Biology subjects

Ramirez, J. M.

Publications and source records attributed to Ramirez, J. M..

8 recordsLinked to original sources

bioRxiv2025

Mecp2 deficiency induces dysphagia in a preclinical model of Rett Syndrome

Rett Syndrome is a rare, x-linked genetic neurological disorder caused by MECP2 gene mutations. This progressive neurodevelopmental disorder hinders patients ability to breathe and eat normally. It is unclear how Mecp2-deficiency results in a high percentage of dysphagia and aspiration pneumonia in patients with Rett syndrome. We aim to determine the effects of Mecp2-deficiency on swallow related neuromuscular mechanisms contributing to dysphagia in Rett syndrome. Swallow and breathing were detected using electrophysiology in the submental and laryngeal muscle complexes and the hypoglossal and vagus nerves. Several medullary motoneuron populations involved in swallowing were examined by immunohistochemistry in pre and post symptomatic Mecp2-deficient male and female mice. Swallow-related submental complex duration and amplitude were significantly decreased in both Mecp2-/y and Mecp2+/-compared to wild-type, due to decreased motor unit activation. In both Mecp2-deficient mice, cholinergic staining in hypoglossal, facial, and trigeminal nuclei were decreased. We noted a significant increase in the transition time from inspiration to swallow, swallow to the subsequent inspiration, and impaired respiratory rhythm regeneration in Mecp2-/y, but not Mecp2+/- mice. Mecp2-deficiency resulted in impaired brainstem cholinergic signaling, which contribute to weakened submental muscle complex activity, and impaired swallow related laryngeal vestibular closure. These results suggest Mecp2-deficient mice are a viable pre-clinical model to further study dysphagia in Rett syndrome.

neuroscience↗

bioRxiv2025

Multimodal data analysis reveals asynchronous aging dynamics across female reproductive organs

Female reproductive aging is a complex process with profound systemic health implications, yet the molecular and structural dynamics of aging across reproductive organs and tissues remain largely unexplored. Here, we integrate deep learning-based analysis of 1,112 histological images with RNA-seq data from 659 samples across seven reproductive organs in 304 female donors aged 20-70 years. We show that female reproductive organs and tissues have asynchronous aging dynamics: while the ovary and vagina age gradually, the uterus undergoes an abrupt transcriptional and cellular transition around the age of menopause. Tissue segmentation highlights that the myometrium in the uterine wall is the most age-affected tissue, marked by extracellular matrix remodeling and immune activation. Across reproductive organs, the epithelial tissue is also strongly affected by age, with the vaginal epithelium showing a unique sharp menopausal transition. Integration via multi-omics factor analysis links these tissue-specific histological transformations to specific molecular shifts, many with nonlinear expression trajectories and enriched in heritable reproductive traits such as pelvic organ prolapse and age at menarche. These findings position menopause as a key inflection point in female aging and provide insights with tissue-specific focus to support healthier menopausal transitions and reduce age-related disease risk.

genomics↗

bioRxiv2025

rDNAcaller: a fast and robust pipeline to call ribosomal DNA variants

Ribosomal DNA (rDNA) genes are essential components of the ribosome, organized as tandem repeats on the mammalian genomes. Extensive genetic and copy number variation in rDNA has been reported both within and between individuals, contributing to phenotypic diversity. However, previous rDNA variant calling strategies have relied on methods designed for diploid regions and have not been systematically benchmarked. With the recent availability of a telomere-to-telomere (T2T) genome assembly, rDNA regions have been fully assembled for the first time, enabling benchmarking and optimization of rDNA variant calling strategies. We developed a customized simulator that replicates real intra- and inter-individual rDNA variation based on the T2T assembly to benchmark the performance of commonly used variant callers, including GATK, Mutect2, and Lofreq. Additionally, we optimized the preprocessing and mapping steps to remove pseudogenes and significantly improve accuracy. Based on these optimizations, we introduce rDNAcaller, a novel pipeline for accurate rDNA variant detection using short-read whole-genome sequencing. rDNAcaller integrates optimized preprocessing with the top-performing variant caller and achieves 94% precision on experimental data from the T2T cell line. Applying our pipeline to data from the 1000 Genomes Project, we identify 5,607 novel rDNA variant positions across human populations, with African individuals showing the highest number of variants. Overall, rDNAcaller is a robust and versatile tool for analyzing rDNA variation, addressing the limitations of existing methods in handling high ploidies. By enabling accurate detection of rDNA variants, it facilitates deeper exploration of rDNAs role in phenotypic diversity, supporting future genomic studies and broadening our understanding of rDNA biology in health and disease. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/653643v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@148419borg.highwire.dtl.DTLVardef@cb3b42org.highwire.dtl.DTLVardef@9fa802org.highwire.dtl.DTLVardef@1cf4ff0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

