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Abstract Autoimmune thyroid diseases (AITD) such as Graves’ disease (GD) or Hashimoto’s thyroiditis (HT) are organ-specific diseases that involve complex interactions between distinct components of thyroid tissue. Here, we use spatial transcriptomics to explore the molecular architecture, heterogeneity and location of different cells present in the thyroid tissue, including thyroid follicular cells (TFCs), stromal cells such as fibroblasts, endothelial cells, and thyroid infiltrating lymphocytes. We identify damaged antigen-presenting TFCs with upregulated CD74 and MIF expression in thyroid samples from AITD patients. Furthermore, we discern two main fibroblast subpopulations in the connective tissue including ADIRF+ myofibroblasts, mainly enriched in GD, and inflammatory fibroblasts, enriched in HT patients. We also demonstrate an increase of fenestrated PLVAP+ vessels in AITD, especially in GD. Our data unveil stromal and thyroid epithelial cell subpopulations that could play a role in the pathogenesis of AITD.

Abstract The use of single-cell technologies for clinical applications requires disconnecting sampling from downstream processing steps. Early sample preservation can further increase robustness and reproducibility by avoiding artifacts introduced during specimen handling. We present FixNCut, a methodology for the reversible fixation of tissue followed by dissociation that overcomes current limitations. We applied FixNCut to human and mouse tissues to demonstrate the preservation of RNA integrity, sequencing library complexity, and cellular composition, while diminishing stress-related artifacts. Besides single-cell RNA sequencing, FixNCut is compatible with multiple single-cell and spatial technologies, making it a versatile tool for robust and flexible study designs.

Abstract Background Ineffective drug treatment is a major problem for many patients with immune-mediated inflammatory diseases (IMIDs). Important reasons are the lack of systematic solutions for drug prioritisation and repurposing based on characterisation of the complex and heterogeneous cellular and molecular changes in IMIDs. Methods Here, we propose a computational framework, scDrugPrio, which constructs network models of inflammatory disease based on single-cell RNA sequencing (scRNA-seq) data. scDrugPrio constructs detailed network models of inflammatory diseases that integrate information on cell type-specific expression changes, altered cellular crosstalk and pharmacological properties for the selection and ranking of thousands of drugs. Results scDrugPrio was developed using a mouse model of antigen-induced arthritis and validated by improved precision/recall for approved drugs, as well as extensive in vitro, in vivo, and in silico studies of drugs that were predicted, but not approved, for the studied diseases. Next, scDrugPrio was applied to multiple sclerosis, Crohn’s disease, and psoriatic arthritis, further supporting scDrugPrio through prioritisation of relevant and approved drugs. However, in contrast to the mouse model of arthritis, great interindividual cellular and gene expression differences were found in patients with the same diagnosis. Such differences could explain why some patients did or did not respond to treatment. This explanation was supported by the application of scDrugPrio to scRNA-seq data from eleven individual Crohn’s disease patients. The analysis showed great variations in drug predictions between patients, for example, assigning a high rank to anti-TNF treatment in a responder and a low rank in a nonresponder to that treatment. Conclusions We propose a computational framework, scDrugPrio, for drug prioritisation based on scRNA-seq of IMID disease. Application to individual patients indicates scDrugPrio’s potential for personalised network-based drug screening on cellulome-, genome-, and drugome-wide scales. For this purpose, we made scDrugPrio into an easy-to-use R package ( https://github.com/SDTC-CPMed/scDrugPrio ).

Abstract The interactions between tumor and immune cells along the course of breast cancer progression remain largely unknown. Here, we extensively characterize multiple sequential and parallel multiregion tumor and blood specimens of an index patient and a cohort of metastatic triple-negative breast cancers. We demonstrate that a continuous increase in tumor genomic heterogeneity and distinct molecular clocks correlated with resistance to treatment, eventually allowing tumors to escape from immune control. TCR repertoire loses diversity over time, leading to convergent evolution as breast cancer progresses. Although mixed populations of effector memory and cytotoxic single T cells coexist in the peripheral blood, defects in the antigen presentation machinery coupled with subdued T cell recruitment into metastases are observed, indicating a potent immune avoidance microenvironment not compatible with an effective antitumor response in lethal metastatic disease. Our results demonstrate that the immune responses against cancer are not static, but rather follow dynamic processes that match cancer genomic progression, illustrating the complex nature of tumor and immune cell interactions.

