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Especially, the local expression patterns and spatio-temporal regulation mechanisms captured by spatial expression images allow more delicate delineation of the interplay between transcript factors and their target genes. However, the complexity and size of spatial image collections pose significant challenges to GRN inference using image-based methods. Extracting regulatory information from expression images is difficult due to the lack of supervision and the multi-instance nature of the problem, where a gene often corresponds to multiple images captured from different views. While graph models, particularly graph neural networks, have emerged as a promising method for leveraging underlying structure information from known GRNs, incorporating expression images into graphs is not straightforward. To address these challenges, we propose a two-stage approach, MIGGRI, for capturing comprehensive regulatory patterns from image collections for each gene and known interactions. Our approach involves a multi-instance graph neural network (GNN) model for GRN inference, which first extracts gene regulatory features from spatial expression images via contrastive learning, and then feeds them to a multi-instance GNN for semi-supervised learning. We apply our approach to a large set of<jats:italic>Drosophila<\/jats:italic>embryonic spatial gene expression images. MIGGRI achieves outstanding performance in the inference of GRNs for early eye development and mesoderm development of<jats:italic>Drosophila<\/jats:italic>, and shows robustness in the scenarios of missing image information. Additionally, we perform interpretable analysis on image reconstruction and functional subgraphs that may reveal potential pathways or coordinate regulations. By leveraging the power of graph neural networks and the information contained in spatial expression images, our approach has the potential to advance our understanding of gene regulation in complex biological systems.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1011623","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T18:54:10Z","timestamp":1699469650000},"page":"e1011623","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":6,"title":["MIGGRI: A multi-instance graph neural network model for inferring gene regulatory networks for Drosophila from spatial expression 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Wang","year":"2006","journal-title":"Bioinformatics"},{"issue":"12","key":"pcbi.1011623.ref002","doi-asserted-by":"crossref","first-page":"1592","DOI":"10.1093\/bioinformatics\/bts245","article-title":"Utilizing RNA-Seq data for de novo coexpression network inference","volume":"28","author":"OD Iancu","year":"2012","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref003","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1186\/1752-0509-4-130","article-title":"Statistical inference of the time-varying structure of gene-regulation networks","volume":"4","author":"D Fr\u00e9d\u00e9ric","year":"2010","journal-title":"BMC Systems Biology"},{"key":"pcbi.1011623.ref004","article-title":"Large-scale mapping and validation of Escherichia coli transcriptional regulation from a compendium of expression profiles","volume":"5","author":"FJ J","year":"2007","journal-title":"PLoS biology"},{"key":"pcbi.1011623.ref005","first-page":"418","article-title":"Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements","author":"BA J","year":"2000","journal-title":"Pacific Symposium on Biocomputing"},{"key":"pcbi.1011623.ref006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pcbi.1000790","article-title":"Analysis and computational dissection of molecular signature multiplicity","volume":"6","author":"A Statnikov","year":"2010","journal-title":"PLoS Computational Biology"},{"issue":"20","key":"pcbi.1011623.ref007","doi-asserted-by":"crossref","first-page":"2523","DOI":"10.1093\/bioinformatics\/btl391","article-title":"Comparative evaluation of reverse engineering gene regulatory networks with relevance networks, graphical Gaussian models and Bayesian networks","volume":"22","author":"AV Werhli","year":"2006","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref008","first-page":"1","article-title":"Gene regulatory network inference in the era of single-cell multi-omics","author":"P Badia-i Mompel","year":"2023","journal-title":"Nature Reviews Genetics"},{"issue":"1","key":"pcbi.1011623.ref009","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.jmoldx.2011.08.002","article-title":"RNAscope: