Clonally expanded PD-1-expressing T cells are enriched in synovial fluid of juvenile idiopathic arthritis patients.

Juvenile idiopathic arthritis (JIA) is the most common chronic rheumatic condition in childhood. The disease etiology remains largely unknown; however, a key role in JIA pathogenesis is surely mediated by T cells. T-lymphocytes activity is controlled via signals, known as immune checkpoints. Delivering an inhibitory signal or blocking a stimulatory signal to achieve immune suppression is critical in autoimmune diseases. However, the role of immune checkpoints in chronic inflammation and autoimmunity must still be deciphered. In this study, we investigated at the single-cell level the feature of T cells in JIA chronic inflammation, both at the transcriptome level via single-cell RNA sequencing and at the protein level by flow cytometry. We found that despite the heterogeneity in the composition of synovial CD4+ and CD8+ T cells, those characterized by PD-1 expression were clonally expanded tissue-resident memory (Trm)-like cells and displayed the highest proinflammatory capacity, suggesting their active contribution in sustaining chronic inflammation in situ. Our data support the concept that novel therapeutic strategies targeting PD-1 may be effective in the treatment of JIA. With this approach, it may become possible to target overactive T cells regardless of their cytokine production profile.

Digital droplet PCR versus quantitative PCR for lipoprotein (a) kringle IV type 2 repeat polymorphism genetic characterization.

BACKGROUND: Lipoprotein(a) [Lp(a)] level variability, related to atherothrombotic risk increase, is mainly attributed to LPA gene, encoding apolipoprotein(a), with kringle IV type 2 (KIV2) copy number variation (CNV) acting as the primary genetic determinant. Genetic characterization of Lp(a) is in continuous growth; nevertheless, the peculiar structural characteristics of this variant constitute a significant challenge to the development of effective detection methods. The aim of the study was to compare quantitative real-time PCR (qPCR) and digital droplet PCR (ddPCR) in the evaluation of KIV2 repeat polymorphism. METHODS: We analysed 100 subjects tested for cardiovascular risk in which Lp(a) plasma levels were assessed. RESULTS: Correlation analysis between CNV values obtained with the two methods was slightly significant (R = 0.413, p = 0.00002), because of the wider data dispersion in qPCR compared with ddPCR. Internal controls C1, C2 and C3 measurements throughout different experimental sessions revealed the superior stability of ddPCR, which was supported by a reduced intra/inter-assay coefficient of variation determined in this method compared to qPCR. A significant inverse correlation between Lp(a) levels and CNV values was confirmed for both techniques, but it was higher when evaluated by ddPCR than qPCR (R = -0.393, p = 0.000053 vs R = -0.220, p = 0.028, respectively). When dividing subjects into two groups according to 500 mg/L Lp(a) cut-off value, a significantly lower number of KIV2 repeats emerged among subjects with greater Lp(a) levels, with stronger evidence in ddPCR than in qPCR (p = 0.000013 and p = 0.001, respectively). CONCLUSIONS: Data obtained support a better performance of ddPCR in the evaluation of KIV2 repeat polymorphism.

Polyploid tubular cells initiate a TGF-ß1 controlled loop that sustains polyploidization and fibrosis after acute kidney injury.

Polyploidization of tubular cells (TC) is triggered by acute kidney injury (AKI) to allow survival in the early phase after AKI, but in the long run promotes fibrosis and AKI-chronic kidney disease (CKD) transition. The molecular mechanism governing the link between polyploid TC and kidney fibrosis remains to be clarified. In this study, we demonstrate that immediately after AKI, expression of cell cycle markers mostly identifies a population of DNA-damaged polyploid TC. Using transgenic mouse models and single-cell RNA sequencing we show that, unlike diploid TC, polyploid TC accumulate DNA damage and survive, eventually resting in the G1 phase of the cell cycle. In vivo and in vitro single-cell RNA sequencing along with sorting of polyploid TC shows that these cells acquire a profibrotic phenotype culminating in transforming growth factor (TGF)-ß1 expression and that TGF-ß1 directly promotes polyploidization. This demonstrates that TC polyploidization is a self-sustained mechanism. Interactome analysis by single-cell RNA sequencing revealed that TGF-ß1 signaling fosters a reciprocal activation loop among polyploid TC, macrophages, and fibroblasts to sustain kidney fibrosis and promote CKD progression. Collectively, this study contributes to the ongoing revision of the paradigm of kidney tubule response to AKI, supporting the existence of a tubulointerstitial cross talk mediated by TGF-ß1 signaling produced by polyploid TC following DNA damage.NEW & NOTEWORTHY Polyploidization in tubular epithelial cells has been neglected until recently. Here, we showed that polyploidization is a self-sustained mechanism that plays an important role during chronic kidney disease development, proving the existence of a cross talk between infiltrating cells and polyploid tubular cells. This study contributes to the ongoing revision of kidney adaptation to injury, posing polyploid tubular cells at the center of the process.

