FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W3045034493> ?p ?o ?g. }

• W3045034493 endingPage "1179.e9" @default.
• W3045034493 startingPage "1160" @default.
• W3045034493 abstract "•Uniform allelic expression of imprinted genes in major forebrain cell types•Cortical cell-type-specific expression levels of imprinted genes•Cell-type-specific transcriptional responses in uniparental chromosome disomy (UPD)•Cortical cell-type-specific phenotype in cells with UPD In mammalian genomes, a subset of genes is regulated by genomic imprinting, resulting in silencing of one parental allele. Imprinting is essential for cerebral cortex development, but prevalence and functional impact in individual cells is unclear. Here, we determined allelic expression in cortical cell types and established a quantitative platform to interrogate imprinting in single cells. We created cells with uniparental chromosome disomy (UPD) containing two copies of either the maternal or the paternal chromosome; hence, imprinted genes will be 2-fold overexpressed or not expressed. By genetic labeling of UPD, we determined cellular phenotypes and transcriptional responses to deregulated imprinted gene expression at unprecedented single-cell resolution. We discovered an unexpected degree of cell-type specificity and a novel function of imprinting in the regulation of cortical astrocyte survival. More generally, our results suggest functional relevance of imprinted gene expression in glial astrocyte lineage and thus for generating cortical cell-type diversity. In mammalian genomes, a subset of genes is regulated by genomic imprinting, resulting in silencing of one parental allele. Imprinting is essential for cerebral cortex development, but prevalence and functional impact in individual cells is unclear. Here, we determined allelic expression in cortical cell types and established a quantitative platform to interrogate imprinting in single cells. We created cells with uniparental chromosome disomy (UPD) containing two copies of either the maternal or the paternal chromosome; hence, imprinted genes will be 2-fold overexpressed or not expressed. By genetic labeling of UPD, we determined cellular phenotypes and transcriptional responses to deregulated imprinted gene expression at unprecedented single-cell resolution. We discovered an unexpected degree of cell-type specificity and a novel function of imprinting in the regulation of cortical astrocyte survival. More generally, our results suggest functional relevance of imprinted gene expression in glial astrocyte lineage and thus for generating cortical cell-type diversity. The cerebral cortex is composed of an extraordinary number of neuronal and glial cell types assembling into cortical circuits that account for cognitive abilities. Remarkable heterogeneity in the cortical cell types has been described (Ecker et al., 2017Ecker J.R. Geschwind D.H. Kriegstein A.R. Ngai J. Osten P. Polioudakis D. Regev A. Sestan N. Wickersham I.R. Zeng H. The BRAIN Initiative Cell Census Consortium: Lessons Learned toward Generating a Comprehensive Brain Cell Atlas.Neuron. 2017; 96: 542-557Abstract Full Text Full Text PDF PubMed Google Scholar; Lein et al., 2017Lein E. Borm L.E. Linnarsson S. The promise of spatial transcriptomics for neuroscience in the era of molecular cell typing.Science. 2017; 358: 64-69Crossref PubMed Scopus (115) Google Scholar; Zeng and Sanes, 2017Zeng H. Sanes J.R. Neuronal cell-type classification: challenges, opportunities and the path forward.Nat. Rev. Neurosci. 2017; 18: 530-546Crossref PubMed Scopus (201) Google Scholar), yet the identity of neuronal classes is largely hardwired genetically (Lodato and Arlotta, 2015Lodato S. Arlotta P. Generating neuronal diversity in the mammalian cerebral cortex.Annu. Rev. Cell Dev. Biol. 2015; 31: 699-720Crossref PubMed Google Scholar). The mechanisms generating cortical cell-type diversity are not well understood. However, efforts employing RNA sequencing (RNA-seq) at the single-cell level indicate that developmentally regulated transcriptional programs play critical roles in establishing the full spectrum of cortical cell fates (Mayer et al., 2018Mayer C. Hafemeister C. Bandler R.C. Machold R. Batista Brito R. Jaglin X. Allaway K. Butler A. Fishell G. Satija R. Developmental diversification of cortical inhibitory interneurons.Nature. 