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Szelenyi ER, Fisenne D, Knox JE, Harris JA, Gornet JA, Palaniswamy R, Kim Y, Venkataraju KU, Osten P. Distributed X chromosome inactivation in brain circuitry is associated with X-linked disease penetrance of behavior. Cell Rep 2024; 43:114068. [PMID: 38614085 PMCID: PMC11107803 DOI: 10.1016/j.celrep.2024.114068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Revised: 02/05/2024] [Accepted: 03/21/2024] [Indexed: 04/15/2024] Open
Abstract
The precise anatomical degree of brain X chromosome inactivation (XCI) that is sufficient to alter X-linked disorders in females is unclear. Here, we quantify whole-brain XCI at single-cell resolution to discover a prevalent activation ratio of maternal to paternal X at 60:40 across all divisions of the adult brain. This modest, non-random XCI influences X-linked disease penetrance: maternal transmission of the fragile X mental retardation 1 (Fmr1)-knockout (KO) allele confers 55% of total brain cells with mutant X-active, which is sufficient for behavioral penetrance, while 40% produced from paternal transmission is tolerated. Local XCI mosaicism within affected maternal Fmr1-KO mice further specifies sensorimotor versus social anxiety phenotypes depending on which distinct brain circuitry is most affected, with only a 50%-55% mutant X-active threshold determining penetrance. Thus, our results define a model of X-linked disease penetrance in females whereby distributed XCI among single cells populating brain circuitries can regulate the behavioral penetrance of an X-linked mutation.
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Affiliation(s)
- Eric R Szelenyi
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Program in Neuroscience, Stony Brook University, Neurobiology and Behavior, Stony Brook, NY 11794, USA.
| | - Danielle Fisenne
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Hofstra University, Hempstead, NY 11549, USA; Certerra, Inc., Farmingdale, NY 11735, USA
| | - Joseph E Knox
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - Julie A Harris
- Allen Institute for Brain Science, Seattle, WA 98109, USA
| | - James A Gornet
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; Columbia University, New York, NY 10027, USA
| | | | - Yongsoo Kim
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA; College of Medicine, Penn State University, Hershey, PA 17033, USA
| | | | - Pavel Osten
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
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2
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Werner JM, Hover J, Gillis J. Population variability in X-chromosome inactivation across 9 mammalian species. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.17.562732. [PMID: 37904929 PMCID: PMC10614859 DOI: 10.1101/2023.10.17.562732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/01/2023]
Abstract
One of the two X chromosomes in female mammals is epigenetically silenced in embryonic stem cells by X chromosome inactivation (XCI). This creates a mosaic of cells expressing either the maternal or the paternal X allele. The XCI ratio, the proportion of inactivated parental alleles, varies widely among individuals, representing the largest instance of epigenetic variability within mammalian populations. While various contributing factors to XCI variability are recognized, namely stochastic and/or genetic effects, their relative contributions are poorly understood. This is due in part to limited cross-species analysis, making it difficult to distinguish between generalizable or species-specific mechanisms for XCI ratio variability. To address this gap, we measured XCI ratios in nine mammalian species (9,143 individual samples), ranging from rodents to primates, and compared the strength of stochastic models or genetic factors for explaining XCI variability. Our results demonstrate the embryonic stochasticity of XCI is a general explanatory model for population XCI variability in mammals, while genetic factors play a minor role.
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Affiliation(s)
- Jonathan M Werner
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - John Hover
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
| | - Jesse Gillis
- Stanley Institute for Cognitive Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY 11724, USA
- Physiology Department and Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, ON, Canada
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3
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Richard Albert J, Kobayashi T, Inoue A, Monteagudo-Sánchez A, Kumamoto S, Takashima T, Miura A, Oikawa M, Miura F, Takada S, Hirabayashi M, Korthauer K, Kurimoto K, Greenberg MVC, Lorincz M, Kobayashi H. Conservation and divergence of canonical and non-canonical imprinting in murids. Genome Biol 2023; 24:48. [PMID: 36918927 PMCID: PMC10012579 DOI: 10.1186/s13059-023-02869-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Accepted: 02/09/2023] [Indexed: 03/15/2023] Open
Abstract
BACKGROUND Genomic imprinting affects gene expression in a parent-of-origin manner and has a profound impact on complex traits including growth and behavior. While the rat is widely used to model human pathophysiology, few imprinted genes have been identified in this murid. To systematically identify imprinted genes and genomic imprints in the rat, we use low input methods for genome-wide analyses of gene expression and DNA methylation to profile embryonic and extraembryonic tissues at allele-specific resolution. RESULTS We identify 14 and 26 imprinted genes in these tissues, respectively, with 10 of these genes imprinted in both tissues. Comparative analyses with mouse reveal that orthologous imprinted gene expression and associated canonical DNA methylation imprints are conserved in the embryo proper of the Muridae family. However, only 3 paternally expressed imprinted genes are conserved in the extraembryonic tissue of murids, all of which are associated with non-canonical H3K27me3 imprints. The discovery of 8 novel non-canonical imprinted genes unique to the rat is consistent with more rapid evolution of extraembryonic imprinting. Meta-analysis of novel imprinted genes reveals multiple mechanisms by which species-specific imprinted expression may be established, including H3K27me3 deposition in the oocyte, the appearance of ZFP57 binding motifs, and the insertion of endogenous retroviral promoters. CONCLUSIONS In summary, we provide an expanded list of imprinted loci in the rat, reveal the extent of conservation of imprinted gene expression, and identify potential mechanisms responsible for the evolution of species-specific imprinting.
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Affiliation(s)
| | - Toshihiro Kobayashi
- Division of Mammalian Embryology, Center for Stem Cell Biology and Regenerative Medicine, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Azusa Inoue
- YCI Laboratory for Metabolic Epigenetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan
| | | | - Soichiro Kumamoto
- NODAI Genome Research Center, Tokyo University of Agriculture, Tokyo, Japan
| | | | - Asuka Miura
- NODAI Genome Research Center, Tokyo University of Agriculture, Tokyo, Japan
| | - Mami Oikawa
- Division of Mammalian Embryology, Center for Stem Cell Biology and Regenerative Medicine, The Institute of Medical Science, The University of Tokyo, Tokyo, Japan
| | - Fumihito Miura
- Department of Biochemistry, Kyushu University Graduate School of Medical Sciences, Fukuoka, Japan
| | - Shuji Takada
- Department of Systems BioMedicine, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Masumi Hirabayashi
- Center for Genetic Analysis of Behavior, National Institute for Physiological Sciences, Okazaki, Japan
| | - Keegan Korthauer
- Department of Statistics, University of British Columbia, Vancouver, Canada.,BC Children's Hospital Research Institute, Vancouver, BC, Canada
| | - Kazuki Kurimoto
- Department of Embryology, Nara Medical University, Nara, Japan
| | | | - Matthew Lorincz
- Department of Medical Genetics, University of British Columbia, Vancouver, Canada
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4
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A long noncoding RNA influences the choice of the X chromosome to be inactivated. Proc Natl Acad Sci U S A 2022; 119:e2118182119. [PMID: 35787055 PMCID: PMC9282422 DOI: 10.1073/pnas.2118182119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
X chromosome inactivation (XCI) is the process of silencing one of the X chromosomes in cells of the female mammal which ensures dosage compensation between the sexes. Although theoretically random in somatic tissues, the choice of which X chromosome is chosen to be inactivated can be biased in mice by genetic element(s) associated with the so-called X-controlling element (Xce). Although the Xce was first described and genetically localized nearly 40 y ago, its mode of action remains elusive. In the approach presented here, we identify a single long noncoding RNA (lncRNA) within the Xce locus, Lppnx, which may be the driving factor in the choice of which X chromosome will be inactivated in the developing female mouse embryo. Comparing weak and strong Xce alleles we show that Lppnx modulates the expression of Xist lncRNA, one of the key factors in XCI, by controlling the occupancy of pluripotency factors at Intron1 of Xist. This effect is counteracted by enhanced binding of Rex1 in DxPas34, another key element in XCI regulating the activity of Tsix lncRNA, the main antagonist of Xist, in the strong but not in the weak Xce allele. These results suggest that the different susceptibility for XCI observed in weak and strong Xce alleles results from differential transcription factor binding of Xist Intron 1 and DxPas34, and that Lppnx represents a decisive factor in explaining the action of the Xce.