Molecular Profiling of Lymphatic Endothelial Cell Activation In Vitro.

The lymphatic vascular system plays a key role in cancer progression. Indeed, the activation of lymphatic endothelial cells (LECs) through the lymphangiogenic process allows for the formation of new lymphatic vessels (LVs) that represent the major route for the dissemination of solid tumors. This process is governed by a plethora of cancer-derived and microevironmental mediators that strictly activate and control specific molecular pathways in LECs. In this work we used an in vitro model of LEC activation to trigger lymphangiogenesis using a mix of recombinant pro-lymphangiogenic factors (VFS) and a co-culture system with human melanoma cells. Both systems efficiently activated LECs, and under these experimental conditions, RNA sequencing was exploited to unveil the transcriptional profile of activated LECs. Our data demonstrate that both recombinant and tumor cell-mediated activation trigger significant molecular pathways associated with endothelial activation, morphogenesis, and cytokine-mediated signaling. In addition, this system provides information on new genes to be further investigated in the lymphangiogenesis process and open the possibility for further exploitation in other tumor contexts where lymphatic dissemination plays a relevant role.

Effect of space flight on the behavior of human retinal pigment epithelial ARPE-19 cells and evaluation of coenzyme Q10 treatment.

Astronauts on board the International Space Station (ISS) are exposed to the damaging effects of microgravity and cosmic radiation. One of the most critical and sensitive districts of an organism is the eye, particularly the retina, and > 50% of astronauts develop a complex of alterations designated as spaceflight-associated neuro-ocular syndrome. However, the pathogenesis of this condition is not clearly understood. In the current study, we aimed to explore the cellular and molecular effects induced in the human retinal pigment ARPE-19 cell line by their transfer to and 3-day stay on board the ISS in the context of an experiment funded by the Agenzia Spaziale Italiana. Treatment of cells on board the ISS with the well-known bioenergetic, antioxidant, and antiapoptotic coenzyme Q10 was also evaluated. In the ground control experiment, the cells were exposed to the same conditions as on the ISS, with the exception of microgravity and radiation. The transfer of ARPE-19 retinal cells to the ISS and their living on board for 3 days did not affect cell viability or apoptosis but induced cytoskeleton remodeling consisting of vimentin redistribution from the cellular boundaries to the perinuclear area, underlining the collapse of the network of intermediate vimentin filaments under unloading conditions. The morphological changes endured by ARPE-19 cells grown on board the ISS were associated with changes in the transcriptomic profile related to the cellular response to the space environment and were consistent with cell dysfunction adaptations. In addition, the results obtained from ARPE-19 cells treated with coenzyme Q10 indicated its potential to increase cell resistance to damage.

Nanopore sequencing from liquid biopsy: analysis of copy number variations from cell-free DNA of lung cancer patients.

In the "precision oncology" era the characterization of tumor genetic features is a pivotal step in cancer patients' management. Liquid biopsy approaches, such as analysis of cell-free DNA from plasma, represent a powerful and noninvasive strategy to obtain information about the genomic status of the tumor. Sequencing-based analyses of cell-free DNA, currently performed with second generation sequencers, are extremely powerful but poorly scalable and not always accessible also due to instrumentation costs. Third generation sequencing platforms, such as Nanopore sequencers, aim at overcoming these obstacles but, unfortunately, are not designed for cell-free DNA analysis.Here we present a customized workflow to exploit low-coverage Nanopore sequencing for the detection of copy number variations from plasma of cancer patients. Whole genome molecular karyotypes of 6 lung cancer patients and 4 healthy subjects were successfully produced with as few as 2 million reads, and common lung-related copy number alterations were readily detected.This is the first successful use of Nanopore sequencing for copy number profiling from plasma DNA. In this context, Nanopore represents a reliable alternative to Illumina sequencing, with the advantages of minute instrumentation costs and extremely short analysis time.The availability of protocols for Nanopore-based cell-free DNA analysis will make this analysis finally accessible, exploiting the full potential of liquid biopsy both for research and clinical purposes.

