TP53 are more resistant to MI-773 than wild type TP53. Here, we explored the compound’s therapeutic potential in vitro using a panel of 274 annotated CLs derived from a diversity of tumours. MI-773 exhibited a pronounced selectivity and moderate potency, with anti-tumour activity in the sub-micromolar range in about 15% of the CLs. The most sensitive tumour types were melanoma, sarcoma, renal and gastric cancers, leukaemia, and lymphoma. A COMPARE analysis showed that the profile of MI-773 was similar to that of Nutlin-3a, the first potent inhibitor of p53–MDM2 interactions, and, in addition, had a superior potency. In contrast, it poorly correlates with profiles of compounds targeting the p53 pathway with another mechanism of action. OMICS analyses confirmed that MI-773 was primarily active in CLs with wild type TP53. In silico biomarker investigations revealed that the TP53 mutation status plus the aggregated expression levels of 11 genes involved in the p53 signalling pathway predicted sensitivity or resistance of CLs to inhibitors of p53–MDM2 interactions reliably. The results obtained for MI-773 could help to refine the selection of cancer patients for therapy.MI-773 is a recently developed small-molecule inhibitor of the mouse double minute 2 (MDM2) proto-oncogene. Preclinical data on the anti-tumour activity of MI-773 are limited and indicate that tumour cell lines (CLs) with mutated  The TP53 gene, encoding for p53, is mutated in ~40% of human cancers, the mutation frequency differs between tumour types and ranges from <5% to >90%4. TP53 mutations profoundly affect tumour cell genomic structure, expression, and clinical outlook. Loss of p53 integrity is correlated with poor patient survival for multiple tumour types5. Mouse double minute 2 (MDM2) primarily regulates the expression of p53, which makes it an attractive target for cancer therapy6.The tumour protein p53 is a transcription factor involved in cell cycle regulation, apoptotic cell death, and maintenance of genetic stability9. MDM2 amplification and overexpression are found at a high frequency in soft tissue tumours, e.g., liposarcoma, at a lower frequency in glioblastoma and breast cancer, but not in tumour types like leukaemia, lymphoma, and melanoma. MDM2 overexpression leads to the downregulation of p53 and, consequently, loss of apoptotic function and cell cycle arrest in wild type TP53 tumours and is associated with drug resistance to chemotherapeutics such as cisplatin13. Small molecule inhibitors which occupy the p53-binding pocket of MDM2 disrupt the MDM2–p53 interaction, leading to the stabilisation of p53 and activation of the pathway14. Several MDM2 inhibitors are currently in clinical development15.MDM2 is a ubiquitin ligase that facilitates p53 proteasomal degradation. Upon stress such as DNA damage, the protein–protein interaction between p53 and MDM2 is disrupted, resulting in elevated p53 levels, cell cycle arrest, DNA repair, or elimination by apoptosisKi = 0.88 nM)16. It is active in wild type TP53 cell lines (CLs) from leukaemia and solid tumours in vitro and induces either durable tumour regression or effective tumour growth inhibition in subcutaneously transplanted patient-derived tumour models (PDX). The compound is less efficacious in CLs and PDX with mutated TP5319. Two-Phase I studies were conducted in patients with locally advanced or metastatic solid tumours (mainly wild type TP53) either as single-agent or in combination with the oral MEK1+2 inhibitor pimasertib. In both studies, MI-773 showed an acceptable safety profile21.The MDM2 inhibitor MI-773  is a recent small molecule that binds to MDM2 with high affinity . Since ~60% of all human tumours are wild type TP53, and preclinical data suggest that CLs with mutated TP53 are more resistant to MI-773 than wild type TP5324, it is of particular interest to explore the therapeutic potential of the compound in a large number of haematological and solid tumours with both wild type and mutated TP53. These data prompted us to explore the therapeutic potential of MI-773 in depth. Here, we report the results of this in vitro and pharmacogenomic study, revealing candidate tumours for treatment with MI-773 and a biomarker set for patient stratification.Preclinical and early clinical proof-of-concept studies have shown that small-molecule MDM2 inhibitors block the p53–MDM2 interaction, activate p53 in patients, and have acceptable safety profiles50 values (Abs IC50) of the CLs ranged from 0.11 to 30.8 µM (Supplementary Table 50 of 13.4 µM (IQR: 5.7–17.6 µM). Three distinct patterns of sensitivity appeared in the rank order of the Abs IC50 values , the second subset of 38 intermediate sensitive CLs , and the third subset of 196 resistant CLs . The subset of highly sensitive CLs was enriched in melanoma, mesothelioma, renal cancer, leukaemia, and lymphoma. The sensitivity of CLs within a given tumour type was highly variable  were correlated with the Abs IC50 values obtained from 181 standard anti-cancer agents with a known mechanism of action from our proprietary drug sensitivity database for cytotoxic potency and selectivity26. The agents most closely related to the MI-773 inhibitory profile were three inhibitors of the p53–MDM2 interaction: Nutlin-3a (ϼ = 0.83), RG-7112 (ϼ = 0.64), and YH239-EE (ϼ = 0.48)  type response as that of MI-773  from the COSMIC cancer cell line database27. Nutlin-3a showed also here the highest correlation with MI-773 , confirming MI-773’s mechanism of action  and 0.23 (p = 7.66E−03), respectively; the correlation coefficient of the inhibitor of MDM2–proteasome interaction JNJ-26854165 (Serdemetan) was 0.12 (p = 1.62E−01) and that of the MDMx inhibitor NSC-207895 was 0.09 (p = 3.04E−01).For independent validation of our results, the MI-773 Abs ICion Fig. . Interes50 value of Nutlin-3a was lower in both GDSC1  and GDSC2 databases  than in our in vitro test , and gene expression profiles were available for 237/274 CLs. This CL panel had similar characteristics as the 274-CL panel regarding (sub)types and distribution into the three subsets of MI-773 sensitivity . TP53 mutations were by far the major genetic determinants for resistance to MI-773  . TP53 mutations were present in 69% (163/237) of the CLs in our panel  than that of the wild type TP53 CL group   Fig. . When thµM) Fig. .Fig. 3GeTP53-mutated CLs and the corresponding MI-773 Abs IC50 values. It highlights that 91% of CLs (149/163) with TP53 mutations were strongly resistant to MI-773   was absent in our 237-CL panel. In the overall CL panel, 135 CLs (57%) showed a moderate SCNA at MDM2 loci , which was, however, not associated with higher expression levels of MDM2 and response to MI-773 (data not shown). Thus, resistance to MI-773 in wild type TP53 CLs in our panel was not related to MDM2 gene alterations. When we broadened the analysis to whole-exome mutations and SCNA of other genes present in these 21 wild type TP53 CLs, we did not find any genomic alteration that could explain the resistance to MI-773.However, sensitivity to MI-773 did not only depend on the mutation status of 50 values. For a robust and stringent result, the analysis was carried out by applying three statistical tests , and Spearman correlation test). At the intersection of the three statistical tests, we obtained a total of 552 probe sets significantly associated with the MI-773 Abs IC50  . After removing probe sets not showing consistent gene expression , a total of 31,751 probe sets were tested for an association between transcript expression level and MI-773 Abs IC05) Fig. . From thMDM2, MDM4, PPM1D) have direct protein–protein interaction with TP53; others were involved in the cell cycle , apoptosis , DNA repair (DDB2), and antioxidant defence (SESN1)29  compared with wild type TP53 CLs sensitive to MI-773. The expression of these genes was similarly low in wild type and mutated TP53 CLs resistant to MI-773, except for the TP53 level that was high in the mutated group  and Gene Ontology (GO) biological process (BP) enrichment analyses were performed on the 113 genes with high expression in CLs sensitive to MI-773. The outcome confirmed that the genes were dominantly related to the compound’s mechanism of action with 11 genes associated with the p53-signalling pathway Fig. . Three gp = 2E−04)  in each of the three clusters is similar (2–3 µM), and that of the resistant CLs is a factor 6–8 higher . The analysis showed three clusters of CLs with significant differences in MI-773 response rate (proportion test TP53 mutation status of the CLs (Supplementary Table TP53 had a high score (>7.5) and 115 out of 163 CLs (70%) with TP53 mutations had a low score (≤7.5) . The regression analysis showed that the predictive score was inversely correlated with the MI-733 Abs IC50 values across the 237-CL panel . With this approach, 53 CLs were predicted sensitive to MI-773 (wild type TP53 and a predictive score >7.5) and 184 CLs were predicted resistant (n = 163 with TP53 mutated and 21 wild type TP53 with a predictive score ≤7.5)  Fig. , left. T.5) Fig. .TP53 mutation status   were predicted resistant with Nutlin-3a Abs IC50 > 19.7 µM. The decisional tree’s sensitivity and specificity for predicting Nutlin-3a sensitivity or resistance were 95% and 43%, whereas the positive predictive value for sensitivity was 77% and the negative one identifying resistance was 83%  the predictive score or (c) the combination of both for association with Abs IC50 for the other TP53 related small molecules in the databases. As shown before, TP53 mutation status was strongly associated with CL Abs IC50 of Nutlin-3a (GDSC2) and RG-7112 , to a lesser extent with YH239-EE, PRIMA-1MET, MIRA-1, JNJ-26854165 but not with NSC-207895   and absent for JNJ-26854165. In wild type TP53 CLs only, the association was well preserved for Nutlin-3a and RG-7112, borderline significant for PRIMA-1MET, MIRA-1, NSC-207895 and not significant for YE239-EE and JNJ-26854165. Thus, the decisional tree combining TP53 mutation status and the predictive score showed a significant association with all compounds (Wilcoxon test p < 0.05), which was much more pronounced for compounds targeting the p53–MDM2 interaction than for the others.We finally tested the association between (a) the 10. The current knowledge of the anti-tumour activity spectrum of these compounds is not exhaustive. Although tumours with gene amplification and overexpressing MDM2 and MDM4, the negative regulators of p5331, are obvious candidates for such therapy, other tumours should be targetable with this type