Biology subjects

Avina-Padilla, K.

Publications and source records attributed to Avina-Padilla, K..

6 recordsLinked to original sources

bioRxiv2025

REvolutionH-tl: A Fast and Robust Tool for Decoding Evolutionary Gene Histories

REvolutionH-tl is a fast, scalable, and integrated software platform for inferring orthology relationships, gene trees, species trees, and reconciled evolutionary scenarios directly from sequence data. Built upon the formal framework of best match graphs (BMGs), REvolutionH-tl predicts orthogroups and orthologous gene pairs with high accuracy, requiring neither precomputed trees nor multiple external tools. The software reconstructs event-labeled gene and species trees, seamlessly integrating reconciliation to produce fast, accurate, and biologically insightful evolutionary scenarios. Through extensive benchmarking on synthetic datasets with known ground truth, REvolutionH-tl outperforms or matches the accuracy of established tools such as OrthoFinder, Proteinortho, RAxML, GeneRax, and RANGER-DTL, while achieving significantly lower runtimes. A key innovation of REvolutionH-tl is its built-in support for detailed, publication-ready visualizations, which allow users to explore genome evolution dynamics, orthogroup composition, and reconciliation results with clarity and ease. These visual features position REvolutionH-tl as the first platform of its kind to combine analytical precision with intuitive interpretability. The software is open-source, cross-platform, and freely available at https://pypi.org/project/revolutionhtl/, providing a robust solution for large-scale evolutionary analyses in comparative genomics. Author summaryComparative genomics relies on understanding how genes evolve across species. This involves identifying groups of related genes, reconstructing their evolutionary trees, and aligning them with the evolutionary history of species. These steps are typically performed using multiple tools, often requiring manual integration and technical expertise. We present REvolutionH-tl, an open-source software that automates the entire evolutionary reconstruction process--starting from protein sequences and producing gene trees, species trees, orthology assignments, and reconciled evolutionary scenarios. Unlike existing tools, REvolutionH-tl also includes built-in, high-quality visualizations that help users interpret complex evolutionary events such as gene duplications and losses. We evaluated REvolutionH-tl on simulated genomes with known evolutionary histories and found that it matches or exceeds the performance of widely used tools, while being significantly faster. Its visual output makes evolutionary analysis more accessible and interpretable, offering a valuable resource for researchers studying genome evolution.

bioinformatics↗

bioRxiv2025

Evolutionary Reconstruction of Hormone-bHLH Regulatory Networks in Solanaceae: Phylogenomic Insights from PSTVd-Tomato Interactions

The evolutionary reconstruction of transcriptional regulatory networks play a crucial role in plant adaptation to biotic stress. In Solanaceae, basic helix-loop-helix (bHLH) transcription factors (TFs) regulate hormone signaling pathways that balance growth and defense responses. In this study, we investigated the phylogenomic evolution of bHLH-mediated hormone networks in response to Potato Spindle Tuber Viroid (PSTVd) infection in tomato (Solanum lycopersicum) and its wild relatives. Among them, the JA-associated bHLH Solyc08g076930, IA3/MYC2 exhibits strong evolutionary conservation across Solanaceae, whereas the auxin regulator Solyc03g113560 miP-bHLH-ARF8 is a tomato-specific gene raising from an ancestral duplication, indicating neofunctionalization. Under PSTVd infection, we observe extensive regulatory rewiring, with bHLH hubs assuming dominant control over target genes typically regulated by multiple TFs in healthy conditions. The JA regulon undergoes the most pronounced shift, with Solyc08g076930 directly regulating 91 genes, compared to shared regulation with over a thousand TFs in healthy plants. This rewiring reflects the adaptive plasticity of bHLH TFs in coordinating stress responses through hormonal crosstalk. These findings reveal key evolutionary pressures shaping Solanaceae stress responses, offering insights for improving viroid tolerance and crop resilience.

evolutionary biology↗

bioRxiv2023

Dynamic co-expression modular network analysis of bHLH transcription factors regulation in the potato spindle tuber viroid-tomato pathosystem

Viroids, minimalist plant pathogens, present significant threats to crops by causing severe diseases. The use of high-throughput sequencing technologies for analyzing the transcriptomes of viroid-infected host plants has yielded informative information on gene regulation by these pathogens, however a complete understanding of the transcriptome data suffers from the inclusion of numerous genes of unknown function. Co-expression analysis addresses this by clustering genes into modules based on global gene expression levels. Our previous study emphasized basic helix-loop-helix protein (bHLH) transcriptional reprogramming in tomato in response to different potato spindle tuber viroid (PSTVd) strains. In the current research, we delve into tissue-specific gene modules, particularly in root and leaf tissues, governed by bHLH transcription factors during PSTVd infections. Utilizing public datasets that span Control (C; (mock-inoculated), PSTVd-mild (M), and PSTVd-severe (S23) strains in time-course infections, we uncovered differentially expressed gene modules. These modules were functionally characterized, identifying essential hub genes. We identified the roles of bHLH transcription factors (TFs) in managing processes like photosynthesis and rapid membrane repair in infected roots. In leaves, external layer alterations influenced photosynthesis, linking bHLH TFs to distinct metabolic functions. Expanding on these findings, we explored bipartite networks, discerning both common and unique bHLH TF regulatory roles, notably highlighting the bifan motifs significance in these interactions. Through this holistic approach, we deepen our understanding of viroid-host interactions and the intricate regulatory mechanisms underpinning them.

