A large-scale, in vivo transcription factor screen defines bivalent chromatin as a key property of regulatory factors mediating Drosophila wing development

Abstract

Transcription factors (TFs) are key regulators of cell fate. The estimated 755 genes that encode DNA binding domain-containing proteins comprise ∼ 5% of all Drosophila genes. However, the majority has remained uncharacterized so far due to the lack of proper genetic tools. We generated 594 site-directed transgenic Drosophila lines that contain integrations of individual UAS-TF constructs to facilitate spatiotemporally controlled misexpression in vivo. All transgenes were expressed in the developing wing, and two-thirds induced specific phenotypic defects. In vivo knockdown of the same genes yielded a phenotype for 50%, with both methods indicating a great potential for misexpression to characterize novel functions in wing growth, patterning, and development. Thus, our UAS-TF library provides an important addition to the genetic toolbox of Drosophila research, enabling the identification of several novel wing development-related TFs. In parallel, we established the chromatin landscape of wing imaginal discs by ChIP-seq analyses of five chromatin marks and RNA Pol II. Subsequent clustering revealed six distinct chromatin states, with two clusters showing enrichment for both active and repressive marks. TFs that carry such "bivalent" chromatin are highly enriched for causing misexpression phenotypes in the wing, and analysis of existing expression data shows that these TFs tend to be differentially expressed across the wing disc. Thus, bivalently marked chromatin can be used as a marker for spatially regulated TFs that are functionally relevant in a developing tissue.

Figure 1.

Phenotypic analysis of the TF library by MS1096-Gal4–driven expression in the developing wing. Phenotypes upon misexpression by MS1096-Gal4 (black bars) are compared to RNAi knockdown (gray bars) and two other misexpressed gene sets: cell cycle regulators (white bars) and miRNAs (green bars). Phenotypic strength was recorded from no effect, weak growth, or patterning defects (+) to severe size or patterning defects (++), almost complete absence of wings (+++) to lethality (lethal); bars show the distribution of observed phenotypes for each data set. Representative examples for the phenotypes (+ to +++) are shown. Arrowheads point to patterning defects.

Figure 2.

Characteristics of phenotype-inducing TFs. (A) The misexpression phenotype distributions of TFs belonging to specific RNA Pol II occupancy bins (from the lowest to the highest 20% RNA Pol II occupancy) are compared. RNA Pol II DNA occupancy was used here as a proxy for the extent of TF expression. Grayscaling of the bars applies also to panel B. (B) Effects of overexpression are compared to those of RNAi-mediated knockdown. UAS-TF and UAS-RNAi were grouped into known genes with annotated names and uncharacterized genes that are only annotated by a CG number.

Figure 3.

The chromatin landscape of wing discs at the third instar larval stage. (A) Clustering of all detected genes according to the distribution of five histone marks and RNA Pol II as measured by ChIP-seq. Activating marks are indicated in green, repressive marks in red. The locations of the transcription start sites (TSSs) and the transcription end sites (TESs) are indicated by lines within each histone modification column. Previously published wing disc RNA-seq data (McKay and Lieb 2013) are also presented to directly link histone modification, RNA Pol II enrichment, and gene expression. (B) Representative examples for genes in clusters 4a, 4b, 5a, and 5b are shown (“a” reflects genes with low H3K27me3 enrichment, while genes in “b” reflect high enrichment of this mark). Gene loci are indicated at the bottom of the panels and the cluster number is listed at the top of the panels. The same molecular marks as in A are displayed. The scale for all tracks represents the tag depth per base pair, except for the RNA-seq data, for which the log₂ of (FPKM + 1) is plotted.

Figure 4.

Distribution of phenotypes induced by TFs in the different clusters. The chart illustrates the distribution of phenotypes caused by misexpression of all TFs and from each cluster (c1–c6, x-axis) by MS1096-Gal4 in the wing.