Biology subjects

Li, W.-P.

Publications and source records attributed to Li, W.-P..

5 recordsLinked to original sources

bioRxiv2025

Identification of cell types associated with 14 brain phenotypes from more than 10 million single cells

Genome-wide association studies (GWAS) have yielded unprecedented insight into the genetic variants associated with many human traits. However, translating this insight into knowledge about causal biological mechanisms remains challenging. One promising recent strategy is to link GWAS-associated genes to information on expression levels of those genes in specific cell types. This strategy allows for the generation of specific, testable hypotheses about which cell types are important for a trait which can then be investigated in functional lab experiments for actual relevance. The success of this strategy strongly depends on the quality and systematic analysis of available single-cell RNAseq datasets. Here we present a comprehensive database of 388 datasets derived from 36 studies spanning different regions of the brain across developmental timepoints. Using this database, we tested for the presence of cell type enrichment in genes associated with 14 traits. We confirmed previous findings such as the association between microglia and Alzheimers disease in the entorhinal cortex. In addition, we found novel evidence for the involvement of specific cell types in disease, such as astrocytes being implicated in alcohol-related phenotypes or neuronal cell types at the prenatal stage in ADHD. Our database has been incorporated to FUMA, a publicly available and widely used tool for post-GWAS functional annotation analyses. Our work provides an approach to facilitate the prioritization of cell types in specific brain regions and/or developmental stages, further informing the design of follow-up experiments.

genetics↗

bioRxiv2024

Data Release: High-Resolution Imaging and Segmentation of P7 Mouse Tissue Microarchitecture Using FIB-SEM and Machine Learning

This report presents a comprehensive data release exploring the tissue microarchitecture of P7 aged mice using Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) combined with machine learning-based segmentations of nuclei. The study includes high-resolution 3D volumes and nucleus segmentations for seven vital tissues--pancreas, liver, kidney, heart, thymus, hippocampus, and skin--from a single mouse. The detailed datasets are openly accessible onOpenOrganelle.org, providing a valuable resource for the scientific community to support further research and collaboration.

cell biology↗

bioRxiv2024

Massively Parallel Polyribosome Profiling Reveals Translation Defects of Human Disease-Relevant UTR Mutations

The untranslated regions (UTRs) of mRNAs harbor regulatory elements influencing translation efficiency. Although 3.7% of disease-relevant human mutations occur in UTRs, their exact role in pathogenesis remains unclear. Through metagene analysis, we mapped pathogenic UTR mutations to regions near coding sequences, with a focus on the upstream open reading frame (uORF) initiation site. Subsequently, we utilized massively parallel poly(ribo)some profiling to compare the ribosome associations of 6,555 pairs of wildtype and mutant UTR fragments. We identified 46 UTR variants that altered polysome profiles, with enrichment in pathogenic mutations. Both univariate analysis and the elastic net regression model highlighted the significance of motifs of short repeated sequences, including SRSF2 binding sites, as mutation hotspots that lead to aberrant translation. Furthermore, these polysome-shifting mutations exhibited considerable impact on RNA secondary structures, particularly for upstream AUG-containing 5 UTRs. Integrating these features, our model achieved high accuracy (AUROC > 0.8) in predicting polysome-shifting mutations in the test dataset. Additionally, several lines of evidence indicate that changes in uORF usage underlie the translation deficiency arising from these mutations. Illustrating this, we demonstrate that a pathogenic mutation in the IRF6 5 UTR suppresses translation of the primary open reading frame by creating a uORF. Remarkably, site- directed ADAR editing of the mutant mRNA rescued this translation deficiency. Overall, our study provides insights into the molecular mechanisms of UTR mutations and their links to clinical impacts through translation defects. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=187 SRC="FIGDIR/small/589132v2_ufig1.gif" ALT="Figure 1000"> View larger version (50K): org.highwire.dtl.DTLVardef@57217corg.highwire.dtl.DTLVardef@575410org.highwire.dtl.DTLVardef@15013bforg.highwire.dtl.DTLVardef@408840_HPS_FORMAT_FIGEXP M_FIG C_FIG

genetics↗

bioRxiv2023

3D architecture and a bi-cellular mechanism of touch detection in mechanosensory corpuscle

Mechanosensory corpuscles detect transient touch and vibratory signals in the skin of vertebrates, enabling navigation, foraging, and precise manipulation of objects1. The corpuscle core comprises a terminal neurite of a mechanoreceptor afferent, the only known touch-sensing element within corpuscles, surrounded by terminal Schwann cells called lamellar cells (LCs)2-4. However, the precise corpuscular ultrastructure, and the role of LCs in touch detection are unknown. Here we used enhanced focused ion beam scanning electron microscopy and electron tomography to reveal the three-dimensional architecture of avian Meissner (Grandry) corpuscle5. We show that corpuscles contain a stack of LCs innervated by two afferents, which form large-area contacts with LCs. LCs form tether-like connections with the afferent membrane and contain dense core vesicles which release their content onto the afferent. Furthermore, by performing simultaneous electrophysiological recordings from both cell types, we show that mechanosensitive LCs use calcium influx to trigger action potential firing in the afferent and thus serve as physiological touch sensors in the skin. Our findings suggest a bi-cellular mechanism of touch detection, which comprises the afferent and LCs, likely enables corpuscles to encode the nuances of tactile stimuli.

neuroscience↗

bioRxiv2020

The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson's disease

Astrocytes are essential cells of the central nervous system, characterized by dynamic relationships with neurons that range from functional metabolic interactions and regulation of neuronal firing activities, to the release of neurotrophic and neuroprotective factors. In Parkinsons disease (PD), dopaminergic neurons are progressively lost during the course of the disease, but the effects of PD on astrocytes and astrocyte-to-neuron communication remains largely unknown. This study focuses on the effects of the PD-related mutation LRRK2 G2019S in astrocytes generated from patient-derived induced pluripotent stem cells. We report the alteration of extracellular vesicle (EV) biogenesis in astrocytes, and we identify the abnormal accumulation of key PD-related proteins within multi vesicular bodies (MVBs). We found that dopaminergic neurons internalize astrocyte-secreted EVs and that LRRK2 G2019S EVs are abnormally enriched in neurites and fail to provide full neurotrophic support to dopaminergic neurons. Thus, dysfunctional astrocyte-to-neuron communication via altered EV biological properties may participate in the progression of PD.

neuroscience↗