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Developmental Effector Gene Regulation: Multiplexed Strategies for Functional Analysis

Overview
Journal Dev Biol
Publisher Elsevier
Date 2018 Nov 6
PMID 30392838
Citations 1
Authors
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Abstract

The staggering complexity of the genome controls for developmental processes is revealed through massively parallel cis-regulatory analysis using new methods of perturbation and readout. The choice of combinations of these new methods is tailored to the system, question and resources at hand. Our focus is on issues that include the necessity or sufficiency of given cis-regulatory modules, cis-regulatory function in the normal spatial genomic context, and easily accessible high throughput and multiplexed analysis methods. In the sea urchin embryonic model, recombineered BACs offer new opportunities for consecutive modes of cis-regulatory analyses that answer these requirements, as we here demonstrate on a diverse suite of previously unstudied sea urchin effector genes expressed in skeletogenic cells. Positively active cis-regulatory modules were located in single Nanostring experiments per BAC containing the gene of interest, by application of our previously reported "barcode" tag vectors of which> 100 can be analyzed at one time. Computational analysis of DNA sequences that drive expression, based on the known skeletogenic regulatory state, then permitted effective identification of functional target site clusters. Deletion of these sub-regions from the parent BACs revealed module necessity, as simultaneous tests of the same regions in short constructs revealed sufficiency. Predicted functional inputs were then confirmed by site mutations, all generated and tested in multiplex formats. There emerged the simple conclusion that each effector gene utilizes a small subset of inputs from the skeletogenic GRN. These inputs may function to only adjust expression levels or in some cases necessary for expression. Since we know the GRN architecture upstream of the effector genes, we could then conceptually isolate and compare the wiring of the effector gene driver sub-circuits and identify the inputs whose removal abolish expression.

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