| Title: |
Novel enzyme-based reduced representation method for DNA methylation profiling with low inputs |
| Authors: |
Liu, Qianli; Helmin, Kathryn A; Dortzbach, Zachary D; Reyes Flores, Carla P; Torres Acosta, Manuel A; Gurkan, Jonathan K; Joudi, Anthony M; Mambetsariev, Nurbek; Morales-Nebreda, Luisa; Kang, Mengjia; Rasmussen, Luke; Pérez-Leonor, Xóchitl G; Abdala-Valencia, Hiam; Singer, Benjamin D |
| Contributors: |
David W. Cugell Fellowship; Genomics Network; NIH; Northwestern University Flow Cytometry Core Facility; D FACSAria SORP; Northwestern University Metabolomics and Integrative Genomics Core; Genomics Compute Cluster; Feinberg School of Medicine; Center for Genetic Medicine; Feinberg’s Department of Biochemistry and Molecular Genetics; Office of the Provost; Office for Research, and Northwestern Information Technology |
| Source: |
Nucleic Acids Research ; volume 53, issue 12 ; ISSN 0305-1048 1362-4962 |
| Publisher Information: |
Oxford University Press (OUP) |
| Publication Year: |
2025 |
| Description: |
Commonly used bisulfite-based procedures for DNA methylation sequencing can degrade DNA, worsening signal-to-noise ratios in samples with low DNA input. Enzymatic methylation sequencing (EM-seq) has been proposed as a less biased alternative for methylation profiling with greater genome coverage. Reduced representation approaches enrich samples for CpG-rich genomic regions, thereby enhancing throughput and cost effectiveness. We hypothesized that enzyme-based technology could be adapted for reduced representation methylation sequencing to enable DNA methylation profiling of low-input samples. We leveraged the well-established differences in methylation profile between mouse CD4+ T cell populations to compare the performance of our reduced representation EM-seq (RREM-seq) procedure against an established reduced representation bisulfite sequencing (RRBS) protocol. While the RRBS method failed to generate reliable DNA libraries when using 10-fold higher DNA input. RREM-seq also successfully detected lineage-defining methylation differences between alveolar conventional T and regulatory T cells obtained from patients with severe SARS-CoV-2 pneumonia. Our RREM-seq method enables single-nucleotide resolution methylation profiling using low-input samples, including from clinical sources. |
| Document Type: |
article in journal/newspaper |
| Language: |
English |
| DOI: |
10.1093/nar/gkaf558 |
| Availability: |
https://doi.org/10.1093/nar/gkaf558; https://academic.oup.com/nar/article-pdf/53/12/gkaf558/63626067/gkaf558.pdf |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.71741D6 |
| Database: |
BASE |