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Raitoharju E, Rajić S, Marttila S. Non-coding 886 ( nc886/ vtRNA2-1), the epigenetic odd duck - implications for future studies. Epigenetics 2024; 19:2332819. [PMID: 38525792 DOI: 10.1080/15592294.2024.2332819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 03/14/2024] [Indexed: 03/26/2024] Open
Abstract
Non-coding 886 (nc886, vtRNA2-1) is the only human polymorphically imprinted gene, in which the methylation status is not determined by genetics. Existing literature regarding the establishment, stability and consequences of the methylation pattern, as well as the nature and function of the nc886 RNAs transcribed from the locus, are contradictory. For example, the methylation status of the locus has been reported to be stable through life and across somatic tissues, but also susceptible to environmental effects. The nature of the produced nc886 RNA(s) has been redefined multiple times, and in carcinogenesis, these RNAs have been reported to have conflicting roles. In addition, due to the bimodal methylation pattern of the nc886 locus, traditional genome-wide methylation analyses can lead to false-positive results, especially in smaller datasets. Herein, we aim to summarize the existing literature regarding nc886, discuss how the characteristics of nc886 give rise to contradictory results, as well as to reinterpret, reanalyse and, where possible, replicate the results presented in the current literature. We also introduce novel findings on how the distribution of the nc886 methylation pattern is associated with the geographical origins of the population and describe the methylation changes in a large variety of human tumours. Through the example of this one peculiar genetic locus and RNA, we aim to highlight issues in the analysis of DNA methylation and non-coding RNAs in general and offer our suggestions for what should be taken into consideration in future analyses.
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Affiliation(s)
- Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Saara Marttila
- Molecular Epidemiology, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Tays Research Services, Wellbeing Services County of Pirkanmaa, Tampere University Hospital, Tampere, Finland
- Gerontology Research Center, Tampere University, Tampere, Finland
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Johnson ND, Cutler DJ, Conneely KN. Investigating the potential of single-cell DNA methylation data to detect allele-specific methylation and imprinting. Am J Hum Genet 2024; 111:654-667. [PMID: 38471507 PMCID: PMC11023823 DOI: 10.1016/j.ajhg.2024.02.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 02/12/2024] [Accepted: 02/12/2024] [Indexed: 03/14/2024] Open
Abstract
Allele-specific methylation (ASM) is an epigenetic modification whereby one parental allele becomes methylated and the other unmethylated at a specific locus. ASM is most often driven by the presence of nearby heterozygous variants that influence methylation, but also occurs somatically in the context of genomic imprinting. In this study, we investigate ASM using publicly available single-cell reduced representation bisulfite sequencing (scRRBS) data on 608 B cells sampled from six healthy B cell samples and 1,230 cells from 11 chronic lymphocytic leukemia (CLL) samples. We developed a likelihood-based criterion to test whether a CpG exhibited ASM, based on the distributions of methylated and unmethylated reads both within and across cells. Applying our likelihood ratio test, 65,998 CpG sites exhibited ASM in healthy B cell samples according to a Bonferroni criterion (p < 8.4 × 10-9), and 32,862 CpG sites exhibited ASM in CLL samples (p < 8.5 × 10-9). We also called ASM at the sample level. To evaluate the accuracy of our method, we called heterozygous variants from the scRRBS data, which enabled variant-based calls of ASM within each cell. Comparing sample-level ASM calls to the variant-based measures of ASM, we observed a positive predictive value of 76%-100% across samples. We observed high concordance of ASM across samples and an overrepresentation of ASM in previously reported imprinted genes and genes with imprinting binding motifs. Our study demonstrates that single-cell bisulfite sequencing is a potentially powerful tool to investigate ASM, especially as studies expand to increase the number of samples and cells sequenced.
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Affiliation(s)
- Nicholas D Johnson
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA; Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA
| | - David J Cutler
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA; Population Biology, Ecology, and Evolution Program, Emory University, Atlanta, GA, USA.
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Huo H, Zhang C, Wang K, Wang S, Chen W, Zhang Y, Yu W, Li S, Li S. A novel imprinted locus on bovine chromosome 18 homologous with human chromosome 16q24.1. Mol Genet Genomics 2024; 299:40. [PMID: 38546894 DOI: 10.1007/s00438-024-02123-8] [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: 08/28/2023] [Accepted: 02/02/2024] [Indexed: 04/02/2024]
Abstract
Genomic imprinting is an epigenetic regulation mechanism in mammals resulting in the parentally dependent monoallelic expression of genes. Imprinting disorders in humans are associated with several congenital syndromes and cancers and remain the focus of many medical studies. Cattle is a better model organism for investigating human embryo development than mice. Imprinted genes usually cluster on chromosomes and are regulated by different methylation regions (DMRs) located in imprinting control regions that control gene expression in cis. There is an imprinted locus on human chromosome 16q24.1 associated with congenital lethal developmental lung disease in newborns. However, genomic imprinting on bovine chromosome 18, which is homologous with human chromosome 16 has not been systematically studied. The aim of this study was to analyze the allelic expressions of eight genes (CDH13, ATP2C2, TLDC1, COTL1, CRISPLD2, ZDHHC7, KIAA0513, and GSE1) on bovine chromosome 18 and to search the DMRs associated gene allelic expression. Three transcript variants of the ZDHHC7 gene (X1, X2, and X5) showed maternal imprinting in bovine placentas. In addition, the monoallelic expression of X2 and X5 was tissue-specific. Five transcripts of the KIAA0513 gene showed tissue- and isoform-specific monoallelic expression. The CDH13, ATP2C2, and TLDC1 genes exhibited tissue-specific imprinting, however, COTL1, CRISLPLD2, and GSE1 escaped imprinting. Four DMRs, established after fertilization, were found in this region. Two DMRs were located between the ZDHHC7 and KIAA0513 genes, and two were in exon 1 of the CDH13 and ATP2C2 genes, respectively. The results from this study support future studies on the molecular mechanism to regulate the imprinting of candidate genes on bovine chromosome 18.
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Affiliation(s)
- Haonan Huo
- College of Life Science, Agricultural University of Hebei, Baoding, Hebei, China
| | - Cui Zhang
- College of Life Science, Agricultural University of Hebei, Baoding, Hebei, China
| | - Kun Wang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
- Key Laboratory of Crop Cultivation Physiology and Green Production in Hebei Province, Shijiazhuang, China
| | - Siwei Wang
- Institute of Cereal and Oil Crops, Hebei Academy of Agricultural and Forestry Sciences, Shijiazhuang, China
- Key Laboratory of Crop Cultivation Physiology and Green Production in Hebei Province, Shijiazhuang, China
| | - Weina Chen
- College of Medical Science, Hebei University, Baoding, Hebei, China
| | - Yinjiao Zhang
- College of Life Science, Agricultural University of Hebei, Baoding, Hebei, China
| | - Wenli Yu
- Shijiazhuang Tianquan Elite Dairy Ltd., Shijiazhuang, Hebei, China
| | - Shujing Li
- Shijiazhuang Tianquan Elite Dairy Ltd., Shijiazhuang, Hebei, China.
| | - Shijie Li
- College of Life Science, Agricultural University of Hebei, Baoding, Hebei, China.
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Warman-Chardon J, Hartley T, Marshall AE, McBride A, Couse M, Macdonald W, Mann MRW, Bourque PR, Breiner A, Lochmüller H, Woulfe J, Sampaio ML, Melkus G, Brais B, Dyment DA, Boycott KM, Kernohan K. Biallelic SOX8 Variants Associated With Novel Syndrome With Myopathy, Skeletal Deformities, Intellectual Disability, and Ovarian Dysfunction. Neurol Genet 2023; 9:e200088. [PMID: 38235364 PMCID: PMC10508790 DOI: 10.1212/nxg.0000000000200088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Accepted: 05/30/2023] [Indexed: 01/19/2024]
Abstract
Background and Objectives The human genome contains ∼20,000 genes, each of which has its own set of complex regulatory systems to govern precise expression in each developmental stage and cell type. Here, we report a female patient with congenital weakness, respiratory failure, skeletal dysplasia, contractures, short stature, intellectual delay, respiratory failure, and amenorrhea who presented to Medical Genetics service with no known cause for her condition. Methods Whole-exome and whole-genome sequencing were conducted, as well as investigational functional studies to assess the effect of SOX8 variant. Results The patient was found to have biallelic SOX8 variants (NM_014587.3:c.422+5G>C; c.583dup p.(His195ProfsTer11)). SOX8 is a transcriptional regulator, which is predicted to be imprinted (expressed from only one parental allele), but this has not yet been confirmed. We provide evidence that while SOX8 was maternally expressed in adult-derived fibroblasts and lymphoblasts, it was biallelically expressed in other cell types and therefore suggest that biallelic variants are associated with this recessive condition. Functionally, we showed that the paternal variant had the capacity to affect mRNA splicing while the maternal variant resulted in low levels of a truncated protein, which showed decreased binding at and altered expression of SOX8 targets. Discussion Our findings associate SOX8 variants with this novel condition, highlight how complex genome regulation can complicate novel disease-gene identification, and provide insight into the molecular pathogenesis of this disease.
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Affiliation(s)
- Jodi Warman-Chardon
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Taila Hartley
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Aren Elizabeth Marshall
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Arran McBride
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Madeline Couse
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - William Macdonald
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Mellissa R W Mann
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Pierre R Bourque
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Ari Breiner
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Hanns Lochmüller
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - John Woulfe
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Marcos Loreto Sampaio
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Gerd Melkus
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Bernard Brais
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - David A Dyment
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Kym M Boycott
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
| | - Kristin Kernohan
- From the Department of Medicine (J.W.-C., P.R.B., A.B., H.L.), The Ottawa Hospital; The Ottawa Hospital Research Institute (J.W.-C., P.R.B., H.L., J.W., M.L.S., G.M.); Faculty of Medicine (J.W.-C., P.R.B., A.B., H.L., J.W., M.L.S., D.A.D., K.M.B.); Children's Hospital of Eastern Ontario Research Institute (J.W.-C., T.H., A.E.M., A.M., H.L., D.A.D., K.M.B., K.K.), University of Ottawa; Hospital for Sick Children (M.C.), Centre for Computational Medicine, Toronto, Canada; Department of Obstetrics (W.M., M.R.W.M.), Gynaecology and Reproductive Sciences, University of Pittsburgh School of Medicine; Magee-Womens Research Institute (W.M., M.R.W.M.), Pittsburgh, PA; Department of Pathology and Laboratory Medicine (A.B., J.W.), The Ottawa Hospital; Department of Radiology (M.L.S., G.M.), Radiation Oncology and Medical Physics, University of Ottawa; Department of Neurology and Neurosurgery (B.B.), Montreal Neurological Institute and Hospital, McGill University; and Newborn Screening Ontario (K.K.), Children's Hospital of Eastern Ontario, Ottawa, Canada
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5
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Eggermann T, Monk D, de Nanclares GP, Kagami M, Giabicani E, Riccio A, Tümer Z, Kalish JM, Tauber M, Duis J, Weksberg R, Maher ER, Begemann M, Elbracht M. Imprinting disorders. Nat Rev Dis Primers 2023; 9:33. [PMID: 37386011 DOI: 10.1038/s41572-023-00443-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/19/2023] [Indexed: 07/01/2023]
Abstract
Imprinting disorders (ImpDis) are congenital conditions that are characterized by disturbances of genomic imprinting. The most common individual ImpDis are Prader-Willi syndrome, Angelman syndrome and Beckwith-Wiedemann syndrome. Individual ImpDis have similar clinical features, such as growth disturbances and developmental delay, but the disorders are heterogeneous and the key clinical manifestations are often non-specific, rendering diagnosis difficult. Four types of genomic and imprinting defect (ImpDef) affecting differentially methylated regions (DMRs) can cause ImpDis. These defects affect the monoallelic and parent-of-origin-specific expression of imprinted genes. The regulation within DMRs as well as their functional consequences are mainly unknown, but functional cross-talk between imprinted genes and functional pathways has been identified, giving insight into the pathophysiology of ImpDefs. Treatment of ImpDis is symptomatic. Targeted therapies are lacking owing to the rarity of these disorders; however, personalized treatments are in development. Understanding the underlying mechanisms of ImpDis, and improving diagnosis and treatment of these disorders, requires a multidisciplinary approach with input from patient representatives.
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Affiliation(s)
- Thomas Eggermann
- Institute for Human Genetics and Genomic Medicine, Medical Faculty, RWTH Aachen University, Aachen, Germany.
| | - David Monk
- School of Biological Sciences, University of East Anglia, Norwich, UK
| | - Guiomar Perez de Nanclares
- Rare Diseases Research Group, Molecular (Epi)Genetics Laboratory, Bioaraba Research Health Institute, Araba University Hospital-Txagorritxu, Vitoria-Gasteiz, Spain
| | - Masayo Kagami
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Eloïse Giabicani
- Sorbonne Université, INSERM, Centre de Recherche Saint-Antoine, APHP, Hôpital Armand Trousseau, Endocrinologie Moléculaire et Pathologies d'Empreinte, Paris, France
| | - Andrea Riccio
- Department of Environmental, Biological and Pharmaceutical Sciences and Technologies, Università della Campania Luigi Vanvitelli, Caserta, Italy
- Institute of Genetics and Biophysics A. Buzzati-Traverso, CNR, Naples, Italy
| | - Zeynep Tümer
- Kennedy Center, Department of Clinical Genetics, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer M Kalish
- Division of Human Genetics and Center for Childhood Cancer Research, Children's Hospital of Philadelphia and the Departments of Pediatrics and Genetics at the Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Maithé Tauber
- Centre de Référence Maladies Rares PRADORT (syndrome de PRADer-Willi et autres Obésités Rares avec Troubles du comportement alimentaire), Hôpital des Enfants, CHU Toulouse, Toulouse, France
- Institut Toulousain des Maladies Infectieuses et Inflammatoires (Infinity) INSERM UMR1291 - CNRS UMR5051 - Université Toulouse III, Toulouse, France
| | - Jessica Duis
- Department of Pediatrics, Children's Hospital Colorado, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Rosanna Weksberg
- Division of Clinical and Metabolic Genetics, Department of Paediatrics and Genetics and Genome Biology Program, Research Institute, Hospital for Sick Children, Toronto, Ontario, Canada
- Institute of Medical Sciences and Department of Molecular Genetics, University of Toronto, Toronto, Canada
| | - Eamonn R Maher
- Department of Medical Genetics, University of Cambridge, Cambridge, UK
| | - Matthias Begemann
- Institute for Human Genetics and Genomic Medicine, Medical Faculty, RWTH Aachen University, Aachen, Germany
| | - Miriam Elbracht
- Institute for Human Genetics and Genomic Medicine, Medical Faculty, RWTH Aachen University, Aachen, Germany
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6
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Martínez-Ruiz C, Black JRM, Puttick C, Hill MS, Demeulemeester J, Larose Cadieux E, Thol K, Jones TP, Veeriah S, Naceur-Lombardelli C, Toncheva A, Prymas P, Rowan A, Ward S, Cubitt L, Athanasopoulou F, Pich O, Karasaki T, Moore DA, Salgado R, Colliver E, Castignani C, Dietzen M, Huebner A, Al Bakir M, Tanić M, Watkins TBK, Lim EL, Al-Rashed AM, Lang D, Clements J, Cook DE, Rosenthal R, Wilson GA, Frankell AM, de Carné Trécesson S, East P, Kanu N, Litchfield K, Birkbak NJ, Hackshaw A, Beck S, Van Loo P, Jamal-Hanjani M, Swanton C, McGranahan N. Genomic-transcriptomic evolution in lung cancer and metastasis. Nature 2023; 616:543-552. [PMID: 37046093 PMCID: PMC10115639 DOI: 10.1038/s41586-023-05706-4] [Citation(s) in RCA: 45] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Accepted: 01/04/2023] [Indexed: 04/14/2023]
Abstract
Intratumour heterogeneity (ITH) fuels lung cancer evolution, which leads to immune evasion and resistance to therapy1. Here, using paired whole-exome and RNA sequencing data, we investigate intratumour transcriptomic diversity in 354 non-small cell lung cancer tumours from 347 out of the first 421 patients prospectively recruited into the TRACERx study2,3. Analyses of 947 tumour regions, representing both primary and metastatic disease, alongside 96 tumour-adjacent normal tissue samples implicate the transcriptome as a major source of phenotypic variation. Gene expression levels and ITH relate to patterns of positive and negative selection during tumour evolution. We observe frequent copy number-independent allele-specific expression that is linked to epigenomic dysfunction. Allele-specific expression can also result in genomic-transcriptomic parallel evolution, which converges on cancer gene disruption. We extract signatures of RNA single-base substitutions and link their aetiology to the activity of the RNA-editing enzymes ADAR and APOBEC3A, thereby revealing otherwise undetected ongoing APOBEC activity in tumours. Characterizing the transcriptomes of primary-metastatic tumour pairs, we combine multiple machine-learning approaches that leverage genomic and transcriptomic variables to link metastasis-seeding potential to the evolutionary context of mutations and increased proliferation within primary tumour regions. These results highlight the interplay between the genome and transcriptome in influencing ITH, lung cancer evolution and metastasis.
