Methylome analysis in girls with idiopathic central precocious puberty.

BACKGROUND: Genetic and environmental factors are implicated in many developmental processes. Recent evidence, however, has suggested that epigenetic changes may also influence the onset of puberty or the susceptibility to a wide range of diseases later in life. The present study aims to investigate changes in genomic DNA methylation profiles associated with pubertal onset analyzing human peripheral blood leukocytes from three different groups of subjects: 19 girls with central precocious puberty (CPP), 14 healthy prepubertal girls matched by age and 13 healthy pubertal girls matched by pubertal stage. For this purpose, the comparisons were performed between pre- and pubertal controls to identify changes in normal pubertal transition and CPP versus pre- and pubertal controls. RESULTS: Analysis of methylation changes associated with normal pubertal transition identified 1006 differentially methylated CpG sites, 86% of them were found to be hypermethylated in prepubertal controls. Some of these CpG sites reside in genes associated with the age of menarche or transcription factors involved in the process of pubertal development. Analysis of methylome profiles in CPP patients showed 65% and 55% hypomethylated CpG sites compared with prepubertal and pubertal controls, respectively. In addition, interestingly, our results revealed the presence of 43 differentially methylated genes coding for zinc finger (ZNF) proteins. Gene ontology and IPA analysis performed in the three groups studied revealed significant enrichment of them in some pathways related to neuronal communication (semaphorin and gustation pathways), estrogens action, some cancers (particularly breast and ovarian) or metabolism (particularly sirtuin). CONCLUSIONS: The different methylation profiles of girls with normal and precocious puberty indicate that regulation of the pubertal process in humans is associated with specific epigenetic changes. Differentially methylated genes include ZNF genes that may play a role in developmental control. In addition, our data highlight changes in the methylation status of genes involved in signaling pathways that determine the migration and function of GnRH neurons and the onset of metabolic and neoplastic diseases that may be associated with CPP in later life.

The Novel Role of Noncoding RNAs in Modulating Platelet Function: Implications in Activation and Aggregation.

It is currently believed that plaque complication, with the consequent superimposed thrombosis, is a key factor in the clinical occurrence of acute coronary syndromes (ACSs). Platelets are major players in this process. Despite the considerable progress made by the new antithrombotic strategies (P2Y12 receptor inhibitors, new oral anticoagulants, thrombin direct inhibitors, etc.) in terms of a reduction in major cardiovascular events, a significant number of patients with previous ACSs treated with these drugs continue to experience events, indicating that the mechanisms of platelet remain largely unknown. In the last decade, our knowledge of platelet pathophysiology has improved. It has been reported that, in response to physiological and pathological stimuli, platelet activation is accompanied by de novo protein synthesis, through a rapid and particularly well-regulated translation of resident mRNAs of megakaryocytic derivation. Although the platelets are anucleate, they indeed contain an important fraction of mRNAs that can be quickly used for protein synthesis following their activation. A better understanding of the pathophysiology of platelet activation and the interaction with the main cellular components of the vascular wall will open up new perspectives in the treatment of the majority of thrombotic disorders, such as ACSs, stroke, and peripheral artery diseases before and after the acute event. In the present review, we will discuss the novel role of noncoding RNAs in modulating platelet function, highlighting the possible implications in activation and aggregation.

Functional Relationships between Long Non-Coding RNAs and Estrogen Receptor Alpha: A New Frontier in Hormone-Responsive Breast Cancer Management.

In the complex and articulated machinery of the human genome, less than 2% of the transcriptome encodes for proteins, while at least 75% is actively transcribed into non-coding RNAs (ncRNAs). Among the non-coding transcripts, those ≥200 nucleotides long (lncRNAs) are receiving growing attention for their involvement in human diseases, particularly cancer. Genomic studies have revealed the multiplicity of processes, including neoplastic transformation and tumor progression, in which lncRNAs are involved by regulating gene expression at epigenetic, transcriptional, and post-transcriptional levels by mechanism(s) that still need to be clarified. In breast cancer, several lncRNAs were identified and demonstrated to have either oncogenic or tumor-suppressive roles. The functional understanding of the mechanisms of lncRNA action in this disease could represent a potential for translational applications, as these molecules may serve as novel biomarkers of clinical use and potential therapeutic targets. This review highlights the relationship between lncRNAs and the principal hallmark of the luminal breast cancer phenotype, estrogen receptor α (ERα), providing an overview of new potential ways to inhibit estrogenic signaling via this nuclear receptor toward escaping resistance to endocrine therapy.