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5
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Anderson DJ, Pauler FM, McKenna A, Shendure J, Hippenmeyer S, Horwitz MS. Simultaneous brain cell type and lineage determined by scRNA-seq reveals stereotyped cortical development. Cell Syst 2022; 13:438-453.e5. [PMID: 35452605 DOI: 10.1016/j.cels.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 01/21/2022] [Accepted: 03/30/2022] [Indexed: 11/30/2022]
Abstract
Mutations are acquired frequently, such that each cell's genome inscribes its history of cell divisions. Common genomic alterations involve loss of heterozygosity (LOH). LOH accumulates throughout the genome, offering large encoding capacity for inferring cell lineage. Using only single-cell RNA sequencing (scRNA-seq) of mouse brain cells, we found that LOH events spanning multiple genes are revealed as tracts of monoallelically expressed, constitutionally heterozygous single-nucleotide variants (SNVs). We simultaneously inferred cell lineage and marked developmental time points based on X chromosome inactivation and the total number of LOH events while identifying cell types from gene expression patterns. Our results are consistent with progenitor cells giving rise to multiple cortical cell types through stereotyped expansion and distinct waves of neurogenesis. This type of retrospective analysis could be incorporated into scRNA-seq pipelines and, compared with experimental approaches for determining lineage in model organisms, is applicable where genetic engineering is prohibited, such as humans.
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Affiliation(s)
- Donovan J Anderson
- Allen Discovery Center for Lineage Tracing and Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA 98109, USA
| | - Florian M Pauler
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | | | - Jay Shendure
- Allen Discovery Center for Lineage Tracing, Department of Genome Sciences, and Howard Hughes Medical Institute, University of Washington, Seattle, WA 98109, USA
| | - Simon Hippenmeyer
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Marshall S Horwitz
- Allen Discovery Center for Lineage Tracing and Department of Laboratory Medicine & Pathology, University of Washington, Seattle, WA 98109, USA.
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6
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Lentini A, Cheng H, Noble JC, Papanicolaou N, Coucoravas C, Andrews N, Deng Q, Enge M, Reinius B. Elastic dosage compensation by X-chromosome upregulation. Nat Commun 2022; 13:1854. [PMID: 35388014 PMCID: PMC8987076 DOI: 10.1038/s41467-022-29414-1] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 03/14/2022] [Indexed: 12/24/2022] Open
Abstract
X-chromosome inactivation and X-upregulation are the fundamental modes of chromosome-wide gene regulation that collectively achieve dosage compensation in mammals, but the regulatory link between the two remains elusive and the X-upregulation dynamics are unknown. Here, we use allele-resolved single-cell RNA-seq combined with chromatin accessibility profiling and finely dissect their separate effects on RNA levels during mouse development. Surprisingly, we uncover that X-upregulation elastically tunes expression dosage in a sex- and lineage-specific manner, and moreover along varying degrees of X-inactivation progression. Male blastomeres achieve X-upregulation upon zygotic genome activation while females experience two distinct waves of upregulation, upon imprinted and random X-inactivation; and ablation of Xist impedes female X-upregulation. Female cells carrying two active X chromosomes lack upregulation, yet their collective RNA output exceeds that of a single hyperactive allele. Importantly, this conflicts the conventional dosage compensation model in which naïve female cells are initially subject to biallelic X-upregulation followed by X-inactivation of one allele to correct the X dosage. Together, our study provides key insights to the chain of events of dosage compensation, explaining how transcript copy numbers can remain remarkably stable across developmental windows wherein severe dose imbalance would otherwise be experienced by the cell.
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Affiliation(s)
- Antonio Lentini
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Huaitao Cheng
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - J C Noble
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Natali Papanicolaou
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Christos Coucoravas
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden
| | - Nathanael Andrews
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Qiaolin Deng
- Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Martin Enge
- Department of Oncology and Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Björn Reinius
- Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
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7
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Mechanisms of Choice in X-Chromosome Inactivation. Cells 2022; 11:cells11030535. [PMID: 35159344 PMCID: PMC8833938 DOI: 10.3390/cells11030535] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/30/2022] [Accepted: 01/31/2022] [Indexed: 12/04/2022] Open
Abstract
Early in development, placental and marsupial mammals harbouring at least two X chromosomes per nucleus are faced with a choice that affects the rest of their lives: which of those X chromosomes to transcriptionally inactivate. This choice underlies phenotypical diversity in the composition of tissues and organs and in their response to the environment, and can determine whether an individual will be healthy or affected by an X-linked disease. Here, we review our current understanding of the process of choice during X-chromosome inactivation and its implications, focusing on the strategies evolved by different mammalian lineages and on the known and unknown molecular mechanisms and players involved.
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8
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Andergassen D, Smith ZD, Kretzmer H, Rinn JL, Meissner A. Diverse epigenetic mechanisms maintain parental imprints within the embryonic and extraembryonic lineages. Dev Cell 2021; 56:2995-3005.e4. [PMID: 34752748 DOI: 10.1016/j.devcel.2021.10.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Revised: 08/06/2021] [Accepted: 10/12/2021] [Indexed: 11/20/2022]
Abstract
Genomic imprinting and X chromosome inactivation (XCI) require epigenetic mechanisms to encode allele-specific expression, but how these specific tasks are accomplished at single loci or across chromosomal scales remains incompletely understood. Here, we systematically disrupt essential epigenetic pathways within polymorphic embryos in order to examine canonical and non-canonical genomic imprinting as well as XCI. We find that DNA methylation and Polycomb group repressors are indispensable for autosomal imprinting, albeit at distinct gene sets. Moreover, the extraembryonic ectoderm relies on a broader spectrum of imprinting mechanisms, including non-canonical targeting of maternal endogenous retrovirus (ERV)-driven promoters by the H3K9 methyltransferase G9a. We further identify Polycomb-dependent and -independent gene clusters on the imprinted X chromosome, which appear to reflect distinct domains of Xist-mediated suppression. From our data, we assemble a comprehensive inventory of the epigenetic pathways that maintain parent-specific imprinting in eutherian mammals, including an expanded view of the placental lineage.
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Affiliation(s)
- Daniel Andergassen
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Institute of Pharmacology and Toxicology, Technical University Munich (TUM), Munich 80802, Germany
| | - Zachary D Smith
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Yale Stem Cell Center, Department of Genetics, Yale School of Medicine, New Haven, CT 06519, USA
| | - Helene Kretzmer
- Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin 14195, Germany
| | - John L Rinn
- Department of Biochemistry, University of Colorado Boulder, Boulder 80303, USA
| | - Alexander Meissner
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Department of Genome Regulation, Max Planck Institute for Molecular Genetics, Berlin 14195, Germany; Institute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin 14195, Germany.