VISOR: a versatile haplotype-aware structural variant simulator for short- and long-read sequencing.

SUMMARY: VISOR is a tool for haplotype-specific simulations of simple and complex structural variants (SVs). The method is applicable to haploid, diploid or higher ploidy simulations for bulk or single-cell sequencing data. SVs are implanted into FASTA haplotypes at single-basepair resolution, optionally with nearby single-nucleotide variants. Short or long reads are drawn at random from these haplotypes using standard error profiles. Double- or single-stranded data can be simulated and VISOR supports the generation of haplotype-tagged BAM files. The tool further includes methods to interactively visualize simulated variants in single-stranded data. The versatility of VISOR is unmet by comparable tools and it lays the foundation to simulate haplotype-resolved cancer heterogeneity data in bulk or at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: VISOR is implemented in python 3.6, open-source and freely available at https://github.com/davidebolo1993/VISOR. Documentation is available at https://davidebolo1993.github.io/visordoc/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Nanopore sequencing data analysis: state of the art, applications and challenges.

The nanopore sequencing process is based on the transit of a DNA molecule through a nanoscopic pore, and since the 90s is considered as one of the most promising approaches to detect polymeric molecules. In 2014, Oxford Nanopore Technologies (ONT) launched a beta-testing program that supplied the scientific community with the first prototype of a nanopore sequencer: the MinION. Thanks to this program, several research groups had the opportunity to evaluate the performance of this novel instrument and develop novel computational approaches for analyzing this new generation of data. Despite the short period of time from the release of the MinION, a large number of algorithms and tools have been developed for base calling, data handling, read mapping, de novo assembly and variant discovery. Here, we face the main computational challenges related to the analysis of nanopore data, and we carry out a comprehensive and up-to-date survey of the algorithmic solutions adopted by the bioinformatic community comparing performance and reporting limits and advantages of using this new generation of sequences for genomic analyses. Our analyses demonstrate that the use of nanopore data dramatically improves the de novo assembly of genomes and allows for the exploration of structural variants with an unprecedented accuracy and resolution. However, despite the impressive improvements reached by ONT in the past 2 years, the use of these data for small-variant calling is still challenging, and at present, it needs to be coupled with complementary short sequences for mitigating the intrinsic biases of nanopore sequencing technology.

PyPore: a python toolbox for nanopore sequencing data handling.

MOTIVATION: The recent technological improvement of Oxford Nanopore sequencing pushed the throughput of these devices to 10-20 Gb allowing the generation of millions of reads. For these reasons, the availability of fast software packages for evaluating experimental quality by generating highly informative and interactive summary plots is of fundamental importance. RESULTS: We developed PyPore, a three module python toolbox designed to handle raw FAST5 files from quality checking to alignment to a reference genome and to explore their features through the generation of browsable HTML files. The first module provides an interface to explore and evaluate the information contained in FAST5 and summarize them into informative quality measures. The second module converts raw data in FASTQ format, while the third module allows to easily use three state-of-the-art aligners and collects mapping statistics. AVAILABILITY AND IMPLEMENTATION: PyPore is an open-source software and is written in Python2.7, source code is freely available, for all OS platforms, in Github at https://github.com/rsemeraro/PyPore. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Nano-GLADIATOR: real-time detection of copy number alterations from nanopore sequencing data.

