Integrative cross-species analysis of GABAergic neuron cell types and their functions in Alzheimer’s disease

[1]  Xiaoqun Wang,et al.  Mouse and human share conserved transcriptional programs for interneuron development , 2021, Science.

[2]  Huanming Yang,et al.  Retina Cell Atlases of Multiple Species and an Online Platform for Retina Cell-Type Markers. , 2021, Journal of genetics and genomics = Yi chuan xue bao.

[3]  Evan Z. Macosko,et al.  Comparative cellular analysis of motor cortex in human, marmoset and mouse , 2021, Nature.

[4]  B. Roska,et al.  Partial recovery of visual function in a blind patient after optogenetic therapy , 2021, Nature Medicine.

[5]  Ping Liu,et al.  A high-resolution cell atlas of the domestic pig lung and an online platform for exploring lung single-cell data. , 2021, Journal of genetics and genomics = Yi chuan xue bao.

[6]  Sterling C. Johnson,et al.  Four distinct trajectories of tau deposition identified in Alzheimer’s disease , 2021, Nature Medicine.

[7]  Xun Xu,et al.  Single-cell atlas of domestic pig cerebral cortex and hypothalamus. , 2021, Science bulletin.

[8]  Guoji Guo,et al.  Tracing cell-type evolution by cross-species comparison of cell atlases. , 2021, Cell reports.

[9]  Jin-hai Tang,et al.  Integrative analyses of scRNA-seq and scATAC-seq reveal CXCL14 as a key regulator of lymph node metastasis in breast cancer. , 2021, Human molecular genetics.

[10]  D. Pollock,et al.  Amalgamated cross-species transcriptomes reveal organ-specific propensity in gene expression evolution , 2020, Nature Communications.

[11]  Y. Saeys,et al.  A scalable SCENIC workflow for single-cell gene regulatory network analysis , 2020, Nature Protocols.

[12]  I. Cobos,et al.  Single-soma transcriptomics of tangle-bearing neurons in Alzheimer’s disease reveals the signatures of tau-associated synaptic dysfunction , 2020, bioRxiv.

[13]  Andrew B Singleton,et al.  The genetic architecture of Parkinson's disease , 2020, The Lancet Neurology.

[14]  Maxim N. Artyomov,et al.  Human and mouse single-nucleus transcriptomics reveal TREM2-dependent and - independent cellular responses in Alzheimer’s disease , 2019, Nature Medicine.

[15]  Yi Zhang,et al.  Cell type-specific transcriptional programs in mouse prefrontal cortex during adolescence and addiction , 2019, Nature Communications.

[16]  S. Pääbo,et al.  Single-cell-resolution transcriptome map of human, chimpanzee, bonobo, and macaque brains , 2019, bioRxiv.

[17]  Concha Bielza,et al.  A community-based transcriptomics classification and nomenclature of neocortical cell types , 2019, Nature Neuroscience.

[18]  Allan R. Jones,et al.  Conserved cell types with divergent features in human versus mouse cortex , 2019, Nature.

[19]  Paul J. Hoffman,et al.  Comprehensive Integration of Single-Cell Data , 2018, Cell.

[20]  Maximilian Haeussler,et al.  Single-cell genomics identifies cell type–specific molecular changes in autism , 2019, Science.

[21]  Timothy J. Hohman,et al.  Genome-wide meta-analysis identifies new loci and functional pathways influencing Alzheimer’s disease risk , 2019, Nature Genetics.

[22]  Trygve E Bakken,et al.  Single-nucleus and single-cell transcriptomes compared in matched cortical cell types , 2018, PloS one.

[23]  Stephan J Sanders,et al.  Integrative functional genomic analysis of human brain development and neuropsychiatric risks , 2018, Science.

[24]  Daniel J. Miller,et al.  Spatiotemporal transcriptomic divergence across human and macaque brain development , 2018, Science.

