Hox genes encode transcription factors (TFs) that establish morphological diversity in the developing embryo. The similar DNA-binding motifs of the various HOX TFs contrast with the wide-range of HOX-dependent genetic programs. The influence of the chromatin context on HOX binding specificity remains elusive. Here, we used the developing limb as a model system to compare the binding specificity of HOXA13 and HOXD13 (HOX13 hereafter), which are required for digit formation, and HOXA11, involved in forearm/leg development. We find that upon ectopic expression in distal limb buds, HOXA11 binds sites normally HOX13-specific. Importantly, these sites are loci whose chromatin accessibility relies on HOX13. Moreover, we show that chromatin accessibility specific to the distal limb requires HOX13 function. Based on these results, we propose that HOX13 TFs pioneer the distal limb-specific chromatin accessibility landscape for the proper implementation of the distal limb developmental program.
The differential expression of the Hox genes along the main axis of the developing embryo establishes positional information that instructs cells about their fate, ultimately generating morphological diversity1,2,3. Consequently, spatial or temporal deregulation of Hox genes can cause severe alterations of the body plan3. In most Vertebrates, Hox genes are grouped in four clusters, referred to as HoxA–D clusters. The coordinated regulation of the Hox genes is associated with their cluster organization, whereby the sequential activation of the Hox genes follows the gene order on the chromosome (groups 1–13). The wide-range of morphological features associated with the distinct HOX TFs contrasts with the similarity in their DNA-binding motifs4. Several studies uncovered the relevance of co-factors, notably the MEIS and PBX family of TFs, in increasing DNA-binding specificity4,5,6. Comparison of genome-wide binding of the HOXA and HOXD TFs relevant to limb development, assessed following retroviral infection of individual Hox gene in chicken mesenchymal limb bud cells, further substantiated the functional significance of co-factors in HOX-binding specificity7. Strikingly, principal component analysis of HOX DNA binding in this primary cell culture system also revealed that group 11 HOX TFs and HOXD13 cluster in the same subgroup7 despite the fact that HOXA11/HOXD11 are required for the zeugopod (forearm) developmental program8, while HOXA13 and HOXD13 are mandatory for digit development9 (Fig. 1a). Such apparent discrepancies between the binding profiles in micromass culture and the function of group 11 and 13 HOX TFs in the developing limb may be related to cell-type dependent DNA-binding specificity, as HOXA11 and HOX13 are expressed in distinct domains of the limb bud. Interestingly, Porcelli et al.10 by analyzing binding specificity of Drosophila HOX factors transfected in Kc167 cells, provided evidence that HOX factors vary in their capacity of binding chromatin in an inaccessible state. In turn, it suggests that cell type-specific differences in the chromatin accessibility landscape may change the genome-wide binding of HOX factors in a cell type-specific manner, at least for those HOX factors unable to bind inaccessible chromatin. More generally, it raises the question of the extent to which changes in the chromatin accessibility landscape modulate the target repertoire of the HOX TFs spatially/temporally during embryogenesis.
To address this question, we investigated the impact of cellular context on the genome-wide binding of HOXA11 and HOX13, which are normally expressed in mutually exclusive domains in the developing limb (Fig. 1a) but have highly similar homeodomain sequences (e.g., ref. 7; Fig. 1b). Our data reveal that the HOX13-specific targets, as compared to the HOXA11-binding repertoire, are loci bound by HOXA11 when HOXA11 is expressed in the HOX13 limb domain. This tissue-specific variation of the HOXA11 binding repertoire is associated with changes in the chromatin accessibility landscape triggered by HOX13. Importantly, our data reveal that the HOX13-dependent gain in accessibility at HOX13 targets corresponds to the gain in accessibility that accompanies the transition from proximal to distal limb.
HOXA11 binding varies in a tissue-specific manner
To investigate the impact of the cellular context on the target repertoire of HOXA11 and HOX13, we first analyzed the genome-wide binding of HOXA11 in wild-type limb buds at embryonic day 11.5 (E11.5), by performing chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) and compared the data with those previously reported for HOX13 (ref. 11) (Fig. 1c; Supplementary Fig. 2). Reminiscent of the distribution of HOX13-bound loci in distal limbs11, the vast majority of HOXA11 ChIP-seq peaks are located at genomic regions distinct from transcriptional start site (TSS; Supplementary Fig. 2h). While most peaks are common in both data sets, 23% of HOXA11 (i.e., 2128) or HOX13 (i.e., 2130) targets are located at distinct loci (Fig. 1c) and de novo motif search uncovered slight differences in HOX motifs for common vs. specific targets (Fig. 1d). We next tested whether the cellular environment could modulate the specificity distinguishing HOXA11 from HOX13-binding sites. To this aim, we analyzed HOXA11-binding profile in Prrx1:Cre;Rosa26Hoxa11/Hoxa11 limb buds in which Hoxa11 is ectopically expressed distally12 (R26A11d/A11d in Fig. 1e). We observed that the loci identified as HOX13-specific targets in the wild-type limb bud are bound by HOXA11 in R26A11d/A11d limb buds (Fig. 1f). This result suggested that the primary driver for the distinct HOXA11- and HOX13-binding profiles in wild-type limb buds is associated with their expression in distinct cell populations. To further assess whether this ectopic HOXA11 binding is due to the presence of HOX13 or triggered by other factors specific to distal limb cells, we took advantage of the Hox13−/− mutant9 in which Hoxa11 is distally expressed11,13,14. Analysis of HOXA11 genome-wide binding in Hox13−/− limbs revealed that the ectopic HOXA11 binding at HOX13 targets observed in R26A11d/A11d limbs were absent in Hox13−/− limbs (Fig. 1f, Supplementary Fig. 3a) while the wild-type HOXA11-binding pattern was unaffected (Supplementary Fig. 3b, c). This result indicated that the capacity of HOXA11 to bind new loci when expressed in the distal limb bud is dependent on HOX13 function.