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9
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Liang W, Zou X, Li G, Zhou S, Tian C, Schaefke B. Systematic Analysis of Monoallelic Gene Expression and Chromatin Accessibility Across Multiple Tissues in Hybrid Mice. Front Cell Dev Biol 2021; 9:717555. [PMID: 34631706 PMCID: PMC8495204 DOI: 10.3389/fcell.2021.717555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Accepted: 09/01/2021] [Indexed: 11/13/2022] Open
Abstract
In diploid eukaryotic organisms, both alleles of each autosomal gene are usually assumed to be simultaneously expressed at similar levels. However, some genes can be expressed preferentially or strictly from a single allele, a process known as monoallelic expression. Classic monoallelic expression of X-chromosome-linked genes, olfactory receptor genes and developmentally imprinted genes is the result of epigenetic modifications. Genetic-origin-dependent monoallelic expression, however, is caused by cis-regulatory differences between the alleles. There is a paucity of systematic study to investigate these phenomena across multiple tissues, and the mechanisms underlying such monoallelic expression are not yet fully understood. Here we provide a detailed portrait of monoallelic gene expression across multiple tissues/cell lines in a hybrid mouse cross between the Mus musculus strain C57BL/6J and the Mus spretus strain SPRET/EiJ. We observed pervasive tissue-dependent allele-specific gene expression: in total, 1,839 genes exhibited monoallelic expression in at least one tissue, and 410 genes in at least two tissues. Among these 88 are monoallelic genes with different active alleles between tissues, probably representing genetic-origin-dependent monoallelic expression. We also identified six autosomal monoallelic genes with the active allele being identical in all eight tissues, which are likely novel candidates of imprinted genes. To depict the underlying regulatory mechanisms at the chromatin layer, we performed ATAC-seq in two different cell lines derived from the F1 mouse. Consistent with the global expression pattern, cell-type dependent monoallelic peaks were found, and a higher proportion of C57BL/6J-active peaks were observed in both cell types, implying possible species-specific regulation. Finally, only a small part of monoallelic gene expression could be explained by allelic differences in chromatin organization in promoter regions, suggesting that other distal elements may play important roles in shaping the patterns of allelic gene expression across tissues.
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Affiliation(s)
- Weizheng Liang
- Harbin Institute of Technology, Harbin, China
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Xudong Zou
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Guipeng Li
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China
| | - Shaojie Zhou
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Chi Tian
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
| | - Bernhard Schaefke
- Shenzhen Key Laboratory of Gene Regulation and Systems Biology, School of Life Sciences, Southern University of Science and Technology, Shenzhen, China
- Department of Biology, Southern University of Science and Technology, Shenzhen, China
- Academy for Advanced Interdisciplinary Studies, Southern University of Science and Technology, Shenzhen, China
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10
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Takemon Y, Wright V, Davenport B, Gatti DM, Sheehan SM, Letson K, Savage HS, Lennon R, Korstanje R. Uncovering Modifier Genes of X-Linked Alport Syndrome Using a Novel Multiparent Mouse Model. J Am Soc Nephrol 2021; 32:1961-1973. [PMID: 34045313 PMCID: PMC8455275 DOI: 10.1681/asn.2020060777] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 03/27/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Mutations in COL4A5 are responsible for 80% of cases of X-linked Alport Syndrome (XLAS). Although genes that cause AS are well characterized, people with AS who have similar genetic mutations present with a wide variation in the extent of kidney impairment and age of onset, suggesting the activities of modifier genes. METHODS We created a cohort of genetically diverse XLAS male and female mice using the Diversity Outbred mouse resource and measured albuminuria, GFR, and gene expression. Using a quantitative trait locus approach, we mapped modifier genes that can best explain the underlying phenotypic variation measured in our diverse population. RESULTS Genetic analysis identified several loci associated with the variation in albuminuria and GFR, including a locus on the X chromosome associated with X inactivation and a locus on chromosome 2 containing Fmn1. Subsequent analysis of genetically reduced Fmn1 expression in Col4a5 knockout mice showed a decrease in albuminuria, podocyte effacement, and podocyte protrusions in the glomerular basement membrane, which support the candidacy of Fmn1 as a modifier gene for AS. CONCLUSION With this novel approach, we emulated the variability in the severity of kidney phenotypes found in human patients with Alport Syndrome through albuminuria and GFR measurements. This approach can identify modifier genes in kidney disease that can be used as novel therapeutic targets.
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Affiliation(s)
| | | | - Bernard Davenport
- Wellcome Centre for Cell-Matrix Research, Division of Cell-Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | | | | | | | | | - Rachel Lennon
- Wellcome Centre for Cell-Matrix Research, Division of Cell-Matrix Biology and Regenerative Medicine, School of Biological Sciences, Faculty of Biology Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom
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11
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Fernandes C, Paúl A, Venâncio MM, Ramos F. Simpson-Golabi-Behmel syndrome: One family, same mutation, different outcome. Am J Med Genet A 2021; 185:2502-2506. [PMID: 34003580 DOI: 10.1002/ajmg.a.62263] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2020] [Revised: 04/12/2021] [Accepted: 04/24/2021] [Indexed: 11/10/2022]
Abstract
Simpson-Golabi-Behmel syndrome (SGBS) is a rare X-linked condition characterized by pre and postnatal overgrowth with visceral and skeletal abnormalities. The syndrome is caused mainly by mutations in the X-linked gene GPC3. Clinical presentation of SGBS in affected males is well defined, but there is a lack of knowledge about affected females, with very few reported cases. In total, eight female carriers with clinical expression of SGBS have been reported to date. In the present report, we describe the ninth patient and her family history. The interesting features of our female patient are the Wilms' tumor and the transfontanelar ultrasound findings. The patient's older sister, carrier of the same mutation, has minor facial dysmorphisms but no congenital anomalies and so far, no further clinical findings, as well as her mother and grandmother. There is a lesson to be learned from these rare cases, namely that SGBS may have a significant clinical expression in females, and therefore, screening should be considered in all patients with SGBS regardless of the sex or phenotypic severity.
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Affiliation(s)
- Carla Fernandes
- Department of Pediatric Oncology, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Alexandra Paúl
- Department of Pediatric Oncology, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Maria Margarida Venâncio
- Department of Genetics, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Medical Genetics Institute - UC Genomics, Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Fabiana Ramos
- Department of Genetics, Hospital Pediátrico, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
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12
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Sun KY, Oreper D, Schoenrock SA, McMullan R, Giusti-Rodríguez P, Zhabotynsky V, Miller DR, Tarantino LM, Pardo-Manuel de Villena F, Valdar W. Bayesian modeling of skewed X inactivation in genetically diverse mice identifies a novel Xce allele associated with copy number changes. Genetics 2021; 218:6162162. [PMID: 33693696 DOI: 10.1093/genetics/iyab034] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2020] [Accepted: 02/15/2021] [Indexed: 11/13/2022] Open
Abstract
Female mammals are functional mosaics of their parental X-linked gene expression due to X chromosome inactivation (XCI). This process inactivates one copy of the X chromosome in each cell during embryogenesis and that state is maintained clonally through mitosis. In mice, the choice of which parental X chromosome remains active is determined by the X chromosome controlling element (Xce), which has been mapped to a 176-kb candidate interval. A series of functional Xce alleles has been characterized or inferred for classical inbred strains based on biased, or skewed, inactivation of the parental X chromosomes in crosses between strains. To further explore the function structure basis and location of the Xce, we measured allele-specific expression of X-linked genes in a large population of F1 females generated from Collaborative Cross (CC) strains. Using published sequence data and applying a Bayesian "Pólya urn" model of XCI skew, we report two major findings. First, inter-individual variability in XCI suggests mouse epiblasts contain on average 20-30 cells contributing to brain. Second, CC founder strain NOD/ShiLtJ has a novel and unique functional allele, Xceg, that is the weakest in the Xce allelic series. Despite phylogenetic analysis confirming that NOD/ShiLtJ carries a haplotype almost identical to the well-characterized C57BL/6J (Xceb), we observed unexpected patterns of XCI skewing in females carrying the NOD/ShiLtJ haplotype within the Xce. Copy number variation is common at the Xce locus and we conclude that the observed allelic series is a product of independent and recurring duplications shared between weak Xce alleles.
