Zechuan Shi

The study of neurodegenerative diseases, particularly tauopathies like Pick’s disease (PiD) and Alzheimer’s disease (AD), offers insights into the underlying regulatory mechanisms. By investigating epigenomic variations in these conditions, we identified critical regulatory changes driving disease progression, revealing potential therapeutic targets. Our comparative analyses uncovered disease-enriched non-coding regions and genome-wide transcription factor (TF) binding differences, linking them to target genes. Notably, we identified a distal human-gained enhancer (HGE) associated with E3 ubiquitin ligase (UBE3A), highlighting disease-specific regulatory alterations. Additionally, fine-mapping of AD risk genes uncovered loci enriched in microglial enhancers and accessible in other cell types. Shared and distinct TF binding patterns were observed in neurons and glial cells across PiD and AD. We validated our findings using CRISPR to excise a predicted enhancer region in UBE3A and developed an interactive database (http://swaruplab.bio.uci.edu/scROAD) to visualize predicted single-cell TF occupancy and regulatory networks.

Central nervous system (CNS) lesions become surrounded by neuroprotective borders of newly proliferated reactive astrocytes; however, fundamental features of these cells are poorly understood. Here we show that following spinal cord injury or stroke, 90% and 10% of border-forming astrocytes derive, respectively, from proliferating local astrocytes and oligodendrocyte progenitor cells in adult mice of both sexes. Temporal transcriptome analysis, single-nucleus RNA sequencing and immunohistochemistry show that after focal CNS injury, local mature astrocytes dedifferentiate, proliferate and become transcriptionally reprogrammed to permanently altered new states, with persisting downregulation of molecules associated with astrocyte–neuron interactions and upregulation of molecules associated with wound healing, microbial defense and interactions with stromal and immune cells. These wound repair astrocytes share morphologic and transcriptional features with perimeningeal limitans astrocytes and are the predominant source of neuroprotective borders that re-establish CNS integrity around lesions by separating neural parenchyma from stromal and immune cells as occurs throughout the healthy CNS.

The majority of mammalian genes encode multiple transcript isoforms that result from differential promoter use, changes in exonic splicing, and alternative 3′ end choice. Detecting and quantifying transcript isoforms across tissues, cell types, and species has been extremely challenging because transcripts are much longer than the short reads normally used for RNA-seq. By contrast, long-read RNA-seq (LR-RNA-seq) gives the complete structure of most transcripts. We sequenced 264 LR-RNA-seq PacBio libraries totaling over 1 billion circular consensus reads (CCS) for 81 unique human and mouse samples. We detect at least one full-length transcript from 87.7% of annotated human protein coding genes and a total of \textbackslashtextasciitilde200,000 full-length transcripts, \textbackslashtextasciitilde40% of which have novel exon junction chains. To capture and compute on the three sources of transcript structure diversity, we introduce a gene and transcript annotation framework that uses triplets representing the transcript start site, exon junction chain, and transcript end site of each transcript. Using triplets in a simplex representation demonstrates how promoter selection, splice pattern, and 3′ processing are deployed across human tissues, with nearly half of multitranscript protein coding genes showing a clear bias toward one of the three diversity mechanisms. Evaluated across samples, the predominantly expressed transcript changes for 74% of protein coding genes. In evolution, the human and mouse transcriptomes are globally similar in types of transcript structure diversity, yet among individual orthologous gene pairs, more than half (57.8%) show substantial differences in mechanism of diversification in matching tissues. This initial large-scale survey of human and mouse long-read transcriptomes provides a foundation for further analyses of alternative transcript usage, and is complemented by short-read and microRNA data on the same samples and by epigenome data elsewhere in the ENCODE4 collection.