Atrophin controls developmental signaling pathways via interactions with Trithorax-like
Abstract
Mutations in human Atrophin1, a transcriptional corepressor, cause dentatorubral-pallidoluysian atrophy, a neurodegenerative disease. Drosophila Atrophin (Atro) mutants display many phenotypes, including neurodegeneration, segmentation, patterning and planar polarity defects. Despite Atro's critical role in development and disease, relatively little is known about Atro's binding partners and downstream targets. We present the first genomic analysis of Atro using ChIP-seq against endogenous Atro. ChIP-seq identified 1300 potential direct targets of Atro including engrailed, and components of the Dpp and Notch signaling pathways. We show Atro regulates Dpp and Notch signaling in larval imaginal discs, at least partially via regulation of thickveins and fringe. In addition, bioinformatics analyses, sequential ChIP and coimmunoprecipitation experiments reveal that Atro interacts with the Drosophila GAGA Factor, Trithorax-like (Trl), and they bind to the same loci simultaneously. Phenotypic analyses of Trl and Atro clones suggest that Atro is required to modulate the transcription activation by Trl in larval imaginal discs. Taken together these data indicate that Atro is a major Trl cofactor that functions to moderate developmental gene transcription.
Data availability
-
ChIP-seq of Atrophin in Drosophila S2 cellsPublicly available at the NCBI Gene (accession no: GSE87509).
-
Atrophin (Atro) ChIP-seq data from Drosophila S2 cellsPublicly available at the NCBI Gene (accession no: GSE87471).
-
Chromatin Binding Site Mapping of Transcription Factors in D. melanogaster by ChIP-seqPublicly available at Modencode (http://intermine.modencode.org).
-
Chromatin Binding Site MappingPublicly available at Modencode (http://intermine.modencode.org).
-
The Genomic Binding Profile of GAGA Element Associated Factor (GAF) in Drosophila S2 cellsPublicly available at the NCBI Gene Expression Omnibus (accession no: GSE40646).
Article and author information
Author details
Funding
Canadian Institutes of Health Research (FDN 143319)
- Helen McNeill
Medical Research Council (NIRG-G1002186)
- Manolis Fanto
Knut och Alice Wallenbergs Stiftelse
- Per Stenberg
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India
Version history
- Received: November 8, 2016
- Accepted: March 15, 2017
- Accepted Manuscript published: March 22, 2017 (version 1)
- Version of Record published: April 28, 2017 (version 2)
Copyright
© 2017, Yeung et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 1,428
- views
-
- 370
- downloads
-
- 14
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Further reading
-
- Computational and Systems Biology
- Developmental Biology
Organisms utilize gene regulatory networks (GRN) to make fate decisions, but the regulatory mechanisms of transcription factors (TF) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.
-
- Developmental Biology
- Evolutionary Biology
Despite rapid evolution across eutherian mammals, the X-linked MIR-506 family miRNAs are located in a region flanked by two highly conserved protein-coding genes (SLITRK2 and FMR1) on the X chromosome. Intriguingly, these miRNAs are predominantly expressed in the testis, suggesting a potential role in spermatogenesis and male fertility. Here, we report that the X-linked MIR-506 family miRNAs were derived from the MER91C DNA transposons. Selective inactivation of individual miRNAs or clusters caused no discernible defects, but simultaneous ablation of five clusters containing 19 members of the MIR-506 family led to reduced male fertility in mice. Despite normal sperm counts, motility, and morphology, the KO sperm were less competitive than wild-type sperm when subjected to a polyandrous mating scheme. Transcriptomic and bioinformatic analyses revealed that these X-linked MIR-506 family miRNAs, in addition to targeting a set of conserved genes, have more targets that are critical for spermatogenesis and embryonic development during evolution. Our data suggest that the MIR-506 family miRNAs function to enhance sperm competitiveness and reproductive fitness of the male by finetuning gene expression during spermatogenesis.