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Genetics
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10.1093/genetics/iyad081
iyad081
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Gene Expression
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Tissue-specific chromatin-binding patterns of Caenorhabditis elegans heterochromatin proteins HPL-1 and HPL-2 reveal differential roles in the regulation of gene expression
de la Cruz-Ruiz Patricia Andalusian Centre for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville 41013, Spain

Rodríguez-Palero María Jesús Andalusian Centre for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville 41013, Spain
Department of Molecular Biology and Biochemical Engineering, Universidad Pablo de Olavide, Seville 41013, Spain

Askjaer Peter Andalusian Centre for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville 41013, Spain

Artal-Sanz Marta Andalusian Centre for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Seville 41013, Spain
Department of Molecular Biology and Biochemical Engineering, Universidad Pablo de Olavide, Seville 41013, Spain

Claycomb J Editor
Corresponding author: Andalusian Centre for Developmental Biology, Consejo Superior de Investigaciones Científicas/Junta de Andalucía/Universidad Pablo de Olavide, Ctra. de Utrera km. 1, Seville 41013, Spain. Email: peter.askjaer@csic.es; *Corresponding author: Department of Molecular Biology and Biochemical Engineering, Universidad Pablo de Olavide, Ctra. de Utrera km. 1, Seville 41013, Spain. Email: martsan@upo.es
Conflicts of interest The author(s) declare no conflict of interest.

7 2023
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© The Author(s) 2023. Published by Oxford University Press on behalf of The Genetics Society of America.
2023
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Abstract

Heterochromatin is characterized by an enrichment of repetitive elements and low gene density and is often maintained in a repressed state across cell division and differentiation. The silencing is mainly regulated by repressive histone marks such as H3K9 and H3K27 methylated forms and the heterochromatin protein 1 (HP1) family. Here, we analyzed in a tissue-specific manner the binding profile of the two HP1 homologs in Caenorhabditis elegans, HPL-1 and HPL-2, at the L4 developmental stage. We identified the genome-wide binding profile of intestinal and hypodermal HPL-2 and intestinal HPL-1 and compared them with heterochromatin marks and other features. HPL-2 associated preferentially to the distal arms of autosomes and correlated positively with the methylated forms of H3K9 and H3K27. HPL-1 was also enriched in regions containing H3K9me3 and H3K27me3 but exhibited a more even distribution between autosome arms and centers. HPL-2 showed a differential tissue-specific enrichment for repetitive elements conversely with HPL-1, which exhibited a poor association. Finally, we found a significant intersection of genomic regions bound by the BLMP-1/PRDM1 transcription factor and intestinal HPL-1, suggesting a corepressive role during cell differentiation. Our study uncovers both shared and singular properties of conserved HP1 proteins, providing information about genomic binding preferences in relation to their role as heterochromatic markers.

The heterochromatin protein 1 (HP1) family regulates the transcriptional repression of numerous genes. C. elegans has two HP1 homologs: HPL-1 and HPL-2. Here, de la Cruis Ruiz et al. analyze the genome-wide binding profiles of HPL-1 in the intestine and HPL-2 in the intestine and hypodermis at the L4 developmental stage, showing that chromosomal distribution differs between HPL-1 and HPL-2. Further comparisons of heterochromatin marks, tissue-specific transcriptomes, and other features demonstrate tissue-specific and unique roles for HPL-1 and HPL-2.

C. elegans
chromatin
DamID
gene expression
heterochromatin protein 1
HPL-1
HPL-2
Spanish FPI program Ministerio de Ciencia Innovación y Universidades Agencia Estatal de Investigación 10.13039/501100011033 Fondo Europeo de Desarrollo Regional 10.13039/501100008530 Consejería de Transformación Económica, Industria, Conocimiento y Universidades de la Junta de Andalucía 10.13039/100020230 CEX2020-001088-M PID 2019-104145GB-I00 PID2019-105069GB-I00 FEDER 2014–2020_UPO-1260918 P20_00873 CEX2020-00108-M Unidad de Excelencia María de Maeztu
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pmcIntroduction

Heterochromatin in worms, like in other species, is tightly packaged, presents a low gene density and is usually enriched at the nuclear periphery (Gu and Fire 2010; Ahringer and Gasser 2018). Facultative heterochromatin is defined by the presence of histone H3 lysine 27 tri-methylation (H3K27me3), which can be erased by demethylation during development, leading to a transcriptionally active state. The Polycomb PRC2 complex comprised of MES-2, MES-3, and MES-6 proteins is responsible for H3K27 methylation (Steffen and Ringrose 2014; Piunti and Shilatifard 2016). The constitutive form of heterochromatin is characterized by H3K9me3, which ensures homeostasis and differentiation of tissues across species (Padeken et al. 2022). H3K9 methylation is performed in sequential steps by the MET-2/SETDB1 enzyme that carries out mono- and di-methylation and SET-25/G9a that performs tri-methylation. Both enzymes are main players in the perinuclear attachment of H3K9me-enriched heterochromatin (Towbin et al. 2012). These heterochromatin domains usually reside within the chromosomal distal regions (“arms”), where most meiotic recombination occurs. The arms are also enriched in repetitive DNA elements, decorated by H3K9me2 and/or H3K9me3 (C. elegans Sequencing Consortium 1998; Liu et al. 2011; McMurchy et al. 2017). In contrast, genes in autosome centers are generally expressed at higher levels and are more evolutionarily conserved (C. elegans Sequencing Consortium 1998).

