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BACKGROUND: The developmental gene regulatory network (GRN) that underlies skeletogenesis in sea urchins and other echinoderms is a paradigm of GRN structure, function, and evolution. This transcriptional network is deployed selectively in skeleton-forming primary mesenchyme cells (PMCs) of the early embryo. To advance our understanding of this model developmental GRN, we used genome-wide chromatin accessibility profiling to identify and characterize PMC cis-regulatory modules (CRMs).
RESULTS: ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) analysis of purified PMCs provided a global picture of chromatin accessibility in these cells. We used both ATAC-seq and DNase-seq (DNase I hypersensitive site sequencing) to identify > 3000 sites that exhibited increased accessibility in PMCs relative to other embryonic cell lineages, and provide both computational and experimental evidence that a large fraction of these sites represent bona fide skeletogenic CRMs. Putative PMC CRMs were preferentially located near genes differentially expressed by PMCs and consensus binding sites for two key transcription factors in the PMC GRN, Alx1 and Ets1, were enriched in these CRMs. Moreover, a high proportion of candidate CRMs drove reporter gene expression specifically in PMCs in transgenic embryos. Surprisingly, we found that PMC CRMs were partially open in other embryonic lineages and exhibited hyperaccessibility as early as the 128-cell stage.
CONCLUSIONS: Our work provides a comprehensive picture of chromatin accessibility in an early embryonic cell lineage. By identifying thousands of candidate PMC CRMs, we significantly enhance the utility of the sea urchin skeletogenic network as a general model of GRN architecture and evolution. Our work also shows that differential chromatin accessibility, which has been used for the high-throughput identification of enhancers in differentiated cell types, is a powerful approach for the identification of CRMs in early embryonic cells. Lastly, we conclude that in the sea urchin embryo, CRMs that control the cell type-specific expression of effector genes are hyperaccessible several hours in advance of gene activation.
Fig. 1. ATAC-seq sample preparation and sequence analysis. a
S. purpuratus embryos were cultured for 24 h at 15 °C in triplicate. PMCs and other cells were isolated and ATAC-seq libraries were generated and sequenced. Sequence reads were analyzed by the bioinformatics pipeline shown in Additional file 1: Fig. S1A. b Examples of ATAC-seq differential peaks. These differential peaks (yellow rectangles) are located near the Sp-kirrelL gene, which encodes a transmembrane protein required for PMC fusion [27]. The aligned reads for each replicate are visualized, and the difference in peak magnitudes can be seen when comparing differential peaks in the isolated PMC replicates (light green peak trace) to the other cell replicates (dark green trace). Nominal p-values for differential peaks are indicated. c The distribution of ATAC-seq peaks in the RPS with respect to the closest gene. See Methods for definitions of peak locations. d Distribution of ATAC-seq differential peaks with respect to the closest gene
Fig. 2. DNase-seq sample preparation and sequence analysis. a
S. purpuratus embryos were treated with U0126 at the 2-cell stage to obtain PMC (â) embryos. Control and U0126-treated embryos were cultured for 28 h at 15 °C in triplicate. Nuclei were isolated and DNase-seq was carried out. Sequence reads were analyzed by the bioinformatics pipeline shown in Additional file 1: Figure S1A. b An example of DNase-seq differential peaks. The differential peaks (yellow rectangles) are located near the WHL22.245306 transcript. The aligned reads for each replicate are visualized as traces, and the differences in peak magnitude are clear when comparing control whole embryos (violet peak trace) to PMC(â) embryos (dark purple trace). Nominal p-values for differential peaks are indicated. c Distribution of DNase-seq peaks in the RPS with respect to the closest gene. See Methods for definitions of peak locations. d Distribution of DNase-seq differential peaks with respect to the closest gene
Fig. 3. Previously analyzed PMC-specific cis-regulatory modules. Previously analyzed cis-regulatory modules (CRMs) (orange and yellow rectangles) that control the spatio-temporal expression of four PMC DE genes are represented in both ATAC-seq (light green trace: isolated PMCs; dark green trace: other cells) and DNase-seq (violet trace: control whole embryos, purple trace: U0126-treated embryos) datasets. a
