Biology subjects

Ramirez-Rafael, J. A.

Publications and source records attributed to Ramirez-Rafael, J. A..

3 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↗

bioRxiv2024

Partial Fitch Graphs: Characterization, Satisfiability and Complexity

Horizontal gene transfer is an important contributor to evolution. Following Walter M. Fitch, two genes are xenologs if at least one HGT separates them. More formally, the directed Fitch graph has a set of genes as its vertices, and directed edges (x, y) for all pairs of genes x and y for which y has been horizontally transferred at least once since it diverged from the last common ancestor of x and y. Subgraphs of Fitch graphs can be inferred by comparative sequence analysis. In many cases, however, only partial knowledge about the "full" Fitch graph can be obtained. Here, we characterize Fitch-satisfiable graphs that can be extended to a biologically feasible "full" Fitch graph and derive a simple polynomial-time recognition algorithm. We then proceed to show that several versions of finding the Fitch graph with total maximum (confidence) edge-weights are NP-hard. In addition, we provide a greedy-heuristic for "optimally" recovering Fitch graphs from partial ones. Somewhat surprisingly, even if [~] 80% of information of the underlying input Fitch-graph G is lost (i.e., the partial Fitch graph contains only [~] 20% of the edges of G), it is possible to recover [~] 90% of the original edges of G on average.

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↗