In Caenorhabditis elegans, HPL-2 is considered as a marker for heterochromatin domains in developing embryos (Grant et al. 2010). HPL-2 is part of the heterochromatin protein 1 (HP1) family, which is highly conserved across the eukaryotic kingdom. HP1 was first characterized in fruit flies, as a component responsible for the variegation position effect, in which inhibition of gene expression occurs via imposition of a heterochromatin-like structure to inactivate it (Eissenberg et al. 1990). The two HP1 homologs in C. elegans, HPL-1 and HPL-2, possess a conserved structure that consists of an N-terminal chromo domain (CD) involved in binding to the K9 residue on histone H3 in its mono-, di-, or tri-methylated form. The CD is followed by a flexible hinge region and a C-terminal chromo shadow domain (CSD) required for dimerization and interaction with other proteins (Eissenberg 2001; Schott et al. 2006).

HPL-1 and HPL-2 are 48% identical along their entire length, with the highest homology within the CD and CSD (60%; Supplementary Fig. 1, c and d). The hinge region is more divergent and consists of only 19 amino acid residues in HPL-1 vs 31 residues in HPL-2. Their expression is ubiquitous in the nuclei of most cells throughout development (Couteau et al. 2002; Schott et al. 2006). The observation of postembryonic defects in hpl-2 mutants, such as sterility, defective growth and brood size, larval arrest, and multivulva phenotypes demonstrated that HPL-2 functions in cell fate determination and gonad development. The similar synthetic phenotypes presented in double hpl-1 and hpl-2 mutants prompted a conclusion of a redundant functionality for HPL-1, which did not show obvious phenotypes when mutated alone (Cardoso et al. 2005; Coustham et al. 2006; Schott et al. 2006, 2009; Simonet et al. 2007; Koester-Eiserfunke and Fischle 2011). HPL-2 has also been implicated in DNA replication and stress response, being enriched in DNA repetitive elements (Cardoso et al. 2005; Coustham et al. 2006; Schott et al. 2009; Black et al. 2010; Meister et al. 2011; Garrigues et al. 2015).

Comparatively, little is known about HPL-1 functions in C. elegans. A physical interaction between HPL-1 and the mono-methylated H1K14me1 histone variant has been observed to regulate innate immunity against pathogenic bacterial infection (Studencka, Konzer, et al. 2012). Like HPL-2, loss of HPL-1 results in transcriptional alteration of genes that encode nuclear hormone receptor family proteins such as NHR-60 and NHR-156, transcription factors such as MIZ-1, ZIP-3, KZIP-8, and MADF-2, and homeobox genes like CEH-82 or the homeodomain gene LIM-7, which cause male tail defects (Studencka, Wesołowski, et al. 2012). Recently, HPL-1 was related to transgenerational embryonic lethality under specific paternal DNA damage. HPL-1 depletion induced a reduction in H3K9me2 levels in the germline, which was beneficial for F2 generation survival (Wang et al. 2022).

Despite the association of HP1 proteins with different functions, the tissue-specific behavior of HPL-1 and HPL-2 has not been characterized. These types of studies have become important to investigate the underlying heterogeneity between tissues. This may help to understand, for instance, potential regulatory links between epigenetic alterations and target gene expression changes to establish an integrative analysis (Yilmaz et al. 2020). To reinforce this idea, contrasting results have been reported when performing rescue experiments with HP1 proteins upon endoplasmic reticulum stress. For example, upon whole-body loss of HPL-2, intestinal-specific expression of HPL-2 restored wild-type level of the stress response, while it was detrimental upon neuronal-specific expression (Kozlowski et al. 2014). However, overexpression in either of the two tissues was sufficient to provide a partial rescue of dauer exit (Meister et al. 2011). This highlights the differences in tissue response due to a lack of HPL-2 when evaluating distinct pathways.

To contribute to the characterization of HP1 proteins, a comparative study of HPL-1 and HPL-2 homologous proteins in C. elegans in a tissue-specific manner is reported here. We identified specific genomic regions bound by HPL-2 in hypodermal and intestinal tissues, as well as HPL-1-associated regions in the intestine at the L4 developmental stage. We found that HPL-2 associated preferentially to chromosome distal arms, while HPL-1 was more equally distributed between the autosome arms and the center. Moreover, both HP1 homologs strongly correlated with the two repressive histone marks H3K9me3 and H3K27me3 in both tissues analyzed. However, only the HPL-2 binding pattern coincided with mono- and di-methylated H3K9 forms.

We confirmed a general repressive role for HP1 proteins when comparing them with transcribed genes in the tissues studied. In addition, the large number of unique genes, together with gene ontology (GO) analyses, suggests tissue-specific patterns of gene silencing. Moreover, we discovered a potential coregulation of chromatin regions by the BLMP-1/PRDM1 transcription factor and intestinal HPL-1. Lastly, HPL-2 was found to be enriched at DNA repetitive elements in both tissues, conversely to intestinal HPL-1. In summary, our study uncovered both unique and common features of HP1 C. elegans homologous proteins in two differentiated tissues.

Materials and methods

C. elegans strains and maintenance

Maintenance of C. elegans strains were done conforming to standard protocols on nematode growth medium (NGM) plates, grown in a monoxenic lawn of Escherichia coli OP50 at 20°C (Stiernagle 2006). For DamID experiments, a lawn of E. coli GM119 dam(-) strain was used to grow the worms (Arraj and Marinus 1983). The complete list of strains used in this study is available in Supplementary Table 6.

