Biology subjects

Borsari, B.

Publications and source records attributed to Borsari, B..

11 recordsLinked to original sources

bioRxiv2025

Epigenetic characterization of pseudogenes across human tissues

Pseudogenes have long been considered non-functional remnants of genome evolution. However, compared to other noncoding elements, their epigenetic regulation remains poorly understood, largely due to their sequence similarity to parent genes and the lack of systematic functional analyses. Here, we leverage matched transcriptomic and epigenomic data from the ENCODE EN-TEx project, spanning [~]30 human tissues, to comprehensively profile pseudogenes and compare them to protein-coding transcripts and lncRNAs. Our analyses reveal epigenetic differences among pseudogene biotypes. Even when transcribed, processed pseudogenes--unlike protein-coding transcripts and unprocessed pseudogenes--lack canonically active histone marks and open chromatin signatures at their promoters. Instead, these regions are frequently associated with retrotransposon sequences, enriched for YY1-binding sites, and often engage distal enhancer-like elements through long-range genomic contacts. These findings suggest that processed pseudogenes may adopt regulatory mechanisms akin to transposable elements such as LINEs, relying on YY1-mediated enhancer-promoter looping or other distal interactions to facilitate transcription. By publicly releasing our catalog of pseudogene promoter regions, we provide a comprehensive resource for investigating the epigenetic and functional roles of pseudogenes in the human genome.

bioinformatics↗

bioRxiv2024

An Expanded Registry of Candidate cis-Regulatory Elements for Studying Transcriptional Regulation

Mammalian genomes contain millions of regulatory elements that control the complex patterns of gene expression. Previously, The ENCODE consortium mapped biochemical signals across many cell types and tissues and integrated these data to develop a Registry of 0.9 million human and 300 thousand mouse candidate cis-Regulatory Elements (cCREs) annotated with potential functions1. We have expanded the Registry to include 2.35 million human and 927 thousand mouse cCREs, leveraging new ENCODE datasets and enhanced computational methods. This expanded Registry covers hundreds of unique cell and tissue types, providing a comprehensive understanding of gene regulation. Functional characterization data from assays like STARR-seq, MPRA, CRISPR perturbation, and transgenic mouse assays now cover over 90% of human cCREs, revealing complex regulatory functions. We identified thousands of novel silencer cCREs and demonstrated their dual enhancer/silencer roles in different cellular contexts. Integrating the Registry with other ENCODE annotations facilitates genetic variation interpretation and trait-associated gene identification, exemplified by discovering KLF1 as a novel causal gene for red blood cell traits. This expanded Registry is a valuable resource for studying the regulatory genome and its impact on health and disease.

genomics↗

bioRxiv2024

GENCODE: massively expanding the lncRNA catalog through capture long-read RNA sequencing

Accurate and complete gene annotations are indispensable for understanding how genome sequences encode biological functions. For more than twenty years, the GENCODE consortium has developed reference annotations for the human and mouse genomes, becoming a foundation for biomedical and genomics communities worldwide. Nevertheless, collections of important yet poorly-understood gene classes like long non-coding RNAs (lncRNAs) remain incomplete and scattered across multiple, uncoordinated catalogs. To address this, GENCODE has undertaken the most comprehensive lncRNA annotation effort to date. This is founded on the manually supervised computational annotation of full-length targeted long-read sequencing, on matched embryonic and adult tissues, of orthologous regions in human and mouse. Altogether 17,931 human genes (140,268 transcripts) and 22,784 mouse genes (136,169 transcripts) have been added to the GENCODE catalog representing a 2-fold and 6-fold growth in transcripts, respectively - the greatest increase in the number of annotated human genes since the sequencing of the human genome. Our targeted design assigned human-mouse orthologs at a rate beyond previous studies, tripling the number of human disease-associated lncRNAs that have mouse orthologs. Novel lncRNA genes consistently exhibit biological signals of functionality, and they greatly enhance the functional interpretability of the human genome. While poorly expressed in bulk RNA-Seq samples, many of them are highly expressed in specific cell populations, maybe even contributing to cell-type determination. The expanded GENCODE lncRNA annotations mark a critical step toward deciphering the human and mouse genomes.

genomics↗

bioRxiv2023

chronODE: A framework to integrate time-series multi-omics data based on ordinary differential equations combined with machine learning

Most functional genomic studies are conducted in steady-state conditions, therefore providing a description of molecular processes at a particular moment of cell differentiation or organismal development. Longitudinal studies can offer a deeper understanding of the kinetics underlying epigenetic events and their contribution to defining cell-type-specific transcriptional programs. Here we develop chronODE, a mathematical framework based on ordinary differential equations that uniformly models the kinetics of temporal changes in gene expression and chromatin features. chronODE employs biologically interpretable parameters that capture tissue-specific kinetics of genes and regulatory elements. We further integrate this framework with a neural-network architecture that can link and predict changes across different data modalities by solving multivariate time-series regressions. Next, we apply this framework to investigate region-specific kinetics of epigenome rewiring in the developing mouse brain, and we demonstrate that changes in chromatin accessibility within regulatory elements can accurately predict changes in the expression of putative target genes over the same time period. Finally, by integrating single-cell ATAC-seq data generated during the same time course, we show that regulatory elements characterized by fast activation kinetics in bulk measurements are active in early-appearing cell types, such as radial glial and other neural progenitors, whereas elements characterized by slow activation kinetics are specific to more differentiated cell types that emerge at later stages of brain development.

