Abstract
BackgroundAccurate computational identification of cis-regulatory motifs is difficult, particularly in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors. Enrichment in combinations of rare motifs in the promoter sequence of functionally or evolutionarily related genes among several species is an indicator of conserved transcriptional regulatory mechanisms. This provides a basis for the computational identification of cis-regulatory motifs.ResultsWe have used a discriminative seeding DNA motif discovery algorithm for an in-depth analysis of 54 seed storage protein (SSP) gene promoters from three plant families, namely Brassicaceae (mustards), Fabaceae (legumes) and Poaceae (grasses) using backgrounds based on complete sets of promoters from a representative species in each family, namely Arabidopsis (Arabidopsis thaliana (L.) Heynh.), soybean (Glycine max (L.) Merr.) and rice (Oryza sativa L.) respectively. We have identified three conserved motifs (two RY-like and one ACGT-like) in Brassicaceae and Fabaceae SSP gene promoters that are similar to experimentally characterized seed-specific cis-regulatory elements. Fabaceae SSP gene promoter sequences are also enriched in a novel, seed-specific E2Fb-like motif. Conserved motifs identified in Poaceae SSP gene promoters include a GCN4-like motif, two prolamin-box-like motifs and an Skn-1-like motif. Evidence of the presence of a variant of the TATA-box is found in the SSP gene promoters from the three plant families. Motifs discovered in SSP gene promoters were used to score whole-genome sets of promoters from Arabidopsis, soybean and rice. The highest-scoring promoters are associated with genes coding for different subunits or precursors of seed storage proteins.ConclusionSeed storage protein gene promoter motifs are conserved in diverse species, and different plant families are characterized by a distinct combination of conserved motifs. The majority of discovered motifs match experimentally characterized cis-regulatory elements. These results provide a good starting point for further experimental analysis of plant seed-specific promoters and our methodology can be used to unravel more transcriptional regulatory mechanisms in plants and other eukaryotes.
Highlights
Accurate computational identification of cis-regulatory motifs is difficult, in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors
Discriminative seeding DNA motif discovery [7] was performed separately in each of the three plant families using a background model based on the complete set of promoters from a representative species, namely Arabidopsis (27,234 sequences), soybean (66,155 sequences) and rice (41,019 sequences)
Discovered motifs were matched to consensus sequences of experimentally characterized plant cis-regulatory elements from the PLACE database [5] using the STAMP suite of tools [22] (Table 1)
Summary
Accurate computational identification of cis-regulatory motifs is difficult, in eukaryotic promoters, which typically contain multiple short and degenerate DNA sequences bound by several interacting factors. Enrichment in combinations of rare motifs in the promoter sequence of functionally or evolutionarily related genes among several species is an indicator of conserved transcriptional regulatory mechanisms. This provides a basis for the computational identification of cis-regulatory motifs. The Seeder DNA motif discovery algorithm, designed for fast and reliable prediction of cis-regulatory elements in eukaryotic promoters, uses a string-based approach to identify motifs that are statistically significant (enriched) in a set of positive sequences as compared to a background set of sequences and it was recently shown to outperform some popular motif discovery tools on biological benchmark data [7]
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