Evidence map›Paper›PMID 38443370›Full record

ArticleCell discovery2024

Mapping crossover events of mouse meiotic recombination by restriction fragment ligation-based Refresh-seq.

Yan Wang, Yijun Chen, Junpeng Gao, Haoling Xie, Yuqing Guo, Jingwei Yang, Jun'e Liu, Zonggui Chen, Qingqing Li, Mengyao Li and 3 more

Open access · goldAbstract read
In one paragraph

Article in Cell discovery, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

13 authors at 1 institution in 2 countries.

Yan Wang *Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-1761-8555
Yijun Chen *Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0001-6122-6271
Junpeng GaoBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-2938-2359
Haoling XieBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Yuqing GuoBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Jingwei YangBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Jun'e LiuBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Zonggui ChenBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Qingqing LiBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0002-1217-365X
Mengyao LiBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.ORCID http://orcid.org/0000-0003-0739-4236
Jie RenBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Lu WenBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Fuchou TangBiomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China. tangfuchou@pku.edu.cn.ORCID http://orcid.org/0000-0002-8625-7717
Peking University · CN

Funding

National Natural Science Foundation of China (National Science Foundation of China) 32288102
6 · The paper itself

Abstract

Single-cell whole-genome sequencing methods have undergone great improvements over the past decade. However, allele dropout, which means the inability to detect both alleles simultaneously in an individual diploid cell, largely restricts the application of these methods particularly for medical applications. Here, we develop a new single-cell whole-genome sequencing method based on third-generation sequencing (TGS) platform named Refresh-seq (restriction fragment ligation-based genome amplification and TGS). It is based on restriction endonuclease cutting and ligation strategy in which two alleles in an individual cell can be cut into equal fragments and tend to be amplified simultaneously. As a new single-cell long-read genome sequencing method, Refresh-seq features much lower allele dropout rate compared with SMOOTH-seq. Furthermore, we apply Refresh-seq to 688 sperm cells and 272 female haploid cells (secondary polar bodies and parthenogenetic oocytes) from F1 hybrid mice. We acquire high-resolution genetic map of mouse meiosis recombination at low sequencing depth and reveal the sexual dimorphism in meiotic crossovers. We also phase the structure variations (deletions and insertions) in sperm cells and female haploid cells with high precision. Refresh-seq shows great performance in screening aneuploid sperm cells and oocytes due to the low allele dropout rate and has great potential for medical applications such as preimplantation genetic diagnosis.

Identifiers

PMID38443370
PMCPMC10915157
OpenAlexW4392470073

What OpenQuestion 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 OpenQuestion graph.