of compound.Various classes and generations of small-molecule MDM2 inhibitors have been developed over the last 20 years, of which Nutlin-3a was the first potent inhibitor33, our COMPARE correlation analyses, a large-scale exercise using hundreds of drug sensitivity datasets annotated for the mechanisms of action, showed that the anti-tumour profile of MI-773 was similar to those of Nutlin-3a and RG-7112, other antagonists targeting the p53–MDM2 interaction. In contrast, the study showed that the MI-773 inhibitory profile was poorly correlated with those of compounds targeting the p53 pathway via another mechanism of action . The comparison study also supported that MI-773 had a superior potency over Nutlin-3a.Testing MI-773 in a wide range of CLs demonstrated that MI-773 has potential for a broad range of solid tumour types and haematological malignancies. Melanoma, renal cancer, sarcoma, gastric cancer, leukaemia, and lymphoma were the most sensitive cancer types. In line with the previously reported mechanism of actionsTP53 mutations can be considered, irrespective of their type or localisation, as a universal marker of resistance to inhibitors targeting p53–MDM2 interactions. This was not the case for the other p53-related compounds for which the TP53 mutation status was only poorly predictive. Our study also demonstrated that the sensitivity of wild type TP53 CLs to MI-773 varied considerably; some CLs were strongly resistant. The recently reported results of the inhibitor of p53–MDM2 DS-3032b are in line with our data. TP53 mutations predicted overall resistance. Only a few TP53-mutated CLs were sensitive to MDM2 inhibition, and just like our results, a part of the wild type TP53 CLs was strongly resistant to the compound34. These observations are in accordance with the work of Donehower et al. 5, demonstrating that more than 90% of TP53-mutant cancers exhibit second allele loss of expression, either by mutation, chromosomal deletion, or copy-neutral loss of heterozygosity, leading to alteration of the p53 protein level in most cases. Thus, the type of TP53 mutation and the level of p53 determine the sensitivity of TP53-mutated CLs for p53–MDM2 inhibitors. In wild type TP53 CLs, the large variety in drug response implies that additional factors determine the sensitivity to MDM2 inhibition.With an extended pharmacogenomic analysis, we validated that TP53 CLs only since the number (n = 74) was an explicit limitation to obtain significant results with adjusted p-values. By considering all CLs, we identified hundreds of differentially expressed genes between groups of CLs that were sensitive or resistant to MI-773. Our work supports that unsupervised hierarchical clustering using these genes was not satisfying to classify CLs since tumour type rather than p53–MDM2 functionality was the basis of the clustering. It had hardly predictive value because each cluster comprised sensitive and resistant CLs. The sensitive CLs were mainly wild type TP53, and >80% of the resistant CLs had TP53 mutations.The large size and the transcriptome annotation of our CL panel allowed us to successfully run a differential gene expression analysis to identify additional predictors of MI-773 sensitivity. To this end, we did not select wild type MDM2 itself. Four genes  were retrieved in the 20 most significantly upregulated genes in wild type TP53 tumours in the TCGA database5. Another four genes  belonged to the 10 upregulated genes in circulating wild type TP53 leukaemia cells of patients treated with the MDM2-antagonist RG7112 and were absent in mutated TP53 leukaemia cells35.Pathway analysis of differentially expressed genes highlighted that the top predictors of MI-773 response were 11 upregulated genes closely related to the p53 signalling pathway, including TP53 status strengthened the identification of CLs sensitive for MI-773 and other p53–MDM2 inhibitors Nutlin-3a and RG-7112. Our results further suggest that the predictive score alone was also applicable to mutant p53-reactivating small molecules (MIRA-1 and PRIMA-1MET) and the MDMx inhibitor NSC-207895, but not to MDM2–proteasome interaction inhibitor JNJ-26854165 (Serdemetan). The predictive value of the score has now to be validated in patient tumour samples and in a prospective study. Most probably, some adjustments will be necessary for assessment in tumours containing stroma. Similarly, Zhong et al. 36 developed a 4-gene mRNA MDM2-antagonist therapy predictive signature, which is under investigation, and Ishizawa et al. 34 developed a 175-gene signature. The 175 genes represented the top 1% of genes upregulated in MDM2-inhibitor sensitive CLs. The Spearman correlation between in vitro sensitivity and the 175-gene signature score obtained by Ishizawa et al. 34 was similar to ours (ϼ = 0.67). An additional 1500-gene signature focusing on AML did not improve the prediction, suggesting that more is not better and is not feasible in a clinical setting. In general, biomarkers are not always used in current clinical studies with MDM2 inhibitors, a part used TP53 for patient selection9.To predict MI-773 response, we decided to test a supervised approach to develop a comprehensive gene expression-based scoring system named “predictive score” based on these 11 genes. The low number of genes and their positive association with the sensitivity to the compound present advantages for better applicability in the clinic. Combining the predictive score and the 37 showed the efficacy of MI-773 in glioblastoma. However, further experiments with orthotopically implanted PDX models demonstrated that the low penetration through the blood–brain barrier limited MI-773’s efficacy. The compound is a substrate of P-glycoprotein limiting its distribution to the brain by active efflux and the authors proposed a combination therapy with efflux transporter inhibitors38. In another aspect, it was observed thatw the treatment of dedifferentiated liposarcoma patients with MI-773 can cause the emergence of resistant TP53-mutated clones39. For long-term control of the disease, combination therapies have been proposed. The combination of MI-773 and pimasertib, an oral MEK1/2 inhibitor, was promising in wild type TP53 preclinical melanoma models in vivo21. The subsequent Phase I clinical study showed that the safety profile of the combination was consistent with the safety profiles of both drugs individually, and preliminary anti-tumour activity was observed21. Other combinations of MDM2 inhibitors with chemotherapeutic or targeted agents are being explored in early clinical studies such as cytarabine, BCL-2 (venetoclax), BRAF (trametinib), MEK (dabrafenib), CDK4/6  inhibitors, and immune checkpoint inhibitors41.Apart from the results of our study, other findings should be considered in the development of MI-773. Kim et al. 42. This approach requires large sets of molecularly annotated preclinical models. It is crucial to first understand the mechanism behind the sensitivity and resistance of new anti-cancer agents before testing the compound in vivo in tumour models, e.g., PDX. Given the inter- and intra-tumour heterogeneity, in vitro screening of compounds should preferably be performed in hundreds of CLs, allowing statistical analysis. The accuracy and reliability of OMICS data, usually obtained from accredited laboratories, is also a prerequisite for the success of such studies. The microenvironment of tumour models in vivo will add another layer of complexity to understand the effect of a drug on sensitivity and resistance.The pharmacogenomic work described here was performed in the context of the development of our “Cancer Data Mining” platform. Our study demonstrated that the drug and molecular information available on our platform is relevant for validating the mechanism of action of compounds and targets, discovering candidate tumours for therapy, and early identification of predictive biomarkers. The concept of our approach is based on testing associations between the sensitivity of CLs for a drug and the basal gene expression levels or genomic alteration profile of the CLs, which recently was successful in revealing mechanisms of action of drugs and protein targetsTP53 haematological and solid tumour types. TP53 status combined with the gene expression-based predictive score may help to infer tumour response to this inhibitor. Additional studies in vivo are needed to validate the anti-tumour effect and assess MI-773 toxicity and other studies in independent cohorts to validate the predictive score. Furthermore, combination studies with p53–MDM2 inhibitors are inevitable and warrant further investigation.In conclusion, the combination of in vitro preclinical investigations and pharmacogenomic studies extended the therapeutic options of the p53–MDM2 inhibitor MI-773 to a broad range of wild type MI-773   and Nutlin-3a  were purchased from Selleckchem . The drugs were dissolved in DMSO to obtain a stock solution, which was kept at 4 °C, and immediately before use further diluted with culture medium to concentrations required for the in vitro experiments.2 in the medium recommended by the provider . The CLs were mycoplasma free.Two hundred and seventy-four CLs from the Oncotest GmbH repository  Germany GmbH) were used in the study (Supplementary Table The 274-CL panel consisted of 222 CLs derived from solid cancers including 68 CLs (25%) from the digestive system , 49 (18%) from the urogenital tract , 43 (15%) from the respiratory system , 10 small cell lung (SCLC) and five mesotheliomas), 15 (5%) from breast cancer, 13 (5%) from sarcomas , 12 (4%) from head and neck (HNSC), 12 (4%) from melanomas, and nine (3%) from the central nervous system  and one epidermoid carcinoma CL (A431) classified as skin tumour (from vulva). The 52 haematological CLs included 27 leukaemia (10%) , seven chronic myeloid leukaemia (CML), one chronic lymphocytic leukaemia (CLL)) and 25 lymphomas (9%) (11 multiple myelomas (MM), four Burkitt, five diffuse large B-cell (DLBC), one Hodgkin and four unclassified).44. Briefly, cells were harvested from exponential phase cultures, counted, and seeded in 96-well flat-bottom microtiter plates at a cell density of 4000–30,000 cells/well, dependent on the growth rate of the CLs. Haematologic and CLs from SCLC were grown in suspension cultures. After a 24-h recovery period to allow the cells to resume exponential growth, 10 μl of culture medium (six control wells/cell line/plate) or culture medium with MI-773 was added. The compound was serially diluted and applied at ten