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Affiliation(s)
- Carlos Martínez-Ruiz
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - James R M Black
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Clare Puttick
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Mark S Hill
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Jonas Demeulemeester
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Integrative Cancer Genomics Laboratory, Department of Oncology, KU Leuven, Leuven, Belgium
- VIB-KU Leuven Center for Cancer Biology, Leuven, Belgium
| | - Elizabeth Larose Cadieux
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Medical Genomics, University College London Cancer Institute, London, UK
| | - Kerstin Thol
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Thomas P Jones
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Selvaraju Veeriah
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | | | - Antonia Toncheva
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Paulina Prymas
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Andrew Rowan
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Sophia Ward
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
- Advanced Sequencing Facility, The Francis Crick Institute, London, UK
| | - Laura Cubitt
- Advanced Sequencing Facility, The Francis Crick Institute, London, UK
| | - Foteini Athanasopoulou
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
- Advanced Sequencing Facility, The Francis Crick Institute, London, UK
| | - Oriol Pich
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Takahiro Karasaki
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
- Cancer Metastasis Laboratory, University College London Cancer Institute, London, UK
| | - David A Moore
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
- Department of Cellular Pathology, University College London Hospitals, London, UK
| | - Roberto Salgado
- Department of Pathology, ZAS Hospitals, Antwerp, Belgium
- Division of Research, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Emma Colliver
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Carla Castignani
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Medical Genomics, University College London Cancer Institute, London, UK
| | - Michelle Dietzen
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Ariana Huebner
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Maise Al Bakir
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Miljana Tanić
- Medical Genomics, University College London Cancer Institute, London, UK
- Experimental Oncology, Institute for Oncology and Radiology of Serbia, Belgrade, Serbia
| | - Thomas B K Watkins
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Emilia L Lim
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Ali M Al-Rashed
- Centre for Nephrology, Division of Medicine, University College London, London, UK
| | - Danny Lang
- Scientific Computing STP, Francis Crick Institute, London, UK
| | - James Clements
- Scientific Computing STP, Francis Crick Institute, London, UK
| | - Daniel E Cook
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Rachel Rosenthal
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Gareth A Wilson
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | - Alexander M Frankell
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
| | | | - Philip East
- Bioinformatics and Biostatistics, The Francis Crick Institute, London, UK
| | - Nnennaya Kanu
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
| | - Kevin Litchfield
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Tumour Immunogenomics and Immunosurveillance Laboratory, University College London Cancer Institute, London, UK
| | - Nicolai J Birkbak
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Allan Hackshaw
- Cancer Research UK & UCL Cancer Trials Centre, London, UK
| | - Stephan Beck
- Medical Genomics, University College London Cancer Institute, London, UK
| | - Peter Van Loo
- Cancer Genomics Laboratory, The Francis Crick Institute, London, UK
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mariam Jamal-Hanjani
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK
- Cancer Metastasis Laboratory, University College London Cancer Institute, London, UK
- Department of Medical Oncology, University College London Hospitals, London, UK
| | - Charles Swanton
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Evolution and Genome Instability Laboratory, The Francis Crick Institute and University College London Cancer Institute, London, UK.
- Department of Medical Oncology, University College London Hospitals, London, UK.
| | - Nicholas McGranahan
- Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
- Cancer Genome Evolution Research Group, Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
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7
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Rozowsky J, Gao J, Borsari B, Yang YT, Galeev T, Gürsoy G, Epstein CB, Xiong K, Xu J, Li T, Liu J, Yu K, Berthel A, Chen Z, Navarro F, Sun MS, Wright J, Chang J, Cameron CJF, Shoresh N, Gaskell E, Drenkow J, Adrian J, Aganezov S, Aguet F, Balderrama-Gutierrez G, Banskota S, Corona GB, Chee S, Chhetri SB, Cortez Martins GC, Danyko C, Davis CA, Farid D, Farrell NP, Gabdank I, Gofin Y, Gorkin DU, Gu M, Hecht V, Hitz BC, Issner R, Jiang Y, Kirsche M, Kong X, Lam BR, Li S, Li B, Li X, Lin KZ, Luo R, Mackiewicz M, Meng R, Moore JE, Mudge J, Nelson N, Nusbaum C, Popov I, Pratt HE, Qiu Y, Ramakrishnan S, Raymond J, Salichos L, Scavelli A, Schreiber JM, Sedlazeck FJ, See LH, Sherman RM, Shi X, Shi M, Sloan CA, Strattan JS, Tan Z, Tanaka FY, Vlasova A, Wang J, Werner J, Williams B, Xu M, Yan C, Yu L, Zaleski C, Zhang J, Ardlie K, Cherry JM, Mendenhall EM, Noble WS, Weng Z, Levine ME, Dobin A, Wold B, Mortazavi A, Ren B, Gillis J, Myers RM, Snyder MP, Choudhary J, Milosavljevic A, Schatz MC, Bernstein BE, Guigó R, Gingeras TR, Gerstein M. The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models. Cell 2023; 186:1493-1511.e40. [PMID: 37001506 PMCID: PMC10074325 DOI: 10.1016/j.cell.2023.02.018] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 10/16/2022] [Accepted: 02/10/2023] [Indexed: 04/03/2023]
Abstract
Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × ∼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.
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Affiliation(s)
- Joel Rozowsky
- Section on Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jiahao Gao
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Beatrice Borsari
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain
| | - Yucheng T Yang
- Institute of Science and Technology for Brain-Inspired Intelligence; MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence; MOE Frontiers Center for Brain Science, Fudan University, Shanghai 200433, China; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Timur Galeev
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Gamze Gürsoy
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | | | - Kun Xiong
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jinrui Xu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Tianxiao Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jason Liu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Keyang Yu
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Ana Berthel
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Zhanlin Chen
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
| | - Fabio Navarro
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Maxwell S Sun
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | | | - Justin Chang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Christopher J F Cameron
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Noam Shoresh
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Jorg Drenkow
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Jessika Adrian
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Sergey Aganezov
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA
| | | | | | | | | | - Sora Chee
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Surya B Chhetri
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Gabriel Conte Cortez Martins
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Cassidy Danyko
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Carrie A Davis
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Daniel Farid
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | | | - Idan Gabdank
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Yoel Gofin
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - David U Gorkin
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Mengting Gu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Vivian Hecht
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Benjamin C Hitz
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Robbyn Issner
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Yunzhe Jiang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Melanie Kirsche
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Xiangmeng Kong
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Bonita R Lam
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Shantao Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Bian Li
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Xiqi Li
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Khine Zin Lin
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Ruibang Luo
- Department of Computer Science, The University of Hong Kong, Hong Kong, CHN
| | - Mark Mackiewicz
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Ran Meng
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jill E Moore
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Jonathan Mudge
- European Bioinformatics Institute, Cambridge, Cambridgeshire, GB
| | | | - Chad Nusbaum
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ioann Popov
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Henry E Pratt
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Yunjiang Qiu
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Srividya Ramakrishnan
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Joe Raymond
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Leonidas Salichos
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Department of Biological and Chemical Sciences, New York Institute of Technology, Old Westbury, NY, USA
| | - Alexandra Scavelli
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Jacob M Schreiber
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Fritz J Sedlazeck
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA; Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Lei Hoon See
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Rachel M Sherman
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA
| | - Xu Shi
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Minyi Shi
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Cricket Alicia Sloan
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - J Seth Strattan
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Zhen Tan
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Forrest Y Tanaka
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | - Anna Vlasova
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain; Comparative Genomics Group, Life Science Programme, Barcelona Supercomputing Centre, Barcelona, Spain; Institute of Research in Biomedicine, Barcelona, Spain
| | - Jun Wang
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Jonathan Werner
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Brian Williams
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Min Xu
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Chengfei Yan
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA
| | - Lu Yu
- Institute of Cancer Research, London, UK
| | - Christopher Zaleski
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Jing Zhang
- Department of Computer Science, University of California, Irvine, Irvine, CA, USA
| | | | - J Michael Cherry
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | | | - William S Noble
- Department of Genome Sciences, University of Washington, Seattle, WA, USA
| | - Zhiping Weng
- Program in Bioinformatics and Integrative Biology, University of Massachusetts Medical School, Worcester, MA, USA
| | - Morgan E Levine
- Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Pathology, Yale University School of Medicine, New Haven, CT, USA
| | - Alexander Dobin
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA
| | - Barbara Wold
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
| | - Ali Mortazavi
- Department of Developmental and Cell Biology, University of California, Irvine, Irvine, CA, USA
| | - Bing Ren
- Ludwig Institute for Cancer Research, University of California, San Diego, La Jolla, CA, USA
| | - Jesse Gillis
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA; Department of Physiology, University of Toronto, Toronto, ON, Canada
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Michael P Snyder
- Department of Genetics, School of Medicine, Stanford University, Palo Alto, CA, USA
| | | | | | - Michael C Schatz
- Departments of Computer Science and Biology, Johns Hopkins University, Baltimore, MD, USA; Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
| | - Bradley E Bernstein
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Department of Cancer Biology, Dana-Farber Cancer Institute, Boston, MA, USA.
| | - Roderic Guigó
- Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Catalonia, Spain; Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.
| | - Thomas R Gingeras
- Functional Genomics, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, USA.
| | - Mark Gerstein
- Section on Biomedical Informatics and Data Science, Yale University, New Haven, CT, USA; Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA; Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, USA; Department of Statistics and Data Science, Yale University, New Haven, CT, USA; Department of Computer Science, Yale University, New Haven, CT, USA.
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8
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Richer S, Tian Y, Schoenfelder S, Hurst L, Murrell A, Pisignano G. Widespread allele-specific topological domains in the human genome are not confined to imprinted gene clusters. Genome Biol 2023; 24:40. [PMID: 36869353 PMCID: PMC9983196 DOI: 10.1186/s13059-023-02876-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 02/13/2023] [Indexed: 03/05/2023] Open
Abstract
BACKGROUND There is widespread interest in the three-dimensional chromatin conformation of the genome and its impact on gene expression. However, these studies frequently do not consider parent-of-origin differences, such as genomic imprinting, which result in monoallelic expression. In addition, genome-wide allele-specific chromatin conformation associations have not been extensively explored. There are few accessible bioinformatic workflows for investigating allelic conformation differences and these require pre-phased haplotypes which are not widely available. RESULTS We developed a bioinformatic pipeline, "HiCFlow," that performs haplotype assembly and visualization of parental chromatin architecture. We benchmarked the pipeline using prototype haplotype phased Hi-C data from GM12878 cells at three disease-associated imprinted gene clusters. Using Region Capture Hi-C and Hi-C data from human cell lines (1-7HB2, IMR-90, and H1-hESCs), we can robustly identify the known stable allele-specific interactions at the IGF2-H19 locus. Other imprinted loci (DLK1 and SNRPN) are more variable and there is no "canonical imprinted 3D structure," but we could detect allele-specific differences in A/B compartmentalization. Genome-wide, when topologically associating domains (TADs) are unbiasedly ranked according to their allele-specific contact frequencies, a set of allele-specific TADs could be defined. These occur in genomic regions of high sequence variation. In addition to imprinted genes, allele-specific TADs are also enriched for allele-specific expressed genes. We find loci that have not previously been identified as allele-specific expressed genes such as the bitter taste receptors (TAS2Rs). CONCLUSIONS This study highlights the widespread differences in chromatin conformation between heterozygous loci and provides a new framework for understanding allele-specific expressed genes.
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Affiliation(s)
- Stephen Richer
- Department of Life Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, UK
| | - Yuan Tian
- Department of Life Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, UK
- UCL Cancer Institute, University College London, Paul O'Gorman Building, London, UK
| | | | - Laurence Hurst
- Department of Life Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, UK
| | - Adele Murrell
- Department of Life Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
| | - Giuseppina Pisignano
- Department of Life Sciences, University of Bath, Claverton Down, Bath, BA2 7AY, UK.
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9
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Haplotype-aware pantranscriptome analyses using spliced pangenome graphs. Nat Methods 2023; 20:239-247. [PMID: 36646895 DOI: 10.1038/s41592-022-01731-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 11/28/2022] [Indexed: 01/18/2023]
Abstract
Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.
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10
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Sibbesen JA, Eizenga JM, Novak AM, Sirén J, Chang X, Garrison E, Paten B. Haplotype-aware pantranscriptome analyses using spliced pangenome graphs. Nat Methods 2023; 20:239-247. [PMID: 36646895 DOI: 10.1101/2021.03.26.437240] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 11/28/2022] [Indexed: 05/24/2023]
Abstract
Pangenomics is emerging as a powerful computational paradigm in bioinformatics. This field uses population-level genome reference structures, typically consisting of a sequence graph, to mitigate reference bias and facilitate analyses that were challenging with previous reference-based methods. In this work, we extend these methods into transcriptomics to analyze sequencing data using the pantranscriptome: a population-level transcriptomic reference. Our toolchain, which consists of additions to the VG toolkit and a standalone tool, RPVG, can construct spliced pangenome graphs, map RNA sequencing data to these graphs, and perform haplotype-aware expression quantification of transcripts in a pantranscriptome. We show that this workflow improves accuracy over state-of-the-art RNA sequencing mapping methods, and that it can efficiently quantify haplotype-specific transcript expression without needing to characterize the haplotypes of a sample beforehand.
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Affiliation(s)
| | | | - Adam M Novak
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Jouni Sirén
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Xian Chang
- UC Santa Cruz Genomics Institute, Santa Cruz, CA, USA
| | - Erik Garrison
- University of Tennessee Health Science Center, Memphis, TN, USA
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11
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Kravitz SN, Ferris E, Love MI, Thomas A, Quinlan AR, Gregg C. Random allelic expression in the adult human body. Cell Rep 2023; 42:111945. [PMID: 36640362 PMCID: PMC10484211 DOI: 10.1016/j.celrep.2022.111945] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2022] [Revised: 10/17/2022] [Accepted: 12/15/2022] [Indexed: 01/07/2023] Open
Abstract
Genes are typically assumed to express both parental alleles similarly, yet cell lines show random allelic expression (RAE) for many autosomal genes that could shape genetic effects. Thus, understanding RAE in human tissues could improve our understanding of phenotypic variation. Here, we develop a methodology to perform genome-wide profiling of RAE and biallelic expression in GTEx datasets for 832 people and 54 tissues. We report 2,762 autosomal genes with some RAE properties similar to randomly inactivated X-linked genes. We found that RAE is associated with rapidly evolving regions in the human genome, adaptive signaling processes, and genes linked to age-related diseases such as neurodegeneration and cancer. We define putative mechanistic subtypes of RAE distinguished by gene overlaps on sense and antisense DNA strands, aggregation in clusters near telomeres, and increased regulatory complexity and inputs compared with biallelic genes. We provide foundations to study RAE in human phenotypes, evolution, and disease.
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Affiliation(s)
- Stephanie N Kravitz
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA; Neurobiology, University of Utah, Salt Lake City, UT, USA
| | - Elliott Ferris
- Neurobiology, University of Utah, Salt Lake City, UT, USA
| | - Michael I Love
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alun Thomas
- Department of Internal Medicine, Epidemiology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Aaron R Quinlan
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA
| | - Christopher Gregg
- Department of Human Genetics, University of Utah, Salt Lake City, UT, USA; Neurobiology, University of Utah, Salt Lake City, UT, USA.