Sp-alx1 cis-regulatory modules are not represented as differential peaks in the ATAC-seq or DNase-seq datasets. b The Sp-sm50 enhancer (orange rectangle) and the minimal element (yellow rectangle) required for correct spatio-temporal expression of Sp-sm50 are encompassed within a differential peak identified in the DNase-seq dataset (violet rectangle), but not identified as differential in the ATAC-seq dataset. c The Sp-sm30a enhancer overlaps a differential peak identified in the ATAC- seq dataset (light green), but is not identified as differential in the DNase-seq dataset. d Two of four previously studied Sp-tbr cis-regulatory modules overlap 2 differential peaks in the ATAC-seq (light green) dataset and 1 differential peak in the DNase-seq (violet) dataset
Fig. 4. Experimental validation of putative PMC CRMs. a The EpGFPII reporter construct: Of a total of 3073 PMC-enriched differential peaks identified using DNase-seq and ATAC-seq, 31 were cloned into the EpGFPII plasmid, upstream of the GFP coding sequence and the Sp-endo16 promoter, and injected into S. purpuratus eggs. b Representative images of S. purpuratus embryos injected with 7 reporter constructs, showing PMC-specific GFP expression (green fluorescence) at 48 hpf. DIC and Sp-kirrelL images show the same embryo; arrows indicate PMCs
Fig. 5. Computational analysis of high-confidence PMC CRMs. a ATAC-seq differential peaks (green rectangles) and DNase-seq differential peaks (violet rectangles) near Sp-p16 and Sp-mitf, both PMC DE genes. Aligned reads averaged across replicates, from isolated PMCs (light green trace) and non-PMC cells (dark green trace) using ATAC-seq, and control 28 hpf embryos (violet trace) and PMC (â) embryos (dark purple trace) using DNase-seq, are shown. b Temporal expression profiles (Tu et al., 2012) of 420 PMC DE genes identified previously (Rafiq et al., 2014). Each gene is represented by a single row. The color scale ranges from deep red (2.5-fold higher than mean expression) to deep blue (2.5-fold lower than mean expression). White indicates mean expression. Four clusters are delineated, corresponding to maximal gene expression at 0â10, 40â72, 24â40 and 18â24 hpf, respectively. c Temporal expression of the 62 PMC DE genes within 10Â kb of overlapping differential peaks: these PMC DE genes were classified into four clusters, delineated in Fig. 3b. d PMC DE genes were classified into categories based on levels of gene expression in isolated PMCs (data obtained from (Rafiq et al., 2014). âHighâ expression genes: FPKM between 2512 and 100 (top 17% of all 420 DE genes); âvery lowâ expression genes: FPKM between 14 and 0 (bottom 25% of all 420 DE genes)
Fig. 6. Examples of overlapping differential peaks accessible at the 128-cell stage. Overlapping differential peaks (yellow rectangles) around the Sp-msp130r gene are accessible at the 128-cell stage (red rectangles represent peaks called at the 128- cell stage). Hypersensitivity corresponding to the overlapping differential peaks is seen at the 128-cell stage (red trace), the 24 hpf stage isolated PMCs (light green trace) and other non-PMC cells (dark green trace), and control 28 hpf embryos (violet trace) and PMC (â) embryos (dark purple trace)
Adkins,
GAGA protein: a multi-faceted transcription factor.
2006, Pubmed
Adkins,
GAGA protein: a multi-faceted transcription factor.
2006,
Pubmed Adomako-Ankomah,
Growth factor-mediated mesodermal cell guidance and skeletogenesis during sea urchin gastrulation.
2013,
Pubmed
,
Echinobase Adomako-Ankomah,
P58-A and P58-B: novel proteins that mediate skeletogenesis in the sea urchin embryo.
2011,
Pubmed
,
Echinobase Akasaka,
Genomic organization of a gene encoding the spicule matrix protein SM30 in the sea urchin Strongylocentrotus purpuratus.
1994,
Pubmed
,
Echinobase Anders,
HTSeq--a Python framework to work with high-throughput sequencing data.
2015,
Pubmed Arnone,
Using reporter genes to study cis-regulatory elements.
2004,
Pubmed
,
Echinobase Bailey,
The MEME Suite.
2015,
Pubmed Bailey,
MEME SUITE: tools for motif discovery and searching.
2009,
Pubmed Barsi,
General approach for in vivo recovery of cell type-specific effector gene sets.
2014,
Pubmed
,
Echinobase Berger,
Evolution goes GAGA: GAGA binding proteins across kingdoms.
2012,
Pubmed Boyle,
F-Seq: a feature density estimator for high-throughput sequence tags.
2008,
Pubmed Buecker,
Enhancers as information integration hubs in development: lessons from genomics.
2012,
Pubmed Buenrostro,
ATAC-seq: A Method for Assaying Chromatin Accessibility Genome-Wide.
2015,
Pubmed Cameron,
cis-Regulatory activity of randomly chosen genomic fragments from the sea urchin.
2004,
Pubmed
,
Echinobase Cameron,
SpBase: the sea urchin genome database and web site.
2009,
Pubmed
,
Echinobase Cary,
Echinoderm development and evolution in the post-genomic era.
