101
|
Abstract
In this review we critically summarize the evidence base and the progress to date regarding the genomic basis of periodontal disease and tooth morbidity (ie, dental caries and tooth loss), and discuss future applications and research directions in the context of precision oral health and care. Evidence for these oral/dental traits from genome-wide association studies first emerged less than a decade ago. Basic and translational research activities in this domain are now under way by multiple groups around the world. Key departure points in the oral health genomics discourse are: (a) some heritable variation exists for periodontal and dental diseases; (b) the environmental component (eg, social determinants of health and behavioral risk factors) has a major influence on the population distribution but probably interacts with factors of innate susceptibility at the person-level; (c) sizeable, multi-ethnic, well-characterized samples or cohorts with high-quality measures on oral health outcomes and genomics information are required to make decisive discoveries; (d) challenges remain in the measurement of oral health and disease, with current periodontitis and dental caries traits capturing only a part of the health-disease continuum, and are little or not informed by the underlying biology; (e) the substantial individual heterogeneity that exists in the clinical presentation and lifetime trajectory of oral disease can be identified and leveraged in a precision medicine framework or, if unappreciated, can hamper translational efforts. In this review we discuss how composite or biologically informed traits may offer improvements over clinically defined ones for the genomic interrogation of oral diseases. We demonstrate the utility of the results of genome-wide association studies for the development and testing of a genetic risk score for severe periodontitis. We conclude that exciting opportunities lie ahead for improvements in the oral health of individual patients and populations via advances in our understanding of the genomic basis of oral health and disease. The pace of new discoveries and their equitable translation to practice will largely depend on investments in the education and training of the oral health care workforce, basic and population research, and sustained collaborative efforts..
Collapse
Affiliation(s)
- Thiago Morelli
- Department of PeriodontologySchool of DentistryUniversity of North Carolina at Chapel HillChapel HillNorth Carolina, USA
| | - Cary S. Agler
- Department of Oral and Craniofacial Health SciencesSchool of DentistryUniversity of North Carolina at Chapel HillChapel HillNorth Carolina, USA
| | - Kimon Divaris
- Department of Pediatric DentistrySchool of DentistryUniversity of North Carolina at Chapel HillChapel HillNorth Carolina, USA
- Department of EpidemiologyGillings School of Global Public HealthUniversity of North Carolina at Chapel HillChapel HillNorth Carolina, USA
| |
Collapse
|
102
|
Hekselman I, Yeger-Lotem E. Mechanisms of tissue and cell-type specificity in heritable traits and diseases. Nat Rev Genet 2020; 21:137-150. [DOI: 10.1038/s41576-019-0200-9] [Citation(s) in RCA: 67] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/12/2019] [Indexed: 02/07/2023]
|
103
|
Iacobuzio-Donahue CA, Michael C, Baez P, Kappagantula R, Hooper JE, Hollman TJ. Cancer biology as revealed by the research autopsy. Nat Rev Cancer 2019; 19:686-697. [PMID: 31519982 PMCID: PMC7453489 DOI: 10.1038/s41568-019-0199-4] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/13/2019] [Indexed: 12/19/2022]
Abstract
A research autopsy is a post-mortem medical procedure performed on a deceased individual with the primary goal of collecting tissue to support basic and translational research. This approach has increasingly been used to investigate the pathophysiological mechanisms of cancer evolution, metastasis and treatment resistance. In this Review, we discuss the rationale for the use of research autopsies in cancer research and provide an evidence-based discussion of the quality of post-mortem tissues compared with other types of biospecimens. We also discuss the advantages of using post-mortem tissues over other types of biospecimens, including the large amounts of tissue that can be obtained and the extent of multiregion sampling that is achievable, which is not otherwise possible in living patients. We highlight how the research autopsy has supported the identification of the clonal origins and modes of spread among metastases, the extent that selective pressures imposed by treatments cause bottlenecks leading to parallel and convergent tumour evolution, and the creation of rare tissue banks and patient-derived model systems. Finally, we comment on the future of the research autopsy as an integral component of precision medicine strategies.
Collapse
Affiliation(s)
- Christine A Iacobuzio-Donahue
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- Human Oncology and Pathogenesis Program, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
- David M. Rubenstein Center for Pancreatic Cancer Research, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
| | - Chelsea Michael
- Department of Health Informatics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Priscilla Baez
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Rajya Kappagantula
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jody E Hooper
- Department of Pathology, The Johns Hopkins University, Baltimore, MD, USA
| | - Travis J Hollman
- Department of Pathology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
- Parker Institute for Cancer Immunotherapy, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| |
Collapse
|
104
|
Lindeboom RGH, Vermeulen M, Lehner B, Supek F. The impact of nonsense-mediated mRNA decay on genetic disease, gene editing and cancer immunotherapy. Nat Genet 2019; 51:1645-1651. [PMID: 31659324 PMCID: PMC6858879 DOI: 10.1038/s41588-019-0517-5] [Citation(s) in RCA: 155] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 09/23/2019] [Indexed: 12/21/2022]
Abstract
Premature termination codons (PTCs) can result in the production of truncated proteins or the degradation of messenger RNAs by nonsense-mediated mRNA decay (NMD). Which of these outcomes occurs can alter the effect of a mutation, with the engagement of NMD being dependent on a series of rules. Here, by applying these rules genome-wide to obtain a resource called NMDetective, we explore the impact of NMD on genetic disease and approaches to therapy. First, human genetic diseases differ in whether NMD typically aggravates or alleviates the effects of PTCs. Second, failure to trigger NMD is a cause of ineffective gene inactivation by CRISPR-Cas9 gene editing. Finally, NMD is a determinant of the efficacy of cancer immunotherapy, with only frameshifted transcripts that escape NMD predicting a response. These results demonstrate the importance of incorporating the rules of NMD into clinical decision-making. Moreover, they suggest that inhibiting NMD may be effective in enhancing cancer immunotherapy.
Collapse
Affiliation(s)
- Rik G H Lindeboom
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Michiel Vermeulen
- Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, Nijmegen, the Netherlands
| | - Ben Lehner
- Systems Biology Program, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, Barcelona, Spain. .,Universitat Pompeu Fabra, Barcelona, Spain. .,Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain.
| | - Fran Supek
- Institució Catalana de Recerca i Estudis Avançats, Barcelona, Spain. .,Institut de Recerca Biomedica Barcelona, The Barcelona Institute of Science and Technology, Barcelona, Spain.
| |
Collapse
|
105
|
Reble E, Feng Y, Wigg KG, Barr CL. DNA Variant in the RPGRIP1L Gene Influences Alternative Splicing. MOLECULAR NEUROPSYCHIATRY 2019; 5:97-106. [PMID: 32399473 DOI: 10.1159/000502199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2018] [Accepted: 06/18/2019] [Indexed: 12/22/2022]
Abstract
The retinitis pigmentosa GTPase regulator interacting protein 1-like (RPGRIP1L) gene encodes a ciliary protein that is critical for processes related to brain development, including development of left-right asymmetry, sonic hedgehog signaling, and neural tube formation. RPGRIP1L is a risk factor for retinal degeneration, and rare, deleterious variants in the RPGRIP1L gene cause Joubert syndrome and Meckel syndrome, both autosomal recessive disorders. These syndromes are characterized by dysfunctional primary cilia that result in abnormal development - and even lethality in the case of Meckel syndrome. Genetic studies have also implicated RPGRIP1L in psychiatric disorders by suggestive findings from genome-wide association studies and findings from rare-variant exome analyses for bipolar disorder and de novo mutations in autism. In this study we identify a common variant in RPGRIP1L, rs7203525, that influences alternative splicing, increasing the inclusion of exon 20 of RPGRIP1L. We detected this alternative splicing association in human postmortem brain tissue samples and, using a minigene assay combined with in vitro mutagenesis, confirmed that the alternative splicing is attributable to the alleles of this variant. The predominate RPGRIP1L isoform expressed in adult brains does not contain exon 20; thus, a shift to include this exon may impact brain function.
Collapse
Affiliation(s)
- Emma Reble
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Yu Feng
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Karen G Wigg
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Cathy L Barr
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
106
|
Components of genetic associations across 2,138 phenotypes in the UK Biobank highlight adipocyte biology. Nat Commun 2019; 10:4064. [PMID: 31492854 PMCID: PMC6731283 DOI: 10.1038/s41467-019-11953-9] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Accepted: 08/14/2019] [Indexed: 01/25/2023] Open
Abstract
Population-based biobanks with genomic and dense phenotype data provide opportunities for generating effective therapeutic hypotheses and understanding the genomic role in disease predisposition. To characterize latent components of genetic associations, we apply truncated singular value decomposition (DeGAs) to matrices of summary statistics derived from genome-wide association analyses across 2,138 phenotypes measured in 337,199 White British individuals in the UK Biobank study. We systematically identify key components of genetic associations and the contributions of variants, genes, and phenotypes to each component. As an illustration of the utility of the approach to inform downstream experiments, we report putative loss of function variants, rs114285050 (GPR151) and rs150090666 (PDE3B), that substantially contribute to obesity-related traits and experimentally demonstrate the role of these genes in adipocyte biology. Our approach to dissect components of genetic associations across the human phenome will accelerate biomedical hypothesis generation by providing insights on previously unexplored latent structures.
Collapse
|
107
|
Jayasinghe RG, Cao S, Gao Q, Wendl MC, Vo NS, Reynolds SM, Zhao Y, Climente-González H, Chai S, Wang F, Varghese R, Huang M, Liang WW, Wyczalkowski MA, Sengupta S, Li Z, Payne SH, Fenyö D, Miner JH, Walter MJ, Vincent B, Eyras E, Chen K, Shmulevich I, Chen F, Ding L. Systematic Analysis of Splice-Site-Creating Mutations in Cancer. Cell Rep 2019; 23:270-281.e3. [PMID: 29617666 PMCID: PMC6055527 DOI: 10.1016/j.celrep.2018.03.052] [Citation(s) in RCA: 159] [Impact Index Per Article: 31.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2017] [Revised: 02/21/2018] [Accepted: 03/13/2018] [Indexed: 12/31/2022] Open
Abstract
For the past decade, cancer genomic studies have focused on mutations leading to splice-site disruption, overlooking those having splice-creating potential. Here, we applied a bioinformatic tool, MiSplice, for the large-scale discovery of splice-site-creating mutations (SCMs) across 8,656 TCGA tumors. We report 1,964 originally mis-annotated mutations having clear evidence of creating alternative splice junctions. TP53 and GATA3 have 26 and 18 SCMs, respectively, and ATRX has 5 from lower-grade gliomas. Mutations in 11 genes, including PARP1, BRCA1, and BAP1, were experimentally validated for splice-site-creating function. Notably, we found that neoantigens induced by SCMs are likely several folds more immunogenic compared to missense mutations, exemplified by the recurrent GATA3 SCM. Further, high expression of PD-1 and PD-L1 was observed in tumors with SCMs, suggesting candidates for immune blockade therapy. Our work highlights the importance of integrating DNA and RNA data for understanding the functional and the clinical implications of mutations in human diseases.
