OPA1 mutation affects autophagy and triggers senescence in autosomal dominant optic atrophy plus fibroblasts.

In several cases of mitochondrial diseases, the underlying genetic and bioenergetic causes of reduced oxidative phosphorylation (OxPhos) in mitochondrial dysfunction are well understood. However, there is still limited knowledge about the specific cellular outcomes and factors involved for each gene and mutation, which contributes to the lack of effective treatments for these disorders. This study focused on fibroblasts from a patient with Autosomal Dominant Optic Atrophy (ADOA) plus syndrome harboring a mutation in the Optic Atrophy 1 (OPA1) gene. By combining functional and transcriptomic approaches, we investigated the mitochondrial function and identified cellular phenotypes associated with the disease. Our findings revealed that fibroblasts with the OPA1 mutation exhibited a disrupted mitochondrial network and function, leading to altered mitochondrial dynamics and reduced autophagic response. Additionally, we observed a premature senescence phenotype in these cells, suggesting a previously unexplored role of the OPA1 gene in inducing senescence in ADOA plus patients. This study provides novel insights into the mechanisms underlying mitochondrial dysfunction in ADOA plus and highlights the potential importance of senescence in disease progression.

Mitofusin 2 mutation drives cell proliferation in Charcot-Marie-Tooth 2A fibroblasts.

Dominant mutations in ubiquitously expressed mitofusin 2 gene (MFN2) cause Charcot-Marie-Tooth type 2A (CMT2A; OMIM 609260), an inherited sensory-motor neuropathy that affects peripheral nerve axons. Mitofusin 2 protein has been found to take part in mitochondrial fusion, mitochondria-endoplasmic reticulum tethering, mitochondrial trafficking along axons, mitochondrial quality control and various types of cancer, in which MFN2 has been indicated as a tumor suppressor gene. Discordant data on the mitochondrial altered phenotypes in patient-derived fibroblasts harboring MFN2 mutations and in animal models have been reported. We addressed some of these issues by focusing on mitochondria behavior during autophagy and mitophagy in fibroblasts derived from a CMT2AMFN2 patient with an MFN2650G > T/C217F mutation in the GTPase domain. This study investigated mitochondrial dynamics, respiratory capacity and autophagy/mitophagy, to tackle the multifaceted MFN2 contribution to CMT2A pathogenesis. We found that MFN2 mutated fibroblasts showed impairment of mitochondrial morphology, bioenergetics capacity, and impairment of the early stages of autophagy, but not mitophagy. Unexpectedly, transcriptomic analysis of mutated fibroblasts highlighted marked differentially expressed pathways related to cell population proliferation and extracellular matrix organization. We consistently found the activation of mTORC2/AKT signaling and accelerated proliferation in the CMT2AMFN2 fibroblasts. In conclusion, our evidence indicates that MFN2 mutation can positively drive cell proliferation in CMT2AMFN2 fibroblasts.

UTRdb 2.0: a comprehensive, expert curated catalog of eukaryotic mRNAs untranslated regions.

The 5' and 3' untranslated regions of eukaryotic mRNAs (UTRs) play crucial roles in the post-transcriptional regulation of gene expression through the modulation of nucleo-cytoplasmic mRNA transport, translation efficiency, subcellular localization, and message stability. Since 1996, we have developed and maintained UTRdb, a specialized database of UTR sequences. Here we present UTRdb 2.0, a major update of UTRdb featuring an extensive collection of eukaryotic 5' and 3' UTR sequences, including over 26 million entries from over 6 million genes and 573 species, enriched with a curated set of functional annotations. Annotations include CAGE tags and polyA signals to label the completeness of 5' and 3'UTRs, respectively. In addition, uORFs and IRES are annotated in 5'UTRs as well as experimentally validated miRNA targets in 3'UTRs. Further annotations include evolutionarily conserved blocks, Rfam motifs, ADAR-mediated RNA editing events, and m6A modifications. A web interface allowing a flexible selection and retrieval of specific subsets of UTRs, selected according to a combination of criteria, has been implemented which also provides comprehensive download facilities. UTRdb 2.0 is accessible at http://utrdb.cloud.ba.infn.it/utrdb/.

The ADAR1 editome reveals drivers of editing-specificity for ADAR1-isoforms.