Abstract Relapse remains a major challenge in the clinical management of acute myeloid leukemia (AML) and is driven by rare therapy‐resistant leukemia stem cells (LSCs) that reside in specific bone marrow niches. Hypoxia signaling maintains cells in a quiescent and metabolically relaxed state, desensitizing them to chemotherapy. This suggests the hypothesis that hypoxia contributes to the chemoresistance of AML‐LSCs and may represent a therapeutic target to sensitize AML‐LSCs to chemotherapy. Here, we identify HIFhigh and HIFlow specific AML subgroups (inv(16)/t(8;21) and MLLr, respectively) and provide a comprehensive single‐cell expression atlas of 119,000 AML cells and AML‐LSCs in paired diagnostic‐relapse samples from these molecular subgroups. The HIF/hypoxia pathway signature is attenuated in AML‐LSCs compared with more differentiated AML cells but is more expressed than in healthy hematopoietic cells. Importantly, chemical inhibition of HIF cooperates with standard‐of‐care chemotherapy to impair AML growth and to substantially eliminate AML‐LSCs in vitro and in vivo. These findings support the HIF pathway in the stem cell‐driven drug resistance of AML and unravel avenues for combinatorial targeted and chemotherapy‐based approaches to specifically eliminate AML‐LSCs.

Abstract Ulcerative colitis and Crohn’s disease are chronic inflammatory intestinal diseases with perplexing heterogeneity in disease manifestation and response to treatment. While the molecular basis for this heterogeneity remains uncharacterized, single-cell technologies allow us to explore the transcriptional states within tissues at an unprecedented resolution which could further understanding of these complex diseases. Here, we apply single-cell RNA-sequencing to human inflamed intestine and show that the largest differences among patients are present within the myeloid compartment including macrophages and neutrophils. Using spatial transcriptomics in human tissue at single-cell resolution (CosMx Spatial Molecular Imaging) we spatially localize each of the macrophage and neutrophil subsets identified by single-cell RNA-sequencing and unravel further macrophage diversity based on their tissue localization. Finally, single-cell RNA-sequencing combined with single-cell spatial analysis reveals a strong communication network involving macrophages and inflammatory fibroblasts. Our data sheds light on the cellular complexity of these diseases and points towards the myeloid and stromal compartments as important cellular subsets for understanding patient-to-patient heterogeneity.

Abstract Background In droplet-based single-cell and single-nucleus RNA-seq experiments, not all reads associated with one cell barcode originate from the encapsulated cell. Such background noise is attributed to spillage from cell-free ambient RNA or barcode swapping events. Results Here, we characterize this background noise exemplified by three scRNA-seq and two snRNA-seq replicates of mouse kidneys. For each experiment, cells from two mouse subspecies are pooled, allowing to identify cross-genotype contaminating molecules and thus profile background noise. Background noise is highly variable across replicates and cells, making up on average 3–35% of the total counts (UMIs) per cell and we find that noise levels are directly proportional to the specificity and detectability of marker genes. In search of the source of background noise, we find multiple lines of evidence that the majority of background molecules originates from ambient RNA. Finally, we use our genotype-based estimates to evaluate the performance of three methods (CellBender, DecontX, SoupX) that are designed to quantify and remove background noise. We find that CellBender provides the most precise estimates of background noise levels and also yields the highest improvement for marker gene detection. By contrast, clustering and classification of cells are fairly robust towards background noise and only small improvements can be achieved by background removal that may come at the cost of distortions in fine structure. Conclusions Our findings help to better understand the extent, sources and impact of background noise in single-cell experiments and provide guidance on how to deal with it.