HOX13 pioneer action expands HOXA11-binding repertoire
To assess whether chromatin accessibility may influence HOXA11 and HOX13 binding, we performed assay for transposase accessible chromatin followed by high-throughput sequencing (ATAC-seq15) on proximal and distal wild-type limb buds. We identified 1629 sites showing stronger accessibility in distal limb buds (Fig. 2a, Supplementary Fig. 4a). The prevalent motif associated with these sites is the previously identified HOX13 motif (Fig. 2b), while distinct motifs are found at proximal limb-enriched ATAC peaks (Supplementary Fig. 4b). Accordingly, HOX13 TFs bind distal limb-enriched accessible sites and not the proximal limb-specific accessible sites (Fig. 2c). Moreover, these distal limb sites tend to be associated with genes involved in digit morphogenesis, supporting their involvement in the distal limb program (Supplementary Fig. 4c–f). Previous analysis of HOX13-dependent gene regulation revealed that the transition from the early to the distal/late limb developmental program relies on HOX13 function and it was proposed that this switch in developmental program could be associated with a potential pioneer activity of the HOX13 TFs11. The finding that cellular environment modulates HOXA11 binding in a HOX13-dependent manner (Fig. 1) prompted us to test whether the ectopic HOXA11 binding at loci normally specifically bound by HOX13 could originate from changes in chromatin accessibility mediated by HOX13 TFs. We thus performed ATAC-seq on wild type and Hox13−/− distal limbs (Supplementary Fig. 5a) and identified substantial changes in chromatin accessibility (Fig. 2d). Interestingly, loci with decreased accessibility in Hox13−/− distal limbs were found primarily associated with a motif highly similar to the HOX13 motif (Fig. 2e) and were loci with distal limb-specific chromatin accessibility in the wild-type context, which for the vast majority were bound by HOX13 (Fig. 2f). In contrast, loci with increased accessibility in Hox13−/− distal limbs were poorly correlated with the HOX13 ChIP-seq peaks identified in the wild-type context, suggesting that this gain in chromatin accessibility is an indirect outcome of Hox13 inactivation (Supplementary Fig. 5b, c). Together, these data provide evidence that the gain of chromatin accessibility during the transition from proximal to distal limb is directly associated with HOX13 function. Moreover, we found that in R26A11d/A11d limb buds, the ectopic HOXA11 binding at sites which are HOX13-specific in wild-type limb buds, are loci for which chromatin accessibility relies on HOX13 (Fig. 2g–i). Importantly, this ectopic HOXA11 binding was lost in Hox13−/− limb buds (Fig. 1f), even though Hoxa11 is expressed in distal cells normally expressing Hox1313. Together, our results suggested that, in R26A11d/A11d limb buds, HOX13-dependent chromatin accessibility allows HOXA11 binding at loci that are HOX13-specific in the wild-type limb bud, i.e., in a context where Hox13 and Hoxa11 are expressed in mutually exclusive domains. These loci included several previously characterized distal limb enhancers. For instance, several enhancers controlling HoxD gene expression in distal limb16,17,18 were identified as loci with ectopic HOXA11 binding in R26A11d/A11d limb buds and with decreased accessibility in absence of HOX13 function (Fig. 2h). This HOX13-dependent chromatin accessibility is also consistent with the loss of transcriptional activity previously reported at these enhancers in Hox13−/− limbs11,19. Similarly, chromatin accessibility and HOXA11 binding dependent on HOX13 were observed at the enhancer driving Hoxa11 antisense transcription in distal limb (Fig. 2i), whose function is associated with digit patterning12.