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12
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Paternal UPD14 with sSMC derived from chromosome 14 in Kagami-Ogata syndrome. CHROMOSOME RESEARCH : AN INTERNATIONAL JOURNAL ON THE MOLECULAR, SUPRAMOLECULAR AND EVOLUTIONARY ASPECTS OF CHROMOSOME BIOLOGY 2023; 31:1. [PMID: 36656404 DOI: 10.1007/s10577-023-09712-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 12/27/2022] [Accepted: 01/02/2023] [Indexed: 01/20/2023]
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13
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Liang D, Aygün N, Matoba N, Ideraabdullah FY, Love MI, Stein JL. Inference of putative cell-type-specific imprinted regulatory elements and genes during human neuronal differentiation. Hum Mol Genet 2023; 32:402-416. [PMID: 35994039 PMCID: PMC9851749 DOI: 10.1093/hmg/ddac207] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/02/2022] [Accepted: 08/17/2022] [Indexed: 01/24/2023] Open
Abstract
Genomic imprinting results in gene expression bias caused by parental chromosome of origin and occurs in genes with important roles during human brain development. However, the cell-type and temporal specificity of imprinting during human neurogenesis is generally unknown. By detecting within-donor allelic biases in chromatin accessibility and gene expression that are unrelated to cross-donor genotype, we inferred imprinting in both primary human neural progenitor cells and their differentiated neuronal progeny from up to 85 donors. We identified 43/20 putatively imprinted regulatory elements (IREs) in neurons/progenitors, and 133/79 putatively imprinted genes in neurons/progenitors. Although 10 IREs and 42 genes were shared between neurons and progenitors, most putative imprinting was only detected within specific cell types. In addition to well-known imprinted genes and their promoters, we inferred novel putative IREs and imprinted genes. Consistent with both DNA methylation-based and H3K27me3-based regulation of imprinted expression, some putative IREs also overlapped with differentially methylated or histone-marked regions. Finally, we identified a progenitor-specific putatively imprinted gene overlapping with copy number variation that is associated with uniparental disomy-like phenotypes. Our results can therefore be useful in interpreting the function of variants identified in future parent-of-origin association studies.
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Affiliation(s)
- Dan Liang
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nil Aygün
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Nana Matoba
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Folami Y Ideraabdullah
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Michael I Love
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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14
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Urakawa T, Ozawa J, Tanaka M, Narusawa H, Matsuoka K, Fukami M, Nagasaki K, Kagami M. Beckwith-Wiedemann syndrome with long QT caused by a deletion involving KCNQ1 but not KCNQ1OT1:TSS-DMR. Eur J Med Genet 2023; 66:104671. [PMID: 36402267 DOI: 10.1016/j.ejmg.2022.104671] [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: 10/03/2022] [Revised: 11/08/2022] [Accepted: 11/15/2022] [Indexed: 11/18/2022]
Abstract
Beckwith-Wiedemann syndrome (BWS) is an imprinting disorder with characteristic features, such as overgrowth, macroglossia, and exomphalos. Hypomethylation of the KCNQ1OT1:TSS-differentially methylated region (DMR) on the 11p15.5 imprinted region is the most common etiology of BWS. KCNQ1 on 11p15.5 is expressed from the maternally inherited allele in most tissues, but is biparentally expressed in the heart, and maternal KCNQ1 transcription is required to establish the maternal DNA imprint in the KCNQ1OT1:TSS-DMR. Loss of function variants in KCNQ1 result in long QT syndrome type 1 (LQT1). To date, eight patients with BWS due to KCNQ1 splice variants or structural abnormalities involving KCNQ1 but not the KCNQ1OT1:TSS-DMR have been reported (KCNQ1-BWS), and four of them had LQT1. We report a Japanese boy with BWS and LQT1 presenting with extreme hypomethylation of the KCNQ1OT1:TSS-DMR caused by a de novo 215-kb deletion including KCNQ1 but not the KCNQ1OT1:TSS-DMR on the maternal allele. He was born by emergency cesarean section due to suspicion of placental abruption at 30 weeks of gestation. His birth weight and length were +1.6 SD and +1.0 SD, respectively. His placental weight was +3.9 SD, and histological examination of his placenta was consistent with mesenchymal dysplasia. He had BWS clinical features, including macroglossia, ear creases and pits, body asymmetry, and rectus abdominis muscle dehiscence, and BWS was therefore diagnosed. LQT1 was first noticed at three months in a preoperative examination for lingual frenectomy. The summarized data of our patient and the previously reported eight patients in KCNQ1-BWS showed more frequent and earlier preterm births and smaller sized birth weight in KCNQ1-BWS cases than those with BWS caused by epimutation of the KCNQ1OT1:TSS-DMR. In addition, in five of nine patients with KCNQ1-BWS, LQT1 was detected, and two of them were identified at school age. In our patient and in another single case with LQT1, the LQT1 was not detected early despite neonatal ECG monitoring. For BWS patients with extreme hypomethylation of the KCNQ1OT1:TSS-DMR, searching for CNVs involving KCNQ1 and mutation screening for KCNQ1 should be considered together with periodic ECG monitoring. (338/500 words).
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Affiliation(s)
- Tatsuki Urakawa
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan; Department of Pediatrics, Graduate School of Medicine, Nagasaki University, Japan
| | - Junichi Ozawa
- Department of Pediatrics, Graduate School of Medicine, Niigata University, Japan
| | - Masato Tanaka
- Department of Pediatrics, Graduate School of Medicine, Niigata University, Japan
| | - Hiromune Narusawa
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Kentaro Matsuoka
- Department of Pathology, Tokyo Metropolitan Children's Medical Center, Fuchu, Tokyo, Japan
| | - Maki Fukami
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Keisuke Nagasaki
- Department of Pediatrics, Graduate School of Medicine, Niigata University, Japan
| | - Masayo Kagami
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan.
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15
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Krushkal J, Vural S, Jensen TL, Wright G, Zhao Y. Increased copy number of imprinted genes in the chromosomal region 20q11-q13.32 is associated with resistance to antitumor agents in cancer cell lines. Clin Epigenetics 2022; 14:161. [PMID: 36461044 PMCID: PMC9716673 DOI: 10.1186/s13148-022-01368-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2022] [Accepted: 10/31/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Parent of origin-specific allelic expression of imprinted genes is epigenetically controlled. In cancer, imprinted genes undergo both genomic and epigenomic alterations, including frequent copy number changes. We investigated whether copy number loss or gain of imprinted genes in cancer cell lines is associated with response to chemotherapy treatment. RESULTS We analyzed 198 human imprinted genes including protein-coding genes and noncoding RNA genes using data from tumor cell lines from the Cancer Cell Line Encyclopedia and Genomics of Drug Sensitivity in Cancer datasets. We examined whether copy number of the imprinted genes in 35 different genome locations was associated with response to cancer drug treatment. We also analyzed associations of pretreatment expression and DNA methylation of imprinted genes with drug response. Higher copy number of BLCAP, GNAS, NNAT, GNAS-AS1, HM13, MIR296, MIR298, and PSIMCT-1 in the chromosomal region 20q11-q13.32 was associated with resistance to multiple antitumor agents. Increased expression of BLCAP and HM13 was also associated with drug resistance, whereas higher methylation of gene regions of BLCAP, NNAT, SGK2, and GNAS was associated with drug sensitivity. While expression and methylation of imprinted genes in several other chromosomal regions was also associated with drug response and many imprinted genes in different chromosomal locations showed a considerable copy number variation, only imprinted genes at 20q11-q13.32 had a consistent association of their copy number with drug response. Copy number values among the imprinted genes in the 20q11-q13.32 region were strongly correlated. They were also correlated with the copy number of cancer-related non-imprinted genes MYBL2, AURKA, and ZNF217 in that chromosomal region. Expression of genes at 20q11-q13.32 was associated with ex vivo drug response in primary tumor samples from the Beat AML 1.0 acute myeloid leukemia patient cohort. Association of the increased copy number of the 20q11-q13.32 region with drug resistance may be complex and could involve multiple genes. CONCLUSIONS Copy number of imprinted and non-imprinted genes in the chromosomal region 20q11-q13.32 was associated with cancer drug resistance. The genes in this chromosomal region may have a modulating effect on tumor response to chemotherapy.
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Affiliation(s)
- Julia Krushkal
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA.
| | - Suleyman Vural
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA.,Marie-Josee and Henry R. Kravis Center for Molecular Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Avenue, New York, NY, 10065, USA
| | | | - George Wright
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA
| | - Yingdong Zhao
- Biometric Research Program, Division of Cancer Treatment and Diagnosis, National Cancer Institute, 9609 Medical Center Dr, Rockville, MD, 20850, USA
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16
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Eggermann T, Prawitt D. Further understanding of paternal uniparental disomy in Beckwith-Wiedemann syndrome. Expert Rev Endocrinol Metab 2022; 17:513-521. [PMID: 36377076 DOI: 10.1080/17446651.2022.2144228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2022] [Accepted: 11/02/2022] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Paternal uniparental disomy of chromosome 11 (upd(11)pat) accounts for up to 20% of molecularly confirmed Beckwith-Wiedemann spectrum (BWSp) cases. It belongs to the BWSp subgroup with the second highest tumor risk, and therefore needs particular awareness in research, diagnostics and clinical management. AREAS COVERED We overview the contribution of paternal (mosaic) uniparental disomy of chromosome 11 (UPD, upd(11)pat) and mosaic paternal uniparental diploidy in patients with Beckwith-Wiedemann features. The review comprises the current knowledge on their formation and their molecular and clinical consequences. Accordingly, the consequences for diagnostic testing and clinical monitoring are compiled. EXPERT OPINION The necessity to diagnostically identify and thus discriminate genome-wide paternal uniparental disomy, and upd(11)pat becomes obvious, due to the differences in the clinical course, disease prognosis, and treatment. In particular, monitoring of tumor development by liquid biopsy might be a promising option in the future. From the research point of view, it should be addressed why 11p is prone to mitotic recombination and thus also provide to the role of upd(11) as second hit in tumorigenesis.
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Affiliation(s)
- Thomas Eggermann
- Medical Faculty, Institute of Human Genetics, RWTH Aachen, Aachen, Germany
| | - Dirk Prawitt
- Center for Paediatrics and Adolescent Medicine, University Medical Center, Mainz, Germany
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17
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Balasooriya GI, Spector DL. Allele-specific differential regulation of monoallelically expressed autosomal genes in the cardiac lineage. Nat Commun 2022; 13:5984. [PMID: 36216821 PMCID: PMC9550772 DOI: 10.1038/s41467-022-33722-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 09/27/2022] [Indexed: 11/29/2022] Open
Abstract
Each mammalian autosomal gene is represented by two alleles in diploid cells. To our knowledge, no insights have been made in regard to allele-specific regulatory mechanisms of autosomes. Here we use allele-specific single cell transcriptomic analysis to elucidate the establishment of monoallelic gene expression in the cardiac lineage. We find that monoallelically expressed autosomal genes in mESCs and mouse blastocyst cells are differentially regulated based on the genetic background of the parental alleles. However, the genetic background of the allele does not affect the establishment of monoallelic genes in differentiated cardiomyocytes. Additionally, we observe epigenetic differences between deterministic and random autosomal monoallelic genes. Moreover, we also find a greater contribution of the maternal versus paternal allele to the development and homeostasis of cardiac tissue and in cardiac health, highlighting the importance of maternal influence in male cardiac tissue homeostasis. Our findings emphasize the significance of allele-specific insights into gene regulation in development, homeostasis and disease.
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18
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Marttila S, Tamminen H, Rajić S, Mishra PP, Lehtimäki T, Raitakari O, Kähönen M, Kananen L, Jylhävä J, Hägg S, Delerue T, Peters A, Waldenberger M, Kleber ME, März W, Luoto R, Raitanen J, Sillanpää E, Laakkonen EK, Heikkinen A, Ollikainen M, Raitoharju E. Methylation status of VTRNA2-1/ nc886 is stable across populations, monozygotic twin pairs and in majority of tissues. Epigenomics 2022; 14:1105-1124. [PMID: 36200237 DOI: 10.2217/epi-2022-0228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.
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Affiliation(s)
- Saara Marttila
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Gerontology Research Center, Tampere University, Tampere, 33014, Finland
| | - Hely Tamminen
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sonja Rajić
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Fimlab Laboratories, Arvo Ylpön katu 4, Tampere, 33520, Finland
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku & Turku University Hospital, Turku, 20014, Finland.,Research Centre of Applied & Preventive Cardiovascular Medicine, University of Turku, Turku, 20014, Finland.,Department of Clinical Physiology & Nuclear Medicine, Turku University Hospital, Turku, 20014, Finland
| | - Mika Kähönen
- Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Department of Clinical Physiology, Tampere University Hospital, Tampere, 33521, Finland
| | - Laura Kananen
- Faculty of Medicine & Health Technology, & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520,Finland.,Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Juulia Jylhävä
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden.,Faculty of Social Sciences (Health Sciences), & Gerontology Research Center, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Sara Hägg
- Department of Medical Epidemiology & Biostatistics, Karolinska Institutet, Stockholm, 171 77, Sweden
| | - Thomas Delerue
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, D-85764,, Germany.,German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, 68167, Germany.,Competence Cluster for Nutrition & Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, 07743, Germany.,SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Augsburg, 86156, Germany.,Clinical Institute of Medical & Chemical Laboratory Diagnostics, Medical University of Graz, Graz, 8010, Austria
| | - Riitta Luoto
- The Social Insurance Institute of Finland (Kela), Helsinki, 00250, Finland.,The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland
| | - Jani Raitanen
- The UKK Institute for Health Promotion Research, Kaupinpuistonkatu 1, Tampere, 33500, Finland.,Faculty of Social Sciences (Health Sciences), Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
| | - Elina Sillanpää
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland.,Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Eija K Laakkonen
- Gerontology Research Center & Faculty of Sport & Health Sciences, University of Jyväskylä, Jyväskylä, 40014, Finland
| | - Aino Heikkinen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, 00014, Finland
| | - Emma Raitoharju
- Molecular Epidemiology, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland.,Finnish Cardiovascular Research Center Tampere, Faculty of Medicine & Health Technology, Tampere University, Arvo Ylpön katu 34, Tampere, 33520, Finland
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19
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Akbari V, Garant JM, O'Neill K, Pandoh P, Moore R, Marra MA, Hirst M, Jones SJM. Genome-wide detection of imprinted differentially methylated regions using nanopore sequencing. eLife 2022; 11:77898. [PMID: 35787786 PMCID: PMC9255983 DOI: 10.7554/elife.77898] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 06/16/2022] [Indexed: 01/02/2023] Open
Abstract
Imprinting is a critical part of normal embryonic development in mammals, controlled by defined parent-of-origin (PofO) differentially methylated regions (DMRs) known as imprinting control regions. Direct nanopore sequencing of DNA provides a means to detect allelic methylation and to overcome the drawbacks of methylation array and short-read technologies. Here, we used publicly available nanopore sequencing data for 12 standard B-lymphocyte cell lines to acquire the genome-wide mapping of imprinted intervals in humans. Using the sequencing data, we were able to phase 95% of the human methylome and detect 94% of the previously well-characterized, imprinted DMRs. In addition, we found 42 novel imprinted DMRs (16 germline and 26 somatic), which were confirmed using whole-genome bisulfite sequencing (WGBS) data. Analysis of WGBS data in mouse (Mus musculus), rhesus monkey (Macaca mulatta), and chimpanzee (Pan troglodytes) suggested that 17 of these imprinted DMRs are conserved. Some of the novel imprinted intervals are within or close to imprinted genes without a known DMR. We also detected subtle parental methylation bias, spanning several kilobases at seven known imprinted clusters. At these blocks, hypermethylation occurs at the gene body of expressed allele(s) with mutually exclusive H3K36me3 and H3K27me3 allelic histone marks. These results expand upon our current knowledge of imprinting and the potential of nanopore sequencing to identify imprinting regions using only parent-offspring trios, as opposed to the large multi-generational pedigrees that have previously been required.
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Affiliation(s)
- Vahid Akbari
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Jean-Michel Garant
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada
| | - Kieran O'Neill
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada
| | - Pawan Pandoh
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada
| | - Richard Moore
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada
| | - Marco A Marra
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, Canada
| | - Martin Hirst
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada.,Department of Microbiology and Immunology, Michael Smith Laboratories, University of British Columbia, Vancouver, Canada
| | - Steven J M Jones
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, Canada.,Department of Medical Genetics, University of British Columbia, Vancouver, Canada
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20
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Yépez VA, Gusic M, Kopajtich R, Mertes C, Smith NH, Alston CL, Ban R, Beblo S, Berutti R, Blessing H, Ciara E, Distelmaier F, Freisinger P, Häberle J, Hayflick SJ, Hempel M, Itkis YS, Kishita Y, Klopstock T, Krylova TD, Lamperti C, Lenz D, Makowski C, Mosegaard S, Müller MF, Muñoz-Pujol G, Nadel A, Ohtake A, Okazaki Y, Procopio E, Schwarzmayr T, Smet J, Staufner C, Stenton SL, Strom TM, Terrile C, Tort F, Van Coster R, Vanlander A, Wagner M, Xu M, Fang F, Ghezzi D, Mayr JA, Piekutowska-Abramczuk D, Ribes A, Rötig A, Taylor RW, Wortmann SB, Murayama K, Meitinger T, Gagneur J, Prokisch H. Clinical implementation of RNA sequencing for Mendelian disease diagnostics. Genome Med 2022; 14:38. [PMID: 35379322 PMCID: PMC8981716 DOI: 10.1186/s13073-022-01019-9] [Citation(s) in RCA: 75] [Impact Index Per Article: 37.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 02/03/2022] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND Lack of functional evidence hampers variant interpretation, leaving a large proportion of individuals with a suspected Mendelian disorder without genetic diagnosis after whole genome or whole exome sequencing (WES). Research studies advocate to further sequence transcriptomes to directly and systematically probe gene expression defects. However, collection of additional biopsies and establishment of lab workflows, analytical pipelines, and defined concepts in clinical interpretation of aberrant gene expression are still needed for adopting RNA sequencing (RNA-seq) in routine diagnostics. METHODS We implemented an automated RNA-seq protocol and a computational workflow with which we analyzed skin fibroblasts of 303 individuals with a suspected mitochondrial disease that previously underwent WES. We also assessed through simulations how aberrant expression and mono-allelic expression tests depend on RNA-seq coverage. RESULTS We detected on average 12,500 genes per sample including around 60% of all disease genes-a coverage substantially higher than with whole blood, supporting the use of skin biopsies. We prioritized genes demonstrating aberrant expression, aberrant splicing, or mono-allelic expression. The pipeline required less than 1 week from sample preparation to result reporting and provided a median of eight disease-associated genes per patient for inspection. A genetic diagnosis was established for 16% of the 205 WES-inconclusive cases. Detection of aberrant expression was a major contributor to diagnosis including instances of 50% reduction, which, together with mono-allelic expression, allowed for the diagnosis of dominant disorders caused by haploinsufficiency. Moreover, calling aberrant splicing and variants from RNA-seq data enabled detecting and validating splice-disrupting variants, of which the majority fell outside WES-covered regions. CONCLUSION Together, these results show that streamlined experimental and computational processes can accelerate the implementation of RNA-seq in routine diagnostics.
