Evidence map›Paper›PMID 42112493›Full record

ArticleBiology methods & protocols2026

A low-input Micro-C protocol for high-resolution 3D genome mapping.

Fengnian Shan, Chongren Pei, Sijian Xia, Fei Ling

Abstract read
In one paragraph

Article in Biology methods & protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Fengnian ShanSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China.ORCID https://orcid.org/0009-0006-1227-8757
Chongren PeiInstitute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen 518132, China.
Sijian XiaInstitute of Molecular Physiology, Shenzhen Bay Laboratory, Shenzhen 518132, China.
Fei LingSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Standard Micro-C protocols typically require millions of cells, limiting their application to rare cell populations. Here, we present an optimized low-input Micro-C workflow that requires only 100 000 cells. By downsampling both our low-input dataset and a control dataset from 5 million cells to 120 million raw read pairs, we demonstrate that all key architectural features-Compartments, Topologically associating domains (TADs), and Chromatin loops-are reliably detected from as few as 100 000 cells. The low-input protocol achieved a high cis interaction ratio (96.1%) and low PCR duplication rate (3.0%), indicating high library complexity and low background noise. Applying this method to investigate acute CTCF (CCCTC-binding factor) degradation, we observed the loss of loops and TAD boundaries in CTCF-degraded samples, consistent with previous reports. Our optimized protocol enables nucleosome-resolution 3D genome mapping for sample-limited studies.

Indexed as

chromatin architectureMicro-cnucleosome resolution

Identifiers

PMID42112493
PMCPMC13152656

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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 OpenQuestion graph.