Distal limb-specific chromatin accessibility requires HOX13
Next, we examined HOX13-dependent chromatin accessibility at the single-cell level to assess whether HOX13 pioneering action shows cell type specificity. To this aim, we performed single-cell ATAC-seq (scATAC-seq) using wild type and Hox13−/− E11.5 forelimb buds (Supplementary Fig. 6). Cell clustering was based on the similarity of their genome-wide chromatin accessibility and the resulting clusters (Fig. 3a) were annotated using aggregated accessibility profiles of several marker genes (Supplementary Fig. 7). Consistent with Hox13 being expressed in the limb mesenchyme, we observed changes in the clustering of Hox13−/− cells only within the mesenchymal cell population (Fig. 3b, c, Supplementary Fig. 8a, b). Among the wild-type mesenchymal cell clusters, clusters 2 and 6 were the only clusters with an average profile specific for the distal limb, as identified from the bulk ATAC-seq from distal limb buds (Fig. 3d). These two clusters were absent in the scATAC-seq data set from Hox13−/− limb (Fig. 3c), further supporting that HOX13 function is required to implement the distal limb-specific chromatin accessibility profile. De novo motif analysis at cluster-specific scATAC-seq peaks uncovered the HOXA13 motif for the clusters 2 and 6 (Fig. 3e) while distinct motifs were found for the other mesenchymal clusters (Supplementary Fig. 9). Accordingly, HOX13-binding profile was highly similar to the chromatin accessibility profile of clusters 2 and 6 (Fig. 3f). Moreover, GREAT analysis indicated that only the accessibility profile of clusters 2 and 6 tends to be associated with digit morphogenesis (Fig. 3g; Supplementary Fig. 9). For instance, the enhancer driving Bmp2 in distal limb20 was in an open state in clusters 2 and 6 and lost its accessible state upon Hox13 inactivation (cluster 3; Fig. 3h). Accordingly, Bmp2 expression is lost in Hox13−/− distal limb while its proximal expression remained unaffected (Fig. 3i). Interestingly, the occurrence of a Hox13−/− specific cluster (cluster 3, Fig. 3c) suggested that chromatin accessibility did not simply switch to a proximal limb bud profile, consistent with the absence of distal to proximal transformation of Hox13−/− limb skeleton9. Together these results provided evidence that the process by which a subset of mesenchymal cells acquire the distal limb-specific chromatin accessibility profile directly relies on HOX13 function.
In this study, we use the developing limb as a model system to investigate the impact of cellular context on HOX-binding specificity. By comparing the genome-wide binding of HOX13 and HOXA11, we found that in the wild-type context about 23% of HOX13 targets are specific to HOX13 consistent with HOX13 being required for the implementation of the digit development program while HOXA11 contributes to the formation of the zeugopod. Our results provide evidence that this specificity relies on HOX13 and HOXA11 being expressed in mutually exclusive domains as the expression of HOXA11 in the HOX13 domain results in HOXA11 binding to the HOX13-specific targets. Importantly, we uncovered that this ectopic HOXA11 binding occurs only in a context where the HOX13-specific targets are in a chromatin accessible state and this open conformation requires HOX13 function. This capacity of HOX13 to trigger the switch from a closed chromatin conformation to an accessible one and to allow the binding of other TFs (Fig. 4), two defining properties of pioneer factors21,22, raises the possibility that HOX13-dependent chromatin accessibility is key to the implementation of the HOX13-specific developmental program. Accordingly, the gain in chromatin accessibility observed in the transition from proximal to distal limb bud occurs at HOX13-specific targets and is dependent on HOX13 function (Fig. 4). Interestingly, binding of HOX13 to initially inaccessible chromatin was observed at the enhancer referred to as Prox, which drives Hoxd expression in the genital bud23 (referred to as Prox in ref. 23), raising the possibility that HOX13 pioneering action may not be limited to the developing limb but rather a general feature of HOX13-dependent developmental programs.
Whether other HOX factors implement their specific developmental program by changing the chromatin accessibility landscape remains to be established. Interestingly, transfection of Drosophila melanogaster HOX factors into Kc167 cells shows that, in this system, a subset of HOX factors (e.g., Antp and Ubx) bind almost exclusively to targets in an accessible chromatin state while other (e.g., Abd-B) bind to loci initially in a closed conformation10. Similarly, a recent study provided evidence that, following transfection of HOXC factors in an in vitro motor neuron differentiation system, the divergence of their genome-wide binding profile is associated with differences in their ability to bind inaccessible chromatin24. These evidence that several HOX factors bind inaccessible chromatin together with the finding that, in vivo, HOX13 TFs establish the distal limb-specific chromatin accessibility landscape, suggest that the differential chromatin accessibility contingent on HOX factors is critical for implementing the distinct HOX-dependent developmental programs.
Our comparative study of HOXA11 and HOX13 in both wild-type and mutant limb buds shows that the HOX13-specific targets can be bound by HOXA11 when HOXA11 is expressed in the HOX13 domain, but not in absence of HOX13, when these targets are in a closed conformation. This might explain why expressing HOXA11 in the HOX13 domain results in the formation of additional digits while distal expression of HOXA11 in the Hox13−/− limb bud is unable to trigger digit development (Fig. 4). Our data also indicate that chromatin opening triggered by the HOX13 factors can expand the target repertoire of other HOX factors expressed in the same limb bud domain, which possibly contributes to the severity of the phenotypes associated with ectopic Hox13 expression. For instance, the severe zeugopod malformation observed in the Ulnaless/+ mice25,26, a mutation corresponding to a genomic inversion resulting in Hoxd13 ectopic expression in the presumptive zeugopod27, may be associated with HOXD13 eliciting chromatin opening at enhancer elements, the transcriptional activity of which could be strengthen/modulated by the other HOX factors expressed in these cells.