Transcriptomic profiling of calcified aortic valves in clonal hematopoiesis of indeterminate potential carriers.

Clonal hematopoiesis of indeterminate potential (CHIP) is characterized by the presence of clones of mutated blood cells without overt blood diseases. In the last few years, it has emerged that CHIP is associated with atherosclerosis and coronary calcification and that it is an independent determinant of cardiovascular mortality. Recently, CHIP has been found to occur frequently in patients with calcific aortic valve disease (CAVD) and it is associated with a poor prognosis after valve replacement. We assessed the frequency of CHIP by DNA sequencing in the blood cells of 168 CAVD patients undergoing surgical aortic valve replacement or transcatheter aortic valve implantation and investigated the effect of CHIP on 12 months survival. To investigate the pathological process of CAVD in CHIP carriers, we compared by RNA-Seq the aortic valve transcriptome of patients with or without CHIP and non-calcific controls. Transcriptomics data were validated by immunohistochemistry on formalin-embedded aortic valve samples. We confirm that CHIP is common in CAVD patients and that its presence is associated with higher mortality following valve replacement. Additionally, we show, for the first time, that CHIP is often accompanied by a broad cellular and humoral immune response in the explanted aortic valve. Our results suggest that an excessive inflammatory response in CHIP patients may be related to the onset and/or progression of CAVD and point to B cells as possible new effectors of CHIP-induced inflammation.

Whole-Exome Sequencing Revealed New Candidate Genes for Human Dilated Cardiomyopathy.

Dilated cardiomyopathy (DCM) is a complex disease affecting young adults. It is a pathological condition impairing myocardium activity that leads to heart failure and, in the most severe cases, transplantation, which is currently the only possible therapy for the disease. DCM can be attributed to many genetic determinants interacting with environmental factors, resulting in a highly variable phenotype. Due to this complexity, the early identification of causative gene mutations is an important goal to provide a genetic diagnosis, implement pre-symptomatic interventions, and predict prognosis. The advent of next-generation sequencing (NGS) has opened a new path for mutation screening, and exome sequencing provides a promising approach for identifying causal variants in known genes and novel disease-associated candidates. We analyzed the whole-exome sequencing (WES) of 15 patients affected by DCM without overloading (hypertension, valvular, or congenital heart disease) or chronic ischemic conditions. We identified 70 pathogenic or likely pathogenic variants and 1240 variants of uncertain clinical significance. Gene ontology enrichment analysis was performed to assess the potential connections between affected genes and biological or molecular function, identifying genes directly related to extracellular matrix organization, transcellular movement through the solute carrier and ATP-binding cassette transporter, and vitamin B12 metabolism. We found variants in genes implicated to a different extent in cardiac function that may represent new players in the complex genetic scenario of DCM.

Identification of functional pathways and molecular signatures in neuroendocrine neoplasms by multi-omics analysis.

BACKGROUND: Neuroendocrine neoplasms (NENs) represent a heterogeneous class of rare tumors with increasing incidence. They are characterized by the ability to secrete peptide hormones and biogenic amines but other reliable biomarkers are lacking, making diagnosis and identification of the primary site very challenging. While in some NENs, such as the pancreatic ones, next generation sequencing technologies allowed the identification of new molecular hallmarks, our knowledge of the molecular profile of NENs from other anatomical sites is still poor. METHODS: Starting from the concept that NENs from different organs may be clinically and genetically correlated, we applied a multi-omics approach by combining multigene panel testing, CGH-array, transcriptome and miRNome profiling and computational analyses, with the aim to highlight common molecular and functional signatures of gastroenteropancreatic (GEP)-NENs and medullary thyroid carcinomas (MTCs) that could aid diagnosis, prognosis and therapy. RESULTS: By comparing genomic and transcriptional profiles, ATM-dependent signaling emerged among the most significant pathways at multiple levels, involving gene variations and miRNA-mediated regulation, thus representing a novel putative druggable pathway in these cancer types. Moreover, a set of circulating miRNAs was also selected as possible diagnostic/prognostic biomarkers useful for clinical management of NENs. CONCLUSIONS: These findings depict a complex molecular and functional landscape of NENs, shedding light on novel therapeutic targets and disease biomarkers to be exploited.