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Affiliation(s)
- Kathie Y Sun
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Bioinformatics and Computational Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Daniel Oreper
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Bioinformatics and Computational Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sarah A Schoenrock
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Neuroscience Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Rachel McMullan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Genetics and Molecular Biology Curriculum, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Paola Giusti-Rodríguez
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Vasyl Zhabotynsky
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Darla R Miller
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lisa M Tarantino
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Division of Pharmacotherapy and Experimental Therapeutics, Eshelman School of Pharmacy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - William Valdar
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.,Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
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13
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Andergassen D, Smith ZD, Lewandowski JP, Gerhardinger C, Meissner A, Rinn JL. In vivo Firre and Dxz4 deletion elucidates roles for autosomal gene regulation. eLife 2019; 8:e47214. [PMID: 31738164 PMCID: PMC6860989 DOI: 10.7554/elife.47214] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2019] [Accepted: 10/30/2019] [Indexed: 12/12/2022] Open
Abstract
Recent evidence has determined that the conserved X chromosome mega-structures controlled by the Firre and Dxz4 loci are not required for X chromosome inactivation (XCI) in cell lines. Here, we examined the in vivo contribution of these loci by generating mice carrying a single or double deletion of Firre and Dxz4. We found that these mutants are viable, fertile and show no defect in random or imprinted XCI. However, the lack of these elements results in many dysregulated genes on autosomes in an organ-specific manner. By comparing the dysregulated genes between the single and double deletion, we identified superloop, megadomain, and Firre locus-dependent gene sets. The largest transcriptional effect was observed in all strains lacking the Firre locus, indicating that this locus is the main driver for these autosomal expression signatures. Collectively, these findings suggest that these X-linked loci are involved in autosomal gene regulation rather than XCI biology.
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Affiliation(s)
- Daniel Andergassen
- Department of Stem Cell and Regenerative BiologyHarvard UniversityCambridgeUnited States
| | - Zachary D Smith
- Department of Stem Cell and Regenerative BiologyHarvard UniversityCambridgeUnited States
| | - Jordan P Lewandowski
- Department of Stem Cell and Regenerative BiologyHarvard UniversityCambridgeUnited States
| | - Chiara Gerhardinger
- Department of Stem Cell and Regenerative BiologyHarvard UniversityCambridgeUnited States
| | - Alexander Meissner
- Department of Stem Cell and Regenerative BiologyHarvard UniversityCambridgeUnited States
- Department of Genome RegulationMax Planck Institute for Molecular GeneticsBerlinGermany
| | - John L Rinn
- Department of BiochemistryUniversity of Colorado BoulderBoulderUnited States
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14
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A Diallel of the Mouse Collaborative Cross Founders Reveals Strong Strain-Specific Maternal Effects on Litter Size. G3-GENES GENOMES GENETICS 2019; 9:1613-1622. [PMID: 30877080 PMCID: PMC6505174 DOI: 10.1534/g3.118.200847] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Reproductive success in the eight founder strains of the Collaborative Cross (CC) was measured using a diallel-mating scheme. Over a 48-month period we generated 4,448 litters, and provided 24,782 weaned pups for use in 16 different published experiments. We identified factors that affect the average litter size in a cross by estimating the overall contribution of parent-of-origin, heterosis, inbred, and epistatic effects using a Bayesian zero-truncated overdispersed Poisson mixed model. The phenotypic variance of litter size has a substantial contribution (82%) from unexplained and environmental sources, but no detectable effect of seasonality. Most of the explained variance was due to additive effects (9.2%) and parental sex (maternal vs. paternal strain; 5.8%), with epistasis accounting for 3.4%. Within the parental effects, the effect of the dam's strain explained more than the sire's strain (13.2% vs. 1.8%), and the dam's strain effects account for 74.2% of total variation explained. Dams from strains C57BL/6J and NOD/ShiLtJ increased the expected litter size by a mean of 1.66 and 1.79 pups, whereas dams from strains WSB/EiJ, PWK/PhJ, and CAST/EiJ reduced expected litter size by a mean of 1.51, 0.81, and 0.90 pups. Finally, there was no strong evidence for strain-specific effects on sex ratio distortion. Overall, these results demonstrate that strains vary substantially in their reproductive ability depending on their genetic background, and that litter size is largely determined by dam's strain rather than sire's strain effects, as expected. This analysis adds to our understanding of factors that influence litter size in mammals, and also helps to explain breeding successes and failures in the extinct lines and surviving CC strains.
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15
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Genome-wide stability of the DNA replication program in single mammalian cells. Nat Genet 2019; 51:529-540. [PMID: 30804559 DOI: 10.1038/s41588-019-0347-5] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2017] [Accepted: 01/09/2019] [Indexed: 11/09/2022]
Abstract
Here, we report a single-cell DNA replication sequencing method, scRepli-seq, a genome-wide methodology that measures copy number differences between replicated and unreplicated DNA. Using scRepli-seq, we demonstrate that replication-domain organization is conserved among individual mouse embryonic stem cells (mESCs). Differentiated mESCs exhibited distinct profiles, which were also conserved among cells. Haplotype-resolved scRepli-seq revealed similar replication profiles of homologous autosomes, while the inactive X chromosome was clearly replicated later than its active counterpart. However, a small degree of cell-to-cell replication-timing heterogeneity was present, which was smallest at the beginning and the end of S phase. In addition, developmentally regulated domains were found to deviate from others and showed a higher degree of heterogeneity, thus suggesting a link to developmental plasticity. Moreover, allelic expression imbalance was found to strongly associate with replication-timing asynchrony. Our results form a foundation for single-cell-level understanding of DNA replication regulation and provide insights into three-dimensional genome organization.
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16
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Johnson T, Keehan M, Harland C, Lopdell T, Spelman RJ, Davis SR, Rosen BD, Smith TPL, Couldrey C. Short communication: Identification of the pseudoautosomal region in the Hereford bovine reference genome assembly ARS-UCD1.2. J Dairy Sci 2019; 102:3254-3258. [PMID: 30712931 DOI: 10.3168/jds.2018-15638] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2018] [Accepted: 12/04/2018] [Indexed: 11/19/2022]
Abstract
In cattle, the X chromosome accounts for approximately 3 and 6% of the genome in bulls and cows, respectively. In spite of the large size of this chromosome, very few studies report analysis of the X chromosome in genome-wide association studies and genomic selection. This lack of genetic interrogation is likely due to the complexities of undertaking these studies given the hemizygous state of some, but not all, of the X chromosome in males. The first step in facilitating analysis of this gene-rich chromosome is to accurately identify coordinates for the pseudoautosomal boundary (PAB) to split the chromosome into a region that may be treated as autosomal sequence (pseudoautosomal region) and a region that requires more complex statistical models. With the recent release of ARS-UCD1.2, a more complete and accurate assembly of the cattle genome than was previously available, it is timely to fine map the PAB for the first time. Here we report the use of SNP chip genotypes, short-read sequences, and long-read sequences to fine map the PAB (X chromosome:133,300,518) and simultaneously determine the neighboring regions of reduced homology and true pseudoautosomal region. These results greatly facilitate the inclusion of the X chromosome in genome-wide association studies, genomic selection, and other genetic analysis undertaken on this reference genome.
