Biology subjects

Guigo, R.

Publications and source records attributed to Guigo, R..

At least 19 recordsLinked to original sources

bioRxiv2025

A phylogeny aware analysis of gene function for the biodiversity genomics era

In the biodiversity genomics era, vast gene catalogs have rapidly accumulated, but how gene functions map onto major evolutionary transitions remains vague. We integrated phylogenomics with functional annotations to trace the emergence of [~]4.5 million genes and their associated functions in 508 representative species across the tree of life. Using this top-down, function-centric approach, we mapped the evolutionary history of well-annotated biological functions, revealing key insights and widespread parallelism. For instance, the largest bursts of gene and function gains aligned with key evolutionary transitions, including the origins of eukaryotes, animals, land plants, and vertebrates. Independent transitions to multicellularity and terrestrial life showed convergent enrichment of semantically similar functions (involving entirely different gene families), and the presence of orthologous genes often belonging to ancient gene families. For example, terrestrialization nodes in slime molds, plants, and animals coincided with gains in stress-tolerance and developmental genes, whereas multicellularity in animals, fungi, plants, and slime molds consistently involved expansions in cell-adhesion and communication functions. Thus, our framework enables scalable interpretation of new genomes in an evolutionary context and offers a roadmap for exploring the genomic basis of biodiversity.

evolutionary biology↗

bioRxiv2025

CapTrap-seq: Advancing zebrafish transcriptomic research through high-fidelity full-length RNA sequencing

Zebrafish is a valuable model organism thanks to its genetic and anatomical similarities to humans, offering a more relevant system for studying human biology and disease than in vitro or non-vertebrate models. However, its use in large-scale transcriptomic research is still limited. Most zebrafish studies focus on global expression profiling in specific developmental contexts, contributing little toward improving and expanding gene annotations. These gaps lead to inaccuracies in gene quantification and downstream functional analyses, ultimately reducing the effectiveness of zebrafish as a model system. Further challenges include ineffective ribodepletion methods and limited resources for validate transcript boundaries and splicing patterns. To overcome these challenges, we applied CapTrap-seq, a long-read sequencing method that combines Cap-trapping with oligo(dT) priming to identify 5-capped, full-length transcripts from both developmental and adult tissue samples. To promote detection of longer RNA molecules, we introduced a size-selection step into CapTrap-seq protocol, which further improved detection of transcript ends without compromising its quantitative accuracy. Our results highlight the genome-agnostic nature of CapTrap-seq, enabling generation of accurate transcript models in non-mammalian systems at high-throughput. CapTrap-seq also facilitates functional annotation of zebrafish genes by uncovering novel, spliced transcript isoforms with potential biological significance.

genomics↗

bioRxiv2025

Evidence of distal regulations orchestrated by RNAs initiating at short tandem repeats

Short Tandem Repeats (STRs), also called microsatellites, correspond to tandemly repeated short DNA motifs (1 to 6 bp) and are one of the most polymorphic and abundant repetitive elements in the human genome. Variations of their length (i.e. number of consecutive repeats) have been implicated in gene expression regulation (termed expression(e)STRs). Using captrapping followed by long read sequencing, we discovered that STRs can host transcription start sites, the presence of which depends mainly on STR flanking sequences. Here, we investigate the effect of SNPs located in these sequences and ask whether STR-initiating RNAs have regulatory potential. First, we develop fully interpretable deep learning-based models, called Modular Neural Networks, able to predict, for each STR class, the level of RNAs using 101bp-long sequences encompassing STRs. Analysis of MNN filters allows us to identify multiple regulatory elements and candidate transcription factors. Second, leveraging genome sequencing and gene expression data from the Genotype-Tissue Expression project, we use the output of our models to link the levels of STR-initiating RNAs to the expression of nearby genes. We identify 14,340 significant associations (coined RNA(r)STRs) and illustrate how this novel resource can help interpret non-coding variants associated with complex traits and diseases. Third, we unveil an intricate transcriptional interplay between STR-initiating RNAs and Alu repeats that may couple their regulatory actions, extending both the nature and the functional importance of non-coding transcription and shedding new light on the complexity of distal regulations orchestrated by repeated sequences.