Molecular cloning

To generate the Dam::HPL-1 expression construct pBN494 (Phsp-16.41::FRT::mCherry::his-58::FRT::Dam::hpl-1), the hpl-1 CDS was PCR amplified from genomic DNA and inserted in the pCRII cloning vector (Invitrogen). Next, MYC-flanked Dam was inserted into the EcoRI site in the first exon of hpl-1. Finally, Dam::hpl-1 was excised with XhoI + SpeI and inserted into pBN488 (Fragoso-Luna et al. 2023) digested with XhoI + NheI. To generate the Dam::HPL-2 expression construct pBN495 (Phsp-16.41::FRT::mCherry::his-58::FRT::Dam::hpl-2a), the hpl-2a CDS was PCR amplified from genomic DNA and inserted in the pCRII cloning vector. Next, MYC-flanked Dam was inserted into the BamHI site in the third exon of hpl-2a. Finally, Dam::hpl-2a was excised with SalI + SpeI and inserted into pBN488 digested with XhoI + NheI. This insertion results in the specific tagging of the hpl-2a isoform. Designs were based on previous constructs for multicopy (Couteau et al. 2002) and endogenous (Patel and Hobert 2017) tagging of HPL-1/2.

Mos single copy insertion

Single-copy integration transgenic strains were made by microinjection into strain EG4322 (ChrII) with unc−119(+) recombination plasmids together with individual transgenes (pBN494 and pBN495) at 25 ng/µl, Mos1 transposase (Peft-3::transposase) at 50 ng/µl and three red coinjection markers pCFJ90 (Pmyo-2::mcherry) at 2.5 ng/µl, pCFJ104 (Pmyo-3::mcherry) at 5 ng/µl and pBN1 (Plmn-1::mcherry::his−58) at 10 ng/µl (Frøkjær-Jensen et al. 2012; Dobrzynska et al. 2016). Plasmids were microinjected into one of the gonad arms of egg-laying and locomotion defective unc-119 young adult worms. Injected worms were individually transferred to NGM petri dishes and placed at 25°C. Successful integrants were spotted after 7−14 days based on wild-type mobility and absence of co-injection markers. Description of plasmids can be found in Supplementary Table 7.

DamID-seq protocol

DamID experiments were performed as described in de la Cruz Ruiz et al. (2022). Strains were synchronized by standard hypochlorite treatment and grown until the L4 stage. Optimal number of 14× cycles were selected for PCR amplification of methylated GATC sites.

DamlD-seq data processing and visualization

The quality control of the DamID technique and the calculation of chromosome association profiles at 100 kb level for all HP1 samples were performed by damid.seq.r pipeline version 0.1.3 in RStudio (R version 3.4.3; available at github.com/damidseq/rDamlDSeq; Sharma et al. 2016). From FastQ files, the pipeline detects and maps reads containing the DamID adapters (adapt.seq = “CGCGGCCGAG”) and match them to genomic regions flanked by GATC sites (restr.seq = “GATC”) to obtain Bam Files. After mapping with the C. elegans genome release “BSgenome.celegans.ucSc.ce11,” the log2 ratio HPL::Dam/GFP::Dam across two replicas was integrated to plot the relative read counts at 100 kb bin along the genome for all chromosome autosomes. Pairwise Wilcoxon rank test values were calculated in R. Coordinates of arms as defined in González-Aguilera et al. (2014) and Sharma et al. (2016). Read numbers for all data sets are summarized in Supplementary Table 8.

For the visualization using UCSC Genome Browser, the Bam files obtained in the previous pipeline (damid.seq.r) were used to generate the normalized log2 HPL::Dam/GFP::Dam ratio scores per GATC genome fragments, using perl script damidseq_pipeline v1.4.5 (Marshall and Brand 2015; available at https://github.com/owenjm/damidseq_pipeline). The pipeline integrates a Bowtie 2 v2.3.4 (Langmead and Salzberg 2012) calling to map reads on C. elegans bowtie indexes from assembly WBcel235 (available in Illumina iGenomes webpage; identical to ce11). In addition, it includes also Samtools v1.9 (Li et al. 2009) for alignment guidance, and a GFF file containing all GATC sites in the C. elegans genome. Last GATC coordinates file was built by gatc.track.maker.pl tool provided by the same pipeline script using WBcel235 FASTA file for C. elegans (available at https://ensembl.org/Caenorhabditis_elegans/Info/Index). Final bedgraph files for each replica were averaged using average_tracks perl script included in damid_misc (available at https://github.com/owenjm/damid_misc). For comparison of chromosome IV arms vs centers, we used the following border coordinates: chrIV 4,790,000 and 12,610,000.

For the heat map depicting Pearson correlations between Histone marks data sets, we did a preprocessing to average the replicas in bedgraph/wig format using WiggleTools (Zerbino et al. 2014). Then, a fixed bin size was selected to standardize all data sets by “bedgraph_to_wig.pl” tool (created by Sebastien Vigneau in Alexander Gimelbrant laboratory; available at https://gist.github.com/svigneau/8846527). After converting wig files to bigwig format, we lifted-over the bigwig to equivalent genome version using Crossmap tool (Zhao et al. 2014). Finally, the matrix and heat map were generated by “multiBigwigSummary” and “plotCorrelation” tools inside Deeptools (Ramírez et al. 2016). Sources for data sets listed in Supplementary Table 9.