MOTIVATION: The past few years have seen the emergence of nanopore-based sequencing technologies which interrogate single molecule of DNA and generate reads sequentially. RESULTS: In this paper, we demonstrate that, thanks to the sequentiality of the nanopore process, the data generated in the first tens of minutes of a typical MinION/GridION run can be exploited to resolve the alterations of a human genome at a karyotype level with a resolution in the order of tens of Mb, while the data produced in the first 6-12 h allow to obtain a resolution comparable to currently available array-based technologies, and thanks to a novel probabilistic approach are capable to predict the allelic fraction of genomic alteration with high accuracy. To exploit the unique characteristics of nanopore sequencing data we developed a novel software tool, Nano-GLADIATOR, that is capable to perform copy number variants/alterations detection and allelic fraction prediction during the sequencing run ('On-line' mode) and after experiment completion ('Off-line' mode). We tested Nano-GLADIATOR on publicly available ('Off-line' mode) and on novel whole genome sequencing dataset generated with MinION device ('On-line' mode) showing that our tool is capable to perform real-time copy number alterations detection obtaining good results with respect to other state-of-the-art tools. AVAILABILITY AND IMPLEMENTATION: Nano-GLADIATOR is freely available at https://sourceforge.net/projects/nanogladiator/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

RNA sequencing reveals PNN and KCNQ1OT1 as predictive biomarkers of clinical outcome in stage III colorectal cancer patients treated with adjuvant chemotherapy.

Five-year overall survival of stage III colorectal cancer (CRC) patients treated with standard adjuvant chemotherapy (ACHT) is highly variable. Genomic biomarkers and/or transcriptomic profiles identified lack of adequate validation. Aim of our study was to identify and validate molecular biomarkers predictive of ACHT response in stage III CRC patients by a transcriptomic approach. From a series of CRC patients who received ACHT, two stage III extreme cohorts (unfavorable vs. favorable prognosis) were selected. RNA-sequencing was performed from fresh frozen explants. Tumors were characterized for somatic mutations. Validation was performed in stage III CRC patients extracted from two GEO datasets. According to disease-free survival (DFS), 108 differentially expressed genes (104/4 up/downregulated in the unfavorable prognosis group) were identified. Among 104 upregulated genes, 42 belonged to olfactory signaling pathways, 62 were classified as pseudogenes (n = 17), uncharacterized noncoding RNA (n = 10), immune response genes (n = 4), microRNA (n = 1), cancer-related genes (n = 14) and cancer-unrelated genes (n = 16). Three out of four down-regulated genes were cancer-related. Mutational status (i.e., RAS, BRAF, PIK3CA) did not differ among the cohorts. In the validation cohort, multivariate analysis showed high PNN and KCNQ1OT1 expression predictive of shorter DFS in ACHT treated patients (p = 0.018 and p = 0.014, respectively); no difference was observed in untreated patients. This is the first study that identifies by a transcriptomic approach and validates PNN and KCNQ1OT1 as molecular biomarkers predictive of chemotherapy response in stage III CRC patients. After a further validation in an independent cohort, PNN and KCNQ1OT1 evaluation could be proposed to prospectively identify stage III CRC patients benefiting from ACHT.

Characterization of MinION nanopore data for resequencing analyses.

The Oxford Nanopore Technologies MinION is a new device, based on nanopore sequencing that is able to generate reads of tens of kilobases in length with faster sequencing time with respect to other platforms. To evaluate the capability of nanopore data to be exploited for resequencing analyses we used the largest MinION data set to date and we compared with Illumina and Pacific Biosciences technologies. By using five different mapping approaches we estimated that the global sequencing error rate of MinION reads, mainly caused by inserted and deleted bases, is around 11%. The study of error distribution showed that substituted, inserted and deleted bases are not randomly distributed along the reads, but mainly occur in specific nucleotide patterns, generating a significant number of genomic loci that can be misclassified as false-positive variants. With 40× sequencing coverage, MinION data can produce at best around one false substitution and insertion every 10-50 kb, and one false deletion every 1000 bp, making use of this technology still challenging for small-sized variant discovery. We also analyzed depth of coverage distribution and we demonstrated that nanopore sequencing is a uniform process that generates sequences randomly and independently without classical sources of bias such as GC-content and mappability. Owing to these properties, the MinION data can be readily used to detect genomic regions involved in copy number variants with high accuracy, outperforming other state-of-the-art sequencing methods in terms of both sensitivity and specificity.

Enhanced copy number variants detection from whole-exome sequencing data using EXCAVATOR2.