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Affiliation(s)
- Vicente A. Yépez
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Garching, Germany
- Quantitative Biosciences Munich, Department of Biochemistry, Ludwig-Maximilians-Universität, Munich, Germany
| | - Mirjana Gusic
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partner site Munich Heart Alliance, Munich, Germany
| | - Robert Kopajtich
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Christian Mertes
- Department of Informatics, Technical University of Munich, Garching, Germany
| | - Nicholas H. Smith
- Department of Informatics, Technical University of Munich, Garching, Germany
| | - Charlotte L. Alston
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH UK
- NHS Highly Specialised Services for Rare Mitochondrial Disorders, Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Foundation Trust, Queen Victoria Road, Newcastle upon Tyne, NE1 4LP UK
| | - Rui Ban
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Pediatric Neurology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Skadi Beblo
- Department of Women and Child Health, Hospital for Children and Adolescents, Center for Pediatric Research Leipzig (CPL), Center for Rare Diseases, University Hospitals, University of Leipzig, Leipzig, Germany
| | - Riccardo Berutti
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Holger Blessing
- Department for Inborn Metabolic Diseases, Children’s and Adolescents’ Hospital, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Elżbieta Ciara
- Department of Medical Genetics, Children’s Memorial Health Institute, Warsaw, Poland
| | - Felix Distelmaier
- Department of General Pediatrics, Neonatology and Pediatric Cardiology, Heinrich-Heine-University, Düsseldorf, Germany
| | - Peter Freisinger
- Department of Pediatrics, Klinikum Reutlingen, Reutlingen, Germany
| | - Johannes Häberle
- University Children’s Hospital Zurich and Children’s Research Centre, Zürich, Switzerland
| | - Susan J. Hayflick
- Department of Molecular and Medical Genetics, Oregon Health & Science University, Portland, USA
| | - Maja Hempel
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | | | - Yoshihito Kishita
- Diagnostics and Therapeutics of Intractable Diseases, Intractable Disease Research Center, Juntendo University, Graduate School of Medicine, Tokyo, Japan
- Department of Life Science, Faculty of Science and Engineering, Kindai University, Osaka, Japan
| | - Thomas Klopstock
- Department of Neurology, Friedrich-Baur-Institute, University Hospital, Ludwig-Maximilians-Universität, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | | | - Costanza Lamperti
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) Istituto Neurologico Carlo Besta, Milan, Italy
| | - Dominic Lenz
- Division of Neuropediatrics and Pediatric Metabolic Medicine, Center for Pediatric and Adolescent Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Christine Makowski
- Department of Pediatrics, Technical University of Munich, Munich, Germany
| | - Signe Mosegaard
- Research Unit for Molecular Medicine, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Michaela F. Müller
- Department of Informatics, Technical University of Munich, Garching, Germany
| | - Gerard Muñoz-Pujol
- Section of Inborn Errors of Metabolism-IBC, Department of Biochemistry and Molecular Genetics, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Agnieszka Nadel
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Akira Ohtake
- Department of Pediatrics & Clinical Genomics, Faculty of Medicine, Saitama Medical University, Saitama, Japan
- Center for Intractable Diseases, Saitama Medical University Hospital, Saitama, Japan
| | - Yasushi Okazaki
- Diagnostics and Therapeutics of Intractable Diseases, Intractable Disease Research Center, Juntendo University, Graduate School of Medicine, Tokyo, Japan
| | - Elena Procopio
- Inborn Metabolic and Muscular Disorders Unit, Anna Meyer Children Hospital, Florence, Italy
| | - Thomas Schwarzmayr
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Joél Smet
- Department of Pediatric Neurology and Metabolism, Ghent University Hospital, Ghent, Belgium
| | - Christian Staufner
- Division of Neuropediatrics and Pediatric Metabolic Medicine, Center for Pediatric and Adolescent Medicine, University Hospital Heidelberg, Heidelberg, Germany
| | - Sarah L. Stenton
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Tim M. Strom
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Caterina Terrile
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Frederic Tort
- Section of Inborn Errors of Metabolism-IBC, Department of Biochemistry and Molecular Genetics, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Rudy Van Coster
- Department of Pediatric Neurology and Metabolism, Ghent University Hospital, Ghent, Belgium
| | - Arnaud Vanlander
- Department of Pediatric Neurology and Metabolism, Ghent University Hospital, Ghent, Belgium
| | - Matias Wagner
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
| | - Manting Xu
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Pediatric Neurology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Fang Fang
- Department of Pediatric Neurology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
| | - Daniele Ghezzi
- Unit of Medical Genetics and Neurogenetics, Fondazione IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) Istituto Neurologico Carlo Besta, Milan, Italy
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy
| | - Johannes A. Mayr
- University Children’s Hospital, Paracelsus Medical University Salzburg, Salzburg, Austria
| | | | - Antonia Ribes
- Section of Inborn Errors of Metabolism-IBC, Department of Biochemistry and Molecular Genetics, Hospital Clínic, IDIBAPS, CIBERER, Barcelona, Spain
| | - Agnès Rötig
- Université de Paris, Institut Imagine, INSERM UMR 1163, Paris, France
| | - Robert W. Taylor
- Wellcome Centre for Mitochondrial Research, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle upon Tyne, NE2 4HH UK
- NHS Highly Specialised Services for Rare Mitochondrial Disorders, Royal Victoria Infirmary, Newcastle upon Tyne Hospitals NHS Foundation Trust, Queen Victoria Road, Newcastle upon Tyne, NE1 4LP UK
| | - Saskia B. Wortmann
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- University Children’s Hospital, Paracelsus Medical University Salzburg, Salzburg, Austria
- Amalia Children’s Hospital, Radboudumc Nijmegen, Nijmegen, The Netherlands
| | - Kei Murayama
- Department of Metabolism, Chiba Children’s Hospital, Chiba, Japan
| | - Thomas Meitinger
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
| | - Julien Gagneur
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Department of Informatics, Technical University of Munich, Garching, Germany
- Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Holger Prokisch
- Institute of Human Genetics, School of Medicine, Technical University of Munich, Munich, Germany
- Institute of Neurogenomics, Helmholtz Zentrum München, Neuherberg, Germany
- Department of Pediatric Neurology, Beijing Children’s Hospital, Capital Medical University, National Center for Children’s Health, Beijing, China
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21
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Genome-wide DNA methylation patterns reveal clinically relevant predictive and prognostic subtypes in human osteosarcoma. Commun Biol 2022; 5:213. [PMID: 35260776 PMCID: PMC8904843 DOI: 10.1038/s42003-022-03117-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 01/24/2022] [Indexed: 12/14/2022] Open
Abstract
Aberrant methylation of genomic DNA has been reported in many cancers. Specific DNA methylation patterns have been shown to provide clinically useful prognostic information and define molecular disease subtypes with different response to therapy and long-term outcome. Osteosarcoma is an aggressive malignancy for which approximately half of tumors recur following standard combined surgical resection and chemotherapy. No accepted prognostic factor save tumor necrosis in response to adjuvant therapy currently exists, and traditional genomic studies have thus far failed to identify meaningful clinical associations. We studied the genome-wide methylation state of primary tumors and tested how they predict patient outcomes. We discovered relative genomic hypomethylation to be strongly predictive of response to standard chemotherapy. Recurrence and survival were also associated with genomic methylation, but through more site-specific patterns. Furthermore, the methylation patterns were reproducible in three small independent clinical datasets. Downstream transcriptional, in vitro, and pharmacogenomic analysis provides insight into the clinical translation of the methylation patterns. Our findings suggest the assessment of genomic methylation may represent a strategy for stratifying patients for the application of alternative therapies.
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22
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Tanaka K, Besson V, Rivagorda M, Oury F, Marazzi G, Sassoon DA. Paternally expressed gene 3 (Pw1/Peg3) promotes sexual dimorphism in metabolism and behavior. PLoS Genet 2022; 18:e1010003. [PMID: 35025875 PMCID: PMC8791484 DOI: 10.1371/journal.pgen.1010003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 01/26/2022] [Accepted: 12/20/2021] [Indexed: 01/06/2023] Open
Abstract
The paternally expressed gene 3 (Pw1/Peg3) is a mammalian-specific parentally imprinted gene expressed in stem/progenitor cells of the brain and endocrine tissues. Here, we compared phenotypic characteristics in Pw1/Peg3 deficient male and female mice. Our findings indicate that Pw1/Peg3 is a key player for the determination of sexual dimorphism in metabolism and behavior. Mice carrying a paternally inherited Pw1/Peg3 mutant allele manifested postnatal deficits in GH/IGF dependent growth before weaning, sex steroid dependent masculinization during puberty, and insulin dependent fat accumulation in adulthood. As a result, Pw1/Peg3 deficient mice develop a sex-dependent global shift of body metabolism towards accelerated adiposity, diabetic-like insulin resistance, and fatty liver. Furthermore, Pw1/Peg3 deficient males displayed reduced social dominance and competitiveness concomitant with alterations in the vasopressinergic architecture in the brain. This study demonstrates that Pw1/Peg3 provides an epigenetic context that promotes male-specific characteristics through sex steroid pathways during postnatal development. Pw1/Peg3 is under parental specific epigenetic regulation. We propose that Pw1/Peg3 confers a selective advantage in mammals by regulating sexual dimorphism. To address this question, we examined the consequences of Pw1/Peg3 loss of function in mice in an age- and sex-dependent context and found that Pw1/Peg3 mutants display reduced sexual dimorphism in growth, metabolism and behaviors. Our findings support the intralocus sexual conflict model of genomic imprinting where it contributes in sexual differentiation. Furthermore, our observations provide a unifying role of sex steroid signaling as a common property of Pw1/Peg3 expressing stem/progenitor cells and differentiated endocrine cells, both of which remain proliferative in response to gonadal hormones in adult life.
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Affiliation(s)
- Karo Tanaka
- Stem Cells and Regenerative Medicine, Institute of Cardiometabolism and Nutrition (ICAN), INSERM U1166, University of Pierre and Marie Curie Paris VI, Paris, France
| | - Vanessa Besson
- Stem Cells and Regenerative Medicine, Institute of Cardiometabolism and Nutrition (ICAN), INSERM U1166, University of Pierre and Marie Curie Paris VI, Paris, France
| | - Manon Rivagorda
- Hormonal Regulation of Brain Development and Functions, INSERM U1151, Institut Necker Enfants Malades, Paris, France
| | - Franck Oury
- Hormonal Regulation of Brain Development and Functions, INSERM U1151, Institut Necker Enfants Malades, Paris, France
| | - Giovanna Marazzi
- Stem Cells and Regenerative Medicine, Institute of Cardiometabolism and Nutrition (ICAN), INSERM U1166, University of Pierre and Marie Curie Paris VI, Paris, France
| | - David A. Sassoon
- Stem Cells and Regenerative Medicine, Institute of Cardiometabolism and Nutrition (ICAN), INSERM U1166, University of Pierre and Marie Curie Paris VI, Paris, France
- * E-mail:
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23
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Lindsly S, Jia W, Chen H, Liu S, Ronquist S, Chen C, Wen X, Stansbury C, Dotson GA, Ryan C, Rehemtulla A, Omenn GS, Wicha M, Li SC, Muir L, Rajapakse I. Functional organization of the maternal and paternal human 4D Nucleome. iScience 2021; 24:103452. [PMID: 34877507 PMCID: PMC8633971 DOI: 10.1016/j.isci.2021.103452] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 10/16/2021] [Accepted: 11/09/2021] [Indexed: 11/19/2022] Open
Abstract
Every human somatic cell inherits a maternal and a paternal genome, which work together to give rise to cellular phenotypes. However, the allele-specific relationship between gene expression and genome structure through the cell cycle is largely unknown. By integrating haplotype-resolved genome-wide chromosome conformation capture, mature and nascent mRNA, and protein binding data from a B lymphoblastoid cell line, we investigate this relationship both globally and locally. We introduce the maternal and paternal 4D Nucleome, enabling detailed analysis of the mechanisms and dynamics of genome structure and gene function for diploid organisms. Our analyses find significant coordination between allelic expression biases and local genome conformation, and notably absent expression bias in universally essential cell cycle and glycolysis genes. We propose a model in which coordinated biallelic expression reflects prioritized preservation of essential gene sets.
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Affiliation(s)
- Stephen Lindsly
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Wenlong Jia
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Haiming Chen
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Sijia Liu
- MIT-IBM Watson AI Lab, IBM Research, Cambridge, MA 02142, USA
| | - Scott Ronquist
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Can Chen
- Department of Mathematics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA
| | - Xingzhao Wen
- Department of Bioengineering, University of California San Diego, La Jolla, CA 92093, USA
| | - Cooper Stansbury
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Gabrielle A. Dotson
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Charles Ryan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Medical Scientist Training Program, University of Michigan, Ann Arbor, MI 48109, USA
- Program in Cellular and Molecular Biology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Alnawaz Rehemtulla
- Department of Hematology/Oncology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Gilbert S. Omenn
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Internal Medicine, Human Genetics, and School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Max Wicha
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Hematology/Oncology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Shuai Cheng Li
- Department of Computer Science, City University of Hong Kong, Kowloon, Hong Kong
| | - Lindsey Muir
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Indika Rajapakse
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Mathematics, University of Michigan, Ann Arbor, MI 48109, USA
- Corresponding author
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24
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Claussnitzer M, Susztak K. Gaining insight into metabolic diseases from human genetic discoveries. Trends Genet 2021; 37:1081-1094. [PMID: 34315631 PMCID: PMC8578350 DOI: 10.1016/j.tig.2021.07.005] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 06/29/2021] [Accepted: 07/05/2021] [Indexed: 12/30/2022]
Abstract
Human large-scale genetic association studies have identified sequence variations at thousands of genetic risk loci that are more common in patients with diverse metabolic disease compared with healthy controls. While these genetic associations have been replicated in multiple large cohorts and sometimes can explain up to 50% of heritability, the molecular and cellular mechanisms affected by common genetic variation associated with metabolic disease remains mostly unknown. A variety of new genome-wide data types, in conjunction with novel biostatistical and computational analytical methodologies and foundational experimental technologies, are paving the way for a principled approach to systematic variant-to-function (V2F) studies for metabolic diseases, turning associated regions into causal variants, cell types and states of action, effector genes, and cellular and physiological mechanisms. Identification of new target genes and cellular programs for metabolic risk loci will improve mechanistic understanding of disease biology and identification of novel therapeutic strategies.
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Affiliation(s)
- Melina Claussnitzer
- Beth Israel Deaconess Medical Center, The Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
| | - Katalin Susztak
- Department of Medicine and Genetics, University of Pennsylvania, Philadelphia, PA 19104, USA.