genomics↗

bioRxiv2025

Long-read transcriptomics of a diverse human cohort reveals widespread ancestry bias in gene annotation

Accurate gene annotations are fundamental for interpreting genetic variation, cellular function, and disease mechanisms. However, current human gene annotations are largely derived from transcriptomic data of individuals with European ancestry, introducing potential biases that remain uncharacterized. Here, we generate over 800 million full-length reads with long-read RNA-seq in 43 lymphoblastoid cell line samples from eight genetically-diverse human populations and build a cross-ancestry gene annotation. We show that transcripts from non-European samples are underrepresented in reference gene annotations, leading to systematic biases in allele-specific transcript usage analyses. Furthermore, we show that personal genome assemblies enhance transcript discovery compared to the generic GRCh38 reference assembly, even though genomic regions unique to each individual are heavily depleted of genes. These findings underscore the urgent need for a more inclusive gene annotation framework that accurately represents global transcriptome diversity.

genomics↗

bioRxiv2025

EPIraction - an atlas of candidate enhancer-gene interactions in human tissues and cell lines.

Enhancer-gene maps are essential to understand gene regulation. The identification of enhancers contributing to regulating a given gene, however, is challenging as they may lie far from the gene and act in a tissue-specific manner. Here we present EPIraction, an enhancer-gene atlas in the human genome. As H3K27ac is a typical mark of enhancer function, EPIraction relies on an exhaustive collection of 1,538 H3K27ac ChIP-Seq datasets. We used these data together with other epigenomic data to measure enhancer activity. To predict enhancer-gene interactions we first applied the conventional Activity By Contact algorithm to score enhancer-gene pairs in individual tissues. Then, we re-scored the interaction rewarding those present in biologically similar tissues. We used our predictions to annotate the candidate target genes for 1,664,956 SNPs from 3,693 UK Biobank and 760 FinnGen GWAS traits. The EPIraction predictions can be accessed through the portal at https://epiraction.crg.es. The portal can be employed to produce annotations for user-provided lists of SNPs or genomic intervals.

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

Overcoming the widespread flaws in the annotation of vertebrate selenoprotein genes in public databases

Selenocysteine (Sec) is a non-canonical amino acid incorporated into selenoproteins, oxidoreductase enzymes carrying essential roles in redox homeostasis. Sec insertion occurs in response to UGA, normally interpreted as stop codon, but recoded in selenoprotein mRNAs. Owing to the dual function of UGA, the identification of selenoprotein genes poses a challenge. We show that the vertebrate selenoprotein genes are widely misannotated in major public databases. Only 12% and 6% of selenoprotein genes are well annotated in Ensembl and NCBI GenBank, respectively, due to the lack of dedicated selenoprotein annotation pipelines. In most cases (81% and 84%), overlapping flawed annotations are present which lack the Sec-encoding UGA. In contrast, NCBI RefSeq employs a dedicated selenoprotein pipeline, yet with some shortcomings: its selenoprotein annotations are correct in 76% of cases, and most errors affect families with a C-terminal Sec residue. We argue that selenoproteins must be correctly annotated in public databases and that must occur via automated pipelines, to keep the pace with genome sequencing. To facilitate this task, we present a new version of Selenoprofiles, an homology based tool for selenoprotein prediction that produces predictions with accuracy comparable to manual curation, and can be easily deployed and integrated in existing annotation pipelines.

bioinformatics↗

bioRxiv2024

Expression dynamics of long non-coding RNAs during imaginal disc development and regeneration in Drosophila

The discovery of functional long non-coding RNAs (lncRNAs) changed their initial concept as transcriptional noise. LncRNAs have been found to participate in the regulation of multiple biological processes, including chromatin structure, gene expression, splicing, and mRNA degradation and translation. However, functional studies of lncRNAs are hindered by the usual lack of phenotypes upon deletion or inhibition. Here, we used Drosophila imaginal discs as a model system to identify lncRNAs involved in development and regeneration. We examined a subset of lncRNAs expressed in the wing, leg, and eye disc development. Additionally, we analyzed transcriptomic data from regenerating wing discs to profile the expression pattern of lncRNAs during tissue repair. We focused on the lncRNA CR40469, which is upregulated during regeneration. We generated CR40469 mutant flies that developed normally but showed impaired wing regeneration upon the induction of cell death. The ability of these mutants to regenerate was restored by the ectopic expression of CR40469. Furthermore, we found that the lncRNA CR34335 has a high degree of sequence similarity with CR40469 and can partially compensate for its function during regeneration in the absence of CR40469. Our findings point to a potential role of the lncRNA CR40469 in trans during the response to damage in the wing imaginal disc.

