Biology subjects

Reverter, F.

Publications and source records attributed to Reverter, F..

8 recordsLinked to original sources

bioRxiv2026

Single-cell atlas of transcript usage remodelling in antiviral immune responses across human populations

Humans exhibit substantial interindividual variation in their immune responses to infection, yet the contribution of transcript usage --the relative abundance of gene isoforms-- to this variation remains poorly understood. Here, we generate the first single-cell atlas of transcript usage variation during early responses to influenza A virus and SARS-CoV-2 across 160 individuals of African and European ancestry. We show that viral stimulation induces widespread remodelling of transcript usage across all major immune lineages, with changes that are largely lineage-restricted and frequently undetected at the gene expression level. We further find that ancestry-associated effects on transcript usage are predominantly cell type-specific and contribute to population differences in antiviral responses. In addition, the genetic regulation of transcript usage during stimulation differs between influenza A and SARS-CoV-2, pointing to virus-dependent regulatory architectures. Together, our findings establish transcript usage as a dynamic regulatory layer shaping responses to viral infection across immune cell types and human populations, providing new insights into the molecular basis of variation in human antiviral immunity.

immunology↗

bioRxiv2023

Exploring functional conservation in silico: a new machine learning approach to RNA-editing

Around 50 years from now, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases, through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed with a remarkable impact in the increase of the complexity of transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with attention layer. These algorithms combined with RNA-editing data coming from databases and variant calling from same-individual RNA and DNA-seq experiments from different species, allowed us to predict RNA-editing events using both primary sequence and secondary structure. Then, we devised a method for assessing conservation or divergence in the molecular mechanisms of editing completely in silico: the cross-training analysis. This novel method not only helps to understand the conservation of the editing mechanism through evolution but could set the basis for understanding how it is involved in several human diseases.

genetics↗

bioRxiv2022

A fast non-parametric test of association for multiple traits

The increasing availability of multidimensional phenotypic data in large cohorts of genotyped individuals requires efficient methods to identify genetic effects on multiple traits. Permutational multivariate analysis of variance (PERMANOVA) offers a powerful non-parametric approach. However, it relies on permutations to assess significance, which hinders the analysis of large datasets. Here, we derive the limiting null distribution of the PERMANOVA test statistic, providing a framework for the fast computation of asymptotic p values. We show that the asymptotic test presents controlled type I error and high power, comparable to or higher than parametric approaches. We illustrate the applicability of our method in a number of use-cases. Using the GTEx cohort, we perform the first population-biased splicing QTL mapping study across multiple tissues. We identify thousands of genetic variants that affect alternative splicing differently depending on ethnicity, including potential disease markers. Using the UK Biobank cohort, we perform the largest GWAS to date of MRI-derived volumes of hippocampal subfields. Most of the identified loci have not been previously related to the hippocampus, but many are associated to cognition or brain disorders, thus contributing to understand the intermediate traits through which genetic variants impact complex organismal phenotypes.

bioinformatics↗

bioRxiv2022

In vivo single-cell profiling of lncRNAs during Ebola virus infection

Long non-coding RNAs (lncRNAs) are pivotal mediators of systemic immune response to viral infection, yet most studies concerning their expression and functions upon immune stimulation are limited to in vitro bulk cell populations. This strongly constrains our understanding of how lncRNA expression varies at single-cell resolution, and how their cell-type specific immune regulatory roles may differ compared to protein-coding genes. Here, we perform the first in-depth characterization of lncRNA expression variation at single-cell resolution during Ebola virus (EBOV) infection in vivo. Using bulk RNA-sequencing from 119 samples and 12 tissue types, we significantly expand the current macaque lncRNA annotation. We then profile lncRNA expression variation in immune circulating single-cells during EBOV infection and find that lncRNAs expression in fewer cells is a major differentiating factor from their protein-coding gene counterparts. Upon EBOV infection, lncRNAs present dynamic and mostly cell-type specific changes in their expression profiles especially in monocytes, the main cell type targeted by EBOV. Such changes are associated with gene regulatory modules related to important innate immune responses such as interferon response and purine metabolism. Within infected cells, several lncRNAs have positively and negatively correlated expression with viral load, suggesting that expression of some of these lncRNAs might be directly hijacked by EBOV to attack host cells. This study provides novel insights into the roles that lncRNAs play in the host response to acute viral infection and paves the way for future lncRNA studies at single-cell resolution.

genomics↗

bioRxiv2020

Identification and analysis of splicing quantitative trait loci across multiple tissues in the human genome