Summary: Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum.

Here the authors show inducible genes and enhancers are regulated mainly by transcriptional burst frequency and that this is coordinated in single cells and individual alleles. Cohesin, which is important for inducible gene expression, is largely dispensable for regulating enhancer burst frequencies; however, it is required for coupling burst frequencies of inducible enhancers and promoters.

Abstract Understanding the molecular mechanisms that contribute to the appearance of chemotherapy resistant cell populations is necessary to improve cancer treatment. We have now investigated the role of β‐catenin/CTNNB1 in the evolution of T‐cell Acute Lymphoblastic Leukemia (T‐ALL) patients and its involvement in therapy resistance. We have identified a specific gene signature that is directly regulated by β‐catenin, TCF/LEF factors and ZBTB33/Kaiso in T‐ALL cell lines, which is highly and significantly represented in five out of six refractory patients from a cohort of 40 children with T‐ALL. By subsequent refinement of this gene signature, we found that a subset of β‐catenin target genes involved with RNA‐processing function are sufficient to segregate T‐ALL refractory patients in three independent cohorts. We demonstrate the implication of β‐catenin in RNA and protein synthesis in T‐ALL and provide in vitro and in vivo experimental evidence that β‐catenin is crucial for the cellular response to chemotherapy, mainly in the cellular recovery phase after treatment. We propose that combination treatments involving chemotherapy plus β‐catenin inhibitors will enhance chemotherapy response and prevent disease relapse in T‐ALL patients.

Common variable immunodeficiency (CVID) is the most prevalent primary immunodeficiency. Here the authors perform single-cell omics analyses in CVID-discordant monozygotic twins and show epigenetic and transcriptional alterations associated with activation in memory B cells.

The use of CSF for diagnosis of metastatic brain tumors could be of clinical and patient benefit. Here the authors undertake a single-cell RNA analysis of CSF and brain to determine whether the phenotype in the CSF is reflective of the phenotype in the tumor.

Developing T cells commit to either CD4/helper or CD8/cytotoxic lineage in the thymus, but how CD4 and CD8 coreceptors and TCR signaling dictate this selection process is still unclear. Here the authors use single cell RNA sequencing of mouse thymocytes to show that, in selection intermediates, TCR signaling strength informs coreceptor expression timing.

Abstract Robust protocols and automation now enable large-scale single-cell RNA and ATAC sequencing experiments and their application on biobank and clinical cohorts. However, technical biases introduced during sample acquisition can hinder solid, reproducible results, and a systematic benchmarking is required before entering large-scale data production. Here, we report the existence and extent of gene expression and chromatin accessibility artifacts introduced during sampling and identify experimental and computational solutions for their prevention.

Abstract Background Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. Results To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community. Conclusions Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used.

Summary: In vertebrates, GATA2 is a master regulator of hematopoiesis and is expressed throughout embryo development and in adult life. Although the essential role of GATA2 in mouse hematopoiesis is well established, its involvement during early human hematopoietic development is not clear. By combining time-controlled overexpression of GATA2 with genetic knockout experiments, we found that GATA2, at the mesoderm specification stage, promotes the generation of hemogenic endothelial progenitors and their further differentiation to hematopoietic progenitor cells, and negatively regulates cardiac differentiation. Surprisingly, genome-wide transcriptional and chromatin immunoprecipitation analysis showed that GATA2 bound to regulatory regions, and repressed the expression of cardiac development-related genes. Moreover, genes important for hematopoietic differentiation were upregulated by GATA2 in a mostly indirect manner. Collectively, our data reveal a hitherto unrecognized role of GATA2 as a repressor of cardiac fates, and highlight the importance of coordinating the specification and repression of alternative cell fates. : Giorgetti A. and colleagues demonstrate that GATA2 induction in early mesodermal cells leads to the robust generation of hemogenic endothelial and hematopoietic cells from human iPSCs. They show the ability of GATA2 to instruct mesodermal precursors toward a hematopoietic cell fate and concurrently inhibit cardiac fates. This study expands our understanding of the regulatory networks that control early human hematopoiesis. Keywords: GATA2, human iPSCs, hemogenic specification, hematopoiesis, mesoderm diversification, cardiac development