Dynamics of nasopharyngeal tract phageome and association with disease severity and age of patients during three waves of COVID-19.

In December 2019, several patients were hospitalized and diagnosed with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, which subsequently led to a global pandemic. To date, there are no studies evaluating the relationship between the respiratory phageome and the SARS-CoV-2 infection. The current study investigated the phageome profiles in the nasopharyngeal swabs collected from 55 patients during the three different waves of coronavirus disease 2019 (COVID-19) in the Campania Region (Southern Italy). Data obtained from the taxonomic profiling show that phage families belonging to the order Caudovirales have a high abundance in the patient samples. Moreover, the severity of the COVID-19 infection seems to be correlated with the phage abundance.

Characterization and Discrimination of Italian Olive (Olea europaea sativa) Cultivars by Production Area Using Different Analytical Methods Combined with Chemometric Analysis.

Olives and olive products are particularly important for the national agroindustrial sector, for the aspects related to the production territory (authenticity), and for the link with the Mediterranean Diet. Several studies indicate that the elemental profile of olive and olive products depends on the production area in which the olive trees were grown, and the elemental content of the olives can be used as a marker of the production area. In order to confirm this hypothesis, the multi-elemental profile of olive drupes and olive leaves of eleven cultivars arising from two different production areas was evaluated through ICP-MS and ICP-AES techniques. In addition, some leaf samples were analysed by LPAS in order to evaluate the applicability of this new analytical technique for determining the geographic origin. The obtained results, combined with chemometric tools, showed the possibility of discriminating samples according to the production area on the basis of the elemental content, as well as by LPAS.

NGS analysis of nasopharyngeal microbiota in SARS-CoV-2 positive patients during the first year of the pandemic in the Campania Region of Italy.

Since its first appearance, the SARS-CoV-2 has spread rapidly in the human population, reaching the pandemic scale with >280 million confirmed infections and more than 5 million deaths to date (https://covid19.who.int/). These data justify the urgent need to enhance our understanding of SARS-CoV-2 effects in the respiratory system, including those linked to co-infections. The principal aim of our study is to investigate existing correlations in the nasopharynx between the bacterial community, potential pathogens, and SARS-CoV-2 infection. The main aim of this study was to provide evidence pointing to possible relationships between components of the bacterial community and SARS-CoV-2 in the nasopharynx. Meta-transcriptomic profiling of the nasopharyngeal microbial community was carried out in 89 SARS-Cov-2 positive subjects from the Campania Region in Italy. To this end, RNA extracted from nasopharyngeal swabs collected at different times during the initial phases of the pandemic was analyzed by Next-Generation Sequencing (NGS). Results show a consistently high presence of members of the Proteobacteria (41.85%), Firmicutes (28.54%), and Actinobacteria (16.10%) phyla, and an inverted correlation between the host microbiome, co-infectious bacteria, and super-potential pathogens such as Staphylococcus aureus, Klebsiella pneumoniae, Streptococcus pneumoniae, Pseudomonas aeruginosa, Acinetobacter baumannii, and Neisseria gonorrhoeae. In depth characterization of microbiota composition in the nasopharynx can provide clues to understand its potential contribution to the clinical phenotype of Covid-19, clarifying the interaction between SARS-Cov-2 and the bacterial flora of the host, and highlighting its dysbiosis and the presence of pathogens that could affect the patient's disease progression and outcome.

In vitro CSC-derived cardiomyocytes exhibit the typical microRNA-mRNA blueprint of endogenous cardiomyocytes.

miRNAs modulate cardiomyocyte specification by targeting mRNAs of cell cycle regulators and acting in cardiac muscle lineage gene regulatory loops. It is unknown if or to-what-extent these miRNA/mRNA networks are operative during cardiomyocyte differentiation of adult cardiac stem/progenitor cells (CSCs). Clonally-derived mouse CSCs differentiated into contracting cardiomyocytes in vitro (iCMs). Comparison of "CSCs vs. iCMs" mRNome and microRNome showed a balanced up-regulation of CM-related mRNAs together with a down-regulation of cell cycle and DNA replication mRNAs. The down-regulation of cell cycle genes and the up-regulation of the mature myofilament genes in iCMs reached intermediate levels between those of fetal and neonatal cardiomyocytes. Cardiomyo-miRs were up-regulated in iCMs. The specific networks of miRNA/mRNAs operative in iCMs closely resembled those of adult CMs (aCMs). miR-1 and miR-499 enhanced myogenic commitment toward terminal differentiation of iCMs. In conclusions, CSC specification/differentiation into contracting iCMs follows known cardiomyo-MiR-dependent developmental cardiomyocyte differentiation trajectories and iCMs transcriptome/miRNome resembles that of CMs.