Peak calling and analysis

The selection of statistically significant peaks for every HP1 sample was done by find_peaks perl script (available at https://github.com/owenjm/find_peaks) with a false discovery rate <0.05 using as input averaged bedgraph files containing normalized log2 HPL::Dam/GFP::Dam ratio scores per GATC fragment.

Intersection between peaks from different data sets and statistical calculation of Fisher exact test were performed by “Intersect” and “Fisher” tools included in Bedtools suit (Quinlan and Hall 2010). We include r and f = 0.1 options, default mode for the rest. Default options were used for the characterization of repetitive element types. When needed, a liftover between genome ce10, ce6, and ce11 was performed by “liftOver” tool (available in https://genome.ucsc.edu/cgi-bin/hgLiftOver). Pairwise association for peaks comparison was performed by intervene tool, using aforementioned bedtools options (Khan and Mathelier 2017). Heat maps and Stacked plots for peaks were generated by GraphPad Prism 8 (www.graphpad.com). The coordinates for comparison between chromosome autosome arms and center were used as described in Garrigues et al. (2015).

A statistical method based on Monte Carlo simulation was applied to plot intersected peaks in Fig. 4a, Fig. 5b and c and Fig. 6e (Ferré et al. 2019). For the analysis of repetitive elements only those with equal or more than 10 repetitions were considered.

Gene assignment and analysis

The statistically significant peaks selected were assigned to genes using UROPA (Kondili et al. 2017) as a web tool (available at http://loosolab.mpi-bn.mpg.de/UROPA_GUI/) with Caenorhabditis_elegans.WBcel235.107.gtf (from http://ensembl.org/Caenorhabditis_elegans/Info/Index) for genome protein coding annotation. Peaks were determined to genes on any strand when their center coordinate was localized up to 3 kb upstream of a gene start site or 3 kb downstream of the gene end site. We used UROPA tool to annotate genes from significant peaks of BLMP-1 data set. Venn diagram overlapping gene data sets was performed using “Interactivenn” webtool (available in http://www.interactivenn.net/index.html;  Heberle et al. 2015). The statistical significance by hypergeometric distribution was done with http://nemates.org/MA/progs/overlap_stats.htmlwebtool.

The GO analysis was done using unique genes from HP1 data sets, by g:Profiler webtool using default options (Raudvere et al. 2019).

To compile lists of genes expressed in hypodermal and intestinal cells, we compared transcriptomic data obtained with PATseq (Blazie et al. 2017), FACS (Kaletsky et al. 2018), FANS (Haenni et al. 2012), TaDa (Katsanos et al. 2021), and RAPID (Gómez-Saldivar et al. 2020; Fragoso-Luna et al. 2023). From these six studies, four gene lists are available for each tissue. For each tissue, we intersected the lists using jvenn (Bardou et al. 2014) and selected genes identified in at least three out of four transcriptomic methods. The resulting lists were further restricted to protein coding genes by intersecting with all protein coding genes from WormBase.

Aggregation plot of signal localization

All aggregation plots were generated using Seqplots, as a GUI application (Stempor and Ahringer 2016). Plots represent the average signal for every 10 bp bins of depicted histone marks or HP1 data sets over the midpoint position of the significant peaks depicted.

Results

HPL-1 and HPL-2 differentially associate with the genome

To study the function of C. elegans HP1 proteins, the DNA-binding profiles for HPL-1 and HPL-2 were determined by tissue-specific DNA adenine methylation identification (DamID) at the L4 larval stage (de la Cruz Ruiz et al. 2022). We generated Dam::HPL-1/2 fusions by inserting Dam at the sites previously used for multicopy (Couteau et al. 2002) and endogenous (Patel and Hobert 2017) tagging of HPL-1/2, which results in functional nuclear-localized proteins (Supplementary Fig. 1a). Of the three hpl-2 isoforms, our Dam insertion tags specifically hpl-2a, the most expressed isoform based on RNAseq data (Supplementary Fig. 1, b and c). Ubiquitous expression of fluorescent protein fusions at endogenous levels results in phenotypically wild-type animals, whereas Dam fusions are expressed at much lower levels from a noninduced hsp-16.41 promoter and only in either intestinal or hypodermal cells. We focused on the intestine, a major metabolic tissue of C. elegans amenable to this technique (Cabianca et al. 2019), and included also the hypodermis for HPL-2 to compare binding profiles across two tissues. We confirmed the tissue-specific expression of intestinal Dam::HPL-1 and Dam::HPL-2 and hypodermal Dam::HPL-2 (Supplementary Fig. 2; Muñoz-Jiménez et al. 2017), as well as the correlation between replicas (Supplementary Fig. 3; Love et al. 2014). We then first analyzed the results at 100 kb resolution to obtain a broad overview of the behavior of the two HP1 proteins. In agreement with previous observations in embryonic cells, HPL-2 is enriched in distal regions (“arms”) of autosomes in both hypodermal and intestinal tissues and depleted from autosome centers (Fig. 1a and Supplementary Fig. 4a; Garrigues et al. 2015). The X chromosome is characterized by only two global regions: a left arm and a center-right region (Gerstein et al. 2010). The left arm contains the meiotic pairing center and we observed that HPL-1 and HPL-2 mainly interact with this region of the X chromosome (Supplementary Fig. 3). For the autosomes, we found that chromosome arms with meiotic pairing center were more frequently in contact with HPL-2 in the hypodermis compared with the intestine (Fig. 1a). Surprisingly, HPL-1 in the intestine is distributed more equally between autosome arms and centers, being significantly different from HPL-2 (Fig. 1a). The difference between HPL-1 and HPL-2 binding profiles in the intestine is also observed at higher resolution (10 kb) for all autosomes (Fig. 1b and Supplementary Fig. 4a). This suggests that HPL-1 might have unique roles in C. elegans. In addition, both HPL-2 DamID profiles exhibit a significant overlap with previous whole-animal HPL-2 ChIP data sets (Gerstein et al. 2010; Supplementary Fig. 5, a–c and Supplementary Table 1).