Collapse
Affiliation(s)
- Reyka G Jayasinghe
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Song Cao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Qingsong Gao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Michael C Wendl
- McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Mathematics, Washington University in St. Louis, St. Louis, MO 63130, USA
| | - Nam Sy Vo
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Yanyan Zhao
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Héctor Climente-González
- Institut Curie, 75248 Paris Cedex, France; MINES ParisTech, PSL-Research University, CBIO-Centre for Computational Biology, 77300 Fontainebleau, France; INSERM U900, 75248 Paris Cedex, France
| | - Shengjie Chai
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Curriculum in Bioinformatics and Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Fang Wang
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Rajees Varghese
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Division of Nephrology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Mo Huang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA
| | - Wen-Wei Liang
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Matthew A Wyczalkowski
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Sohini Sengupta
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Zhi Li
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA; Institute for Systems Genetics, New York University School of Medicine, New York, NY 10016, USA
| | - Samuel H Payne
- Biological Sciences Division, Pacific Northwest National Laboratory, Richland, WA, USA
| | - David Fenyö
- Department of Biochemistry and Molecular Pharmacology, New York University School of Medicine, New York, NY 10016, USA; Institute for Systems Genetics, New York University School of Medicine, New York, NY 10016, USA
| | - Jeffrey H Miner
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Division of Nephrology, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Matthew J Walter
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110, USA
| | | | - Benjamin Vincent
- Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Curriculum in Bioinformatics and Computational Biology, The University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Eduardo Eyras
- Catalan Institution of Research and Advanced Studies (ICREA), 08010 Barcelona, Spain; Computational RNA Biology Group, Pompeu Fabra University (UPF), 08003 Barcelona, Spain
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | | | - Feng Chen
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; Division of Nephrology, Washington University in St. Louis, St. Louis, MO 63110, USA.
| | - Li Ding
- Department of Medicine, Washington University in St. Louis, St. Louis, MO 63110, USA; McDonnell Genome Institute, Washington University in St. Louis, St. Louis, MO 63108, USA; Division of Oncology, Washington University in St. Louis, St. Louis, MO 63110, USA; Department of Genetics, Washington University in St. Louis, St. Louis, MO 63110, USA; Siteman Cancer Center, Washington University in St. Louis, St. Louis, MO 63110, USA.
| |
Collapse
|
108
|
Dalton WB, Helmenstine E, Walsh N, Gondek LP, Kelkar DS, Read A, Natrajan R, Christenson ES, Roman B, Das S, Zhao L, Leone RD, Shinn D, Groginski T, Madugundu AK, Patil A, Zabransky DJ, Medford A, Lee J, Cole AJ, Rosen M, Thakar M, Ambinder A, Donaldson J, DeZern AE, Cravero K, Chu D, Madero-Marroquin R, Pandey A, Hurley PJ, Lauring J, Park BH. Hotspot SF3B1 mutations induce metabolic reprogramming and vulnerability to serine deprivation. J Clin Invest 2019; 129:4708-4723. [PMID: 31393856 DOI: 10.1172/jci125022] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Cancer-associated mutations in the spliceosome gene SF3B1 create a neomorphic protein that produces aberrant mRNA splicing in hundreds of genes, but the ensuing biologic and therapeutic consequences of this missplicing are not well understood. Here we have provided evidence that aberrant splicing by mutant SF3B1 altered the transcriptome, proteome, and metabolome of human cells, leading to missplicing-associated downregulation of metabolic genes, decreased mitochondrial respiration, and suppression of the serine synthesis pathway. We also found that mutant SF3B1 induces vulnerability to deprivation of the nonessential amino acid serine, which was mediated by missplicing-associated downregulation of the serine synthesis pathway enzyme PHGDH. This vulnerability was manifest both in vitro and in vivo, as dietary restriction of serine and glycine in mice was able to inhibit the growth of SF3B1MUT xenografts. These findings describe a role for SF3B1 mutations in altered energy metabolism, and they offer a new therapeutic strategy against SF3B1MUT cancers.
Collapse
Affiliation(s)
- W Brian Dalton
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Eric Helmenstine
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Noel Walsh
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Lukasz P Gondek
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Dhanashree S Kelkar
- McKusick-Nathans Institute of Genetic Medicine, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Abigail Read
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
| | - Rachael Natrajan
- The Breast Cancer Now Toby Robins Research Centre, The Institute of Cancer Research, London, United Kingdom
| | - Eric S Christenson
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | | | - Samarjit Das
- Department of Pathology, Cardiovascular Division.,Department of Anesthesiology and Critical Care Medicine, and
| | - Liang Zhao
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Robert D Leone
- Bloomberg-Kimmel Institute for Cancer Immunotherapy, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
| | - Daniel Shinn
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Taylor Groginski
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Anil K Madugundu
- McKusick-Nathans Institute of Genetic Medicine, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Institute of Bioinformatics, International Technology Park, Bangalore, India.,Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India
| | - Arun Patil
- McKusick-Nathans Institute of Genetic Medicine, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Institute of Bioinformatics, International Technology Park, Bangalore, India
| | - Daniel J Zabransky
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Arielle Medford
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Justin Lee
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Alex J Cole
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Marc Rosen
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Maya Thakar
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Alexander Ambinder
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Joshua Donaldson
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Amy E DeZern
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Karen Cravero
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - David Chu
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and
| | - Rafael Madero-Marroquin
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,Department of Medicine, Icahn School of Medicine, Mount Sinai St. Luke's Roosevelt Hospital Center, New York, New York, USA
| | - Akhilesh Pandey
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,McKusick-Nathans Institute of Genetic Medicine, Department of Biological Chemistry, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Institute of Bioinformatics, International Technology Park, Bangalore, India.,Manipal Academy of Higher Education (MAHE), Manipal, Karnataka, India.,Department of Pathology and
| | - Paula J Hurley
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,Department of Urology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Josh Lauring
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,Janssen Research and Development, Spring House, Pennsylvania, USA
| | - Ben Ho Park
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center, and.,Department of Chemical and Biomolecular Engineering, The Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.,Division of Hematology, Oncology, Department of Medicine, Vanderbilt Ingram Cancer Center, Nashville, Tennessee, USA
| |
Collapse
|
109
|
Lo W, Zhu B, Sabesan A, Wu HH, Powers A, Sorber RA, Ravichandran S, Chen I, McDuffie LA, Quadri HS, Beane JD, Calzone K, Miettinen MM, Hewitt SM, Koh C, Heller T, Wacholder S, Rudloff U. Associations of CDH1 germline variant location and cancer phenotype in families with hereditary diffuse gastric cancer (HDGC). J Med Genet 2019; 56:370-379. [PMID: 30745422 PMCID: PMC6716162 DOI: 10.1136/jmedgenet-2018-105361] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2018] [Revised: 12/11/2018] [Accepted: 01/03/2019] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Hereditary diffuse gastric cancer (HDGC) is a cancer syndrome associated with variants in E-cadherin (CDH1), diffuse gastric cancer and lobular breast cancer. There is considerable heterogeneity in its clinical manifestations. This study aimed to determine associations between CDH1 germline variant status and clinical phenotypes of HDGC. METHODS One hundred and fifty-two HDGC families, including six previously unreported families, were identified. CDH1 gene-specific guidelines released by the Clinical Genome Resource (ClinGen) CDH1 Variant Curation Expert Panel were applied for pathogenicity classification of truncating, missense and splice site CDH1 germline variants. We evaluated ORs between location of truncating variants of CDH1 and incidence of colorectal cancer, breast cancer and cancer at young age (gastric cancer at <40 or breast cancer <50 years of age). RESULTS Frequency of truncating germline CDH1 variants varied across functional domains of the E-cadherin receptor gene and was highest in linker (0.05785 counts/base pair; p=0.0111) and PRE regions (0.10000; p=0.0059). Families with truncating CDH1 germline variants located in the PRE-PRO region were six times more likely to have family members affected by colorectal cancer (OR 6.20, 95% CI 1.79 to 21.48; p=0.004) compared with germline variants in other regions. Variants in the intracellular E-cadherin region were protective for cancer at young age (OR 0.2, 95% CI 0.06 to 0.64; p=0.0071) and in the linker regions for breast cancer (OR 0.35, 95% CI 0.12 to 0.99; p=0.0493). Different CDH1 genotypes were associated with different intracellular signalling activation levels including different p-ERK, p-mTOR and β-catenin levels in early submucosal T1a lesions of HDGC families with different CDH1 variants. CONCLUSION Type and location of CDH1 germline variants may help to identify families at increased risk for concomitant cancers that might benefit from individualised surveillance and intervention strategies.
Collapse
Affiliation(s)
- Winifred Lo
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
| | - Bin Zhu
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, Maryland, USA
| | - Arvind Sabesan
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
| | - Ho-Hsiang Wu
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, Maryland, USA
| | - Astin Powers
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Rebecca A Sorber
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Department of Surgery, indiana University School of Medicine, indianapolis, indiana, USA
| | - Sarangan Ravichandran
- Advanced Biomedical Computing Center, Frederick National Laboratory for Cancer Research, Frederick, Maryland, USA
| | - Ina Chen
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Department of Surgery, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Lucas A McDuffie
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Department of Surgery, indiana University School of Medicine, indianapolis, indiana, USA
| | - Humair S Quadri
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Department of Surgery, MedStar Georgetown University Hospital, Washington, District of Columbia, USA
| | - Joal D Beane
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Department of Surgery, indiana University School of Medicine, indianapolis, indiana, USA
| | - Kathleen Calzone
- Genetics Branch, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Markku M Miettinen
- Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, Bethesda, Maryland, USA
| | - Stephen M Hewitt
- Experimental Pathology Laboratory, National Cancer Institute, Bethesda, Maryland, USA
| | - Christopher Koh
- Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA
| | - Theo Heller
- Liver Diseases Branch, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, Maryland, USA
| | - Sholom Wacholder
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institute of Health, Bethesda, Maryland, USA
| | - Udo Rudloff
- Thoracic and Surgical Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
- Rare Tumor initiative, Pediatric Oncology Branch, National Cancer Institute, Bethesda, Maryland, USA
| |
Collapse
|
110
|
Lake NJ, Formosa LE, Stroud DA, Ryan MT, Calvo SE, Mootha VK, Morar B, Procopis PG, Christodoulou J, Compton AG, Thorburn DR. A patient with homozygous nonsense variants in two Leigh syndrome disease genes: Distinguishing a dual diagnosis from a hypomorphic protein-truncating variant. Hum Mutat 2019; 40:893-898. [PMID: 30981218 DOI: 10.1002/humu.23753] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2018] [Revised: 03/19/2019] [Accepted: 03/24/2019] [Indexed: 01/04/2023]
Abstract
Leigh syndrome is a mitochondrial disease caused by pathogenic variants in over 85 genes. Whole exome sequencing of a patient with Leigh-like syndrome identified homozygous protein-truncating variants in two genes associated with Leigh syndrome; a reported pathogenic variant in PDHX (NP_003468.2:p.(Arg446*)), and an uncharacterized variant in complex I (CI) assembly factor TIMMDC1 (NP_057673.2:p.(Arg225*)). The TIMMDC1 variant was predicted to truncate 61 amino acids at the C-terminus and functional studies demonstrated a hypomorphic impact of the variant on CI assembly. However, the mutant protein could still rescue CI assembly in TIMMDC1 knockout cells and the patient's clinical phenotype was not clearly distinct from that of other patients with the same PDHX defect. Our data suggest that the hypomorphic effect of the TIMMDC1 protein-truncating variant does not constitute a dual diagnosis in this individual. We recommend cautious assessment of variants in the C-terminus of TIMMDC1 and emphasize the need to consider the caveats detailed within the American College of Medical Genetics and Genomics (ACMG) criteria when assessing variants.
