Biology subjects

Vilarrasa-Blasi, R.

Publications and source records attributed to Vilarrasa-Blasi, R..

7 recordsLinked to original sources

bioRxiv2026

An integrated multimodal pan-organ atlas of the female reproductive system across the lifespan contextualises gynaecological pathologies

Single cell transcriptomics has transformed our knowledge of reproductive tissues, yet studies remain largely organ-specific and temporally limited, leaving an incomplete picture of how cell types are distributed across the reproductive system over a lifetime. Gynaecological conditions affect more than one in four females and frequently span multiple organs and life stages. To advance our understanding and treatment of these conditions, an integrated cellular reference is essential. Here we present the Human Female Reproductive System Cell Atlas v1: a single-cell transcriptomic resource integrating more than 2M cells across the ovary, fallopian tube, uterus, cervix and vagina over the lifespan and menstrual cycle, further integrated with spatial transcriptomics and chromatin accessibility profiling to define 210 cell types through community-based annotation. Cross-organ integration resolves shared and organ-specific cellular states, identifying uterine-specific perivascular populations lining uterine spiral arteries, hypoxia-sensing type 3 innate lymphoid cells (ILC3s) enriched in the uterus, and lipid-associated macrophages with distinct subsets in each reproductive organ, including a previously undescribed population shared between the uterus and fallopian tube. Cross-organ integration enables detection of ectopic epithelial populations in otherwise healthy donors, including endometrial-like cells within a paediatric ovary consistent with early endometriosis. Integration with genome-wide association studies (GWAS) reveals that risk variants for major gynecological conditions act in mesenchymal cell states defined by specific transcriptional programmes and spatial or temporal context - for instance, heavy menstrual bleeding risk is enriched in basal fibroblasts (SFRP5) of the regenerative endometrial compartment. An integrated chromatin accessibility atlas provides peak-to-gene maps across reproductive cell types, enabling nomination of disease effector genes and providing the first regulatory evidence linking a Polyendocrine Metabolic Ovarian Syndrome (PMOS) risk locus to INHBB in granulosa cells. Together, this resource establishes a cellular and molecular framework for reproductive biology and the pathogenesis of neglected gynaecological conditions.

Cell Biology↗

bioRxiv2026

Self-supervised learning for a gene program-centric view of cell states

Single-cell omics has extended the biological interrogation of cell state from examining the expression of individual genes to unbiased profiling of tens of thousands of genes at once. However, extracting biological insights from such high-dimensional data remains challenging. To enable downstream analyses, many computational approaches compress cell state into a single latent representation. This can obscure the structure of underlying gene programs (GP), defined as coordinated sets of biologically related genes, such as signalling pathway response modules or transcription factor targets. Here, we present Tripso, a self-supervised transformer deep learning model which learns multiple GP-specific embeddings from predefined GPs, while also enabling the discovery of novel, data-driven GPs. Tripso facilitates principled comparisons across development, disease, and experimental systems. Firstly, in a dataset of human hematopoietic cells spanning prenatal development through adulthood and aging and including newly generated data, Tripso resolved age-specific GP patterns, including elevated JAK-STAT activity in pediatric hematopoietic cells and postnatal shifts in IKZF1 GP activity during B cell differentiation. Secondly, leveraging Tripso GP embeddings and comparing in vivo to in vitro data, we hypothesized and experimentally validated that inhibition of the SEC61 translocon improved maintenance of hematopoietic stem cells in culture. Finally, Tripsos capacity for data-driven GP discovery revealed a previously uncharacterized tissue-resident memory T cell GP with increased activity in atopic dermatitis. Its spatial co-localization with sebaceous gland-associated immune niches was demonstrated in spatial transcriptomic and proteomic data. Thus, by moving beyond single embeddings of cellular states, Tripso enables interpretable and actionable discoveries, demonstrating how GP-centric modelling can generate hypotheses with substantial biomedical relevance. By anchoring cellular representations in meaningful GPs, Tripso establishes a principled and biologically grounded framework towards the development of interpretable virtual cell models.

bioinformatics↗

bioRxiv2025

Decoding human B cell ontogeny in prenatal and adult bone marrow and in vitro models via single-cell multiomics