Fig. 1. Tissue-specific chromatin binding of HPL-1 and HPL-2 and their association to histone marks. a) Boxplot showing the HP1 association profile in all autosomes based on arms with and without meiotic pairing centers at 100 kb bin resolution in hypodermal and intestinal tissues. P-values from the Wilcoxon rank sum test with continuity correction are indicated. PC, pairing center. b) Example of average signal tracks over 10 kb regions in chromosome IV for HP1 proteins in hypodermal and intestinal tissues. The shaded region represents the chromosome center, while the flanking regions correspond to the left and right arms. A snapshot from the IGV viewer. c) Heat map showing pairwise Pearson correlation coefficients between indicated data sets at 25 bp window size. d) Aggregation plot depicting the genome-wide average signal tracks for H3K9me1 data set over HPL-2 hypodermal and intestinal peaks. The center position represents the midpoint location of peaks. The regions up to 3 kb upstream and 3 kb downstream of the midpoint in 10 bp bins are shown.

HPL-1 and HPL-2 differentially correlate with H3K9me3 and H3K27me3 histone marks

As reader of methylated H3K9, HPL-2 binding sites in the genome coincide with the pattern of mono- and di-methylated H3K9 (H3K9me1-2) in C. elegans embryos, and less so with H3K9me3 (Garrigues et al. 2015). To determine if the correlation also exists in differentiated cells and for both HP1 proteins, we compared the HPL-1 and HPL-2 binding profiles with published histone ChIP data sets from the L3 larval stage. Indeed, a high correlation was found between both HP1 proteins and repressive H3K9me3 and H3K27me3 histone marks, clustering together in the pairwise Pearson correlation heat map (Fig. 1c). Both histone marks usually colocalize on distal autosome arms, while only H3K27me3 associates with central regions as well (Liu et al. 2011; Ahringer and Gasser 2018).

Interestingly, HPL-2 in both tissues positively correlated with mono- and di-methylated H3K9, whereas HPL-1 protein failed to show any significant association (Fig. 1, c and d and Supplementary Fig. 4, b–d). Therefore, our data indicate that only HPL-2 exhibits more flexibility to bind to the three methylated forms of H3 in both differentiated tissues, suggesting a differential role in the control of gene expression for HPL-1 and HPL-2 through development.

HP1 proteins bind to genomic regions in a tissue-specific manner

We next asked if the differences in distribution of large HP1-associated genomic regions across autosomes (Fig. 1, a and b) and the correlation with heterochromatin marks (Fig. 1, c and d) reflect a differential binding of HPL-1 and HPL-2 to smaller specific DNA regions. In addition, the different proportion of overlapping peaks between HP1 proteins and whole-animal HPL-2 ChIP data could indicate tissue-specific differences (Supplementary Fig. 5a and Supplementary Table 1). To address this, we compared the regions present in each HP1 data set. Strikingly, we found that around 70% of bound genomic regions are unique for either HPL-1 or HPL-2 (Fig. 2a and Supplementary File 1). The highest overlap was found between the two tissue-specific HPL-2 profiles, suggesting a conserved regulation for specific regions in both tissues (Fig. 2a). Despite the statistically significant overlap between HP1 proteins in all tissues analyzed, the proportion of overlapped regions does not reach 30%, remarking a high degree of specificity. This suggests that HP1 proteins play both overlapping and distinctive roles in chromatin regulation. Some tissue-specific regions might need to be simultaneously bound by both HP1 proteins for a more robust control of gene expression, presumably repression. Further information about the transcriptional state of those regions would be needed.

Fig. 2. Tissue-specific binding of HP1 proteins and association with gene expression. a) Venn diagram depicting the overlapping DNA regions bound by HP1 proteins in hypodermis and intestine. The intersection was performed using 10% of fraction reciprocal between genomic regions. Fisher’s exact test P-values represent enrichment. b) Pie charts showing the percentages of peaks inside various genomic features. Peak assignment was done to the nearest gene whose center coordinate was within 3 kb upstream and 3 kb downstream of the TSS and TES, respectively, of a gene. Ratios above pie charts show the number of peaks assigned to genes relative to the total number of peaks. TSS, transcription start site; TES, transcription end site. c) Venn diagram depicting the overlap between HPL-2-bound genes in the hypodermis and genes robustly expressed in this tissue. d) Venn diagram depicting the overlaps between HPL-1- and HPL-2-bound genes in the intestine and genes expressed in this tissue. Exact hypergeometric probability representation factor and P-values are shown.

Annotation of genomic features for regions bound by HP1 proteins showed that more than 70% of the peaks reside inside protein coding regions (Fig. 2b; see peak ratio). Most bound regions are placed within transcribed chromatin, and a notable proportion overlaps with transcription start sites or promoter regions (Fig. 2b).