2017,
Pubmed
,
Echinobase Cheers,
P16 is an essential regulator of skeletogenesis in the sea urchin embryo.
2005,
Pubmed
,
Echinobase Coffman,
Identification of sequence-specific DNA binding proteins.
2004,
Pubmed
,
Echinobase Crawford,
Genome-wide mapping of DNase hypersensitive sites using massively parallel signature sequencing (MPSS).
2006,
Pubmed Damle,
Precise cis-regulatory control of spatial and temporal expression of the alx-1 gene in the skeletogenic lineage of s. purpuratus.
2011,
Pubmed
,
Echinobase Duloquin,
Localized VEGF signaling from ectoderm to mesenchyme cells controls morphogenesis of the sea urchin embryo skeleton.
2007,
Pubmed
,
Echinobase Ernst,
Mapping and analysis of chromatin state dynamics in nine human cell types.
2011,
Pubmed Ettensohn,
Encoding anatomy: developmental gene regulatory networks and morphogenesis.
2013,
Pubmed
,
Echinobase Ettensohn,
Alx1, a member of the Cart1/Alx3/Alx4 subfamily of Paired-class homeodomain proteins, is an essential component of the gene network controlling skeletogenic fate specification in the sea urchin embryo.
2003,
Pubmed
,
Echinobase Ettensohn,
KirrelL, a member of the Ig-domain superfamily of adhesion proteins, is essential for fusion of primary mesenchyme cells in the sea urchin embryo.
2017,
Pubmed
,
Echinobase Ettensohn,
Cell lineage conversion in the sea urchin embryo.
1988,
Pubmed
,
Echinobase Fernandez-Serra,
Role of the ERK-mediated signaling pathway in mesenchyme formation and differentiation in the sea urchin embryo.
2004,
Pubmed
,
Echinobase Grant,
FIMO: scanning for occurrences of a given motif.
2011,
Pubmed Guay,
Single embryo-resolution quantitative analysis of reporters permits multiplex spatial cis-regulatory analysis.
2017,
Pubmed
,
Echinobase Harkey,
Isolation, culture, and differentiation of echinoid primary mesenchyme cells.
1980,
Pubmed
,
Echinobase Hart,
Functional Consequences of Phenotypic Plasticity in Echinoid Larvae.
1994,
Pubmed
,
Echinobase Ingersoll,
Matrix metalloproteinase inhibitors disrupt spicule formation by primary mesenchyme cells in the sea urchin embryo.
1998,
Pubmed
,
Echinobase John,
Genome-scale mapping of DNase I hypersensitivity.
2013,
Pubmed Koga,
The echinoderm larval skeleton as a possible model system for experimental evolutionary biology.
2014,
Pubmed
,
Echinobase Koohy,
A comparison of peak callers used for DNase-Seq data.
2014,
Pubmed Kurokawa,
HpEts, an ets-related transcription factor implicated in primary mesenchyme cell differentiation in the sea urchin embryo.
1999,
Pubmed
,
Echinobase Langmead,
Fast gapped-read alignment with Bowtie 2.
2012,
Pubmed Li,
The Sequence Alignment/Map format and SAMtools.
2009,
Pubmed Livingston,
A genome-wide analysis of biomineralization-related proteins in the sea urchin Strongylocentrotus purpuratus.
2006,
Pubmed
,
Echinobase Logan,
Nuclear beta-catenin is required to specify vegetal cell fates in the sea urchin embryo.
1999,
Pubmed
,
Echinobase Love,
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2.
2014,
Pubmed Lyons,
Morphogenesis in sea urchin embryos: linking cellular events to gene regulatory network states.
2012,
Pubmed
,
Echinobase Makabe,
Cis-regulatory control of the SM50 gene, an early marker of skeletogenic lineage specification in the sea urchin embryo.
1995,
Pubmed
,
Echinobase McClay,
Sea Urchin Morphogenesis.
2016,
Pubmed
,
Echinobase McClay,
Regulative capacity of the archenteron during gastrulation in the sea urchin.
1996,
Pubmed
,
Echinobase McLeay,
Motif Enrichment Analysis: a unified framework and an evaluation on ChIP data.
2010,
Pubmed Mitsunaga,
Carbonic anhydrase activity in developing sea urchin embryos with special reference to calcification of spicules.
1986,
Pubmed
,
Echinobase Nam,
Barcoded DNA-tag reporters for multiplex cis-regulatory analysis.
2012,
Pubmed
,
Echinobase Natarajan,
Predicting cell-type-specific gene expression from regions of open chromatin.
2012,
Pubmed Neph,
BEDOPS: high-performance genomic feature operations.