Abstract Background Single-cell RNA sequencing (scRNA-seq) plays a pivotal role in our understanding of cellular heterogeneity. Current analytical workflows are driven by categorizing principles that consider cells as individual entities and classify them into complex taxonomies. Results We devise a conceptually different computational framework based on a holistic view, where single-cell datasets are used to infer global, large-scale regulatory networks. We develop correlation metrics that are specifically tailored to single-cell data, and then generate, validate, and interpret single-cell-derived regulatory networks from organs and perturbed systems, such as diabetes and Alzheimer’s disease. Using tools from graph theory, we compute an unbiased quantification of a gene’s biological relevance and accurately pinpoint key players in organ function and drivers of diseases. Conclusions Our approach detects multiple latent regulatory changes that are invisible to single-cell workflows based on clustering or differential expression analysis, significantly broadening the biological insights that can be obtained with this leading technology.

Background: The aim of this study was to test the feasibility and utility of developing patient-derived orthotopic xenograft (PDOX) models for patients with malignant peripheral nerve sheath tumors (MPNSTs) to aid therapeutic interventions in real time. Patient & Methods: A sporadic relapsed MPNST developed in a 14-year-old boy was engrafted in mice, generating a PDOX model for use in co-clinical trials after informed consent. SNP-array and exome sequencing was performed on the relapsed tumor. Genomics, drug availability, and published literature guided PDOX treatments. Results: A MPNST PDOX model was generated and expanded. Analysis of the patient’s relapsed tumor revealed mutations in the MAPK1, EED , and CDK2NA/B genes. First, the PDOX model was treated with the same therapeutic regimen as received by the patient (everolimus and trametinib); after observing partial response, tumors were left to regrow. Regrown tumors were treated based on mutations (palbociclib and JQ1), drug availability, and published literature (nab-paclitaxel; bevacizumab; sorafenib plus doxorubicin; and gemcitabine plus docetaxel). The patient had a lung metastatic relapse and was treated according to PDOX results, first with nab-paclitaxel, second with sorafenib plus doxorubicin after progression, although a complete response was not achieved and multiple metastasectomies were performed. The patient is currently disease free 46 months after first relapse. Conclusion: Our results indicate the feasibility of generating MPNST-PDOX and genomic characterization to guide treatment in real time. Although the treatment responses observed in our model did not fully recapitulate the patient’s response, this pilot study identify key aspects to improve our co-clinical testing approach in real time.

Summary: Reprogramming to induced pluripotent stem cells (iPSCs) and differentiation of pluripotent stem cells (PSCs) are regulated by epigenetic machinery. Tripartite motif protein 28 (TRIM28), a universal mediator of Krüppel-associated box domain zinc fingers (KRAB-ZNFs), is known to regulate both processes; however, the exact mechanism and identity of participating KRAB-ZNF genes remain unknown. Here, using a reporter system, we show that TRIM28/KRAB-ZNFs alter DNA methylation patterns in addition to H3K9me3 to cause stable gene repression during reprogramming. Using several expression datasets, we identified KRAB-ZNFs (ZNF114, ZNF483, ZNF589) in the human genome that maintain pluripotency. Moreover, we identified target genes repressed by these KRAB-ZNFs. Mechanistically, we demonstrated that these KRAB-ZNFs directly alter gene expression of important developmental genes by modulating H3K9me3 and DNA methylation of their promoters. In summary, TRIM28 employs KRAB-ZNFs to evoke epigenetic silencing of its target differentiation genes via H3K9me3 and DNA methylation. : Oleksiewicz et al. report that, during somatic cells reprogramming to iPSCs, KRAB-ZNF target genes become stably silenced through H3K9 and DNA methylation. Endogenous KRAB-ZNFs overexpressed in iPSCs, together with TRIM28, were found to participate in the maintenance of pluripotency by targeting and repressing differentiation genes in PSCs. Keywords: reprogramming, induced pluripotent stem cells, epigenetics, TRIM28, KRAB-ZNF repressors, differentiation

Altered genomic imprinting is frequently reported in cancer. Here, the authors analyze copy number and methylation in cancer cell lines and primary tumors to show that imprinted methylation profiles represent the accumulation of copy number alteration, rather than epigenetic alterations.