The evidence that HOX13 function is required for chromatin accessibility at a subset of distal limb HoxD enhancers suggests that it contributes to the distal expansion of the HoxD expression as limb development proceeds. Interestingly, it was previously proposed that the increase/expansion of the Hoxd13 expression domain might have been a driver for the origin of the novel endoskeletal elements characterizing the fin-to-limb transition28. In this view, the HOX13-dependent chromatin accessibility identified here for a subset of the HoxD enhancers might have been important to trigger the activity of evolutionary novel enhancers in the distal limb bud, which in turn have contributed to the emergence of digits. Similarly, the HOX13-dependent chromatin accessibility at the evolutionary novel enhancer driving Hoxa11 antisense transcription, required to prevent distal Hoxa11 expression and polydactyly12,29, ensured a distal-specific modification of Hoxa11 expression in tetrapods. Consistent with this view, we found that the enhancer driving Hoxa11 antisense transcription is in an accessible state in the presumptive digit domain of chicken limb buds while it is in a closed configuration in early limb buds, when Hox13 genes are not expressed (Supplementary Fig. 10). This result corroborates the findings in wild-type and mutant mouse limb buds and points to a conserved role of the HOX13 TFs in regulating chromatin accessibility during both mouse and chicken embryonic development. Based on these data, we propose that HOX13 pioneer activity added spatial constraints to the activity of evolutionary novel enhancer elements, which may have contributed to the broader morphological diversity of the distal limb as compared to the proximal limb.
The generation of Hoxa13null (Hoxa13Str), Hoxd13null (Hoxd13lacZ), and RosaHoxa11 mouse lines were described elsewhere9,12,30. All mice were maintained in mixed background (C57BL/6× 129). The mice were housed in a 12 h light: dark cycle between 18 and 26 °C temperature with relative humidity of 30–70% and given ad libitum access to food and water for the duration of the study. Noon of the day of the vaginal plug was considered as E0.5. Mice and embryos were genotyped by polymerase chain reaction (PCR) using genomic DNA extracted from tail biopsy specimens and yolk sacs, respectively. Mice work at the Institut de Recherches Cliniques de Montréal (IRCM) was reviewed and approved by the IRCM animal care committee (protocols 2015-14 and 2017-10) in accordance with Canadian regulations. We have complied with all relevant ethical regulations.
ChIP and sequencing
HOXA11 ChIP was performed in forelimb buds of CD1 (wild type) and Prx1Cre; RosaHoxa11/Hoxa11 (R26A11d/A11d) mice at E11.5 in the same conditions as described for HOX13 ChIP11. Chromatin was cross-linked using a combination of disuccinimidyl glutarate (DSG) and formaldehyde and sonicated using Fisher Scientific, Model 100 sonic dismembrator to obtain fragments between 100 and 600 bp. Protein A and Protein G Dynabeads (Invitrogen) were incubated for 6 h at 4 °C with 5 µg HOXA11 (SAB1304728, Sigma) antibody. The chromatin was coupled to the beads overnight at 4 °C. The immunoprecipitated samples were then sequentially washed in low salt (1% Triton, 0,1% sodium dodecyl sulfate (SDS), 150 mM NaCl, 20 mM Tris (pH8), 2 mM EDTA), high salt (1% Triton, 0,1% SDS, 500 mM NaCl, 20 mM Tris pH8, 2 mM EDTA), LiCl (1% NP-40, 250 mM LiCl, 10 mM Tris (pH8), 1 mM EDTA) and TE buffer (50 mM NaCl, 10 mM Tris (pH8), 1 mM EDTA). The DNA was then purified on QIAquick columns (Qiagen). Library and flow cells were prepared by the IRCM Molecular Biology Core Facility according to Illumina’s recommendations and sequenced on Illumina Hiseq 2500 in a 50 cycles paired-end configuration.
Dissection of proximal and distal forelimb buds from wild-type embryos and distal forelimb buds of Hox13−/− embryos11 were performed at E11.5. All samples for ATAC-seq were processed as described21. Briefly, 50,000 cells were washed in phosphate-buffered saline (PBS) and incubated on ice for 30 min in a hypotonic cell lysis buffer (0.1% w/v sodium citrate tribasic dehydrate and 0.1% v/v Triton X100) centrifugated (5 min at 2000g at 4 °C). Cells were then incubated 30 min on ice in cell lysis buffer (10 mM Tris-HCl, pH7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% v/v IGEPAL CA-630. After centrifugation (5 min at 2000g at 4 °C) the resulting pellet of nuclei was resuspended in transposase Master Mix (1.25 µl 10× TD buffer, 5 µl H2O and 6.5 µl of Tn5: Illumina Nextera Kit; FC-121-1031) and incubated for 30 min at 37 °C. Samples were purified using MinElute PCR purification column (Qiagen). The eluted DNA was enriched and barcoded for multiplexing of samples using Nextera barcodes by PCR using Phusion kit. The library was recovered with GeneRead Purification columns. Samples were then evaluated by qPCR to test for the enrichment of open regions and sequenced on Illumina Hiseq 2500 with 50 bp paired-end reads, according to Illumina’s recommendation.