In humans, the bone marrow becomes the primary site for B lymphopoiesis during the second trimester of pregnancy and continues throughout life. Prenatal and adult B cell progenitors play distinct roles in the aetiology and pathology of paediatric and adult hematopoietic malignancies, though the molecular drivers of these differences remain unclear. Here, we created a comprehensive multiomics atlas of over 500k cells covering immune and stromal compartment from prenatal and adult bone marrow, enabling high-resolution analysis of the cell-intrinsic and cell-extrinsic processes that modulate prenatal and adult B lymphopoiesis. Even though B cells follow broadly similar developmental trajectories, we identify a novel postnatal lateCLP subset equivalent to prenatal preProB cells, and uncover prenatal cells carry several signatures characteristic of leukemias, including enhanced proliferation, higher RAG1/RAG2 activity, extrinsic B cell signals such as IL7, and lower retention signals in the bone marrow. We also developed and characterised, at both cellular and molecular levels, a new experimental framework for generating B cell precursors from human induced pluripotent stem cells (hiPSCs), and show that it faithfully recapitulates key stages of B cell differentiation. Together, our single-cell multiomics atlas of B lymphopoiesis in vivo and in vitro offers detailed insights into the unique molecular features of prenatal and adult B cell lymphopoiesis, and serves as a powerful resource for investigating the early events that contribute to haematological disorders.

immunology↗

bioRxiv2023

Time- and lineage-resolved transcriptional profiling uncovers gene expression programs and clonal relationships that underlie human T lineage specification

T cells develop from multi-potent hematopoietic progenitors in the thymus and provide adaptive protection against pathogens and cancer. However, the emergence of human T cell-competent blood progenitors, and their subsequent specification to the T lineage, has been challenging to capture in real time. Here, we leveraged a pluripotent stem cell differentiation system to understand the transcriptional dynamics and cell fate restriction events that underlie this critical developmental process. Time-resolved single cell RNA sequencing revealed that cell-cycle exit, downregulation of the multipotent hematopoietic program, and upregulation of >90 lineage-associated transcription factors all occur within a highly co-ordinated and narrow developmental window. Computational gene-regulatory network inference elucidated the transcriptional logic of T lineage specification, uncovering an important role for YBX1. We mapped the differentiation cell fate hierarchy using transcribed lineage barcoding and mathematical trajectory inference and discovered that mast and myeloid potential bifurcate from each other early in haematopoiesis, upstream of T lineage restriction. Collectively, our analyses provide a quantitative, time-resolved model of human T cell specification with relevance for regenerative medicine and developmental immunology.

immunology↗

bioRxiv2019

Dynamics of genome architecture and chromatin function during human B cell differentiation and neoplastic transformation

Despite recent advances, the dynamics of genome architecture and chromatin function during human cell differentiation and its potential reorganization upon neoplastic transformation remains poorly characterized. Here, we integrate in situ Hi-C and nine additional omic layers to define and biologically characterize the dynamic changes in three-dimensional (3D) genome architecture across normal B cell differentiation and in neoplastic cells from different subtypes of chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) patients. Beyond conventional active (A) and inactive (B) compartments, an integrative analysis of Hi-C data reveals the presence of a highly-dynamic intermediate compartment enriched in poised and polycomb-repressed chromatin. During B cell development, we detect that 28% of the compartments change at defined maturation stages and mostly involve the intermediate compartment. The transition from naive to germinal center B cells is associated with widespread chromatin activation, which mostly reverts into the naive state upon further maturation of germinal center cells into memory B cells. The analysis of CLL and MCL neoplastic cells points both to entity and subtype-specific alterations in chromosome organization. Remarkably, we observe that large chromatin blocks containing key disease-specific genes alter their 3D genome organization. These include the inactivation of a 2Mb region containing the EBF1 gene in CLL and the activation of a 6.1Mb region containing the SOX11 gene in clinically aggressive MCL. This study indicates that 3D genome interactions are extensively modulated during normal B cell differentiation and that the genome of B cell neoplasias acquires a tumor-specific 3D genome architecture.

genomics↗

bioRxiv2019

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting co-regulated adjacent genes. Among target genes upregulated by this process, we found members of the NOTCH, NFkB, mTOR1 signaling and p53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status, and in addition identified PRDM5 as a novel essential gene for MM. Collectively our data indicates that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

cancer biology↗

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↗