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25
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Sherbina K, León-Novelo LG, Nuzhdin SV, McIntyre LM, Marroni F. Power calculator for detecting allelic imbalance using hierarchical Bayesian model. BMC Res Notes 2021; 14:436. [PMID: 34838135 PMCID: PMC8626927 DOI: 10.1186/s13104-021-05851-x] [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: 07/16/2021] [Accepted: 11/15/2021] [Indexed: 11/10/2022] Open
Abstract
OBJECTIVE Allelic imbalance (AI) is the differential expression of the two alleles in a diploid. AI can vary between tissues, treatments, and environments. Methods for testing AI exist, but methods are needed to estimate type I error and power for detecting AI and difference of AI between conditions. As the costs of the technology plummet, what is more important: reads or replicates? RESULTS We find that a minimum of 2400, 480, and 240 allele specific reads divided equally among 12, 5, and 3 replicates is needed to detect a 10, 20, and 30%, respectively, deviation from allelic balance in a condition with power > 80%. A minimum of 960 and 240 allele specific reads divided equally among 8 replicates is needed to detect a 20 or 30% difference in AI between conditions with comparable power. Higher numbers of replicates increase power more than adding coverage without affecting type I error. We provide a Python package that enables simulation of AI scenarios and enables individuals to estimate type I error and power in detecting AI and differences in AI between conditions.
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Affiliation(s)
- Katrina Sherbina
- Quantitative and Computational Biology Section, University of Southern California, Los Angeles, CA, 90046, USA
| | - Luis G León-Novelo
- Department of Biostatistics and Data Science, The University of Texas Health Science Center at Houston-School of Public Health, Houston, TX, 77030, USA
| | - Sergey V Nuzhdin
- Molecular and Computational Biology Section, University of Southern California, Los Angeles, CA, 90046, USA
| | - Lauren M McIntyre
- Genetics Institute and Department of Molecular Genetics and Microbiology, University of Florida, Gainesville, FL, 32603, USA
| | - Fabio Marroni
- Dipartimento di Scienze Agroalimentari, Ambientali e Animali, Università di Udine, 33100, Udine, Italy.
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26
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Jang J, Amblard F, Ghim CM. Heterogeneity is not always a source of noise: Stochastic gene expression in regulatory heterozygote. Phys Rev E 2021; 104:044401. [PMID: 34781474 DOI: 10.1103/physreve.104.044401] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2020] [Accepted: 09/16/2021] [Indexed: 01/22/2023]
Abstract
Zygosity of diploid genome (i.e., degree to which two parental alleles of a gene have varied genetic sequences) adds another dimension to stochastic gene expression. The allelic imbalance in chromatin accessibility or divergence in regulatory sequences leads to fitness effects but the quantitative aspects thereof are largely left unexplored. We investigate diploid gene expression systems with homozygous (the same) and heterozygous (varied) combination of alleles in cis-regulatory sequences, not in structural gene loci, and characterize the zygosity-associated stochastic fluctuations in protein abundance. An emerging feat of heterozygosity is its counterintuitive capacity for genetic noise control. Especially when the noise is dominantly contributed to by the fluctuations in duty cycle ("reliability") rather than in process speed ("productivity") of gene expression machinery, its interallelic discrepancy acts to reduce the gene expression noise. These findings offer a novel insight into the rich repertoire of balancing selection enriched in the regulatory elements of immune response genes.
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Affiliation(s)
- Juneil Jang
- Department of Biomedical Engineering, Ulsan National Institute of Science & Technology, Ulsan 44919, Republic of Korea
| | - François Amblard
- Center for Soft and Living Matter, Institute for Basic Science, Ulsan 44919, Republic of Korea.,Department of Physics, Ulsan National Institute of Science & Technology, Ulsan 44919, Republic of Korea
| | - C-M Ghim
- Department of Biomedical Engineering, Ulsan National Institute of Science & Technology, Ulsan 44919, Republic of Korea.,Department of Physics, Ulsan National Institute of Science & Technology, Ulsan 44919, Republic of Korea
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27
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Wang T, Li J, Yang L, Wu M, Ma Q. The Role of Long Non-coding RNAs in Human Imprinting Disorders: Prospective Therapeutic Targets. Front Cell Dev Biol 2021; 9:730014. [PMID: 34760887 PMCID: PMC8573313 DOI: 10.3389/fcell.2021.730014] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 09/23/2021] [Indexed: 12/26/2022] Open
Abstract
Genomic imprinting is a term used for an intergenerational epigenetic inheritance and involves a subset of genes expressed in a parent-of-origin-dependent way. Imprinted genes are expressed preferentially from either the paternally or maternally inherited allele. Long non-coding RNAs play essential roles in regulating this allele-specific expression. In several well-studied imprinting clusters, long non-coding RNAs have been found to be essential in regulating temporal- and spatial-specific establishment and maintenance of imprinting patterns. Furthermore, recent insights into the epigenetic pathological mechanisms underlying human genomic imprinting disorders suggest that allele-specific expressed imprinted long non-coding RNAs serve as an upstream regulator of the expression of other protein-coding or non-coding imprinted genes in the same cluster. Aberrantly expressed long non-coding RNAs result in bi-allelic expression or silencing of neighboring imprinted genes. Here, we review the emerging roles of long non-coding RNAs in regulating the expression of imprinted genes, especially in human imprinting disorders, and discuss three strategies targeting the central long non-coding RNA UBE3A-ATS for the purpose of developing therapies for the imprinting disorders Prader-Willi syndrome and Angelman syndrome. In summary, a better understanding of long non-coding RNA-related mechanisms is key to the development of potential therapeutic targets for human imprinting disorders.
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Affiliation(s)
- Tingxuan Wang
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Jianjian Li
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Liuyi Yang
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Manyin Wu
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Qing Ma
- Shenzhen Key Laboratory of Synthetic Genomics, Guangdong Provincial Key Laboratory of Synthetic Genomics, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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28
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Identification of Nephrogenic Therapeutic Biomarkers of Wilms Tumor Using Machine Learning. JOURNAL OF ONCOLOGY 2021; 2021:6471169. [PMID: 34422051 PMCID: PMC8371641 DOI: 10.1155/2021/6471169] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 06/22/2021] [Accepted: 07/24/2021] [Indexed: 01/18/2023]
Abstract
Wilms tumor is the most common renal malignancy in children, with a survival rate of more than 90%; however, treatment outcomes for certain patient subgroups, such as those with bilateral and recurrent diseases, remain significantly below this survival rate. Therefore, it remains essential to identify new biomarkers and develop effective therapeutic strategies. Based on the Therapeutically Applicable Research to Generate Effective Treatments and Gene Expression Omnibus RNA microarray datasets, we have identified eight differentially expressed genes in Wilms tumors as renal-specific in 33 randomly selected adult tumors. The risk model, constructed using survival forest and multivariate Cox regression, can effectively predict the prognosis; the risk score is an independent prognostic factor in Wilms tumor. Gene set enrichment analysis showed that most of the signature genes were involved in regulating human development-related pathways. At the same time, patients in the high-risk group exhibited more sensitive immunological and chemotherapeutic properties than those in the low-risk group. These results provide new insights into personalized and precise Wilms tumor treatment strategies.
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29
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Wu W, Lovett JL, Shedden K, Strassmann BI, Vincenz C. Targeted RNA-seq improves efficiency, resolution, and accuracy of allele specific expression for human term placentas. G3 (BETHESDA, MD.) 2021; 11:jkab176. [PMID: 34009305 PMCID: PMC8496276 DOI: 10.1093/g3journal/jkab176] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Accepted: 05/12/2021] [Indexed: 12/30/2022]
Abstract
Genomic imprinting is an epigenetic mechanism that results in allele-specific expression (ASE) based on the parent of origin. It is known to play a role in the prenatal and postnatal allocation of maternal resources in mammals. ASE detected by whole transcriptome RNA-seq (wht-RNAseq) has been widely used to analyze imprinted genes using reciprocal crosses in mice to generate large numbers of informative SNPs. Studies in humans are more challenging due to the paucity of SNPs and the poor preservation of RNA in term placentas and other tissues. Targeted RNA-seq (tar-RNAseq) can potentially mitigate these challenges by focusing sequencing resources on the regions of interest in the transcriptome. Here, we compared tar-RNAseq and wht-RNAseq in a study of ASE in known imprinted genes in placental tissue collected from a healthy human cohort in Mali, West Africa. As expected, tar-RNAseq substantially improved the coverage of SNPs. Compared to wht-RNAseq, tar-RNAseq produced on average four times more SNPs in twice as many genes per sample and read depth at the SNPs increased fourfold. In previous research on humans, discordant ASE values for SNPs of the same gene have limited the ability to accurately quantify ASE. We show that tar-RNAseq reduces this limitation as it unexpectedly increased the concordance of ASE between SNPs of the same gene, even in cases of degraded RNA. Studies aimed at discovering associations between individual variation in ASE and phenotypes in mammals and flowering plants will benefit from the improved power and accuracy of tar-RNAseq.
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Affiliation(s)
- Weisheng Wu
- BRCF Bioinformatics Core, University of Michigan, Ann Arbor, MI 48109, USA
| | - Jennie L Lovett
- Department of Anthropology, University of Michigan, Ann Arbor, MI 48109, USA
| | - Kerby Shedden
- Department of Statistics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Beverly I Strassmann
- Department of Anthropology, University of Michigan, Ann Arbor, MI 48109, USA
- Research Center for Group Dynamics, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
| | - Claudius Vincenz
- Research Center for Group Dynamics, Institute for Social Research, University of Michigan, Ann Arbor, MI 48106, USA
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30
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Li J, Chen W, Li D, Gu S, Liu X, Dong Y, Jin L, Zhang C, Li S. Conservation of Imprinting and Methylation of MKRN3, MAGEL2 and NDN Genes in Cattle. Animals (Basel) 2021; 11:1985. [PMID: 34359112 PMCID: PMC8300276 DOI: 10.3390/ani11071985] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 06/25/2021] [Accepted: 06/30/2021] [Indexed: 01/02/2023] Open
Abstract
Genomic imprinting is the epigenetic mechanism of transcriptional regulation that involves differential DNA methylation modification. Comparative analysis of imprinted genes between species can help us to investigate the biological significance and regulatory mechanisms of genomic imprinting. MKRN3, MAGEL2 and NDN are three maternally imprinted genes identified in the human PWS/AS imprinted locus. This study aimed to assess the allelic expression of MKRN3, MAGEL2 and NDN and to examine the differentially methylated regions (DMRs) of bovine PWS/AS imprinted domains. An expressed single-nucleotide polymorphism (SNP)-based approach was used to investigate the allelic expression of MKRN3, MAGEL2 and NDN genes in bovine adult tissues and placenta. Consistent with the expression in humans and mice, we found that the MKRN3, MAGEL2 and NDN genes exhibit monoallelic expression in bovine somatic tissues and the paternal allele expressed in the bovine placenta. Three DMRs, PWS-IC, MKRN3 and NDN DMR, were identified in the bovine PWS/AS imprinted region by analysis of the DNA methylation status in bovine tissues using the bisulfite sequencing method and were located in the promoter and exon 1 of the SNRPN gene, NDN promoter and 5' untranslated region (5'UTR) of MKRN3 gene, respectively. The PWS-IC DMR is a primary DMR inherited from the male or female gamete, but NDN and MKRN3 DMR are secondary DMRs that occurred after fertilization by examining the methylation status in gametes.
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Affiliation(s)
- Junliang Li
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Weina Chen
- Department of Traditional Chinese Medicine, Hebei University, Baoding 071000, China;
| | - Dongjie Li
- College of Bioscience and Bioengineering, Hebei University of Science and Technology, Shijiazhuang 050081, China;
| | - Shukai Gu
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Xiaoqian Liu
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Yanqiu Dong
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Lanjie Jin
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Cui Zhang
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
| | - Shijie Li
- College of Life Science, Agricultural University of Hebei, Baoding 071000, China; (J.L.); (S.G.); (X.L.); (Y.D.); (L.J.)
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31
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Lee M, Lee G, Kang HG, Suh JS. New susceptible locus, rs9428555, is associated with pediatric-onset immunoglobulin A nephropathy and immunoglobulin A vasculitis in Koreans. Genes Genomics 2021; 43:1049-1057. [PMID: 34146253 DOI: 10.1007/s13258-021-01120-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Accepted: 06/06/2021] [Indexed: 10/21/2022]
Abstract
BACKGROUND Immunoglobulin A nephropathy (IgAN) is one of the most common primary forms of glomerulonephritis, while IgA vasculitis (IgAV) is the most common systemic vasculitis in children. OBJECTIVE Herein we aimed to uncover single nucleotide polymorphism (SNP) markers associated with these two related diseases by applying association tests and Sanger sequencing. METHODS Within the discovery stage, genomic DNA in blood samples from 101 enrolled patients were genotyped by the Korean Biobank Array. Association tests were performed with 397 Korean reference genomes. In the validation stage, 26 independent samples were genotyped by Sanger sequencing. RESULTS Four SNPs were identified (P < 5 × 10-8) in the discovery stage. To determine whether the genotypes determined by SNP array were accurate, additional genotyping via Sanger sequencing was performed. As a result, only one SNP, rs9428555, was properly genotyped. In the validation stage, the minor allele (A > G) was found in as many as 15 out of 26 samples (minor allele frequency = 0.288), even though this minor allele is rare in East Asians (< 3%). CONCLUSIONS We found rs9428555 as a novel susceptible locus associated with the development of both IgAN and IgAV in Koreans. Though we cannot conclude rs9428555 is the unique susceptible locus of IgAN and IgAV, it is likely a good marker as the minor allele of this SNP occurred much more often in the patient group here versus within East Asians as a whole.
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Affiliation(s)
- Minho Lee
- Department of Life Science, Dongguk University-Seoul, Ilsandong-gu, Goyang-si, Gyeonggi-do, Republic of Korea
| | - Gunhee Lee
- Department of Biomedicine & Health Sciences, Graduate School, The Catholic University of Korea, Seoul, Republic of Korea
| | - Hee Gyung Kang
- Department of Pediatrics, Seoul National University, College of Medicine and Seoul National University Children's Hospital, Seoul, Republic of Korea
| | - Jin-Soon Suh
- Department of Pediatrics, Bucheon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Bucheon-Si, Gyeonggi-do, Republic of Korea.
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32
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Lorenzi L, Chiu HS, Avila Cobos F, Gross S, Volders PJ, Cannoodt R, Nuytens J, Vanderheyden K, Anckaert J, Lefever S, Tay AP, de Bony EJ, Trypsteen W, Gysens F, Vromman M, Goovaerts T, Hansen TB, Kuersten S, Nijs N, Taghon T, Vermaelen K, Bracke KR, Saeys Y, De Meyer T, Deshpande NP, Anande G, Chen TW, Wilkins MR, Unnikrishnan A, De Preter K, Kjems J, Koster J, Schroth GP, Vandesompele J, Sumazin P, Mestdagh P. The RNA Atlas expands the catalog of human non-coding RNAs. Nat Biotechnol 2021; 39:1453-1465. [PMID: 34140680 DOI: 10.1038/s41587-021-00936-1] [Citation(s) in RCA: 65] [Impact Index Per Article: 21.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2019] [Accepted: 04/26/2021] [Indexed: 12/24/2022]
Abstract
Existing compendia of non-coding RNA (ncRNA) are incomplete, in part because they are derived almost exclusively from small and polyadenylated RNAs. Here we present a more comprehensive atlas of the human transcriptome, which includes small and polyA RNA as well as total RNA from 300 human tissues and cell lines. We report thousands of previously uncharacterized RNAs, increasing the number of documented ncRNAs by approximately 8%. To infer functional regulation by known and newly characterized ncRNAs, we exploited pre-mRNA abundance estimates from total RNA sequencing, revealing 316 microRNAs and 3,310 long non-coding RNAs with multiple lines of evidence for roles in regulating protein-coding genes and pathways. Our study both refines and expands the current catalog of human ncRNAs and their regulatory interactions. All data, analyses and results are available for download and interrogation in the R2 web portal, serving as a basis for future exploration of RNA biology and function.
