Evidence map›Paper›PMID 39719707›Full record

ArticleCell genomics2025

Atlas-scale single-cell DNA methylation profiling with sciMETv3.

Ruth V Nichols, Lauren E Rylaarsdam, Brendan L O'Connell, Zohar Shipony, Nika Iremadze, Sonia N Acharya, Andrew C Adey

Abstract read
In one paragraph

Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Layering Methylome and Transcriptome in the Same Tissue Slice.Genomics, proteomics & bioinformatics · 2026
    Article
  4. Dissecting Normal and Abnormal Human Kidney Development Using Multiomics.Journal of the American Society of Nephrology : JASN · 2026
    Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Ruth V NicholsDepartment of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA.
Lauren E RylaarsdamDepartment of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA.
Brendan L O'ConnellDepartment of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA.
Zohar ShiponyUltima Genomics, Fremont, CA, USA.
Nika IremadzeUltima Genomics, Fremont, CA, USA.
Sonia N AcharyaDepartment of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA.
Andrew C AdeyDepartment of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA. Electronic address: adey@ohsu.edu.

Funding

High-content single-cell epigenetic technologies scalable to the human brainRF1MH128842 · NIMH · OREGON HEALTH & SCIENCE UNIVERSITY · PI ADEY, ANDREW · 2021 to 2021
$1.9M
NIMH NIH HHS RF1 MH128842
6 · The paper itself

Abstract

Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity. We showcase the throughput of sciMETv3 by producing a >140,000 cell library from human middle frontal gyrus split across four multiplexed individuals using both Illumina and Ultima sequencing instrumentation. Finally, we introduce sciMET+ATAC to enable high-throughput exploration of the interplay between chromatin accessibility and DNA methylation within the same cell.

Indexed as

DNA MethylationSingle-Cell AnalysisChromatinGene LibraryHigh-Throughput Nucleotide SequencingHumansSequence Analysis, DNAChromatinDNA methylationepigeneticsneurosciencesingle cell

Identifiers

PMID39719707
PMCPMC11770211

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.