IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v16y2025i1d10.1038_s41467-025-63418-x.html
   My bibliography  Save this article

MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning

Author

Listed:
  • Jishuai Miao

    (The Chinese University of Hong Kong)

  • Jinzhao Li

    (The Chinese University of Hong Kong)

  • Jingxue Xin

    (The Chinese University of Hong Kong)

  • Jiajuan Tu

    (Hubei University of Technology)

  • Muyang Ge

    (The Chinese University of Hong Kong)

  • Ji Qi

    (The Chinese University of Hong Kong)

  • Xiaocheng Zhou

    (The Chinese University of Hong Kong)

  • Ying Zhu

    (Fudan University)

  • Can Yang

    (The Hong Kong University of Science and Technology
    The Hong Kong University of Science and Technology)

  • Zhixiang Lin

    (The Chinese University of Hong Kong
    CUHK Shenzhen Research Institute)

Abstract

New spatial multi-omics technologies, which jointly profile transcriptome and epigenome/protein markers for the same tissue section, expand the frontiers of spatial techniques. Here, we introduce MultiGATE, which utilizes a two-level graph attention auto-encoder to integrate the multi-modality and spatial information in spatial multi-omics data. The key feature of MultiGATE is that it simultaneously performs embedding of the spatial pixels and infers the cross-modality regulatory relationship, which allows deeper data integration and provides insights on transcriptional regulation. We evaluate the performance of MultiGATE on spatial multi-omics datasets obtained from different tissues and platforms. Through effectively integrating spatial multi-omics data, MultiGATE both enhances the extraction of latent embeddings of the pixels and boosts the inference of transcriptional regulation for cross-modality genomic features.

