Evidence map›Paper›PMID 37443062›Full record

ArticleGenome biology2023

Stable maternal proteins underlie distinct transcriptome, translatome, and proteome reprogramming during mouse oocyte-to-embryo transition.

Hongmei Zhang, Shuyan Ji, Ke Zhang, Yuling Chen, Jia Ming, Feng Kong, Lijuan Wang, Shun Wang, Zhuoning Zou, Zhuqing Xiong and 8 more

Open access · goldAbstract read
In one paragraph

Article in Genome biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed
9.6field-weighted citation impact, top 1% 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

24 citing papers in PubMed, 33 citations in OpenAlex.

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  8. Translational Fidelity Decline in the Aging Oocyte and Embryo Development.International journal of molecular sciences · 2026
    Review
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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

18 authors at 6 institutions in 2 countries.

Hongmei Zhang *Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Shuyan Ji *Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Ke Zhang *Center for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Yuling ChenSchool of Life Sciences, Tsinghua University, Beijing, China.
Jia MingCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Feng KongCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Lijuan WangCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Shun WangSchool of Mathematics and Statistics, Wuhan University, Wuhan, China.
Zhuoning ZouCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Zhuqing XiongCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Kai XuCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Zili LinCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Bo HuangZhejiang Provincial Key Laboratory of Pancreatic Disease, School of Medicine, the First Affiliated Hospital, Zhejiang University, Hangzhou, 310002, China.
Ling LiuCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Qiang FanCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China.
Suoqin JinSchool of Mathematics and Statistics, Wuhan University, Wuhan, China.
Haiteng DengSchool of Life Sciences, Tsinghua University, Beijing, China.
Wei XieCenter for Stem Cell Biology and Regenerative Medicine, MOE Key Laboratory of Bioinformatics, New Cornerstone Science Laboratory, School of Life Sciences, Tsinghua University, Beijing, 100084, China. xiewei121@tsinghua.edu.cn.ORCID 0000-0003-2126-3849
Center for Life Sciences · CNTsinghua University · CNWuhan University · CNFirst Affiliated Hospital Zhejiang University · CNKing Center · USPeking University · CN

Funding

Beijing Municipal Science and Technology Commission Z181100001318006National Key R&D Program of China 2019YFA0508900National Key R&D Program of China 2022YFC2702300National Natural Science Foundation of China 31725018National Natural Science Foundation of China 31830047National Natural Science Foundation of China 31988101
6 · The paper itself

Abstract

backgroundThe oocyte-to-embryo transition (OET) converts terminally differentiated gametes into a totipotent embryo and is critically controlled by maternal mRNAs and proteins, while the genome is silent until zygotic genome activation. How the transcriptome, translatome, and proteome are coordinated during this critical developmental window remains poorly understood.

resultsUtilizing a highly sensitive and quantitative mass spectrometry approach, we obtain high-quality proteome data spanning seven mouse stages, from full-grown oocyte (FGO) to blastocyst, using 100 oocytes/embryos at each stage. Integrative analyses reveal distinct proteome reprogramming compared to that of the transcriptome or translatome. FGO to 8-cell proteomes are dominated by FGO-stockpiled proteins, while the transcriptome and translatome are more dynamic. FGO-originated proteins frequently persist to blastocyst while corresponding transcripts are already downregulated or decayed. Improved concordance between protein and translation or transcription is observed for genes starting translation upon meiotic resumption, as well as those transcribed and translated only in embryos. Concordance between protein and transcription/translation is also observed for proteins with short half-lives. We built a kinetic model that predicts protein dynamics by incorporating both initial protein abundance in FGOs and translation kinetics across developmental stages.

conclusionsThrough integrative analyses of datasets generated by ultrasensitive methods, our study reveals that the proteome shows distinct dynamics compared to the translatome and transcriptome during mouse OET. We propose that the remarkably stable oocyte-originated proteome may help save resources to accommodate the demanding needs of growing embryos. This study will advance our understanding of mammalian OET and the fundamental principles governing gene expression.

Indexed as

ProteomeTranscriptomeAnimalsBlastocystEmbryo, MammalianGene Expression Regulation, DevelopmentalMammalsMiceOocytesProteomeEarly embryo developmentOETOocyte-to-embryo transitionProteomeTranscriptomeTranslatome

Identifiers

PMID37443062
PMCPMC10347836
OpenAlexW4384200572

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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.