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Affiliation(s)
- T Johnson
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - M Keehan
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - C Harland
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - T Lopdell
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - R J Spelman
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - S R Davis
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - B D Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service USDA, Beltsville, MD 20705
| | - T P L Smith
- US Meat Animal Research Center, Agricultural Research Service USDA, Clay Center, NE 68933
| | - C Couldrey
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand.
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17
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Epigenetic and Cellular Diversity in the Brain through Allele-Specific Effects. Trends Neurosci 2018; 41:925-937. [PMID: 30098802 DOI: 10.1016/j.tins.2018.07.005] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 06/29/2018] [Accepted: 07/10/2018] [Indexed: 01/18/2023]
Abstract
The benefits of diploidy are considered to involve masking partially recessive mutations and increasing genetic diversity. Here, we review new studies showing evidence for diverse allele-specific expression and epigenetic states in mammalian brain cells, which suggest that diploidy expands the landscape of gene regulatory and expression programs in cells. Allele-specific expression has been thought to be restricted to a few specific classes of genes. However, new studies show novel genomic imprinting effects that are brain-region-, cell-type- and age-dependent. In addition, novel forms of random monoallelic expression that impact many autosomal genes have been described in vitro and in vivo. We discuss the implications for understanding the benefits of diploidy, and the mechanisms shaping brain development, function, and disease.
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18
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Roy SW. Intragenomic Conflict and Immune Tolerance: Do Selfish X-Linked Alleles Drive Skewed X Chromosome Inactivation? Genome Biol Evol 2018; 10:857-862. [PMID: 29092048 PMCID: PMC5861445 DOI: 10.1093/gbe/evx221] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/29/2017] [Indexed: 12/18/2022] Open
Abstract
In mammalian females, diploid somatic cells contain two X chromosomes, one of which is transcriptionally silenced, in a process termed X chromosome inactivation (XCI). Whereas XCI is largely random in placental females, many women exhibit skewed XCI (SXCI), in which the vast majority cells have the same X chromosome inactivated. SXCI has serious health consequences, associated with conditions ranging from Alzheimer’s to various autoimmune disorders. SXCI is also associated with outcomes of pregnancies, with higher rates of recurrent spontaneous abortion in women with SXCI. Here, I suggest that SXCI could be driven by selfish X-linked alleles. Consistent with the association of SXCI with autoimmunity, I first note the possibility that recurrent spontaneous abortion could reflect immune rejection of fetuses inheriting alleles from the largely silenced maternal X chromosome. Preferential abortion of fetuses carrying silenced X-linked alleles implies a transmission advantage for X-linked alleles on the largely expressed chromosome, which could drive the emergence of X-linked alleles that make the chromosome resistant to XCI. I discuss the evolutionary dynamics, fitness tradeoffs and implications of this hypothesis, and suggest future directions.
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Affiliation(s)
- Scott W Roy
- Department of Biology, San Francisco State University
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19
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Veale AJ, Russell JC, King CM. The genomic ancestry, landscape genetics and invasion history of introduced mice in New Zealand. ROYAL SOCIETY OPEN SCIENCE 2018; 5:170879. [PMID: 29410804 PMCID: PMC5792881 DOI: 10.1098/rsos.170879] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/11/2017] [Accepted: 12/15/2017] [Indexed: 06/07/2023]
Abstract
The house mouse (Mus musculus) provides a fascinating system for studying both the genomic basis of reproductive isolation, and the patterns of human-mediated dispersal. New Zealand has a complex history of mouse invasions, and the living descendants of these invaders have genetic ancestry from all three subspecies, although most are primarily descended from M. m. domesticus. We used the GigaMUGA genotyping array (approximately 135 000 loci) to describe the genomic ancestry of 161 mice, sampled from 34 locations from across New Zealand (and one Australian city-Sydney). Of these, two populations, one in the south of the South Island, and one on Chatham Island, showed complete mitochondrial lineage capture, featuring two different lineages of M. m. castaneus mitochondrial DNA but with only M. m. domesticus nuclear ancestry detectable. Mice in the northern and southern parts of the North Island had small traces (approx. 2-3%) of M. m. castaneus nuclear ancestry, and mice in the upper South Island had approximately 7-8% M. m. musculus nuclear ancestry including some Y-chromosomal ancestry-though no detectable M. m. musculus mitochondrial ancestry. This is the most thorough genomic study of introduced populations of house mice yet conducted, and will have relevance to studies of the isolation mechanisms separating subspecies of mice.
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Affiliation(s)
- Andrew J. Veale
- Department of Environmental and Animal Sciences, Unitec, 139 Carrington Road, Auckland 1025, New Zealand
| | - James C. Russell
- School of Biological Sciences, University of Auckland, Private Bag 92019, Auckland Mail Centre, Auckland 1142, New Zealand
| | - Carolyn M. King
- Environmental Research Institute, School of Science, University of Waikato, Private Bag 2105, Hamilton 3240, New Zealand
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20
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Andergassen D, Dotter CP, Wenzel D, Sigl V, Bammer PC, Muckenhuber M, Mayer D, Kulinski TM, Theussl HC, Penninger JM, Bock C, Barlow DP, Pauler FM, Hudson QJ. Mapping the mouse Allelome reveals tissue-specific regulation of allelic expression. eLife 2017; 6. [PMID: 28806168 PMCID: PMC5555720 DOI: 10.7554/elife.25125] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 06/14/2017] [Indexed: 01/02/2023] Open
Abstract
To determine the dynamics of allelic-specific expression during mouse development, we analyzed RNA-seq data from 23 F1 tissues from different developmental stages, including 19 female tissues allowing X chromosome inactivation (XCI) escapers to also be detected. We demonstrate that allelic expression arising from genetic or epigenetic differences is highly tissue-specific. We find that tissue-specific strain-biased gene expression may be regulated by tissue-specific enhancers or by post-transcriptional differences in stability between the alleles. We also find that escape from X-inactivation is tissue-specific, with leg muscle showing an unexpectedly high rate of XCI escapers. By surveying a range of tissues during development, and performing extensive validation, we are able to provide a high confidence list of mouse imprinted genes including 18 novel genes. This shows that cluster size varies dynamically during development and can be substantially larger than previously thought, with the Igf2r cluster extending over 10 Mb in placenta. DOI:http://dx.doi.org/10.7554/eLife.25125.001
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Affiliation(s)
- Daniel Andergassen
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Christoph P Dotter
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Daniel Wenzel
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
| | - Verena Sigl
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
| | - Philipp C Bammer
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Markus Muckenhuber
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Daniela Mayer
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Tomasz M Kulinski
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | | | - Josef M Penninger
- IMBA, Institute of Molecular Biotechnology of the Austrian Academy of Sciences, Vienna, Austria
| | - Christoph Bock
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Denise P Barlow
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Florian M Pauler
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
| | - Quanah J Hudson
- CeMM, Research Center for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria
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21
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Couldrey C, Johnson T, Lopdell T, Zhang IL, Littlejohn MD, Keehan M, Sherlock RG, Tiplady K, Scott A, Davis SR, Spelman RJ. Bovine mammary gland X chromosome inactivation. J Dairy Sci 2017; 100:5491-5500. [PMID: 28477999 DOI: 10.3168/jds.2016-12490] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2016] [Accepted: 03/15/2017] [Indexed: 11/19/2022]
Abstract
X chromosome inactivation (XCI) is a process by which 1 of the 2 copies of the X chromosomes present in female mammals is inactivated. The transcriptional silencing of one X chromosome achieves dosage compensation between XX females and XY males and ensures equal expression of X-linked genes in both sexes. Although all mammals use this form of dosage compensation, the complex mechanisms that regulate XCI vary between species, tissues, and development. These mechanisms include not only varying levels of inactivation, but also the nature of inactivation, which can range from being random in nature to driven by parent of origin. To date, no data describing XCI in calves or adult cattle have been reported and we are reliant on data from mice to infer potential mechanisms and timings for this process. In the context of dairy cattle breeding and genomic prediction, the implications of X chromosome inheritance and XCI in the mammary gland are particularly important where a relatively small number of bulls pass their single X chromosome on to all of their daughters. We describe here the use of RNA-seq, whole genome sequencing and Illumina BovineHD BeadChip (Illumina, San Diego, CA) genotypes to assess XCI in lactating mammary glands of dairy cattle. At a population level, maternally and paternally inherited copies of the X chromosome are expressed equally in the lactating mammary gland consistent with random inactivation of the X chromosome. However, average expression of the paternal chromosome ranged from 10 to 90% depending on the individual animal. These results suggest that either the mammary gland arises from 1 or 2 stem cells, or a nongenetic mechanism that skews XCI exists. Although a considerable amount of future work is required to fully understand XCI in cattle, the data reported here represent an initial step in ensuring that X chromosome variation is captured and used in an appropriate manner for future genomic selection.
