Evidence map›Paper›PMID 41484648›Full record

ArticleGenome biology2026

Unravelling the progression of the zebrafish primary body axis with reconstructed spatiotemporal transcriptomics.

Yang Dong, Tao Cheng, Xiang Liu, Xin-Xin Fu, Yang Hu, Xian-Fa Yang, Ling-En Yang, Hao-Ran Li, Zhi-Wen Bian, Naihe Jing and 3 more

Abstract read
In one paragraph

Article in Genome biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Yang Dong *Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.ORCID http://orcid.org/0000-0002-4810-2730
Tao Cheng *Women's Hospital, Zhejiang University School of Medicine, Hangzhou, China.
Xiang Liu *Institute of Genetics and Department of Human Genetics, Zhejiang University School of Medicine, Hangzhou, China.
Xin-Xin FuInstitute of Genetics and Department of Human Genetics, Zhejiang University School of Medicine, Hangzhou, China.
Yang HuYong Loo Lin School of Medicine, National University of Singapore, Queenstown, Singapore.
Xian-Fa YangGuangzhou National Laboratory, Guangzhou, China.
Ling-En YangNational Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan, China.
Hao-Ran LiState Key Laboratory of Chinese Medicine Modernization, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Zhi-Wen BianState Key Laboratory of Chinese Medicine Modernization, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
Naihe JingGuangzhou National Laboratory, Guangzhou, China.
Jie LiaoState Key Laboratory of Chinese Medicine Modernization, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China. liaojie@zju.edu.cn.
Xiaohui FanWomen's Hospital, Zhejiang University School of Medicine, Hangzhou, China. fanxh@zju.edu.cn.
Peng-Fei XuWomen's Hospital, Zhejiang University School of Medicine, Hangzhou, China. pengfei_xu@zju.edu.cn.ORCID http://orcid.org/0000-0002-7318-8548

Funding

National Key Research and Development Program of China 2024YFA1803001National Natural Science Foundation of China 32050109National Natural Science Foundation of China 32300677National Natural Science Foundation of China 32300688National Natural Science Foundation of China 82522092National Natural Science Foundation of China U23A20513Ningbo Top Medical and Health Research Program 2022030309the Pioneer and Leading Goose R&D Program of Zhejiang 2024C03106
6 · The paper itself

Abstract

backgroundElucidating the spatiotemporal dynamics of gene expression is essential for understanding complex physiological and pathological processes. Current spatial transcriptomics techniques are hindered by low read depths and limited gene detection.

resultsHere, we introduce Palette, a pipeline that infers detailed spatial gene expression patterns from bulk RNA-seq data, utilizing existing spatial transcriptomics data as the sole reference. This method identifies more precise expression patterns by smoothing, imputing and adjusting gene expressions. We apply Palette to reconstruct the zebrafish SpatioTemporal Expression Profiles (zSTEP) by integrating 53-slice serial bulk RNA-seq data from three developmental stages with existing spatial transcriptomics and image references. zSTEP provides a comprehensive cartographic resource for examining gene expression and investigating developmental events within zebrafish embryos. Utilizing machine learning-based screening, we identify key morphogens and transcription factors essential for anteroposterior axis development and characterized their dynamic distribution throughout embryogenesis. In addition, among these transcription factors, Hox family genes are found to be pivotal in anteroposterior axis refinement. Their expression is closely correlated with cellular anteroposterior identities, and hoxb genes may act as central regulators in this process.

conclusionsThis study presents Palette, a pipeline for integrating bulk RNA-seq data and spatial transcriptomics data, and zSTEP, a comprehensive cartographic resource for investigating zebrafish early embryonic development. In addition, key morphogens and transcriptional factors essential for anteroposterior axis establishment and refinement are identified.

Indexed as

Body PatterningGene Expression ProfilingTranscriptomeZebrafishAnimalsEmbryonic DevelopmentEmbryo, NonmammalianGene Expression Regulation, DevelopmentalSpatio-Temporal AnalysisTranscription FactorsZebrafish ProteinsTranscription FactorsZebrafish ProteinsPrimary body axisSpatial deconvolutionSpatial transcriptomicsSpatiotemporal gene expressionZebrafish

Identifiers

PMID41484648
PMCPMC12857030

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.