Collapse
Affiliation(s)
- Nicole J Lake
- Brain and Mitochondrial Research, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - Luke E Formosa
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton Campus, Melbourne, Victoria, Australia
| | - David A Stroud
- Department of Biochemistry and Molecular Biology, The Bio21 Molecular Science and Biotechnology Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Michael T Ryan
- Department of Biochemistry and Molecular Biology, Monash Biomedicine Discovery Institute, Monash University, Clayton Campus, Melbourne, Victoria, Australia
| | - Sarah E Calvo
- Department of Molecular Biology, Howard Hughes Medical Institute, Massachusetts General Hospital, Boston, Massachusetts.,Department of Systems Biology, Harvard Medical School, Boston, Massachusetts.,Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Vamsi K Mootha
- Department of Molecular Biology, Howard Hughes Medical Institute, Massachusetts General Hospital, Boston, Massachusetts.,Department of Systems Biology, Harvard Medical School, Boston, Massachusetts.,Metabolism Program, Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Bharti Morar
- Centre for Clinical Research in Neuropsychiatry, School of Psychiatry and Clinical Neurosciences, University of Western Australia, Perth, Western Australia, Australia.,Mitochondrial Medicine and Biology, Harry Perkins Institute of Medical Research and Centre for Medical Research, University of Western Australia, Nedlands, Western Australia, Australia
| | - Peter G Procopis
- Department of Neurology, Children's Hospital at Westmead, Sydney, New South Wales, Australia.,Discipline of Child and Adolescent Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia
| | - John Christodoulou
- Brain and Mitochondrial Research, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia.,Discipline of Child and Adolescent Health, Sydney Medical School, University of Sydney, Sydney, New South Wales, Australia.,Mitochondrial Laboratory, Victorian Clinical Genetics Services, Royal Children's Hospital, Melbourne, Victoria, Australia
| | - Alison G Compton
- Brain and Mitochondrial Research, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia
| | - David R Thorburn
- Brain and Mitochondrial Research, Murdoch Children's Research Institute, Royal Children's Hospital, Melbourne, Victoria, Australia.,Department of Paediatrics, University of Melbourne, Melbourne, Victoria, Australia.,Mitochondrial Laboratory, Victorian Clinical Genetics Services, Royal Children's Hospital, Melbourne, Victoria, Australia
| |
Collapse
|
111
|
Dahl A, Guillemot V, Mefford J, Aschard H, Zaitlen N. Adjusting for Principal Components of Molecular Phenotypes Induces Replicating False Positives. Genetics 2019; 211:1179-1189. [PMID: 30692194 PMCID: PMC6456307 DOI: 10.1534/genetics.118.301768] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2018] [Accepted: 01/23/2019] [Indexed: 12/20/2022] Open
Abstract
High-throughput measurements of molecular phenotypes provide an unprecedented opportunity to model cellular processes and their impact on disease. These highly structured datasets are usually strongly confounded, creating false positives and reducing power. This has motivated many approaches based on principal components analysis (PCA) to estimate and correct for confounders, which have become indispensable elements of association tests between molecular phenotypes and both genetic and nongenetic factors. Here, we show that these correction approaches induce a bias, and that it persists for large sample sizes and replicates out-of-sample. We prove this theoretically for PCA by deriving an analytic, deterministic, and intuitive bias approximation. We assess other methods with realistic simulations, which show that perturbing any of several basic parameters can cause false positive rate (FPR) inflation. Our experiments show the bias depends on covariate and confounder sparsity, effect sizes, and their correlation. Surprisingly, when the covariate and confounder have [Formula: see text], standard two-step methods all have [Formula: see text]-fold FPR inflation. Our analysis informs best practices for confounder correction in genomic studies, and suggests many false discoveries have been made and replicated in some differential expression analyses.
Collapse
Affiliation(s)
- Andy Dahl
- Department of Medicine, University of California San Francisco, 94158 California
| | - Vincent Guillemot
- Centre de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur, Paris, 75015 France
| | - Joel Mefford
- Department of Medicine, University of California San Francisco, 94158 California
| | - Hugues Aschard
- Centre de Bioinformatique, Biostatistique et Biologie Intégrative, Institut Pasteur, Paris, 75015 France
- Department of Epidemiology, Harvard TH Chan School of Public Health, Boston, 02115 Massachusetts
| | - Noah Zaitlen
- Department of Medicine, University of California San Francisco, 94158 California
| |
Collapse
|
112
|
Lappalainen T, Scott AJ, Brandt M, Hall IM. Genomic Analysis in the Age of Human Genome Sequencing. Cell 2019; 177:70-84. [PMID: 30901550 PMCID: PMC6532068 DOI: 10.1016/j.cell.2019.02.032] [Citation(s) in RCA: 158] [Impact Index Per Article: 31.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2019] [Revised: 02/19/2019] [Accepted: 02/19/2019] [Indexed: 02/08/2023]
Abstract
Affordable genome sequencing technologies promise to revolutionize the field of human genetics by enabling comprehensive studies that interrogate all classes of genome variation, genome-wide, across the entire allele frequency spectrum. Ongoing projects worldwide are sequencing many thousands-and soon millions-of human genomes as part of various gene mapping studies, biobanking efforts, and clinical programs. However, while genome sequencing data production has become routine, genome analysis and interpretation remain challenging endeavors with many limitations and caveats. Here, we review the current state of technologies for genetic variant discovery, genotyping, and functional interpretation and discuss the prospects for future advances. We focus on germline variants discovered by whole-genome sequencing, genome-wide functional genomic approaches for predicting and measuring variant functional effects, and implications for studies of common and rare human disease.
Collapse
Affiliation(s)
- Tuuli Lappalainen
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA.
| | - Alexandra J Scott
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
| | - Margot Brandt
- New York Genome Center, New York, NY, USA; Department of Systems Biology, Columbia University, New York, NY, USA
| | - Ira M Hall
- McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA; Department of Medicine, Washington University School of Medicine, St. Louis, MO, USA; Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
| |
Collapse
|
113
|
Manzoni C, Kia DA, Vandrovcova J, Hardy J, Wood NW, Lewis PA, Ferrari R. Genome, transcriptome and proteome: the rise of omics data and their integration in biomedical sciences. Brief Bioinform 2019; 19:286-302. [PMID: 27881428 PMCID: PMC6018996 DOI: 10.1093/bib/bbw114] [Citation(s) in RCA: 388] [Impact Index Per Article: 77.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2016] [Indexed: 02/07/2023] Open
Abstract
Advances in the technologies and informatics used to generate and process large biological data sets (omics data) are promoting a critical shift in the study of biomedical sciences. While genomics, transcriptomics and proteinomics, coupled with bioinformatics and biostatistics, are gaining momentum, they are still, for the most part, assessed individually with distinct approaches generating monothematic rather than integrated knowledge. As other areas of biomedical sciences, including metabolomics, epigenomics and pharmacogenomics, are moving towards the omics scale, we are witnessing the rise of inter-disciplinary data integration strategies to support a better understanding of biological systems and eventually the development of successful precision medicine. This review cuts across the boundaries between genomics, transcriptomics and proteomics, summarizing how omics data are generated, analysed and shared, and provides an overview of the current strengths and weaknesses of this global approach. This work intends to target students and researchers seeking knowledge outside of their field of expertise and fosters a leap from the reductionist to the global-integrative analytical approach in research.
Collapse
Affiliation(s)
- Claudia Manzoni
- School of Pharmacy, University of Reading, Whiteknights, Reading, United Kingdom.,Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Demis A Kia
- Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Jana Vandrovcova
- Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - John Hardy
- Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Nicholas W Wood
- Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Patrick A Lewis
- School of Pharmacy, University of Reading, Whiteknights, Reading, United Kingdom.,Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| | - Raffaele Ferrari
- Department Molecular Neuroscience, UCL Institute of Neurology, London, United Kingdom
| |
Collapse
|
114
|
Abstract
PURPOSE OF REVIEW The purpose of this review was to summarize recent advances in the genomics of type 2 diabetes (T2D) and to highlight current initiatives to advance precision health. RECENT FINDINGS Generation of multi-omic data to measure each of the "biologic layers," developments in describing genomic function and annotation in T2D relevant tissue, along with the increasing recognition that T2D is a heterogeneous disease, and large-scale collaborations have all contributed to advancing our understanding of the molecular basis of T2D. Substantial advances have been made in understanding the molecular basis of T2D pathogenesis, such that precision health diabetes is increasingly becoming a reality. For precision diabetes to become a routine in clinical and public health, additional large-scale multi-omic initiatives are needed along with better assessment of our environment to delineate an individual's diabetes subtype for improved detection and management.
Collapse
Affiliation(s)
- Yuan Lin
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Jennifer Wessel
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA.
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA.
- Diabetes Translational Research Center, Indiana University School of Medicine, Indianapolis, IN, USA.
| |
Collapse
|
115
|
Agler CS, Shungin D, Ferreira Zandoná AG, Schmadeke P, Basta PV, Luo J, Cantrell J, Pahel TD, Meyer BD, Shaffer JR, Schaefer AS, North KE, Divaris K. Protocols, Methods, and Tools for Genome-Wide Association Studies (GWAS) of Dental Traits. Methods Mol Biol 2019; 1922:493-509. [PMID: 30838596 PMCID: PMC6613560 DOI: 10.1007/978-1-4939-9012-2_38] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Oral health and disease are known to be influenced by complex interactions between environmental (e.g., social and behavioral) factors and innate susceptibility. Although the exact contribution of genomics and other layers of "omics" to oral health is an area of active research, it is well established that the susceptibility to dental caries, periodontal disease, and other oral and craniofacial traits is substantially influenced by the human genome. A comprehensive understanding of these genomic factors is necessary for the realization of precision medicine in the oral health domain. To aid in this direction, the advent and increasing affordability of high-throughput genotyping has enabled the simultaneous interrogation of millions of genetic polymorphisms for association with oral and craniofacial traits. Specifically, genome-wide association studies (GWAS) of dental caries and periodontal disease have provided initial insights into novel loci and biological processes plausibly implicated in these two common, complex, biofilm-mediated diseases. This paper presents a summary of protocols, methods, tools, and pipelines for the conduct of GWAS of dental caries, periodontal disease, and related traits. The protocol begins with the consideration of different traits for both diseases and outlines procedures for genotyping, quality control, adjustment for population stratification, heritability and association analyses, annotation, reporting, and interpretation. Methods and tools available for GWAS are being constantly updated and improved; with this in mind, the presented approaches have been successfully applied in numerous GWAS and meta-analyses among tens of thousands of individuals, including dental traits such as dental caries and periodontal disease. As such, they can serve as a guide or template for future genomic investigations of these and other traits.
Collapse
Affiliation(s)
- Cary S Agler
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Dmitry Shungin
- Department of Odontology, Umeå University, Umeå, Sweden
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA
| | - Andrea G Ferreira Zandoná
- Department of Comprehensive Dentistry, Tufts University School of Dental Medicine, Tufts University, Boston, MA, USA
| | - Paige Schmadeke
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Biospecimen Core Processing Facility, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Patricia V Basta
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Biospecimen Core Processing Facility, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Jason Luo
- Lineberger Comprehensive Cancer Center, School of Medicine, University of North Carolina, Chapel Hill, NC, USA
- Mammalian Genotyping Core, University of North Carolina, Chapel Hill, NC, USA
| | - John Cantrell
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Thomas D Pahel
- Oral and Craniofacial Health Sciences, UNC School of Dentistry, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Beau D Meyer
- Department of Pediatric Dentistry, UNC School of Dentistry, CB#7450, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - John R Shaffer
- Center for Craniofacial and Dental Genetics, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Oral Biology, School of Dental Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Arne S Schaefer
- Department of Periodontology, Institute of Dental, Oral and Maxillary Medicine, Charité-University Medicine Berlin, Berlin, Germany
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA
| | - Kimon Divaris
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
- Department of Pediatric Dentistry, UNC School of Dentistry, CB#7450, University of North Carolina-Chapel Hill, Chapel Hill, NC, USA.