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Affiliation(s)
- C Couldrey
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand.
| | - T Johnson
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - T Lopdell
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - I L Zhang
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - M D Littlejohn
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - M Keehan
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - R G Sherlock
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - K Tiplady
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - A Scott
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - S R Davis
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
| | - R J Spelman
- Research and Development, Livestock Improvement Corporation, Hamilton 3240, New Zealand
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22
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Whole Genome Sequence of Two Wild-Derived Mus musculus domesticus Inbred Strains, LEWES/EiJ and ZALENDE/EiJ, with Different Diploid Numbers. G3-GENES GENOMES GENETICS 2016; 6:4211-4216. [PMID: 27765810 PMCID: PMC5144988 DOI: 10.1534/g3.116.034751] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Wild-derived mouse inbred strains are becoming increasingly popular for complex traits analysis, evolutionary studies, and systems genetics. Here, we report the whole-genome sequencing of two wild-derived mouse inbred strains, LEWES/EiJ and ZALENDE/EiJ, of Mus musculus domesticus origin. These two inbred strains were selected based on their geographic origin, karyotype, and use in ongoing research. We generated 14× and 18× coverage sequence, respectively, and discovered over 1.1 million novel variants, most of which are private to one of these strains. This report expands the number of wild-derived inbred genomes in the Mus genus from six to eight. The sequence variation can be accessed via an online query tool; variant calls (VCF format) and alignments (BAM format) are available for download from a dedicated ftp site. Finally, the sequencing data have also been stored in a lossless, compressed, and indexed format using the multi-string Burrows-Wheeler transform. All data can be used without restriction.
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23
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Have humans lost control: The elusive X-controlling element. Semin Cell Dev Biol 2016; 56:71-77. [DOI: 10.1016/j.semcdb.2016.01.044] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2015] [Revised: 01/22/2016] [Accepted: 01/28/2016] [Indexed: 02/01/2023]
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24
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Payer B. Developmental regulation of X-chromosome inactivation. Semin Cell Dev Biol 2016; 56:88-99. [PMID: 27112543 DOI: 10.1016/j.semcdb.2016.04.014] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2016] [Revised: 04/13/2016] [Accepted: 04/21/2016] [Indexed: 12/01/2022]
Abstract
With the emergence of sex-determination by sex chromosomes, which differ in composition and number between males and females, appeared the need to equalize X-chromosomal gene dosage between the sexes. Mammals have devised the strategy of X-chromosome inactivation (XCI), in which one of the two X-chromosomes is rendered transcriptionally silent in females. In the mouse, the best-studied model organism with respect to XCI, this inactivation process occurs in different forms, imprinted and random, interspersed by periods of X-chromosome reactivation (XCR), which is needed to switch between the different modes of XCI. In this review, I describe the recent advances with respect to the developmental control of XCI and XCR and in particular their link to differentiation and pluripotency. Furthermore, I review the mechanisms, which influence the timing and choice, with which one of the two X-chromosomes is chosen for inactivation during random XCI. This has an impact on how females are mosaics with regard to which X-chromosome is active in different cells, which has implications on the severity of diseases caused by X-linked mutations.
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Affiliation(s)
- Bernhard Payer
- Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology and Universitat Pompeu Fabra (UPF), Dr. Aiguader, 88, Barcelona 08003, Spain.
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25
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Abstract
Genotyping microarrays are an important resource for genetic mapping, population genetics, and monitoring of the genetic integrity of laboratory stocks. We have developed the third generation of the Mouse Universal Genotyping Array (MUGA) series, GigaMUGA, a 143,259-probe Illumina Infinium II array for the house mouse (Mus musculus). The bulk of the content of GigaMUGA is optimized for genetic mapping in the Collaborative Cross and Diversity Outbred populations, and for substrain-level identification of laboratory mice. In addition to 141,090 single nucleotide polymorphism probes, GigaMUGA contains 2006 probes for copy number concentrated in structurally polymorphic regions of the mouse genome. The performance of the array is characterized in a set of 500 high-quality reference samples spanning laboratory inbred strains, recombinant inbred lines, outbred stocks, and wild-caught mice. GigaMUGA is highly informative across a wide range of genetically diverse samples, from laboratory substrains to other Mus species. In addition to describing the content and performance of the array, we provide detailed probe-level annotation and recommendations for quality control.
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26
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Bonthuis PJ, Huang WC, Stacher Hörndli CN, Ferris E, Cheng T, Gregg C. Noncanonical Genomic Imprinting Effects in Offspring. Cell Rep 2015; 12:979-91. [PMID: 26235621 DOI: 10.1016/j.celrep.2015.07.017] [Citation(s) in RCA: 51] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2014] [Revised: 06/19/2015] [Accepted: 07/08/2015] [Indexed: 12/13/2022] Open
Abstract
Here, we describe an RNA-sequencing (RNA-seq)-based approach that accurately detects even modest maternal or paternal allele expression biases at the tissue level, which we call noncanonical genomic imprinting effects. We profile imprinting in the arcuate nucleus (ARN) and dorsal raphe nucleus of the female mouse brain as well as skeletal muscle (mesodermal) and liver (endodermal). Our study uncovers hundreds of noncanonical autosomal and X-linked imprinting effects. Noncanonical imprinting is highly tissue-specific and enriched in the ARN, but rare in the liver. These effects are reproducible across different genetic backgrounds and associated with allele-specific chromatin. Using in situ hybridization for nascent RNAs, we discover that autosomal noncanonical imprinted genes with a tissue-level allele bias exhibit allele-specific expression effects in subpopulations of neurons in the brain in vivo. We define noncanonical imprinted genes that regulate monoamine signaling and determine that these effects influence the impact of inherited mutations on offspring behavior.