2018; 555: 457-462Crossref PubMed Scopus (111) Google Scholar; Mi et al., 2018Mi D. Li Z. Lim L. Li M. Moissidis M. Yang Y. Gao T. Hu T.X. Pratt T. Price D.J. et al.Early emergence of cortical interneuron diversity in the mouse embryo.Science. 2018; 360: 81-85Crossref PubMed Scopus (72) Google Scholar; Nowakowski et al., 2017Nowakowski T.J. Bhaduri A. Pollen A.A. Alvarado B. Mostajo-Radji M.A. Di Lullo E. Haeussler M. Sandoval-Espinosa C. Liu S.J. Velmeshev D. et al.Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex.Science. 2017; 358: 1318-1323Crossref PubMed Scopus (205) Google Scholar; Telley et al., 2016Telley L. Govindan S. Prados J. Stevant I. Nef S. Dermitzakis E. Dayer A. Jabaudon D. Sequential transcriptional waves direct the differentiation of newborn neurons in the mouse neocortex.Science. 2016; 351: 1443-1446Crossref PubMed Google Scholar, Telley et al., 2019Telley L. Agirman G. Prados J. Amberg N. Fièvre S. Oberst P. Bartolini G. Vitali I. Cadilhac C. Hippenmeyer S. et al.Temporal patterning of apical progenitors and their daughter neurons in the developing neocortex.Science. 2019; 364: eaav2522Crossref PubMed Scopus (50) Google Scholar). The control of precise transcriptional programs establishing cortical cell fates includes epigenetic mechanisms (Amberg et al., 2019Amberg N. Laukoter S. Hippenmeyer S. Epigenetic cues modulating the generation of cell-type diversity in the cerebral cortex.J. Neurochem. 2019; 149: 12-26Crossref PubMed Scopus (2) Google Scholar). For instance, DNA methylation represents a critical epigenetic mark modifying DNA-protein interactions and thus controlling transcriptional states and cellular identity (Albert et al., 2017Albert M. Kalebic N. Florio M. Lakshmanaperumal N. Haffner C. Brandl H. Henry I. Huttner W.B. Epigenome profiling and editing of neocortical progenitor cells during development.EMBO J. 2017; 36: 2642-2658Crossref PubMed Scopus (43) Google Scholar; Gray et al., 2017Gray L.T. Yao Z. Nguyen T.N. Kim T.K. Zeng H. Tasic B. Layer-specific chromatin accessibility landscapes reveal regulatory networks in adult mouse visual cortex.eLife. 2017; 6: e21883Crossref PubMed Scopus (22) Google Scholar; Luo et al., 2017Luo C. Keown C.L. Kurihara L. Zhou J. He Y. Li J. Castanon R. Lucero J. Nery J.R. Sandoval J.P. et al.Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex.Science. 2017; 357: 600-604Crossref PubMed Scopus (146) Google Scholar). Although many DNA methylation regulatory mechanisms involve large-scale and global chromatin modulation, some cues act at highly specific locations. In particular, differential DNA methylation at imprinting control regions serves as a fundamental mechanism of genomic imprinting. Imprinting is an epigenetic phenomenon and results in monoallelic parent-of-origin-specific gene expression (Barlow and Bartolomei, 2014Barlow D.P. Bartolomei M.S. Genomic imprinting in mammals.Cold Spring Harb. Perspect. Biol. 2014; 6: a018382Crossref PubMed Scopus (311) Google Scholar; Ferguson-Smith, 2011Ferguson-Smith A.C. Genomic imprinting: the emergence of an epigenetic paradigm.Nat. Rev. Genet. 2011; 12: 565-575Crossref PubMed Scopus (449) Google Scholar). Thus, certain genes are only expressed from the paternally inherited allele and others are only expressed from the maternally inherited allele. The most characteristic feature of imprinted genes is reflected in their cardinal gene-dosage sensitivity. Whether and how allelic expression, and therefore imprinted gene dosage, is regulated at the single-cell level and whether imprinting contributes mechanistically to the generation of transcriptional and/or phenotypic cell-type diversity are unknown. Although the overall number of imprinted genes is relatively small (<1%) (Tucci et al., 2019Tucci V. Isles A.R. Kelsey G. Ferguson-Smith A.C. Erice Imprinting GroupGenomic Imprinting and Physiological Processes in Mammals.Cell. 2019; 176: 952-965Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar; Williamson et al., 2013Williamson C.M. Blake A. Thomas S. Beechey C.V. Hancock J. Cattanach B.M. Peters J. Mouse Imprinting Data and References. MRC Harwell, 2013http://www.mousebook.org/imprinting-gene-listGoogle Scholar), many imprinted genes are prominently expressed during neural development and in the adult brain (Andergassen et al., 2017Andergassen D. Dotter C.P. Wenzel D. Sigl V. Bammer P.C. Muckenhuber M. Mayer D. Kulinski T.M. Theussl H.C. Penninger J.M. et al.Mapping the mouse Allelome reveals tissue-specific regulation of allelic expression.eLife. 