Epigenetics & ChromatinBioinformaticsPeer-reviewed journal article
Genome-wide Search for Zelda-like Chromatin Signatures Identifies GAF as a Pioneer Factor in Early Fly Development
Abstract
MotivationThe protein Zelda was shown to play a key role in early Drosophila development, binding thousands of promoters and enhancers prior to maternal-to-zygotic transition (MZT), and marking them for transcriptional activation. Recently, we showed that Zelda acts through specific chromatin patterns of histone modifications to mark developmental enhancers and active promoters. Intriguingly, some Zelda sites still maintain these chromatin patterns in Drosophila embryos lacking maternal Zelda protein. This suggests that additional Zelda-like pioneer factors may act in early fly embryos.\n\nResultsWe developed a computational method to analyze and refine the chromatin landscape surrounding early Zelda peaks, using a multi-channel spectral clustering. This allowed us to characterize their chromatin patterns through MZT (mitotic cycles 8-14). Specifically, we focused on H3K4me1, H3K4me3, H3K18ac, H3K27ac, and H3K27me3 and identified three different classes of chromatin signatures, matching \"promoters\", \"enhancers\" and \"transiently bound\" Zelda peaks.\n\nWe then further scanned the genome using these chromatin patterns and identified additional loci - with no Zelda binding - that show similar chromatin patterns, resulting with hundreds of Zelda-independent putative enhancers. These regions were found to be enriched with GAGA factor (GAF, Trl), and are typically located near early developmental zygotic genes. Overall our analysis suggests that GAF, together with Zelda, plays an important role in activating the zygotic genome.\n\nAs we show, our computational approach offers an efficient algorithm for characterizing chromatin signatures around some loci of interest, and allows a genome-wide identification of additional loci with similar chromatin patterns.\n\nContact: tommy@cs.huji.ac.il
- organism: Drosophila
- assay: ChIP-seq
- research focus: gene regulatory network inference
- research focus: differential expression
- research focus: database / resource
- approach: statistical model
- Citations
- 27
- FWCI
- 0.89
- Field percentile
- top 28%
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