Adenosine deaminase acting on RNA ADAR1 promotes A-to-I conversion in double-stranded and structured RNAs. ADAR1 has two isoforms transcribed from different promoters: cytoplasmic ADAR1p150 is interferon-inducible while ADAR1p110 is constitutively expressed and primarily localized in the nucleus. Mutations in ADAR1 cause Aicardi - Goutières syndrome (AGS), a severe autoinflammatory disease associated with aberrant IFN production. In mice, deletion of ADAR1 or the p150 isoform leads to embryonic lethality driven by overexpression of interferon-stimulated genes. This phenotype is rescued by deletion of the cytoplasmic dsRNA-sensor MDA5 indicating that the p150 isoform is indispensable and cannot be rescued by ADAR1p110. Nevertheless, editing sites uniquely targeted by ADAR1p150 remain elusive. Here, by transfection of ADAR1 isoforms into ADAR-less mouse cells we detect isoform-specific editing patterns. Using mutated ADAR variants, we test how intracellular localization and the presence of a Z-DNA binding domain-α affect editing preferences. These data show that ZBDα only minimally contributes to p150 editing-specificity while isoform-specific editing is primarily directed by the intracellular localization of ADAR1 isoforms. Our study is complemented by RIP-seq on human cells ectopically expressing tagged-ADAR1 isoforms. Both datasets reveal enrichment of intronic editing and binding by ADAR1p110 while ADAR1p150 preferentially binds and edits 3'UTRs.

Unraveling C-to-U RNA editing events from direct RNA sequencing.

In mammals, RNA editing events involve the conversion of adenosine (A) in inosine (I) by ADAR enzymes or the hydrolytic deamination of cytosine (C) in uracil (U) by the APOBEC family of enzymes, mostly APOBEC1. RNA editing has a plethora of biological functions, and its deregulation has been associated with various human disorders. While the large-scale detection of A-to-I is quite straightforward using the Illumina RNAseq technology, the identification of C-to-U events is a non-trivial task. This difficulty arises from the rarity of such events in eukaryotic genomes and the challenge of distinguishing them from background noise. Direct RNA sequencing by Oxford Nanopore Technology (ONT) permits the direct detection of Us on sequenced RNA reads. Surprisingly, using ONT reads from wild-type (WT) and APOBEC1-knock-out (KO) murine cell lines as well as in vitro synthesized RNA without any modification, we identified a systematic error affecting the accuracy of the Cs call, thereby leading to incorrect identifications of C-to-U events. To overcome this issue in direct RNA reads, here we introduce a novel machine learning strategy based on the isolation Forest (iForest) algorithm in which C-to-U editing events are considered as sequencing anomalies. Using in vitro synthesized and human ONT reads, our model optimizes the signal-to-noise ratio improving the detection of C-to-U editing sites with high accuracy, over 90% in all samples tested. Our results suggest that iForest, known for its rapid implementation and minimal memory requirements, is a promising tool to denoise ONT reads and reliably identify RNA modifications.

Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities.

Various next generation sequencing (NGS) based strategies have been successfully used in the recent past for tracing origins and understanding the evolution of infectious agents, investigating the spread and transmission chains of outbreaks, as well as facilitating the development of effective and rapid molecular diagnostic tests and contributing to the hunt for treatments and vaccines. The ongoing COVID-19 pandemic poses one of the greatest global threats in modern history and has already caused severe social and economic costs. The development of efficient and rapid sequencing methods to reconstruct the genomic sequence of SARS-CoV-2, the etiological agent of COVID-19, has been fundamental for the design of diagnostic molecular tests and to devise effective measures and strategies to mitigate the diffusion of the pandemic. Diverse approaches and sequencing methods can, as testified by the number of available sequences, be applied to SARS-CoV-2 genomes. However, each technology and sequencing approach has its own advantages and limitations. In the current review, we will provide a brief, but hopefully comprehensive, account of currently available platforms and methodological approaches for the sequencing of SARS-CoV-2 genomes. We also present an outline of current repositories and databases that provide access to SARS-CoV-2 genomic data and associated metadata. Finally, we offer general advice and guidelines for the appropriate sharing and deposition of SARS-CoV-2 data and metadata, and suggest that more efficient and standardized integration of current and future SARS-CoV-2-related data would greatly facilitate the struggle against this new pathogen. We hope that our 'vademecum' for the production and handling of SARS-CoV-2-related sequencing data, will contribute to this objective.