2017; 6: e25125Crossref PubMed Scopus (42) Google Scholar; Babak et al., 2015Babak T. DeVeale B. Tsang E.K. Zhou Y. Li X. Smith K.S. Kukurba K.R. Zhang R. Li J.B. van der Kooy D. et al.Genetic conflict reflected in tissue-specific maps of genomic imprinting in human and mouse.Nat. Genet. 2015; 47: 544-549Crossref PubMed Google Scholar; Perez et al., 2015Perez J.D. Rubinstein N.D. Fernandez D.E. Santoro S.W. Needleman L.A. Ho-Shing O. Choi J.J. Zirlinger M. Chen S.K. Liu J.S. Dulac C. Quantitative and functional interrogation of parent-of-origin allelic expression biases in the brain.eLife. 2015; 4: e07860Crossref PubMed Scopus (32) Google Scholar). The preferential expression of the maternal or the paternal allele of certain genes suggests widespread implications for the development and function of the brain. Indeed, genetic deletion of individual imprinted genes results in various neuronal and behavioral deficits (Perez et al., 2016Perez J.D. Rubinstein N.D. Dulac C. New Perspectives on Genomic Imprinting, an Essential and Multifaceted Mode of Epigenetic Control in the Developing and Adult Brain.Annu. Rev. Neurosci. 2016; 39: 347-384Crossref PubMed Scopus (30) Google Scholar; Peters, 2014Peters J. The role of genomic imprinting in biology and disease: an expanding view.Nat. Rev. Genet. 2014; 15: 517-530Crossref PubMed Scopus (231) Google Scholar; Wilkinson et al., 2007Wilkinson L.S. Davies W. Isles A.R. Genomic imprinting effects on brain development and function.Nat. Rev. Neurosci. 2007; 8: 832-843Crossref PubMed Scopus (250) Google Scholar). However, many phenotypes with loss of imprinted gene function have been analyzed at the whole-animal and/or global tissue level. Thus, the functional role of imprinting, and therefore the regulated expression of imprinted gene dosage, at the individual-cell level is poorly understood (Barlow and Bartolomei, 2014Barlow D.P. Bartolomei M.S. Genomic imprinting in mammals.Cold Spring Harb. Perspect. Biol. 2014; 6: a018382Crossref PubMed Scopus (311) Google Scholar; Chess, 2016Chess A. Monoallelic Gene Expression in Mammals.Annu. Rev. Genet. 2016; 50: 317-327Crossref PubMed Google Scholar; Huang et al., 2018Huang W.C. Bennett K. Gregg C. Epigenetic and Cellular Diversity in the Brain through Allele-Specific Effects.Trends Neurosci. 2018; 41: 925-937Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Perez et al., 2016Perez J.D. Rubinstein N.D. Dulac C. New Perspectives on Genomic Imprinting, an Essential and Multifaceted Mode of Epigenetic Control in the Developing and Adult Brain.Annu. Rev. Neurosci. 2016; 39: 347-384Crossref PubMed Scopus (30) Google Scholar; Tucci et al., 2019Tucci V. Isles A.R. Kelsey G. Ferguson-Smith A.C. Erice Imprinting GroupGenomic Imprinting and Physiological Processes in Mammals.Cell. 2019; 176: 952-965Abstract Full Text Full Text PDF PubMed Scopus (57) Google Scholar). The investigation of genomic imprinting at the organismal level has vastly benefited from the analysis of mice carrying uniparental chromosome disomy (UPD, somatic cells containing either two copies of the maternal or paternal chromosome) (Cattanach and Kirk, 1985Cattanach B.M. Kirk M. Differential activity of maternally and paternally derived chromosome regions in mice.Nature. 1985; 315: 496-498Crossref PubMed Google Scholar; Ferguson-Smith et al., 1991Ferguson-Smith A.C. Cattanach B.M. Barton S.C. Beechey C.V. Surani M.A. Embryological and molecular investigations of parental imprinting on mouse chromosome 7.Nature. 1991; 351: 667-670Crossref PubMed Google Scholar; Schulz et al., 2006Schulz R. Menheniott T.R. Woodfine K. Wood A.J. Choi J.D. Oakey R.J. Chromosome-wide identification of novel imprinted genes using microarrays and uniparental disomies.Nucleic Acids Res. 2006; 34: e88Crossref PubMed Scopus (0) Google Scholar). Because one parental allele is duplicated and the other is not present in cells carrying UPD, imprinted genes are in principle either 2-fold overexpressed or not expressed. Several imprinting phenotypes in mice, as well as certain human disorders, are due to UPD and resulting imbalances of imprinted gene expression (Peters, 2014Peters J. The role of genomic imprinting in biology and disease: an expanding view.Nat. Rev. Genet. 