The impact of sex, age, and genetic ancestry on DNA methylation across tissues

Understanding the consequences of individual DNA methylation variation is crucial for advancing our knowledge of human biology and disease. Yet, the collective impact of individual traits on DNA methylation and their downstream effects on gene expression across human tissues remain poorly understood. Here, we quantify the contributions of sex, age, genetic ancestry, and BMI on autosomal DNA methylation variation across 9 human tissues and 424 individuals from the Genotype-Tissue Expression project. We show that genetic ancestry and age have a greater impact on DNA methylation than sex, with aging effects being more widespread but less pronounced. On average, less than 10% of the gene expression variation in sex, age, and ancestry are mediated by DNA methylation differences, with ancestry showing the largest proportion of mediation. We further show that ancestry-associated DNA methylation differences accumulate at CpG sites with extreme methylation states and are largely under genetic control. The female autosomal genome exhibits consistent hypermethylation across tissues at Polycomb-repressed regions. Ultimately, we show that age-related Polycomb target hypermethylation is observed across multiple tissues, but not in the gonads. Our multi-individual, multi-tissue approach defines the key drivers of human DNA methylation variation in healthy conditions, establishing a baseline for the interpretation of DNA methylation changes in disease contexts.

bioinformatics↗

bioRxiv2024

Ndufs4 inactivation in glutamatergic neurons reveals swallow-breathing discoordination in a mouse model of Leigh Syndrome

Swallowing, both nutritive and non-nutritive, is highly dysfunctional in children with Leigh Syndrome (LS) and contributes to the need for both gastrostomy and tracheostomy tube placement. Without these interventions aspiration of food, liquid, and mucus occur resulting in repeated bouts of respiratory infection. No study has investigated whether mouse models of LS, a neurometabolic disorder, exhibit dysfunctions in neuromuscular activity of swallow and breathing integration. We used a genetic mouse model of LS in which the NDUFS4 gene is knocked out (KO) specifically in Vglut2 or Gad2 neurons. We found increased variability of the swallow motor pattern, disruption in breathing regeneration post swallow, and water-induced apneas only in Vglut2 KO mice. These physiological changes likely contribute to weight loss and premature death seen in this mouse model. Following chronic hypoxia (CH) exposure, swallow motor pattern, breathing regeneration, weight, and life expectancy were not changed in the Vglut2-Ndufs4-KO CH mice compared to control, indicating a rescue of phenotypes. These findings show that like patients with LS, Ndufs4 mouse models of LS exhibit swallow impairments as well as swallow-breathing dyscoordination alongside the other phenotypic traits described in previous studies. Understanding this aspect of LS will open roads for the development of future more efficacious therapeutic intervention for this illness.

neuroscience↗

bioRxiv2024

Cigarette smoking drives accelerated aging across human tissues

Tobacco smoke is the main cause of preventable mortality worldwide. Smoking increases the risk of developing many diseases and has been proposed as an aging accelerator. Yet, the molecular mechanisms driving smoking-related health decline and aging acceleration in most tissues remain unexplored. Here, we characterize gene expression, alternative splicing, DNA methylation and histological alterations induced by cigarette smoking across human tissues. We show that smoking impacts tissue architecture and triggers systemic inflammation. We find that in many tissues, the effects of smoking significantly overlap those of aging in the same direction. Specifically, both age and smoking upregulate inflammatory genes and drive hypomethylation at enhancers. In addition, we observe widespread smoking-driven hypermethylation at target regions of the Polycomb repressive complex, which is a well-known aging effect. Smoking-induced epigenetic changes overlap causal aging CpGs, suggesting that these methylation changes may directly mediate aging acceleration observed in smokers. Finally, we find that smoking effects that are shared with aging are more persistent over time. Overall, our multi-tissue and multi-omic analysis of the effects of cigarette smoking provides an extensive characterization of the impact of tobacco smoke across tissues and unravels the molecular mechanisms driving smoking-induced tissue homeostasis decline and aging acceleration.