Immunodeficiency is one of the most important causes of mortality associated with Wolf-Hirschhorn syndrome (WHS), a severe rare disease originated by a deletion in chromosome 4p. The WHS candidate 1 (WHSC1) gene has been proposed as one of the main genes responsible for many of the alterations in WHS, but its mechanism of action is still unknown. Here, we present in vivo genetic evidence showing that Whsc1 plays an important role at several points of hematopoietic development. Particularly, our results demonstrate that both differentiation and function of Whsc1-deficient B cells are impaired at several key developmental stages due to profound molecular defects affecting B cell lineage specification, commitment, fitness, and proliferation, demonstrating a causal role for WHSC1 in the immunodeficiency of WHS patients.

Summary: Mammalian gametogenesis involves dramatic and tightly regulated chromatin remodeling, whose regulatory pathways remain largely unexplored. Here, we generate a comprehensive high-resolution structural and functional atlas of mouse spermatogenesis by combining in situ chromosome conformation capture sequencing (Hi-C), RNA sequencing (RNA-seq), and chromatin immunoprecipitation sequencing (ChIP-seq) of CCCTC-binding factor (CTCF) and meiotic cohesins, coupled with confocal and super-resolution microscopy. Spermatogonia presents well-defined compartment patterns and topological domains. However, chromosome occupancy and compartmentalization are highly re-arranged during prophase I, with cohesins bound to active promoters in DNA loops out of the chromosomal axes. Compartment patterns re-emerge in round spermatids, where cohesin occupancy correlates with transcriptional activity of key developmental genes. The compact sperm genome contains compartments with actively transcribed genes but no fine-scale topological domains, concomitant with the presence of protamines. Overall, we demonstrate how genome-wide cohesin occupancy and transcriptional activity is associated with three-dimensional (3D) remodeling during spermatogenesis, ultimately reprogramming the genome for the next generation. : The formation of mammalian germ cells involves dramatic chromosomal movements and chromatin remodeling, whose regulatory pathways are far from understood. Vara et al. show how the dynamics of insulator proteins’ occupancy and transcriptional activity are coupled during the 3D genome re-organization that takes place during mouse spermatogenesis.

Forced transcription factor expression can transdifferentiate somatic cells into other specialised cell types or reprogram them into induced pluripotent stem cells (iPSCs) with variable efficiency. To better understand the heterogeneity of these processes, we used single-cell RNA sequencing to follow the transdifferentation of murine pre-B cells into macrophages as well as their reprogramming into iPSCs. Even in these highly efficient systems, there was substantial variation in the speed and path of fate conversion. We predicted and validated that these differences are inversely coupled and arise in the starting cell population, with Mychigh large pre-BII cells transdifferentiating slowly but reprogramming efficiently and Myclow small pre-BII cells transdifferentiating rapidly but failing to reprogram. Strikingly, differences in Myc activity predict the efficiency of reprogramming across a wide range of somatic cell types. These results illustrate how single cell expression and computational analyses can identify the origins of heterogeneity in cell fate conversion processes.