a novel in situ RNA analysis platform for formalin-fixed, paraffin-embedded tissues","volume":"14","author":"F Wang","year":"2012","journal-title":"The Journal of molecular diagnostics"},{"issue":"7751","key":"pcbi.1011623.ref010","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1038\/s41586-019-1049-y","article-title":"Transcriptome-scale super-resolved imaging in tissues by RNA seqFISH+","volume":"568","author":"CHL Eng","year":"2019","journal-title":"Nature"},{"issue":"39","key":"pcbi.1011623.ref011","doi-asserted-by":"crossref","first-page":"19490","DOI":"10.1073\/pnas.1912459116","article-title":"Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression","volume":"116","author":"C Xia","year":"2019","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"1","key":"pcbi.1011623.ref012","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-020-02214-w","article-title":"GCNG: graph convolutional networks for inferring gene interaction from spatial transcriptomics data","volume":"21","author":"Y Yuan","year":"2020","journal-title":"Genome Biology"},{"issue":"1","key":"pcbi.1011623.ref013","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13059-022-02653-7","article-title":"Statistical and machine learning methods for spatially resolved transcriptomics data analysis","volume":"23","author":"Z Zeng","year":"2022","journal-title":"Genome biology"},{"key":"pcbi.1011623.ref014","article-title":"GINI: from ISH images to gene interaction networks","volume":"9","author":"P Kriti","year":"2013","journal-title":"PLoS computational biology"},{"key":"pcbi.1011623.ref015","first-page":"4290","article-title":"Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks","volume":"113","author":"W Siqi","year":"2016","journal-title":"Proceedings of the National Academy of Sciences of the United States of America"},{"key":"pcbi.1011623.ref016","article-title":"Inferring gene regulatory network via fusing gene expression image and RNA-seq data","author":"X Li","year":"2022","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref017","doi-asserted-by":"crossref","DOI":"10.1371\/journal.pcbi.1007324","article-title":"Predicting gene regulatory interactions based on spatial gene expression data and deep learning","volume":"15","author":"Y Yang","year":"2019","journal-title":"PLoS computational biology"},{"key":"pcbi.1011623.ref018","doi-asserted-by":"crossref","first-page":"746","DOI":"10.1093\/bioinformatics\/btab718","article-title":"Accurate inference of gene regulatory interactions from spatial gene expression with deep contrastive learning","volume":"38","author":"L Zheng","year":"2022","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref019","doi-asserted-by":"crossref","unstructured":"He K, et al. Deep residual learning for image recognition. In: Proceedings of the IEEE conference on computer vision and pattern recognition; 2016. p. 770\u2013778.","DOI":"10.1109\/CVPR.2016.90"},{"key":"pcbi.1011623.ref020","doi-asserted-by":"crossref","unstructured":"Dong X, Shen J. Triplet loss in siamese network for object tracking. In: Proceedings of the European conference on computer vision (ECCV); 2018. p. 459\u2013474.","DOI":"10.1007\/978-3-030-01261-8_28"},{"key":"pcbi.1011623.ref021","doi-asserted-by":"crossref","first-page":"3335","DOI":"10.1016\/j.csbj.2020.10.022","article-title":"Inductive inference of gene regulatory network using supervised and semi-supervised graph neural networks","volume":"18","author":"J Wang","year":"2020","journal-title":"Computational and Structural Biotechnology Journal"},{"key":"pcbi.1011623.ref022","doi-asserted-by":"crossref","first-page":"2290","DOI":"10.1016\/j.celrep.2014.11.038","article-title":"Mapping Gene Regulatory Networks in Drosophila Eye Development by Large-Scale Transcriptome Perturbations and Motif Inference","volume":"9","author":"D Potier","year":"2014","journal-title":"Cell Reports"},{"issue":"4","key":"pcbi.1011623.ref023","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1101\/gad.1509007","article-title":"A core transcriptional network for early mesoderm development in Drosophila melanogaster","volume":"21","author":"T Sandmann","year":"2007","journal-title":"Genes & development"},{"issue":"12","key":"pcbi.1011623.ref024","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/gb-2002-3-12-research0088","article-title":"Systematic determination of patterns of gene expression during Drosophila embryogenesis","volume":"3","author":"P