Biology subjects

Watson, C. M.

Publications and source records attributed to Watson, C. M..

3 recordsLinked to original sources

bioRxiv2026

Temporal RNA splicing dysregulation in a human multicellular model of C9orf72 ALS

Amyotrophic lateral sclerosis (ALS) is a complex and heterogenous disease, comprising of familial and sporadic forms, numerous genetic mutations, and a wide range of affected cell types and proposed dysregulated processes. While the usage of in vitro cell cultures, mouse models, and postmortem patient tissue have advanced our understanding of ALS disease mechanisms, the temporal progression of the disease and how early molecular changes evolve remain poorly understood. Here, we establish human spinal cord organoids (hSpO) derived from C9orf72 patient induced pluripotent stem cells (C9-ALS hiPSCs) as a platform to model longitudinal changes across the disease trajectory. We show that C9-ALS hSpO recapitulate hallmark C9orf72-related pathologies, increased cell death, and progressive neuronal dysfunction. We further identify RNA splicing dysregulation as an early and persistent feature of C9-ALS, with splicing signatures in hSpO closely mirroring those observed in postmortem patient tissue. Finally, prediction of RNA binding proteins (RBPs) that induce early splicing changes in C9-ALS reveals signatures consistent with a broad RBP network dysfunction. Together, this work establishes hSpO as an in vitro system for investigating early disease mechanisms of ALS in a human multicellular context and highlights dysregulated events that precede cell death.

neuroscience↗

bioRxiv2022

Quantitative proteomics of cerebrospinal fluid from African Americans and Caucasians reveals shared and divergent changes in Alzheimer's disease

Despite being twice as likely to get Alzheimers disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers. Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. Network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. CSF modules which included 14-3-3 proteins (YWHAZ and YWHAG), demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Using a targeted proteomic approach (selected reaction monitoring) followed by a receiver operating characteristic curve (ROC) analysis we measured levels of VGF, SCG2, and NPTX2, which were significantly better at classifying African Americans than Caucasians with AD. Collectively, our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.

neuroscience↗

bioRxiv2019

SVCurator: A Crowdsourcing app to visualize evidence of structural variants for the human genome

A high quality benchmark for small variants encompassing 88 to 90% of the reference genome has been developed for seven Genome in a Bottle (GIAB) reference samples. However a reliable benchmark for large indels and structural variants (SVs) is yet to be defined. In this study, we manually curated 1235 SVs which can ultimately be used to evaluate SV callers or train machine learning models. We developed a crowdsourcing app - SVCurator - to help curators manually review large indels and SVs within the human genome, and report their genotype and size accuracy.\n\nSVCurator is a Python Flask-based web platform that displays images from short, long, and linked read sequencing data from the GIAB Ashkenazi Jewish Trio son [NIST RM 8391/HG002], We asked curators to assign labels describing SV type (deletion or insertion), size accuracy, and genotype for 1235 putative insertions and deletions sampled from different size bins between 20 and 892,149 bp. The crowdsourced results were highly concordant with 37 out of the 61 curators having at least 78% concordance with a set of expert curators, where there was 93% concordance amongst expert curators. This produced high confidence labels for 935 events. When compared to the heuristic-based draft benchmark SV callset from GIAB, the SVCurator crowdsourced labels were 94.5% concordant with the benchmark set. We found that curators can successfully evaluate putative SVs when given evidence from multiple sequencing technologies.

genomics↗