Dissection of forelimb buds from wild type and Hox13−/− embryos11 were performed at E11.5. Forelimbs were dissected in cold 1× PBS, after centrifugation at 300 rcf for 5 min at 4 °C the forelimbs were incubated in dissociation buffer (450 μl of 0.25% Trypsine/EDTA (GIBCO), 50 μl 10% bovine serum albumin (BSA), 1 μl DNAseI (NEB)) for 10 min at 37 °C. After incubation limb cells were gently mixed by pipetting up and down 10–15 times until they were dissociated, then 10% final fetal bovine serum was added. Dissociated cells were filtered using a cell strainer (40 μm Nylon, BD Falcon) and after centrifugation at 300 rcf for 5 min at 4 °C the resulting pellet of cells was resuspended in 1× PBS, 0.1% BSA. Dissociated cells were counted and assessed for cell viability using 0.4% Trypan blue. After centrifugation at 300 rcf for 5 min at 4 °C, the cell pellet was resuspended in 100 μl of ice-cold lysis buffer (10 mM Tris-HCl, pH7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% Tween-20, 0.1% NP-40, 0.01% Digitonin, 1% BSA) and incubated for 5 min on ice. Then 1 ml of wash buffer (10 mM Tris-HCl, pH7.4, 10 mM NaCl, 3 mM MgCl2, 0.1% Tween-20, 1% BSA) was added to the cells. After centrifugation at 300 rcf for 5 min at 4 °C, the pellet of nuclei was resuspended in diluted nuclei buffer in order to have 3500 nuclei/μl and processed using Chromium Single Cell ATAC Reagent Kits (10× Genomics, Pleasanton, CA) following the manufacturer recommendation. Briefly, nuclei were incubated in a Transposition Mix that includes a Transposase that preferentially fragments the DNA in open regions of the chromatin and simultaneously, adapter sequences were added to the ends of the DNA fragments. GEMs were then generated, using partitioning oil, in order to contain a single nucleus and a Master Mix to produce 10× barcoded single-stranded DNA after thermal cycling. The chromium single-cell ATAC Library was amplified and double sided size selected. Samples were controlled at multiple steps during the procedure by running on BioAnalyzer. Libraries were sequenced on Hiseq 4000 with 100 bp paired-end reads.
RNA preparation and sequencing
Dissection of proximal and distal of forelimb buds were performed at E11.5 as described above. The dissected limb buds were stored at −80 °C in Qiagen RNAlater until genotyping was performed. RNA was extracted from two independent embryos and performed in biological duplicate using RNAeasy Plus mini kit (Qiagen 74134). Ribosomal depletion, library preparation and flow-cell preparation for sequencing were performed by the IRCM Molecular Biology Core Facility according to Illumina’s recommendations. Sequencing was done on a HiSeq 2500 instrument with a paired-end 50 cycles protocol.
ChIP-seq and ATAC-seq data analysis
ChIP-seq and ATAC-seq reads were aligned to the mm10 genome using bowtie v.2.3.1 with the following settings: bowtie2 -p 8 --fr --no-mixed --no-unal. Sam files were converted into tag directories using HOMER v4.9.1 (ref. 31) and into bam files using Samtools v1.4.1 (ref. 32) view function. Peaks were identified by comparing each sample to its input using MACS v126.96.36.19960309 (ref. 33) callpeak function using the parameters: --bw 250 -g mm --mfold 10 30 -p 1e−5. For HOXA11 ChIP, peaks found in both replicates with a p value < 10−20 were considered for further analysis. For HOX13 peaks, HOXA/D13 peaks underwent the same stringent filter. To obtain a high confidence list of specific peaks we considered binding as a specific peak when it did not overlap any peak with a p value of 10−5 from either replicate of the compared ChIP. This strategy likely eliminates weakly specific or enriched binding (false negative) but allowed to focus on highly pure lists (true positive) of common vs. specific peaks.
Heatmaps and average profiles were generated using the Easeq software34. ChIP-seq and ATAC-seq data were visualized on the IGV software35 using BigWig files generated using the makeUCSCfile HOMER command. For ATAC-seq differential analysis, peaks from ATAC datasets (proximal wild type and distal wild type for the proximo-distal comparison; distal wild type and distal Hox13−/− for the WT vs. Hox13−/− comparison) were merged using HOMER v4.9.1 mergePeaks tool to obtain a file with all the unique position from all the ATAC-seq datasets. ATAC-seq signals were quantified in these different datasets using the analyzeRepeats.pl HOMER command and differential accessibility analyses were performed using getDiffExpression.pl with default parameters, which uses DESeq2 (ref. 36) to perform differential enrichment analysis. Peaks showing differential accessibility of more than two folds and an adjusted p value smaller than 0.05 were considered differentially accessible. Association of ATAC-seq peaks with closest genes was analyzed using GREAT software37.
The ChIP-seq data for HOX13 in distal limb at E11.511 were retrieved using Sratoolkit v2..8.2-1 from the NCBI Gene Expression Omnibus repository under the accession numbers GSE81356 and the Chicken ChIP-seq data of HOXA13 and HOXA117 from the accession numbers GSE86088.
Motif analysis on ChIP data was performed using a fixed 200 bp window around the peak center. Motif analysis on ATAC-seq data was performed on the whole peak window as the aim is to identify any factors associated with chromatin accessibility and these may not be at the center of the ATAC-seq peak. In all cases, HOMER findMotifsGenome command was used to perform de novo analysis against background sequences generated by HOMER that matches GC content. When the motif rank is not indicated, only the top scoring motif based on its p value is shown.