Tomancak","year":"2002","journal-title":"Genome biology"},{"issue":"7","key":"pcbi.1011623.ref025","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/gb-2007-8-7-r145","article-title":"Global analysis of patterns of gene expression during Drosophila embryogenesis","volume":"8","author":"P Tomancak","year":"2007","journal-title":"Genome biology"},{"key":"pcbi.1011623.ref026","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1002\/dvdy.22749","article-title":"Comparison of embryonic expression within multigene families using the FlyExpress discovery platform reveals more spatial than temporal divergence","volume":"241","author":"KC E","year":"2012","journal-title":"Developmental dynamics: an official publication of the American Association of Anatomists"},{"key":"pcbi.1011623.ref027","doi-asserted-by":"crossref","first-page":"3319","DOI":"10.1093\/bioinformatics\/btr567","article-title":"FlyExpress: visual mining of spatiotemporal patterns for genes and publications in Drosophila embryogenesis","volume":"27","author":"K Sudhir","year":"2011","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref028","doi-asserted-by":"crossref","first-page":"2847","DOI":"10.1093\/bioinformatics\/bts518","article-title":"Exploring spatial patterns of gene expression from Fruit Fly embryogenesis on the iPhone","volume":"28","author":"S Kumar","year":"2012","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref029","doi-asserted-by":"crossref","unstructured":"Hadsell R, Chopra S, LeCun Y. Dimensionality Reduction by Learning an Invariant Mapping. In: 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR 2006), 17-22 June 2006, New York, NY, USA; 2006. p. 1735\u20131742.","DOI":"10.1109\/CVPR.2006.100"},{"key":"pcbi.1011623.ref030","unstructured":"Hamilton WL, Ying Z, Leskovec J. Inductive Representation Learning on Large Graphs. In: Guyon I, von Luxburg U, Bengio S, Wallach HM, Fergus R, Vishwanathan SVN, et al., editors. Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, December 4-9, 2017, Long Beach, CA, USA; 2017. p. 1024\u20131034."},{"key":"pcbi.1011623.ref031","unstructured":"Kingma DP, Ba J. Adam: A Method for Stochastic Optimization. In: Bengio Y, LeCun Y, editors. 3rd International Conference on Learning Representations, ICLR 2015, San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings; 2015."},{"key":"pcbi.1011623.ref032","doi-asserted-by":"crossref","unstructured":"Hadsell R, Chopra S, LeCun Y. Dimensionality reduction by learning an invariant mapping. In: 2006 IEEE computer society conference on computer vision and pattern recognition (CVPR\u201906). vol. 2. IEEE; 2006. p. 1735\u20131742.","DOI":"10.1109\/CVPR.2006.100"},{"key":"pcbi.1011623.ref033","doi-asserted-by":"crossref","first-page":"91","DOI":"10.1023\/B:VISI.0000029664.99615.94","article-title":"Distinctive image features from scale-invariant keypoints","volume":"60","author":"DG Lowe","year":"2004","journal-title":"International journal of computer vision"},{"key":"pcbi.1011623.ref034","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s12859-015-0553-9","article-title":"Deep convolutional neural networks for annotating gene expression patterns in the mouse brain","volume":"16","author":"T Zeng","year":"2015","journal-title":"BMC bioinformatics"},{"issue":"12","key":"pcbi.1011623.ref035","doi-asserted-by":"crossref","first-page":"i16","DOI":"10.1093\/bioinformatics\/bts220","article-title":"Joint stage recognition and anatomical annotation of drosophila gene expression patterns","volume":"28","author":"X Cai","year":"2012","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref036","doi-asserted-by":"crossref","first-page":"2834","DOI":"10.1093\/bioinformatics\/bty1064","article-title":"AnnoFly: annotating Drosophila embryonic images based on an attention-enhanced RNN model","volume":"35","author":"Y Yang","year":"2019","journal-title":"Bioinformatics"},{"key":"pcbi.1011623.ref037","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/978-1-59745-583-1_3","article-title":"FlyBase","author":"R Drysdale","year":"2008","journal-title":"Drosophila"},{"issue":"D1","key":"pcbi.1011623.ref038","doi-asserted-by":"crossref","first-page":"D605","DOI":"10.1093\/nar\/gkaa1074","article-title":"The STRING database in 2021: customizable protein\u2013protein networks, and functional characterization of user-uploaded gene\/measurement sets","volume":"49","author":"D Szklarczyk","year":"2021","journal-title":"Nucleic acids research"},{"issue":"8","key":"pcbi.1011623.ref039","doi-asserted-by":"crossref","first-page":"R173","DOI":"10.1016\/S0969-2126(99)80112-9","article-title":"Protein