WIND (Workflow for pIRNAs aNd beyonD): a strategy for in-depth analysis of small RNA-seq data.

Current bioinformatics workflows for PIWI-interacting RNA (piRNA) analysis focus primarily on germline-derived piRNAs and piRNA-clusters. Frequently, they suffer from outdated piRNA databases, questionable quantification methods, and lack of reproducibility. Often, pipelines specific to miRNA analysis are used for the piRNA research in silico. Furthermore, the absence of a well-established database for piRNA annotation, as for miRNA, leads to uniformity issues between studies and generates confusion for data analysts and biologists. For these reasons, we have developed WIND ( Workflow for p IRNAs a Nd beyon D), a bioinformatics workflow that addresses the crucial issue of piRNA annotation, thereby allowing a reliable analysis of small RNA sequencing data for the identification of piRNAs and other small non-coding RNAs (sncRNAs) that in the past have been incorrectly classified as piRNAs. WIND allows the creation of a comprehensive annotation track of sncRNAs combining information available in RNAcentral, with piRNA sequences from piRNABank, the first database dedicated to piRNA annotation. WIND was built with Docker containers for reproducibility and integrates widely used bioinformatics tools for sequence alignment and quantification. In addition, it includes Bioconductor packages for exploratory data and differential expression analysis. Moreover, WIND implements a "dual" approach for the evaluation of sncRNAs expression level quantifying the aligned reads to the annotated genome and carrying out an alignment-free transcript quantification using reads mapped to the transcriptome. Therefore, a broader range of piRNAs can be annotated, improving their quantification and easing the subsequent downstream analysis. WIND performance has been tested with several small RNA-seq datasets, demonstrating how our approach can be a useful and comprehensive resource to analyse piRNAs and other classes of sncRNAs.

HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities): a specific and comprehensive pipeline for metagenomic shotgun sequencing data analysis.

BACKGROUND: Next-Generation-Sequencing (NGS) enables detection of microorganisms present in biological and other matrices of various origin and nature, allowing not only the identification of known phyla and strains but also the discovery of novel ones. The large amount of metagenomic shotgun data produced by NGS require comprehensive and user-friendly pipelines for data analysis, that speed up the bioinformatics steps, relieving the users from the need to manually perform complex and time-consuming tasks. RESULTS: We describe here HOME-BIO (sHOtgun MEtagenomic analysis of BIOlogical entities), an exhaustive pipeline for metagenomics data analysis, comprising three independent analytical modules designed for an inclusive analysis of large NGS datasets. CONCLUSIONS: HOME-BIO is a powerful and easy-to-use tool that can be run also by users with limited computational expertise. It allows in-depth analyses by removing low-complexity/ problematic reads, integrating the analytical steps that lead to a comprehensive taxonomy profile of each sample by querying different source databases, and it is customizable according to specific users' needs.

First evidence of altered microbiota and intestinal damage and their link to absence epilepsy in a genetic animal model, the WAG/Rij rat.

OBJECTIVE: A large number of studies have highlighted the important role of the gut microbiota in the pathophysiology of neurological disorders, suggesting that its manipulation might serve as a treatment strategy. We hypothesized that the gut microbiota participates in absence seizure development and maintenance in the WAG/Rij rat model and tested this hypothesis by evaluating potential gut microbiota and intestinal alterations in the model, as well as measuring the impact of microbiota manipulation using fecal microbiota transplantation (FMT). METHODS: Initially, gut microbiota composition and intestinal histology of WAG/Rij rats (a well-recognized genetic model of absence epilepsy) were studied at 1, 4, and 8 months of age in comparison to nonepileptic Wistar rats. Subsequently, in a second set of experiments, at 6 months of age, untreated Wistar or WAG/Rij rats treated with ethosuximide (ETH) were used as gut microbiota donors for FMT in WAG/Rij rats, and electroencephalographic (EEG) recordings were obtained over 4 weeks. At the end of FMT, stool and gut samples were collected, absence seizures were measured on EEG recordings, and microbiota analysis and histopathological examinations were performed. RESULTS: Gut microbiota analysis showed differences in beta diversity and specific phylotypes at all ages considered and significant variances in the Bacteroidetes/Firmicutes ratio between Wistar and WAG/Rij rats. FMT, from both Wistar and ETH-treated WAG/Rij donors to WAG/Rij rats, significantly decreased the number and duration of seizures. Histological results indicated that WAG/Rij rats were characterized by intestinal villi disruption and inflammatory infiltrates already at 1 month of age, before seizure occurrence; FMT partially restored intestinal morphology while also significantly modifying gut microbiota and concomitantly reducing absence seizures. SIGNIFICANCE: Our results demonstrate for the first time that the gut microbiota is modified and contributes to seizure occurrence in a genetic animal model of absence epilepsy and that its manipulation may be a suitable therapeutic target for absence seizure management.

