Biology subjects

Royo, R.

Publications and source records attributed to Royo, R..

5 recordsLinked to original sources

bioRxiv2026

Anonymized Somatic Tumor Twins (STTs) enable open genome data sharing and use in research and clinical oncology

The study of somatic variants from tumor genomes is fundamental to cancer research and clinical decision-making. However, existing data protection frameworks impose restrictions on the use and sharing of these variants in conjunction with sensitive germline information. To overcome these challenges, we developed GenomeAnonymizer, the first method to anonymize short-read DNA sequences from tumor-normal pairs. This generates Somatic Tumor Twins (STTs), an anonymized version of the original data that preserves the donors privacy while retaining somatic tumor information and sequencing noise. This method successfully removed all detectable germline variants from the 47 PCAWG-Pilot samples. We further demonstrate that Whole-Genome Sequencing (WGS) STTs preserve more than 98% of the original somatic variants, enabling reliable downstream analysis that replicates somatic-related findings from the original samples, including cancer driver genes, mutational signatures, and intratumor heterogeneity. Importantly, we also show that STTs can reproduce the identification of actionable genes and downstream clinical interpretations and decision-making. We generated a cancer cohort of STTs matched with synthetic clinical data that could be openly shared and used across projects and centers worldwide. This paradigm-shifting approach will accelerate discovery and clinical translation in oncology and enable the robust benchmarking of genome analysis and large-scale data infrastructures.

bioinformatics↗

bioRxiv2021

TIGER: The gene expression regulatory variation landscape of human pancreatic islets

GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

bioinformatics↗

bioRxiv2019

MuGVRE. A virtual research environment for 3D/4D genomics

Multiscale Genomics (MuG) Virtual Research Environment (MuGVRE) is a cloud-based computational infrastructure created to support the deployment of software tools addressing the various levels of analysis in 3D/4D genomics. Integrated tools tackle needs ranging from high computationally demanding applications (e.g. molecular dynamics simulations) to high-throughput data analysis applications (like the processing of next generation sequencing). The MuG Infrastructure is based on openNebula cloud systems implemented at the Institute for research in Biomedicine, and the Barcelona Supercomputing Center, and has specific interfaces for users and developers. Interoperability of the tools included in MuGVRE is maintained through a rich set of metadata allowing the system to associate tools and data in a transparent manner. Execution scheduling is based in a traditional queueing system to handle demand peaks in applications of fixed needs, and an elastic and multi-scale programming model (pyCOMPSs, controlled by the PMES scheduler), for complex workflows requiring distributed or multi-scale executions schemes. MuGVRE is available at https://vre.multiscalegenomics.eu and documentation and general information at https://www.multiscalegenomics.eu. The infrastructure is open and freely accessible.

bioinformatics↗

bioRxiv2017

Comparative analysis of neutrophil and monocyte epigenomes

Neutrophils and monocytes provide a first line of defense against infections as part of the innate immune system. Here we report the integrated analysis of transcriptomic and epigenetic landscapes for circulating monocytes and neutrophils with the aim to enable downstream interpretation and functional validation of key regulatory elements in health and disease. We collected RNA-seq data, ChIP-seq of six histone modifications and of DNA methylation by bisulfite sequencing at base pair resolution from up to 6 individuals per cell type. Chromatin segmentation analyses suggested that monocytes have a higher number of cell-specific enhancer regions (4-fold) compared to neutrophils. This highly plastic epigenome is likely indicative of the greater differentiation potential of monocytes into macrophages, dendritic cells and osteoclasts. In contrast, most of the neutrophil-specific features tend to be characterized by repressed chromatin, reflective of their status as terminally differentiated cells. Enhancers were the regions where most of differences in DNA methylation between cells were observed, with monocyte-specific enhancers being generally hypomethylated. Monocytes show a substantially higher gene expression levels than neutrophils, in line with epigenomic analysis revealing that gene more active elements in monocytes. Our analyses suggest that the overexpression of c-Myc in monocytes and its binding to monocyte-specific enhancers could be an important contributor to these differences. Altogether, our study provides a comprehensive epigenetic chart of chromatin states in primary human neutrophils and monocytes, thus providing a valuable resource for studying the regulation of the human innate immune system.

genomics↗

bioRxiv2017

Large-Scale Uniform Analysis of Cancer Whole Genomes in Multiple Computing Environments

The International Cancer Genome Consortium (ICGC)s Pan-Cancer Analysis of Whole Genomes (PCAWG) project aimed to categorize somatic and germline variations in both coding and non-coding regions in over 2,800 cancer patients. To provide this dataset to the research working groups for downstream analysis, the PCAWG Technical Working Group marshalled ~800TB of sequencing data from distributed geographical locations; developed portable software for uniform alignment, variant calling, artifact filtering and variant merging; performed the analysis in a geographically and technologically disparate collection of compute environments; and disseminated high-quality validated consensus variants to the working groups. The PCAWG dataset has been mirrored to multiple repositories and can be located using the ICGC Data Portal. The PCAWG workflows are also available as Docker images through Dockstore enabling researchers to replicate our analysis on their own data.

genomics↗