Biology subjects

Navarro-Paya, D.

Publications and source records attributed to Navarro-Paya, D..

7 recordsLinked to original sources

bioRxiv2025

AEGIS: an annotation extraction and genomic integration resource

The GTF/GFF3 formats are the standard for storing and exchanging genome annotations. However, their flexibility often results in inconsistent and poorly formatted files across different sources, creating a major bottleneck for downstream bioinformatics analyses. Here, we present Annotation Extraction and Genomic Integration Suite (AEGIS), a comprehensive and user-friendly command-line toolkit designed to parse, validate and standardise genome annotation files. AEGIS robustly corrects common structural and formatting errors, ensuring interoperability with downstream tools. Beyond standardisation, the suite provides advanced modules for analysis, such as flexible sequence extraction (e.g. genes, CDS, proteins) with isoform handling, customisable promoter region definitions and targeted DNA motif searches. A key feature of AEGIS is its integrated workflow for comparative genomics, which combines multiple lines of evidence (i.e., sequence homology, synteny and coordinate-based lift-overs) to enable a robust gene ID correspondence and orthology assessment. We demonstrate the utility of AEGIS by comparing two major Arabidopsis thaliana annotations (TAIR10 vs. Araport11), successfully identifying and quantifying complex structural changes such as gene splits and fusions. AEGIS provides a unified solution for annotation quality control, feature extraction and comparative genomic analysis, simplifying complex workflows and enhancing reliability in bioinformatic research. The software is open-source, implemented in Python and is available on GitHub, PyPI, and as a Docker container to ensure accessibility and reproducibility.

bioinformatics↗

bioRxiv2025

Developing the Grapevine Hydric Stress Atlas: A Meta-Analysis Resource for Exploring transcriptome Responses to Drought

Climate change poses a significant threat to agriculture, particularly in regions where increased drought periods, abnormal heat, and intensified pest pressure threaten crop productivity. Viticulture, as one of the most economically important crops, is highly vulnerable to these challenges. Understanding the molecular mechanisms underlying drought responses in grapevines is essential for developing innovative molecular breeding strategies aimed at enhancing drought tolerance, improving cultivar resilience, and promoting agricultural sustainability. In this context, transcriptomic meta-analyses have proven valuable for uncovering global regulatory trends, gene co-expression networks and conserved biological responses across diverse conditions. As part of this study, 1107 public transcriptomic datasets from Illumina (631 runs) and ABI SOLID (476 runs) platforms were searched, reclassified and reanalyzed in the latest T2T genome assembly, in order to construct condition, cultivar and tissue-specific gene expression atlases associated with drought stress in grapevine. To facilitate exploration of this data, a web-based application, the Hydric Stress Atlas App (https://plantaeviz.tomsbiolab.com/vitviz/hydric_atlas/), was developed, as part of the Vitis module within the PlantaeViz platform. Together with this tool, we generated a whole-genome co-expression network using the same datasets (https://plantaeviz.tomsbiolab.com/vitviz/networks/non_agg_gcns/T2T/hydric_stress_TI/). This water stress condition-dependent GCN allows to explore and visualize gene co-expression relationships related to stress and identify network hubs holding novel drought stress regulators. We manually curated experimental metadata, and enabled the classification of transcriptomic data by cultivar, tissue, and drought tolerance. Finally, candidate genes associated with drought tolerance were identified via network topology analysis. These genes can be further used as molecular markers, or characterized via gene editing or cisgenesis, providing insights into their molecular roles in drought tolerance. This resource contributes to a deeper understanding of grapevine drought responses, offering a pathway for sustainable viticulture and innovative biotechnological solutions to address climate-related challenges.

plant biology↗

bioRxiv2025

Organ-level Gene Regulatory Network models enable the identification of central transcription factors in Solanum lycopersicum