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Affiliation(s)
- Lucia Lorenzi
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Hua-Sheng Chiu
- Texas Children's Cancer Center, Baylor College of Medicine, Houston, TX, USA
| | - Francisco Avila Cobos
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | | | - Pieter-Jan Volders
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium.,VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium
| | - Robrecht Cannoodt
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium.,Data Mining and Modelling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium.,Department of Applied Mathematics, Computer Science, and Statistics, Ghent University, Ghent, Belgium.,Data Intuitive, Lebbeke, Belgium
| | - Justine Nuytens
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Katrien Vanderheyden
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Jasper Anckaert
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Steve Lefever
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Aidan P Tay
- Australian e-Health Research Centre, Commonwealth Scientific and Industrial Research Organisation, New South Wales, Sydney NSW, Australia.,Department of Biomedical Sciences, Macquarie University, New South Wales, Sydney NSW, Australia
| | - Eric J de Bony
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Wim Trypsteen
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Fien Gysens
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Marieke Vromman
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Tine Goovaerts
- Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
| | - Thomas Birkballe Hansen
- Interdisciplinary Nanoscience Centre (iNANO), Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | | | | | - Tom Taghon
- Department of Diagnostic Sciences, Ghent University, Ghent, Belgium
| | - Karim Vermaelen
- Department of Respiratory Medicine, Ghent University, Ghent, Belgium
| | - Ken R Bracke
- Department of Respiratory Medicine, Ghent University, Ghent, Belgium
| | - Yvan Saeys
- VIB-UGent Center for Medical Biotechnology, VIB, Ghent, Belgium.,Data Mining and Modelling for Biomedicine Group, VIB Center for Inflammation Research, Ghent, Belgium
| | - Tim De Meyer
- Cancer Research Institute Ghent (CRIG), Ghent, Belgium.,Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
| | - Nandan P Deshpande
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney NSW, Australia
| | - Govardhan Anande
- Adult Cancer Program, Lowy Cancer Research Centre, UNSW Sydney, Sydney NSW, Australia.,Prince of Wales Clinical School, UNSW Sydney, Sydney NSW, Australia
| | - Ting-Wen Chen
- Institute of Bioinformatics and Systems Biology, National Yang Ming Chiao Tung University, Hsinchu, Taiwan
| | - Marc R Wilkins
- Systems Biology Initiative, School of Biotechnology and Biomolecular Sciences, UNSW Sydney, Sydney NSW, Australia
| | - Ashwin Unnikrishnan
- Adult Cancer Program, Lowy Cancer Research Centre, UNSW Sydney, Sydney NSW, Australia.,Prince of Wales Clinical School, UNSW Sydney, Sydney NSW, Australia
| | - Katleen De Preter
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Jørgen Kjems
- Interdisciplinary Nanoscience Centre (iNANO), Department of Molecular Biology and Genetics, Aarhus University, Aarhus, Denmark
| | - Jan Koster
- Department of Oncogenomics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | | | - Jo Vandesompele
- Center for Medical Genetics, Ghent University, Ghent, Belgium.,Cancer Research Institute Ghent (CRIG), Ghent, Belgium
| | - Pavel Sumazin
- Texas Children's Cancer Center, Baylor College of Medicine, Houston, TX, USA.
| | - Pieter Mestdagh
- Center for Medical Genetics, Ghent University, Ghent, Belgium. .,Cancer Research Institute Ghent (CRIG), Ghent, Belgium.
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33
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Genome-wide detection of cytosine methylation by single molecule real-time sequencing. Proc Natl Acad Sci U S A 2021; 118:2019768118. [PMID: 33495335 PMCID: PMC7865158 DOI: 10.1073/pnas.2019768118] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Single molecule real-time (SMRT) sequencing theoretically offers the opportunity to directly assess certain base modifications of native DNA molecules without any prior chemical/enzymatic conversions and PCR amplification, using kinetic signals of a DNA polymerase. However, the kinetic signal changes caused by 5mC modification are extremely subtle. Hence, the robust genome-wide measurement of 5mC modification has not been achieved. We enhanced 5mC detection using SMRT sequencing by holistically analyzing kinetic signals of a DNA polymerase and sequence context for every base within a measurement window. We employed a convolutional neural network to train a methylation classification model, leading to genome-wide 5mC detection. The sensitivity and specificity reached 90% and 94%, with a 99% correlation of overall methylation level with bisulfite sequencing. 5-Methylcytosine (5mC) is an important type of epigenetic modification. Bisulfite sequencing (BS-seq) has limitations, such as severe DNA degradation. Using single molecule real-time sequencing, we developed a methodology to directly examine 5mC. This approach holistically examined kinetic signals of a DNA polymerase (including interpulse duration and pulse width) and sequence context for every nucleotide within a measurement window, termed the holistic kinetic (HK) model. The measurement window of each analyzed double-stranded DNA molecule comprised 21 nucleotides with a cytosine in a CpG site in the center. We used amplified DNA (unmethylated) and M.SssI-treated DNA (methylated) (M.SssI being a CpG methyltransferase) to train a convolutional neural network. The area under the curve for differentiating methylation states using such samples was up to 0.97. The sensitivity and specificity for genome-wide 5mC detection at single-base resolution reached 90% and 94%, respectively. The HK model was then tested on human–mouse hybrid fragments in which each member of the hybrid had a different methylation status. The model was also tested on human genomic DNA molecules extracted from various biological samples, such as buffy coat, placental, and tumoral tissues. The overall methylation levels deduced by the HK model were well correlated with those by BS-seq (r = 0.99; P < 0.0001) and allowed the measurement of allele-specific methylation patterns in imprinted genes. Taken together, this methodology has provided a system for simultaneous genome-wide genetic and epigenetic analyses.
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Abstract
Genomic imprinting is the monoallelic expression of a gene based on parent of origin and is a consequence of differential epigenetic marking between the male and female germlines. Canonically, genomic imprinting is mediated by allelic DNA methylation. However, recently it has been shown that maternal H3K27me3 can result in DNA methylation-independent imprinting, termed "noncanonical imprinting." In this review, we compare and contrast what is currently known about the underlying mechanisms, the role of endogenous retroviral elements, and the conservation of canonical and noncanonical genomic imprinting.
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Affiliation(s)
- Courtney W Hanna
- Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, United Kingdom
- Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, United Kingdom
| | - Gavin Kelsey
- Epigenetics Programme, Babraham Institute, Cambridge CB22 3AT, United Kingdom
- Centre for Trophoblast Research, University of Cambridge, Cambridge CB2 3EG, United Kingdom
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Scagliotti V, Esse R, Willis TL, Howard M, Carrus I, Lodge E, Andoniadou CL, Charalambous M. Dynamic Expression of Imprinted Genes in the Developing and Postnatal Pituitary Gland. Genes (Basel) 2021; 12:genes12040509. [PMID: 33808370 PMCID: PMC8066104 DOI: 10.3390/genes12040509] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2021] [Revised: 03/22/2021] [Accepted: 03/23/2021] [Indexed: 12/19/2022] Open
Abstract
In mammals, imprinted genes regulate many critical endocrine processes such as growth, the onset of puberty and maternal reproductive behaviour. Human imprinting disorders (IDs) are caused by genetic and epigenetic mechanisms that alter the expression dosage of imprinted genes. Due to improvements in diagnosis, increasing numbers of patients with IDs are now identified and monitored across their lifetimes. Seminal work has revealed that IDs have a strong endocrine component, yet the contribution of imprinted gene products in the development and function of the hypothalamo-pituitary axis are not well defined. Postnatal endocrine processes are dependent upon the production of hormones from the pituitary gland. While the actions of a few imprinted genes in pituitary development and function have been described, to date there has been no attempt to link the expression of these genes as a class to the formation and function of this essential organ. This is important because IDs show considerable overlap, and imprinted genes are known to define a transcriptional network related to organ growth. This knowledge deficit is partly due to technical difficulties in obtaining useful transcriptomic data from the pituitary gland, namely, its small size during development and cellular complexity in maturity. Here we utilise high-sensitivity RNA sequencing at the embryonic stages, and single-cell RNA sequencing data to describe the imprinted transcriptome of the pituitary gland. In concert, we provide a comprehensive literature review of the current knowledge of the role of imprinted genes in pituitary hormonal pathways and how these relate to IDs. We present new data that implicate imprinted gene networks in the development of the gland and in the stem cell compartment. Furthermore, we suggest novel roles for individual imprinted genes in the aetiology of IDs. Finally, we describe the dynamic regulation of imprinted genes in the pituitary gland of the pregnant mother, with implications for the regulation of maternal metabolic adaptations to pregnancy.
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Affiliation(s)
- Valeria Scagliotti
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London SE19RT, UK; (V.S.); (R.C.F.E.); (I.C.)
| | - Ruben Esse
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London SE19RT, UK; (V.S.); (R.C.F.E.); (I.C.)
| | - Thea L. Willis
- Centre for Craniofacial and Regenerative Biology, Faculty of Dentistry, Oral and Craniofacial Sciences, King’s College London, London SE19RT, UK; (T.L.W.); (E.L.); (C.L.A.)
| | - Mark Howard
- MRC Centre for Transplantation, Peter Gorer Department of Immunobiology, School of Immunology & Microbial Sciences, King’s College London, London SE19RT, UK;
| | - Isabella Carrus
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London SE19RT, UK; (V.S.); (R.C.F.E.); (I.C.)
| | - Emily Lodge
- Centre for Craniofacial and Regenerative Biology, Faculty of Dentistry, Oral and Craniofacial Sciences, King’s College London, London SE19RT, UK; (T.L.W.); (E.L.); (C.L.A.)
| | - Cynthia L. Andoniadou
- Centre for Craniofacial and Regenerative Biology, Faculty of Dentistry, Oral and Craniofacial Sciences, King’s College London, London SE19RT, UK; (T.L.W.); (E.L.); (C.L.A.)
- Department of Medicine III, University Hospital Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany
| | - Marika Charalambous
- Department of Medical and Molecular Genetics, Faculty of Life Sciences and Medicine, King’s College London, London SE19RT, UK; (V.S.); (R.C.F.E.); (I.C.)
- Correspondence:
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Pauler FM, Hudson QJ, Laukoter S, Hippenmeyer S. Inducible uniparental chromosome disomy to probe genomic imprinting at single-cell level in brain and beyond. Neurochem Int 2021; 145:104986. [PMID: 33600873 DOI: 10.1016/j.neuint.2021.104986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Revised: 01/23/2021] [Accepted: 02/06/2021] [Indexed: 12/27/2022]
Abstract
Genomic imprinting is an epigenetic mechanism that results in parental allele-specific expression of ~1% of all genes in mouse and human. Imprinted genes are key developmental regulators and play pivotal roles in many biological processes such as nutrient transfer from the mother to offspring and neuronal development. Imprinted genes are also involved in human disease, including neurodevelopmental disorders, and often occur in clusters that are regulated by a common imprint control region (ICR). In extra-embryonic tissues ICRs can act over large distances, with the largest surrounding Igf2r spanning over 10 million base-pairs. Besides classical imprinted expression that shows near exclusive maternal or paternal expression, widespread biased imprinted expression has been identified mainly in brain. In this review we discuss recent developments mapping cell type specific imprinted expression in extra-embryonic tissues and neocortex in the mouse. We highlight the advantages of using an inducible uniparental chromosome disomy (UPD) system to generate cells carrying either two maternal or two paternal copies of a specific chromosome to analyze the functional consequences of genomic imprinting. Mosaic Analysis with Double Markers (MADM) allows fluorescent labeling and concomitant induction of UPD sparsely in specific cell types, and thus to over-express or suppress all imprinted genes on that chromosome. To illustrate the utility of this technique, we explain how MADM-induced UPD revealed new insights about the function of the well-studied Cdkn1c imprinted gene, and how MADM-induced UPDs led to identification of highly cell type specific phenotypes related to perturbed imprinted expression in the mouse neocortex. Finally, we give an outlook on how MADM could be used to probe cell type specific imprinted expression in other tissues in mouse, particularly in extra-embryonic tissues.
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Affiliation(s)
- Florian M Pauler
- Institute of Science and Technology Austria, Am Campus 1, 3400, Klosterneuburg, Austria
| | - Quanah J Hudson
- Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
| | - Susanne Laukoter
- Institute of Science and Technology Austria, Am Campus 1, 3400, Klosterneuburg, Austria
| | - Simon Hippenmeyer
- Institute of Science and Technology Austria, Am Campus 1, 3400, Klosterneuburg, Austria.
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Beletskiy A, Chesnokova E, Bal N. Insulin-Like Growth Factor 2 As a Possible Neuroprotective Agent and Memory Enhancer-Its Comparative Expression, Processing and Signaling in Mammalian CNS. Int J Mol Sci 2021; 22:ijms22041849. [PMID: 33673334 PMCID: PMC7918606 DOI: 10.3390/ijms22041849] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Revised: 02/04/2021] [Accepted: 02/08/2021] [Indexed: 12/13/2022] Open
Abstract
A number of studies performed on rodents suggest that insulin-like growth factor 2 (IGF-2) or its analogs may possibly be used for treating some conditions like Alzheimer’s disease, Huntington’s disease, autistic spectrum disorders or aging-related cognitive impairment. Still, for translational research a comparative knowledge about the function of IGF-2 and related molecules in model organisms (rats and mice) and humans is necessary. There is a number of important differences in IGF-2 signaling between species. In the present review we emphasize species-specific patterns of IGF-2 expression in rodents, humans and some other mammals, using, among other sources, publicly available transcriptomic data. We provide a detailed description of Igf2 mRNA expression regulation and pre-pro-IGF-2 protein processing in different species. We also summarize the function of IGF-binding proteins. We describe three different receptors able to bind IGF-2 and discuss the role of IGF-2 signaling in learning and memory, as well as in neuroprotection. We hope that comprehensive understanding of similarities and differences in IGF-2 signaling between model organisms and humans will be useful for development of more effective medicines targeting IGF-2 receptors.
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Baulina N, Kiselev I, Favorova O. Imprinted Genes and Multiple Sclerosis: What Do We Know? Int J Mol Sci 2021; 22:1346. [PMID: 33572862 PMCID: PMC7866243 DOI: 10.3390/ijms22031346] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Revised: 01/23/2021] [Accepted: 01/26/2021] [Indexed: 02/06/2023] Open
Abstract
Multiple sclerosis (MS) is a chronic autoimmune neurodegenerative disease of the central nervous system that arises from interplay between non-genetic and genetic risk factors. The epigenetics functions as a link between these factors, affecting gene expression in response to external influence, and therefore should be extensively studied to improve the knowledge of MS molecular mechanisms. Among others, the epigenetic mechanisms underlie the establishment of parent-of-origin effects that appear as phenotypic differences depending on whether the allele was inherited from the mother or father. The most well described manifestation of parent-of-origin effects is genomic imprinting that causes monoallelic gene expression. It becomes more obvious that disturbances in imprinted genes at the least affecting their expression do occur in MS and may be involved in its pathogenesis. In this review we will focus on the potential role of imprinted genes in MS pathogenesis.
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Affiliation(s)
- Natalia Baulina
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia; (I.K.); (O.F.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
| | - Ivan Kiselev
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia; (I.K.); (O.F.)
| | - Olga Favorova
- Institute of Translational Medicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia; (I.K.); (O.F.)
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Pirogov Russian National Research Medical University, 117997 Moscow, Russia
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Icick R, Bloch V, Prince N, Karsinti E, Lépine JP, Laplanche JL, Mouly S, Marie-Claire C, Brousse G, Bellivier F, Vorspan F. Clustering suicidal phenotypes and genetic associations with brain-derived neurotrophic factor in patients with substance use disorders. Transl Psychiatry 2021; 11:72. [PMID: 33479229 PMCID: PMC7820499 DOI: 10.1038/s41398-021-01200-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Revised: 06/13/2020] [Accepted: 07/03/2020] [Indexed: 11/09/2022] Open
Abstract
Suicide attempts (SA), especially recurrent SA or serious SA, are common in substance use disorders (SUD). However, the genetic component of SA in SUD samples remains unclear. Brain-derived neurotrophic factor (BDNF) alleles and levels have been repeatedly involved in stress-related psychopathology. This investigation uses a within-cases study of BDNF and associated factors in three suicidal phenotypes ('any', 'recurrent', and 'serious') of outpatients seeking treatment for opiate and/or cocaine use disorder. Phenotypic characterization was ascertained using a semi-structured interview. After thorough quality control, 98 SNPs of BDNF and associated factors (the BDNF pathway) were extracted from whole-genome data, leaving 411 patients of Caucasian ancestry, who had reliable data regarding their SA history. Binary and multinomial regression with the three suicidal phenotypes were further performed to adjust for possible confounders, along with hierarchical clustering and compared to controls (N = 2504). Bayesian analyses were conducted to detect pleiotropy across the suicidal phenotypes. Among 154 (37%) ever suicide attempters, 104 (68%) reported at least one serious SA and 96 (57%) two SA or more. The median number of non-tobacco SUDs was three. The BDNF gene remained associated with lifetime SA in SNP-based (rs7934165, rs10835210) and gene-based tests within the clinical sample. rs10835210 clustered with serious SA. Bayesian analysis identified genetic correlation between 'any' and 'serious' SA regarding rs7934165. Despite limitations, 'serious' SA was shown to share both clinical and genetic risk factors of SA-not otherwise specified, suggesting a shared BDNF-related pathophysiology of SA in this population with multiple SUDs.