concentrations in half-log increments from 0.001 up to 30 µM in singlicate and treatment continued for four days. Cells were then washed with 200 µl phosphate-buffered saline to remove dead cells and debris. Next, 200 µl of a solution containing 7 µg/ml propidium iodide and 0.1% (v/v) Triton X-100 was added to the wells. After 1–2 h incubation at room temperature, fluorescence was measured using an Enspire® multimode plate reader  to quantify the number of viable cells.A modified propidium iodide assay was used to screen the CLs, growing in a 2D-monolayer culture, for sensitivity to MI-77350 values, absolute and relative, were calculated by a four-parameter non-linear curve fit (Charles River Data Warehouse Software).Drug effects on cell proliferation and survival were expressed as Test/Control × 100 (%) values, using the mean fluorescence signal of treated and control wells. IC50 values determined the overall potency of MI-773. If an individual IC50 value could not be determined within the examined dose range (because the compound was either too active or lacked activity), the lowest or highest concentration studied was used for the value calculation.The median of all individual IC45 (downloaded 2017). In this case, processed whole-exome mutation data were directly downloaded. CEL files of both SNP6.0 and Human Genome U133 Plus 2.0 Array were processed together with the internal CL profiles to limit batch effects.Most of the CLs tested for MI-773 were characterised by 4HF Biotec GmbH as described below. CLs were characterised by next-generation sequencing for whole-exome mutations, single nucleotide polymorphism (SNP) array (Affymetrix Genome-Wide Human SNP Array 6.0 (SNP6.0)) for SCNA and gene expression array for transcriptomic profiles (Affymetrix Human Genome U133 Plus 2.0 Array). Missing profiles and additional data used for the biomarker validation were obtained from the Cancer Cell Line Encyclopedia46. In brief, cells were placed on ice, washed three times with cold phosphate-buffered saline to remove any traces of medium. Adherent cells were removed from the cell culture dish using sterile cell scrapers. Cell pellets were frozen in liquid nitrogen immediately after the last washing step and stored at −80 °C until extraction. On the day of DNA and RNA extraction, the frozen cell pellets were placed on ice, and then the appropriate lysis buffer was added.DNA and RNA were extracted, according to the adapted protocols previously describedFor DNA extraction, proteinase K buffer  was added to the lysed cell suspension, and the mixture was incubated overnight at 55 °C. The lysates were digested with DNase-free RNase , the DNA was extracted with phenol/chloroform/isoamyl alcohol and precipitated with ethanol. The pellets were washed and resuspended in TE buffer . The DNA integrity of each preparation was checked on a 1.3% agarose gel, and the quantity and purity were analysed with a NanoDrop 2000 spectrophotometer .™ miRNA isolation kit  according to the manufacturer’s instructions. The RNA quality and purity were controlled with a NanoDrop 2000 spectrophotometer (RRID:SCR_018042), and RNA integrity by a Bioanalyzer .RNA was extracted using the mirVana47. Signal values were log2 transformed.Microarray gene expression profiles were generated by using the Affymetrix Human Genome U133 Plus 2.0 GeneChip arrays according to Affymetrix recommendations at the AROS laboratory . CEL files were subjected to internal quality control measures using Affymetrix RLE/NUSE. Gene expression signal values were extracted directly from the CEL files using the GeneChip robust multi-array average (gcrma) expression algorithm. This was achieved using the R package “gcrma” from the Bioconductor projectWhole-exome sequencing was performed at the GATC laboratory . The enriched exonic DNA was sequenced on an Illumina Hiseq2000, 2500 or 4000  with a minimum coverage of 100×.48. After the alignment to the human reference genome (Burrows–Wheeler Aligner version 0.7.17)49, the quality of BAM files was assessed by Qualimap 2.2.1 (RRID:SCR_001209) to obtain the percentage of mapped reads and coverage of reads to the targeted exons (as defined by Agilent)50. The mapped reads were recalibrated with GATK (RRID:SCR_001876) BaseRecalibrator function after duplicates removal and indel local realignment51. Reads mapped around indels were realigned used the GATK’s IndelRealigner function before performing the variant calling step. Variants were detected independently using three different variant callers: the GATK UnifiedGenotyper, the combination of Samtools (RRID:SCR_002105) mpileup and bcftools, and Freebayes (RRID:SCR_010761)54. Only variants identified by all three tools, showing a minimum number of variant-supporting reads of three and a minimum variant frequency of 5%, were further analysed. Candidate mutations were annotated with SnpEff (RRID:SCR_005191) by selecting only single-nucleotide variants and insertions/deletions (Indels) with a high or moderate protein impact from UCSC or Ensembl transcripts55, and by filtering out known polymorphisms from annotation databases if a variant (1) has at least three allele counts from Hapmap (RRID:SCR_002846) or CGI 69 genomes or EVS + 1000 Genomes or (2) shows more than 5% of a minor allele in at least one population from dbSNP (RRID:SCR_002338). The quality control of variant detection analysis was evaluated with SnpEff by computing and validating the transition/transversion ratio from SNP found in exons.Raw reads were subjected to FastQC (RRID:SCR_014583) to calculate read quality metrics56.The detection of chromosomal alterations was performed with the Affymetrix SNP6.0 array following the standard protocol recommended by the manufacturer at the AROS laboratory . According to Affymetrix guidelines, CEL files were subjected to internal quality control measures, including contrast quality control and MAPD threshold using Genotyping Console Software . SCNA values (0–14) were determined from the CEL files using the PICNIC algorithm57. p-values < 0.05 were considered statistically significant. Data are represented as means ± standard deviation (SD), and median (interquartile range (IQR)). For biomarker screening, drug response data were treated either as continuous variables using absolute IC50 (Abs IC50) or as categorical variables ). To identify whole-exome mutations and SCNA associated with drug response, for each gene, samples with at least one alteration (whole-exome mutation or SCNA ≥ 8 or SCNA = 0) were given the value 1 and no alteration was given 0, resulting in matrices of binary representation. Next, binary matrices of genomic alterations  were used for a gene per gene statistical analysis for association with drug sensitivity (Abs IC50 and drug sensitivity groups). Wilcoxon rank-sum test was performed between continuous variables (Abs IC50) and binary categorical variables (mutated versus not mutated or high SCNA versus no SCNA). Fisher’s exact test was used for independence between two categorical variables. For any test between two continuous variables, statistical dependence between the rankings of the two variables was evaluated by Spearman’s rank correlation test.Statistical analyses were carried out using The R Project for Statistical Computing  and associated packages from Bioconductor in the Linux operating system 50 or sensitivity groups was tested using Limma (package version 3.34.9)59, t-test and Spearman tests. A cut-off was set at 10.7 µM to dichotomise sensitive CLs to MI-773 from resistant ones (which corresponds to 30% of the 237-CL panel). The gene expression profiles were curated by removing probe sets with lack of expression (probe sets < 5 were excluded), resulting in 31,751 probe sets with consistent expression. They were tested for an association between their expression levels and MI-773 Abs IC50 values. Probe sets significantly associated with sensitivity to MI-773 in all three statistical tests (adjusted p < 0.05) were then filtered by Jetset curation52 to retain unique gene transcripts. Those with a pronounced differential expression between CLs sensitive and resistant to MI773 (log2 fold difference > ±0.5) were used to perform unsupervised hierarchical clustering using the function clustering from the EMA library (version 1.4.4). The ComplexHeatmap package (version 2.4.3) was used to create and visualise the clusters and heatmaps.The association between gene expression and drug Abs ICp-values were adjusted with Benjamini and Hochberg correction as a conservative method for probability thresholding to control the occurrence of false positives60. Lollipop mutation diagrams were generated using the lollipops software61. To gain insight into the nature of the gene subset that were positively associated with MI-773 sensitivity, Kyoto Encyclopedia of Genes and Genomes (KEGG) and the GO BP-enrichment pathway analysis was carried out with enrichKEGG and enrichGO (ont = “BP”), respectively in clusterProfiler 62.For each statistical test with multiple testing hypotheses, Anti-tumour activity and genomic data were unified in an in silico platform called “4HF Cancer Data Miner”, dedicated to accelerate R&D efforts in drug discovery and development, optimise target evaluation, identify promising clinical therapeutic areas, and discover putative predictive biomarkers.Further information on research design is available in the Supplementary InformationReporting Summary


