Distinct roles of nucleosome sliding and histone modifications in controlling the fidelity of transcription initiation

Brain 5-hydroxymethylcytosine alterations are associated with Alzheimer's disease neuropathology

5-hydroxymethylcytosine, also known as the sixth DNA base of the genome, plays an important role in brain aging and neurological disorders such as Alzheimer's disease. However, little is known about its genome-wide distribution and its association with Alzheimer's disease pathology. Here, we report a genome-wide profiling of 5-hydroxymethylcytosine in 1079 autopsied brains (dorsolateral prefrontal cortex) of older individuals and assess its association with multiple measures of Alzheimer's disease pathologies, including pathological diagnosis of Alzheimer's disease, amyloid-β load, and PHFtau tangle density. Of 197,765 5-hydroxymethylcytosine regions detected, we identified 2821 differentially hydroxymethylated regions associated with Alzheimer's disease neuropathology after controlling for multiple testing and covariates. Many differentially hydroxymethylated regions are located within known Alzheimer's disease loci, such as RIN3, PLCG2, ITGA2B, and USP6NL. Integrative multi-omics analyses support a potential mechanistic role of 5-hydroxymethylcytosine alterations in Alzheimer's disease. Our study presents a large-scale genome-wide atlas of 5-hydroxymethylcytosine in Alzheimer's brain and offers insight into the mechanism underlying Alzheimer's disease pathogenesis.

An Epigenetic Manifestation of Alzheimer's Disease: DNA Methylation

Alzheimer's disease (AD), the most common form of dementia, has a complex pathogenesis. The number of AD patients has increased in recent years due to population aging, while a trend toward a younger age of onset has arisen, imposing a substantial burden on society and families, and garnering extensive attention. DNA methylation has recently been revealed to play an important role in AD onset and progression. DNA methylation is a critical mechanism regulating gene expression, and alterations in this mechanism dysregulate gene expression and disrupt important pathways, including oxidative stress responses, inflammatory reactions, and protein degradation processes, eventually resulting in disease. Studies have revealed widespread changes in AD patients' DNA methylation in the peripheral blood and brain tissues, affecting multiple signaling pathways and severely impacting neuronal cell and synaptic functions. This review summarizes the role of DNA methylation in the pathogenesis of AD, aiming to provide a theoretical basis for its early prevention and treatment.

TSSr: an R package for comprehensive analyses of TSS sequencing data

Transcription initiation is regulated in a highly organized fashion to ensure proper cellular functions. Accurate identification of transcription start sites (TSSs) and quantitative characterization of transcription initiation activities are fundamental steps for studies of regulated transcriptions and core promoter structures. Several high-throughput techniques have been developed to sequence the very 5'end of RNA transcripts (TSS sequencing) on the genome scale. Bioinformatics tools are essential for processing, analysis, and visualization of TSS sequencing data. Here, we present TSSr, an R package that provides rich functions for mapping TSS and characterizations of structures and activities of core promoters based on all types of TSS sequencing data. Specifically, TSSr implements several newly developed algorithms for accurately identifying TSSs from mapped sequencing reads and inference of core promoters, which are a prerequisite for subsequent functional analyses of TSS data. Furthermore, TSSr also enables users to export various types of TSS data that can be visualized by genome browser for inspection of promoter activities in association with other genomic features, and to generate publication-ready TSS graphs. These user-friendly features could greatly facilitate studies of transcription initiation based on TSS sequencing data. The source code and detailed documentations of TSSr can be freely accessed at https://github.com/Linlab-slu/TSSr.