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Affiliation(s)
- Romain Icick
- Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis-Lariboisière-Fernand Widal, Paris, France. .,INSERM U1144, "Therapeutic Optimization in Neuropsychopharmacology", Paris, France. .,Université de Paris, Inserm UMR-S1144, Paris, France.
| | - Vanessa Bloch
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Nathalie Prince
- grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Emily Karsinti
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,ED139, Paris Nanterre University, Nanterre, France
| | - Jean-Pierre Lépine
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Jean-Louis Laplanche
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France
| | - Stéphane Mouly
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Cynthia Marie-Claire
- grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Georges Brousse
- grid.494717.80000000115480420Inserm UMR-1107, Neuro-Dol, Université Clermont-Auvergne, Clermont-Ferrand, France
| | - Frank Bellivier
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
| | - Florence Vorspan
- grid.50550.350000 0001 2175 4109Assistance Publique-Hôpitaux de Paris (AP-HP), Groupe Hospitalier Saint-Louis–Lariboisière–Fernand Widal, Paris, France ,grid.7429.80000000121866389INSERM U1144, “Therapeutic Optimization in Neuropsychopharmacology”, Paris, France ,Université de Paris, Inserm UMR-S1144, Paris, France
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Chang S, Wang Y, Xin Y, Wang S, Luo Y, Wang L, Zhang H, Li J. DNA methylation abnormalities of imprinted genes in congenital heart disease: a pilot study. BMC Med Genomics 2021; 14:4. [PMID: 33407475 PMCID: PMC7789576 DOI: 10.1186/s12920-020-00848-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2020] [Accepted: 12/03/2020] [Indexed: 12/14/2022] Open
Abstract
Background Congenital heart disease (CHD) is resulted from the interaction of genetic aberration and environmental factors. Imprinted genes, which are regulated by epigenetic modifications, are essential for the normal embryonic development. However, the role of imprinted genes in the etiology of CHD remains unclear. Methods After the samples were treated with bisulfate salt, imprinted genes methylation were measured by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. T test and One-way ANOVA were performed to evaluate the differences among groups. Odds ratios (ORs) were performed to evaluate the incidence risk of CHD in relation to methylation levels. Results We investigated the alterations of imprinted gene germline differential methylation regions (gDMRs) methylation in patients with CHD. Eighteen imprinted genes that are known to affect early embryonic development were selected and the methylation modification genes were detected by massarray in 27 CHD children and 28 healthy children. Altered gDMR methylation level of 8 imprinted genes was found, including 2 imprinted genes with hypermethylation of GRB10 and MEST and 6 genes with hypomethylation of PEG10, NAP1L5, INPP5F, PLAGL1, NESP and MEG3. Stratified analysis showed that the methylation degree of imprinted genes was different in different types of CHD. Risk analysis showed that 6 imprinted genes, except MEST and NAP1L5, within a specific methylation level range were the risk factors for CHD Conclusion Altered methylation of imprinted genes is associated with CHD and varies in different types of CHD. Further experiments are warranted to identify the methylation characteristics of imprinted genes in different types of CHD and clarify the etiologies of imprinted genes in CHD.
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Affiliation(s)
- Shaoyan Chang
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, 100020, China
| | - Yubo Wang
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, 100020, China
| | - Yu Xin
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, 100020, China
| | - Shuangxing Wang
- Department of Cardiac Surgery, Children's Hospital Affiliated to Capital Institute of Pediatrics, No. 2 Yabao Road, Chao Yang District, Beijing, 100020, China
| | - Yi Luo
- Department of Cardiac Surgery, Children's Hospital Affiliated to Capital Institute of Pediatrics, No. 2 Yabao Road, Chao Yang District, Beijing, 100020, China
| | - Li Wang
- Beijing Municipal Key Laboratory of Child Development and Nutriomics, Capital Institute of Pediatrics, Beijing, 100020, China
| | - Hui Zhang
- Department of Cardiac Surgery, Children's Hospital Affiliated to Capital Institute of Pediatrics, No. 2 Yabao Road, Chao Yang District, Beijing, 100020, China.
| | - Jia Li
- Clinical Physiology Laboratory, Institute of Pediatrics, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, No. 9 Jinsui Road, Tianhe District, Guangzhou City, 510000, Guangdong Province, China. .,Guangdong Provincial Key Laboratory of Research in Structural Birth Defect Disease, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou, 510000, Guangdong Province, China.
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Daigneault BW. Dynamics of paternal contributions to early embryo development in large animals. Biol Reprod 2020; 104:274-281. [PMID: 32997138 DOI: 10.1093/biolre/ioaa182] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 09/21/2020] [Accepted: 09/25/2020] [Indexed: 12/31/2022] Open
Abstract
This review focuses on current knowledge of paternal contributions to preimplantation embryonic development with particular emphasis on large animals. Specifically, the included content aims to summarize genomic and epigenomic contributions of paternally expressed genes, their regulation, and chromatin structure that are indispensable for early embryo development. The accumulation of current knowledge will summarize conserved allelic function among species to include functional molecular and genomic studies across large domestic animals in context with reference to founding experimental models.
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Laukoter S, Pauler FM, Beattie R, Amberg N, Hansen AH, Streicher C, Penz T, Bock C, Hippenmeyer S. Cell-Type Specificity of Genomic Imprinting in Cerebral Cortex. Neuron 2020; 107:1160-1179.e9. [PMID: 32707083 PMCID: PMC7523403 DOI: 10.1016/j.neuron.2020.06.031] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Revised: 05/20/2020] [Accepted: 06/24/2020] [Indexed: 12/20/2022]
Abstract
In mammalian genomes, a subset of genes is regulated by genomic imprinting, resulting in silencing of one parental allele. Imprinting is essential for cerebral cortex development, but prevalence and functional impact in individual cells is unclear. Here, we determined allelic expression in cortical cell types and established a quantitative platform to interrogate imprinting in single cells. We created cells with uniparental chromosome disomy (UPD) containing two copies of either the maternal or the paternal chromosome; hence, imprinted genes will be 2-fold overexpressed or not expressed. By genetic labeling of UPD, we determined cellular phenotypes and transcriptional responses to deregulated imprinted gene expression at unprecedented single-cell resolution. We discovered an unexpected degree of cell-type specificity and a novel function of imprinting in the regulation of cortical astrocyte survival. More generally, our results suggest functional relevance of imprinted gene expression in glial astrocyte lineage and thus for generating cortical cell-type diversity.
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Affiliation(s)
- Susanne Laukoter
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Florian M Pauler
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Robert Beattie
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Nicole Amberg
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Andi H Hansen
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Carmen Streicher
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - Thomas Penz
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Christoph Bock
- CeMM Research Center for Molecular Medicine of the Austrian Academy of Sciences, 1090 Vienna, Austria
| | - Simon Hippenmeyer
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria.
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Castel SE, Aguet F, Mohammadi P, Ardlie KG, Lappalainen T. A vast resource of allelic expression data spanning human tissues. Genome Biol 2020; 21:234. [PMID: 32912332 PMCID: PMC7488534 DOI: 10.1186/s13059-020-02122-z] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 07/27/2020] [Indexed: 01/12/2023] Open
Abstract
Allele expression (AE) analysis robustly measures cis-regulatory effects. Here, we present and demonstrate the utility of a vast AE resource generated from the GTEx v8 release, containing 15,253 samples spanning 54 human tissues for a total of 431 million measurements of AE at the SNP level and 153 million measurements at the haplotype level. In addition, we develop an extension of our tool phASER that allows effect sizes of cis-regulatory variants to be estimated using haplotype-level AE data. This AE resource is the largest to date, and we are able to make haplotype-level data publicly available. We anticipate that the availability of this resource will enable future studies of regulatory variation across human tissues.
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Affiliation(s)
- Stephane E Castel
- New York Genome Center, New York, NY, USA.
- Department of Systems Biology, Columbia University, New York, NY, USA.
| | | | - Pejman Mohammadi
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
- Department of Integrative Structural and Computational Biology, The Scripps Research Institute, La Jolla, CA, USA
- Scripps Translational Science Institute, La Jolla, CA, USA
| | | | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA.
- Department of Systems Biology, Columbia University, New York, NY, USA.
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Forget B, Icick R, Robert J, Correia C, Prevost MS, Gielen M, Corringer PJ, Bellivier F, Vorspan F, Besson M, Maskos U. Alterations in nicotinic receptor alpha5 subunit gene differentially impact early and later stages of cocaine addiction: a translational study in transgenic rats and patients. Prog Neurobiol 2020; 197:101898. [PMID: 32841724 DOI: 10.1016/j.pneurobio.2020.101898] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/06/2020] [Accepted: 08/14/2020] [Indexed: 12/13/2022]
Abstract
Cocaine addiction is a chronic and relapsing disorder with an important genetic component. Human candidate gene association studies showed that the single nucleotide polymorphism (SNP) rs16969968 in the α5 subunit (α5SNP) of nicotinic acetylcholine receptors (nAChRs), previously associated with increased tobacco dependence, was linked to a lower prevalence of cocaine use disorder (CUD). Three additional SNPs in the α5 subunit, previously shown to modify α5 mRNA levels, were also associated with CUD, suggesting an important role of the subunit in this pathology. To investigate the link between this subunit and CUD, we submitted rats knockout for the α5 subunit gene (α5KO), or carrying the α5SNP, to cocaine self-administration (SA) and showed that the acquisition of cocaine-SA was impaired in α5SNP rats while α5KO rats exhibited enhanced cocaine-induced relapse associated with altered neuronal activity in the nucleus accumbens. In addition, we observed in a human cohort of patients with CUD that the α5SNP was associated with a slower transition from first cocaine use to CUD. We also identified a novel SNP in the β4 nAChR subunit, part of the same gene cluster in the human genome and potentially altering CHRNA5 expression, associated with shorter time to relapse to cocaine use in patients. In conclusion, the α5SNP is protective against CUD by influencing early stages of cocaine exposure while CHRNA5 expression levels may represent a biomarker for the risk to relapse to cocaine use. Drugs modulating α5 containing nAChR activity may thus represent a novel therapeutic strategy against CUD.
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Affiliation(s)
- Benoît Forget
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France.
| | - Romain Icick
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France; Département de Psychiatrie et de Médecine Addictologique, Groupe Hospitalier Saint-Louis - Lariboisière - Fernand Widal, Assistance-Publique Hôpitaux de Paris, 75010, Paris, France; INSERM UMR_S1144, 4 avenue de l'Observatoire, 75006, Paris, France; Université Sorbonne - Paris - Cité, Paris, France
| | - Jonathan Robert
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France
| | - Caroline Correia
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France
| | - Marie S Prevost
- Unité Récepteurs-Canaux, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724 Paris Cedex 15, France
| | - Marc Gielen
- Université Sorbonne - Paris - Cité, Paris, France; Unité Récepteurs-Canaux, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724 Paris Cedex 15, France
| | - Pierre-Jean Corringer
- Unité Récepteurs-Canaux, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724 Paris Cedex 15, France
| | - Frank Bellivier
- Département de Psychiatrie et de Médecine Addictologique, Groupe Hospitalier Saint-Louis - Lariboisière - Fernand Widal, Assistance-Publique Hôpitaux de Paris, 75010, Paris, France; Université Sorbonne - Paris - Cité, Paris, France; Unité Récepteurs-Canaux, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724 Paris Cedex 15, France
| | - Florence Vorspan
- Département de Psychiatrie et de Médecine Addictologique, Groupe Hospitalier Saint-Louis - Lariboisière - Fernand Widal, Assistance-Publique Hôpitaux de Paris, 75010, Paris, France; INSERM UMR_S1144, 4 avenue de l'Observatoire, 75006, Paris, France; Université Sorbonne - Paris - Cité, Paris, France
| | - Morgane Besson
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France.
| | - Uwe Maskos
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 rue du Dr Roux, 75724, Paris Cedex 15, France.
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Mauvais-Jarvis F, Bairey Merz N, Barnes PJ, Brinton RD, Carrero JJ, DeMeo DL, De Vries GJ, Epperson CN, Govindan R, Klein SL, Lonardo A, Maki PM, McCullough LD, Regitz-Zagrosek V, Regensteiner JG, Rubin JB, Sandberg K, Suzuki A. Sex and gender: modifiers of health, disease, and medicine. Lancet 2020; 396:565-582. [PMID: 32828189 PMCID: PMC7440877 DOI: 10.1016/s0140-6736(20)31561-0] [Citation(s) in RCA: 887] [Impact Index Per Article: 221.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2019] [Revised: 06/12/2020] [Accepted: 06/16/2020] [Indexed: 02/09/2023]
Abstract
Clinicians can encounter sex and gender disparities in diagnostic and therapeutic responses. These disparities are noted in epidemiology, pathophysiology, clinical manifestations, disease progression, and response to treatment. This Review discusses the fundamental influences of sex and gender as modifiers of the major causes of death and morbidity. We articulate how the genetic, epigenetic, and hormonal influences of biological sex influence physiology and disease, and how the social constructs of gender affect the behaviour of the community, clinicians, and patients in the health-care system and interact with pathobiology. We aim to guide clinicians and researchers to consider sex and gender in their approach to diagnosis, prevention, and treatment of diseases as a necessary and fundamental step towards precision medicine, which will benefit men's and women's health.
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Affiliation(s)
- Franck Mauvais-Jarvis
- Diabetes Discovery & Sex-Based Medicine Laboratory, Section of Endocrinology, John W Deming Department of Medicine, Tulane University School of Medicine and Southeast Louisiana Veterans Health Care System Medical Center, New Orleans, LA, USA.
| | - Noel Bairey Merz
- Barbra Streisand Women's Heart Center, Cedars-Sinai Smidt Heart Institute, Los Angeles, CA, USA
| | - Peter J Barnes
- National Heart & Lung Institute, Imperial College London, London, UK
| | - Roberta D Brinton
- Department of Pharmacology and Department of Neurology, College of Medicine, Center for Innovation in Brain Science, University of Arizona, Tucson, AZ, USA
| | - Juan-Jesus Carrero
- Department of Medical Epidemiology and Biostatistics and Center for Gender Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Dawn L DeMeo
- Channing Division of Network Medicine and the Division of Pulmonary and Critical Care Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Geert J De Vries
- Neuroscience Institute and Department of Biology, Georgia State University, Atlanta, GA, USA
| | - C Neill Epperson
- Department of Psychiatry, University of Colorado School of Medicine, Anschutz Medical Campus, Aurora, CO, USA
| | - Ramaswamy Govindan
- Division of Oncology, Department of Medicine, Washington University School of Medicine, St Louis, MO, USA
| | - Sabra L Klein
- W Harry Feinstone Department of Molecular Microbiology and Immunology, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Amedeo Lonardo
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Azienda Ospedaliero-Universitaria di Modena, Ospedale Civile di Baggiovara, Modena, Italy
| | - Pauline M Maki
- Department of Psychiatry, Department of Psychology, and Department of Obstetrics & Gynecology, University of Illinois at Chicago, Chicago, IL, USA
| | - Louise D McCullough
- Department of Neurology, McGovern Medical School, University of Texas Health Science Center, Houston, TX, USA
| | - Vera Regitz-Zagrosek
- Berlin Institute of Gender Medicine, Charité-Universitätsmedizin Berlin, Berlin, Germany; Department of Cardiology, University Hospital Zürich, University of Zürich, Switzerland
| | - Judith G Regensteiner
- Center for Women's Health Research, Divisions of General Internal Medicine and Cardiology, University of Colorado School of Medicine, Aurora, CO, USA
| | - Joshua B Rubin
- Department of Medicine, Department of Paediatrics, and Department of Neuroscience, Washington University School of Medicine St Louis, MO, USA
| | - Kathryn Sandberg
- Center for the Study of Sex Differences in Health, Aging and Disease, Georgetown University, Washington, DC, USA
| | - Ayako Suzuki
- Division of Gastroenterology, Duke University Medical Center Durham, NC, USA; Durham VA Medical Center, Durham, NC, USA
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47
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Meguro A, Ishihara M, Petrek M, Yamamoto K, Takeuchi M, Mrazek F, Kolek V, Benicka A, Yamane T, Shibuya E, Yoshino A, Isomoto A, Ota M, Yatsu K, Shijubo N, Nagai S, Yamaguchi E, Yamaguchi T, Namba K, Kaburaki T, Takase H, Morimoto SI, Hori J, Kono K, Goto H, Suda T, Ikushima S, Ando Y, Takenaka S, Takeuchi M, Yuasa T, Sugisaki K, Ohguro N, Hiraoka M, Kitaichi N, Sugiyama Y, Horita N, Asukata Y, Kawagoe T, Kimura I, Ishido M, Inoko H, Mochizuki M, Ohno S, Bahram S, Remmers EF, Kastner DL, Mizuki N. Genetic control of CCL24, POR, and IL23R contributes to the pathogenesis of sarcoidosis. Commun Biol 2020; 3:465. [PMID: 32826979 PMCID: PMC7442816 DOI: 10.1038/s42003-020-01185-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Accepted: 07/30/2020] [Indexed: 12/17/2022] Open
Abstract
Sarcoidosis is a genetically complex systemic inflammatory disease that affects multiple organs. We present a GWAS of a Japanese cohort (700 sarcoidosis cases and 886 controls) with replication in independent samples from Japan (931 cases and 1,042 controls) and the Czech Republic (265 cases and 264 controls). We identified three loci outside the HLA complex, CCL24, STYXL1-SRRM3, and C1orf141-IL23R, which showed genome-wide significant associations (P < 5.0 × 10−8) with sarcoidosis; CCL24 and STYXL1-SRRM3 were novel. The disease-risk alleles in CCL24 and IL23R were associated with reduced CCL24 and IL23R expression, respectively. The disease-risk allele in STYXL1-SRRM3 was associated with elevated POR expression. These results suggest that genetic control of CCL24, POR, and IL23R expression contribute to the pathogenesis of sarcoidosis. We speculate that the CCL24 risk allele might be involved in a polarized Th1 response in sarcoidosis, and that POR and IL23R risk alleles may lead to diminished host defense against sarcoidosis pathogens. Akira Meguro et al. report a genome-wide association study for sarcoidosis—a systemic inflammatory disease—in the Japanese population. They identify 3 non-HLA loci with genome-wide significance, 2 of which have not been previously associated with sarcoidosis in any population.