2012,
Pubmed Oliveri,
A regulatory gene network that directs micromere specification in the sea urchin embryo.
2002,
Pubmed
,
Echinobase Oliveri,
Global regulatory logic for specification of an embryonic cell lineage.
2008,
Pubmed
,
Echinobase Pearson,
Chromatin profiling of Drosophila CNS subpopulations identifies active transcriptional enhancers.
2016,
Pubmed Peled-Kamar,
Spicule matrix protein LSM34 is essential for biomineralization of the sea urchin spicule.
2002,
Pubmed
,
Echinobase Pennington,
Consequences of the Calcite Skeletons of Planktonic Echinoderm Larvae for Orientation, Swimming, and Shape.
1990,
Pubmed Peter,
Implications of Developmental Gene Regulatory Networks Inside and Outside Developmental Biology.
2016,
Pubmed Quinlan,
BEDTools: a flexible suite of utilities for comparing genomic features.
2010,
Pubmed Rafiq,
Genome-wide analysis of the skeletogenic gene regulatory network of sea urchins.
2014,
Pubmed
,
Echinobase Rafiq,
The genomic regulatory control of skeletal morphogenesis in the sea urchin.
2012,
Pubmed
,
Echinobase Ramírez,
deepTools: a flexible platform for exploring deep-sequencing data.
2014,
Pubmed Revilla-i-Domingo,
A missing link in the sea urchin embryo gene regulatory network: hesC and the double-negative specification of micromeres.
2007,
Pubmed
,
Echinobase Roe,
Inhibitors of metalloendoproteases block spiculogenesis in sea urchin primary mesenchyme cells.
1989,
Pubmed
,
Echinobase Röttinger,
A Raf/MEK/ERK signaling pathway is required for development of the sea urchin embryo micromere lineage through phosphorylation of the transcription factor Ets.
2004,
Pubmed
,
Echinobase Sharma,
Regulative deployment of the skeletogenic gene regulatory network during sea urchin development.
2011,
Pubmed
,
Echinobase Sharma,
Activation of the skeletogenic gene regulatory network in the early sea urchin embryo.
2010,
Pubmed
,
Echinobase Sodergren,
The genome of the sea urchin Strongylocentrotus purpuratus.
2006,
Pubmed
,
Echinobase Song,
Open chromatin defined by DNaseI and FAIRE identifies regulatory elements that shape cell-type identity.
2011,
Pubmed Sun,
TGF-β sensu stricto signaling regulates skeletal morphogenesis in the sea urchin embryo.
2017,
Pubmed
,
Echinobase Thurman,
The accessible chromatin landscape of the human genome.
2012,
Pubmed Tu,
Gene structure in the sea urchin Strongylocentrotus purpuratus based on transcriptome analysis.
2012,
Pubmed
,
Echinobase Tu,
Quantitative developmental transcriptomes of the sea urchin Strongylocentrotus purpuratus.
2014,
Pubmed
,
Echinobase Wahl,
The cis-regulatory system of the tbrain gene: Alternative use of multiple modules to promote skeletogenic expression in the sea urchin embryo.
2009,
Pubmed
,
Echinobase Weitzel,
Differential stability of beta-catenin along the animal-vegetal axis of the sea urchin embryo mediated by dishevelled.
2004,
Pubmed
,
Echinobase Wilken,
DNase I hypersensitivity analysis of the mouse brain and retina identifies region-specific regulatory elements.
2015,
Pubmed Wu,
Ingression of primary mesenchyme cells of the sea urchin embryo: a precisely timed epithelial mesenchymal transition.
2007,
Pubmed
,
Echinobase Xiong,
Comprehensive characterization of erythroid-specific enhancers in the genomic regions of human Krüppel-like factors.
2013,
Pubmed Xu,
Transcriptional competence and the active marking of tissue-specific enhancers by defined transcription factors in embryonic and induced pluripotent stem cells.
2009,
Pubmed Yamasu,
Functional organization of DNA elements regulating SM30alpha, a spicule matrix gene of sea urchin embryos.
1999,
Pubmed
,
Echinobase Yamazaki,
The micro1 gene is necessary and sufficient for micromere differentiation and mid/hindgut-inducing activity in the sea urchin embryo.
2005,
Pubmed
,
Echinobase Yuh,
Genomic cis-regulatory logic: experimental and computational analysis of a sea urchin gene.
1998,
Pubmed
,
Echinobase Yuh,
Patchy interspecific sequence similarities efficiently identify positive cis-regulatory elements in the sea urchin.
2002,
Pubmed
,
Echinobase Zaret,
Pioneer transcription factors: establishing competence for gene expression.
2011,
Pubmed