Suggested Citation

  • Jishuai Miao & Jinzhao Li & Jingxue Xin & Jiajuan Tu & Muyang Ge & Ji Qi & Xiaocheng Zhou & Ying Zhu & Can Yang & Zhixiang Lin, 2025. "MultiGATE: integrative analysis and regulatory inference in spatial multi-omics data via graph representation learning," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63418-x
    DOI: 10.1038/s41467-025-63418-x
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-025-63418-x
    File Function: Abstract
    Download Restriction: no
    File URL: https://libkey.io/10.1038/s41467-025-63418-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Lulu Shang & Xiang Zhou, 2022. "Spatially aware dimension reduction for spatial transcriptomics," Nature Communications, Nature, vol. 13(1), pages 1-22, December.
    2. Douglas B. Johnson & Monica V. Estrada & Roberto Salgado & Violeta Sanchez & Deon B. Doxie & Susan R. Opalenik & Anna E. Vilgelm & Emily Feld & Adam S. Johnson & Allison R. Greenplate & Melinda E. San, 2016. "Melanoma-specific MHC-II expression represents a tumour-autonomous phenotype and predicts response to anti-PD-1/PD-L1 therapy," Nature Communications, Nature, vol. 7(1), pages 1-10, April.
    3. Edward Seung & Zhen Xing & Lan Wu & Ercole Rao & Virna Cortez-Retamozo & Beatriz Ospina & Liqing Chen & Christian Beil & Zhili Song & Bailin Zhang & Mikhail Levit & Gejing Deng & Andrew Hebert & Patri, 2022. "Publisher Correction: A trispecific antibody targeting HER2 and T cells inhibits breast cancer growth via CD4 cells," Nature, Nature, vol. 604(7905), pages 13-13, April.
    4. Kangning Dong & Shihua Zhang, 2022. "Deciphering spatial domains from spatially resolved transcriptomics with an adaptive graph attention auto-encoder," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    5. Edward Seung & Zhen Xing & Lan Wu & Ercole Rao & Virna Cortez-Retamozo & Beatriz Ospina & Liqing Chen & Christian Beil & Zhili Song & Bailin Zhang & Mikhail Levit & Gejing Deng & Andrew Hebert & Patri, 2022. "A trispecific antibody targeting HER2 and T cells inhibits breast cancer growth via CD4 cells," Nature, Nature, vol. 603(7900), pages 328-334, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Zhiyuan Yuan, 2024. "MENDER: fast and scalable tissue structure identification in spatial omics data," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    2. Ankit Agrawal & Stefan Thomann & Sukanya Basu & Dominic Grün, 2024. "NiCo identifies extrinsic drivers of cell state modulation by niche covariation analysis," Nature Communications, Nature, vol. 15(1), pages 1-22, December.
    3. Yuqiao Gong & Xin Yuan & Qiong Jiao & Zhangsheng Yu, 2025. "Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST," Nature Communications, Nature, vol. 16(1), pages 1-14, December.
    4. Chunman Zuo & Junjie Xia & Luonan Chen, 2024. "Dissecting tumor microenvironment from spatially resolved transcriptomics data by heterogeneous graph learning," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
    5. Jingyang Qian & Xin Shao & Hudong Bao & Yin Fang & Wenbo Guo & Chengyu Li & Anyao Li & Hua Hua & Xiaohui Fan, 2025. "Identification and characterization of cell niches in tissue from spatial omics data at single-cell resolution," Nature Communications, Nature, vol. 16(1), pages 1-21, December.
    6. Kaichen Xu & Yan Lu & Suyang Hou & Kainan Liu & Yihang Du & Mengqian Huang & Hao Feng & Hao Wu & Xiaobo Sun, 2024. "Detecting anomalous anatomic regions in spatial transcriptomics with STANDS," Nature Communications, Nature, vol. 15(1), pages 1-23, December.
    7. Yuchen Liang & Guowei Shi & Runlin Cai & Yuchen Yuan & Ziying Xie & Long Yu & Yingjian Huang & Qian Shi & Lizhe Wang & Jun Li & Zhonghui Tang, 2024. "PROST: quantitative identification of spatially variable genes and domain detection in spatial transcriptomics," Nature Communications, Nature, vol. 15(1), pages 1-17, December.
    8. Alex J. Lee & Alma Dubuc & Michael Kunst & Shenqin Yao & Nicholas Lusk & Lydia Ng & Hongkui Zeng & Bosiljka Tasic & Reza Abbasi-Asl, 2025. "Data-driven fine-grained region discovery in the mouse brain with transformers," Nature Communications, Nature, vol. 16(1), pages 1-16, December.
    9. Xiyu Peng & James W. Smithy & Mohammad Yosofvand & Caroline E. Kostrzewa & MaryLena Bleile & Fiona D. Ehrich & Jasme Lee & Michael A. Postow & Margaret K. Callahan & Katherine S. Panageas & Ronglai Sh, 2025. "Scalable topic modelling decodes spatial tissue architecture for large-scale multiplexed imaging analysis," Nature Communications, Nature, vol. 16(1), pages 1-15, December.
    10. Yuyao Liu & Zhen Li & Xiaoyang Chen & Xuejian Cui & Zijing Gao & Rui Jiang, 2025. "INSTINCT: Multi-sample integration of spatial chromatin accessibility sequencing data via stochastic domain translation," Nature Communications, Nature, vol. 16(1), pages 1-23, December.
    11. Danni Hong & Muya Shu & Jiamao Liu & Lifang Liu & Hao Cheng & Ming Zhu & Yi Du & Bo Xu & Di Hu & Zhiyong Liu & Yannan Zhao & Jianwu Dai & Falong Lu & Jialiang Huang, 2025. "Divergent combinations of enhancers encode spatial gene expression," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
    12. Guanshen Cui & Kangning Dong & Jia-Yi Zhou & Shang Li & Ying Wu & Qinghua Han & Bofei Yao & Qunlun Shen & Yong-Liang Zhao & Ying Yang & Jun Cai & Shihua Zhang & Yun-Gui Yang, 2023. "Spatiotemporal transcriptomic atlas reveals the dynamic characteristics and key regulators of planarian regeneration," Nature Communications, Nature, vol. 14(1), pages 1-16, December.
    13. Chen Zhang & Junhui Gao & Hong-Yu Chen & Lingxin Kong & Guangshuo Cao & Xiangyu Guo & Wei Liu & Bin Ren & Dong-Qing Wei, 2024. "STGIC: A graph and image convolution-based method for spatial transcriptomic clustering," PLOS Computational Biology, Public Library of Science, vol. 20(2), pages 1-24, February.
    14. Chen-Rui Xia & Zhi-Jie Cao & Ge Gao, 2025. "DECIPHER for learning disentangled cellular embeddings in large-scale heterogeneous spatial omics data," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    15. Yanming Ren & Zongyao Huang & Lingling Zhou & Peng Xiao & Junwei Song & Ping He & Chuanxing Xie & Ran Zhou & Menghan Li & Xiangqun Dong & Qing Mao & Chao You & Jianguo Xu & Yanhui Liu & Zhigang Lan & , 2023. "Spatial transcriptomics reveals niche-specific enrichment and vulnerabilities of radial glial stem-like cells in malignant gliomas," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
    16. Benjamin L. Walker & Qing Nie, 2023. "NeST: nested hierarchical structure identification in spatial transcriptomic data," Nature Communications, Nature, vol. 14(1), pages 1-17, December.
    17. Xiaomeng Wan & Jiashun Xiao & Sindy Sing Ting Tam & Mingxuan Cai & Ryohichi Sugimura & Yang Wang & Xiang Wan & Zhixiang Lin & Angela Ruohao Wu & Can Yang, 2023. "Integrating spatial and single-cell transcriptomics data using deep generative models with SpatialScope," Nature Communications, Nature, vol. 14(1), pages 1-22, December.
    18. Chunman Zuo & Yijian Zhang & Chen Cao & Jinwang Feng & Mingqi Jiao & Luonan Chen, 2022. "Elucidating tumor heterogeneity from spatially resolved transcriptomics data by multi-view graph collaborative learning," Nature Communications, Nature, vol. 13(1), pages 1-14, December.
    19. Lulu Shang & Peijun Wu & Xiang Zhou, 2025. "Statistical identification of cell type-specific spatially variable genes in spatial transcriptomics," Nature Communications, Nature, vol. 16(1), pages 1-20, December.
    20. Tianci Song & Charles Broadbent & Rui Kuang, 2023. "GNTD: reconstructing spatial transcriptomes with graph-guided neural tensor decomposition informed by spatial and functional relations," Nature Communications, Nature, vol. 14(1), pages 1-17, December.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:16:y:2025:i:1:d:10.1038_s41467-025-63418-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.