Biology subjects

Garcia-Campos, M. A.

Publications and source records attributed to Garcia-Campos, M. A..

3 recordsLinked to original sources

bioRxiv2024

Passive shaping of intra- and intercellular m6A dynamics via mRNA metabolism

m6A is the most widespread mRNA modification and is primarily implicated in controlling mRNA stability. Fundamental questions pertaining to m6A are the extent to which it is dynamically modulated within cells and across stimuli, and the forces underlying such modulation. Prior work has focused on investigating active mechanisms governing m6A levels, such as recruitment of m6A writers or erasers leading to either global or site-specific modulation. Here, we propose that changes in m6A levels across subcellular compartments and biological trajectories may result from passive changes in gene-level mRNA metabolism. To predict the intricate interdependencies between m6A levels, mRNA localization, and mRNA decay, we establish a differential model m6ADyn encompassing mRNA transcription, methylation, export, and m6A-dependent and independent degradation. We validate the predictions of m6ADyn in the context of intracellular m6A dynamics, where m6ADyn predicts associations between relative mRNA localization and m6A levels, which we experimentally confirm. We further explore m6ADyn predictions pertaining to changes in m6A levels upon controlled perturbations of mRNA metabolism, which we also experimentally confirm. Finally, we demonstrate the relevance of m6ADyn in the context of cellular heat stress response, where genes subjected to altered mRNA product and export also display predictable changes in m6A levels, consistent with m6ADyn predictions. Our findings establish a framework for dissecting m6A dynamics and suggest the role of passive dynamics in shaping m6A levels in mammalian systems.

systems biology↗

bioRxiv2023

txtools: an R package facilitating analysis of RNA modifications, structures, and interactions

AO_SCPLOWBSTRACTC_SCPLOWWe present txtools, an R package that enables the processing, analysis, and visualization of RNA-seq data at the nucleotide-level resolution, seamlessly integrating alignments to the genome with transcriptomic representation. txtools main inputs are BAM files and a transcriptome annotation, and the main output is a table, capturing mismatches, deletions, and the number of reads beginning and ending at each nucleotide in the transcriptomic space. txtools further facilitates downstream visualization and analyses. We showcase, using examples from the epitranscriptomic field, how a few calls to txtools functions can yield insightful and ready-to-publish results. txtools is of broad utility also in the context of structural mapping and RNA:protein interaction mapping. By providing a simple and intuitive framework, we believe that txtools will be a useful and convenient tool and pave the path for future discovery. txtools is available for installation from its GitHub repository at https://github.com/AngelCampos/txtools.

bioinformatics↗

bioRxiv2019

Deciphering the ‘m6A code’ via quantitative profiling of m6A at single-nucleotide resolution

N6-methyladenosine (m6A) is the most abundant modification on mRNA, and is implicated in critical roles in development, physiology and disease. The ability to map m6A using immunoprecipitation-based approaches has played a critical role in dissecting m6A functions and mechanisms of action. Yet, these approaches are of limited specificity, unknown sensitivity, and unable to quantify m6A stoichiometry. These limitations have severely hampered our ability to unravel the factors determining where m6A will be deposited, to which levels (the m6A code), and to quantitatively profile m6A dynamics across biological systems. Here, we used the RNase MazF, which cleaves specifically at unmethylated RNA sites, to develop MASTER-seq for systematic quantitative profiling of m6A sites at 16-25% of all m6A sites at single nucleotide resolution. We established MASTER-seq for orthogonal validation and de novo detection of m6A sites, and for tracking of m6A dynamics in yeast gametogenesis and in early mammalian differentiation. We discover that antibody-based approaches severely underestimate the number of m6A sites, and that both the presence of m6A and its stoichiometry are hard-coded via a simple and predictable code within the extended sequence composition at the methylation sites. This code accounts for ~50% of the variability in methylation levels across sites, allows excellent de novo prediction of methylation sites, and predicts methylation acquisition and loss across evolution. We anticipate that MASTER-seq will pave the path towards a more quantitative investigation of m6A biogenesis and regulation in a wide variety of systems, including diverse cell types, stimuli, subcellular components, and disease states.

molecular biology↗