folding in a specialized compartment: the endoplasmic reticulum","volume":"7","author":"A Zapun","year":"1999","journal-title":"Structure"},{"issue":"6","key":"pcbi.1011623.ref040","doi-asserted-by":"crossref","first-page":"e1006104","DOI":"10.1371\/journal.pgen.1006104","article-title":"The Drosophila ETV5 homologue Ets96B: molecular link between obesity and bipolar disorder","volume":"12","author":"MJ Williams","year":"2016","journal-title":"PLoS genetics"},{"issue":"23","key":"pcbi.1011623.ref041","doi-asserted-by":"crossref","first-page":"2890","DOI":"10.1091\/mbc.E19-08-0434","article-title":"ER membrane protein complex is required for the insertions of late-synthesized transmembrane helices of Rh1 in Drosophila photoreceptors","volume":"30","author":"N Hiramatsu","year":"2019","journal-title":"Molecular biology of the cell"},{"issue":"20","key":"pcbi.1011623.ref042","doi-asserted-by":"crossref","first-page":"11723","DOI":"10.1073\/pnas.1934748100","article-title":"Cytosol-endoplasmic reticulum interplay by Sec61\u03b1; translocon in polyglutamine-mediated neurotoxicity in Drosophila","volume":"100","author":"H Kanuka","year":"2003","journal-title":"Proceedings of the National Academy of Sciences"},{"issue":"3","key":"pcbi.1011623.ref043","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.bbagen.2005.06.020","article-title":"Gain-of-function screen identifies a role of the Sec61\u03b1 translocon in Drosophila postmitotic neurotoxicity","volume":"1726","author":"H Kanuka","year":"2005","journal-title":"Biochimica et Biophysica Acta (BBA)\u2014General Subjects"},{"issue":"3","key":"pcbi.1011623.ref044","doi-asserted-by":"crossref","first-page":"359","DOI":"10.1016\/S1534-5807(03)00059-5","article-title":"Cell cycle withdrawal, progression, and cell survival regulation by EGFR and its 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receptor signaling pathway","volume":"128","author":"J Bai","year":"2001","journal-title":"Development"},{"issue":"5","key":"pcbi.1011623.ref048","doi-asserted-by":"crossref","first-page":"1606","DOI":"10.1128\/MCB.01567-07","article-title":"Deubiquitylating enzyme UBP64 controls cell fate through stabilization of the transcriptional repressor tramtrack","volume":"28","author":"PK Bajpe","year":"2008","journal-title":"Molecular and cellular biology"},{"issue":"3","key":"pcbi.1011623.ref049","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/S0092-8674(00)80507-3","article-title":"Photoreceptor cell differentiation requires regulated proteolysis of the transcriptional repressor Tramtrack","volume":"90","author":"S Li","year":"1997","journal-title":"Cell"},{"issue":"2","key":"pcbi.1011623.ref050","doi-asserted-by":"crossref","first-page":"1076","DOI":"10.1074\/jbc.M707765200","article-title":"Two modes of degradation of the tramtrack transcription factors by Siah homologues","volume":"283","author":"SE Cooper","year":"2008","journal-title":"Journal of Biological Chemistry"},{"issue":"3","key":"pcbi.1011623.ref051","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1016\/S0092-8674(00)80506-1","article-title":"PHYL acts to down-regulate TTK88, a transcriptional repressor of neuronal cell fates, by a SINA-dependent mechanism","volume":"90","author":"AH Tang","year":"1997","journal-title":"Cell"},{"issue":"1","key":"pcbi.1011623.ref052","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1016\/j.stemcr.2017.11.014","article-title":"A phyllopod-mediated feedback loop promotes intestinal stem cell enteroendocrine commitment in Drosophila","volume":"10","author":"C Yin","year":"2018","journal-title":"Stem Cell Reports"},{"issue":"17","key":"pcbi.1011623.ref053","first-page":"3145","article-title":"Genome-wide identification of Grainy head targets in Drosophila reveals regulatory interactions with the POU domain transcription factor Vvl","volume":"144","author":"L Yao","year":"2017","journal-title":"Development"},{"issue":"1","key":"pcbi.1011623.ref054","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1128\/MCB.00003-10","article-title":"Differential regulation of transcription through distinct Suppressor of Hairless DNA binding site architectures during Notch signaling in proneural clusters","volume":"31","author":"JW Cave","year":"2011","journal-title":"Molecular and Cellular Biology"},{"issue":"2","key":"pcbi.1011623.ref055","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1016\/j.ydbio.2007.12.034","article-title":"Prepatterning