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Affiliation(s)
- Paul J Bonthuis
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA
| | - Wei-Chao Huang
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA
| | - Cornelia N Stacher Hörndli
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA
| | - Elliott Ferris
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA
| | - Tong Cheng
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA
| | - Christopher Gregg
- Department of Neurobiology & Anatomy, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA; Department of Human Genetics, University of Utah School of Medicine, Salt Lake City, UT 84132-3401, USA.
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27
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Andergassen D, Dotter CP, Kulinski TM, Guenzl PM, Bammer PC, Barlow DP, Pauler FM, Hudson QJ. Allelome.PRO, a pipeline to define allele-specific genomic features from high-throughput sequencing data. Nucleic Acids Res 2015. [PMID: 26202974 PMCID: PMC4666383 DOI: 10.1093/nar/gkv727] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Detecting allelic biases from high-throughput sequencing data requires an approach that maximises sensitivity while minimizing false positives. Here, we present Allelome.PRO, an automated user-friendly bioinformatics pipeline, which uses high-throughput sequencing data from reciprocal crosses of two genetically distinct mouse strains to detect allele-specific expression and chromatin modifications. Allelome.PRO extends approaches used in previous studies that exclusively analyzed imprinted expression to give a complete picture of the ‘allelome’ by automatically categorising the allelic expression of all genes in a given cell type into imprinted, strain-biased, biallelic or non-informative. Allelome.PRO offers increased sensitivity to analyze lowly expressed transcripts, together with a robust false discovery rate empirically calculated from variation in the sequencing data. We used RNA-seq data from mouse embryonic fibroblasts from F1 reciprocal crosses to determine a biologically relevant allelic ratio cutoff, and define for the first time an entire allelome. Furthermore, we show that Allelome.PRO detects differential enrichment of H3K4me3 over promoters from ChIP-seq data validating the RNA-seq results. This approach can be easily extended to analyze histone marks of active enhancers, or transcription factor binding sites and therefore provides a powerful tool to identify candidate cis regulatory elements genome wide.
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Affiliation(s)
- Daniel Andergassen
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Christoph P Dotter
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Tomasz M Kulinski
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Philipp M Guenzl
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Philipp C Bammer
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Denise P Barlow
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Florian M Pauler
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
| | - Quanah J Hudson
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, Lazarettgasse 14, AKH BT 25.3,1090 Vienna, Austria
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Massah S, Beischlag TV, Prefontaine GG. Epigenetic events regulating monoallelic gene expression. Crit Rev Biochem Mol Biol 2015; 50:337-58. [PMID: 26155735 DOI: 10.3109/10409238.2015.1064350] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
In mammals, generally it is assumed that the genes inherited from each parent are expressed to similar levels. However, it is now apparent that in non-sex chromosomes, 6-10% of genes are selected for monoallelic expression. Monoallelic expression or allelic exclusion is established either in an imprinted (parent-of-origin) or a stochastic manner. The stochastic model explains random selection while the imprinted model describes parent-of-origin specific selection of alleles for expression. Allelic exclusion occurs during X chromosome inactivation, parent-of-origin expression of imprinted genes and stochastic monoallelic expression of cell surface molecules, clustered protocadherin (PCDH) genes. Mis-regulation or loss of allelic exclusion contributes to developmental diseases. Epigenetic mechanisms are fundamental players that determine this type of expression despite a homogenous genetic background. DNA methylation and histone modifications are two mediators of the epigenetic phenomena. The majority of DNA methylation is found on cytosines of the CpG dinucleotide in mammals. Several covalent modifications of histones change the electrostatic forces between DNA and histones modifying gene expression. Long-range chromatin interactions organize chromatin into transcriptionally permissive and prohibitive regions leading to simultaneous regulation of gene expression and repression. Non-coding RNAs (ncRNAs) are also players in regulating gene expression. Together, these epigenetic mechanisms fine-tune gene expression levels essential for normal development and survival. In this review, first we discuss what is known about monoallelic gene expression. Then, we focus on the molecular mechanisms that regulate expression of three monoallelically expressed gene classes: the X-linked genes, selected imprinted genes and PCDH genes.
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Affiliation(s)
- Shabnam Massah
- a The Faculty of Health Sciences , Simon Fraser University , Burnaby , BC , Canada
| | - Timothy V Beischlag
- a The Faculty of Health Sciences , Simon Fraser University , Burnaby , BC , Canada
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29
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Morgan AP, Welsh CE. Informatics resources for the Collaborative Cross and related mouse populations. Mamm Genome 2015; 26:521-39. [PMID: 26135136 DOI: 10.1007/s00335-015-9581-z] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2015] [Accepted: 06/23/2015] [Indexed: 02/05/2023]
Affiliation(s)
- Andrew P Morgan
- Department of Genetics, University of North Carolina, Chapel Hill, NC, USA
| | - Catherine E Welsh
- Department of Mathematics & Computer Science, Rhodes College, Memphis, TN, USA.
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30
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Galupa R, Heard E. X-chromosome inactivation: new insights into cis and trans regulation. Curr Opin Genet Dev 2015; 31:57-66. [PMID: 26004255 DOI: 10.1016/j.gde.2015.04.002] [Citation(s) in RCA: 107] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2015] [Accepted: 04/02/2015] [Indexed: 12/19/2022]
Abstract
X-chromosome inactivation (XCI) is a developmentally associated process that evolved in mammals to enable gene dosage compensation between XX and XY individuals. In placental mammals, it is triggered by the long noncoding RNA Xist, which is produced from a complex regulatory locus, the X-inactivation centre (Xic). Recent insights into the regulatory landscape of the Xic, including its partitioning into topological associating domains (TADs) and its genetic dissection, have important implications for the monoallelic regulation of Xist. Here, we present some of the latest studies on X inactivation with a special focus on the regulation of Xist, its various functions and the putative role of chromosome conformation in regulating the dynamics of this locus during development and differentiation.
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Affiliation(s)
- Rafael Galupa
- Mammalian Developmental Epigenetics Group, Institut Curie, PSL University, CNRS UMR3215, INSERM U934, 26, rue d'Ulm, 75005 Paris, France
| | - Edith Heard
- Mammalian Developmental Epigenetics Group, Institut Curie, PSL University, CNRS UMR3215, INSERM U934, 26, rue d'Ulm, 75005 Paris, France.
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31
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Crowley JJ, Zhabotynsky V, Sun W, Huang S, Pakatci IK, Kim Y, Wang JR, Morgan AP, Calaway JD, Aylor DL, Yun Z, Bell TA, Buus RJ, Calaway ME, Didion JP, Gooch TJ, Hansen SD, Robinson NN, Shaw GD, Spence JS, Quackenbush CR, Barrick CJ, Nonneman RJ, Kim K, Xenakis J, Xie Y, Valdar W, Lenarcic AB, Wang W, Welsh CE, Fu CP, Zhang Z, Holt J, Guo Z, Threadgill DW, Tarantino LM, Miller DR, Zou F, McMillan L, Sullivan PF, Pardo-Manuel de Villena F. Analyses of allele-specific gene expression in highly divergent mouse crosses identifies pervasive allelic imbalance. Nat Genet 2015; 47:353-60. [PMID: 25730764 PMCID: PMC4380817 DOI: 10.1038/ng.3222] [Citation(s) in RCA: 162] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2014] [Accepted: 01/26/2015] [Indexed: 12/15/2022]
Abstract
Complex human traits are influenced by variation in regulatory DNA through mechanisms that are not fully understood. Since regulatory elements are conserved between humans and mice, a thorough annotation of cis regulatory variants in mice could aid in this process. Here we provide a detailed portrait of mouse gene expression across multiple tissues in a three-way diallel. Greater than 80% of mouse genes have cis regulatory variation. These effects influence complex traits and usually extend to the human ortholog. Further, we estimate that at least one in every thousand SNPs creates a cis regulatory effect. We also observe two types of parent-of-origin effects, including classical imprinting and a novel, global allelic imbalance in favor of the paternal allele. We conclude that, as with humans, pervasive regulatory variation influences complex genetic traits in mice and provide a new resource toward understanding the genetic control of transcription in mammals.