In order to know whether genes bound by HP1 proteins (Supplementary File 2) are repressed or activated, a comparison with gene data sets from alternative methods of tissue-specific transcriptomic profiling was performed. First, for hypodermal tissue, we selected genes identified in at least three out of four transcriptomic methods (Blazie et al. 2017; Kaletsky et al. 2018; Katsanos et al. 2021; Fragoso-Luna et al. 2023). We found a significant underrepresentation of transcribed genes among HPL-2 hypodermal-bound genes (<3% overlap; P < 0.001), suggesting a repressive role for HPL-2 in the hypodermis (Fig. 2c, Supplementary File 3, and Supplementary Table 2). We followed a similar procedure with intestinal genes, resulting in an underrepresentation of transcribed genes when compared with HPL-1-bound genes (<3% overlap; P < 6.862e-07; Fig. 2d, Supplementary File 3, and Supplementary Table 2; Haenni et al. 2012; Blazie et al. 2017; Kaletsky et al. 2018; Gómez-Saldivar et al. 2020). In contrast, HPL-2 in the intestine did not show any tendency (Fig. 2d). These comparisons suggest a tissue-specific repressive role for HPL-2 and that HPL-1 and HPL-2 act differently in intestinal cells.

Interestingly, when comparing HP1 bound genes across the three data sets, we found that although a significant proportion of genes are concurrently bound by both HP1 proteins (Fig. 3a), around 60% of genes are unique in each data set. This is similar to the proportion of unique binding sites (Fig. 3a; compare with Fig. 2a; Supplementary File 4), suggesting a more precise transcriptional regulation of those genes. GO enrichment analysis for biological processes with genes bound by HPL-2 in the intestine identified only a few and rather broad terms, such as development and anatomical structures (Fig. 3b). Because these terms are based on genes primarily expressed in proliferative tissues, their association with HPL-2 in terminally differentiated intestinal cells is concordant with a repressive role of HPL-2. Similarly, gene sets retrieved from either HPL-2 DamID in hypodermal tissue or HPL-1 DamID in the intestine identified only a few enriched GO terms and none of them related to the tissue where the Dam fusion protein was expressed (Supplementary Fig. 6, a and b).

Fig. 3. Differential tissue-specific binding of HP1 proteins. a) Venn diagram depicting the overlapping genes bound by HP1 proteins in the different tissues. Exact hypergeometric probability representation factor and P-values are shown. b) GO terms associated to biological process category of genes bound by HPL-2 in the intestine. The number of intersected genes is depicted at the end of the bars. c) Aggregation plot depicting the Z-score of aggregated average signal of HP1 proteins over 3 kb upstream and 3 kb downstream of BLMP-1 peaks’ midpoint position.

In our attempt to get more insight about new biological functions of HP1 proteins, we compared HP1-bound regions with those bound by different transcription factors at the L1 larval stage (ALR-1, MAB-5, EOR-1, PQM-1, PHA-4, ELT-3, ELT-2, EGL-5, SKN-1, UNC-130, EGL-27, and BLMP-1; Niu et al. 2011). Interestingly, this analysis revealed a significant overlap between the transcription factor BLMP-1/PRDM1 and HPL-1 in the intestine, which is maintained at the L4 stage as well (Supplementary Fig. 6, c and d and Supplementary Table 3; Stec et al. 2021). Around 13% of peaks are common to HPL-1 and BLMP-1, mainly in autosome centers in L1 (Supplementary Fig. 6e). In line with this, the genome-wide average signal of HP1 binding at BLMP-1 peaks showed a strong enrichment for HPL-1 (Fig. 3c). Then, we assigned the BLMP1 significant peaks to genes using the same criteria and method employed for HP1 data sets described here. We found a significant overlap between BLMP-1 and HPL-1 bound genes, with >100 genes in common (Supplementary Fig. 6f and Supplementary File 4). GO terms were only available for 35 genes out of the 108 common genes between HPL-1 and BLMP-1 and are related to external cell structure, molting, and cuticle (Supplementary Fig. 6g). Moreover, only one-third (38/108) of the genes bound by both BLMP-1 (in whole animals) and HPL-1 (in the intestine) are expressed in the intestine (Supplementary File 4), implying that a generally repressive role of HPL-1 during larval development is a plausible explanation.

Collectively, those results strongly suggest that HPL-1 and BLMP-1 could potentially coregulate specific genes or transcription factors. Knowing that PRDM1, the human BLMP-1 ortholog, was first described as a repressor of beta-interferon (beta-IFN) expression, a tissue-specific corepression by HPL-1 and BLMP-1 may occur (Keller and Maniatis 1991).

Only HPL-2 protein is enriched at repetitive elements

It has been previously reported a role for several heterochromatin proteins, among them HPL-2, in maintaining repetitive elements and particular genes silenced, which is crucial for germline and fertility processes (Ashe et al. 2012; McMurchy et al. 2017). HPL-2 is also enriched at repetitive elements both, in embryos and young adults (Garrigues et al. 2015; McMurchy et al. 2017). These analyses were performed on whole animals and hence offered no information about tissue specificity nor the behavior of HPL-1. Therefore, we assessed potential differences in the binding of HPL-1 and HPL-2 to repetitive elements using annotation from the most recent UCSC Genome Browser based on repeat masker that classified 61,527 individual repetitive elements (https://genome.ucsc.edu; Tarailo-Graovac and Chen 2009). Interestingly, our analysis corroborates the high proportion of overlapping regions between HPL-2 and genomic repetitive elements in both tissues (Fig. 4a and Supplementary Table 4). However, the overlap is reduced and not significant in the case of HPL-1 protein (Fig. 4a and Supplementary Table 4), indicating that HPL-1 is not enriched at repetitive elements.