bioinformatics↗

bioRxiv2023

The ENCODE4 long-read RNA-seq collection reveals distinct classes of transcript structure diversity

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3 end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of 200,000 full-length transcripts, 40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3 processing are deployed across human tissues, with nearly half of multitranscript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.

genomics↗

bioRxiv2021

Multi-tissue integrative analysis of personal epigenomes

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of personal epigenomes, for [~]25 tissues and >10 assays in four donors (>1500 open-access functional genomic and proteomic datasets, in total). Each dataset is mapped to a matched, diploid personal genome, which has long-read phasing and structural variants. The mappings enable us to identify >1 million loci with allele-specific behavior. These loci exhibit coordinated epigenetic activity along haplotypes and less conservation than matched, non-allele-specific loci, in a fashion broadly paralleling tissue-specificity. Surprisingly, they can be accurately modelled just based on local nucleotide-sequence context. Combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci and enables models for transferring known eQTLs to difficult-to-profile tissues. Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

genomics↗

bioRxiv2020

Dynamics of gene expression and chromatin marking during cell state transition

We have monitored the transcriptomic and epigenomic status of cells at twelve time-points during the transdifferentiation of human pre-B cells into macrophages. Using this data, we have investigated some fundamental questions regarding the role of chromatin in gene expression. We have found that, over time, genes are characterized by a limited number of chromatin states (combinations of histone modifications), and that, consistently, chromatin changes over genes tend to occur in a coordinated manner. We have observed strong association between these changes and gene expression only at the time of initial gene activation. Activation is preceded by H3K4me1 and H3K4me2, and followed in a precise order by most other histone modifications. Further changes in gene expression, comparable or even stronger than those at initial activation, occur without associated changes in histone modifications. The data generated here constitutes, thus, a unique resource to investigate transcriptomic and epigenomic dynamics during a differentiation process.

genomics↗

bioRxiv2020

Intronic enhancers regulate the expression of genes involved in tissue-specific functions and homeostasis

Tissue function and homeostasis reflect the gene expression signature by which the combination of ubiquitous and tissue-specific genes contribute to the tissue maintenance and stimuli-responsive function. Enhancers are central to control this tissue-specific gene expression pattern. Here, we explore the correlation between the genomic location of enhancers and their role in tissue-specific gene expression. We found that enhancers showing tissue-specific activity are highly enriched in intronic regions and regulate the expression of genes involved in tissue-specific functions, while housekeeping genes are more often controlled by intergenic enhancers. Notably, an intergenic-to-intronic active enhancers continuum is observed in the transition from developmental to adult stages: the most differentiated tissues present higher rates of intronic enhancers, while the lowest rates are observed in embryonic stem cells. Altogether, our results suggest that the genomic location of active enhancers is key for the tissue-specific control of gene expression.

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

Functional Annotation of Human Long Non-Coding RNAs via Molecular Phenotyping

Long non-coding RNAs (lncRNAs) constitute the majority of transcripts in the mammalian genomes and yet, their functions remain largely unknown. We systematically knockdown 285 lncRNAs expression in human dermal fibroblasts and quantified cellular growth, morphological changes, and transcriptomic responses using Capped Analysis of Gene Expression (CAGE). Antisense oligonucleotides targeting the same lncRNA exhibited global concordance, and the molecular phenotype, measured by CAGE, recapitulated the observed cellular phenotypes while providing additional insights on the affected genes and pathways. Here, we disseminate the largest to-date lncRNA knockdown dataset with molecular phenotyping (over 1,000 CAGE deep-sequencing libraries) for further exploration and highlight functional roles for ZNF213-AS1 and lnc-KHDC3L-2.

genomics↗

bioRxiv2018

Novel autoregulatory cases of alternative splicing coupled with nonsense-mediated mRNA decay

Nonsense-mediated decay (NMD) is a eukaryotic mRNA surveillance system that selectively degrades transcripts with premature termination codons (PTC). Many RNA-binding proteins (RBP) regulate their expression levels by a negative feedback loop, in which RBP binds its own pre-mRNA and causes alternative splicing to introduce a PTC. We present a bioinformatic framework to identify novel such autoregulatory feedback loops by combining eCLIP assays for a large panel of RBPs with the data on shRNA inactivation of NMD pathway, and shRNA-depletion of RBPs followed by RNA-seq. We show that RBPs frequently bind their own pre-mRNAs and respond prominently to NMD pathway disruption. Poison and essential exons, i.e., exons that trigger NMD when included in the mRNA or skipped, respectively, respond oppositely to the inactivation of NMD pathway and to the depletion of their host genes, which allows identification of novel autoregulatory mechanisms for a number of human RBPs. For example, SRSF7 binds its own pre-mRNA and facilitates the inclusion of two poison exons; SFPQ binding promotes switching to an alternative distal 3-UTR that is targeted by NMD; RPS3 activates a poison 5-splice site in its pre-mRNA that leads to a frame shift; U2AF1 binding activates one of its two mutually exclusive exons, leading to NMD; TBRG4 is regulated by cluster splicing of its two essential exons. Our results indicate that autoregulatory negative feedback loop of alternative splicing and NMD is a generic form of post-transcriptional control of gene expression.

bioinformatics↗