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Affiliation(s)
- James J Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Vasyl Zhabotynsky
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Sun
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Shunping Huang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Isa Kemal Pakatci
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yunjung Kim
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jeremy R Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Andrew P Morgan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John D Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David L Aylor
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zaining Yun
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Timothy A Bell
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ryan J Buus
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Mark E Calaway
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - John P Didion
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Terry J Gooch
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Stephanie D Hansen
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Nashiya N Robinson
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Ginger D Shaw
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Jason S Spence
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Corey R Quackenbush
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Cordelia J Barrick
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Randal J Nonneman
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Kyungsu Kim
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Xenakis
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Yuying Xie
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - William Valdar
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alan B Lenarcic
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Wei Wang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Catherine E Welsh
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Chen-Ping Fu
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhaojun Zhang
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - James Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Zhishan Guo
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - David W Threadgill
- Department of Molecular and Cellular Medicine, Texas A&M Health Science Center, College Station, Texas, USA
| | - Lisa M Tarantino
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Darla R Miller
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Fei Zou
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Patrick F Sullivan
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [4] Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Fernando Pardo-Manuel de Villena
- 1] Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [2] Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA. [3] Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
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Didion JP, Morgan AP, Clayshulte AMF, Mcmullan RC, Yadgary L, Petkov PM, Bell TA, Gatti DM, Crowley JJ, Hua K, Aylor DL, Bai L, Calaway M, Chesler EJ, French JE, Geiger TR, Gooch TJ, Garland T, Harrill AH, Hunter K, McMillan L, Holt M, Miller DR, O'Brien DA, Paigen K, Pan W, Rowe LB, Shaw GD, Simecek P, Sullivan PF, Svenson KL, Weinstock GM, Threadgill DW, Pomp D, Churchill GA, Pardo-Manuel de Villena F. A multi-megabase copy number gain causes maternal transmission ratio distortion on mouse chromosome 2. PLoS Genet 2015; 11:e1004850. [PMID: 25679959 PMCID: PMC4334553 DOI: 10.1371/journal.pgen.1004850] [Citation(s) in RCA: 67] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2014] [Accepted: 10/24/2014] [Indexed: 12/29/2022] Open
Abstract
Significant departures from expected Mendelian inheritance ratios (transmission ratio distortion, TRD) are frequently observed in both experimental crosses and natural populations. TRD on mouse Chromosome (Chr) 2 has been reported in multiple experimental crosses, including the Collaborative Cross (CC). Among the eight CC founder inbred strains, we found that Chr 2 TRD was exclusive to females that were heterozygous for the WSB/EiJ allele within a 9.3 Mb region (Chr 2 76.9 - 86.2 Mb). A copy number gain of a 127 kb-long DNA segment (designated as responder to drive, R2d) emerged as the strongest candidate for the causative allele. We mapped R2d sequences to two loci within the candidate interval. R2d1 is located near the proximal boundary, and contains a single copy of R2d in all strains tested. R2d2 maps to a 900 kb interval, and the number of R2d copies varies from zero in classical strains (including the mouse reference genome) to more than 30 in wild-derived strains. Using real-time PCR assays for the copy number, we identified a mutation (R2d2WSBdel1) that eliminates the majority of the R2d2WSB copies without apparent alterations of the surrounding WSB/EiJ haplotype. In a three-generation pedigree segregating for R2d2WSBdel1, the mutation is transmitted to the progeny and Mendelian segregation is restored in females heterozygous for R2d2WSBdel1, thus providing direct evidence that the copy number gain is causal for maternal TRD. We found that transmission ratios in R2d2WSB heterozygous females vary between Mendelian segregation and complete distortion depending on the genetic background, and that TRD is under genetic control of unlinked distorter loci. Although the R2d2WSB transmission ratio was inversely correlated with average litter size, several independent lines of evidence support the contention that female meiotic drive is the cause of the distortion. We discuss the implications and potential applications of this novel meiotic drive system.
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Affiliation(s)
- John P. Didion
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Andrew P. Morgan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Amelia M.-F. Clayshulte
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Rachel C. Mcmullan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Liran Yadgary
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petko M. Petkov
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Timothy A. Bell
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Daniel M. Gatti
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - James J. Crowley
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kunjie Hua
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - David L. Aylor
- Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Ling Bai
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Mark Calaway
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - John E. French
- National Toxicology Program, National Institute of Environmental Sciences, NIH, Research Triangle Park, North Carolina, United States of America
| | - Thomas R. Geiger
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Terry J. Gooch
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Theodore Garland
- Department of Biology, University of California Riverside, Riverside, California, United States of America
| | - Alison H. Harrill
- Department of Environmental and Occupational Health, University of Arkansas for Medical Sciences, Little Rock, Arkansas, United States of America
| | - Kent Hunter
- Laboratory of Cancer Biology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, United States of America
| | - Leonard McMillan
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Matt Holt
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Darla R. Miller
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Deborah A. O'Brien
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Kenneth Paigen
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Wenqi Pan
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Lucy B. Rowe
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Ginger D. Shaw
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Petr Simecek
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - Patrick F. Sullivan
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | - Karen L Svenson
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| | - George M. Weinstock
- Jackson Laboratory for Genomic Medicine, Farmington, Connecticut, United States of America
| | - David W. Threadgill
- Department of Veterinary Pathobiology and Department of Molecular and Cellular Medicine, Texas A&M University, College Station, Texas, United States of America
| | - Daniel Pomp
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Department of Cell Biology and Physiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
| | | | - Fernando Pardo-Manuel de Villena
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
- Carolina Center for Genome Science, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States of America
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Gregg C. Known unknowns for allele-specific expression and genomic imprinting effects. F1000PRIME REPORTS 2014; 6:75. [PMID: 25343032 PMCID: PMC4166941 DOI: 10.12703/p6-75] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Recent studies have provided evidence for non-canonical imprinting effects that are associated with allele-specific expression biases at the tissue level in mice. These imprinting effects have features that are distinct from canonical imprinting effects that involve allele silencing. Here, I discuss some of the evidence for non-canonical imprinting effects in the context of random X-inactivation and epigenetic allele-specific expression effects on the autosomes. I propose several mechanisms that may underlie non-canonical imprinting effects and outline future directions and approaches to study these effects at the cellular level in vivo. The growing evidence for complex allele-specific expression effects that are cell- and developmental stage-specific has opened a new frontier for study. Currently, the function of these effects and the underlying regulatory mechanisms are largely unknown.
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Affiliation(s)
- Christopher Gregg
- Department of Neurobiology & Anatomy and Human Genetics, University of Utah School of Medicine, 323 Wintrobe Bldg 530, University of Utah, School of Medicine20 North 1900 East, Salt Lake City, UT 84132-3401USA
- The New York Stem Cell Foundation178 Columbus Avenue #237064, New York, NY 10023USA
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