systems biology↗

bioRxiv2022

Discovering hub genes involved in the pathophysiological impact of COVID-19 on diabetes kidney disease by differential gene expression and interactome analysis

Diabetic kidney disease (DKD) is a frequently chronic kidney pathology derived from diabetes comorbidity. This condition has irreversible damage, and its risk factor increases with SARS-CoV-2 infection. The prognostic outcome for diabetic patients with COVID-19 is dismal, even with intensive medical treatment. However, there is still scarce information on critical genes involved in the pathophysiological impact of COVID-19 on DKD. Herein, we characterize differential expression gene (DEG) profiles and determine hub genes undergoing transcriptional reprogramming in both disease conditions. Out of 995 DEGs, we identified 42 DEGs shared with COVID-19 pathways. Enrichment analysis elucidated that they are significantly induced with implications for immune and inflammatory responses. By performing a protein-protein interaction (PPI) network and applying topological methods, we determine the following five hub genes STAT1, IRF7, ISG15, MX1, and OAS1. Then, by network deconvolution, we determine their co-expressed gene modules. Moreover, we validate the conservancy of their upregulation using the Coronascape database (DB). Finally, tissue-specific regulation of the five predictive hub genes indicates that OAS1 and MX1 expression levels are lower in healthy kidney tissue. Altogether, our results suggest that these genes could play an essential role in developing severe outcomes of COVID-19 in DKD patients.

bioinformatics↗

bioRxiv2022

Deciphering the tissue-specific regulatory role of intronless genes across cancers

Intronless genes (IGs) or single-exon genes lacking an intron are found across most Eukaryotes. Notably, IGs display a higher transcriptional fidelity as they are not regulated through alternative splicing, suggesting better predictability biomarkers and easier regulation as targets for therapy. Cancer is a complex disease that relies on progressive uncontrolled cell division linked with multiple dysfunctional biological processes. Tumor heterogeneity remains the most challenging feature in cancer diagnosis and treatment. Given the clinical relevance of IGs, we aim to identify their unique expression profiles and interactome, that may act as functional signatures across eight different cancers. We identified 940 protein-coding IGs in the human genome, of which about 35% were differentially expressed across the analyzed cancer datasets. Specifically, [~]78% of differentially expressed IGs were undergoing transcriptional reprogramming with elevated expression in tumor cells. Remarkably, in all the studied tumors, a highly conserved induction of a group of deacetylase-histones located in a region of chromosome 6 enriched in nucleosome and chromatin condensation processes. This study highlights that differentially expressed human intronless genes across cancer types are prevalent in epigenetic regulatory roles participating in specific PPI networks for ESCA, GBM, and LUAD tumors. We determine that IGs play a key role in the tumor phenotype at transcriptional and post-transcriptional levels, with important mechanisms such as interactomics rewiring.

genomics↗

bioRxiv2021

Evolutionary Perspective And Expression Analysis Of Intronless Genes Highlight The Conservation On Their Regulatory Role

Eukaryotic gene structure is a combination of exons generally interrupted by intragenic non-coding DNA regions termed introns removed by RNA splicing to generate the mature mRNA. Thus, eukaryotic genes can be either single exon genes (SEGs) or multiple exon genes (MEGs). Among SEGs, intronless genes (IGs) are a subgroup that additionally lacks introns at their UTRs, and code for proteins essentially involved in development, growth, and cell proliferation. Gene expression of IGs has been proposed to be highly specialized for neuro-specific functions and linked to cancer, neuropathies, and developmental disorders. The abundant presence of introns in eukaryotic genomes is pivotal for the precise control of gene expression. Notwithstanding, IGs exempting splicing events entail a higher transcriptional fidelity, making them even more valuable for regulatory roles. This work aimed to infer the functional role and evolutionary history of IGs using the mouse genome. Intronless protein-coding genes consist of a subgroup of ~6 % of a total of 21,527 genes with one exon. To understand the prevalence, biological relevance, and evolution, we identified and studied their 1,116 functional proteins. We validated differential expression in transcriptomics data of early embryo stages using mouse telencephalon tissue. Our results showed that expression levels of IGs are lower compared to MEGs. However, strongly upregulated IGs include transcription factors (TFs) such as the class 3 of POU (HMG Box), Neurog1, Olig1, and BHLHe22, BHLHe23, among other essential genes including the beta cluster of protocadherins. Most striking was the finding that IG-encoded BHLH TFs qualify the criteria to be referred to as microprotein candidates. Finally, predicted protein orthologs in other six genomes confirmed a high conservancy of IGs associated with regulating neurobiological processes and with chromatin organization and epigenetic regulation in Vertebrata. Moreover, this study highlights that IGs are essential modulators of regulatory processes, as Wnt signaling pathway and biological processes as pivotal as sensory organs developing at a transcriptional and post-translational level. Overall, our results suggest that IG proteins have specialized, prevalent, and unique biological roles and that functional divergence between IGs and MEGs is likely to be the result of specific evolutionary constraints.

evolutionary biology↗