Sight depends on the tight cooperation between photoreceptors and pigmented cells, which derive from common progenitors through the bifurcation of a single gene regulatory network into the neural retina (NR) and retinal-pigmented epithelium (RPE) programs. Although genetic studies have identified upstream nodes controlling these networks, their regulatory logic remains poorly investigated. Here, we characterize transcriptome dynamics and chromatin accessibility in segregating NR/RPE populations in zebrafish. We analyze cis-regulatory modules and enriched transcription factor motives to show extensive network redundancy and context-dependent activity. We identify downstream targets, highlighting an early recruitment of desmosomal genes in the flattening RPE and revealing Tead factors as upstream regulators. We investigate the RPE specification network dynamics to uncover an unexpected sequence of transcription factors recruitment, which is conserved in humans. This systematic interrogation of the NR/RPE bifurcation should improve both genetic counseling for eye disorders and hiPSCs-to-RPE differentiation protocols for cell-replacement therapies in degenerative diseases. The gene regulatory network controlling the bifurcation of common progenitors into the neural retina and retinal-pigmented epithelium programs remains poorly understood. Here the authors study transcriptome dynamics and chromatin accessibility during this process in zebrafish, revealing network redundancy, as well as context-dependent and sequential transcription factor activity. Fate map experiments in vertebrates have shown that the precursors of the neural retina (NR) and retinal pigmented epithelium (RPE) derive from the undifferentiated eye field2. In the permanently growing retinas of teleost fish, stem cells located at the ciliary marginal zone are capable of producing both cell types3. Furthermore, in tetrapods RPE precursors retain a certain potential to acquire NR identity4 and vice versa5.Vision depends on the close physical and physiological interaction between pigmented cells and photoreceptors. Pigmented cells protect photoreceptors by maintaining their homeostasis through growth factors secretion, visual pigments recycling, and outer segments phagocytosis6. The specification of both retinal domains occurs simultaneously to the folding of the vesicle into a bi-layered cup and entails profound cell shape changes in each domain. Precursors at the LL elongate along their apicobasal axis, differentiate as NR, and constrict basally to direct the folding of the retinal neuroepithelium8. In contrast, precursors at the ML either acquire a squamous epithelial shape and differentiate as RPE, or flow into the LL to contribute to the NR domain12. In other vertebrates, the specification of the NR/RPE domains and the morphogenesis of the optic cup follow a pattern similar to that of the zebrafish, though the relative weight of the different morphogenetic mechanisms may vary among species13.In zebrafish, the RPE and NR presumptive domains start differentiating at the optic vesicle stage from the medial (ML) and lateral (LL) epithelial layers, respectively14. Eye identity is established in the anterior neural plate by the early activation of a gene regulatory network (GRN) pivoting on a few key regulators collectively known as eye field transcription factors (EFTF): including Lhx2, Otx2, Pax6, Rx, or Six315. Upon the influence of inductive signals derived from the lens epithelium (FGFs) or the extraocular mesenchyme (Wnts and BMPs), the eye field network branches into the mutually exclusive developmental programs of the NR and RPE16. Classical genetic experiments performed mainly in mice have identified key nodes of the NR and RPE specification networks. The TF-encoding gene Vsx2 (previously known as Chx10) was identified as the earliest determination gene differentially expressed in NR but not in RPE precursors17. Vxs2 plays an essential role in specifying the NR domain by restraining the RPE identity through direct repression of the TF Mitf20. Other homeobox regulators, many inherited from the eye field specification network, contribute to the network of NR specifiers. This list includes Lhx2, Sox2, Rx, Six3, and Six6 genes, which are required either for NR maintenance or for suppressing RPE identity22. The establishment of the RPE network depends instead on the cooperative activity between Mitf and Otx factors24. Classical experiments in mice showed that inactivation of either Mitf or Otx genes results in an RPE differentiation failure, with the alternative acquisition of NR molecular and morphological features27. More recently, mutation of the main effectors of the Hippo pathway, Yap and Taz, showed the essential role of these co-regulators in the differentiation of the RPE lineage29.During the last decades, numerous studies have investigated how the RPE and NR domains get genetically specified30. Systematic attempts to reconstruct retinal GRNs using next-generation sequencing (NGS) methods have focused mainly on the differentiation of neuronal types at later stages of development or in epigenetic changes linked to retinal degeneration33. Very recently, scRNA-seq has been proved a useful tool to characterize cell heterogeneity and infer differentiation trajectories in human tissues and retinal organoids35. However, a comprehensive analysis of the NR and RPE bifurcating networks would require a deeper sequencing coverage approach, while dealing with the limited cell population size at optic cup stages.Despite the identification of these key regulators, the architecture of the NR and RPE specification subnetworks is far from being well understoodIn this study, we address previous limitations by applying a combination of RNA-seq and ATAC-seq on sorted NR and RPE populations. Using the zebrafish retina as a model system, we follow transcriptome dynamics and chromatin accessibility changes in both cell populations, as they depart from a common pool of progenitors. The cross-correlation of RNA-seq and ATAC-seq data allow us to identify activating and repressing cis-regulatory elements (CREs), discover enriched transcription factor (TF) binding motifs, and unveil relevant downstream targets for the main specifiers. Our analyzes confirm previously known TFs as central nodes of the eye GRNs, and more importantly, provide information on their recruitment sequence both in zebrafish and human cells.2. It is important to state that at the end of this window (23 hpf), neurogenesis has not started yet in the retina, neither the RPE display pigmentation. We used the transgenic lines E1_bHLHe40:GFP and vsx2.2:GFP to isolate the NR and RPE populations at 18 and 23 hpf by FACS  throughout development and between domains , and their average chromatin accessibility fold change was higher than that of NR associated DOCRs  in the morphologically divergent NR and RPE domains. To this end, we performed ATAC-seq experiments from isolated NR and RPE precursors at 23 hpf. A total of 238,369 open chromatin regions (OCRs) were detected using this approach. After statistical analysis, a fraction of the peaks were identified as DOCRs, corresponding to putative CREs that are more active in the NR than in the RPE or vice versa. Approximately 12.6% of all peaks (30172 peaks) were differentially open with an adjusted 39, to obtain insight into DOCRs DNA methylation (5mC) dynamics. Supervised clustering (k = 2) of 5mC patterns separates both datasets into two well-defined clusters  morphants in whole 24 hpf embryos39. Data from two independent MO knockdown experiments revealed that their chromatin accessibility signature is significantly  reduced for NR ATAC-seq peaks in tet morphants when compared to wild type embryos, even when whole embryos were assessed  and hydroxymethylome (TAB-seq) data of zebrafish embryogenesis and adult tissues41. By intersecting RNA-seq and ATAC-seq datasets, we observed a substantial overlap between DEGs and genes associated with DOCRs at 23 hpf. Thus, 47% of all DEGs are associated with at least one DOCR  was significantly higher for TFs than for a control sample of randomized DEGs   Fig. . More im01) Fig. . This op01) Fig. .Fig. 2CRrx3, an early eye specifier with a known role in optic vesicle evagination45; and her factors required to maintain the progenitor neural state46  is shared by members of the family expressed in RPE, such as mitfa, bHLHE40, bHLHE41, and tfec  appeared associated with many GO terms, others were more specific: such as the case of mitfa that was associated only with pigment cell differentiation  are under the antagonistic regulation of the NR and RPE GRNs  in committed RPE cells , as well as pigmentation genes (tyr and tyrp1b), were significantly reduced in yap −/− taz −/− double mutant head tissue at 18 hpf as determined by RT-qPCR  displayed eye malformations, such as microphthalmia, eye fissure closure defects, and/or hypopigmentation , pluripotent stem cells progressively change their morphology to a cobblestone appearance, acquiring a light pigmentation at the end of the fourth week ; mature RPE markers ; known RPE specifiers activated in the second wave of gene expression ; desmosomal components ; and TFs and signaling molecules activated in the first wave of gene expression   also clustered together reaching a maximum expression level in the fourth week of culture. These findings indicated that despite the very different time scales of the developmental programs in these far-related vertebrate species, hours in zebrafish, and days in humans, their RPE regulatory networks share a common logic of two waves in the TFs recruitment sequence.A second important finding derived from our gene expression clustering analysis was the identification of two waves of transcriptional regulators during the specification of the RPE in zebrafish. Understanding this TF recruitment sequence in humans may have important basic and translational applications. We thus asked whether the same eek Fig. . Using RL2) Fig. . This an6, have hindered any systemic approach to investigate the architecture of the specification networks as they branch. Using tissue-specific transgenic lines, we have isolated NR and RPE precursors by FACS. Although expression driven by the RPE-specific element E1_bHLHe40 has also been reported in the ciliary marginal zone and periocular neural crest cells, this is only reported after optic cup folding38. Therefore, only minor contamination, if any, would be expected in RPE precursors isolated at 23 hpf. The combination of isolated cell populations with the high sensitivity and deep sequencing coverage of the RNA-seq and ATAC-seq methods51, allowed us to overcome previous constraints: permitting not only the detection of transcriptomic variations and active cis-regulatory modules but also helping to define hierarchical relationships among the core components of the network.Here we have used a double RNA-seq/ATAC-seq approach to zoom into the bifurcation of the NR/RPE developmental programs, which will give rise to specialized neurons and pigmented squamous cells respectively. The transient nature of this differentiation process, as well as the limiting size of the cell populations involved52. Therefore, although this estimate should be taken cautiously when individual CREs are examined, it is a valid approach when conclusions are driven from genome-wide analysis. In this study, we identified approximately 30,000 chromatin regions differentially open (DOCRs) between the NR and RPE domains. The examination of their methylation status, as well as their overlap with H3K27ac and H3K4me3 marks, indicates that most of these regions (≈95%) correspond