TL;DR
A comprehensive ATAC-seq protocol that is utilized by laboratories, along with detailed troubleshooting steps at each point, is outlined in the hopes that it will aid other researchers in utilizing this tool to the fullest capability.
Fiber-seq simultaneously profiles chromatin accessibility, DNA methylation, protein footprints, and genetic variation on single molecules at near—base-pair resolution, revealing how genetic and epigenetic features interact to regulate gene expression and provides a powerful new framework for dissecting immune cell function and disease mechanisms.
The protocols for ChIP-seq are outlined, including immunoprecipitation, library preparation for high-throughput sequencing, and bioinformatics analysis of sequencing data that the authors routinely perform in their lab groups, and include troubleshooting tips for each step.
Background: Epigenomics has emerged as an essential field in modern molecular biology, providing a critical layer of gene regulation. DNA methylation, histone modifications and alterations to the chromatin accessibility of DNA have been widely associated with complex diseases including cancer. The most recent developments in high-throughput sequencing technology have made it possible to profile epigenetic landscapes genomically on a large scale. However, bulk averaging can obscure cellular heterogeneity essential for understanding complex disease states. The purpose of the review is to survey accessible tools and algorithms to conduct an Epigenomic study in the field of biomedical research, from bulk tissue analysis to the high-resolution frontier of single-cell epigenomics. Methods: We performed a comparative analysis of common methods used to analyze DNA methylation, chromatin immunoprecipitation, sequencing analysis and chromatin accessibility profiling. We described the standardized bioinformatics tools and pipelines required to transform raw sequencing data into mechanistic biological understanding, highlighting the role of quality control, peak calling, and differential analysis. Furthermore, we explore the integration of epigenomics with other “omics” layers through advanced computational frameworks, including machine learning and network-based modeling. Results: These advanced multi-omics techniques demonstrate promising clinical utility by enabling biomarker discovery, disease subtyping, and identification of novel therapeutic targets. Conclusions: Despite challenges with data complexity, the fusion of Artificial Intelligence (AI) and single-cell technologies will accelerate the transition toward precision medicine.
A detailed protocol for flap-enabled next-generation capture (FENGC), a cost-effective method for targeted, multiplexed enrichment of DNA sequences for epigenetic and genetic analysis.
Transposable elements (TEs) account for nearly half of the human genome and shape chromatin organization, gene regulation, and genome evolution. However, their contributions to human physiology and disease remain incompletely understood. The most active elements in humans, LINE-1 (L1), Alu, and SVA, retain some copies with the ability to evade epigenetic repression and mobilize via target-primed reverse transcription (TPRT), whereas copies become inactive through various fragmentations and mutations. TE activity contributes to genomic instability and has been implicated in aging, cancer, neurological disorders, chromatin organization, and epigenetic regulation. Studying TE is challenging due to their repetitive and polymorphic nature. Recent advances in sequencing technologies and short- and long-read sequencing platforms, combined with specialized bioinformatic pipelines, currently enable more comprehensive characterization of TE insertions, deletions, expression, and epigenetic status. Computational approaches vary in sensitivity, specificity, and resource requirements, and their performance is influenced by sequencing modality, coverage, and the reference genome used. Assembly-based and read-based methods, as well as integrating methylation data or single-cell data, provide complementary insights into TE biology. This review summarizes the biology of active human TE, surveys state-of-the-art short- and long-read pipelines for TE analysis, and highlights their applications in studies of aging, cancer, and other complex diseases. We also provide practical guidance for selecting appropriate sequencing strategies and tools for TE-focused projects, and discuss emerging approaches and open questions in the field.
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