bioinformatics↗

bioRxiv2020

Decoding ribosomal RNA modification dynamics at single molecule resolution

A broad diversity of modifications decorate RNA molecules. Originally conceived as static components, evidence is accumulating that some RNA modifications may be dynamic, contributing to cellular responses to external signals and environmental circumstances. A major difficulty in studying these modifications, however, is the need of tailored protocols to map each modification type individually. Here, we present a new approach that uses direct RNA nanopore sequencing to identify and quantify RNA modifications present in native RNA molecules. First, we show that each RNA modification type results in a distinct and characteristic base-calling error signature, which we validate using a battery of genetic strains lacking either pseudouridine (Y) or 2-O-methylation (Nm) modifications. We then demonstrate the value of these signatures for de novo prediction of Y modifications transcriptome-wide, confirming known Y-modified sites as well as uncovering novel Y sites in mRNAs, ncRNAs and rRNAs, including a previously unreported Pus4-dependent Y modification in yeast mitochondrial rRNA, which we validate using orthogonal methods. To explore the dynamics of pseudouridylation across environmental stresses, we treat the cells with oxidative, cold and heat stresses, finding that yeast ribosomal rRNA modifications do not change upon environmental exposures, contrary to the general belief. By contrast, our method reveals many novel heat-sensitive Y-modified sites in snRNAs, snoRNAs and mRNAs, in addition to recovering previously reported sites. Finally, we develop a novel software, nanoRMS, which we show can estimate per-site modification stoichiometries from individual RNA molecules by identifying the reads with altered current intensity and trace profiles, and quantify the RNA modification stoichiometry changes between two conditions. Our work demonstrates that Y RNA modifications can be predicted de novo and in a quantitative manner using native RNA nanopore sequencing.

molecular biology↗

bioRxiv2019

Integrative analyses of the RNA modification machinery reveal tissue- and cancer-specific signatures

BackgroundRNA modifications play central roles in cellular fate and differentiation. These features have placed the epitranscriptome in the forefront of developmental biology and cancer research. However, the machinery responsible for placing, removing and recognizing more than 170 RNA modifications remains largely uncharacterized and poorly annotated, and we currently lack integrative studies that identify which RNA modification-related proteins (RMPs) may be dysregulated in each cancer type. ResultsHere we have performed a comprehensive annotation and evolutionary analysis of human RMPs as well as an integrative analysis of their expression patterns across 32 tissues, 10 species and 13,358 paired tumor-normal human samples. Our analysis reveals an unanticipated heterogeneity of RMP expression patterns across mammalian tissues, with a vast proportion of duplicated enzymes displaying testis-specific expression, suggesting a key role for RNA modifications in sperm formation and possibly intergenerational inheritance. Moreover, through the analysis of paired tumor-normal human samples we uncover many RMPs that are dysregulated in various types of cancer, and whose expression levels are predictive of cancer progression. Surprisingly, we find that several commonly studied RNA modification enzymes such as METTL3 or FTO, are not significantly up-regulated in most cancer types, once the sample is properly scaled and normalized to the full dataset, whereas several less-characterized RMPs, such as LAGE3 and HENMT1, are dysregulated in many cancers. ConclusionsOur analyses reveal an unanticipated heterogeneity in the expression patterns of RMPs across mammalian tissues, and uncover a large proportion of dysregulated RMPs in multiple cancer types. We provide novel targets for future cancer research studies targeting the human epitranscriptome, as well as foundations to understand cell type-specific behaviours that are orchestrated by RNA modifications.

molecular biology↗