| |
Collapse
|
116
|
Frayling IM, Mautner VF, van Minkelen R, Kallionpaa RA, Aktaş S, Baralle D, Ben-Shachar S, Callaway A, Cox H, Eccles DM, Ferkal S, LaDuca H, Lázaro C, Rogers MT, Stuenkel AJ, Summerour P, Varan A, Yap YS, Zehou O, Peltonen J, Evans DG, Wolkenstein P, Upadhyaya M. Breast cancer risk in neurofibromatosis type 1 is a function of the type of NF1 gene mutation: a new genotype-phenotype correlation. J Med Genet 2018; 56:209-219. [DOI: 10.1136/jmedgenet-2018-105599] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2018] [Revised: 10/30/2018] [Accepted: 11/15/2018] [Indexed: 01/19/2023]
Abstract
BackgroundNeurofibromatosis type 1 (NF1) predisposes to breast cancer (BC), but no genotype-phenotype correlations have been described.MethodsConstitutional NF1 mutations in 78 patients with NF1 with BC (NF1-BC) were compared with the NF1 Leiden Open Variation Database (n=3432).ResultsNo cases were observed with whole or partial gene deletions (HR 0.10; 95% CI 0.006 to 1.63; p=0.014, Fisher’s exact test). There were no gross relationships with mutation position. Forty-five (64.3%; HR 6.4–83) of the 70 different mutations were more frequent than expected (p<0.05), while 52 (74.3%; HR 5.3–83) were significant when adjusted for multiple comparisons (adjusted p≤0.125; Benjamini-Hochberg). Higher proportions of both nonsense and missense mutations were also observed (adjusted p=0.254; Benjamini-Hochberg). Ten of the 11 missense cases with known age of BC occurred at <50 years (p=0.041). Eighteen cases had BRCA1/2 testing, revealing one BRCA2 mutation.DiscussionThese data strongly support the hypothesis that certain constitutional mutation types, and indeed certain specific variants in NF1 confer different risks of BC. The lack of large deletions and excess of nonsenses and missenses is consistent with gain of function mutations conferring risk of BC, and also that neurofibromin may function as a dimer. The observation that somatic NF1 amplification can occur independently of ERBB2 amplification in sporadic BC supports this concept. A prospective clinical-molecular study of NF1-BC needs to be established to confirm and build on these findings, but regardless of NF1 mutation status patients with NF1-BC warrant testing of other BC-predisposing genes.
Collapse
|
117
|
Allelic imbalance and haploinsufficiency in MYBPC3-linked hypertrophic cardiomyopathy. Pflugers Arch 2018; 471:781-793. [PMID: 30456444 DOI: 10.1007/s00424-018-2226-9] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 10/04/2018] [Accepted: 10/17/2018] [Indexed: 01/04/2023]
Abstract
Mutations in cardiac myosin binding protein C (MYBPC3) represent the most frequent cause of familial hypertrophic cardiomyopathy (HCM), making up approximately 50% of identified HCM mutations. MYBPC3 is distinct among other sarcomere genes associated with HCM in that truncating mutations make up the vast majority, whereas nontruncating mutations predominant in other sarcomere genes. Several studies using myocardial tissue from HCM patients have found reduced abundance of wild-type MYBPC3 compared to control hearts, suggesting haploinsufficiency of full-length MYBPC3. Further, decreased mutant versus wild-type mRNA and lack of truncated mutant MYBPC3 protein has been demonstrated, highlighting the presence of allelic imbalance. In this review, we will begin by introducing allelic imbalance and haploinsufficiency, highlighting the broad role each plays within the spectrum of human disease. We will subsequently focus on the roles allelic imbalance and haploinsufficiency play within MYBPC3-linked HCM. Finally, we will explore the implications of these findings on future directions of HCM research. An improved understanding of allelic imbalance and haploinsufficiency may help us better understand genotype-phenotype relationships in HCM and develop novel targeted therapies, providing exciting future research opportunities.
Collapse
|
118
|
Ye CJ, Chen J, Villani AC, Gate RE, Subramaniam M, Bhangale T, Lee MN, Raj T, Raychowdhury R, Li W, Rogel N, Simmons S, Imboywa SH, Chipendo PI, McCabe C, Lee MH, Frohlich IY, Stranger BE, De Jager PL, Regev A, Behrens T, Hacohen N. Genetic analysis of isoform usage in the human anti-viral response reveals influenza-specific regulation of ERAP2 transcripts under balancing selection. Genome Res 2018; 28:1812-1825. [PMID: 30446528 PMCID: PMC6280757 DOI: 10.1101/gr.240390.118] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Accepted: 10/09/2018] [Indexed: 02/02/2023]
Abstract
While genetic variants are known to be associated with overall gene abundance in stimulated immune cells, less is known about their effects on alternative isoform usage. By analyzing RNA-seq profiles of monocyte-derived dendritic cells from 243 individuals, we uncovered thousands of unannotated isoforms synthesized in response to influenza infection and type 1 interferon stimulation. We identified more than a thousand quantitative trait loci (QTLs) associated with alternate isoform usage (isoQTLs), many of which are independent of expression QTLs (eQTLs) for the same gene. Compared with eQTLs, isoQTLs are enriched for splice sites and untranslated regions, but depleted of sequences upstream of annotated transcription start sites. Both eQTLs and isoQTLs explain a significant proportion of the disease heritability attributed to common genetic variants. At the ERAP2 locus, we shed light on the function of the gene and how two frequent, highly differentiated haplotypes with intermediate frequencies could be maintained by balancing selection. At baseline and following type 1 interferon stimulation, the major haplotype is associated with low ERAP2 expression caused by nonsense-mediated decay, while the minor haplotype, known to increase Crohn's disease risk, is associated with high ERAP2 expression. In response to influenza infection, we found two uncharacterized isoforms expressed from the major haplotype, likely the result of multiple perfectly linked variants affecting the transcription and splicing at the locus. Thus, genetic variants at a single locus could modulate independent gene regulatory processes in innate immune responses and, in the case of ERAP2, may confer a historical fitness advantage in response to virus.
Collapse
Affiliation(s)
- Chun Jimmie Ye
- Institute for Human Genetics, Institute for Health and Computational Sciences, Department of Biostatistics and Epidemiology, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94143, USA
| | - Jenny Chen
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Department of Medicine, Massachusetts General Hospital Cancer Center, Boston, Massachusetts 02114, USA
| | - Rachel E Gate
- Institute for Human Genetics, Institute for Health and Computational Sciences, Department of Biostatistics and Epidemiology, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94143, USA.,Biomedical Informatics Program, University of California, San Francisco, California 94143, USA
| | - Meena Subramaniam
- Institute for Human Genetics, Institute for Health and Computational Sciences, Department of Biostatistics and Epidemiology, Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California 94143, USA.,Biomedical Informatics Program, University of California, San Francisco, California 94143, USA
| | - Tushar Bhangale
- Genentech Incorporated, South San Francisco, California 94080, USA
| | - Mark N Lee
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Department of Medicine, Massachusetts General Hospital Cancer Center, Boston, Massachusetts 02114, USA.,Harvard Medical School, Boston, Massachusetts 02116, USA
| | - Towfique Raj
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Harvard Medical School, Boston, Massachusetts 02116, USA.,Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
| | | | - Weibo Li
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Noga Rogel
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Sean Simmons
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | | | | | - Cristin McCabe
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
| | - Michelle H Lee
- Harvard Medical School, Boston, Massachusetts 02116, USA
| | | | - Barbara E Stranger
- Section of Genetic Medicine, Department of Medicine, Institute for Genomics and Systems Biology, Center for Data Intensive Science, The University of Chicago, Chicago, Illinois 60637, USA
| | - Philip L De Jager
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Harvard Medical School, Boston, Massachusetts 02116, USA.,Departments of Neurology and Psychiatry, Brigham and Women's Hospital, Boston, Massachusetts 02115, USA
| | - Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Department of Biology, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, USA.,Howard Hughes Medical Institute, Chevy Chase, Maryland 20815, USA
| | - Tim Behrens
- Genentech Incorporated, South San Francisco, California 94080, USA
| | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA.,Department of Medicine, Massachusetts General Hospital Cancer Center, Boston, Massachusetts 02114, USA
| |
Collapse
|
119
|
Stenton SL, Prokisch H. The Clinical Application of RNA Sequencing in Genetic Diagnosis of Mendelian Disorders. ACTA ACUST UNITED AC 2018. [DOI: 10.1016/j.yamp.2018.06.004] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
120
|
Lee K, Krempely K, Roberts ME, Anderson MJ, Carneiro F, Chao E, Dixon K, Figueiredo J, Ghosh R, Huntsman D, Kaurah P, Kesserwan C, Landrith T, Li S, Mensenkamp AR, Oliveira C, Pardo C, Pesaran T, Richardson M, Slavin TP, Spurdle AB, Trapp M, Witkowski L, Yi CS, Zhang L, Plon SE, Schrader KA, Karam R. Specifications of the ACMG/AMP variant curation guidelines for the analysis of germline CDH1 sequence variants. Hum Mutat 2018; 39:1553-1568. [PMID: 30311375 PMCID: PMC6188664 DOI: 10.1002/humu.23650] [Citation(s) in RCA: 103] [Impact Index Per Article: 17.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 08/30/2018] [Accepted: 09/06/2018] [Indexed: 12/22/2022]
Abstract
The variant curation guidelines published in 2015 by the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) provided the genetics community with a framework to assess variant pathogenicity; however, these rules are not gene specific. Germline pathogenic variants in the CDH1 gene cause hereditary diffuse gastric cancer and lobular breast cancer, a clinically challenging cancer predisposition syndrome that often requires a multidisciplinary team of experts to be properly managed. Given this challenge, the Clinical Genome Resource (ClinGen) Hereditary Cancer Domain prioritized the development of the CDH1 variant curation expert panel (VCEP) to develop and implement rules for CDH1 variant classifications. Here, we describe the CDH1 specifications of the ACMG/AMP guidelines, which were developed and validated after a systematic evaluation of variants obtained from a cohort of clinical laboratory data encompassing ∼827,000 CDH1 sequenced alleles. Comparing previously reported germline variants that were classified using the 2015 ACMG/AMP guidelines to the CDH1 VCEP recommendations resulted in reduced variants of uncertain significance and facilitated resolution of variants with conflicted assertions in ClinVar. The ClinGen CDH1 VCEP recommends the use of these CDH1-specific guidelines for the assessment and classification of variants identified in this clinically actionable gene.