Fig. 4. Association of HP1 proteins to repetitive elements. a) Number of intersected peaks between HPL-1 and HPL-2 and repetitive elements assessed by Monte Carlo simulation statistical test. The probabilities of obtaining the same overlap by chance are indicated (shaded P-values). b) Stacked plot depicting the proportion of repetitive element types bound by HPL-2 data sets (top panel, Supplementary Table 5). The proportion of repetitive element types in the C. elegans genome is shown in the bottom panel (from UCSC Genome Browser based on repeat masker and excluding simple repeats). c) Column bar graph representing the proportion of HPL-2-bound repetitive elements in the intestine (right columns) in the hypodermis (middle columns) and in both tissues (left columns).

Moreover, the hypodermal tissue exhibited 14% more overlapping regions compared with the intestine for HPL-2 protein, remarking tissue-specific divergence (Supplementary Table 4). To further study this difference, we looked at repetitive element types, finding DNA transposon as the most predominant type for both tissues (Fig. 4b and Supplementary Table 5). In agreement, six out of the nine most frequent repetitive element families bound by HPL-2 in both tissues were DNA transposons (CELE14B, CELE42, CELE14A, PALTA5_CE, TIR9TA1B_CE, TIR9TA1_CE; Fig. 4c and Supplementary Table 5). Three of these (CELE14B, CELE42, and PALTA5_CE) were also found to be frequently bound by HPL-2 in embryonic cells (Garrigues et al. 2015). Interestingly, the percentage of regions bound by HPL-2 in the two tissues varied from 2 to 31% for the most frequent repetitive element families, suggesting that a broad majority correspond to uniquely enriched repetitive elements depending on the tissue (Fig. 4c and Supplementary Table 5). However, a large fraction of HPL-1 bound repetitive elements overlapped with HPL-2 associated elements in the intestine (Supplementary Table 5). Importantly, for some DNA transposon families, such as CELE14B, CELE42, and CELE14A, the HPL-2 enrichment for both tissues represented >10% of the total repeats in the genome, suggesting a relevant role for HPL-2 to maintain transposon silencing (Supplementary Table 5). The strongest association reported for HPL-2 in young adults was found with DNA transposons Helitron families, being less abundant compared with other families at the L4 stage analyzed here (Supplementary Table 5; McMurchy et al. 2017). Nonetheless, for all stages analyzed here and in other studies, DNA transposons are the most representative, suggesting the necessity to maintain these repressed in differentiated tissues.

Discussion

Here we characterized the genomic binding profile of the two C. elegans HP1 protein homologs HPL-1 and HPL-2 in the intestine, as well as the binding profile of HPL-2 in the hypodermis. We showed that HPL-2-bound regions are enriched in distal chromosome arms, as published for embryos and young adults (Garrigues et al. 2015; McMurchy et al. 2017). In contrast, we showed an unprecedented location of HPL-1 in the center of autosomes.

When assessing the binding to heterochromatic histone marks, we found a strong correlation of HP1 proteins with H3K9me3 and H3K27me3. On the one hand, methylated H3K9 correlates with chromatin compaction, which prevents the access of transcription factors to their binding sites in differentiated cells, being crucial for restricting plasticity and maintaining tissue identity. On the other hand, H3K27me3 seems to limit plasticity, acting in a parallel manner (Patel and Hobert 2017). Our data suggest that HP1 proteins act nonredundantly in controlling tissue specificity in differentiated somatic cells. In agreement with this, cellular plasticity is affected both in single hpl-1 or hpl-2 mutants and more strongly upon deletion of both HP1 proteins (Patel and Hobert 2017). Moreover, Evans et al. (2016) described some domains decorated by H3K27me marks, considered the most suceptible to be regulated during development. Lastly, in embryos, genes expressed in terminally differentiated tissues were marked specifically by H3K9me3 (Zeller et al. 2016). It could be that HP1 proteins contribute to the formation of these domains, as well as controlling tissue-specific genes, affecting chromatin activity and gene expression in a context-dependent manner. In other words, the ability of HP1 proteins to bind concurrently to both repressive histone modifications, reinforce the repression, and could account for developmental gene regulatory networks. Nevertheless, the lack of tissue-specific profiles for histone methylation limits the possibility to interpret in an exhaustive manner the behavior of HPL-1 and HPL-2 in differentiated hypodermal and intestinal tissues in terms of their association to particular histone marks. Recently, single-cell analyses have revealed that histone modifications contribute to cell heterogeneity within and between tissues (Carter and Zhao 2021). In addition, H3K9me histone mark deposition is essential to confer tissue-specific gene expression and preserve the integrity of differentiated muscles (Methot et al. 2021). Moreover, in mammals, HP1 protein isoforms show complex cell type and tissue-specific patterns. While HP1 isoforms had the same pattern in the hepatic tissue, patterns where strikingly different in the lymph nodes (Ritou et al. 2007). However, our approach is relevant, considering the relative contribution of intestinal and hypodermal tissues in worms (Froehlich et al. 2021).