to initially inactive enhancers that get progressively demethylated and activated at the phylotypic period, a behavior reported for developmental genes in general39. A much smaller cluster (≈5%) matches hypomethylated constitutively active promoter regions , which is shared by mitfa, bHLHE40, bHLHE41, and tfec. In agreement with this, the simultaneous elimination of mitfa and mitfb has no apparent consequences on RPE specification or pigmentation in zebrafish24. All these observations further point to a broad redundancy and cooperativity among the main nodes of the eye specification networks.One of our main observations is that NR and RPE networks are remarkably robust. This is the case particularly in teleosts, in which whole-genome duplication resulted in additional copies of eye specifiers. In zebrafish, several homeobox TFs expressed in the NR converge on the 5′–TAATT–3′ motif, including vsx1, vsx2, rx1, rx2, rx3, lhx2b, lhx9, hmx1, and hmx4. Our motif discovery predictions suggest these proteins, together with sox factors, may co-regulate the same genes and cooperate within the same CREs, although these are theoretical predictions that may require validation by direct ChIP-seq studies. Supporting a co-regulation, the mutation of genes encoding for retinal homeobox TFs, such as 7. In contrast, here we show that a significant number of keratins and other desmosomal genes get recruited in the presumptive RPE hours before this tissue acquires its distinctive pigmentation. Although keratins and plaque proteins have been reported as RPE markers in several vertebrate species59, their contribution to the morphogenetic program of this tissue remains unexplored. Given the role of desmosomal plaques in conferring resistance to mechanical load49, it is tempting to hypothesize that the activation of these cytoskeletal genes may be linked to RPE precursors adapting their cytoskeleton to increased tissue tension as they flatten. Motif enrichment analysis of CREs linked to desmosomal genes, together with the genetic evidence here provided by yap −/−; taz −/− double mutants and Tead crispants, support a role for Tead TFs in the activation of keratin genes at the RPE. Indeed, several keratin , and desmosomal genes  have been identified as targets for Yap/Tead complexes by ChIP-seq studies in mammalian cells60 and DamID-seq studies in zebrafish embryos61. Thus, the direct transcriptional regulation of keratins and plaque genes by Yap/Tead complexes seems a conserved theme across tissues and vertebrate species.As expected, cell shape changes associated with the acquisition of the NR and RPE identities have a clear reflection at the transcriptomic level. The differentiation of the NR entails the activation of cytoskeletal components associated with microtubules polarization, in agreement with the neuroepithelial character of the tissuemitfa or otx2, which were previously considered among the earliest RPE specifiers47. Their delayed peak of expression occurs after the specification and flattening of RPE precursors have commenced, and rather coincides with the onset of pigmentation in the tissue at 23 hpf. This agrees with previous studies indicating a cooperative role for Otx and Mitf in the direct activation of the melanogenic gene battery23. A detailed expression study in zebrafish also reported two separated phases for RPE specification, the first of which is mitf independent36. Here we show that the early phase of specification entails the recruitment of a different set of transcriptional regulators, including smad6b, tead1b, tead3b, tfap2a, tfap2c, tcf12, and vgll2b. Some of these TFs, or their cofactors, act as upstream regulators of Otx and Mitf, such is the case for Tcf62 and Tead-cofactors Yap and Taz29. Others, such as tfap2a, play an important role in RPE specification, although their hierarchical role within the RPE GRN remains unclear48. Finally, here we also describe a similar sequence of TF recruitment in human differentiating RPE cells. Thus, despite the different morphology of the cells  and the large evolutionary distance (≈450 mya), the regulatory logic that specifies the RPE seems largely conserved across vertebrates.Arguably one of the most notable observations in this study is the relatively late peak of expression of genes such as 63. Importantly, our findings uncover an unanticipated regulatory logic within the RPE specification network. This provides critical information to improve hiPSCs-to-RPE differentiation protocols, a key step in cell replacement strategies for retinal degenerative diseases.Our results may be relevant to identify causative genes for eye hereditary diseases, as mutations in many nodes of the eye GRNs result in congenital eye malformationsDanio rerio) AB/Tübingen (AB/TU) wild-type strains, the transgenic lines tg(vsx2.2:GFP-caax)8 and tg(E1_bHLHe40:GFP)38 .The zebrafish . RPE at 18 and 23 hpf were isolated from whole tg(E1_bHLHE40:GFP) embryos. A FACSAriaTM Fusion flow cytometer (BD FacsDiva Software 8.0.1) was used to recollect only the GFP + cells  following the manufacturer’s protocol. Possible DNA contamination was eliminated by treating the RNA samples with TURBO DNAse-free (Ambion). The concentration of the RNA samples was evaluated by Qubit (Thermo Fisher), and then the samples were used for subsequent applications.61. For primer sequences, see Supplementary Tables HPRT1 and GAPDH were used as housekeeping genes for human samples, whereas eef1a1l1 was used for zebrafish samples.cDNA retrotranscription and qPCR were performed as describedp-value < 0.05 as the cutoff for statistical significance of the differential expression. Multidimensional scaling analysis (MDS) was performed using the function MDSplot of the CummeRbund package in R 3.6.1. Soft clustering of time-series gene expression data was done for all the transcripts with variance among the five conditions ≥3 using the R package Mfuzz with m = 1.565. The TF transcript subset was extracted from the total list of genes using the tool “Classification System” of PANTHER66 filtering for the protein class “transcription factors” (PC00218). Some TFs not present in the database for annotation issues  were added manually. The cytoskeleton component subset was obtained retrieving all the genes belonging to GO term “cytoskeleton” (GO:0005856), including all the child and further descendant GO terms, with biomaRt. Hierarchical clustering was defined with R function hclust with agglomeration method “complete”. Heatmap representation was obtained using the R package pheatmap. Transcriptomic variations were plotted using exclusively transcripts that resulted to be differentially expressed from the comparison between at least two of our experimental conditions. TFs and cytoskeleton components were filtered using the same methodology used for Mfuzz clustering. Gene ontology analysis was performed with the online tool GOrilla67 or Panther66 using two unranked lists of genes (target and background lists).RNA was extracted from sorted cells and then treated with DNAse as described above. rRNAs were eliminated from the samples with Ribo-Zero® rRNA Removal Kit (Illumina) prior to library preparation. Samples were sequenced in SEx125bps or PEx125bps reads with an Illumina Hiseq 2500. We obtained at least 35 M reads from the sequencing of each library. Three biological replicates were used for each analyzed condition . All heatmaps were made using Deeptools80 and Gene ontology enrichments were calculated with GREAT72. ATAC-seq reads were counted using BEDtools81 and statistics were performed in R.Whole-genome bisulfite sequencing and TET-assisted bisulfite sequencinghttps://www.crisprscan.org/)82 and synthesized following described protocols83. All the sgRNAs were selected to target the first half of the CDS in exons resulting actually expressed in the eye tissues from our RNA-seq data , with an efficiency score > 58 and no predicted off-targets . Before sample collection, a clinician and a researcher provided detailed information to the donor about the procedure, the research project, the implications for his/her health, and his /her rights on the biological sample and its derivatives. Then, the donor, the clinician, and the researcher signed an Informed Consent sheet. The primary biological sample was obtained at the University Hospital Virgen Macarena  with the participation of the Public Health System Biobank (BBSPA), which generated the codes for the pseudonymization of the samples. The donor provided 4 mL of peripheral blood using a regular arm venipuncture procedure. From the fresh blood sample, mononuclear cells were enriched and reprogrammed. Cells were maintained in feeder-free adherent conditions onto Matrigel-covered plates in standard incubation at 37 °C, 5% CO2, 20% O2. hiPSCs were fed every two days with mTser1 serum-free culture medium and passaged every 5-7 days depending on confluency. Dispase was used for gentle dissociation for passage. A 6-well plate with undifferentiated, well-grown hiPSCs was the starting point of the experiment (Day 0). To induce RPE differentiation culture medium was changed to the following: KO DMEM, KSR 15%, Glutamax 2 mM, non-essential aminoacids 0.1 mM, β-mercaptoethanol 0.23 mM, Penicillin/streptomycin. Differentiating cells were harvested directly in Trizol LS (Invitrogen) at day 0, and weeks 1, 2, 3, and 4 for gene expression studies.Human hiPSCs were obtained, after informed consent, from peripheral blood monocytes by cell reprogramming using a non-integrative Sendai virus vector as describedFurther information on research design is available in the Supplementary InformationPeer Review FileDescription of Additional Supplementary FilesSupplementary Dataset 1Supplementary Dataset 2Supplementary Dataset 3Supplementary Dataset 4Supplementary Dataset 5Supplementary Dataset 6Supplementary Dataset 7Supplementary Dataset 8Supplementary Dataset 9Supplementary Dataset 10Supplementary Dataset 11Supplementary Dataset 12Supplementary Dataset 13Supplementary Dataset 14Supplementary Dataset 15Supplementary Dataset 16Reporting Summary


