2023
Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings
Hicks E, Seah C, Cote A, Marchese S, Brennand K, Nestler E, Girgenti M, Huckins L. Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings. Translational Psychiatry 2023, 13: 129. PMID: 37076454, PMCID: PMC10115809, DOI: 10.1038/s41398-023-02412-7.Peer-Reviewed Original ResearchMeSH KeywordsBrainComputational BiologyDepressive Disorder, MajorGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansTranscriptomeConceptsBioinformatics approachTranscriptomic dataBrain transcriptomeGenome-wide analysisDynamic transcriptional landscapeBrain gene expression dataGene expression dataTranscriptional landscapeTranscriptomic studiesIntegrating GeneticExpression dataPhenotypic signaturesGenomic driversTranscriptomeMajor depressive disorderValuable resourceRecent findingsEnvironmental influencesTranscriptomicsDepressive disorderGeneticsMultiple approachesPathophysiology of depressionSignaturesDysregulation
2021
Analysis framework and experimental design for evaluating synergy-driving gene expression
Schrode N, Seah C, Deans P, Hoffman G, Brennand K. Analysis framework and experimental design for evaluating synergy-driving gene expression. Nature Protocols 2021, 16: 812-840. PMID: 33432232, PMCID: PMC8609447, DOI: 10.1038/s41596-020-00436-7.Peer-Reviewed Original ResearchConceptsRaw read countsPluripotent stem cell-derived neuronsRNA sequencing experimentsRNA sequencing datasetsStem cell-derived neuronsDifferential expression analysisCell-derived neuronsComplex genetic disorderNon-additive interactionsGenetic risk variantsChemical perturbagensBioinformatics skillsExpression analysisSequencing datasetsGene expressionTranscriptomic effectsSequencing experimentsComputational pipelineRead countsRisk variantsCareful experimental designCombinatorial manipulationGenetic variantsComplex diseasesPerturbation studies
2017
An Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells
Julia T, Wang M, Pimenova A, Bowles K, Hartley B, Lacin E, Machlovi S, Abdelaal R, Karch C, Phatnani H, Slesinger P, Zhang B, Goate A, Brennand K. An Efficient Platform for Astrocyte Differentiation from Human Induced Pluripotent Stem Cells. Stem Cell Reports 2017, 9: 600-614. PMID: 28757165, PMCID: PMC5550034, DOI: 10.1016/j.stemcr.2017.06.018.Peer-Reviewed Original ResearchMEF2C transcription factor is associated with the genetic and epigenetic risk architecture of schizophrenia and improves cognition in mice
Mitchell A, Javidfar B, Pothula V, Ibi D, Shen E, Peter C, Bicks L, Fehr T, Jiang Y, Brennand K, Neve R, Gonzalez-Maeso J, Akbarian S. MEF2C transcription factor is associated with the genetic and epigenetic risk architecture of schizophrenia and improves cognition in mice. Molecular Psychiatry 2017, 23: 123-132. PMID: 28115742, PMCID: PMC5966823, DOI: 10.1038/mp.2016.254.Peer-Reviewed Original ResearchMeSH KeywordsAnimalsBrainChromatin ImmunoprecipitationCognition DisordersComputational BiologyDisease Models, AnimalEpigenomicsGene Expression RegulationGreen Fluorescent ProteinsHistonesMEF2 Transcription FactorsMiceMice, Inbred C57BLMice, KnockoutNerve Tissue ProteinsNeuronsPolymorphism, Single NucleotideSchizophreniaTransduction, GeneticConceptsTherapeutic potentialPrefrontal projection neuronsNeuron-specific promoterUnexplored therapeutic potentialProjection neuronsDrug challengeDisease casesRelated disordersRisk architecturePrefrontal cortexSchizophreniaSingle nucleotide polymorphismsCognitive performancePsychiatric Genomics ConsortiumNeuronal genomeH3K4 hypermethylationRisk lociCognitive enhancement