Biology subjects

Raineri, E.

Publications and source records attributed to Raineri, E..

5 recordsLinked to original sources

bioRxiv2024

ASMS: finding allele specific methylation in human genomes without phasing

MotivationAllele-specific methylation (ASM) refers to differential DNA methylation patterns between two alleles at a given locus. This phenomenon is often driven by genetic variants, such as single nucleotide variants (SNVs), which influence methylation in cis by affecting transcription factor or methylation regulator binding, leading to allele-specific differences. Understanding ASM is critical for elucidating gene regulation, as it impacts gene expression and contributes to normal biological variation as well as disease processes, including cancer [1] and autoimmune disorders [2],[3]. Another key driver of ASM is genomic imprinting, an epigenetic mechanism in which gene expression is regulated in a parent-of-origin-specific manner. Imprinted regions, marked during gametogenesis and maintained through cell divisions, are essential for growth, development, and metabolism. Dysregulation of imprinting is associated with developmental and metabolic disorders, such as Prader-Willi and Angelman syndromes, and certain cancers. Detecting ASM across the genome remains challenging due to its tissue- and cell-specific nature and the technical difficulty of phasing reads to assign methylation patterns to specific alleles. Current ASM detection pipelines (e.g., [4])) often require phasing via genetic variants, a computationally intensive process that is limited in regions with low heterozygosity. ResultsTo address these limitations, we developed asms (Allele-Specific Methylation Scanner), a tool designed to detect ASM directly from methylation data without the need for prior phasing. asms offers a faster and complementary approach to uncovering the regulatory effects of ASM, particularly in genomic regions where genetic variants or imprinting play a critical role. For demonstration purposes we leverage the fact that reads generated by Oxford Nanopore (ONT) technology measure sequence and methylation status at once, but the same software can be used with other sequencing technologies. asms can check thousands of loci in a short time. The initial list of loci to examine can be given by the user, or generated by asms through a genomic scan. The asms cluster subcommand separates the reads based on methylation. If phasing results are available, asms can use them to verify whether distinct alleles correspond to distinct base modifications patterns. We benchmark our software using publicly available Ashkenazi trio data [5]. Implementation and availabilityasms is implemented in rust and python. The software is available at https://github.com/ecmra/asms.

bioinformatics↗

bioRxiv2022

Finding heterogeneously methylated genomicregions using ONT reads

SummaryNanopore reads encode information on the methylation status of cytosines in CpG dinucleotides. The length of the reads makes it comparatively easy to look at patterns consisting of multiple loci; here we exploit this property to look for regions where one can define subpopulations of cells based on methylation patterns. As a benchmark we run our clustering algorithm on known imprinted genes and show that the clustering based on methylation is consistent with the phasing of the genome; we then scan chromosome 15 looking for windows corresponding to heterogeneous methylation. We can also compute the covariance of methylation across these regions while keeping into account the mixture of different types of reads. Availabilityhttps://github.com/EmanueleRaineri/releases Contactemanuele.raineri@cnag.crg.eu, simon.heath@cnag.crg.eu Supplementary informationTables, figures, and some further explanations of the algorithms are available as online supplementary information.

bioinformatics↗

bioRxiv2019

GARDEN-NET and ChAseR: a suite of tools for the analysis of chromatin networks

We introduce an R package and a web-based visualization tool for the representation, analysis and integration of epigenomic data in the context of 3D chromatin interaction networks. GARDEN-NET allows for the projection of user-submitted genomic features on pre-loaded chromatin interaction networks exploiting the functionalities of the ChAseR package to explore the features in combination with chromatin network topology. We demonstrate the approach on epigenomic and chromatin structure datasets in haematopoietic cells.

genomics↗

bioRxiv2018

Inference of genomic spatial organization from a whole genome bisulfite sequencing sample.

Common approaches to characterize the structure of the DNA in the nucleus, such as the different Chromosome Conformation Capture methods, have not currently been widely applied to different tissue types due to several practical difficulties including the requirement for intact cells to start the sample preparation. In contrast, techniques based on sodium bisulfite conversion of DNA to assay DNA methylation, have been widely applied to many different tissue types in a variety of organisms. Recent work has shown the possibility of inferring some aspects of the three dimensional DNA structure from DNA methylation data, raising the possibility of three dimensional DNA structure prediction using the large collection of already generated DNA methylation datasets. We propose a simple method to predict the values of the first eigenvector of the Hi-C matrix of a sample (and hence the positions of the A and B compartments) using only the GC content of the sequence and a single whole genome bisulfite sequencing (WGBS) experiment which yields information on the methylation levels and their variability along the genome. We train and test our model on 10 samples for which we have data from both bisulfite sequencing and chromosome conformation experiments and our most relevant finding is that the variability of DNA methylation along the sequence is often a better predictor than methylation itself. We then run a prediction on 206 DNA methylation profiles produced by the Blueprint project and use ChIP-Seq and RNA-Seq data to confirm that the forecasted eigenvector delineates correctly the physical chromatin compartments observed with the Hi-C experiment.

bioinformatics↗

bioRxiv2017

The expected neutral frequency spectrum of linked sites

We introduce the conditional Site Frequency Spectrum (SFS) for a genomic region linked to a focal mutation of known frequency. An exact expression for its expected value is provided for the neutral model without recombination. Its relation with the expected SFS for two sites, 2-SFS, is discussed. These spectra derive from the coalescent approach of Fu (1995) for finite samples, which is reviewed. Remarkably simple expressions are obtained for the linked SFS of a large population, which are also solutions of the multiallelic Kolmogorov equations. These formulae are the immediate extensions of the well known single site{theta} /f neutral SFS. Besides the general interest in these spectra, they relate to relevant biological cases, such as structural variants and introgressions. As an application, a recipe to adapt Tajimas D and other SFS-based neutrality tests to a non-recombining region containing a neutral marker is presented.

genetics↗