REDIportal: millions of novel A-to-I RNA editing events from thousands of RNAseq experiments.

RNA editing is a relevant epitranscriptome phenomenon able to increase the transcriptome and proteome diversity of eukaryotic organisms. ADAR mediated RNA editing is widespread in humans in which millions of A-to-I changes modify thousands of primary transcripts. RNA editing has pivotal roles in the regulation of gene expression or modulation of the innate immune response or functioning of several neurotransmitter receptors. Massive transcriptome sequencing has fostered the research in this field. Nonetheless, different aspects of the RNA editing biology are still unknown and need to be elucidated. To support the study of A-to-I RNA editing we have updated our REDIportal catalogue raising its content to about 16 millions of events detected in 9642 human RNAseq samples from the GTEx project by using a dedicated pipeline based on the HPC version of the REDItools software. REDIportal now allows searches at sample level, provides overviews of RNA editing profiles per each RNAseq experiment, implements a Gene View module to look at individual events in their genic context and hosts the CLAIRE database. Starting from this novel version, REDIportal will start collecting non-human RNA editing changes for comparative genomics investigations. The database is freely available at http://srv00.recas.ba.infn.it/atlas/index.html.

A high resolution A-to-I editing map in the mouse identifies editing events controlled by pre-mRNA splicing.

Pre-mRNA-splicing and adenosine to inosine (A-to-I) RNA-editing occur mostly cotranscriptionally. During A-to-I editing, a genomically encoded adenosine is deaminated to inosine by adenosine deaminases acting on RNA (ADARs). Editing-competent stems are frequently formed between exons and introns. Consistently, studies using reporter assays have shown that splicing efficiency can affect editing levels. Here, we use Nascent-seq and identify ∼90,000 novel A-to-I editing events in the mouse brain transcriptome. Most novel sites are located in intronic regions. Unlike previously assumed, we show that both ADAR (ADAR1) and ADARB1 (ADAR2) can edit repeat elements and regular transcripts to the same extent. We find that inhibition of splicing primarily increases editing levels at hundreds of sites, suggesting that reduced splicing efficiency extends the exposure of intronic and exonic sequences to ADAR enzymes. Lack of splicing factors NOVA1 or NOVA2 changes global editing levels, demonstrating that alternative splicing factors can modulate RNA editing. Finally, we show that intron retention rates correlate with editing levels across different brain tissues. We therefore demonstrate that splicing efficiency is a major factor controlling tissue-specific differences in editing levels.

Critical assessment of bioinformatics methods for the characterization of pathological repeat expansions with single-molecule sequencing data.

A number of studies have reported the successful application of single-molecule sequencing technologies to the determination of the size and sequence of pathological expanded microsatellite repeats over the last 5 years. However, different custom bioinformatics pipelines were employed in each study, preventing meaningful comparisons and somewhat limiting the reproducibility of the results. In this review, we provide a brief summary of state-of-the-art methods for the characterization of expanded repeats alleles, along with a detailed comparison of bioinformatics tools for the determination of repeat length and sequence, using both real and simulated data. Our reanalysis of publicly available human genome sequencing data suggests a modest, but statistically significant, increase of the error rate of single-molecule sequencing technologies at genomic regions containing short tandem repeats. However, we observe that all the methods herein tested, irrespective of the strategy used for the analysis of the data (either based on the alignment or assembly of the reads), show high levels of sensitivity in both the detection of expanded tandem repeats and the estimation of the expansion size, suggesting that approaches based on single-molecule sequencing technologies are highly effective for the detection and quantification of tandem repeat expansions and contractions.

The A to I editing landscape in melanoma and its relation to clinical outcome.

RNA editing refers to non-transient RNA modifications that occur after transcription and prior to translation by the ribosomes. RNA editing is more widespread in cancer cells than in non-transformed cells and is associated with tumorigenesis of various cancer tissues. However, RNA editing can also generate neo-antigens that expose tumour cells to host immunosurveillance. Global RNA editing in melanoma and its relevance to clinical outcome currently remain poorly characterized. The present study compared RNA editing as well as gene expression in tumour cell lines from melanoma patients of short or long metastasis-free survival, patients relapsing or not after immuno- and targeted therapy and tumours harbouring BRAF or NRAS mutations. Overall, our results showed that NTRK gene expression can be a marker of resistance to BRAF and MEK inhibition and gives some insights of candidate genes as potential biomarkers. In addition, this study revealed an increase in Adenosine-to-Inosine editing in Alu regions and in non-repetitive regions, including the hyperediting of the MOK and DZIP3 genes in relapsed tumour samples during targeted therapy and of the ZBTB11 gene in NRAS mutated melanoma cells. Therefore, RNA editing could be a promising tool for identifying predictive markers, tumour neoantigens and targetable pathways that could help in preventing relapses during immuno- or targeted therapies.