developmental biology↗

bioRxiv2024

Studying relative RNA localization. From nucleus to the cytosol.

The precise coordination of important biological processes, such as differentiation and development, is highly dependent on the regulation of expression of the genetic information. The flow of the genetic information is tightly regulated on multiple levels. Among them, RNA export to cytosol is an essential step for the production of proteins in eukaryotic cells. Hence, estimating the relative concentration of RNA molecules of a given transcript species in the nucleus and in the cytosol is of major significance as it contributes to the understanding of the dynamics of RNA trafficking between the nucleus and the cytosol. The most efficient way to estimate the levels of RNA species genome-wide is through RNA sequencing (RNAseq). While RNAseq can be performed separately in the nucleus and in the cytosol, because measured transcript levels are relative to the total volume of RNA in these compartments, and because this volume is usually unknown, the transcript levels in the nucleus and in the cytosol cannot be directly compared. Here we show theoretically that if, in addition to nuclear and cytosolic RNA-seq, whole cell RNA-seq is also performed, then accurate estimations of the localization of transcripts can be obtained. Based on this, we designed a method that estimates, first the fraction of the total RNA volume in the cytosol (nucleus), and then, this fraction for every transcript. We evaluate our methodology on simulated data and nuclear and cytosolic single cell data available. Finally, we use our method to investigate the cellular localization of transcripts using bulk RNAseq data from the ENCODE project.

bioinformatics↗

bioRxiv2023

The BioGenome Portal: a web-based platform for biodiversity genomics data management

Biodiversity genomics projects are underway with the aim of sequencing the genomes of all eukaryotic species on Earth. Here we describe the BioGenome Portal, a web-based application to facilitate organization and access to the data produced by biodiversity genomics projects. The portal integrates user-generated data with data deposited in public repositories. The portal generates sequence status reports that can be eventually ingested by designated meta-data tracking systems, facilitating the coordination task of these systems. The portal is open-source and fully customizable. It can be deployed at any site with minimum effort, contributing to the democratization of biodiversity genomics projects. Here, we illustrate the features of the BioGenome Portal through two specific instances. One instance corresponds to the Earth Biogenome Project, the worldwide umbrella for most biodiversity genomics projects. The other instance corresponds to the Catalan Initiative for the Earth Biogenome Project, a regional project aiming to sequencing the genomes of the species of the Catalan Linguistic Area.

bioinformatics↗

bioRxiv2023

Integration of transcription regulation and functional genomic data reveals lncRNA SNHG6's role in hematopoietic differentiation and leukemia