Summary: Epigenetic regulation and, in particular, DNA methylation have been linked to the underlying genetic sequence. DNA methylation quantitative trait loci (meQTL) have been identified through significant associations between the genetic and epigenetic codes in physiological and pathological contexts. We propose that interrogating the interplay between polymorphic alleles and DNA methylation is a powerful method for improving our interpretation of risk alleles identified in genome-wide association studies that otherwise lack mechanistic explanation. We integrated patient cancer risk genotype data and genome-scale DNA methylation profiles of 3,649 primary human tumors, representing 13 solid cancer types. We provide a comprehensive meQTL catalog containing DNA methylation associations for 21% of interrogated cancer risk polymorphisms. Differentially methylated loci harbor previously reported and as-yet-unidentified cancer genes. We suggest that such regulation at the DNA level can provide a considerable amount of new information about the biology of cancer-risk alleles. : An integrative study from Heyn et al. now provides a comprehensive catalog of DNA methylation quantitative trait loci of cancer-risk alleles associated with the most common solid tumor types. The authors demonstrate that DNA methylation linkage analysis is a powerful tool for functional interpretation of genetic risk variants identified in GWAS that otherwise lack mechanistic explanation. They suggest that such regulation represents a mediator trait that provides valuable information about the biology of cancer-risk alleles.

The interpretation of noncoding alterations in cancer genomes presents an unresolved problem in cancer studies. While the impact of somatic variations in protein-coding regions is widely accepted, noncoding aberrations are mostly considered as passenger events. However, with the advance of genome-wide profiling strategies, alterations outside the coding context entered the focus, and multiple examples highlight the role of gene deregulation as cancer-driving events. This review describes the implication of noncoding alterations in oncogenesis and provides a theoretical framework for the identification of causal somatic variants using quantitative trait loci (QTL) analysis. Assuming that functional noncoding alterations affect quantifiable regulatory processes, somatic QTL studies constitute a valuable strategy to pinpoint cancer gene deregulation. Eventually, the comprehensive identification and interpretation of coding and noncoding alterations will guide our future understanding of cancer biology.

Nature Communications 5: Article number: 4608 (2014); Published: 3 April 2014; Updated: 2 November 2016 During the preparation of the PCR gel panels in Fig. 1b,c, duplicate or otherwise irrelevant lanes were excised; these excisions were not noted in the published figure as per the Nature journal policy.

While interplay between BRCA1 and AURKA-RHAMM-TPX2-TUBG1 regulates mammary epithelial polarization, common genetic variation in HMMR (gene product RHAMM) may be associated with risk of breast cancer in BRCA1 mutation carriers. Following on these observations, we further assessed the link between the AURKA-HMMR-TPX2-TUBG1 functional module and risk of breast cancer in BRCA1 or BRCA2 mutation carriers. Forty-one single nucleotide polymorphisms (SNPs) were genotyped in 15,252 BRCA1 and 8,211 BRCA2 mutation carriers and subsequently analyzed using a retrospective likelihood approach. The association of HMMR rs299290 with breast cancer risk in BRCA1 mutation carriers was confirmed: per-allele hazard ratio (HR) = 1.10, 95% confidence interval (CI) 1.04-1.15, p = 1.9 x 10(-4) (false discovery rate (FDR)-adjusted p = 0.043). Variation in CSTF1, located next to AURKA, was also found to be associated with breast cancer risk in BRCA2 mutation carriers: rs2426618 per-allele HR = 1.10, 95% CI 1.03-1.16, p = 0.005 (FDR-adjusted p = 0.045). Assessment of pairwise interactions provided suggestions (FDR-adjusted pinteraction values > 0.05) for deviations from the multiplicative model for rs299290 and CSTF1 rs6064391, and rs299290 and TUBG1 rs11649877 in both BRCA1 and BRCA2 mutation carriers. Following these suggestions, the expression of HMMR and AURKA or TUBG1 in sporadic breast tumors was found to potentially interact, influencing patients' survival. Together, the results of this study support the hypothesis of a causative link between altered function of AURKA-HMMR-TPX2-TUBG1 and breast carcinogenesis in BRCA1/2 mutation carriers.