Collapse
Affiliation(s)
- Kristy Lee
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | | | | | - Fatima Carneiro
- Institute for Research and Innovation in Health of the University of Porto, Instituto de Investigação e Inovação em Saúde – (i3S), Faculty of Medicine – University of Porto, Porto, PRT
| | - Elizabeth Chao
- Ambry Genetics, Aliso Viejo, CA, USA
- University of California Irvine, Irvine, CA, USA
| | | | - Joana Figueiredo
- Institute for Research and Innovation in Health of the University of Porto, Instituto de Investigação e Inovação em Saúde – (i3S), Faculty of Medicine – University of Porto, Porto, PRT
| | | | | | | | | | | | - Shuwei Li
- Ambry Genetics, Aliso Viejo, CA, USA
| | | | - Carla Oliveira
- Institute for Research and Innovation in Health of the University of Porto, Instituto de Investigação e Inovação em Saúde – (i3S), Faculty of Medicine – University of Porto, Porto, PRT
| | | | | | | | - Thomas P. Slavin
- Department of Medical Oncology and Therapeutics Research, City of Hope, Duarte, CA, USA
| | | | - Mackenzie Trapp
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Leora Witkowski
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, MA, USA
| | | | | | | | - Kasmintan A. Schrader
- Institute for Research and Innovation in Health of the University of Porto, Instituto de Investigação e Inovação em Saúde – (i3S), Faculty of Medicine – University of Porto, Porto, PRT
| | | |
Collapse
|
121
|
Heller R, Chatterjee N, Krieger A, Shi J. Post-Selection Inference Following Aggregate Level Hypothesis Testing in Large-Scale Genomic Data. J Am Stat Assoc 2018. [DOI: 10.1080/01621459.2017.1375933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Affiliation(s)
- Ruth Heller
- Department of Statistics and Operations Research, Tel-Aviv University, Tel-Aviv, Israel
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
| | - Nilanjan Chatterjee
- Department of Biostatistics, Bloomberg School of Public Health, and Department of Oncology, School of Medicine, Johns Hopkins University, Baltimore, MD
| | - Abba Krieger
- Department of Statistics, University of Pennsylvania, Philadelphia, PA
| | - Jianxin Shi
- Biostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD
| |
Collapse
|
122
|
Zhang Q, Cong M, Wang N, Li X, Zhang H, Zhang K, Jin M, Wu N, Qiu C, Li J. Association of angiotensin-converting enzyme 2 gene polymorphism and enzymatic activity with essential hypertension in different gender: A case-control study. Medicine (Baltimore) 2018; 97:e12917. [PMID: 30335025 PMCID: PMC6211892 DOI: 10.1097/md.0000000000012917] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Angiotensin-converting enzyme 2 (ACE2) plays an important role in the development of essential hypertension (EH). The aim of this study was to investigate the relationship of ACE2 gene polymorphisms and enzymatic activity with EH in the northeastern Chinese Han population. 34 single-nucleotide polymorphism (SNP) loci of ACE2 were detected in 1024 EH patients and 956 normotensive (NT) controls by Sequenom Mass-ARRAY RS1000. Five SNPs (rs1514283, rs4646155, rs4646176, rs2285666, and rs879922) in ACE2 gene were determined to significantly associate with EH in female participants, while no SNP locus was linked to male group. Specifically, it was the first time to report that rs4646155 was significantly associated with EH in females. Furthermore, the correlation between ACE2 activity and clinical parameters were performed by Pearson correlation analysis in EH patients. We found that the ACE2 activity level was negatively correlated with body mass index (BMI), DBP, and pulse pressure, and significantly positively with ACE2 concentration, blood glucose and estrogen level in female EH patients. These results demonstrated that the genetic variants of ACE2 played vital roles in the development of EH. And the serum ACE2 activity can predict the development of cardiac dysfunction in EH patients.
Collapse
Affiliation(s)
- Qi Zhang
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Mingyu Cong
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Ningning Wang
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Xueyan Li
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Hao Zhang
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Keyong Zhang
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Ming Jin
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Nan Wu
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| | - Changchun Qiu
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
- Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, P. R. China
| | - Jingping Li
- Institute of Medicine and Drug Research, Qiqihar Medical University, Qiqihar, Heilongjiang Province
| |
Collapse
|
123
|
Abou Tayoun AN, Pesaran T, DiStefano MT, Oza A, Rehm HL, Biesecker LG, Harrison SM. Recommendations for interpreting the loss of function PVS1 ACMG/AMP variant criterion. Hum Mutat 2018; 39:1517-1524. [PMID: 30192042 DOI: 10.1002/humu.23626] [Citation(s) in RCA: 479] [Impact Index Per Article: 79.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 07/15/2018] [Accepted: 08/23/2018] [Indexed: 12/24/2022]
Abstract
The 2015 ACMG/AMP sequence variant interpretation guideline provided a framework for classifying variants based on several benign and pathogenic evidence criteria, including a pathogenic criterion (PVS1) for predicted loss of function variants. However, the guideline did not elaborate on specific considerations for the different types of loss of function variants, nor did it provide decision-making pathways assimilating information about variant type, its location, or any additional evidence for the likelihood of a true null effect. Furthermore, this guideline did not take into account the relative strengths for each evidence type and the final outcome of their combinations with respect to PVS1 strength. Finally, criteria specifying the genes for which PVS1 can be applied are still missing. Here, as part of the ClinGen Sequence Variant Interpretation (SVI) Workgroup's goal of refining ACMG/AMP criteria, we provide recommendations for applying the PVS1 criterion using detailed guidance addressing the above-mentioned gaps. Evaluation of the refined criterion by seven disease-specific groups using heterogeneous types of loss of function variants (n = 56) showed 89% agreement with the new recommendation, while discrepancies in six variants (11%) were appropriately due to disease-specific refinements. Our recommendations will facilitate consistent and accurate interpretation of predicted loss of function variants.
Collapse
Affiliation(s)
- Ahmad N Abou Tayoun
- The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.,The University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania
| | | | - Marina T DiStefano
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, Massachusetts
| | - Andrea Oza
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, Massachusetts
| | - Heidi L Rehm
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, Massachusetts.,Center for Genomic Medicine, Massachusetts General Hospital, Boston, Massachusetts.,The Broad Institute of MIT and Harvard, Cambridge, Massachusetts
| | - Leslie G Biesecker
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Steven M Harrison
- Laboratory for Molecular Medicine, Partners Healthcare Personalized Medicine, Cambridge, Massachusetts
| | | |
Collapse
|
124
|
Filatova EN, Utkin OV. The Role of Noncoding mRNA Isoforms in the Regulation of Gene Expression. RUSS J GENET+ 2018. [DOI: 10.1134/s1022795418080057] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
|
125
|
Coban-Akdemir Z, White JJ, Song X, Jhangiani SN, Fatih JM, Gambin T, Bayram Y, Chinn IK, Karaca E, Punetha J, Poli C, Boerwinkle E, Shaw CA, Orange JS, Gibbs RA, Lappalainen T, Lupski JR, Carvalho CM, Carvalho CMB. Identifying Genes Whose Mutant Transcripts Cause Dominant Disease Traits by Potential Gain-of-Function Alleles. Am J Hum Genet 2018; 103:171-187. [PMID: 30032986 DOI: 10.1016/j.ajhg.2018.06.009] [Citation(s) in RCA: 150] [Impact Index Per Article: 25.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2018] [Accepted: 06/14/2018] [Indexed: 12/14/2022] Open
Abstract
Premature termination codon (PTC)-bearing transcripts are often degraded by nonsense-mediated decay (NMD) resulting in loss-of-function (LoF) alleles. However, not all PTCs result in LoF mutations, i.e., some such transcripts escape NMD and are translated to truncated peptide products that result in disease due to gain-of-function (GoF) effects. Since the location of the PTC is a major factor determining transcript fate, we hypothesized that depletion of protein-truncating variants (PTVs) within the gene region predicted to escape NMD in control databases could provide a rank for genic susceptibility for disease through GoF versus LoF. We developed an NMD escape intolerance score to rank genes based on the depletion of PTVs that would render them able to escape NMD using the Atherosclerosis Risk in Communities Study (ARIC) and the Exome Aggregation Consortium (ExAC) control databases, which was further used to screen the Baylor-Center for Mendelian Genomics disease database. This analysis revealed 1,996 genes significantly depleted for PTVs that are predicted to escape from NMD, i.e., PTVesc; further studies provided evidence that revealed a subset as candidate genes underlying Mendelian phenotypes. Importantly, these genes have characteristically low pLI scores, which can cause them to be overlooked as candidates for dominant diseases. Collectively, we demonstrate that this NMD escape intolerance score is an effective and efficient tool for gene discovery in Mendelian diseases due to production of truncated or altered proteins. More importantly, we provide a complementary analytical tool to aid identification of genes associated with dominant traits through a mechanism distinct from LoF.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Claudia M B Carvalho
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX 77030, USA.
| |
Collapse
|
126
|
Krempely K, Karam R. A novel de novo CDH1 germline variant aids in the classification of carboxy-terminal E-cadherin alterations predicted to escape nonsense-mediated mRNA decay. Cold Spring Harb Mol Case Stud 2018; 4:mcs.a003012. [PMID: 29798843 PMCID: PMC6071572 DOI: 10.1101/mcs.a003012] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Accepted: 05/16/2018] [Indexed: 12/30/2022] Open
Abstract
Most truncating cadherin 1 (CDH1) pathogenic alterations confer an elevated lifetime risk of diffuse gastric cancer (DGC) and lobular breast cancer (LBC). However, transcripts containing carboxy-terminal premature stop codons have been demonstrated to escape the nonsense-mediated mRNA decay pathway, and gastric and breast cancer risks associated with these truncations should be carefully evaluated. A female patient underwent multigene panel testing because of a personal history of invasive LBC diagnosed at age 54, which identified the germline CDH1 nonsense alteration, c.2506G>T (p.Glu836*), in the last exon of the gene. Subsequent parental testing for the alteration was negative and additional short tandem repeat analysis confirmed the familial relationships and the de novo occurrence in the proband. Based on the de novo occurrence, clinical history, and rarity in general population databases, this alteration was classified as a likely pathogenic variant. This is the most carboxy-terminal pathogenic alteration reported to date. Additionally, this alteration contributed to the classification of six other upstream CDH1 carboxy-terminal truncating variants as pathogenic or likely pathogenic. Identifying the most distal pathogenic alteration provides evidence to classify other carboxy-terminal truncating variants as either pathogenic or benign, a fundamental step to offering presymptomatic screening and prophylactic procedures to the appropriate patients.
Collapse
Affiliation(s)
| | - Rachid Karam
- Ambry Genetics, Aliso Viejo, California 92656, USA
| |
Collapse
|
127
|
Abstract
Single-cell analyses have revealed a tremendous variety among cells in the abundance and chemical composition of RNA. Much of this heterogeneity is due to alternative splicing by the spliceosome. Little is known about how many of the resulting isoforms are biologically functional or just provide noise with little to no impact. The dynamic nature of the spliceosome provides numerous opportunities for regulation but is also the source of stochastic fluctuations. We discuss possible origins of splicing stochasticity, the experimental approaches for studying heterogeneity in isoforms, and the potential biological significance of noisy splicing in development and disease.
Collapse
Affiliation(s)
- Yihan Wan
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA
| | - Daniel R Larson
- Laboratory of Receptor Biology and Gene Expression, Center for Cancer Research, National Cancer Institute, Bethesda, MD, 20892, USA.
| |
Collapse
|
128
|
Genome Sequencing in Hypertrophic Cardiomyopathy. J Am Coll Cardiol 2018; 72:430-433. [DOI: 10.1016/j.jacc.2018.05.029] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/15/2018] [Revised: 05/24/2018] [Accepted: 05/24/2018] [Indexed: 11/20/2022]
|
129
|
Zhang S, Samocha KE, Rivas MA, Karczewski KJ, Daly E, Schmandt B, Neale BM, MacArthur DG, Daly MJ. Base-specific mutational intolerance near splice sites clarifies the role of nonessential splice nucleotides. Genome Res 2018; 28:968-974. [PMID: 29858273 PMCID: PMC6028136 DOI: 10.1101/gr.231902.117] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 05/31/2018] [Indexed: 12/20/2022]
Abstract
Variation in RNA splicing (i.e., alternative splicing) plays an important role in many diseases. Variants near 5' and 3' splice sites often affect splicing, but the effects of these variants on splicing and disease have not been fully characterized beyond the two "essential" splice nucleotides flanking each exon. Here we provide quantitative measurements of tolerance to mutational disruptions by position and reference allele-alternative allele combinations. We show that certain reference alleles are particularly sensitive to mutations, regardless of the alternative alleles into which they are mutated. Using public RNA-seq data, we demonstrate that individuals carrying such variants have significantly lower levels of the correctly spliced transcript, compared to individuals without them, and confirm that these specific substitutions are highly enriched for known Mendelian mutations. Our results propose a more refined definition of the "splice region" and offer a new way to prioritize and provide functional interpretation of variants identified in diagnostic sequencing and association studies.
