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A combinatorial cis-regulatory logic restricts color-sensing Rhodopsins to specific photoreceptor subsets in Drosophila.

ABSTRACT: Color vision in Drosophila melanogaster is based on the expression of five different color-sensing Rhodopsin proteins in distinct subtypes of photoreceptor neurons. Promoter regions of less than 300 base pairs are sufficient to reproduce the unique, photoreceptor subtype-specific rhodopsin expression patterns. The underlying cis-regulatory logic remains poorly understood, but it has been proposed that the rhodopsin promoters have a bipartite structure: the distal promoter region directs the highly restricted expression in a specific photoreceptor subtype, while the proximal core promoter region provides general activation in all photoreceptors. Here, we investigate whether the rhodopsin promoters exhibit a strict specialization of their distal (subtype specificity) and proximal (general activation) promoter regions, or if both promoter regions contribute to generating the photoreceptor subtype-specific expression pattern. To distinguish between these two models, we analyze the expression patterns of a set of hybrid promoters that combine the distal promoter region of one rhodopsin with the proximal core promoter region of another rhodopsin. We find that the function of the proximal core promoter regions extends beyond providing general activation: these regions play a previously underappreciated role in generating the non-overlapping expression patterns of the different rhodopsins. Therefore, cis-regulatory motifs in both the distal and the proximal core promoter regions recruit transcription factors that generate the unique rhodopsin patterns in a combinatorial manner. We compare this combinatorial regulatory logic to the regulatory logic of olfactory receptor genes and discuss potential implications for the evolution of rhodopsins.

SUBMITTER: Poupault C

PROVIDER: S-EPMC8259978 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundA major goal of computational studies of gene regulation is to accurately predict the expression of genes based on the cis-regulatory content of their promoters. The development of computational methods to decode the interactions among cis-regulatory elements has been slow, in part, because it is difficult to know, without extensive experimental validation, whether a particular method identifies the correct cis-regulatory interactions that underlie a given set of expression data. There is an urgent need for test expression data in which the interactions among cis-regulatory sites that produce the data are known. The ability to rapidly generate such data sets would facilitate the development and comparison of computational methods that predict gene expression patterns from promoter sequence.ResultsWe developed a gene expression simulator which generates expression data using user-defined interactions between cis-regulatory sites. The simulator can incorporate additive, cooperative, competitive, and synergistic interactions between regulatory elements. Constraints on the spacing, distance, and orientation of regulatory elements and their interactions may also be defined and Gaussian noise can be added to the expression values. The simulator allows for a data transformation that simulates the sigmoid shape of expression levels from real promoters. We found good agreement between sets of simulated promoters and predicted regulatory modules from real expression data. We present several data sets that may be useful for testing new methodologies for predicting gene expression from promoter sequence.ConclusionWe developed a flexible gene expression simulator that rapidly generates large numbers of simulated promoters and their corresponding transcriptional output based on specified interactions between cis-regulatory sites. When appropriate rule sets are used, the data generated by our simulator faithfully reproduces experimentally derived data sets. We anticipate that using simulated gene expression data sets will facilitate the direct comparison of computational strategies to predict gene expression from promoter sequence. The source code is available online and as additional material. The test sets are available as additional material.

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A combinatorial cis-regulatory logic restricts color-sensing Rhodopsins to specific photoreceptor subsets in Drosophila.

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