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Affiliation(s)
- Akira Meguro
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Mami Ishihara
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Martin Petrek
- Department of Pathological Physiology, Faculty of Medicine and Dentistry, Palacky University, Hnevotinska Str., 77515, Olomouc, Czech Republic
| | - Ken Yamamoto
- Department of Medical Biochemistry, Kurume University School of Medicine, 67 Asahimachi, Kurume, Fukuoka, 830-0011, Japan.,Division of Genome Analysis, Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, Fukuoka, 812-8582, Japan
| | - Masaki Takeuchi
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan.,Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, 10 Center Drive, 10 CRC East/B2-5235, Bethesda, MD, 20892-1849, USA
| | - Frantisek Mrazek
- Department of Immunology, Faculty of Medicine and Dentistry, Palacky University, I.P.Pavlova Str. 6, 77520, Olomouc, Czech Republic
| | - Vitezslav Kolek
- Department of Respiratory Medicine, Faculty of Medicine and Dentistry, Palacky University, I. P. Pavlova Str. 6, 77900, Olomouc, Czech Republic
| | - Alzbeta Benicka
- Department of Pathological Physiology, Faculty of Medicine and Dentistry, Palacky University, Hnevotinska Str., 77515, Olomouc, Czech Republic
| | - Takahiro Yamane
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Etsuko Shibuya
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Atsushi Yoshino
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Akiko Isomoto
- Division of Genome Analysis, Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, Fukuoka, 812-8582, Japan
| | - Masao Ota
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan.,Division of Hepatology and Gastroenterology, Department of Medicine, Shinshu University School of Medicine, 3-1-1 Asahi, Matsumoto, Nagano, 390-8621, Japan.,INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Strasbourg, France.,INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Nagano, Japan
| | - Keisuke Yatsu
- Department of Medical Science and Cardiorenal Medicine, Yokohama City University School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Noriharu Shijubo
- Department of Respiratory Medicine, Japan Railway Sapporo Hospital, Higashi-1, Kita-3, Chuo-ku, Sapporo, 060-0033, Japan
| | - Sonoko Nagai
- Kyoto Central Clinic/Clinical Research Center, 56-58 Masuyacho Sanjo-Takakura, Nakagyo-ku, Kyoto, 604-8111, Japan
| | - Etsuro Yamaguchi
- Division of Respiratory Medicine and Allergology, Aichi Medical University, 21 Karimata, Yazako, Nagakute-cho, Aichi-gun, Aichi, 480-1195, Japan
| | - Tetsuo Yamaguchi
- Department of Respiratory Medicine, Japan Railway Tokyo General Hospital, 2-1-3 Yoyogi, Shibuya-ku, Tokyo, 151-0053, Japan
| | - Kenichi Namba
- Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, N15, W7, Kita-ku, Sapporo, Hokkaido, 060-8638, Japan
| | - Toshikatsu Kaburaki
- Department of Ophthalmology, University of Tokyo School of Medicine, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-8655, Japan
| | - Hiroshi Takase
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University Graduate School of Medicine, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8519, Japan
| | - Shin-Ichiro Morimoto
- Division of Cardiology, Department of Internal Medicine, Fujita Health University School of Medicine, 1-98 Dengakugakubo, Kutsukakecho, Toyoake, Aichi, 470-1192, Japan
| | - Junko Hori
- Department of Ophthalmology, Nippon Medical School, 1-1-5 Sendagi, Bunkyo-ku, Tokyo, 113-8602, Japan
| | - Keiko Kono
- Department of Ophthalmology, Kono Medical Clinic, 3-30-28 Soshigaya, Setagaya-ku, Tokyo, 157-0072, Japan
| | - Hiroshi Goto
- Department of Ophthalmology, Tokyo Medical University, 6-7-1 Nishishinjuku, Shinjuku-ku, Tokyo, 160-0023, Japan
| | - Takafumi Suda
- Second Division, Department of Internal Medicine, Hamamatsu University School of Medicine, 1-20-1 Handayama, Hamamatsu, Shizuoka, 431-3192, Japan
| | - Soichiro Ikushima
- Department of Respiratory Medicine, Japanese Red Cross Medical Centre, 4-1-22 Hiroo, Shibuya-ku, Tokyo, 150-8953, Japan
| | - Yasutaka Ando
- Department of Ophthalmology, Kitasato Institute Hospital, 5-9-1 Shirokane, Minato-ku, Tokyo, 108-8642, Japan.,Department of Ophthalmology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-0016, Japan
| | - Shinobu Takenaka
- Department of Respiratory Diseases, Kumamoto City Hospital, 1-1-60 Kotoh, Kumamoto, Kumamoto, 862-8505, Japan
| | - Masaru Takeuchi
- Department of Ophthalmology, National Defense Medical College, 3-2 Namiki, Tokorozawa, Saitama, 359-8513, Japan
| | - Takenosuke Yuasa
- Yuasa Eye Clinic, 3-1-1 Nishimoto-cho, Nishi-ku, Osaka, 550-0005, Japan
| | - Katsunori Sugisaki
- Department of Internal Medicine, National Hospital Organization Nishibeppu National Hospital, 4548 Oaza-Tsurumi, Beppu, Oita, 874-0840, Japan
| | - Nobuyuki Ohguro
- Department of Ophthalmology, Japan Community Health care Organization Osaka Hospital, 4-2-78 Fukushima, Fukushima-ku, Osaka, 553-0003, Japan
| | - Miki Hiraoka
- Department of Ophthalmology, School of Medicine, Sapporo Medical University, S1 W16 Chuo-ku, Sapporo, Hokkaido, 060-8543, Japan
| | - Nobuyoshi Kitaichi
- Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, N15, W7, Kita-ku, Sapporo, Hokkaido, 060-8638, Japan.,Department of Ophthalmology, Health Sciences University of Hokkaido, Ainosato 2-5, Kita-ku, Sapporo, Hokkaido, 002-8072, Japan
| | - Yukihiko Sugiyama
- Division of Pulmonary Medicine, Department of Medicine, Jichi Medical University, 3311-1 Yakushiji, Shimotsuke, Tochigi, 329-0498, Japan
| | - Nobuyuki Horita
- Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, 10 Center Drive, 10 CRC East/B2-5235, Bethesda, MD, 20892-1849, USA.,Department of Pulmonology, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Yuri Asukata
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Tatsukata Kawagoe
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Ikuko Kimura
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Mizuho Ishido
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan
| | - Hidetoshi Inoko
- INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Strasbourg, France.,INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Nagano, Japan.,Department of Molecular Life Science, Division of Molecular Medical Science and Molecular Medicine, Tokai University School of Medicine, 143 Shimokasuya, Isehara, Kanagawa, 259-1193, Japan
| | - Manabu Mochizuki
- Department of Ophthalmology and Visual Science, Tokyo Medical and Dental University Graduate School of Medicine, 1-5-45 Yushima, Bunkyo-ku, Tokyo, 113-8519, Japan
| | - Shigeaki Ohno
- Department of Ophthalmology, Faculty of Medicine and Graduate School of Medicine, Hokkaido University, N15, W7, Kita-ku, Sapporo, Hokkaido, 060-8638, Japan.,Department of Ophthalmology, Health Sciences University of Hokkaido, Ainosato 2-5, Kita-ku, Sapporo, Hokkaido, 002-8072, Japan
| | - Seiamak Bahram
- INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Strasbourg, France.,INSERM Franco-Japanese "Laboratoire International Associé" (LIA) Nextgen HLA Laboratory, Nagano, Japan.,Plateforme GENOMAX, Laboratoire d'ImmunoRhumatologie Moléculaire, INSERM UMR_S1109, LabEx Transplantex, Centre de Recherche d'Immunologie et d'Hématologie. Faculté de Médecine, Fédération Hospitalo-Universitaire (FHU) OMICARE, Fédération de Médecine Translationnelle de Strasbourg (FMTS), Université de Strasbourg, Strasbourg, France
| | - Elaine F Remmers
- Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, 10 Center Drive, 10 CRC East/B2-5235, Bethesda, MD, 20892-1849, USA
| | - Daniel L Kastner
- Inflammatory Disease Section, National Human Genome Research Institute, National Institutes of Health, 10 Center Drive, 10 CRC East/B2-5235, Bethesda, MD, 20892-1849, USA
| | - Nobuhisa Mizuki
- Department of Ophthalmology and Visual Science, Yokohama City University Graduate School of Medicine, 3-9 Fukuura, Kanazawa-ku, Yokohama, Kanagawa, 236-0004, Japan.
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Icick R, Forget B, Cloëz-Tayarani I, Pons S, Maskos U, Besson M. Genetic susceptibility to nicotine addiction: Advances and shortcomings in our understanding of the CHRNA5/A3/B4 gene cluster contribution. Neuropharmacology 2020; 177:108234. [PMID: 32738310 DOI: 10.1016/j.neuropharm.2020.108234] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Revised: 06/28/2020] [Accepted: 07/07/2020] [Indexed: 12/12/2022]
Abstract
Over the last decade, robust human genetic findings have been instrumental in elucidating the heritable basis of nicotine addiction (NA). They highlight coding and synonymous polymorphisms in a cluster on chromosome 15, encompassing the CHRNA5, CHRNA3 and CHRNB4 genes, coding for three subunits of the nicotinic acetylcholine receptor (nAChR). They have inspired an important number of preclinical studies, and will hopefully lead to the definition of novel drug targets for treating NA. Here, we review these candidate gene and genome-wide association studies (GWAS) and their direct implication in human brain function and NA-related phenotypes. We continue with a description of preclinical work in transgenic rodents that has led to a mechanistic understanding of several of the genetic hits. We also highlight important issues with regards to CHRNA3 and CHRNB4 where we are still lacking a dissection of their role in NA, including even in preclinical models. We further emphasize the use of human induced pluripotent stem cell-derived models for the analysis of synonymous and intronic variants on a human genomic background. Finally, we indicate potential avenues to further our understanding of the role of this human genetic variation. This article is part of the special issue on 'Contemporary Advances in Nicotine Neuropharmacology'.
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Affiliation(s)
- Romain Icick
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; Département de Psychiatrie et de Médecine Addictologique, Groupe Hospitalier Saint-Louis, Lariboisière, Fernand Widal, Assistance-Publique Hôpitaux de Paris, Paris, F-75010, France; INSERM UMR-S1144, Paris, F-75006, France; FHU "NOR-SUD", Assistance-Publique Hôpitaux de Paris, Paris, F-75001, France
| | - Benoît Forget
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; Génétique Humaine et Fonctions Cognitives, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France
| | - Isabelle Cloëz-Tayarani
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; FHU "NOR-SUD", Assistance-Publique Hôpitaux de Paris, Paris, F-75001, France
| | - Stéphanie Pons
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; FHU "NOR-SUD", Assistance-Publique Hôpitaux de Paris, Paris, F-75001, France
| | - Uwe Maskos
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; FHU "NOR-SUD", Assistance-Publique Hôpitaux de Paris, Paris, F-75001, France
| | - Morgane Besson
- Neurobiologie Intégrative des Systèmes Cholinergiques, CNRS UMR3571, Institut Pasteur, 25 Rue du Dr Roux, 75724, Paris Cedex 15, France; FHU "NOR-SUD", Assistance-Publique Hôpitaux de Paris, Paris, F-75001, France.
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49
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Yamazawa K, Inoue T, Sakemi Y, Nakashima T, Yamashita H, Khono K, Fujita H, Enomoto K, Nakabayashi K, Hata K, Nakashima M, Matsunaga T, Nakamura A, Matsubara K, Ogata T, Kagami M. Loss of imprinting of the human-specific imprinted gene ZNF597 causes prenatal growth retardation and dysmorphic features: implications for phenotypic overlap with Silver-Russell syndrome. J Med Genet 2020; 58:427-432. [PMID: 32576657 PMCID: PMC8142457 DOI: 10.1136/jmedgenet-2020-107019] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 05/12/2020] [Accepted: 05/13/2020] [Indexed: 11/04/2022]
Abstract
BACKGROUND ZNF597, encoding a zinc-finger protein, is the human-specific maternally expressed imprinted gene located on 16p13.3. The parent-of-origin expression of ZNF597 is regulated by the ZNF597:TSS-DMR, of which only the paternal allele acquires methylation during postimplantation period. Overexpression of ZNF597 may contribute to some of the phenotypes associated with maternal uniparental disomy of chromosome 16 (UPD(16)mat), and some patients with UPD(16)mat presenting with Silver-Russell syndrome (SRS) phenotype have recently been reported. METHODS A 6-year-old boy presented with prenatal growth restriction, macrocephaly at birth, forehead protrusion in infancy and clinodactyly of the fifth finger. Methylation, expression, microsatellite marker, single nucleotide polymorphism array and trio whole-exome sequencing analyses were conducted. RESULTS Isolated hypomethylation of the ZNF597:TSS-DMR and subsequent loss of imprinting and overexpression of ZNF597 were confirmed in the patient. Epigenetic alterations, such as UPD including UPD(16)mat and other methylation defects, were excluded. Pathogenic sequence or copy number variants affecting his phenotypes were not identified, indicating that primary epimutation occurred postzygotically. CONCLUSION We report the first case of isolated ZNF597 imprinting defect, showing phenotypic overlap with SRS despite not satisfying the clinical SRS criteria. A novel imprinting disorder entity involving the ZNF597 imprinted domain can be speculated.
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Affiliation(s)
- Kazuki Yamazawa
- Medical Genetics Center, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Takanobu Inoue
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan.,Department of Pediatrics, University of Tokyo, Tokyo, Japan
| | - Yoshihiro Sakemi
- Department of Pediatrics, National Hospital Organization Kokura Medical Center, Kitakyushu, Japan
| | - Toshinori Nakashima
- Department of Pediatrics, National Hospital Organization Kokura Medical Center, Kitakyushu, Japan
| | - Hironori Yamashita
- Department of Pediatrics, National Hospital Organization Kokura Medical Center, Kitakyushu, Japan
| | | | | | | | - Kazuhiko Nakabayashi
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Kenichiro Hata
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Moeko Nakashima
- Medical Genetics Center, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Tatsuo Matsunaga
- Medical Genetics Center, National Hospital Organization Tokyo Medical Center, Tokyo, Japan
| | - Akie Nakamura
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan.,Department of Pediatrics, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Keiko Matsubara
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Tsutomu Ogata
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan.,Department of Pediatrics, Hamamatsu University School of Medicine, Hamamatsu, Japan
| | - Masayo Kagami
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
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The influence of DNA methylation on monoallelic expression. Essays Biochem 2020; 63:663-676. [PMID: 31782494 PMCID: PMC6923323 DOI: 10.1042/ebc20190034] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2019] [Revised: 11/10/2019] [Accepted: 11/11/2019] [Indexed: 01/02/2023]
Abstract
Monoallelic gene expression occurs in diploid cells when only one of the two alleles of a gene is active. There are three main classes of genes that display monoallelic expression in mammalian genomes: (1) imprinted genes that are monoallelically expressed in a parent-of-origin dependent manner; (2) X-linked genes that undergo random X-chromosome inactivation in female cells; (3) random monoallelically expressed single and clustered genes located on autosomes. The heritability of monoallelic expression patterns during cell divisions implies that epigenetic mechanisms are involved in the cellular memory of these expression states. Among these, methylation of CpG sites on DNA is one of the best described modification to explain somatic inheritance. Here, we discuss the relevance of DNA methylation for the establishment and maintenance of monoallelic expression patterns among these three groups of genes, and how this is intrinsically linked to development and cellular states.
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