2014; 15: 517-530Crossref PubMed Scopus (231) Google Scholar; Yamazawa et al., 2010Yamazawa K. Ogata T. Ferguson-Smith A.C. Uniparental disomy and human disease: an overview.Am. J. Med. Genet. C. Semin. Med. Genet. 2010; 154C: 329-334Crossref PubMed Scopus (98) Google Scholar). Two prominent examples affecting the brain include Prader-Willi and Angelman syndromes (Buiting et al., 2016Buiting K. Williams C. Horsthemke B. Angelman syndrome—insights into a rare neurogenetic disorder.Nat. Rev. Neurol. 2016; 12: 584-593Crossref PubMed Scopus (110) Google Scholar; Horsthemke and Wagstaff, 2008Horsthemke B. Wagstaff J. Mechanisms of imprinting of the Prader-Willi/Angelman region.Am. J. Med. Genet. A. 2008; 146A: 2041-2052Crossref PubMed Scopus (0) Google Scholar; Mabb et al., 2011Mabb A.M. Judson M.C. Zylka M.J. Philpot B.D. Angelman syndrome: insights into genomic imprinting and neurodevelopmental phenotypes.Trends Neurosci. 2011; 34: 293-303Abstract Full Text Full Text PDF PubMed Scopus (167) Google Scholar). Cell-type-specific and/or allelic expression strength of imprinted genes could contribute to overall phenotype and clinical manifestation in conditions with deregulated imprinted gene expression in UPD (Buiting et al., 2016Buiting K. Williams C. Horsthemke B. Angelman syndrome—insights into a rare neurogenetic disorder.Nat. Rev. Neurol. 2016; 12: 584-593Crossref PubMed Scopus (110) Google Scholar; Cassidy and Driscoll, 2009Cassidy S.B. Driscoll D.J. Prader-Willi syndrome.Eur. J. Hum. Genet. 2009; 17: 3-13Crossref PubMed Scopus (383) Google Scholar; Horsthemke and Wagstaff, 2008Horsthemke B. Wagstaff J. Mechanisms of imprinting of the Prader-Willi/Angelman region.Am. J. Med. Genet. A. 2008; 146A: 2041-2052Crossref PubMed Scopus (0) Google Scholar; LaSalle et al., 2015LaSalle J.M. Reiter L.T. Chamberlain S.J. Epigenetic regulation of UBE3A and roles in human neurodevelopmental disorders.Epigenomics. 2015; 7: 1213-1228Crossref PubMed Google Scholar; Mabb et al., 2011Mabb A.M. Judson M.C. Zylka M.J. Philpot B.D. Angelman syndrome: insights into genomic imprinting and neurodevelopmental phenotypes.Trends Neurosci. 2011; 34: 293-303Abstract Full Text Full Text PDF PubMed Scopus (167) Google Scholar). However, the lack of experimental approaches allowing the interrogation and phenotypic analysis upon deregulated imprinted gene expression at the single-cell level has thus far precluded the investigation of cell-type specificity. Here, we first used single-cell RNA sequencing (scRNA-seq) to map and quantitatively assess allelic expression strength in genetically defined major forebrain cell types at single-cell resolution. We then exploited the potential of UPD and established a quantitative assay to probe genomic imprinting at unprecedented single-cell resolution in the developing cortex using MADM (mosaic analysis with double markers) technology (Hippenmeyer et al., 2010Hippenmeyer S. Youn Y.H. Moon H.M. Miyamichi K. Zong H. Wynshaw-Boris A. Luo L. Genetic mosaic dissection of Lis1 and Ndel1 in neuronal migration.Neuron. 2010; 68: 695-709Abstract Full Text Full Text PDF PubMed Scopus (120) Google Scholar, Hippenmeyer et al., 2013Hippenmeyer S. Johnson R.L. Luo L. Mosaic analysis with double markers reveals cell-type-specific paternal growth dominance.Cell Rep. 2013; 3: 960-967Abstract Full Text Full Text PDF PubMed Scopus (26) Google Scholar; Zong et al., 2005Zong H. Espinosa J.S. Su H.H. Muzumdar M.D. Luo L. Mosaic analysis with double markers in mice.Cell. 2005; 121: 479-492Abstract Full Text Full Text PDF PubMed Scopus (345) Google Scholar). By capitalizing upon the MADM assay, we determined the prevalence and phenotypic cell-type specificity of imprinted gene dosage in the developing cerebral cortex at the single-cell level. Previous studies have established genome-wide allelic expression maps (allelomes) in many organs and tissues (Andergassen et al., 2017Andergassen D. Dotter C.P. Wenzel D. Sigl V. Bammer P.C. Muckenhuber M. Mayer D. Kulinski T.M. Theussl H.C. Penninger J.M. et al.Mapping the mouse Allelome reveals tissue-specific regulation of allelic expression.eLife. 