Chromatin profiling data indicate regulatory mechanisms for differentiation during development in the acoel Hofstenia miamia
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Abstract
Chromatin profiling data can corroborate and generate hypotheses for regulatory events that underlie the control of gene expression in any biological process. Here, we applied the Assay for Transposase Accessible Chromatin (ATAC) sequencing to build a catalog of putative regulatory DNA during the process of embryonic development in an acoel. Acoels represent an enigmatic phylum-level lineage of animals, the Xenacoelomorpha, which is placed either as a sister-group to all other animals with bilateral symmetry or as an early-diverging ambulacrarian, two alternative phylogenetic placements that both position acoels equally well to inform the evolution of developmental mechanisms. We focused on the acoel Hofstenia miamia , a.k.a. the three-banded panther worm, which has emerged as a new laboratory research organism for whole-body regeneration that also enables the study of development from zygote to hatching. We profiled chromatin landscapes over a time course encompassing many major morphological events, including gastrulation, axial patterning, and differentiation of tissues such as epidermis and muscle. Broad patterns of chromatin accessibility and predicted binding of various transcription factor (TF) motifs identified major biological processes and their putative regulators, and we noted that differential accessibility tended to precede major developmental transitions in embryogenesis. Focused analysis of TF binding combined with single-cell RNA-seq data provided regulatory linkages for genes in a previously hypothesized differentiation trajectory for epidermis and generated new hypotheses for gene regulatory networks associated with the formation of muscle. This work provides a platform for the identification of developmental mechanisms in Hofstenia and enables comparisons of embryogenesis in acoels to other animals as well as comparisons of embryogenesis to regeneration.
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In this manuscript, the authors generate a developmental timecourse of ATAC-Seq data for the acoel worm Hofstenia miamia. The authors use a variety of computational approaches to characterize the position and function of regulatory elements, identify clusters of regulatory elements with similar accessibility trajectories over time, and predict relationships between transcription factor binding and gene expression.
The authors test their predictions by identifying a hierarchy of predicted binding sites in the muscle lineage based on scRNA-seq data and confirming that genes predicted to be bound by transcription factors expressed in the muscle lineage are expressed in tropomyosin+ cells, suggesting that TF binding predictions can be used to identify lineage-specific genes.
The data and resources generated by this manuscript will be useful …
In this manuscript, the authors generate a developmental timecourse of ATAC-Seq data for the acoel worm Hofstenia miamia. The authors use a variety of computational approaches to characterize the position and function of regulatory elements, identify clusters of regulatory elements with similar accessibility trajectories over time, and predict relationships between transcription factor binding and gene expression.
The authors test their predictions by identifying a hierarchy of predicted binding sites in the muscle lineage based on scRNA-seq data and confirming that genes predicted to be bound by transcription factors expressed in the muscle lineage are expressed in tropomyosin+ cells, suggesting that TF binding predictions can be used to identify lineage-specific genes.
The data and resources generated by this manuscript will be useful to both the community of researchers working on this specific organism, as well as scientists interested in performing cross-species analyses on gene regulatory evolution.
It would be interesting to know whether previously identified regulatory elements/ transgenic drivers in Hofstenia are also identified by ATAC-Seq, and whether the authors were able to use ATAC-Seq peaks to develop new reporters in Hofstenia.
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(I) ATACseq peak-accessibility and corresponding RNA expression of transcription factors and differentiated markers of muscle. Abbreviations are EP (Early Pooled), PH (Prehatchling), PPH (Pigmented Prehatchling).
I think this should say "H"? The temporal relationship might be a bit more legible if the RNA-Seq and peak accessibility heatmaps were stacked vertically rather than placed side-by-side.
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Thus, to better understand the downstream roles of these transcription factors in muscle specification, we considered other genes that were bound by motifs predicted to be associated with these transcripts (ZIC4, PITX1, and FOX).
It's cool to see that stepping along the hierarchy of predicted binding can actually lead to accurate predictions of gene expression!
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tropomyosin gene expression (purple)
labels in the figure image say "tropopyosin" rather than "tropomyosin"
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(F) Accessibility of the dlx gene locus with candidate RUNT binding sites. URD tree with expression of dlx, epidermal lineage is boxed. (G) Accessibility of the sox4 gene locus with candidate RUNT binding sites. URD tree with expression of sox4, neural lineage is boxed. (I) Accessibility of the foxA gene locus with candidate RUNT binding sites. URD tree with expression of foxA, gut/endodermal lineage is boxed. (H) Accessibility of the zic3 gene locus with candidate RUNT binding sites. URD tree with expression of zic3, muscle lineage is boxed
Is it possible to visualize the footprints generated by TOBIAS for each timepoint which are likely to match the RUNT binding site at these loci? That might make it easier to evaluate whether RUNT binding is correlated with accessibility.
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We considered genes to be 1:1 with a motif if they occurred as a single copy and could be assigned to one motif.
How well-conserved are the DNA binding domains of the Hofstenia hits for JASPAR TFs? I'm curious whether you'd expect the motifs to be comparable over large evolutionary distances – from my understanding, JASPAR motifs tend to be enriched for arthropod and vertebrate TFs.
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ion, sodium, and calcium transport, indicating that membrane transport processes could play important roles early in Hofstenia development.
It appears that many of the GO functions reported are higher-level biological functions; were there any more granular terms that showed up as significant in your analysis?
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fuzzifier value m
Is there a specific value for this parameter that might be missing?
It might be helpful, if available, to share the cluster number ranges you tried to provide more clarity into the range of possible clustering outcomes.
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asked how these proportions of accessible regions change across development
I'd be curious to know about the distribution of distances between promoter peaks and nearby intergenic peaks. Are putative regulatory regions mostly proximal to promoters, or are there lots of distal regulatory elements as well?
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Principle
"principal"
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