The cell line A-to-I RNA editing catalogue.

Adenosine-to-inosine (A-to-I) RNA editing is a common post transcriptional modification. It has a critical role in protecting against false activation of innate immunity by endogenous double stranded RNAs and has been associated with various regulatory processes and diseases such as autoimmune and cardiovascular diseases as well as cancer. In addition, the endogenous A-to-I editing machinery has been recently harnessed for RNA engineering. The study of RNA editing in humans relies heavily on the usage of cell lines as an important and commonly-used research tool. In particular, manipulations of the editing enzymes and their targets are often developed using cell line platforms. However, RNA editing in cell lines behaves very differently than in normal and diseased tissues, and most cell lines exhibit low editing levels, requiring over-expression of the enzymes. Here, we explore the A-to-I RNA editing landscape across over 1000 human cell lines types and show that for almost every editing target of interest a suitable cell line that mimics normal tissue condition may be found. We provide CLAIRE, a searchable catalogue of RNA editing levels across cell lines available at http://srv00.recas.ba.infn.it/atlas/claire.html, to facilitate rational choice of appropriate cell lines for future work on A-to-I RNA editing.

Elucidating the editome: bioinformatics approaches for RNA editing detection.

RNA editing is a widespread co/posttranscriptional mechanism affecting primary RNAs by specific nucleotide modifications, which plays relevant roles in molecular processes including regulation of gene expression and/or the processing of noncoding RNAs. In recent years, the detection of editing sites has been improved through the availability of high-throughput RNA sequencing (RNA-Seq) technologies. Accurate bioinformatics pipelines are essential for the analysis of next-generation sequencing (NGS) data to ensure the correct identification of edited sites. Several pipelines, using various read mappers and variant callers with a wide range of adjustable parameters, are available for the detection of RNA editing events. In this review, we discuss some of the most recent and popular tools and provide guidelines for RNA-Seq data generation and analysis for the detection of RNA editing in massive transcriptome data. Using simulated and real data sets, we provide an overview of their behavior, emphasizing the fact that the RNA editing detection in NGS data sets remains a challenging task.

HPC-REDItools: a novel HPC-aware tool for improved large scale RNA-editing analysis.

BACKGROUND: RNA editing is a widespread co-/post-transcriptional mechanism that alters primary RNA sequences through the modification of specific nucleotides and it can increase both the transcriptome and proteome diversity. The automatic detection of RNA-editing from RNA-seq data is computational intensive and limited to small data sets, thus preventing a reliable genome-wide characterisation of such process. RESULTS: In this work we introduce HPC-REDItools, an upgraded tool for accurate RNA-editing events discovery from large dataset repositories. AVAILABILITY: https://github.com/BioinfoUNIBA/REDItools2 . CONCLUSIONS: HPC-REDItools is dramatically faster than the previous version, REDItools, enabling big-data analysis by means of a MPI-based implementation and scaling almost linearly with the number of available cores.

ELIXIR-IT HPC@CINECA: high performance computing resources for the bioinformatics community.

