCUUAUCCUA
CCCCUUAUCCUA
DESIGN PROBES
WUUUGCWNNNNWUUGCW
CCCWUWAUCCUANNNCCCWUWAUCCUA
MOTIF1
MOTIF2
PROBE1
PROBE2
Considerations for selecting motifs:
-type of mRNA
-p-value
-number of occurences
-degeneracy of the motif
-other biological information
Fig. 2 Identifying enriched motifs and designing RNA probes. Motif enrichment
tools can identify overrepresented sequence motifs present in a collection of
sequences such as putative RBP-binding sites. Users can elect motifs based on
several criteria and generate RNA probes. For RNA sequence motifs <20
nucleotides in length, the sequence should be duplicated and separated by
several random nucleotides to minimize the possibility of proteins binding and
occluding the site through chance
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Mengge Shan and Brian D. Gregory