Identification of Antiestrogen-Bound Estrogen Receptor α Interactomes in Hormone-Responsive Human Breast Cancer Cell Nuclei.

Estrogen receptor alpha (ERα) is a ligand-inducible transcription factor which mediates estrogen actions in hormone-responsive tumors and is targeted by effective anticancer therapies based on the ERα antagonist ligands, selective estrogen receptor modulators (such as Tamoxifen/TAM) or disruptors (such as Fulvestrant/ICI). Despite its importance for cancer therapy, including acquired resistance to endocrine therapy, the molecular basis of ERα response to different ligands is not fully known to date. Interaction proteomics shows great potential to identify and characterize molecular mechanisms of disease based on physical and functional protein-protein interaction networks. Tandem affinity purification coupled to mass spectrometry is applied here for mapping in hormone-responsive breast cancer cells nuclei, the ERα interactomes, induced by each of the two classes of antiestrogens. The results provide new insights on the molecular bases for antiestrogen-mediated control of ERα function and reveal new potential ways to overcome endocrine therapy resistance in cancer.

DNA sequence context as a marker of CpG methylation instability in normal and cancer tissues.

DNA methylation alterations are related to multiple molecular mechanisms. The DNA context of CpG sites plays a crucial role in the maintenance and stability of methylation patterns. The quantitative relationship between DNA composition and DNA methylation has been studied in normal as well as pathological conditions, showing that DNA methylation status is highly dependent on the local sequence context. In this work, we describe this relationship by analyzing the DNA sequence context associated to methylation profiles in both physiological and pathological conditions. In particular, we used DNA motifs to describe methylation stability patterns in normal tissues and aberrant methylation events in cancer lesions. In this manuscript, we show how different groups of DNA sequences can be related to specific epigenetic events, across normal and cancer tissues, and provide a thorough structural and functional characterization of these sequences.

Nucleotide distance influences co-methylation between nearby CpG sites.

The tendency of individual CpG sites to be methylated is distinctive, non-random and well-regulated throughout the genome. We investigated the structural and spatial factors influencing CpGs methylation by performing an ultra-deep targeted methylation analysis on human, mouse and zebrafish genes. We found that methylation is not a random process and that closer neighboring CpG sites are more likely to share the same methylation status. Moreover, if the distance between CpGs increases, the degree of co-methylation decreases. We set up a simulation model to analyze the contribution of both the intrinsic susceptibility and the distance effect on the probability of a CpG to be methylated. Our finding suggests that the establishment of a specific methylation pattern follows a universal rule that must take into account of the synergistic and dynamic interplay of these two main factors: the intrinsic methylation susceptibility of specific CpG and the nucleotide distance between two CpG sites.

Buckwheat Hull Extracts Inhibit Aspergillus flavus Growth and AFB1 Biosynthesis.

Fungal contamination poses at risk the whole food production chain - from farm to fork - with potential negative impact on human health. So far, the insurgence of pathogens has been restrained by the use of chemical compounds, whose residues have gradually accumulated determining toxic effects in the environment. Modern innovative techniques imply the use of natural and eco-sustainable bioactive plant molecules as pathogens and pests-control agents. These may be profitably recovered in large amounts at the end of industrial milling processes. This is the case of the non-digestible hull of common buckwheat (Fagopyrum esculentum Moench), a natural source of polyphenols, tocopherols, phytosterols and fatty acids. We extract these compounds from the hull of buckwheat; apply them to Aspergillus flavus - aflatoxin producer - under in vitro conditions, checking their ability to inhibit fungal growth and aflatoxin biosynthesis. Moreover, a solvent free method implying the adoption of supercritical CO2 as solvent was set up to extract lipophilic molecules from the buckwheat' hulls. Positive results in controlling fungal growth and aflatoxin biosynthesis let infer that the extracts could be further tested also under in vivo conditions.

