Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs
Song T, Cosatto E, Wang G, Kuang R, Gerstein M, Min M, Warrell J. Predicting spatially resolved gene expression via tissue morphology using adaptive spatial GNNs. Bioinformatics 2024, 40: ii111-ii119. PMID: 39230702, PMCID: PMC11373608, DOI: 10.1093/bioinformatics/btae383.Peer-Reviewed Original ResearchConceptsGene expressionSpatial gene expressionSpatial transcriptomics technologiesTissue histology imagesExpressed genesGene activationTranscriptomic technologiesMolecular underpinningsGraph neural networksState-of-the-artSpatial expressionGenesTissue architectureExpressionHistological imagesNeural networkSingle-cell multi-cohort dissection of the schizophrenia transcriptome
Ruzicka W, Mohammadi S, Fullard J, Davila-Velderrain J, Subburaju S, Tso D, Hourihan M, Jiang S, Lee H, Bendl J, Voloudakis G, Haroutunian V, Hoffman G, Roussos P, Kellis M, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Berretta S, Bharadwaj R, Bhattacharya A, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clarke D, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Galani K, Galeev T, Gandal M, Gaynor S, Gerstein M, Geschwind D, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Huang Y, Huuki-Myers L, Hwang A, Hyde T, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu C, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Margolis M, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollard K, Pollen A, Pratt H, Przytycki P, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Rozowsky J, Ruth M, Sanders S, Schneider J, Scuderi S, Sebra R, Sestan N, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Weinberger D, Wen C, Weng Z, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. Single-cell multi-cohort dissection of the schizophrenia transcriptome. Science 2024, 384: eadg5136. PMID: 38781388, DOI: 10.1126/science.adg5136.Peer-Reviewed Original ResearchConceptsGenetic risk factorsRisk factorsTranscriptional changesHeterogeneity of schizophreniaNeuronal cell statesSchizophrenia pathophysiologySingle-cell dissectionExcitatory neuronsEffective therapySchizophrenia transcriptomicsCortical cytoarchitectureSingle-cell atlasGenomic variantsCell groupsHuman prefrontal cortexMolecular pathwaysSchizophreniaTranscriptional alterationsTranscriptomic changesPrefrontal cortexCell statesAlterationsTherapyPathophysiologyDissectionA data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex
Huuki-Myers L, Spangler A, Eagles N, Montgomery K, Kwon S, Guo B, Grant-Peters M, Divecha H, Tippani M, Sriworarat C, Nguyen A, Ravichandran P, Tran M, Seyedian A, Hyde T, Kleinman J, Battle A, Page S, Ryten M, Hicks S, Martinowich K, Collado-Torres L, Maynard K, Akbarian S, Abyzov A, Ahituv N, Arasappan D, Almagro Armenteros J, Beliveau B, Bendl J, Berretta S, Bharadwaj R, Bhattacharya A, Bicks L, Brennand K, Capauto D, Champagne F, Chatterjee T, Chatzinakos C, Chen Y, Chen H, Cheng Y, Cheng L, Chess A, Chien J, Chu Z, Clarke D, Clement A, Collado-Torres L, Cooper G, Crawford G, Dai R, Daskalakis N, Davila-Velderrain J, Deep-Soboslay A, Deng C, DiPietro C, Dracheva S, Drusinsky S, Duan Z, Duong D, Dursun C, Eagles N, Edelstein J, Emani P, Fullard J, Galani K, Galeev T, Gandal M, Gaynor S, Gerstein M, Geschwind D, Girdhar K, Goes F, Greenleaf W, Grundman J, Guo H, Guo Q, Gupta C, Hadas Y, Hallmayer J, Han X, Haroutunian V, Hawken N, He C, Henry E, Hicks S, Ho M, Ho L, Hoffman G, Huang Y, Huuki-Myers L, Hwang A, Hyde T, Iatrou A, Inoue F, Jajoo A, Jensen M, Jiang L, Jin P, Jin T, Jops C, Jourdon A, Kawaguchi R, Kellis M, Kleinman J, Kleopoulos S, Kozlenkov A, Kriegstein A, Kundaje A, Kundu S, Lee C, Lee D, Li J, Li M, Lin X, Liu S, Liu J, Liu J, Liu C, Liu S, Lou S, Loupe J, Lu D, Ma S, Ma L, Margolis M, Mariani J, Martinowich K, Maynard K, Mazariegos S, Meng R, Myers R, Micallef C, Mikhailova T, Ming G, Mohammadi S, Monte E, Montgomery K, Moore J, Moran J, Mukamel E, Nairn A, Nemeroff C, Ni P, Norton S, Nowakowski T, Omberg L, Page S, Park S, Patowary A, Pattni R, Pertea G, Peters M, Phalke N, Pinto D, Pjanic M, Pochareddy S, Pollard K, Pollen A, Pratt H, Przytycki P, Purmann C, Qin Z, Qu P, Quintero D, Raj T, Rajagopalan A, Reach S, Reimonn T, Ressler K, Ross D, Roussos P, Rozowsky J, Ruth M, Ruzicka W, Sanders S, Schneider J, Scuderi S, Sebra R, Sestan N, Seyfried N, Shao Z, Shedd N, Shieh A, Shin J, Skarica M, Snijders C, Song H, State M, Stein J, Steyert M, Subburaju S, Sudhof T, Snyder M, Tao R, Therrien K, Tsai L, Urban A, Vaccarino F, van Bakel H, Vo D, Voloudakis G, Wamsley B, Wang T, Wang S, Wang D, Wang Y, Warrell J, Wei Y, Weimer A, Weinberger D, Wen C, Weng Z, Whalen S, White K, Willsey A, Won H, Wong W, Wu H, Wu F, Wuchty S, Wylie D, Xu S, Yap C, Zeng B, Zhang P, Zhang C, Zhang B, Zhang J, Zhang Y, Zhou X, Ziffra R, Zeier Z, Zintel T. A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex. Science 2024, 384: eadh1938. PMID: 38781370, PMCID: PMC11398705, DOI: 10.1126/science.adh1938.Peer-Reviewed Original ResearchConceptsRNA sequencing dataCell type compositionGene expression platformSpatial transcriptomics technologiesAnterior-posterior axisCell-cell interactionsTranscriptome mapExpression platformHuman dorsolateral prefrontal cortexTranscriptomic technologiesSingle-cellCell typesPrefrontal cortexMolecular organizationDorsolateral prefrontal cortexHuman prefrontal cortex