Biology subjects

Samaco, R. C.

Publications and source records attributed to Samaco, R. C..

3 recordsLinked to original sources

bioRxiv2024

Counter-balancing X-linked Mecp2 hypofunction by hyperfunction ameliorates disease features in a model of Rett syndrome: implications for genetic therapies

Treating monogenic neurodevelopmental disorders remains challenging and mostly symptomatic. X-linked disorders affecting women such as the postnatal neurodevelopmental disorder Rett syndrome (caused by mutations in the gene MECP2) have additional challenges due to dosage sensitivity and to cellular mosaicism caused by random X-chromosome inactivation. An approach to augment MECP2 expression from wild-type cells in RTT may be feasible and simpler than gene replacement but has never been tested due to known toxicity of MECP2 over-expression, as evidenced by the distinct neurological condition known as MECP2 Duplication Syndrome. Here, using genetic techniques, we find that "counter-balancing" Mecp2-null cells in female Mecp2-null/+ mice by a complementary population of cells harboring an X-linked transgene associated with 3X normal levels of MECP2 leads to normalization of multiple whole animal phenotypic outcomes without noticeable toxicity. In addition, in vivo LFP recordings demonstrate that counter-balancing Mecp2 loss-of-function improves select within-region and between-region abnormalities. By comparing the counter-balance approach with an approach based on cell autonomous restoration of MeCP2 using an autosomal transgene expressing 2X normal levels of MECP2 in all cells (mimicking gene replacement), we identify neurobehavioral and electrographic features best suited for preclinical biomarkers of a therapeutic response to cell autonomous versus non-cell autonomous correction. Notably, these proof-of-concept findings demonstrate how non-cell autonomous suppression of MeCP2 deficiency by boosting overall wild-type MeCP2 levels may be a viable disease-modifying therapy for RTT, with potential implications for genetic-based therapies of monogenic X-linked disorders. One Sentence SummaryIn a mouse model of Rett syndrome, counterbalancing mosaic LOF with complementary mosaic GOF improves phenotypic outcome.

neuroscience↗

bioRxiv2022

A truncating mutation of Magel2 in the rat modelled for the study of Schaaf-Yang and Prader-Willi syndromes alters select behavioral and physiological outcomes

Truncating mutations of the maternally imprinted, paternally expressed MAGEL2 gene are the predicted genetic cause of several rare neurodevelopmental disorders including Schaaf-Yang (SYS), Chitayat-Hall and Opitz Trigonocephaly C syndromes. MAGEL2 is also deleted or inactivated in Prader-Willi syndrome (PWS). Previous studies in mice have utilized Magel2 gene deletion models to examine the consequences of its absence. In this study, we report the generation, molecular validation, and phenotypic characterization of a novel rat model with a truncating Magel2 mutation generating a mutant peptide sequence more closely modeling variants associated with SYS-causing mutations. Within the hypothalamus, a brain region wherein mouse and human MAGEL2 is paternally-expressed, we demonstrate at the level of transcript and peptide detection that Magel2 in the rat exhibits a paternal, parent-of-origin effect. In the evaluation of behavioral features across several domains, juvenile Magel2 mutant rats display select alterations in anxiety-like behavior and sociability measures. Moreover, the analysis of peripheral organ systems detected alterations in body composition, cardiac structure and function, and breathing irregularities in Magel2 mutant rats. Several of these findings are concordant with reported mouse phenotypes, signifying the conservation of MAGEL2 function across rodent species for specific behavioral outcome measures. We conclude that our comprehensive analysis demonstrating impairments across multiple domains demonstrates the tractability of this model system for the study of truncating MAGEL2 mutations.

neuroscience↗

bioRxiv2019

Soft Windowing Application to Improve Analysis of High-throughput Phenotyping Data

MotivationHigh-throughput phenomic projects generate complex data from small treatment and large control groups that increase the power of the analyses but introduce variation over time. A method is needed to utlize a set of temporally local controls that maximises analytic power while minimising noise from unspecified environmental factors.\n\nResultsHere we introduce \"soft windowing\", a methodological approach that selects a window of time that includes the most appropriate controls for analysis. Using phenotype data from the International Mouse Phenotyping Consortium (IMPC), adaptive windows were applied such that control data collected proximally to mutants were assigned the maximal weight, while data collected earlier or later had less weight. We applied this method to IMPC data and compared the results with those obtained from a standard non-windowed approach. Validation was performed using a resampling approach in which we demonstrate a 10% reduction of false positives from 2.5 million analyses. We applied the method to our production analysis pipeline that establishes genotype-phenotype associations by comparing mutant versus control data. We report an increase of 30% in significant p-values, as well as linkage to 106 versus 99 disease models via phenotype overlap with the soft windowed and non-windowed approaches, respectively, from a set of 2,082 mutant mouse lines. Our method is generalisable and can benefit large-scale human phenomic projects such as the UK Biobank and the All of Us resources.\n\nAvailability and ImplementationThe method is freely available in the R package SmoothWin, available on CRAN http://CRAN.R-project.org/package=SmoothWin.

bioinformatics↗