High-Fidelity Long-term Whole-embryo Lineage and Fate Reconstruction by Iterative Tracking with Error Correction

Reconstructing the complete cell lineages and fate maps of a living embryo has remained a central challenge in developmental biology. Here we introduce ITEC (Iterative Tracking with Error Correction), a fully unsupervised method that automatically reconstructs the lineage of every cell in the embryo with high fidelity. ITEC was validated with manually annotated lineages on four cross-species datasets including zebrafish, mouse, and <i>Drosophila</i> . We reconstructed the developmental lineages of a zebrafish embryo from terabyte-scale data of total 18.5 million cells with an estimated accuracy of over 99.7%. With ITEC, we revealed spatiotemporal dynamics of key morphogenetic processes such as somite boundary formation, demonstrated the various patterns of spatial sorting among adjacent organs or anatomical regions, and identified associations between cellular movement and spatial transcriptomics. ITEC provides a powerful platform for retrospective fate mapping and systematic exploration of developmental dynamics at the cellular scale and single-embryo level.

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Publication Details

Journal
bioRxiv (Cold Spring Harbor Laboratory)
Published
2026-03-16
DOI
https://doi.org/10.64898/2026.03.12.711203
Primary Topic
Single-cell and spatial transcriptomics
Type
article
Field-Weighted Citation Impact
0.00

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article

High-Fidelity Long-term Whole-embryo Lineage and Fate Reconstruction by Iterative Tracking with Error Correction

Xiangyu Cao, Weizhan Zhang, Joaquín Navajas Acedo, Yunfeng Chi et al.
bioRxiv (Cold Spring Harbor Laboratory)
Single-cell and spatial transcriptomics
article

High-Fidelity Long-term Whole-embryo Lineage and Fate Reconstruction by Iterative Tracking with Error Correction

Xiangyu Cao, Weizhan Zhang, Joaquín Navajas Acedo, Yunfeng Chi, Alexander F. Schier, Congchao Wang, Mengfan Wang, Boao Yang, Qinghua Zhang, Yinan Wan, Zeyu Mu, Guoqiang Yu, Wei Zheng
article en

Abstract

Reconstructing the complete cell lineages and fate maps of a living embryo has remained a central challenge in developmental biology. Here we introduce ITEC (Iterative Tracking with Error Correction), a fully unsupervised method that automatically reconstructs the lineage of every cell in the embryo with high fidelity. ITEC was validated with manually annotated lineages on four cross-species datasets including zebrafish, mouse, and <i>Drosophila</i> . We reconstructed the developmental lineages of a zebrafish embryo from terabyte-scale data of total 18.5 million cells with an estimated accuracy of over 99.7%. With ITEC, we revealed spatiotemporal dynamics of key morphogenetic processes such as somite boundary formation, demonstrated the various patterns of spatial sorting among adjacent organs or anatomical regions, and identified associations between cellular movement and spatial transcriptomics. ITEC provides a powerful platform for retrospective fate mapping and systematic exploration of developmental dynamics at the cellular scale and single-embryo level.

bioRxiv (Cold Spring Harbor Laboratory)
McGovern Institute for Brain Research (US), University of Basel (CH), National Center for Mathematics and Interdisciplinary Sciences (CN), Chinese Institute for Brain Research (CN), National Engineering Research Center for Information Technology in Agriculture (CN), Allen Institute for Cell Science (US), Virginia Tech (US), Tsinghua University (CN)
Universität Basel, Tsinghua University, National Institutes of Health, Horizon 2020 Framework Programme
Openalex Percentile: Top 20%
Single-cell and spatial transcriptomics
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