2017; 6: e25125Crossref PubMed Scopus (42) Google Scholar; Babak et al., 2015Babak T. DeVeale B. Tsang E.K. Zhou Y. Li X. Smith K.S. Kukurba K.R. Zhang R. Li J.B. van der Kooy D. et al.Genetic conflict reflected in tissue-specific maps of genomic imprinting in human and mouse.Nat. Genet. 2015; 47: 544-549Crossref PubMed Google Scholar; Bonthuis et al., 2015Bonthuis P.J. Huang W.C. Stacher Hörndli C.N. Ferris E. Cheng T. Gregg C. Noncanonical Genomic Imprinting Effects in Offspring.Cell Rep. 2015; 12: 979-991Abstract Full Text Full Text PDF PubMed Scopus (38) Google Scholar; Gregg et al., 2010Gregg C. Zhang J. Weissbourd B. Luo S. Schroth G.P. Haig D. Dulac C. High-resolution analysis of parent-of-origin allelic expression in the mouse brain.Science. 2010; 329: 643-648Crossref PubMed Scopus (399) Google Scholar; Perez et al., 2015Perez J.D. Rubinstein N.D. Fernandez D.E. Santoro S.W. Needleman L.A. Ho-Shing O. Choi J.J. Zirlinger M. Chen S.K. Liu J.S. Dulac C. Quantitative and functional interrogation of parent-of-origin allelic expression biases in the brain.eLife. 2015; 4: e07860Crossref PubMed Scopus (32) Google Scholar) using well-established genetic differences (single-nucleotide polymorphisms, SNPs) in the F1 generation of crosses between distinct mouse strains (Figure 1A). These efforts proved extremely useful to identify tissue-specific imprinted gene expression but lacked the cellular resolution to determine cell-type-specific allelic expression. To this end, we set out to first analyze the allelomes of genetically defined cell types compared with whole tissue. We focused on cortical projection neurons, interneurons, and olfactory bulb (OB) granule cells and crossed Emx1- and Nkx2.1-Cre drivers to fluorescent Z/EG and Ai14 reporter lines, respectively, all in the C57BL/6J (B6) genetic background. These B6-Cre/reporter mice were then crossed to CAST/EiJ (CAST) mice with the father in B6 and the mother in CAST (initial cross), or vice versa (reverse cross). We used 2 biological replicates for both crosses (Table S1A; Figure 1A). Next, labeled cells from F1 of the preceding crosses were isolated by fluorescence-activated cell sorting (FACS) followed by RNA-seq and allelic expression analysis using Allelome.PRO (Andergassen et al., 2015Andergassen D. Dotter C.P. Kulinski T.M. Guenzl P.M. Bammer P.C. Barlow D.P. Pauler F.M. Hudson Q.J. Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data.Nucleic Acids Res. 2015; 43: e146PubMed Google Scholar) to determine genome-wide allelic gene expression (Figure 1B). For global imprinted gene identification, we used a false discovery rate (FDR) cutoff of 1% and an allelic expression ratio cutoff of 0.7, indicating a 70/30 ratio of expressed/silent allele (Andergassen et al., 2017Andergassen D. Dotter C.P. Wenzel D. Sigl V. Bammer P.C. Muckenhuber M. Mayer D. Kulinski T.M. Theussl H.C. Penninger J.M. et al.Mapping the mouse Allelome reveals tissue-specific regulation of allelic expression.eLife. 2017; 6: e25125Crossref PubMed Scopus (42) Google Scholar). To refine this definition, we separated genes showing canonical (allelic ratio cutoff of 0.95) and biased (allelic ratio cutoff between 0.95 and 0.7) imprinted expression (Figure 1A). We confirmed cell-type identity in our samples using principal-component analysis (Figure S1A) and marker gene expression (Figure S1B). To identify cell-type-specific differences in imprinted gene expression, we focused our analysis on 25 genes with imprinted expression in embryonic and adult whole mouse brain (Andergassen et al., 2017Andergassen D. Dotter C.P. Wenzel D. Sigl V. Bammer P.C. Muckenhuber M. Mayer D. Kulinski T.M. Theussl H.C. Penninger J.M. et al.Mapping the mouse Allelome reveals tissue-specific regulation of allelic expression.eLife. 2017; 6: e25125Crossref PubMed Scopus (42) Google Scholar; Perez et al., 2015Perez J.D. Rubinstein N.D. Fernandez D.E. Santoro S.W. Needleman L.A. Ho-Shing O. Choi J.J. Zirlinger M. Chen S.K. Liu J.S. Dulac C. Quantitative and functional interrogation of parent-of-origin allelic expression biases in the brain.eLife. 