Biology subjects

Hsiao, Y.

Publications and source records attributed to Hsiao, Y..

4 recordsLinked to original sources

bioRxiv2025

PepCentric Enables Fast Repository-Scale Proteogenomics Searches

Identifying novel peptides arising from alternative splicing, mutations, or non-canonical translations is a crucial yet challenging aspect of proteogenomics. We introduce PepCentric, a scalable computational platform and a web-based portal utilizing advanced 2-D fragment indexing for rapid peptide-centric searches across extensive mass spectrometry datasets. With robust false discovery rate control and optimized search performance, PepCentric offers an efficient tool for validating novel peptides and exploring proteomic variations. In a matter of seconds, users can search their novel peptides or proteins against 2.3 billion spectra collected from 66700 mass spectrometry runs, making it practical to rapidly validate proteogenomic hypotheses.

bioinformatics↗

bioRxiv2025

Persistent large-scale changes in alternative splicing in prefrontal cortical neuron types following psychedelic exposure

Psychedelics engage the serotonergic system as potent neuromodulators, increasing neuroplasticity in humans and rodents. Persistent changes in cognitive flexibility, emotional regulation, and social cognition are thought to underlie the therapeutic effects of psychedelics. However, the underlying molecular and cellular basis of psychedelic-induced plasticity remains unclear. Here, we identify persistent, cell type-specific alternative splicing changes in the mouse medial prefrontal cortex (mPFC) induced by a single dose of psychedelics. Combining deep RiboTag sequencing and bioinformatics, we find that a single dose of psychedelics modestly alters gene expression while dramatically shifting patterns of alternative splicing lasting at least a month. We connect our functional enrichment and alternative splicing analysis with changes in the extracellular matrix, synaptic physiology, and intrinsic physiology in parvalbumin interneurons days to a week after psychedelic treatment. Our dataset is an essential resource for understanding the persistent, cell type-specific effects of psychedelics on cortical cell types and functions.

neuroscience↗

bioRxiv2024

Analysis and visualization of quantitative proteomics data using FragPipe-Analyst

The FragPipe computational proteomics platform is gaining widespread popularity among the proteomics research community because of its fast processing speed and user-friendly graphical interface. Although FragPipe produces well-formatted output tables that are ready for analysis, there is still a need for an easy-to-use and user-friendly downstream statistical analysis and visualization tool. FragPipe-Analyst addresses this need by providing an R shiny web server to assist FragPipe users in conducting downstream analyses of the resulting quantitative proteomics data. It supports major quantification workflows including label-free quantification, tandem mass tags, and data-independent acquisition. FragPipe-Analyst offers a range of useful functionalities, such as various missing value imputation options, data quality control, unsupervised clustering, differential expression (DE) analysis using Limma, and gene ontology and pathway enrichment analysis using Enrichr. To support advanced analysis and customized visualizations, we also developed FragPipeAnalystR, an R package encompassing all FragPipe-Analyst functionalities that is extended to support site-specific analysis of post-translational modifications (PTMs). FragPipe-Analyst and FragPipeAnalystR are both open-source and freely available.

bioinformatics↗

bioRxiv2019

Application of TurboID-mediated proximity labeling for mapping a GSK3 kinase signaling network in Arabidopsis

Transient protein-protein interactions (PPIs), such as those between posttranslational modifying enzymes and their substrates, play key roles in cellular regulation, but are difficult to identify. Here we demonstrate the application of enzyme-catalyzed proximity labeling (PL), using the engineered promiscuous biotin ligase TurboID, as a sensitive method for characterizing PPIs in signaling networks. We show that TurboID fused with the GSK3-like kinase BIN2 or a PP2A phosphatase biotinylates their known substrate, the BZR1 transcription factor, with high specificity and efficiency. We optimized the protocol of biotin labeling and affinity purification in transgenic Arabidopsis expressing a BIN2-TurboID fusion protein. Subsequent quantitative mass spectrometry (MS) analysis identified about three hundred proteins biotinylated by BIN2-TurboID more efficiently than the YFP-TurboID control. These include a significant subset of previously proven BIN2 interactors and a large number of new BIN2-proximal proteins that uncover a broad BIN2 signaling network. Our study illustrates that PL-MS using TurboID is a powerful tool for mapping signaling networks, and reveals broad roles of BIN2 kinase in cellular signaling and regulation in plants.\n\nImpact StatementTurboID-mediated proximity labeling is a powerful tool for protein interactomics in plants.

plant biology↗