DNA Methylation variability among individuals is related to CpGs cluster density and evolutionary signatures.

BACKGROUND: In recent years, epigenetics has gained a central role in the understanding of the process of natural selection. It is now clear how environmental impacts on the methylome could promote methylation variability with direct effects on disease etiology as well as phenotypic and genotypic variations in evolutionary processes. To identify possible factors influencing inter-individual methylation variability, we studied methylation values standard deviation of 166 healthy individuals searching for possible associations with genomic features and evolutionary signatures. RESULTS: We analyzed methylation variability values in relation to CpG cluster density and we found a strong association between them (p-value < 2.2 × 10- 16). Furthermore, we found that genes related to CpGs with high methylation variability values were enriched for immunological pathways; instead, those associated with low ones were enriched for pathways related to basic cellular functions. Finally, we found an association between methylation variability values and signals of both ancient (p-value < 2.2 × 10- 16) and recent selective pressure (p-value < 1 × 10- 4). CONCLUSION: Our results indicate the presence of an intricate interplay between genetics, epigenetic code and evolutionary constraints in humans.

Subgingival dysbiosis in smoker and non­smoker patients with chronic periodontitis.

Periodontitis is one of the most common oral inflammatory diseases, and results in connective tissue degradation and gradual tooth loss. It manifests with formation of periodontal pockets, in which anaerobic and Gram­negative bacteria proliferate rapidly. Consequently, alteration of the subgingival microbiota is considered the primary etiologic agent of periodontitis. Previous studies have reported that smokers are at increased risk of periodontal disease, in both prevalence and severity, indicating that smoking is a risk factor for the onset and progression of the pathology. In the present study, 16S rRNA sequencing was employed to assess the subgingival microbiota in 6 smoker patients with chronic periodontitis, 6 non­smoker patients with chronic periodontitis and 8 healthy controls. The results demonstrated significant alterations in the microbial structure of periodontitis patients. High relative abundance of Parvimonans, Desulfubulbus, Paludibacter, Haemophilus, and Sphaerochaeta genera characterized subgingival microbiota of periodontitis patients, both smokers and non­smokers. Due to the high precision and sensitivity of the 16S rRNA sequencing method, analysis for low­abundant genera (including Pedobacter, Granulicatella, Paracoccus, Atopobium, Bifidobacterium, Coprococcus, Oridobacteriu, Peptococcus, Oscillospira and Akkermansia) was feasible, and revealed novel phylotypes associated with periodontitis. Of note, a major microbial community alteration was evident in smoker patients, suggesting an association between smoking and severity of subgingival dysbiosis. The present study confirmed that chronic periodontitis is a polymicrobial disease where changes in the equilibrium of subgingival microbiota contribute to severity of pathology.

ampliMethProfiler: a pipeline for the analysis of CpG methylation profiles of targeted deep bisulfite sequenced amplicons.

BACKGROUND: CpG sites in an individual molecule may exist in a binary state (methylated or unmethylated) and each individual DNA molecule, containing a certain number of CpGs, is a combination of these states defining an epihaplotype. Classic quantification based approaches to study DNA methylation are intrinsically unable to fully represent the complexity of the underlying methylation substrate. Epihaplotype based approaches, on the other hand, allow methylation profiles of cell populations to be studied at the single molecule level. For such investigations, next-generation sequencing techniques can be used, both for quantitative and for epihaplotype analysis. Currently available tools for methylation analysis lack output formats that explicitly report CpG methylation profiles at the single molecule level and that have suited statistical tools for their interpretation. RESULTS: Here we present ampliMethProfiler, a python-based pipeline for the extraction and statistical epihaplotype analysis of amplicons from targeted deep bisulfite sequencing of multiple DNA regions. CONCLUSIONS: ampliMethProfiler tool provides an easy and user friendly way to extract and analyze the epihaplotype composition of reads from targeted bisulfite sequencing experiments. ampliMethProfiler is written in python language and requires a local installation of BLAST and (optionally) QIIME tools. It can be run on Linux and OS X platforms. The software is open source and freely available at http://amplimethprofiler.sourceforge.net .