DNA methylation is an epigenetic modification involved in regulatory processes such as cell differentiation during development, X-chromosome inactivation, genomic imprinting and susceptibility to complex disease. However, the dynamics of DNA methylation changes between humans and their closest relatives are still poorly understood. We performed a comparative analysis of CpG methylation patterns between 9 humans and 23 primate samples including all species of great apes (chimpanzee, bonobo, gorilla and orangutan) using Illumina Methylation450 bead arrays. Our analysis identified ∼800 genes with significantly altered methylation patterns among the great apes, including ∼170 genes with a methylation pattern unique to human. Some of these are known to be involved in developmental and neurological features, suggesting that epigenetic changes have been frequent during recent human and primate evolution. We identified a significant positive relationship between the rate of coding variation and alterations of methylation at the promoter level, indicative of co-occurrence between evolution of protein sequence and gene regulation. In contrast, and supporting the idea that many phenotypic differences between humans and great apes are not due to amino acid differences, our analysis also identified 184 genes that are perfectly conserved at protein level between human and chimpanzee, yet show significant epigenetic differences between these two species. We conclude that epigenetic alterations are an important force during primate evolution and have been under-explored in evolutionary comparative genomics.

Epigenetic changes are involved in a wide range of common human diseases. Although DNA methylation defects are known to be associated with male infertility in mice, their impact on human deficiency of sperm production has yet to be determined. We have assessed the global genomic DNA methylation profiles in human infertile male patients with spermatogenic disorders by using the Infinium Human Methylation27 BeadChip. Three populations were studied: conserved spermatogenesis, spermatogenic failure due to germ cell maturation defects, and Sertoli cell-only syndrome samples. A disease-associated DNA methylation profile, characterized by targeting members of the PIWI-associated RNA (piRNA) processing machinery, was obtained. Bisulfite genomic sequencing and pyrosequencing in a large cohort (n = 46) of samples validated the altered DNA methylation patterns observed in piRNA-processing genes. In particular, male infertility was associated with the promoter hypermethylation-associated silencing of PIWIL2 and TDRD1. The downstream effects mediated by the epigenetic inactivation of the PIWI pathway genes were a defective production of piRNAs and a hypomethylation of the LINE-1 repetitive sequence in the affected patients. Overall, our data suggest that DNA methylation, at least that affecting PIWIL2/TDRD1, has a role in the control of gene expression in spermatogenesis and its imbalance contributes to an unsuccessful germ cell development that might explain a group of male infertility disorders.

Data about the entire sperm DNA methylome are limited to two sperm donors whereas studies dealing with a greater number of subjects focused only on a few genes or were based on low resolution arrays. This implies that information about what we can consider as a normal sperm DNA methylome and whether it is stable among different normozoospermic individuals is still missing. The definition of the DNA methylation profile of normozoospermic men, the entity of inter-individual variability and the epigenetic characterization of quality-fractioned sperm subpopulations in the same subject (intra-individual variability) are relevant for a better understanding of pathological conditions. We addressed these questions by using the high resolution Infinium 450K methylation array and compared normal sperm DNA methylomes against somatic and cancer cells. Our study, based on the largest number of subjects (n = 8) ever considered for such a large number of CpGs (n = 487,517), provided clear evidence for i) a highly conserved DNA methylation profile among normozoospermic subjects; ii) a stable sperm DNA methylation pattern in different quality-fractioned sperm populations of the same individual. The latter finding is particularly relevant if we consider that different quality fractioned sperm subpopulations show differences in their structural features, metabolic and genomic profiles. We demonstrate, for the first time, that DNA methylation in normozoospermic men remains highly uniform regardless the quality of sperm subpopulations. In addition, our analysis provided both confirmatory and novel data concerning the sperm DNA methylome, including its peculiar features in respect to somatic and cancer cells. Our description about a highly polarized sperm DNA methylation profile, the clearly distinct genomic and functional organization of hypo- versus hypermethylated loci as well as the association of histone-enriched hypomethylated loci with embryonic development, which we now extended also to hypomethylated piRNAs-linked genes, provides solid basis for future basic and clinical research.