[25]  J. Tepper,et al.  Heterogeneity and Diversity of Striatal GABAergic Interneurons: Update 2018 , 2018, Front. Neuroanat..

[26]  H. Heyn,et al.  Single-cell transcriptomics unveils gene regulatory network plasticity , 2018, Genome Biology.

[27]  Oscar Marín,et al.  Development and Functional Diversification of Cortical Interneurons , 2018, Neuron.

[28]  Mingfeng Li,et al.  Early emergence of cortical interneuron diversity in the mouse embryo , 2018, Science.

[29]  Z. J. Huang,et al.  Characterizing the replicability of cell types defined by single cell RNA-sequencing data using MetaNeighbor , 2018, Nature Communications.

[30]  S. Aerts,et al.  Mapping gene regulatory networks from single-cell omics data , 2018, Briefings in functional genomics.

[31]  J. Hardy,et al.  Alzheimer's disease , 2018, European journal of neurology.

[32]  Z. J. Huang,et al.  Transcriptional Architecture of Synaptic Communication Delineates GABAergic Neuron Identity , 2017, Cell.

[33]  Jason C. Wester,et al.  Hippocampal GABAergic Inhibitory Interneurons. , 2017, Physiological reviews.

[34]  Q. Deng,et al.  Single-cell RNA sequencing: Technical advancements and biological applications. , 2017, Molecular aspects of medicine.

[35]  J. Aerts,et al.  SCENIC: Single-cell regulatory network inference and clustering , 2017, Nature Methods.

[36]  Gord Fishell,et al.  Genetic and activity-dependent mechanisms underlying interneuron diversity , 2017, Nature Reviews Neuroscience.

[37]  S. Durinck,et al.  Single-cell RNA sequencing identifies distinct mouse medial ganglionic eminence cell types , 2017, Scientific Reports.

[38]  Roland Eils,et al.  Complex heatmaps reveal patterns and correlations in multidimensional genomic data , 2016, Bioinform..

[39]  R. Tremblay,et al.  GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits , 2016, Neuron.

[40]  Allan R. Jones,et al.  Canonical Genetic Signatures of the Adult Human Brain , 2015, Nature Neuroscience.

[41]  J. T. Erichsen,et al.  Enhancer Evolution across 20 Mammalian Species , 2015, Cell.

[42]  Y. Gilad,et al.  Comparative studies of gene expression and the evolution of gene regulation , 2012, Nature Reviews Genetics.

[43]  Guangchuang Yu,et al.  clusterProfiler: an R package for comparing biological themes among gene clusters. , 2012, Omics : a journal of integrative biology.

[44]  A. Draguhn,et al.  GABA Metabolism and Transport: Effects on Synaptic Efficacy , 2012, Neural plasticity.

[45]  Eric H. Davidson,et al.  Evolution of Gene Regulatory Networks Controlling Body Plan Development , 2011, Cell.

[46]  I. Cobos,et al.  Dlx1&2 and Mash1 transcription factors control MGE and CGE patterning and differentiation through parallel and overlapping pathways. , 2009, Cerebral cortex.

[47]  Winnie S. Liang,et al.  Dlx1&2 and Mash1 transcription factors control striatal patterning and differentiation through parallel and overlapping pathways , 2009, The Journal of comparative neurology.

[48]  S. Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[49]  A. McGregor,et al.  Morphological evolution through multiple cis-regulatory mutations at a single gene , 2007, Nature.

[50]  P. Francis.  Genetics of inherited retinal disease. , 2006, Journal of the Royal Society of Medicine.

[51]  C. Bondy,et al.  Expression of Catenin family members CTNNA1, CTNNA2, CTNNB1 and JUP in the primate prefrontal cortex and hippocampus. , 2005, Brain research. Molecular brain research.

[52]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[53]  Santa Jeremy Ono,et al.  Retinal transplantation: progress and problems in clinical application , 2003, Journal of leukocyte biology.

[54]  H. Wickham.  ggplot2 , 2011 .