Transposable elements (TEs) initially attracted attention because they comprise a major portion of the genomic sequences in plants and animals. TEs may jump around the genome and disrupt both coding genes as well as regulatory sequences to cause disease. Host cells have therefore evolved various epigenetic and functional RNA-mediated mechanisms to mitigate the disruption of genomic integrity by TEs. TE associated sequences therefore acquire the tendencies of attracting various epigenetic modifiers to induce epigenetic alterations that may spread to the neighboring genes. In addition to posting threats for (epi)genome integrity, emerging evidence suggested the physiological importance of endogenous TEs either as cis-acting control elements for controlling gene regulation or as TE-containing functional transcripts that modulate the transcriptome of the host cells. Recent advances in long-reads sequence analysis technologies, bioinformatics and genetic editing tools have enabled the profiling, precise annotation and functional characterization of TEs despite their challenging repetitive nature. The importance of specific TEs in preimplantation embryonic development, germ cell differentiation and meiosis, cell fate determination and in driving species specific differences in mammals will be discussed. Transposable elements (TEs) were first discovered in maize in the late 1940s . TEs havMost TEs contain numerous copies, which makes it difficult for scientists to map each TE sequences to the exact genomic location with second-generation short read sequencing platforms. However, in the last few years, advanced third-generation sequencing technologies  have enTEs are usually silenced by epigenetic modifications, including DNA methylation and histone modifications –14. SomeBRCA2) [APC) [RB1) [., are correlated with DNA hypomethylation and TE deregulation [Some of the activated TEs have the ability to insert into other genomic sites, the processing of which can cause DNA double-strand breaks (DSBs). Gasior et al. documented that the transfection of LINE-1 into HeLa cells induces DSBs and G2/M cell cycle arrest . AlthougBRCA2)  or tumor2) [APC)  and retiC) [RB1) , they magulation , 32, 33.gulation . Lee et gulation .. investigated 15 cancer types in 7,769 tumor and 625 normal tissue datasets to identify 129 TE-related promoter activation events. The authors showed that the global profile of these TEs is associated with 106 oncogenes across 3,864 tumors, and TEs are the cause of oncogenic activation [Even without transposition, the presence of TE sequences may still disrupt (epi)genome stability. TE enriched sequences can be found in the flanking sequences of DSBs in cancer cells. It is suggested that during DNA replication, short inverted repeats such as the Alu element may form a secondary hairpin structure, which can lead to replication stalling and even DNA DSB formation , 37. On tivation , 39, whitivation , 38. As tivation , 40–43, tivation .Fig. 1GlGlobal DNA hypomethylation associated with de-repression of TEs can be observed in normal aging cells as well , but maySeveral strategies for protecting host cells from TE-derived disruption have emerged during evolution. Both transcriptional and posttranscriptional pathways are involved in TE regulation. The consummate management of TEs is presumably performed with the coordination of DNA methylation, histone modifications, and small RNA-mediated RNA degradation in mammalian cells.Among the TE modulation machineries, DNA methylation is used for long-term TE surveillance in mammals. Both LTR and non-LTR retrotransposons are inhibited by DNA methylation , 47. In . examined the complete DNA sequences of 53 organisms, and the results supported the original hypotheses that DNA methylation enables TE-driven genome expansion. The results of these analysis also indicated that DNA methylation spreads to the flanking host DNA sequences associated with the inserted TEs [Thirty years ago, Prof. Timothy Bestor hypothesized that the DNA methylation machinery evolved from immune mechanisms in prokaryotes designed to protect against phage infection into gene expression and genome structural modulation in large-genome plants and vertebrate animals, including silencing of TEs and other repeat sequences to reduce their exposure to the transcriptional machinery . Recentlrted TEs .th carbon of cytosine , catalyzed by a family of DNA methyltransferases (DNMTs) [DNA methylation in mammals predominantly take place on the 5 (DNMTs) . DNMT1 t (DNMTs) –52. DNMT (DNMTs) , 54. Ano (DNMTs) , 56. DNA (DNMTs) –59.Post-translational histone modifications, including acetylation, methylation and ubiquitylation, collaborate with DNA methylation machineries to accomplish multiple layers of epigenetic modulation . The repKrüppel-associated box zinc finger protein (KRAB-ZFP)- KRAB-associated protein-1 (KAP1)-mediated silencing is an interesting system that coevolves with TEs and is critical in early embryogenesis. Its targeting might be adapted to new retroelements through evolutionarily changing the DNA-binding region , 66. KRAThe small RNA-mediated pathway is another mechanism that manages gene expression in a sequence-dependent manner. Additionally, it is vital for controlling and counteracting TE transcripts, especially at the developmental stages when repressive DNA methylation and histone marks are modified during epigenetic reprogramming. In germ cells and early embryos, the DNA methylation profile changes dynamically during development . RNA intJoint protection by DNA methylation, histone modification, and small RNA-mediated regulation defends against invasion by TEs. The crosstalk between these strategies affords different layers of retroelement regulation and modulates the orchestration of gene expression.Accumulating evidence suggest that TEs acquire important physiological functions through evolution. Several LTR retrotransposon-derived genes have been discovered in the human genome, domesticated to neogenes of functional proteins. These include sushi/Mart [shi/Mart , paraneoshi/Mart , SCAN -seq analyses in human and mouse leukemia cell lines (K562 and MEL) and lymphoblast cell lines (GM12878 and CH12), researchers have shown that TE sequences are present in 20% of transcription factor binding sites in immune cells in which neighboring areas show open chromatin marks, including DNA hypomethylation, H3K4me1, H3K4me3 and H3K27ac. In addition, LTRs comprise the majority of TE-derived binding peaks in human . FurtherTE-containing transcripts can be processed into microRNAs (miRNAs) –102. ManTE sequences are prevalent in lncRNAs. Approximately 80% of the lncRNAs identified in several studies contain at least one TE –106. TEsLEADeR). The Alu sequence within LEADeR binds to the Alu element present in the regulatory sequences of its target gene, possibly by forming a paired RNA–DNA hybrid, which prevents interferon-regulatory factor 1 (IRF1) from interacting with a binding site proximal to the Alu element, thus leading to transcriptional repression of genes for luminal cell differentiation and subsequently sustaining basal cell identity [Fendrr), a mouse lateral plate mesoderm-specific lncRNA, functioning as a putative DNA binding domain that binds to low-complexity repeats in the promoter region of target genes. The histone-modifying complexes polycomb repressive complex 2 (PRC2) and mixed lineage leukemia protein (MLL) associated with Fendrr are thus recruited to regulate the embryonic development of the heart and body wall by shaping the chromatin signatures of the genes involved [The lncRNAs that are involved in development may exploit embedded TEs to interact with the regulatory region of developmental genes for transcriptional modulation. During human prostate development, the canonical miRNA MIR205HG locus alternatively derives a lncRNA, long epithelial Alu-interacting differentiation-related RNA , which is derived from human endogenous retrovirus H (HERV-H), is reported to protect the mRNAs of pluripotency-associated core transcription factors (octamer-binding transcription factor 4 (OCT4), SRY (sex determining region Y)-box 2 (SOX2), and NANOG) from miR-145-mediated degradation in self-renewing ESCs [CYP20A1) was found to be untranslated and hence considered an lncRNA (CYP20A1_Alu-LT), harboring a stretch of Alu sequences at the 3’UTR to form a potential miRNA sponge [CYP20A1_Alu-LT expression in primary human neurons are deduced to have mRNA targets involved in tissue-specific processes of blood coagulation and neuron development. Other cancer-relevant TE-lncRNAs modulate signaling pathways by competing for the miRNAs that target mRNAs encoding the related proteins; for example, the lncRNA hepatocellular carcinoma up-regulated long non-coding RNA ) is expressed at high levels in liver cancer, and BRAF-activated nonprotein coding RNA  has been shown to act as a sponge for miR-372 to derepress protein kinase cAMP-activated catalytic subunit beta (PRKACB) and for miR-338-3p to derepress insulin-like growth factor 1 receptor (IGF1R) in esophageal squamous cell carcinoma [Moreover, TE-containing lncRNAs control the expression of protein-coding genes through diverse posttranscriptional mechanisms. In contrast to the generation of miRNAs, TEs in some lncRNAs function as competing endogenous RNAs  that recruit miRNAs with a complementary sequence from their recognition element in an mRNA, thereby stabilizing the target mRNA. For example, long intergenic non-protein-coding RNA, regulator of reprogramming  and heterogeneous nuclear ribonucleoprotein K (HNRNPK), leading to the translocation of the paired lncRNA and target mRNA into the cytoplasm to facilitate the assembly of translational initiation complexes [Uchl1) containing the SINEUP feature has been identified. It increases the translation of Uchl1/Park5, which is essential for brain function and particularly for neuron maintenance [SINEUP lncRNA discovered in the brain transcriptome was shown to upregulate the translation of protein phosphatase 1 regulatory subunit 12A (PPP1R12A), a downstream effector of inhibitory glutamate receptor delta-1 (GluD1), in postsynaptic cortical pyramidal neurons [SINEUP to increase the translation of proteins of interest [omplexes . A lncRNntenance   to elicit the SMD mechanism by recruiting up-frameshift suppressor 1 (UPF1) and UPF2, the core factors in the mRNA degradation pathway. Examples of development-relevant ½-sbsRNA lncRNAs in humans include lncRNAs that target the mRNA of PAX3 (encoding the myogenesis inhibitor paired box gene 3), which is implicated in myogenesis [KLF2) mRNA  in adipogenesis [SINE B1, B2, and B4 subfamilies (except for the primate-specific Alu) among the putative mouse ½-sbsRNAs targeting the 3’UTRs of several mRNAs for degradation  mechanism , 121. STogenesis , lncRNAsogenesis , and lncogenesis , with SIXist is a well-known lncRNA that is critical for initiating and was recently shown to also be important for maintaining X chromosome inactivation (Xi) in female