2015; 4: e07860Crossref PubMed Scopus (32) Google Scholar; Figure 1C). Most (20/25, or 80%) showed uniform canonical allelic expression (i.e., no switching of parental allele-specific expression) in all informative cell types, as well as in whole tissue (Figure 1D). We next plotted the allelic maternal expression/paternal expression (mat/pat) ratios for several representative maternally (Rian and Meg3) and paternally (Sgce and Snrpn) expressed imprinted genes (Figure 1E). Only 5/25 genes appeared to show biased imprinted expression (Ago2, Cdkn1c, Grb10, Impact, and Inpp5f). Of these 5 genes, Grb10 is known to switch promoter usage and thus imprinted expression developmentally and cell type specifically (Plasschaert and Bartolomei, 2015Plasschaert R.N. Bartolomei M.S. Tissue-specific regulation and function of Grb10 during growth and neuronal commitment.Proc. Natl. Acad. Sci. USA. 2015; 112: 6841-6847Crossref PubMed Scopus (21) Google Scholar; Yamasaki-Ishizaki et al., 2007Yamasaki-Ishizaki Y. Kayashima T. Mapendano C.K. Soejima H. Ohta T. Masuzaki H. Kinoshita A. Urano T. Yoshiura K. Matsumoto N. et al.Role of DNA methylation and histone H3 lysine 27 methylation in tissue-specific imprinting of mouse Grb10.Mol. Cell. Biol. 2007; 27: 732-742Crossref PubMed Scopus (40) Google Scholar), and Cdkn1c shows almost exclusive imprinted expression with only one cell-type exception (OB, mat/pat ratio of 0.940 and cutoff of 0.95). Next, we investigated Ago2, Impact, and Inpp5f and found marked cell-type-specific variation in the allelic mat/pat ratios, contrasting with canonical imprinted expression (Figure 1E). In summary, most (80%) expressed imprinted genes exhibit canonical imprinting in all major, genetically defined, cortical cell types, with a smaller fraction (20%) showing expression bias. Biased imprinted gene expression can arise either from uniformly skewed expression in all cells within a population or from a major population showing exclusive imprinted expression from one parental allele and a minority population switching parental alleles and showing exclusive expression of the opposite parental allele (Chess, 2016Chess A. Monoallelic Gene Expression in Mammals.Annu. Rev. Genet. 2016; 50: 317-327Crossref PubMed Google Scholar; Huang et al., 2018Huang W.C. Bennett K. Gregg C. Epigenetic and Cellular Diversity in the Brain through Allele-Specific Effects.Trends Neurosci. 2018; 41: 925-937Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar; Perez et al., 2016Perez J.D. Rubinstein N.D. Dulac C. New Perspectives on Genomic Imprinting, an Essential and Multifaceted Mode of Epigenetic Control in the Developing and Adult Brain.Annu. Rev. Neurosci. 2016; 39: 347-384Crossref PubMed Scopus (30) Google Scholar). To discriminate between these possibilities we isolated single cells from the cortical Emx1+ lineage of F1 progeny from B6 and CAST parents, as described earlier, at two developmental time points, postnatal day (P) 0 and P42 using FACS (initial and reverse cross) (Figures 1F and S1C). Next, we performed scRNA-seq using SMARTer technology. Upon quality control, we identified 404 cells from both crosses (223 B6xCAST and 181 CASTxB6; the maternal strain is written on the left). We classified all informative cells into 5 classes using hierarchical clustering of gene expression (Figure 1G; Table S1B; STAR Methods). Clustering did not result in major bias with respect to the direction of B6xCAST cross in any class (Figure S1C). We separated neurons into two groups, with neuron I (NI, nascent projection neurons) and neuron II (NII, mature projection neurons) originating mainly from P0 and P42, respectively (Figure S1C). Astrocyte intermediate progenitor cells (aIPCs) were mainly observed at P0, whereas mature astrocytes (astros) and oligodendrocytes (oligos) were mostly identified at P42 (Figure S1C). Using a modified version of Allelome.PRO, we calculated allelic mat/pat ratios of the 25 known imprinted genes as described earlier and two control (i.e., biallelically expressed) genes (Ncam1 and Fgfr2) (STAR Methods). Our analysis revealed that the parental bias of all investigated imprinted genes was present at the single-cell level (Table S2). Importantly, biased paternal expression of Inpp5f and Impact at the single-cell level was detected in all major cell types (Figure 1H), similar to our observation at the bulk level (Figure 1E). In contrast, almost