BACKGROUND: The advent of Next Generation Sequencing (NGS) technologies and the concomitant reduction in sequencing costs allows unprecedented high throughput profiling of biological systems in a cost-efficient manner. Modern biological experiments are increasingly becoming both data and computationally intensive and the wealth of publicly available biological data is introducing bioinformatics into the "Big Data" era. For these reasons, the effective application of High Performance Computing (HPC) architectures is becoming progressively more recognized also by bioinformaticians. Here we describe HPC resources provisioning pilot programs dedicated to bioinformaticians, run by the Italian Node of ELIXIR (ELIXIR-IT) in collaboration with CINECA, the main Italian supercomputing center. RESULTS: Starting from April 2016, CINECA and ELIXIR-IT launched the pilot Call "ELIXIR-IT HPC@CINECA", offering streamlined access to HPC resources for bioinformatics. Resources are made available either through web front-ends to dedicated workflows developed at CINECA or by providing direct access to the High Performance Computing systems through a standard command-line interface tailored for bioinformatics data analysis. This allows to offer to the biomedical research community a production scale environment, continuously updated with the latest available versions of publicly available reference datasets and bioinformatic tools. Currently, 63 research projects have gained access to the HPC@CINECA program, for a total handout of ~ 8 Millions of CPU/hours and, for data storage, ~ 100 TB of permanent and ~ 300 TB of temporary space. CONCLUSIONS: Three years after the beginning of the ELIXIR-IT HPC@CINECA program, we can appreciate its impact over the Italian bioinformatics community and draw some considerations. Several Italian researchers who applied to the program have gained access to one of the top-ranking public scientific supercomputing facilities in Europe. Those investigators had the opportunity to sensibly reduce computational turnaround times in their research projects and to process massive amounts of data, pursuing research approaches that would have been otherwise difficult or impossible to undertake. Moreover, by taking advantage of the wealth of documentation and training material provided by CINECA, participants had the opportunity to improve their skills in the usage of HPC systems and be better positioned to apply to similar EU programs of greater scale, such as PRACE. To illustrate the effective usage and impact of the resources awarded by the program - in different research applications - we report five successful use cases, which have already published their findings in peer-reviewed journals.

RNentropy: an entropy-based tool for the detection of significant variation of gene expression across multiple RNA-Seq experiments.

RNA sequencing (RNA-Seq) has become the experimental standard in transcriptome studies. While most of the bioinformatic pipelines for the analysis of RNA-Seq data and the identification of significant changes in transcript abundance are based on the comparison of two conditions, it is common practice to perform several experiments in parallel (e.g. from different individuals, developmental stages, tissues), for the identification of genes showing a significant variation of expression across all the conditions studied. In this work we present RNentropy, a methodology based on information theory devised for this task, which given expression estimates from any number of RNA-Seq samples and conditions identifies genes or transcripts with a significant variation of expression across all the conditions studied, together with the samples in which they are over- or under-expressed. To show the capabilities offered by our methodology, we applied it to different RNA-Seq datasets: 48 biological replicates of two different yeast conditions; samples extracted from six human tissues of three individuals; seven different mouse brain cell types; human liver samples from six individuals. Results, and their comparison to different state of the art bioinformatic methods, show that RNentropy can provide a quick and in depth analysis of significant changes in gene expression profiles over any number of conditions.

Changes in gene expression and metabolic profile of drupes of Olea europaea L. cv Carolea in relation to maturation stage and cultivation area.

BACKGROUND: Olive (Olea europaea L.) is an emblematic oil tree crop in the Mediterranean basin. Currently, despite olive features as a moderately thermophilic species, its cultivation is worldwide spreading due to the health-related impact of olive products on human nutrition. A point of concern for the expanding olive cultivation is related to the influence that, in addition to genotype, environmental factors exerts on drupe development and metabolism with consequent impact on fruit key traits. In this context, the aim of the present work was to gain further information on the genetic networks controlling drupe maturation phase and, mainly, on their modulation in response to environmental cues. RESULTS: To achieve this goal, a comparative transcriptome-wide investigation was carried out on drupes of Olea europaea cultivar Carolea, collected from plants growing in areas at different altitude level and therefore experiencing different climatic conditions. Two maturation stages of drupe were analysed: green mature and turning-purple. Metabolic characterization of drupe was also performed. At both transcriptomic and metabolic level differences were detected in the pathway of fatty acids (FAs) and phenol compounds, in relation to both drupe maturation stage and cultivation area. Among the most relevant differences detected during the transition from GM to TP stages there were: the upregulation of FADs genes in the drupes of population growing at 700 masl, the upregulation of phenol biosynthesis-related genes in drupes growing at 10 and 200 masl and very interestingly the downregulation of specific genes involved in secoiridoids production in drupes growing at 700 masl. Globally, these results suggested that stability of FAs and phenols, mainly of secoiridoids group, is promoted at high altitude, while at lower altitude phenol biosynthesis is prolonged. CONCLUSION: The obtained results showed a differential modulation of genetic pathways related to olive compound quality in relation to the cultivation area, likely imposed by the different temperature impending at each altitude. The derived molecular information appears of interest for both breeding and biotechnological programs of olive species, especially with respect to the modulation of antioxidant secoiridoid compounds which play a key role in conferring both sensorial and healthy characteristic to olive products.