HPL-2 showed a strong correlation with H3K9me1 and H3K9me2 in both tissues analyzed, which was not observed with HPL-1. The different preferences of the two C. elegans HP1 proteins is reminiscent to the reported association of the three Drosophila homologs, HP1a, HP1b, and HP1c to specific classes of chromatin (Schoelz et al. 2021) and their different affinities toward H3K9me isoforms (Lee et al. 2019). In embryos, HPL-2 closely associated with H3K9me1 and H3K9me2, and less with H3 tri-methylated forms (Garrigues et al. 2015). Moreover, >20% of regulatory elements were uniquely enriched for H3K9me2 in this stage, mostly tandem or simple repeats type (Zeller et al. 2016). This could be in line with the tight association between HPL-2, but not HPL-1, and repetitive elements previously reported in other stages (Garrigues et al. 2015; McMurchy et al. 2017). Those repetitive elements are mostly represented by DNA transposon families, conversely to retrotransposon families. HPL-2 could bind to H3K9 di-methylated forms to prevent de-repression of repeats and maintain genome stability during development. The higher proportion of repetitive elements enrichment among HPL-2 peaks in the hypodermis compared with the intestine suggests a specific regulation of genome silencing, highlighting both unique and more general role for HPL-2 during tissue differentiation.

Lastly, the significant underrepresentation of transcribed genes bound by HP1 proteins in either hypodermis or intestine strongly suggests a general repressive role for both HPL-1 and HPL-2. However, the reduced number of peaks (thus genes) shared by all HP1 data sets indicate that they control gene expression in a tissue-specific manner. In fact, in flies, the characterization of HP1a, HP1b, and HP1c protein homologs revealed a tissue-specific pattern and a reduced number of canonical target genes (Schoelz et al. 2021). This is likely influenced by histone modifications, but may also be regulated by phosphorylation of HP1 proteins which alter their association with chromatin (Zhao et al. 2001; Hiragami-Hamada et al. 2011).

Our analysis showed a significant number of genomic regions commonly bound by intestinal HPL-1 and the BLMP-1/PRDM1 transcription factor in two developmental stages. In C. elegans, BLMP-1 is relevant for the proper development of several tissues, such as vulva, hypodermis, and gonad (Horn et al. 2014; Huang et al. 2014; Yang et al. 2015). PRDM1 was first described as responsible for B-cell identity by repressing other transcription factors, thereby controlling indirectly numerous target genes (Shaffer et al. 2002). Moreover, during cell plasma differentiation, PRDM1 recruits histone deacetylase HDAC1/2 and lysine demethylase LSD1 chromatin regulators to repress the mature B-cell gene expression pattern (Su et al. 2009). In worms, the recruitment of HDAC proteins through the binding of HPL-2 to H3K27me3 represses Hox genes (Jedrusik-Bode 2013). We note that the majority of genes bound by both HPL-1 and BLMP-1 are repressed and we speculate that the two proteins could act in parallel to maintain silent genomic regions that are crucial for cell identity. As in plasma cells, BLMP-1 may coregulate with HPL-1 and other epigenetic factors the repression of specific genomic regions in order to control the fate of cells. The specific mechanism behind this remains elusive, but a recent study proposed that BLMP-1 regulates chromatin accessibility during development (Stec et al. 2021).

In summary, this tissue-specific study of HP1 proteins revealed important differences that highlight their relevance as heterochromatic markers for cell identity during development. This potential restriction of plasticity accompanied by changes in other crucial heterochromatin marks, such as histone modifications, opens new questions about the role of chromatin modifiers in this complex process. Lastly, we revealed the unique features of the underexplored HPL-1 homolog in C. elegans, which will encourage further studies to uncover its biological roles.

Supplementary Material

iyad081_Supplementary_Data

Acknowledgments

A very special thanks to Ildefonso Cases from the CABD Bioinformatics Facility for support with data analysis.

Data availability

Plasmids and strains can be requested from the authors. Nematode strains will be sent to the Caenorhabditis Genetics Center (CGC) and will be available to the community. Supplemental files are available at figshare: https://doi.org/10.25386/genetics.22665562. Supplementary File 1 contains the list of peaks bound by HP1 proteins. Supplementary File 2 contains the list of genes bound by HP1 proteins. Supplementary File 3 contains the overlap between HP1 bound genes with tissue-specific expressed genes. Supplementary File 4 contains the overlap between tissue-specific genes bound by HP1 proteins and the list of common genes bound by HPL-1 and BLMP-1 and those that are expressed in the intestine. Data sets generated in this paper are available, and are deposited, at Gene Expression Omnibus (GEO) accession GSE222056 (https://www.ncbi.nlm.nih.gov/geo/).

Funding

P.dl.C.R. was supported by contract BES-2017-081183 from the Spanish Ministerio de Ciencia e Innovación. Research was funded through grants from the Spanish Ministerio de Ciencia e Innovación, the Spanish Agencia Estatal de Investigación, the European Regional Development Fund (FEDER), and the Consejería de Economía, Innovación, Ciencia y Empleo, Junta de Andalucía (CEX2020-001088-M, PID 2019-104145GB-I00, PID2019-105069GB-I00, FEDER 2014–2020_UPO-1260918, and P20_00873).

Author contributions

P.dl.C.R., P.A., and M.A.-S. designed the experiments; P.dl.C.R. and M.J.R.-P. carried out the experiments; P.dl.C.R. analyzed the data; P.dl.C.R., P.A., and M.A.-S. interpreted the results and wrote the manuscript. All authors read, commented, and approved the final manuscript.
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