Copy Number Variants (CNVs) are structural rearrangements contributing to phenotypic variation that have been proved to be associated with many disease states. Over the last years, the identification of CNVs from whole-exome sequencing (WES) data has become a common practice for research and clinical purpose and, consequently, the demand for more and more efficient and accurate methods has increased. In this paper, we demonstrate that more than 30% of WES data map outside the targeted regions and that these reads, usually discarded, can be exploited to enhance the identification of CNVs from WES experiments. Here, we present EXCAVATOR2, the first read count based tool that exploits all the reads produced by WES experiments to detect CNVs with a genome-wide resolution. To evaluate the performance of our novel tool we use it for analysing two WES data sets, a population data set sequenced by the 1000 Genomes Project and a tumor data set made of bladder cancer samples. The results obtained from these analyses demonstrate that EXCAVATOR2 outperforms other four state-of-the-art methods and that our combined approach enlarge the spectrum of detectable CNVs from WES data with an unprecedented resolution. EXCAVATOR2 is freely available at http://sourceforge.net/projects/excavator2tool/.

SLMSuite: a suite of algorithms for segmenting genomic profiles.

BACKGROUND: The identification of copy number variants (CNVs) is essential to study human genetic variation and to understand the genetic basis of mendelian disorders and cancers. At present, genome-wide detection of CNVs can be achieved using microarray or second generation sequencing (SGS) data. Although these technologies are very different, the genomic profiles that they generate are mathematically very similar and consist of noisy signals in which a decrease or increase of consecutive data represent deletions or duplication of DNA. In this framework, the most important step of the analysis consists of segmenting genomic profiles for the identification of the boundaries of genomic regions with increased or decreased signal. RESULTS: Here we introduce SLMSuite, a collection of algorithms, based on shifting level models (SLM), to segment genomic profiles from array and SGS experiments. The SLM algorithms take as input the log-transformed genomic profiles from SGS or microarray experiments and output segmentation results. We apply our method to the analysis of synthetic genomic profiles and real whole genome sequencing data and we demonstrate that it outperforms the state of the art circular binary segmentation algorithm in terms of sensitivity, specificity and computational speed. CONCLUSION: The SLMSuite contains an R library with the segmentation methods and three wrappers that allow to use them in Python, Ruby and C++. SLMSuite is freely available at https://sourceforge.net/projects/slmsuite .

XCAVATOR: accurate detection and genotyping of copy number variants from second and third generation whole-genome sequencing experiments.

BACKGROUND: We developed a novel software package, XCAVATOR, for the identification of genomic regions involved in copy number variants/alterations (CNVs/CNAs) from short and long reads whole-genome sequencing experiments. RESULTS: By using simulated and real datasets we showed that our tool, based on read count approach, is capable to predict the boundaries and the absolute number of DNA copies CNVs/CNAs with high resolutions. To demonstrate the power of our software we applied it to the analysis Illumina and Pacific Bioscencies data and we compared its performance to other ten state of the art tools. CONCLUSION: All the analyses we performed demonstrate that XCAVATOR is capable to detect germline and somatic CNVs/CNAs outperforming all the other tools we compared. XCAVATOR is freely available at http://sourceforge.net/projects/xcavator/ .

A novel founder MYO15A frameshift duplication is the major cause of genetic hearing loss in Oman.

The increased risk for autosomal recessive disorders is one of the most well-known medical implications of consanguinity. In the Sultanate of Oman, a country characterized by one of the highest rates of consanguineous marriages worldwide, prevalence of genetic hearing loss (GHL) is estimated to be 6/10 000. Families of GHL patients have higher consanguinity rates than the general Omani population, indicating a major role for recessive forms. Mutations in GJB2, the most commonly mutated GHL gene, have been sporadically described. We collected 97 DNA samples of GHL probands, affected/unaffected siblings and parents from 26 Omani consanguineous families. Analyzing a first family by whole-exome sequencing, we identified a novel homozygous frameshift duplication (c.1171_1177dupGCCATCT) in MYO15A, the gene linked to the deafness locus DFNB3. This duplication was then found in a total of 8/26 (28%) families, within a 849 kb founder haplotype. Reconstruction of haplotype structure at MYO15A surrounding genomic regions indicated that the founder haplotype branched out in the past two to three centuries from a haplotype present worldwide. The MYO15A duplication emerges as the major cause of GHL in Oman. These findings have major implications for the design of GHL diagnosis and prevention policies in Oman.