Single-cell transcriptomics reveals specific RNA editing signatures in the human brain.

While RNA editing by A-to-I deamination is a requisite for neuronal function in humans, it is under-investigated in single cells. Here we fill this gap by analyzing RNA editing profiles of single cells from the brain cortex of living human subjects. We show that RNA editing levels per cell are bimodally distributed and distinguish between major brain cell types, thus providing new insights into neuronal dynamics.

REDIportal: a comprehensive database of A-to-I RNA editing events in humans.

RNA editing by A-to-I deamination is the prominent co-/post-transcriptional modification in humans. It is carried out by ADAR enzymes and contributes to both transcriptomic and proteomic expansion. RNA editing has pivotal cellular effects and its deregulation has been linked to a variety of human disorders including neurological and neurodegenerative diseases and cancer. Despite its biological relevance, many physiological and functional aspects of RNA editing are yet elusive. Here, we present REDIportal, available online at http://srv00.recas.ba.infn.it/atlas/, the largest and comprehensive collection of RNA editing in humans including more than 4.5 millions of A-to-I events detected in 55 body sites from thousands of RNAseq experiments. REDIportal embeds RADAR database and represents the first editing resource designed to answer functional questions, enabling the inspection and browsing of editing levels in a variety of human samples, tissues and body sites. In contrast with previous RNA editing databases, REDIportal comprises its own browser (JBrowse) that allows users to explore A-to-I changes in their genomic context, empathizing repetitive elements in which RNA editing is prominent.

A-GAME: improving the assembly of pooled functional metagenomics sequence data.

BACKGROUND: Expression screening of environmental DNA (eDNA) libraries is a popular approach for the identification and characterization of novel microbial enzymes with promising biotechnological properties. In such "functional metagenomics" experiments, inserts, selected on the basis of activity assays, are sequenced with high throughput sequencing technologies. Assembly is followed by gene prediction, annotation and identification of candidate genes that are subsequently evaluated for biotechnological applications. RESULTS: Here we present A-GAME (A GAlaxy suite for functional MEtagenomics), a web service incorporating state of the art tools and workflows for the analysis of eDNA sequence data. We illustrate the potential of A-GAME workflows using real functional metagenomics data, showing that they outperform alternative metagenomics assemblers. Dedicated tools available in A-GAME allow efficient analysis of pooled libraries and rapid identification of candidate genes, reducing sequencing costs and saving the need for laborious manual annotation. CONCLUSION: In conclusion, we believe A-GAME will constitute a valuable resource for the functional metagenomics community. A-GAME is publicly available at http://beaconlab.it/agame.

CoVaCS: a consensus variant calling system.

BACKGROUND: The advent and ongoing development of next generation sequencing technologies (NGS) has led to a rapid increase in the rate of human genome re-sequencing data, paving the way for personalized genomics and precision medicine. The body of genome resequencing data is progressively increasing underlining the need for accurate and time-effective bioinformatics systems for genotyping - a crucial prerequisite for identification of candidate causal mutations in diagnostic screens. RESULTS: Here we present CoVaCS, a fully automated, highly accurate system with a web based graphical interface for genotyping and variant annotation. Extensive tests on a gold standard benchmark data-set -the NA12878 Illumina platinum genome- confirm that call-sets based on our consensus strategy are completely in line with those attained by similar command line based approaches, and far more accurate than call-sets from any individual tool. Importantly our system exhibits better sensitivity and higher specificity than equivalent commercial software. CONCLUSIONS: CoVaCS offers optimized pipelines integrating state of the art tools for variant calling and annotation for whole genome sequencing (WGS), whole-exome sequencing (WES) and target-gene sequencing (TGS) data. The system is currently hosted at Cineca, and offers the speed of a HPC computing facility, a crucial consideration when large numbers of samples must be analysed. Importantly, all the analyses are performed automatically allowing high reproducibility of the results. As such, we believe that CoVaCS can be a valuable tool for the analysis of human genome resequencing studies. CoVaCS is available at: https://bioinformatics.cineca.it/covacs .