Collapse
Affiliation(s)
- Sidi Zhang
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Kaitlin E Samocha
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, Massachusetts 02115, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Manuel A Rivas
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Emma Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Ben Schmandt
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Daniel G MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
| | - Mark J Daly
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, Massachusetts 02114, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, Massachusetts 02142, USA
- Institute for Molecular Medicine Finland (FIMM), 00290 Helsinki, Finland
| |
Collapse
|
130
|
Wang Z, Ng KS, Chen T, Kim TB, Wang F, Shaw K, Scott KL, Meric-Bernstam F, Mills GB, Chen K. Cancer driver mutation prediction through Bayesian integration of multi-omic data. PLoS One 2018; 13:e0196939. [PMID: 29738578 PMCID: PMC5940219 DOI: 10.1371/journal.pone.0196939] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2017] [Accepted: 04/23/2018] [Indexed: 01/23/2023] Open
Abstract
Identification of cancer driver mutations is critical for advancing cancer research and personalized medicine. Due to inter-tumor genetic heterogeneity, many driver mutations occur at low frequencies, which make it challenging to distinguish them from passenger mutations. Here, we show that a novel Bayesian hierarchical modeling approach, named rDriver can achieve enhanced prediction accuracy by identifying mutations that not only have high functional impact scores but also are associated with systemic variation in gene expression levels. In examining 3,080 tumor samples from 8 cancer types in The Cancer Genome Atlas, rDriver predicted 1,389 driver mutations. Compared with existing tools, rDriver identified more low frequency mutations associated with lineage specific functional properties, timing of occurrence and patient survival. Evaluation of rDriver predictions using engineered cell-line models resulted in a positive predictive value of 0.94 in PIK3CA genes. Our study highlights the importance of integrating multi-omic data in predicting cancer driver mutations and provides a statistically rigorous solution for cancer target discovery and development.
Collapse
Affiliation(s)
- Zixing Wang
- Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Kwok-Shing Ng
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Tenghui Chen
- Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Tae-Beom Kim
- Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Fang Wang
- Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Kenna Shaw
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Kenneth L. Scott
- Department of Human and Molecular Genetics, Baylor College of Medicine, Houston, Texas, United States of America
| | - Funda Meric-Bernstam
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
- Department of Investigational Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Gordon B. Mills
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
- Department of Systems Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
- Institute for Personalized Cancer Therapy, The University of Texas M.D. Anderson Cancer Center, Houston, Texas, United States of America
- * E-mail:
| |
Collapse
|
131
|
Barshir R, Hekselman I, Shemesh N, Sharon M, Novack L, Yeger-Lotem E. Role of duplicate genes in determining the tissue-selectivity of hereditary diseases. PLoS Genet 2018; 14:e1007327. [PMID: 29723191 PMCID: PMC5953478 DOI: 10.1371/journal.pgen.1007327] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2017] [Revised: 05/15/2018] [Accepted: 03/21/2018] [Indexed: 11/18/2022] Open
Abstract
A longstanding puzzle in human genetics is what limits the clinical manifestation of hundreds of hereditary diseases to certain tissues, while their causal genes are expressed throughout the human body. A general conception is that tissue-selective disease phenotypes emerge when masking factors operate in unaffected tissues, but are specifically absent or insufficient in disease-manifesting tissues. Although this conception has critical impact on the understanding of disease manifestation, it was never challenged in a systematic manner across a variety of hereditary diseases and affected tissues. Here, we address this gap in our understanding via rigorous analysis of the susceptibility of over 30 tissues to 112 tissue-selective hereditary diseases. We focused on the roles of paralogs of causal genes, which are presumably capable of compensating for their aberration. We show for the first time at large-scale via quantitative analysis of omics datasets that, preferentially in the disease-manifesting tissues, paralogs are under-expressed relative to causal genes in more than half of the diseases. This was observed for several susceptible tissues and for causal genes with varying number of paralogs, suggesting that imbalanced expression of paralogs increases tissue susceptibility. While for many diseases this imbalance stemmed from up-regulation of the causal gene in the disease-manifesting tissue relative to other tissues, it was often combined with down-regulation of its paralog. Notably in roughly 20% of the cases, this imbalance stemmed only from significant down-regulation of the paralog. Thus, dosage relationships between paralogs appear as important, yet currently under-appreciated, modifiers of disease manifestation.
Collapse
Affiliation(s)
- Ruth Barshir
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Idan Hekselman
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Netta Shemesh
- Department of Life Sciences, Faculty of Natural Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Moran Sharon
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Lena Novack
- Department of Public Health, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| | - Esti Yeger-Lotem
- Department of Clinical Biochemistry and Pharmacology, Faculty of Health Sciences, Ben-Gurion University of the Negev, Beer-Sheva, Israel
- National Institute for Biotechnology in the Negev, Ben-Gurion University of the Negev, Beer-Sheva, Israel
| |
Collapse
|
132
|
DeBoever C, Tanigawa Y, Lindholm ME, McInnes G, Lavertu A, Ingelsson E, Chang C, Ashley EA, Bustamante CD, Daly MJ, Rivas MA. Medical relevance of protein-truncating variants across 337,205 individuals in the UK Biobank study. Nat Commun 2018; 9:1612. [PMID: 29691392 PMCID: PMC5915386 DOI: 10.1038/s41467-018-03910-9] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2017] [Accepted: 03/21/2018] [Indexed: 02/08/2023] Open
Abstract
Protein-truncating variants can have profound effects on gene function and are critical for clinical genome interpretation and generating therapeutic hypotheses, but their relevance to medical phenotypes has not been systematically assessed. Here, we characterize the effect of 18,228 protein-truncating variants across 135 phenotypes from the UK Biobank and find 27 associations between medical phenotypes and protein-truncating variants in genes outside the major histocompatibility complex. We perform phenome-wide analyses and directly measure the effect in homozygous carriers, commonly referred to as “human knockouts,” across medical phenotypes for genes implicated as being protective against disease or associated with at least one phenotype in our study. We find several genes with strong pleiotropic or non-additive effects. Our results illustrate the importance of protein-truncating variants in a variety of diseases. Protein-truncating variants (PTVs) are predicted to significantly affect a gene’s function and, thus, human traits. Here, DeBoever et al. systematically analyze PTVs in more than 300,000 individuals across 135 phenotypes and identify 27 associations between PTVs and medical conditions.
Collapse
Affiliation(s)
- Christopher DeBoever
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.,Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Yosuke Tanigawa
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA
| | | | - Greg McInnes
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA
| | - Adam Lavertu
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA
| | - Erik Ingelsson
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Chris Chang
- Grail, Inc., 1525 O'Brien Drive, Menlo Park, CA, 94025, USA
| | - Euan A Ashley
- Department of Medicine, School of Medicine, Stanford University, Stanford, CA, 94305, USA
| | - Carlos D Bustamante
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.,Department of Genetics, Stanford University, Stanford, CA, 94305, USA
| | - Mark J Daly
- Analytical and Translational Genetics Unit, Boston, MA, 02114, USA.,Broad Institute of MIT and Harvard, Cambridge, 02142, MA, USA
| | - Manuel A Rivas
- Department of Biomedical Data Science, Stanford University, Stanford, CA, 94305, USA.
| |
Collapse
|
133
|
Mutations in the pancreatic secretory enzymes CPA1 and CPB1 are associated with pancreatic cancer. Proc Natl Acad Sci U S A 2018; 115:4767-4772. [PMID: 29669919 DOI: 10.1073/pnas.1720588115] [Citation(s) in RCA: 45] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
To evaluate whether germline variants in genes encoding pancreatic secretory enzymes contribute to pancreatic cancer susceptibility, we sequenced the coding regions of CPB1 and other genes encoding pancreatic secretory enzymes and known pancreatitis susceptibility genes (PRSS1, CPA1, CTRC, and SPINK1) in a hospital series of pancreatic cancer cases and controls. Variants in CPB1, CPA1 (encoding carboxypeptidase B1 and A1), and CTRC were evaluated in a second set of cases with familial pancreatic cancer and controls. More deleterious CPB1 variants, defined as having impaired protein secretion and induction of endoplasmic reticulum (ER) stress in transfected HEK 293T cells, were found in the hospital series of pancreatic cancer cases (5/986, 0.5%) than in controls (0/1,045, P = 0.027). Among familial pancreatic cancer cases, ER stress-inducing CPB1 variants were found in 4 of 593 (0.67%) vs. 0 of 967 additional controls (P = 0.020), with a combined prevalence in pancreatic cancer cases of 9/1,579 vs. 0/2,012 controls (P < 0.01). More ER stress-inducing CPA1 variants were also found in the combined set of hospital and familial cases with pancreatic cancer than in controls [7/1,546 vs. 1/2,012; P = 0.025; odds ratio, 9.36 (95% CI, 1.15-76.02)]. Overall, 16 (1%) of 1,579 pancreatic cancer cases had an ER stress-inducing CPA1 or CPB1 variant, compared with 1 of 2,068 controls (P < 0.00001). No other candidate genes had statistically significant differences in variant prevalence between cases and controls. Our study indicates ER stress-inducing variants in CPB1 and CPA1 are associated with pancreatic cancer susceptibility and implicate ER stress in pancreatic acinar cells in pancreatic cancer development.
Collapse
|
134
|
Li D, Tian L, Hakonarson H. Increasing diagnostic yield by RNA-Sequencing in rare disease-bypass hurdles of interpreting intronic or splice-altering variants. ANNALS OF TRANSLATIONAL MEDICINE 2018; 6:126. [PMID: 29955586 DOI: 10.21037/atm.2018.01.14] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Dong Li
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Lifeng Tian
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Hakon Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA.,Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA.,Divisions of Human Genetics and Pulmonary Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| |
Collapse
|
135
|
Yamauchi T, Masuda T, Canver MC, Seiler M, Semba Y, Shboul M, Al-Raqad M, Maeda M, Schoonenberg VAC, Cole MA, Macias-Trevino C, Ishikawa Y, Yao Q, Nakano M, Arai F, Orkin SH, Reversade B, Buonamici S, Pinello L, Akashi K, Bauer DE, Maeda T. Genome-wide CRISPR-Cas9 Screen Identifies Leukemia-Specific Dependence on a Pre-mRNA Metabolic Pathway Regulated by DCPS. Cancer Cell 2018; 33:386-400.e5. [PMID: 29478914 PMCID: PMC5849534 DOI: 10.1016/j.ccell.2018.01.012] [Citation(s) in RCA: 76] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2017] [Revised: 11/23/2017] [Accepted: 01/19/2018] [Indexed: 12/26/2022]
Abstract
To identify novel targets for acute myeloid leukemia (AML) therapy, we performed genome-wide CRISPR-Cas9 screening using AML cell lines, followed by a second screen in vivo. Here, we show that the mRNA decapping enzyme scavenger (DCPS) gene is essential for AML cell survival. The DCPS enzyme interacted with components of pre-mRNA metabolic pathways, including spliceosomes, as revealed by mass spectrometry. RG3039, a DCPS inhibitor originally developed to treat spinal muscular atrophy, exhibited anti-leukemic activity via inducing pre-mRNA mis-splicing. Humans harboring germline biallelic DCPS loss-of-function mutations do not exhibit aberrant hematologic phenotypes, indicating that DCPS is dispensable for human hematopoiesis. Our findings shed light on a pre-mRNA metabolic pathway and identify DCPS as a target for AML therapy.