BackgroundLong non-coding RNAs (lncRNAs) are pivotal players in cellular processes, and their unique cell-type specific expression patterns make them attractive biomarkers and therapeutic targets. Yet, the functional roles of most lncRNAs remain enigmatic. To address the need to identify new druggable lncRNAs, we developed a comprehensive approach integrating transcription factor binding data with other genetic features to generate a machine learning model, which we have called INFLAMeR (Identifying Novel Functional LncRNAs with Advanced Machine Learning Resources). MethodsINFLAMeR was trained on high-throughput CRISPR interference (CRISPRi) screens across seven cell lines, and the algorithm was based on 71 genetic features. To validate the predictions, we selected candidate lncRNAs in the K562 leukemia cell line and determined the effect of their knockdown on cell proliferation and chemotherapy drug resistance. We further performed transcriptomic analysis for candidate genes. Based on these findings, we assessed the lncRNA Small Nucleolar RNA Host Gene 6 (SNHG6) for its role in myeloid differentiation by incubation with Phorbol 12-myristate 13-acetate (PMA) to induce megakaryocyte differentiation, or with hemin to induce erythrocyte differentiation. ResultsThe INFLAMeR model successfully reconstituted CRISPRi screening data and predicted functional lncRNAs that were previously overlooked. Intensive cell-based and transcriptomic validation of nearly fifty genes in K562 revealed cell type-specific functionality for 85% of the predicted lncRNAs. Our cell-based and transcriptomic analyses predicted a role for SNHG6 in hematopoiesis and leukemia. Consistent with its predicted role in hematopoietic differentiation, SNHG6 transcription is regulated by hematopoiesis-associated transcription factors. Knockdown of SNHG6 reduced the proliferation of leukemia cells and sensitized them to differentiation. Treatment of K562 leukemic cells with hemin and PMA, respectively, demonstrated that SNHG6 inhibits red blood cell differentiation but strongly promotes megakaryocyte differentiation. Despite SNHG6 transcripts showing strong cytoplasmic enrichment, SNHG6 regulates the expression of hematopoietic genes such as PPBP (Pro-Platelet Basic Protein) and PF4 (Platelet Factor 4). ConclusionsOur approach not only improved the identification and characterization of functional lncRNAs through genomic approaches in a cell type-specific manner, but also identified new lncRNAs with a role in hematopoiesis and leukemia. Such approaches cab be used to identify new targets for precision therapy.

genetics↗

bioRxiv2023

An encyclopedia of enhancer-gene regulatory interactions in the human genome

Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation and the impact of human genetic variation on disease1-6. Here we create and evaluate a resource of >13 million enhancer-gene regulatory interactions across 352 cell types and tissues, by integrating predictive models, measurements of chromatin state and 3D contacts, and large-scale genetic perturbations generated by the ENCODE Consortium7. We first create a systematic benchmarking pipeline to compare predictive models, assembling a dataset of 10,411 element-gene pairs measured in CRISPR perturbation experiments, >30,000 fine-mapped eQTLs, and 569 fine-mapped GWAS variants linked to a likely causal gene. Using this framework, we develop a new predictive model, ENCODE-rE2G, that achieves state-of-the-art performance across multiple prediction tasks, demonstrating a strategy involving iterative perturbations and supervised machine learning to build increasingly accurate predictive models of enhancer regulation. Using the ENCODE-rE2G model, we build an encyclopedia of enhancer-gene regulatory interactions in the human genome, which reveals global properties of enhancer networks, identifies differences in the functions of genes that have more or less complex regulatory landscapes, and improves analyses to link noncoding variants to target genes and cell types for common, complex diseases. By interpreting the model, we find evidence that, beyond enhancer activity and 3D enhancer-promoter contacts, additional features guide enhancer-promoter communication including promoter class and enhancer-enhancer synergy. Altogether, these genome-wide maps of enhancer-gene regulatory interactions, benchmarking software, predictive models, and insights about enhancer function provide a valuable resource for future studies of gene regulation and human genetics.

genomics↗

bioRxiv2023

CapTrap-Seq: A platform-agnostic and quantitative approach for high-fidelity full-length RNA transcript sequencing

Long-read RNA sequencing is essential to produce accurate and exhaustive annotation of eukaryotic genomes. Despite advancements in throughput and accuracy, achieving reliable end-to-end identification of RNA transcripts remains a challenge for long-read sequencing methods. To address this limitation, we developed CapTrap-seq, a cDNA library preparation method, which combines the Cap-trapping strategy with oligo(dT) priming to detect 5capped, full-length transcripts, together with the data processing pipeline LyRic. We benchmarked CapTrap-seq and other popular RNA-seq library preparation protocols in a number of human tissues using both ONT and PacBio sequencing. To assess the accuracy of the transcript models produced, we introduced a capping strategy for synthetic RNA spike-in sequences that mimics the natural 5cap formation in RNA spike-in molecules. We found that the vast majority (up to 90%) of transcript models that LyRic derives from CapTrap-seq reads are full-length. This makes it possible to produce highly accurate annotations with minimal human intervention.

genomics↗

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↗

bioRxiv2022

Molecular signatures of alternative fitness strategies in a facultatively social hover wasp