exclusive expression from the maternal or the paternal allele was detected in each informative cell for selected genes with canonical imprinted expression (maternal, Meg3 and Rian; paternal, Snrpn) (Figure 1H). Highly expressed genes that are not subject to genomic imprinting, e.g., Fgfr2 and Ncam1, were found to be expressed either from both parental alleles (i.e., biallelic, green bar in Figure 1H) or from one of the parental alleles in equal amounts of single cells (red/blue bars in Figure 1H), consistent with the observation and concept of transcriptional bursts (Larsson et al., 2019Larsson A.J.M. Johnsson P. Hagemann-Jensen M. Hartmanis L. Faridani O.R. Reinius B. Segerstolpe Å. Rivera C.M. Ren B. Sandberg R. Genomic encoding of transcriptional burst kinetics.Nature. 2019; 565: 251-254Crossref PubMed Scopus (73) Google Scholar). In summary, we found uniform canonical imprinted gene expression across distinct cell types, which is in contrast to the idea of cell-type-specific variation of biased expression. Both canonical expression and biased expression of the respective analyzed imprinted genes were observed in all different cortical cell types with no detectable allele switching. In the above analysis, we noticed that although relative ratios of allelic expression were rather uniform across cell types, absolute imprinted gene expression levels were not. Extreme examples included Rasgrf1 and Magel2, which were not informative in allelic expression analysis because of low expression in several (i.e., 2–4) cell types (Figure 1C, white boxes). These findings prompted us to comparatively investigate the expression levels of all 25 well-characterized imprinted genes listed earlier in all distinct cortical cell types. We first re-analyzed the bulk RNA-seq data of the preceding B6xCAST crosses (Figure 2A). We plotted the relative expression levels in a heatmap to reveal similarities and differences in expression profiles across specific cortical cell types (Figure 2B). This analysis indicated marked differences in the expression of most analyzed imprinted genes across distinct cell types. We next plotted the normalized read counts of Impact, which shows similar expression levels in all cortical cell types. In contrast, the normalized read counts of Meg3 and Grb10 revealed substantial differences of expression in distinct cortical cell types (Figure 2C). To corroborate these findings, we calculated a cell-type specificity index based on differential gene expression (bulk) (see STAR Methods). This analysis identified progressively increasing but significant cell-type-specific imprinted expression levels for 84% of the investigated 25 imprinted genes (Figure 2D). Next, we analyzed cell-type-specific expression of imprinted genes at the single-cell level and re-analyzed the data from scRNA-seq of the B6xCAST crosses (Figure 2E). Normalized expression of 20 informative imprinted genes, visualized in a heatmap, indicated that even in individual cells, imprinted gene expression varies strongly across distinct cortical cell types (Figure 2F). Furthermore, normalized expression values for three genes—Impact, similar expression, and Meg3 and Grb10, cell-type-specific expression—supported the preceding observation (Figure 2G). Based on the highest fraction of cumulative expression, we calculated a specificity index for single cells (single cell) (see STAR Methods). Strikingly, 13/20 genes showed significant differential expression among the 5 cortical cell types (Figure 2H, indicated with asterisks next to the gene name, Monocle2, adjusted p value (padj) < 0.05). Altogether, we found that imprinted genes with uniform canonical or biased allelic expression exhibit significant variation in absolute expression levels across cortical cell types. The preceding findings show that imprinted gene expression strength varies significantly across distinct cortical cell types. How relevant is the absolute expression of imprinted genes in a particular cell type? To address this question, it is imperative to modulate the expressed dose of imprinted genes in a cell-type-specific" @default.
• W3045034493 created "2020-07-29" @default.
• W3045034493 creator A5007570011 @default.
• W3045034493 creator A5036585037 @default.
• W3045034493 creator A5045127741 @default.