Collapse
Affiliation(s)
- Takuji Yamauchi
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan; Department of Stem Cell Biology and Medicine, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan
| | - Takeshi Masuda
- Department of Pharmaceutical Microbiology, Faculty of Life Sciences, Kumamoto University, Kumamoto 862-0973, Japan
| | - Matthew C Canver
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | | | - Yuichiro Semba
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan
| | - Mohammad Shboul
- Institute of Medical Biology, A∗STAR, 8A Biomedical Grove, Singapore 138648, Singapore
| | - Mohammed Al-Raqad
- Institute of Medical Biology, A∗STAR, 8A Biomedical Grove, Singapore 138648, Singapore; Al-Balqa Applied University, Faculty of Science, Al-Salt, Salt 19117, Jordan
| | - Manami Maeda
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Vivien A C Schoonenberg
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Mitchel A Cole
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Claudio Macias-Trevino
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Yuichi Ishikawa
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Qiuming Yao
- Department of Pathology & Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Michitaka Nakano
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan
| | - Fumio Arai
- Department of Stem Cell Biology and Medicine, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan
| | - Stuart H Orkin
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Bruno Reversade
- Institute of Medical Biology, A∗STAR, 8A Biomedical Grove, Singapore 138648, Singapore
| | | | - Luca Pinello
- Department of Pathology & Center for Cancer Research, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Koichi Akashi
- Department of Medicine and Biosystemic Science, Kyushu University Graduate School of Medical Sciences, Fukuoka 812-8582, Japan; Center for Cellular and Molecular Medicine, Kyushu University Hospital, Fukuoka 812-8582, Japan
| | - Daniel E Bauer
- Division of Hematology/Oncology, Boston Children's Hospital, Department of Pediatric Oncology, Dana-Farber Cancer Institute, Harvard Stem Cell Institute, Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Takahiro Maeda
- Division of Hematology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA; Center for Cellular and Molecular Medicine, Kyushu University Hospital, Fukuoka 812-8582, Japan.
| |
Collapse
|
136
|
Liu C, Moschou PN. Phenotypic novelty by CRISPR in plants. Dev Biol 2018; 435:170-175. [DOI: 10.1016/j.ydbio.2018.01.015] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 01/21/2018] [Accepted: 01/23/2018] [Indexed: 01/15/2023]
|
137
|
Abstract
Dilated cardiomyopathy (DCM) affects approximately 1 in 250 individuals and is the leading indication for heart transplantation. DCM is often familial, and the most common genetic predisposition is a truncating variation in the giant sarcomeric protein, titin, which occurs in up to 15% of ambulant patients with DCM and 25% of end-stage or familial cases. In this article, we review the evidence for the role of titin truncation in the pathogenesis of DCM and our understanding of the molecular mechanisms and pathophysiological consequences of variation in the gene encoding titin (TTN). Such variation is common in the general population (up to 1% of individuals), and we consider key features that discriminate variants with disease-causing potential from those that are benign. We summarize strategies for clinical interpretation of genetic variants for use in the diagnosis of patients and the evaluation of their relatives. Finally, we consider the contemporary and potential future role for genetic stratification in cardiomyopathy and in the general population, evaluating titin variation as a predictor of outcome and treatment response for precision medicine.
Collapse
Affiliation(s)
- James S Ware
- National Heart and Lung Institute, Imperial College London, Royal Brompton Hospital, Sydney Street, London SW3 6NP, UK.,Medical Research College (MRC) London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK
| | - Stuart A Cook
- National Heart and Lung Institute, Imperial College London, Royal Brompton Hospital, Sydney Street, London SW3 6NP, UK.,Medical Research College (MRC) London Institute of Medical Sciences, Du Cane Road, London W12 0NN, UK.,Duke-National University of Singapore (Duke-NUS) Medical School and National Heart Centre Singapore, 8 College Road, 169857, Singapore
| |
Collapse
|
138
|
Reble E, Dineen A, Barr CL. The contribution of alternative splicing to genetic risk for psychiatric disorders. GENES BRAIN AND BEHAVIOR 2017; 17:e12430. [PMID: 29052934 DOI: 10.1111/gbb.12430] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Revised: 09/25/2017] [Accepted: 10/12/2017] [Indexed: 12/12/2022]
Abstract
A genetic contribution to psychiatric disorders has clearly been established and genome-wide association studies now provide the location of risk genes and genetic variants associated with risk. However, the mechanism by which these genes and variants contribute to psychiatric disorders is mostly undetermined. This is in part because non-synonymous protein coding changes cannot explain the majority of variants associated with complex genetic traits. Based on this, it is predicted that these variants are causing gene expression changes, including changes to alternative splicing. Genetic changes influencing alternative splicing have been identified as risk factors in Mendelian disorders; however, currently there is a paucity of research on the role of alternative splicing in complex traits. This stems partly from the difficulty of predicting the role of genetic variation in splicing. Alterations to canonical splice site sequences, nucleotides adjacent to splice junctions, and exonic and intronic splicing regulatory sequences can influence splice site choice. Recent studies have identified global changes in alternatively spliced transcripts in brain tissues, some of which correlate with altered levels of splicing trans factors. Disease-associated variants have also been found to affect cis-acting splicing regulatory sequences and alter the ratio of alternatively spliced transcripts. These findings are reviewed here, as well as the current datasets and resources available to study alternative splicing in psychiatric disorders. Identifying and understanding risk variants that cause alternative splicing is critical to understanding the mechanisms of risk as well as to pave the way for new therapeutic options.
Collapse
Affiliation(s)
- E Reble
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - A Dineen
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - C L Barr
- Genetics and Development Division, Krembil Research Institute, University Health Network, Toronto, Ontario, Canada.,Program in Neurosciences and Mental Health, The Hospital for Sick Children, Toronto, Ontario, Canada.,Institute of Medical Sciences, University of Toronto, Toronto, Ontario, Canada.,Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada.,Department of Physiology, University of Toronto, Toronto, Ontario, Canada
| |
Collapse
|
139
|
Stranger BE, Brigham LE, Hasz R, Hunter M, Johns C, Johnson M, Kopen G, Leinweber WF, Lonsdale JT, McDonald A, Mestichelli B, Myer K, Roe B, Salvatore M, Shad S, Thomas JA, Walters G, Washington M, Wheeler J, Bridge J, Foster BA, Gillard BM, Karasik E, Kumar R, Miklos M, Moser MT, Jewell SD, Montroy RG, Rohrer DC, Valley D, Davis DA, Mash DC, Gould SE, Guan P, Koester S, Little AR, Martin C, Moore HM, Rao A, Struewing JP, Volpi S, Hansen KD, Hickey PF, Rizzardi LF, Hou L, Liu Y, Molinie B, Park Y, Rinaldi N, Wang LB, Van Wittenberghe N, Claussnitzer M, Gelfand ET, Li Q, Linder S, Smith KS, Tsang EK, Demanelis K, Doherty JA, Jasmine F, Kibriya MG, Jiang L, Lin S, Wang M, Jian R, Li X, Chan J, Bates D, Diegel M, Halow J, Haugen E, Johnson A, Kaul R, Lee K, Maurano MT, Nelson J, Neri FJ, Sandstrom R, Fernando MS, Linke C, Oliva M, Skol A, Wu F, Akey JM, Feinberg AP, Li JB, Pierce BL, Stamatoyannopoulos JA, Tang H, Ardlie KG, Kellis M, Snyder MP, Montgomery SB. Enhancing GTEx by bridging the gaps between genotype, gene expression, and disease. Nat Genet 2017; 49:1664-1670. [PMID: 29019975 PMCID: PMC6636856 DOI: 10.1038/ng.3969] [Citation(s) in RCA: 133] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Genetic variants have been associated with myriad molecular phenotypes that provide new insight into the range of mechanisms underlying genetic traits and diseases. Identifying any particular genetic variant's cascade of effects, from molecule to individual, requires assaying multiple layers of molecular complexity. We introduce the Enhancing GTEx (eGTEx) project that extends the GTEx project to combine gene expression with additional intermediate molecular measurements on the same tissues to provide a resource for studying how genetic differences cascade through molecular phenotypes to impact human health.
Collapse
Affiliation(s)
- Barbara E. Stranger
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
- Center for Data Intensive Science, The University of Chicago, Chicago, IL 60637, USA
| | - Lori E. Brigham
- Washington Regional Transplant Community, Annandale, VA 22003, USA
| | - Richard Hasz
- Gift of Life Donor Program, Philadelphia, PA 19103, USA
| | | | | | | | - Gene Kopen
- National Disease Research Interchange, Philadelphia, PA 19103, USA
| | | | - John T. Lonsdale
- National Disease Research Interchange, Philadelphia, PA 19103, USA
| | - Alisa McDonald
- National Disease Research Interchange, Philadelphia, PA 19103, USA
| | | | | | | | | | - Saboor Shad
- National Disease Research Interchange, Philadelphia, PA 19103, USA
| | | | | | | | - Joseph Wheeler
- Center for Organ Recovery and Education, Pittsburgh, PA 15238, USA
| | | | - Barbara A. Foster
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Bryan M. Gillard
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Ellen Karasik
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Rachna Kumar
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Mark Miklos
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | - Michael T. Moser
- Pharmacology and Therapeutics, Roswell Park Cancer Institute, Buffalo, NY 14263, USA
| | | | | | | | - Dana Valley
- Van Andel Research Institute, Grand Rapids, MI 49503, USA
| | - David A. Davis
- Brain Endowment Bank, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Deborah C. Mash
- Brain Endowment Bank, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Sarah E. Gould
- Division of Genomic Medicine, National Human Genome Research Institute, Rockville, MD 20852, USA
| | - Ping Guan
- Biorepositories and Biospecimen Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Susan Koester
- Division of Neuroscience and Basic Behavioral Science, National Institute of Mental Health, NIH, Bethesda, MD 20892, USA
| | - A. Roger Little
- National Institute on Drug Abuse, NIH, Bethesda, MD 20892, USA
| | - Casey Martin
- Division of Genomic Medicine, National Human Genome Research Institute, Rockville, MD 20852, USA
| | - Helen M. Moore
- Biorepositories and Biospecimen Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Abhi Rao
- Biorepositories and Biospecimen Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, MD 20892, USA
| | - Jeffery P. Struewing
- Division of Genomic Medicine, National Human Genome Research Institute, Rockville, MD 20852, USA
| | - Simona Volpi
- Division of Genomic Medicine, National Human Genome Research Institute, Rockville, MD 20852, USA
| | - Kasper D. Hansen
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins School of Medicine, Baltimore, MD 21205, USA
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Peter F. Hickey
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Lindsay F. Rizzardi
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Lei Hou
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Yaping Liu
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Benoit Molinie
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Yongjin Park
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Nicola Rinaldi
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Li B. Wang
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Nicholas Van Wittenberghe
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Melina Claussnitzer
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
- Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
- Technical University Munich, 8350 Freising, Germany
| | - Ellen T. Gelfand
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Qin Li
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Sandra Linder
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Kevin S. Smith
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| | - Emily K. Tsang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
- Biomedical Informatics Program, Stanford University, Stanford, CA 94305, USA
| | - Kathryn Demanelis
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Jennifer A. Doherty
- Department of Epidemiology, Geisel School of Medicine at Dartmouth, Lebanon, NH 03756, USA
| | - Farzana Jasmine
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Muhammad G. Kibriya
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | - Lihua Jiang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Shin Lin
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Meng Wang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Ruiqi Jian
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Xiao Li
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Joanne Chan
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Daniel Bates
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Morgan Diegel
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Jessica Halow
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Eric Haugen
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Audra Johnson
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Rajinder Kaul
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Kristen Lee
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Matthew T. Maurano
- Institute for Systems Genetics, New York University Langone Medical Center, New York, NY 10016, USA
| | - Jemma Nelson
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | - Fidencio J. Neri
- Altius Institute for Biomedical Sciences, Seattle, WA 98121, USA
| | | | - Marian S. Fernando
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Caroline Linke
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Meritxell Oliva
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Andrew Skol
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
- Center for Data Intensive Science, The University of Chicago, Chicago, IL 60637, USA
| | - Fan Wu
- Section of Genetic Medicine, Department of Medicine, The University of Chicago, Chicago, IL 60637, USA
- Institute for Genomics and Systems Biology, The University of Chicago, Chicago, IL 60637, USA
| | - Joshua M. Akey
- Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
| | - Andrew P. Feinberg
- Center for Epigenetics, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Department of Mental Health, Johns Hopkins University School of Public Health, Baltimore, MD 21205, USA
| | - Jin Billy Li
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Brandon L. Pierce
- Department of Public Health Sciences, The University of Chicago, Chicago, IL 60637, USA
| | | | - Hua Tang
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Kristin G. Ardlie
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Manolis Kellis
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, MA 02142, USA
| | - Michael P. Snyder
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Stephen B. Montgomery
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
- Department of Pathology, Stanford University, Stanford, CA 94305, USA
| |
Collapse
|
140
|
Affiliation(s)
- Gianfranco Sinagra
- From the Cardiovascular Department, Cardiomyopathy Centre, University of Trieste, Italy
| | - Matteo Dal Ferro
- From the Cardiovascular Department, Cardiomyopathy Centre, University of Trieste, Italy
| | - Marco Merlo
- From the Cardiovascular Department, Cardiomyopathy Centre, University of Trieste, Italy
| |
Collapse
|
141
|
Li M, Zauhar RJ, Grazal C, Curcio CA, DeAngelis MM, Stambolian D. RNA expression in human retina. Hum Mol Genet 2017; 26:R68-R74. [PMID: 28854577 DOI: 10.1093/hmg/ddx219] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Accepted: 06/05/2017] [Indexed: 01/07/2023] Open
Abstract
Recent Genome-wide Association Studies (GWASs) for eye diseases/traits have delivered a number of novel findings across a diverse range of diseases, including age-related macular degeneration (AMD), glaucoma and refractive error. However, despite this astonishing rate of success, the major challenge still remains to not only confirm that the genes implicated in these studies are truly the genes conferring protection from or risk of disease but also to define the functional roles these genes play in disease. Ongoing evidence is accumulating that the single nucleotide polymorphisms (SNPs) used in GWAS and fine mapping studies have causal effects through their influence on gene expression rather than affecting protein function. The biological interpretation of SNP regulatory effects for a tissue requires knowledge of the transcriptome for that tissue. We summarize the reasons to characterize the complete retinal transcriptome as well as the evidence to include an assessment of differences in regional retinal expression.