cells. It consists of various tandem repeats (A–F), possibly originating from a variety of TE families, including ERVs, LINEs and SINEs. When Xist “coats” the inactivating X chromosome, these TE components within the RNA sequence are required for the recruitment of several transcriptional silencers, polycomb repressive histone modifiers, and other factors related to the establishment and maintenance of X chromosome inactivation  –114. Whent genes . FurtherApart from being incorporated into functional RNAs to execute trans-acting functions, TE DNA sequences are also substantially involved in modulating gene expression by serving as binding sites for heavily weighted transcription factors, epigenetic modifiers or insulator binding proteins. For example, thousands of ERVs carry functional tumor suppressor protein P53 binding sites and regulate nearby genes, especially in the event of DNA damage , 129. ThAfter fertilization, different ERVs are activated at different stages of preimplantation embryo development . For insUnder in vitro culture conditions, ESCs and trophoblast stem cells (TSCs) can be derived from blastocyst-stage embryos. ESCs and TSCs are responsible for the development of fetal and extraembryonic tissue, respectively. Researchers performed assay for transposase-accessible chromatin using sequencing (ATAC-seq), ChIP-seq and promoter capture Hi-C (PCHi-C) to study ESCs and TSCs and suggested that they contained distinct TE subfamilies that functioned as enhancers to regulate gene expression and determine cell differentiation. By performing ATAC-seq and H3K27ac enrichment analyses and confirming binding by at least one of the three key transcription factors , a subset of TEs were defined as “ESC/TSC TE enhancers” , 99  to facilitate germ cell differentiation Fig. . In vitrEnhancer-like ERVs are also associated with the diversity of gene expression in different species during evolution. Forty-eight mouse-specific genes were identified among 381 enhancer-like ERV-adjacent genes. Moreover, by analyzing rodent-specific ERVKs, researchers found that enhancer-like ERVs show differences in both copy numbers and genome distributions between mice and rats. In humans, 52 of 66 enhancer-like MER57E3 sequences are located at the first intron of a zinc finger protein. Among them, 47 of 52 were KRAB-ZFPs, suggesting a coevolutionary mechanism. This phenomenon was also observed in neuronal differentiation-briefly, KRAB-ZFPs partner with ERVs, regulating gene expression in human neurons . The lev. showed that ERVs are significantly enriched in numerous interferon (IFN) regulatory elements in different mammalian genomes [+ cells than in nonimmune cells, supporting the hypothesis that the immune response may depend on the function of TEs as enhancers to rapidly activate immune pathways. In adaptive immune cells, TEs have been reported to function as enhancers that regulate putative CD8+ T cell immunity [+ T cells, which further shows a high correlation with TEs, especially those in the ERV subfamily [In the immune system, Chuong et al genomes . As a re genomes . Additioimmunity . Ye et aimmunity  employedimmunity , which iimmunity . Ye et aimmunity  further ubfamily .trans-acting transcriptional repressor and a critical mediator of chromatin looping. Some retrotransposons contain CTCF binding sites, and with their expansion in a particular host genome, the 3D chromatin looping structures change with them, sometimes generating species-specific chromatin looping structures [Apart from attracting epigenetic modifiers to spread histone modifications and sometimes DNA methylation and therefore affecting the transcriptional activities of their neighboring genes, the involvement of TE sequences as insulators or factors contributing to the modulation of 3D chromatin architecture has been revealed over the last 2 decades  Fig. 44A–F. Forructures  (Fig. 4Eructures  (Fig. 4Fructures  (Fig. 4Bructures .Fig. 4TETEs can cause genomic instability via transposition dependent and independent mechanisms, potentially resulting in cell death or cancer formation. DNA methylation, histone modifications and functional RNA machineries are evolved to modulate TE at the cell type dependent and developmental stage-dependent manner. Cumulative evidence also suggested physiological significance of TE sequence-dependent mechanisms that provide novel layers of transcriptome modulation in epigenetic, nuclear architecture and post-transcriptional levels. These include TE-containing transcripts serving as miRNA sources, miRNA sponges and functional RNAs for guiding DNA binding proteins; TE-containing cis regulatory element as enhancers, promoters and insulator to regulate gene expression. In addition, TEs also act as genetic accelerators of evolution, contributing to the genome size, species-specific gene regulatory network rewiring, morphological innovation. Further understanding of TE related physiological functions and pathological etiology could lead to novel therapeutic opportunities.


Regulation of chromatin accessibility and transcription are tightly coordinated processes. Studies in yeast and higher eukaryotes have described accessible chromatin regions, but little work has been done in filamentous fungi.Neurospora crassa, which revealed characteristic molecular features of accessible and inaccessible chromatin. We present experimental evidence of inaccessibility within heterochromatin regions in Neurospora, and we examine features of both accessible and inaccessible chromatin, including the presence of histone modifications, types of transcription, transcription factor binding, and relative nucleosome turnover rates. Chromatin accessibility is not strictly correlated with expression level. Accessible chromatin regions in the model filamentous fungus Neurospora are characterized the presence of H3K27 acetylation and commonly associated with pervasive non-coding transcription. Conversely, methylation of H3 lysine-36 catalyzed by ASH1 is correlated with inaccessible chromatin within promoter regions. Conclusions: In N. crassa, H3K27 acetylation is the most predictive histone modification for open chromatin. Conversely, our data show that H3K36 methylation is a key marker of inaccessible chromatin in gene-rich regions of the genome. Our data are consistent with an expanded role for H3K36 methylation in intergenic regions of filamentous fungi compared to the model yeasts, S. cerevisiae and S. pombe, which lack homologs of the ASH1 methyltransferase.Here we present a genome-scale characterization of accessible chromatin regions in The online version contains supplementary material available at 10.1186/s12864-021-07774-0. Functionally distinct chromatin environments are defined by characteristic molecular features including histone modifications, occupancy of DNA- and chromatin-binding proteins, and varying degrees of chromatin accessibility . EuchroNeurospora, previous MNase experiments have shown that binding of the light-response master regulator white collar complex (WCC) subunit white collar 2 (wc-2) can change nucleosome organization at promoters of WCC-inducible genes [Cryptococcus neoformans has demonstrated that transcription factor ZNF2 and the Switch/Sucrose non-fermentable (SWI/SNF) complex create chromatin accessibility at filamentation genes during filamentation [cis-regulatory elements in cnidarians, fungi, and human cells, providing evidence that small RNAs or RNA polymerase activity are evolutionary conserved features of accessible chromatin [Neurospora, raising the possibility that transcription may contribute to accessible chromatin, the authors did not identify accessible chromatin regions in this fungus.Euchromatic and heterochromatic environments display marked differences in the level of chromatin accessibility to DNA-binding proteins or other regulatory factors. The Assay for Transposase-Accessible Chromatin sequencing (ATAC-seq) method has proven to be useful tool for characterizing chromatin accessibility in eukaryotes . ATAC-sele genes . Additentation . Anotheentation –36. Indehromatin . WhilSaccharomyces cerevisiae, methylation of H3K36 is mediated by a single histone methyltransferase, SET2, which associates with elongating RNA polymerase to methylate H3K36 in coding sequences [Neurospora and the closely related Fusarium fujikuroi encode two H3K36 methyltransferases that have been genetically characterized (SET-2 and ASH1) [Neurospora SET-2 trimethylates H3K36 along gene bodies and is presumably targeted by elongating RNA polymerase [Neurospora ASH1, instead, deposits mono- and di-methylation on H3K36 residues across promoters and gene bodies of silent genes in a transcriptionally independent manner [Other chromatin features are correlated with inaccessible chromatin. Constitutive heterochromatin domains marked by H3K9me3 and H3K27me3 are reported to be largely inaccessible in higher eukaryotes , but chrequences –42. Althequences –47. In nd ASH1) –50. Likelymerase . NeurosNeurospora and we show that histone acetylation and small RNA production are highly correlated with accessible chromatin, whereas repressive modifications including H3K9me3, H3K27me2/3 and ASH1-catalyzed H3K36 methylation are correlated with inaccessible chromatin in this fungus.Here, we report the development of an ATAC-seq protocol for filamentous fungi. Using ATAC-seq, we carried out a comprehensive analysis of chromatin features associated with accessible chromatin. We report a diversity of promotor structures in Neurospora, we performed ATAC-seq on wild type mycelial cultures. Because this assay is sensitive to contamination by mitochondria, we first performed ATAC-seq in nuclei that were sorted by flow cytometry and nuclei that were not sorted. In both cases, sequence reads mapped to the Neurospora genome assembly at > 98.4% . We identified 7132 ACRs unsorted cells and 5181 ACRs sorted cells from the wild-type strain. Of the ACRs we identified in sorted cells, 92% overlapped with ACRs called in unsorted cells by bedtools intersect  [We next wanted to determine what chromatin environments contain high enrichment of accessible chromatin. To do this, we first visually inspected ATAC-seq enrichment across the er (IGV) . We founTo quantify the level of accessibility in heterochromatin and euchromatin, we used bedtools intersect to determine the number of ACRs that overlap with H3K27me2/3 or H3K9me3 Table . H3K27meNeurospora genes  of DNA centered on the transcription start site (TSS) of each Neurospora gene  of genes within each k-means cluster , and