Tomato (Solanum lycopersicum) is a globally important crop, yet the gene regulatory networks (GRNs) controlling gene expression remain poorly understood. In this study, we constructed GRNs for roots, leaves, flowers, fruits, and seeds by inferring transcription factor (TF)-target interactions from over 10,000 RNA-seq libraries using the GENIE3 algorithm. We refined these networks with gene co-expression data and computational predictions of TF binding sequences in open chromatin sites. Our networks confirmed key TFs, including TOMATO AGAMOUS LIKE 1 and RIPENING INHIBITOR in fruit ripening, as well as ABF3 and ABF5 in abscisic acid response in leaves. Additionally, we identified novel candidate regulators, including AUXIN RESPONSE FACTOR 2A and ETHYLENE RESPONSE FACTOR.E2 in fruit ripening and G-BOX BINDING FACTOR 3 (SlGBF3) in ABA-related and drought pathways. To further validate the GRNs, we used DNA Affinity Purification Sequencing (DAP-seq) for SlGBF3, confirming the accuracy of our GRNs. This study provides a valuable resource for dissecting transcriptional regulation in tomato, with potential applications in crop improvement. The GRNs are publicly accessible through a user-friendly web platform at https://plantaeviz.tomsbiolab.com/tomviz. HighlightWe developed organ-level gene regulatory networks for tomato using 10,000+ RNA-seq libraries, validated predictions and identified new regulators of fruit ripening and ABA response. These networks are available at https://plantaeviz.tomsbiolab.com/tomviz.

systems biology↗

bioRxiv2024

The Plantae Visualization Platform: a comprehensive web-based tool for the integration, visualization, and analysis of omic data across plant and related species

The increasing availability of omics data from non-model plant species has created a pressing need for centralized, user-friendly platforms that maximize the utility of these datasets in a FAIR manner. Here, we introduce PlantaeViz, a web-based tool designed for the integration, visualization, and analysis of multi-omics data across a wide range of plant species. PlantaeViz offers advanced functionalities, including gene catalogues built from curated literature, transcriptomic meta-analyses presented as gene expression atlases, gene co-expression and regulatory networks with on-the-fly ontology analyses, cistrome visualization and metabolomics-transcriptomics integration, among other tools, providing a robust framework for hypothesis generation and biological interpretation. Gene Cards applications, tailored to each plant species, provide both community-curated and automatically generated functional annotation information. One of the platforms core features is its big data approach: over 58,000 publicly available SRA transcriptomic samples have been processed and visualized to date. Significant efforts have been made in orthology assessment using multiple layers of evidence, as well as in the automatic classification and standardization of omics metadata through regular expressions and data mining. As a result, around 90% of transcriptomic runs have been successfully classified according to sample tissue. These data have been used to construct gene networks via computationally intensive methods based on diverse algorithms. We present a study case to illustrate the platforms integration and exploratory capabilities. PlantaeViz bridges genomics and functional knowledge between model and non-model plant species and aims to expand its species catalogue of species in the future, democratizing access to large-scale plant omics data. Further developments will include the incorporation of additional data types, and the implementation of new tools to further support plant research across diverse biological contexts.

bioinformatics↗

bioRxiv2024

Biosynthesis of oxyresveratrol in mulberry (Morus alba L.) is mediated by a group of p-coumaroyl-CoA 2'-hydroxylases acting upstream of stilbene synthases

