Biology subjects

Carbonell-Sala, S.

Publications and source records attributed to Carbonell-Sala, S..

6 recordsLinked to original sources

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

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↗

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

Systematic assessment of long-read RNA-seq methods for transcript identification and quantification

AbstractThe Long-read RNA-Seq Genome Annotation Assessment Project (LRGASP) Consortium was formed to evaluate the effectiveness of long-read approaches for transcriptome analysis. The consortium generated over 427 million long-read sequences from cDNA and direct RNA datasets, encompassing human, mouse, and manatee species, using different protocols and sequencing platforms. These data were utilized by developers to address challenges in transcript isoform detection and quantification, as well as de novo transcript isoform identification. The study revealed that libraries with longer, more accurate sequences produce more accurate transcripts than those with increased read depth, whereas greater read depth improved quantification accuracy. In well-annotated genomes, tools based on reference sequences demonstrated the best performance. When aiming to detect rare and novel transcripts or when using reference-free approaches, incorporating additional orthogonal data and replicate samples are advised. This collaborative study offers a benchmark for current practices and provides direction for future method development in transcriptome analysis.

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↗

bioRxiv2021

Profiling subcellular localization of nuclear-encoded mitochondrial gene products in zebrafish

Most mitochondrial proteins are encoded by nuclear genes, synthetized in the cytosol and targeted into the organelle. The import of some, but not all, nuclear-encoded mitochondrial proteins begins with translation of messenger RNAs (mRNAs) on the surface of mitochondria. To characterize the spatial organization of mitochondrial gene products in zebrafish (Danio rerio), we sequenced RNA from different cellular fractions. Our results confirmed the presence of nuclear-encoded mRNAs in the mitochondrial fraction, which in unperturbed conditions, are mainly transcripts encoding large proteins with specific properties, like transmembrane domains. To further explore the principles of mitochondrial protein compartmentalization in zebrafish, we quantified the transcriptomic changes for each subcellular fraction triggered by the chchd4a-/- mutation, causing the disorders in the mitochondrial protein import. Our results indicate that the proteostatic stress further restricts the population of transcripts on the mitochondrial surface, allowing only the largest and the most evolutionary conserved proteins to be synthetized there. We also show that many nuclear-encoded mitochondrial transcripts translated by the cytosolic ribosomes stay resistant to the global translation shutdown. Thus, vertebrates, in contrast to yeast, are not likely to employ localized translation to facilitate synthesis of mitochondrial proteins under proteostatic stress conditions.

genomics↗