we ranked them by size. We annotated ACRs greater than 2 kb (n = 84) to their closest genes .We next asked if distinct promoter structures were enriched for any functional categories of genes. In particular, we were interested in genes with large, hyperaccessible chromatin regulatory regions. We used ACRs identified from unsorted nuclei, as described above  under the control of a copper-inducible promoter, and we confirmed that the H3-3xFLAG protein is induced under copper limiting conditions and incorporated into chromatin .Pioneer factors are DNA-binding proteins that can displace nucleosomes to create accessible chromatin regions. To determine if ACRs are associated with higher rates of nucleosome turnover, we examined rates of nucleosome exchange across the tin Fig. A. We the. crassa –56. We pNeurospora by asking if disruption of the White Collar Complex (WCC) would lead to altered patterns of accessible chromatin measured by ATAC-seq. Transcription factors have been demonstrated to provide a mechanism for creating chromatin accessibility at gene promoters, and Sancar and colleagues previously implicated WCC in maintenance of accessible chromatin using MNase assays in wild type and strains lacking a functional WCC. Thus, WCC is proposed to function as a pioneer transcription factor [wc-2 mutant. We plotted ATAC-seq reads across all WCC binding sites [wc-2 mutant. We observed a striking reduction of chromatin accessibility in the Δwc-2 mutant at these sites. These data confirm prior work indicating that the WCC functions as a pioneer transcription factor  that map to karyotes , 37. Thn = 5213) overlap with at least one annotated csRNA transcript. Conversely, only 60% of csRNA transcripts (n = 9709) are found within accessible chromatin regions. Many of these csRNA transcripts appeared to flank accessible chromatin regions. This is a feature that is common among higher eukaryotic promoters and enhancers [Neurospora using bedtools closest. We found that 83% of ACRs either contained or occurred within 100 bp of an annotated csRNA transcript (n = 5939). Conversely, approximately 9% of csRNAs were identified within these 100-bp regions (n = 1570). In total, 69% of csRNA transcripts either overlapped or were within 100 bp of an ACR . Together, these data indicate that non-coding transcriptional activity is a widespread feature of accessible regions in Neurospora.To quantify the extent of overlap between chromatin accessibility and csRNA transcripts, we used bedtools intersect to identify ACRs that contain csRNA transcripts Table  and founnhancers , 59. We To identify additional chromatin features that are associated with accessible regions, we plotted enrichment of ChIP-seq data for various histone modifications surrounding accessible regions Fig. A. We perΔhH2Az, which revealed that loss of H2A.Z did not alter global patterns of chromatin accessibility in Neurospora , which is proposed to play a critical role in compacting chromatin within H3K27me3-enriched regions in higher eukaryotes [We carried out a global analysis of chromatin accessibility in a filamentous fungus using ATAC-seq. Filamentous fungi are important in ecological, industrial, clinical, and evolutionary contexts, and karyotes , 16. Ourkaryotes , 65. We Neurospora. The presence of non-coding transcription from distal accessible regions in Neurospora is reminiscent of enhancers in higher eukaryotes. Similar results were obtained in the cnidarian Nematostella [Our findings in combination with those of Duttke et al. demonstrate that abortive transcription is a key feature of accessible chromatin in tostella , 66 supptostella , 59. It tostella . This moNeurospora expression profiles. It will be important, therefore, to perform more in-depth analysis at these putative cis-regulatory regions to determine the role and abundance of these types of RNAs. Importantly, the growth conditions of the csRNA-seq experiments performed by Duttke et al. vary from our ATAC-seq protocol: csRNA-seq cultures were grown for 2 days at constant light, while cultures used for ATAC-seq were grown overnight at constant light. Therefore, matched experiments will allow for more fine-tuned associations between csRNA production and chromatin accessibility.We did find a subset of annotated csRNA loci that were not associated with ACRs; however, these may reflect differences in growth conditions used for our ATAC-seq experiments and the csRNA experiments carried out by Duttke et al. Experimental variations including growth conditions, single versus mixed tissue type, and light exposure can produce quite varied results in The presence of H3K27me2/3 in a small number of accessible chromatin regions also presents an interesting finding, suggesting that PRE equivalents may exist in filamentous fungi. Recent work has identified telomere repeat sequences and the presence of H3K36me2 as prerequisites for H3K27me via PRC2 , and a rNeursopora frequency (frq) locus has been demonstrated to regulate circadian clock function via H3K36me3 [frq (qrf) is proposed to stall RNA Polymerase II at the frq locus, resulting in premature termination of transcription and establishment of H3K36me3 that precludes binding by the WCC [Neurospora could provide a model for gene repression in other fungi, especially those that lack PRC2 and H3K27 methylation [F. fujikuroi strains lacking ASH1 mediated H3K36me2 exhibited increased expression of secondary metabolism biosynthetic clusters [S. cerevisiae and S. pombe, where it is responsible for preventing cryptic transcription and heterochromatic silencing via recruitment of nucleosome remodelers and histone deacetylases [Our results support the findings reported in Bicocca et al. , and sugH3K36me3 , 70. Thhylation , 72. F.clusters . Despitetylases , 73, 74.N. crassa genome. Accessible chromatin is found in promoters and 5′ regulatory regions of genes. Distinct patterns of accessibility exist, with large, highly accessible intergenic regions frequently associated with master regulatory genes. Accessible regions depend on transcription factor binding and are associated with high rates of nucleosome turnover. H3K27 acetylation is strongly correlated with accessible chromatin, whereas ASH-1-dependent H3K36 methylation, H3K27 methylation, and H3K9 methylation are correlated with inaccessible chromatin.Profiling accessible chromatin by ATAC-seq uncovered key features of accessible and inaccessible chromatin in the Neurospora protocols [hH3-3xflag under control of the copper-regulated tcu-1 promoter [hH3 coding sequence was amplified using primers, hH3 inF FP and hH3 inF RP, and then cloned using the In-Fusion HD Cloning HD kit (Clontech) into PacI site of a linearized version of pCCG-3xFLAG plasmid [hH3-3xflag fragment was amplified using primers hH3 CDS FP and hH3 CDS + FLAG RP from the constructed vector (pCCG-C-hH3-3xFLAG). A fragment of the tcu-1 promoter was amplified using primers Ptcu-1 FP and Ptcu-1 RP + h3 CDS. To assemble Ptcu-1-hH3-3xflag, equal molar amounts of each DNA fragment was mixed and used as a template for PCR with primers, Ptcu-1 FP and 3xFLAG RP. The Ptcu-1-hH3-3xflag was cloned into the pMD19 TA cloning vector.All liquid cultures were grown in Vogel’s minimal medium with 1.5% sucrose with shaking at 32 °C for 18 h. Strains were constructed using standard rotocols , 76. Apromoter , the hH3 plasmid . An hH3-csr-1 locus containing csr-1 5′ flank-CDS-csr-1 3′ flank was amplified by using primers, csr-1 5′ FLANK FP3 and csr-1 3′ FLANK RP3, and cloned into pMD19 TA cloning vector to create plasmid pMD19-CSR-1. To generate the CDS-less version of a linearized version of this vector, inverse PCR was performed using primers csr-1 5 flank RP + Ptcu-1 and csr-1 3 flank FP + FLAG. The Ptcu-1-hH3-3xflag fragment was cloned into this linearized vector using In-Fusion cloning. The construct was integrated into the csr-1 locus by transformation and selection on Cyclosporin A as described [The escribed .ATAC-seq was performed as described with minor modifications , 25. Brihttps://github.com/FelixKrueger/TrimGalore). Trimmed reads were mapped to the NC12 genome (GCA_000182925.2_NC12) with BowTie2 using the –very-sensitive option and setting the maximum insert size set at 2000 bp [ATAC-seq reads were trimmed and quality scored with TrimGalore! (n = 5200).Analysis of transcriptional start sites (TSSs) was performed on genes with unambiguous regulatory regions. Briefly, a list of promoters that could be unambiguously assigned to a single promoter was generated from a list of all TSSs in the Neurospora genome created with the GenomicRanges package in R , 84. Thihttps://github.com/jsh58/Genrich) using the ATAC setting (−j). Reads were separated by insert size using R [peakPermTest function of the ChIPpeakAnno R package to test for significant overlap between ACRs and H3-3xFLAG turnover [ACRs were called using Genrich  and sonicated to shear the chromatin. MNase was performed with 20 U/μl Takara MNase (Cat # 2910A) at 37 °C for 60 min. MNase digestion was quenched with 10 mM EDTA and 100 mM NaCl. Anti-flag ChIP was performed as described above. Previously published data for H3K36me2 in the ∆ mutant, , and WC- mutant,  were re-csRNA-seq was downloaded from the NCBI Short Read archive and mapped to the NC12 genome (GCA_000182925.2_NC12) and analyzed using csRNA tools developed in HOMER as described in ..Additional file 1: Figure S1. Sorting nuclei does not fully remove mitochondrial contamination. (A) Bar chart of mapped reads per chromosome. Sorted and Unsorted nuclei both exhibit reads mapped to mitochondrial contigs (chromosomes beginning with KC or KI). (B) Heatmap of ATAC-seq enrichment surrounding ACRs called from unsorted nuclei. Patterns of enrichment do not change in sorted versus unsorted nuclei. (C) Representative browser shot of the left arm for LG I showing overlap of sorted and unsorted nuclei ATAC-seq experiments.Additional file 2: Figure S2. GO analysis of genes from Cluster 1 and Cluster 2 in Fig. Additional file 3: Figure S3. Uncropped blot from Fig. Additional file 4: Figure S4. Comparison of ATAC-seq experiments in wild type and Δwc-2. Heatmap showing ATAC-seq enrichment of all ACRs in wild type and Δwc-2. Heatmap is centered on wild type ACRs.Additional file 5: Figure S5. Motif analysis results. Both known and de novo motif analyses of ACRs within H3K27me2/3 regions as determined by HOMER.Additional file 6.Additional file 7.Additional file 8.Additional file 9.Additional file 10.Additional file 11.Additional file 12.Additional file 13.Additional file 14.