the Drosophila notum: the three genes of the iroquois complex play intrinsically distinct roles","volume":"317","author":"A Ikmi","year":"2008","journal-title":"Developmental biology"},{"issue":"16","key":"pcbi.1011623.ref056","doi-asserted-by":"crossref","first-page":"3448","DOI":"10.1093\/bioinformatics\/bti551","article-title":"BiNGO: a Cytoscape plugin to assess overrepresentation of gene ontology categories in biological networks","volume":"21","author":"S Maere","year":"2005","journal-title":"Bioinformatics"},{"issue":"11","key":"pcbi.1011623.ref057","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: a software environment for integrated models of biomolecular interaction networks","volume":"13","author":"P Shannon","year":"2003","journal-title":"Genome research"},{"key":"pcbi.1011623.ref058","unstructured":"Ying Z, Bourgeois D, You J, Zitnik M, Leskovec J. GNNExplainer: Generating Explanations for Graph Neural Networks. In: Wallach HM, Larochelle H, Beygelzimer A, d\u2019Alch\u00e9-Buc F, Fox EB, Garnett R, editors. Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, NeurIPS 2019, December 8-14, 2019, Vancouver, BC, Canada; 2019. p. 9240\u20139251."},{"issue":"3","key":"pcbi.1011623.ref059","doi-asserted-by":"crossref","first-page":"5920","DOI":"10.3390\/ijms14035920","article-title":"Functions and Mechanisms of Fibroblast Growth Factor (FGF) Signalling in Drosophila melanogaster","volume":"14","author":"V Muha","year":"2013","journal-title":"International Journal of Molecular Sciences"},{"issue":"300","key":"pcbi.1011623.ref060","doi-asserted-by":"crossref","first-page":"ra96","DOI":"10.1126\/scisignal.2004651","article-title":"Antagonistic Feedback Loops Involving Rau and Sprouty in the Drosophila Eye Control Neuronal and Glial Differentiation","volume":"6","author":"F Sieglitz","year":"2013","journal-title":"Science Signaling"},{"issue":"6294","key":"pcbi.1011623.ref061","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1126\/science.aaf2403","article-title":"Visualization and analysis of gene expression in tissue sections by spatial transcriptomics","volume":"353","author":"PL St\u00e5hl","year":"2016","journal-title":"Science"},{"issue":"12","key":"pcbi.1011623.ref062","doi-asserted-by":"crossref","first-page":"1794","DOI":"10.1038\/s41587-022-01483-z","article-title":"High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging","volume":"40","author":"S He","year":"2022","journal-title":"Nature Biotechnology"},{"issue":"6601","key":"pcbi.1011623.ref063","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1126\/science.abm1741","article-title":"Conservation and divergence of cortical cell organization in human and mouse revealed by MERFISH","volume":"377","author":"R Fang","year":"2022","journal-title":"Science"},{"key":"pcbi.1011623.ref064","article-title":"Identification of genetic modifiers of TDP-43 neurotoxicity in Drosophila","volume":"8","author":"Z Lihong","year":"2013","journal-title":"PloS one"},{"key":"pcbi.1011623.ref065","article-title":"Rs1h- \/y exon 3-del rat model of X-linked retinoschisis with early onset and rapid phenotype is rescued by RS1 supplementation","author":"H Zeng","year":"2021","journal-title":"Gene Therapy"},{"key":"pcbi.1011623.ref066","article-title":"Clinical and genetic features of retinoschisis in 120 families with RS1 mutations","author":"S Xiao","year":"2021","journal-title":"British Journal of Ophthalmology"}],"updated-by":[{"DOI":"10.1371\/journal.pcbi.1011623","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2023,11,20]],"date-time":"2023-11-20T00:00:00Z","timestamp":1700438400000}}],"container-title":["PLOS Computational Biology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011623","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,1]],"date-time":"2024-11-01T18:02:50Z","timestamp":1730484170000},"score":1,"resource":{"primary":{"URL":"https:\/\/dx.plos.org\/10.1371\/journal.pcbi.1011623"}},"subtitle":[],"editor":[{"given":"Hatice Ulku","family":"Osmanbeyoglu","sequence":"first","affiliation":[],"role":[{"role":"editor","vocabulary":"crossref"}]}],"short-title":[],"issued":{"date-parts":[[2023,11,8]]},"references-count":66,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2023,11,8]]}},"URL":"https:\/\/doi.org\/10.1371\/journal.pcbi.1011623","relation":{"new_version":[{"id-type":"doi","id":"10.1371\/journal.pcbi.1011623","asserted-by":"object"}]},"ISSN":["1553-7358"],"issn-type":[{"value":"1553-7358","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,8]]}}}