• W3045034493 creator A5048756693 @default.
• W3045034493 creator A5054342456 @default.
• W3045034493 creator A5057673564 @default.
• W3045034493 creator A5059183480 @default.
• W3045034493 creator A5079187712 @default.
• W3045034493 creator A5080499335 @default.
• W3045034493 date "2020-09-01" @default.
• W3045034493 modified "2023-10-13" @default.
• W3045034493 title "Cell-Type Specificity of Genomic Imprinting in Cerebral Cortex" @default.
• W3045034493 cites W1831618129 @default.
• W3045034493 cites W1904875888 @default.
• W3045034493 cites W1934829741 @default.
• W3045034493 cites W1964322942 @default.
• W3045034493 cites W1973485468 @default.
• W3045034493 cites W1978679947 @default.
• W3045034493 cites W1979892065 @default.
• W3045034493 cites W1981849389 @default.
• W3045034493 cites W1984883254 @default.
• W3045034493 cites W1988939568 @default.
• W3045034493 cites W1990155888 @default.
• W3045034493 cites W1990626904 @default.
• W3045034493 cites W1997639239 @default.
• W3045034493 cites W2000761601 @default.
• W3045034493 cites W2000819178 @default.
• W3045034493 cites W2007573212 @default.
• W3045034493 cites W2009940298 @default.
• W3045034493 cites W2020541351 @default.
• W3045034493 cites W2021905453 @default.
• W3045034493 cites W2023887100 @default.
• W3045034493 cites W2027537562 @default.
• W3045034493 cites W2029252550 @default.
• W3045034493 cites W2031215168 @default.
• W3045034493 cites W2032284140 @default.
• W3045034493 cites W2035618305 @default.
• W3045034493 cites W2036895520 @default.
• W3045034493 cites W2044622151 @default.
• W3045034493 cites W2047936342 @default.
• W3045034493 cites W2052721941 @default.
• W3045034493 cites W2053955820 @default.
• W3045034493 cites W2055550188 @default.
• W3045034493 cites W2061062553 @default.
• W3045034493 cites W2061448757 @default.
• W3045034493 cites W2065899830 @default.
• W3045034493 cites W2068767807 @default.
• W3045034493 cites W2071211988 @default.
• W3045034493 cites W2073111188 @default.
• W3045034493 cites W2083813589 @default.
• W3045034493 cites W2085315897 @default.
• W3045034493 cites W2094697218 @default.
• W3045034493 cites W2095027692 @default.
• W3045034493 cites W2102619694 @default.
• W3045034493 cites W2104135721 @default.
• W3045034493 cites W2108234281 @default.
• W3045034493 cites W2109797220 @default.
• W3045034493 cites W2110387447 @default.
• W3045034493 cites W2110427132 @default.
• W3045034493 cites W2113294438 @default.
• W3045034493 cites W2114546997 @default.
• W3045034493 cites W2115833219 @default.
• W3045034493 cites W2122551650 @default.
• W3045034493 cites W2123021448 @default.
• W3045034493 cites W2125522929 @default.
• W3045034493 cites W2137111266 @default.
• W3045034493 cites W2141458291 @default.
• W3045034493 cites W2144824933 @default.
• W3045034493 cites W2146512944 @default.
• W3045034493 cites W2147987903 @default.
• W3045034493 cites W2153218957 @default.
• W3045034493 cites W2155108307 @default.
• W3045034493 cites W2155325698 @default.
• W3045034493 cites W2159675211 @default.
• W3045034493 cites W2162423225 @default.
• W3045034493 cites W2163035954 @default.
• W3045034493 cites W2167757094 @default.
• W3045034493 cites W2169456326 @default.
• W3045034493 cites W2170120898 @default.
• W3045034493 cites W2177136124 @default.
• W3045034493 cites W2179438025 @default.
• W3045034493 cites W2186289814 @default.
• W3045034493 cites W2290583093 @default.
• W3045034493 cites W2292671099 @default.
• W3045034493 cites W2308611819 @default.
• W3045034493 cites W2344468352 @default.
• W3045034493 cites W2489724827 @default.
• W3045034493 cites W2520272104 @default.
• W3045034493 cites W2522022412 @default.
• W3045034493 cites W2522070895 @default.
• W3045034493 cites W2557306380 @default.
• W3045034493 cites W2582412045 @default.
• W3045034493 cites W2586474818 @default.
• W3045034493 cites W2610566370 @default.
• W3045034493 cites W2739665045 @default.
• W3045034493 cites W2744040456 @default.

• next