RNA-seq data analysis
Strand specific paired-end reads were aligned to the mm10 reference genome using TopHat2 v2.1.0 (ref. 38) with the parameters --rg-library “L” --rg-platform “ILLUMINA” --rg-platform-unit “X” --rg-id “run#many” --no-novel-juncs --library-type fr-firststrand -p 12. The resulted Bam files were converted to tagDirectory using HOMER and BigWig were produced using the makeUCSCfile HOMER command.
RNA reads quantification was performed using HOMER analyzeRepeats.pl commands with the parameters: rna mm10 -count exons -condenseGenes -noadj -strand -.
Differential expression analysis was performed using HOMER getDiffExpression.pl command with the default parameters which performs differential expression with DESeq2.
Single-cell ATAC-seq analysis
Sequencing reads were aligned using Cellranger-atac version1.1.0 (from 10×Genomics®) and the resulted sorted bam files were structured into hdf5 snapfiles (single-nucleus accessibility profiles) using snaptools version 1.4.1. Quality control analysis was performed using R_Bioconductor v3.5.1_3.7 and SnapATAC 1.0.0. (ref. 39). Cells with logUMI in [3.5–5] and fragment overlapping peaks above 25% were selected. They were cleaned by eliminating bins overlapping with ENCODE Blacklist regions40, mitochondrial DNA as well as the top 5% of invariant features (house-keeping gene promoters). Dimensionality reduction was performed using a nonlinear diffusion map algorithm41 available in the SnapATAC 1.0.0 package to produce 50 eigen-vectors of which the first 26 were selected (see Supplementary Fig. 6e) in order to generate K Nearst Neighbor graph with K = 15. The clustering was performed using Leiden Algorithm42 available in the package leidenalg version 0.7.0 with a resolution of 0.4 and 2 UMAP (uniform Manifold Approximation and Projection version 0.2.3.1) embedding were generated using umap-learn v0.3.10 to visualize the data43. Fragments originating from the cells belonging to them same clusters were pooled using snaptools 1.4.1 and peak calling was performed using MACS2 version 2.1.2 for each of the clusters44. In order to create a reference peak list NarrowPeaks from each cluster of both WT and Hox13 mutant were merged using Bedtools 2.28.0, the resulting list was added to the hdf5 snapfiles using the snap-add-pmat function available in snaptools v1.4.1 in order to generate a cell by peak matrix which was subsequently loaded into the r snap-object. Differentially accessible regions (DARs) between the different clusters were identified using the findDAR function available in SnapATAC package v1.0.0 with a BCV of 0.1 (biological coefficient of variation) and which relies internally on the exactTest function from EdgeR v.3.14.0 to evaluate the significance of the difference in accessibility. The 2000 DARs with the lowest p value and highest log fold change were further processed though Homer v4.11 to recover cluster-specific motifs (using a scanning window of 300 bp).
The HOXA11- and HOX13-specific binding sites coordinates obtained from our previous ChIPseq experiments were loaded on our hdf5 snapfiles (using Snaptools as described above) to generate a cell by peak matrix then added to the R snap-object; subsequently chromatin accessibility at specific binding sites was computed using a standard scoring method (z-score). Finaly, association of scATAC-seq peaks with closest genes was analyzed using GREAT software37.
Whole-mount in situ hybridization
Whole-mount in situ hybridization was performed using standard procedure45. Generation of the Bmp2 probe was described elsewhere46. Briefly, embryos were rehydrated through a methanol series (100–30%), washed in PBST (0.1% Tween) and bleached for an hour on ice using 6% hydrogen peroxide before undergoing Proteinase K treatment for 15 min at RT and refixed with 4% formaldehyde. Next, embryos were hybridized with the RNA probes (5× SSC pH 4.5; 50% deionized formamide; 1% SDS; 0.1% Tween; 5 mg/mL torula RNA, 0.5 mg/mL heparin) overnight at 68 °C. Embryos were then washed with 1× TBS; 0.1% Tween, treated with 10% Goat serum; 1% BSA and incubated with alkaline phosphatase-conjugated anti-DIG antibodies (1/3000; Roche) overnight at 4 °C. The coloration was done using nitrotetrazolium blue chloride (NBT)/5-bromo-4-chloro-3-indolyl-phosphate, 4-toluidine salt (BCIP) substrate (Roche). After staining, the samples were washed in PBS and post-fixed. Embryos were photographed using the Leica, Wetzlar, Germany M165FC stereomicroscope coupled to the DFC450.C camera. Embryos were genotyped prior to experimentation and WT and Hox13−/− were treated identically in the same assay for comparison. A minimum of three embryos per genotype was assayed for reproducibility (n = 3).
Protein extraction and western-blot analysis
Nuclear extracts were performed using pooled forelimb and hindlimb buds at E11.5 from wild-type and Hoxa11−/− embryos. Western blot was performed using the anti-HOXA11 antibody (1:500) (SAB1304728, Sigma) and the anti-H3 antibody (1:3000) (abcam) was used as loading control (Supplementary Fig. 1).
Further information on research design is available in the Nature Research Reporting Summary linked to this article.