Social insect queens and workers represent ideal models with which to understand the expression and regulation of alternative reproductive phenotypes. Most research in this area has focused on the molecular regulation of reproductive castes in obligately social taxa with complex social systems, while relatively few studies have addressed the molecular basis of caste in species in which the division of reproductive labour is more plastic. As a result, it is not clear whether, and to what extent, the mechanisms of caste in species with reproductive plasticity are the same as those that exist at the highest levels of social complexity. To address this knowledge gap, we analyse brain transcriptomic data for non-reproductives and reproductives of the facultatively social hover wasp Liostenogaster flavolineata, a representative of one of the simplest forms of social living. By experimentally manipulating the reproductive queues exhibited by social groups of this species, we show that reproductive division of labour in this species is associated with surprisingly distinct transcriptomic signatures, similar to those observed in more complex social taxa; that variation in gene expression among non-reproductives reflects their investment into foraging effort more than their social rank; and that distinct co-expressed gene sets are associated with differential investment into alternative reproductive strategies. These results elucidate robust transcriptomic signals that represent the proximate basis of division of labour at the simplest level of insect sociality, and show these signals to be remarkably similar to those in more derived species.

evolutionary biology↗

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

A transcriptional program shared across lineages underlies cell differentiation during metazoan development

BackgroundDuring development, most cells undergo striking changes in order to develop into functional tissues. All along this process, the identity of each tissue arises from the particular combination of regulatory transcription factors that specifically control the expression of relevant genes for growth, pattern formation and differentiation. In this scenario, regulation of gene expression turns out to be essential to determine cell fate and tissue specificity. ResultsTo characterize the dynamic transcriptional profiles during cellular differentiation, we tracked down the transcriptome of committed cells in different Drosophila melanogaster tissues and compartments at a number of developmental stages. We found that during fly development, temporal transcriptional changes shared across lineages are much larger than spatial lineage-specific transcriptional changes, and that cellular differentiation is dominated by a transcriptional program, common to multiple lineages, that governs the transition from undifferentiated to fully differentiated cells independently from the differentiation end point. The program is under weak epigenetic regulation, and it is characterized by downregulation of genes associated with cell cycle, and concomitant activation of genes involved in oxidative metabolism. Largely orthogonal to this program, tissue specific transcriptional programs, defined by a comparatively small number of genes are responsible for lineage specification. Transcriptome comparisons with worm, mouse and human, reveal that this transcriptional differentiation program is broadly conserved within metazoans. ConclusionsOur data provides a novel perspective to metazoan development, and strongly suggest a model, in which the main transcriptional drive during cell type and tissue differentiation is the transition from precursor undifferentiated to terminally differentiated cells, irrespective of cell type.

genomics↗

bioRxiv2021

Alu-mediated weak CEBPA binding and slow B cell transdifferentiation in human

Many developmental and differentiation processes take substantially longer in human than in mouse. To investigate the molecular mechanisms underlying this phenomenon, here we have specifically focused on the transdifferentiation from B cells to macrophages. The process is triggered by exactly the same molecular mechanism -- the induction by the transcription factor (TF) CEBPA -- but takes three days in mouse and seven in human (1, 2). In mouse, the speed of this process is known to be associated with Myc expression (3). We found that in this species, CEBPA binds strongly to the Myc promoter, efficiently down-regulating Myc. In human, in contrast, CEBPA does not bind this promoter, and MYC is indirectly and more slowly down-regulated. Attenuation of CEBPA binding is not specific to the MYC promoter, but a general trait of the human genome across multiple biological conditions. We traced back weak CEBPA binding to the primate-specific Alu repeat expansion. Many Alu repeats carry strong CEBPA binding motifs, which sequester CEBPA, and attenuate CEBPA binding genome-wide. We observed similar CEBPA and MYC dynamics in natural processes regulated by CEBPA, suggesting that CEBPA attenuation could underlie the longer duration in human processes controlled by this factor. Our work highlights the highly complex mode in which biological information is encoded in genome sequences, evolutionarily connecting, in an unexpected way, lineage-specific transposable element expansions to species-specific changes in developmental tempos.

bioinformatics↗