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Gene W Yeo

Publications and source records attributed to Gene W Yeo.

7 recordsLinked to original sources

RNA dysregulation as a determinant of aging and neurodegenerative vulnerability.

In the nervous system, aging causes deterioration of cellular and molecular processes that are associated with declines in cognition, sensory perception, and motor coordination. Aging is also the strongest risk factor for neurodegenerative disease, yet the mechanisms by which aging predisposes neurons to dysfunction remain incompletely understood. While genomic instability, proteostasis decline, mitochondrial dysfunction, and chronic inflammation have dominated prevailing models, recent evidence highlights RNA dysregulation as a central component of age-associated decline. In this review, we summarize recent findings suggesting that aging progressively erodes RNA regulatory fidelity through alterations in RNA-binding protein abundance, localization, biophysical behavior, and RNA interactions. We argue that age-dependent RNA dysregulation represents an important mechanism that converges with genetic risk to drive neuronal vulnerability and neurodegeneration.

RNA dysregulation↗

ARID5A RNA-binding coordinates microglial defense and ferroptosis in iPSC-derived models.

RNA-binding proteins (RBPs) are key regulators of gene expression that shape cellular function in health and disease. However, the roles of RBPs in immune cells within the central nervous system (CNS) remain poorly understood. Here, we identify ARID5A as an RBP highly expressed in microglia and uncover its RNA-mediated regulatory functions using integrated multi-omics analyses of its RNA, DNA, and protein interactions. ARID5A regulates the splicing and translation of its RNA targets, many of which are integral to lysosomal, immune, and iron metabolism pathways. We confirm the functional relevance of this ARID5A-dependent RNA regulatory network by demonstrating that ARID5A modulates lysosomal activity, cytokine secretion, iron accumulation, and ferroptosis in iPSC-derived microglia. We further demonstrate that knockdown of microglial ARID5A reduces neuronal ferroptosis in co-cultures, underscoring the interconnected nature of these pathways. Moreover, in microglia harboring the TREM2-T66M mutation, ARID5A depletion restores dysregulated lysosomal and metabolic functions. Our results highlight the importance of protein-RNA interactions in regulating microglial cell biology.

Microglia↗

Identification of RBP binding sites using RNA deaminases.

RNA-binding proteins (RBPs) are critical regulators of gene expression and RNA processing. Identification of their binding sites has important implications for their physiological and disease-related functions. Crosslinking and immunoprecipitation, followed by sequencing (CLIP-seq) and its derivatives, are the most commonly used methods to identify RBP binding sites, but are laborious and require a large amount of starting material. Recent advancements harnessing RNA deaminases in fusion to any RBP of interest, allow for the profiling of RBP binding sites from low-input samples in simpler procedures. Among these efforts, we developed STAMP (Surveying Targets by APOBEC-Mediated Profiling), which efficiently detects RBP-RNA interactions. This chapter describes the detailed protocol for the STAMP method, including plasmid construction, delivery and sorting, library preparation and bioinformatic data analysis.

RNA-Binding Proteins↗

Mudskipper detects combinatorial RNA binding protein interactions in multiplexed CLIP data.

The uncovering of protein-RNA interactions enables a deeper understanding of RNA processing. Recent multiplexed crosslinking and immunoprecipitation (CLIP) technologies such as antibody-barcoded eCLIP (ABC) dramatically increase the throughput of mapping RNA binding protein (RBP) binding sites. However, multiplex CLIP datasets are multivariate, and each RBP suffers non-uniform signal-to-noise ratio. To address this, we developed Mudskipper, a versatile computational suite comprising two components: a Dirichlet multinomial mixture model to account for the multivariate nature of ABC datasets and a softmasking approach that identifies and removes non-specific protein-RNA interactions in RBPs with low signal-to-noise ratio. Mudskipper demonstrates superior precision and recall over existing tools on multiplex datasets and supports analysis of repetitive elements and small non-coding RNAs. Our findings unravel splicing outcomes and variant-associated disruptions, enabling higher-throughput investigations into diseases and regulation mediated by RBPs.

RNA-Binding Proteins↗

Inference of splicing regulatory activities by sequence neighborhood analysis.

Sequence-specific recognition of nucleic-acid motifs is critical to many cellular processes. We have developed a new and general method called Neighborhood Inference (NI) that predicts sequences with activity in regulating a biochemical process based on the local density of known sites in sequence space. Applied to the problem of RNA splicing regulation, NI was used to predict hundreds of new exonic splicing enhancer (ESE) and silencer (ESS) hexanucleotides from known human ESEs and ESSs. These predictions were supported by cross-validation analysis, by analysis of published splicing regulatory activity data, by sequence-conservation analysis, and by measurement of the splicing regulatory activity of 24 novel predicted ESEs, ESSs, and neutral sequences using an in vivo splicing reporter assay. These results demonstrate the ability of NI to accurately predict splicing regulatory activity and show that the scope of exonic splicing regulatory elements is substantially larger than previously anticipated. Analysis of orthologous exons in four mammals showed that the NI score of ESEs, a measure of function, is much more highly conserved above background than ESE primary sequence. This observation indicates a high degree of selection for ESE activity in mammalian exons, with surprisingly frequent interchangeability between ESE sequences.

Binding Sites↗

Identification and analysis of alternative splicing events conserved in human and mouse.

Alternative pre-mRNA splicing affects a majority of human genes and plays important roles in development and disease. Alternative splicing (AS) events conserved since the divergence of human and mouse are likely of primary biological importance, but relatively few of such events are known. Here we describe sequence features that distinguish exons subject to evolutionarily conserved AS, which we call alternative conserved exons (ACEs), from other orthologous human/mouse exons and integrate these features into an exon classification algorithm, acescan. Genome-wide analysis of annotated orthologous human-mouse exon pairs identified approximately 2,000 predicted ACEs. Alternative splicing was verified in both human and mouse tissues by using an RT-PCR-sequencing protocol for 21 of 30 (70%) predicted ACEs tested, supporting the validity of a majority of acescan predictions. By contrast, AS was observed in mouse tissues for only 2 of 15 (13%) tested exons that had EST or cDNA evidence of AS in human but were not predicted ACEs, and AS was never observed for 11 negative control exons in human or mouse tissues. Predicted ACEs were much more likely to preserve the reading frame and less likely to disrupt protein domains than other AS events and were enriched in genes expressed in the brain and in genes involved in transcriptional regulation, RNA processing, and development. Our results also imply that the vast majority of AS events represented in the human EST database are not conserved in mouse.

Alternative Splicing↗

RESCUE-ESE identifies candidate exonic splicing enhancers in vertebrate exons.

A typical gene contains two levels of information: a sequence that encodes a particular protein and a host of other signals that are necessary for the correct expression of the transcript. While much attention has been focused on the effects of sequence variation on the amino acid sequence, variations that disrupt gene processing signals can dramatically impact gene function. A variation that disrupts an exonic splicing enhancer (ESE), for example, could cause exon skipping which would result in the exclusion of an entire exon from the mRNA transcript. RESCUE-ESE, a computational approach used in conjunction with experimental validation, previously identified 238 candidate ESE hexamers in human genes. The RESCUE-ESE method has recently been implemented in three additional species: mouse, zebrafish and pufferfish. Here we describe an online ESE analysis tool (http://genes.mit.edu/burgelab/rescue-ese/) that annotates RESCUE-ESE hexamers in vertebrate exons and can be used to predict splicing phenotypes by identifying sequence changes that disrupt or alter predicted ESEs.

Animals↗