A5091412191- RNA Research and Splicing
- Neurogenetic and Muscular Disorders Research
- Amyotrophic Lateral Sclerosis Research
- Single-cell and spatial transcriptomics
- Genomics and Chromatin Dynamics
- RNA modifications and cancer
- Congenital heart defects research
- Genetic Associations and Epidemiology
- RNA and protein synthesis mechanisms
- Genomics and Rare Diseases
- Cancer-related molecular mechanisms research
- Extracellular vesicles in disease
- Cell Image Analysis Techniques
- Lipoproteins and Cardiovascular Health
- Cancer-related gene regulation
- Vascular Malformations Diagnosis and Treatment
- Ubiquitin and proteasome pathways
- Congenital Heart Disease Studies
- Genomic variations and chromosomal abnormalities
- Atherosclerosis and Cardiovascular Diseases
Stanford University
2020-2025
Lucile Packard Children's Hospital
2022-2025
Abstract A hallmark pathological feature of the neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is depletion RNA-binding protein TDP-43 from nucleus neurons in brain spinal cord 1 . major function as a repressor cryptic exon inclusion during RNA splicing 2–4 Single nucleotide polymorphisms UNC13A are among strongest hits associated with FTD ALS human genome-wide association studies 5,6 , but how those variants increase risk for disease...
Abstract Identifying transcriptional enhancers and their target genes is essential for understanding gene regulation the impact of human genetic variation on disease 1–6 . Here we create evaluate a resource >13 million enhancer-gene regulatory interactions across 352 cell types tissues, by integrating predictive models, measurements chromatin state 3D contacts, large-scale perturbations generated ENCODE Consortium 7 We first systematic benchmarking pipeline to compare assembling dataset...
Positively charged repeat peptides are emerging as key players in neurodegenerative diseases. These can perturb diverse cellular pathways but a unifying framework for how such promiscuous toxicity arises has remained elusive. We used mass-spectrometry-based proteomics to define the protein targets of these neurotoxic and found that they all share similar sequence features drive their aberrant condensation with positively peptides. trained machine learning algorithm detect unexpectedly...
A hallmark pathological feature of neurodegenerative diseases amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) is the depletion RNA-binding protein TDP-43 from nucleus neurons in brain spinal cord. major function as a repressor cryptic exon inclusion during RNA splicing. Single nucleotide polymorphisms (SNPs) UNC13A are among strongest genome-wide association study (GWAS) hits associated with FTD/ALS humans, but how those variants increase risk for disease unknown. Here...
Abstract Congenital heart defects (CHD) arise in part due to inherited genetic variants that alter genes and noncoding regulatory elements the human genome. These are thought act during fetal development influence formation of different structures. However, identifying genes, pathways, cell types mediate these effects has been challenging immense diversity involved as well superimposed complexities interpreting sequences. As such, understanding molecular functions both coding remains...
Abstract Genome-wide association studies (GWAS) have discovered thousands of risk loci for common, complex diseases, each which could point to genes and gene programs that influence disease. For some it has been observed GWAS signals converge on a smaller number biological programs, this convergence can help identify causal 1–6 . However, identifying such remains challenging: locus many candidate genes, might act in one or more possible unclear disease risk. Here, we developed new approach...
Abstract Mapping enhancers and their target genes in specific cell types is crucial for understanding gene regulation human disease genetics. However, accurately predicting enhancer-gene regulatory interactions from single-cell datasets has been challenging. Here, we introduce a new family of classification models, scE2G, to predict regulation. These models use features ATAC-seq or multiomic RNA data are trained on CRISPR perturbation dataset including >10,000 evaluated element-gene...