We have developed an efficient and reproducible pipeline for the discovery of genetic variants affecting splicing (sQTLs), based on an approach that captures the intrinsically multivariate nature of this phenomenon. We employed it to analyze the multi-tissue transcriptome GTEx dataset, generating a comprehensive catalogue of sQTLs in the human genome. A core set of these sQTLs is shared across multiple tissues. Downstream analyses of this catalogue contribute to the understanding of the mechanisms underlying splicing regulation. We found that sQTLs often target the global splicing pattern of genes, rather than individual splicing events. Many of them also affect gene expression, but not always of the same gene, potentially uncovering regulatory loci that act on different genes through different mechanisms. sQTLs tend to be preferentially located in introns that are post-transcriptionally spliced, which would act as hotspots for splicing regulation. While many variants affect splicing patterns by directly altering the sequence of splice sites, many more modify the binding of RNA-binding proteins (RBPs) to target sequences within the transcripts. Genetic variants affecting splicing can have a phenotypic impact comparable or even stronger than variants affecting expression, with those that alter RBP binding playing a prominent role in disease.

genomics↗

bioRxiv2019

A limited set of transcriptional programs define major histological types and provide the molecular basis for a cellular taxonomy of the human body

We have produced RNA sequencing data for a number of primary cells from different locations in the human body. The clustering of these primary cells reveals that most cells in the human body share a few broad transcriptional programs, which define five major cell types: epithelial, endothelial, mesenchymal, neural and blood cells. These act as basic components of many tissues and organs. Based on gene expression, these cell types redefine the basic histological types by which tissues have been traditionally classified. We identified genes whose expression is specific to these cell types, and from these genes, we estimated the contribution of the major cell types to the composition of human tissues. We found this cellular composition to be a characteristic signature of tissues, and to reflect tissue morphological heterogeneity and histology. We identified changes in cellular composition in different tissues associated with age and sex and found that departures from the normal cellular composition correlate with histological phenotypes associated to disease. One Sentence SummaryA few broad transcriptional programs define the major cell types underlying the histology of human tissues and organs.

genomics↗

bioRxiv2019

Atlas of transcriptionally active transposable elements in human adult tissues

Approximately half of the human genome consists of mobile repetitive DNA sequences known as transposable elements (TEs). They are usually silenced by epigenetic mechanisms, but a few are known to escape silencing at embryonic stages, affecting early human development by regulating nearby protein-coding genes. To investigate transcriptional activity in human adult tissues we systematically investigate the expression landscape of about 4.2 million non-coding TEs in 8,051 RNA-Seq datasets from up to 49 adult tissues and 540 individuals. We show that approximately 79,558 individual TEs (2%). belonging to 856 subfamilies escape epigenetic silencing in adult tissues and become transcriptionally active, often in a very tissue-specific manner. Supporting a role for TEs in the regulation of expression of nearby genes, we found the expression of TEs often correlated with the expression of nearby genes, and significantly stronger when the TEs include eQTLs for the genes. We identified thousands of tissue-elevated, sex-associated TEs in the breast, ethnicity-associated in the skin and age-associated in the tibial artery, where we found a potential implication of two TE subfamilies in atherosclerosis. Our results suggest a functional role of TEs in the regulation of gene expression, support their implication in human phenotypes, and also serve as a comprehensive resource of transcriptionally active TEs in human adult tissues.

genomics↗

bioRxiv2017

Modified penetrance of coding variants by cis-regulatory variation shapes human traits

Coding variants represent many of the strongest associations between genotype and phenotype, however they exhibit inter-individual differences in effect, known as variable penetrance. In this work, we study how cis-regulatory variation modifies the penetrance of coding variants in their target gene. Using functional genomic and genetic data from GTEx, we observed that in the general population, purifying selection has depleted haplotype combinations that lead to higher penetrance of pathogenic coding variants. Conversely, in cancer and autism patients, we observed an enrichment of haplotype combinations that lead to higher penetrance of pathogenic coding variants in disease implicated genes, which provides direct evidence that regulatory haplotype configuration of causal coding variants affects disease risk. Finally, we experimentally demonstrated that a regulatory variant can modify the penetrance of a coding variant by introducing a Mendelian SNP using CRISPR/Cas9 on distinct expression haplotypes and using the transcriptome as a phenotypic readout. Our results demonstrate that joint effects of regulatory and coding variants are an important part of the genetic architecture of human traits, and contribute to modified penetrance of disease-causing variants.

genetics↗