Characterization and identification of hidden rare variants in the human genome.

BACKGROUND: By examining the genotype calls generated by the 1000 Genomes Project we discovered that the human reference genome GRCh37 contains almost 20,000 loci in which the reference allele has never been observed in healthy individuals and around 70,000 loci in which it has been observed only in the heterozygous state. RESULTS: We show that a large fraction of this rare reference allele (RRA) loci belongs to coding, functional and regulatory elements of the genome and could be linked to rare Mendelian disorders as well as cancer. We also demonstrate that classical germline and somatic variant calling tools are not capable to recognize the rare allele when present in these loci. To overcome such limitations, we developed a novel tool, named RAREVATOR, that is able to identify and call the rare allele in these genomic positions. By using a small cancer dataset we compared our tool with two state-of-the-art callers and we found that RAREVATOR identified more than 1,500 germline and 22 somatic RRA variants missed by the two methods and which belong to significantly mutated pathways. CONCLUSIONS: These results show that, to date, the investigation of around 100,000 loci of the human genome has been missed by re-sequencing experiments based on the GRCh37 assembly and that our tool can fill the gap left by other methods. Moreover, the investigation of the latest version of the human reference genome, GRCh38, showed that although the GRC corrected almost all insertions and a small part of SNVs and deletions, a large number of functionally relevant RRAs still remain unchanged. For this reason, also future resequencing experiments, based on GRCh38, will benefit from RAREVATOR analysis results. RAREVATOR is freely available at http://sourceforge.net/projects/rarevator .

H3M2: detection of runs of homozygosity from whole-exome sequencing data.

MOTIVATION: Runs of homozygosity (ROH) are sizable chromosomal stretches of homozygous genotypes, ranging in length from tens of kilobases to megabases. ROHs can be relevant for population and medical genetics, playing a role in predisposition to both rare and common disorders. ROHs are commonly detected by single nucleotide polymorphism (SNP) microarrays, but attempts have been made to use whole-exome sequencing (WES) data. Currently available methods developed for the analysis of uniformly spaced SNP-array maps do not fit easily to the analysis of the sparse and non-uniform distribution of the WES target design. RESULTS: To meet the need of an approach specifically tailored to WES data, we developed [Formula: see text], an original algorithm based on heterogeneous hidden Markov model that incorporates inter-marker distances to detect ROH from WES data. We evaluated the performance of [Formula: see text] to correctly identify ROHs on synthetic chromosomes and examined its accuracy in detecting ROHs of different length (short, medium and long) from real 1000 genomes project data. [Formula: see text] turned out to be more accurate than GERMLINE and PLINK, two state-of-the-art algorithms, especially in the detection of short and medium ROHs. AVAILABILITY AND IMPLEMENTATION: [Formula: see text] is a collection of bash, R and Fortran scripts and codes and is freely available at https://sourceforge.net/projects/h3m2/. CONTACT: albertomagi@gmail.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Detection of runs of homozygosity from whole exome sequencing data: state of the art and perspectives for clinical, population and epidemiological studies.

Runs of homozygosity (ROH) are sizeable stretches of homozygous genotypes at consecutive polymorphic DNA marker positions, traditionally captured by means of genome-wide single nucleotide polymorphism (SNP) genotyping. With the advent of next-generation sequencing (NGS) technologies, a number of methods initially devised for the analysis of SNP array data (those based on sliding-window algorithms such as PLINK or GERMLINE and graphical tools like HomozygosityMapper) or specifically conceived for NGS data have been adopted for the detection of ROH from whole exome sequencing (WES) data. In the latter group, algorithms for both graphical representation (AgileVariantMapper, HomSI) and computational detection (H(3)M(2)) of WES-derived ROH have been proposed. Here we examine these different approaches and discuss available strategies to implement ROH detection in WES analysis. Among sliding-window algorithms, PLINK appears to be well-suited for the detection of ROH, especially of the long ones. As a method specifically tailored for WES data, H(3)M(2) outperforms existing algorithms especially on short and medium ROH. We conclude that, notwithstanding the irregular distribution of exons, WES data can be used with some approximation for unbiased genome-wide analysis of ROH features, with promising applications to homozygosity mapping of disease genes, comparative analysis of populations and epidemiological studies based on consanguinity.