The ChIP-seq data for HOX13 in distal limb and RNA-seq for wild type and Hox13−/− distal limb buds11 at E11.5 are available from the NCBI Gene Expression Omnibus repository under the accession numbers GSE81356. Chicken ChIP-seq data of HOXA13 and HOXA117 were obtained from the accession numbers GSE86088. Raw files and processed files of all ChIP-seq, ATAC-seq and scATAC-seq can be found on GEO under the accession number GSE123482 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE123482] and GSE145657 [https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE145657]. The source data underlying Figs. 1c, f, 2a, c, d, f, g, and 3d; and Supplementary Figs. 2h, 3b, c, 4a, d–f, and 5b, c, e are provided as a Source Data file. Full scans of the blots are available in Supplementary Fig. 11. All other relevant data supporting the key findings of this study are available within the article or from the corresponding author upon reasonable request.
All script used for the single-cell ATAC-seq analysis is available through Github (https://github.com/BCYasser/DigitMorphoScATAC/blob/master/analysis_script).
Kmita, M. & Duboule, D. Organizing axes in time and space; 25 years of colinear tinkering. Science 301, 331–333 (2003).
Krumlauf, R. Hox genes in vertebrate development. Cell 78, 191–201 (1994).
Mallo, M., Wellik, D. M. & Deschamps, J. Hox genes and regional patterning of the vertebrate body plan. Dev. Biol. 344, 7–15 (2010).
Zandvakili, A. & Gebelein, B. Mechanisms of specificity for hox factor activity. J. Dev. Biol. https://doi.org/10.3390/jdb4020016 (2016).
Merabet, S. & Mann, R. S. To be specific or not: the critical relationship between Hox and TALE proteins. Trends Genet. 32, 334–347 (2016).
Slattery, M. et al. Cofactor binding evokes latent differences in DNA binding specificity between Hox proteins. Cell 147, 1270–1282 (2011).
Jerkovic, I. et al. Genome-wide binding of posterior HOXA/D transcription factors reveals subgrouping and association with CTCF. PLoS Genet 13, e1006567 (2017).
Davis, A. P., Witte, D. P., Hsieh-Li, H. M., Potter, S. S. & Capecchi, M. R. Absence of radius and ulna in mice lacking hoxa-11 and hoxd-11. Nature 375, 791–795 (1995).
Fromental-Ramain, C. et al. Hoxa-13 and Hoxd-13 play a crucial role in the patterning of the limb autopod. Development 122, 2997–3011 (1996).
Porcelli, D., Fischer, B., Russell, S. & White, R. Chromatin accessibility plays a key role in selective targeting of Hox proteins. Genome Biol. 20, 115 (2019).
Sheth, R. et al. Distal limb patterning requires modulation of cis-regulatory activities by HOX13. Cell Rep. 17, 2913–2926 (2016).
Kherdjemil, Y. et al. Evolution of Hoxa11 regulation in vertebrates is linked to the pentadactyl state. Nature 539, 89–92 (2016).
Sheth, R., Bastida, M. F., Kmita, M. & Ros, M. “Self-regulation,” a new facet of Hox genes’ function. Dev. Dyn. 243, 182–191 (2014).
Woltering, J. M., Noordermeer, D., Leleu, M. & Duboule, D. Conservation and divergence of regulatory strategies at hox Loci and the origin of tetrapod digits. PLoS Biol. 12, e1001773 (2014).
Buenrostro, J. D., Giresi, P. G., Zaba, L. C., Chang, H. Y. & Greenleaf, W. J. Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position. Nat. Methods 10, 1213–1218 (2013).
Andrey, G. et al. A switch between topological domains underlies HoxD genes collinearity in mouse limbs. Science 340, 1234167 (2013).
Gonzalez, F., Duboule, D. & Spitz, F. Transgenic analysis of Hoxd gene regulation during digit development. Dev. Biol. 306, 847–859 (2007).
Montavon, T. et al. A regulatory archipelago controls Hox genes transcription in digits. Cell 147, 1132–1145 (2011).
Beccari, L. et al. A role for HOX13 proteins in the regulatory switch between TADs at the HoxD locus. Genes Dev. 30, 1172–1186 (2016).
Yamamoto, S. et al. Hoxa13 regulates expression of common Hox target genes involved in cartilage development to coordinate the expansion of the autopodal anlage. Dev. Growth Differ. 61, 228–251 (2019).
Mayran, A. et al. Pioneer factor Pax7 deploys a stable enhancer repertoire for specification of cell fate. Nat. Genet. 50, 259–269 (2018).
Zaret, K. S. & Carroll, J. S. Pioneer transcription factors: establishing competence for gene expression. Genes Dev. 25, 2227–2241 (2011).
Amândio, A. R., Lopez-Delisle, L., Bolt, C. C., Mascrez, B. & Duboule, D. A Complex Regulatory Landscape Involved In The Development Of External Genitals. eLife. https://doi.org/10.7554/eLife.52962 (2020).
Bulajić, M. et al. Hox Binding Specificity is Directed by DNA Sequence Preferences and Differential Abilities to Engage Inaccessible Chromatin. Preprint at https://www.biorxiv.org/content/10.1101/2019.12.29.890335v1 (2019).