Mulberry (Morus alba L.) is considered a millenary medicinal plant and a food source for silkworms. Different M. alba extracts offer a variety of biological and pharmacological properties that are in part attributed to stilbenoids, a small group of phenylpropanoids that include resveratrol and oxyresveratrol. These are naturally present in non-renewable parts of mulberry trees, impeding their efficient extraction. As a way to bypass this spatiotemporal restriction, we generated cell suspensions from mulberry twigs and demonstrated that the combined use of methyl jasmonate and methyl- or hydroxypropyl-{beta}-cyclodextrins elicited a high production of resveratrol and oxyresveratrol, both intra and extracellularly. To identify oxyresveratrol-producing enzymes (unknown to date), we first improved the structural and functional annotation of the mulberry genome by integrating short and long-read sequencing data. We further combined this data with transcriptome, metabolite and proteome time-series evidence to identify a complete set of elicited phenylpropanoid- and stilbenoid-related genes. These included 22 stilbene synthase (STS) genes and a group of six p-coumaroyl-CoA 2-hydroxylases (C2Hs) that were highly co-expressed with resveratrol and oxyresveratrol accumulation. We transiently transformed Nicotiana benthamiana plants and grapevine (Vitis vinifera L.) cell suspensions to functionally validate the role of C2Hs as the first committed step of oxyresveratrol synthesis, providing an alternative substrate for STSs by hydroxylating p-coumaroyl-coA into 24-dihydroxycinnamoyl-CoA. We offer tools for genomic and transcriptomic exploration in the context of jasmonate elicitation aiding in the characterization of novel stilbenoid-modifying and regulatory genes in the Morus genus.

molecular biology↗

bioRxiv2023

Aggregated gene co-expression networks for predicting transcription factor regulatory landscapes in a non-model plant species

Gene co-expression networks (GCNs) have not been extensively studied in non-model plants. However, the rapid accumulation of transcriptome datasets in these species represents an opportunity to explore underutilized network aggregation approaches that highlight robust co-expression interactions and improve functional connectivity. We applied and evaluated two different aggregation methods on public grapevine RNA- Seq datasets belonging to three different tissue conditions (leaf, berry and all organs). Our results show that co-occurrence-based aggregation generally yielded the best-performing networks. We applied GCNs to study several TF gene families, showing its capacity of detecting both already-described and novel regulatory relationships between R2R3-MYBs, bHLH/MYC and multiple secondary metabolism pathway reactions. Specifically, TF gene-and pathway-centered network analyses successfully ascertained the previously established role of VviMYBPA1 in controlling the accumulation of proanthocyanidins while providing insights into its novel role as a regulator of p-coumaroyl-CoA biosynthesis as well as the shikimate and aromatic amino-acid pathways. This network was validated using DNA Affinity Purification Sequencing data, demonstrating that co-expression networks of transcriptional activators can serve as a proxy of gene regulatory networks. This study presents an open repository to reproduce networks and a GCN application within the Vitviz platform, a user-friendly tool for exploring co-expression relationships.

plant biology↗

bioRxiv2022

An improved reference of the grapevine genome supports reasserting the origin of the PN40024 highly-homozygous genotype

The genome sequence assembly of the diploid and highly homozygous V. vinifera genotype PN40024 serves as the reference for many grapevine studies. Despite several improvements of the PN40024 genome assembly, its current version PN12X.v2 is quite fragmented and only represents the haploid state of the genome with mixed haplotypes. In fact, despite the PN40024 genome is nearly homozygous, it still contains various heterozygous regions. Taking the opportunity of the improvements that long-read sequencing technologies offer to fully discriminate haplotype sequences and considering that several Vitis sp. genomes have recently been assembled with these approaches, an improved version of the reference, called PN40024.v4, was generated. Through incorporating long genomic sequencing reads to the assembly, the continuity of the 12X.v2 scaffolds was highly increased. The number of scaffolds decreased from 2,059 to 640 and the number of N bases was reduced by 88%. Additionally, the full alternative haplotype sequence was built for the first time, the chromosome anchoring was improved and the amount of unplaced scaffolds were reduced by half. To obtain a high-quality gene annotation that outperforms previous versions, a liftover approach was complemented with an optimized annotation workflow for Vitis. Integration of the gene reference catalogue and its manual curation have also assisted in improving the annotation, while defining the most reliable estimation to date of 35,230 genes. Finally, we demonstrate that PN40024 resulted from selfings of cv. Helfensteiner (cross of cv. Pinot noir and Schiava grossa) instead of a single Pinot noir. These advances will help maintaining the PN40024 genome as a gold-standard reference also contributing in the eventual elaboration of the grapevine pangenome.

genomics↗