Peichel, C. L., Prabhakaran, B. & Vogt, T. F. The mouse Ulnaless mutation deregulates posterior HoxD gene expression and alters appendicular patterning. Development 124, 3481–3492 (1997).
Herault, Y., Fraudeau, N., Zakany, J. & Duboule, D. Ulnaless (Ul), a regulatory mutation inducing both loss-of-function and gain-of-function of posterior Hoxd genes. Development 124, 3493–3500 (1997).
Spitz, F., Gonzalez, F. & Duboule, D. A global control region defines a chromosomal regulatory landscape containing the HoxD cluster. Cell 113, 405–417 (2003).
Freitas, R., Gomez-Marin, C., Wilson, J. M., Casares, F. & Gomez-Skarmeta, J. L. Hoxd13 contribution to the evolution of vertebrate appendages. Dev. Cell 23, 1219–1229 (2012).
Kherdjemil, Y. & Kmita, M. Insights on the role of hox genes in the emergence of the pentadactyl ground state. Genesis https://doi.org/10.1002/dvg.23046 (2018).
Kmita, M., Kondo, T. & Duboule, D. Targeted inversion of a polar silencer within the HoxD complex re-allocates domains of enhancer sharing. Nat. Genet. 26, 451–454 (2000).
Heinz, S. et al. Simple combinations of lineage-determining transcription factors prime cis-regulatory elements required for macrophage and B cell identities. Mol. Cell 38, 576–589 (2010).
Li, H. et al. The sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012).
Lerdrup, M., Johansen, J. V., Agrawal-Singh, S. & Hansen, K. An interactive environment for agile analysis and visualization of ChIP-sequencing data. Nat. Struct. Mol. Biol. 23, 349–357 (2016).
Thorvaldsdottir, H., Robinson, J. T. & Mesirov, J. P. Integrative Genomics Viewer (IGV): high-performance genomics data visualization and exploration. Brief. Bioinform. 14, 178–192 (2013).
Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).
McLean, C. Y. et al. GREAT improves functional interpretation of cis-regulatory regions. Nat. Biotechnol. 28, 495–501 (2010).
Kim, D. et al. TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions. Genome Biol. 14, R36 (2013).
Fang, R. et al. Fast and Accurate Clustering of Single Cell Epigenomes Reveals Cis-Regulatory Elements in Rare Cell Types. Preprint at https://www.biorxiv.org/content/10.1101/615179v2 (2019).
Amemiya, H. M., Kundaje, A. & Boyle, A. P. The ENCODE blacklist: identification of problematic regions of the genome. Sci. Rep. 9, 9354 (2019).
Haghverdi, L., Buettner, F. & Theis, F. J. Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics 31, 2989–2998 (2015).
Traag, V. A., Waltman, L. & van Eck, N. J. From Louvain to Leiden: guaranteeing well-connected communities. Sci. Rep. 9, 5233 (2019).
McInnes, L., Healy, J. & Melville, J. UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction. Preprint at https://arxiv.org/abs/1802.03426 (2018).
Zhang, Y. et al. Model-based analysis of ChIP-Seq (MACS). Genome Biol. 9, R137 (2008).
Scotti, M. & Kmita, M. Recruitment of 5’ Hoxa genes in the allantois is essential for proper extra-embryonic function in placental mammals. Development 139, 731–739 (2012).
Dickinson, M. E. et al. Chromosomal localization of seven members of the murine TGF-beta superfamily suggests close linkage to several morphogenetic mutant loci. Genomics 6, 505–520 (1990).
We are particularly grateful to Guillaume Andrey for critical reading of the manuscript, lab members for insightful discussions and sharing reagents, Odile Neyret for NGS analyses and Jessica Barthe for mouse management. This work was supported by the Canadian Institute for Health Research (MOP-115127 and -126110 to M.K and FRN-154297 to J.D.) and ERC advanced grant INTEGRAL (ID 695032) to R.Z. Bioinformatics analyses were enabled in part by support provided by Calcul Quebec (www.calculquebec.ca), Compute Canada (www.computecanada.ca) and the Scientific IT and Application Support Center of EPFL. Y.K. was supported by a fellowship from the Molecular Biology program of the Université de Montréal and the IRCM fellowship Michel-Bélanger. A.M. was supported by an IRCM Challenge fellowship, C.G. was supported by the Jacques Gauthier IRCM fellowship, and I.D. is supported by the IRCM-Jean Coutu fellowship.
The authors declare no competing interests.
Peer review information Nature Communications thanks Jose Luis Gómez-Skarmeta and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
About this article
Cite this article
Desanlis, I., Kherdjemil, Y., Mayran, A. et al. HOX13-dependent chromatin accessibility underlies the transition towards the digit development program. Nat Commun 11, 2491 (2020). https://doi.org/10.1038/s41467-020-16317-2
This article is cited by
Pioneer factors as master regulators of the epigenome and cell fate
Nature Reviews Molecular Cell Biology (2022)
Context-dependent enhancer function revealed by targeted inter-TAD relocation
Nature Communications (2022)
Biasing the conformation of ELMO2 reveals that myoblast fusion can be exploited to improve muscle regeneration
Nature Communications (2022)
Mesomelic dysplasias associated with the HOXD locus are caused by regulatory reallocations
Nature Communications (2021)
By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.