Collapse
Affiliation(s)
- Mingyao Li
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Randy J Zauhar
- Department of Chemistry and Biochemistry, The University of the Sciences in Philadelphia, Philadelphia, PA 19104, USA
| | - Clare Grazal
- Department of Ophthalmology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| | - Christine A Curcio
- Department of Ophthalmology, University of Alabama at Birmingham School of Medicine, Birmingham, AL 35294, USA
| | - Margaret M DeAngelis
- Department of Ophthalmology, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Dwight Stambolian
- Department of Ophthalmology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA
| |
Collapse
|
142
|
Xiong Y, Soumillon M, Wu J, Hansen J, Hu B, van Hasselt JGC, Jayaraman G, Lim R, Bouhaddou M, Ornelas L, Bochicchio J, Lenaeus L, Stocksdale J, Shim J, Gomez E, Sareen D, Svendsen C, Thompson LM, Mahajan M, Iyengar R, Sobie EA, Azeloglu EU, Birtwistle MR. A Comparison of mRNA Sequencing with Random Primed and 3'-Directed Libraries. Sci Rep 2017; 7:14626. [PMID: 29116112 PMCID: PMC5676863 DOI: 10.1038/s41598-017-14892-x] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 10/18/2017] [Indexed: 11/26/2022] Open
Abstract
Creating a cDNA library for deep mRNA sequencing (mRNAseq) is generally done by random priming, creating multiple sequencing fragments along each transcript. A 3'-end-focused library approach cannot detect differential splicing, but has potentially higher throughput at a lower cost, along with the ability to improve quantification by using transcript molecule counting with unique molecular identifiers (UMI) that correct PCR bias. Here, we compare an implementation of such a 3'-digital gene expression (3'-DGE) approach with "conventional" random primed mRNAseq. Given our particular datasets on cultured human cardiomyocyte cell lines, we find that, while conventional mRNAseq detects ~15% more genes and needs ~500,000 fewer reads per sample for equivalent statistical power, the resulting differentially expressed genes, biological conclusions, and gene signatures are highly concordant between two techniques. We also find good quantitative agreement at the level of individual genes between two techniques for both read counts and fold changes between given conditions. We conclude that, for high-throughput applications, the potential cost savings associated with 3'-DGE approach are likely a reasonable tradeoff for modest reduction in sensitivity and inability to observe alternative splicing, and should enable many larger scale studies focusing on not only differential expression analysis, but also quantitative transcriptome profiling.
Collapse
Affiliation(s)
- Yuguang Xiong
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Magali Soumillon
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Berkeley Lights, Inc. 5858 Horton St., Emeryville, CA, 94608, USA
| | - Jie Wu
- Department of Biological Chemistry, University of California, Irvine, CA, USA
- UCI MIND, University of California, Irvine, CA, USA
| | - Jens Hansen
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Bin Hu
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Johan G C van Hasselt
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Gomathi Jayaraman
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ryan Lim
- Department of Biological Chemistry, University of California, Irvine, CA, USA
- UCI MIND, University of California, Irvine, CA, USA
| | - Mehdi Bouhaddou
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Loren Ornelas
- Board of Governors-Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- iPSC Core, The David and Janet Polak Foundation Stem Cell Core Laboratory, Los Angeles, CA, USA
| | | | - Lindsay Lenaeus
- Board of Governors-Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- iPSC Core, The David and Janet Polak Foundation Stem Cell Core Laboratory, Los Angeles, CA, USA
| | | | - Jaehee Shim
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Emilda Gomez
- Board of Governors-Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- iPSC Core, The David and Janet Polak Foundation Stem Cell Core Laboratory, Los Angeles, CA, USA
| | - Dhruv Sareen
- Board of Governors-Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- iPSC Core, The David and Janet Polak Foundation Stem Cell Core Laboratory, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Clive Svendsen
- Board of Governors-Regenerative Medicine Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
- iPSC Core, The David and Janet Polak Foundation Stem Cell Core Laboratory, Los Angeles, CA, USA
- Department of Biomedical Sciences, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Leslie M Thompson
- Department of Biological Chemistry, University of California, Irvine, CA, USA
- UCI MIND, University of California, Irvine, CA, USA
- Department of Psychiatry and Human Behavior, Neurobiology and Behavior, University of California, Irvine, CA, USA
| | - Milind Mahajan
- Department of Genetics, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ravi Iyengar
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Eric A Sobie
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Evren U Azeloglu
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Marc R Birtwistle
- Department of Pharmacological Sciences and DToxS LINCS Center, Icahn School of Medicine at Mount Sinai, New York, NY, USA.
- Department of Chemical and Biomolecular Engineering, Clemson University, Clemson, SC, USA.
| |
Collapse
|
143
|
Rogawski DS, Vitanza NA, Gauthier AC, Ramaswamy V, Koschmann C. Integrating RNA sequencing into neuro-oncology practice. Transl Res 2017; 189:93-104. [PMID: 28746860 PMCID: PMC5659901 DOI: 10.1016/j.trsl.2017.06.013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 05/27/2017] [Accepted: 06/30/2017] [Indexed: 12/22/2022]
Abstract
Malignant tumors of the central nervous system (CNS) cause substantial morbidity and mortality, yet efforts to optimize chemo- and radiotherapy have largely failed to improve dismal prognoses. Over the past decade, RNA sequencing (RNA-seq) has emerged as a powerful tool to comprehensively characterize the transcriptome of CNS tumor cells in one high-throughput step, leading to improved understanding of CNS tumor biology and suggesting new routes for targeted therapies. RNA-seq has been instrumental in improving the diagnostic classification of brain tumors, characterizing oncogenic fusion genes, and shedding light on intratumor heterogeneity. Currently, RNA-seq is beginning to be incorporated into regular neuro-oncology practice in the form of precision neuro-oncology programs, which use information from tumor sequencing to guide implementation of personalized targeted therapies. These programs show great promise in improving patient outcomes for tumors where single agent trials have been ineffective. As RNA-seq is a relatively new technique, many further applications yielding new advances in CNS tumor research and management are expected in the coming years.
Collapse
Affiliation(s)
- David S Rogawski
- Department of Pediatrics, University of Michigan School of Medicine, Ann Arbor, Mich
| | | | | | - Vijay Ramaswamy
- Division of Haematology/Oncology, Department of Pediatrics, Hospital for Sick Children, Toronto, ON, Canada
| | - Carl Koschmann
- Department of Pediatrics, University of Michigan School of Medicine, Ann Arbor, Mich.
| |
Collapse
|
144
|
Mohammadi P, Castel SE, Brown AA, Lappalainen T. Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change. Genome Res 2017; 27:1872-1884. [PMID: 29021289 PMCID: PMC5668944 DOI: 10.1101/gr.216747.116] [Citation(s) in RCA: 83] [Impact Index Per Article: 11.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2016] [Accepted: 06/05/2017] [Indexed: 12/11/2022]
Abstract
Mapping cis-acting expression quantitative trait loci (cis-eQTL) has become a popular approach for characterizing proximal genetic regulatory variants. In this paper, we describe and characterize log allelic fold change (aFC), the magnitude of expression change associated with a given genetic variant, as a biologically interpretable unit for quantifying the effect size of cis-eQTLs and a mathematically convenient approach for systematic modeling of cis-regulation. This measure is mathematically independent from expression level and allele frequency, additive, applicable to multiallelic variants, and generalizable to multiple independent variants. We provide efficient tools and guidelines for estimating aFC from both eQTL and allelic expression data sets and apply it to Genotype Tissue Expression (GTEx) data. We show that aFC estimates independently derived from eQTL and allelic expression data are highly consistent, and identify technical and biological correlates of eQTL effect size. We generalize aFC to analyze genes with two eQTLs in GTEx and show that in nearly all cases the two eQTLs act independently in regulating gene expression. In summary, aFC is a solid measure of cis-regulatory effect size that allows quantitative interpretation of cellular regulatory events from population data, and it is a valuable approach for investigating novel aspects of eQTL data sets.
Collapse
Affiliation(s)
- Pejman Mohammadi
- New York Genome Center, New York, New York 10013, USA
- Department of Systems Biology, Columbia University, New York, New York 10032, USA
| | - Stephane E Castel
- New York Genome Center, New York, New York 10013, USA
- Department of Systems Biology, Columbia University, New York, New York 10032, USA
| | - Andrew A Brown
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, 1211, Switzerland
- Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, 1211, Switzerland
- Swiss Institute of Bioinformatics, Geneva, 1211, Switzerland
| | - Tuuli Lappalainen
- New York Genome Center, New York, New York 10013, USA
- Department of Systems Biology, Columbia University, New York, New York 10032, USA
| |
Collapse
|
145
|
Li AH, Hanchard NA, Furthner D, Fernbach S, Azamian M, Nicosia A, Rosenfeld J, Muzny D, D'Alessandro LCA, Morris S, Jhangiani S, Parekh DR, Franklin WJ, Lewin M, Towbin JA, Penny DJ, Fraser CD, Martin JF, Eng C, Lupski JR, Gibbs RA, Boerwinkle E, Belmont JW. Whole exome sequencing in 342 congenital cardiac left sided lesion cases reveals extensive genetic heterogeneity and complex inheritance patterns. Genome Med 2017; 9:95. [PMID: 29089047 PMCID: PMC5664429 DOI: 10.1186/s13073-017-0482-5] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2017] [Accepted: 10/12/2017] [Indexed: 01/30/2023] Open
Abstract
BACKGROUND Left-sided lesions (LSLs) account for an important fraction of severe congenital cardiovascular malformations (CVMs). The genetic contributions to LSLs are complex, and the mutations that cause these malformations span several diverse biological signaling pathways: TGFB, NOTCH, SHH, and more. Here, we use whole exome sequence data generated in 342 LSL cases to identify likely damaging variants in putative candidate CVM genes. METHODS Using a series of bioinformatics filters, we focused on genes harboring population-rare, putative loss-of-function (LOF), and predicted damaging variants in 1760 CVM candidate genes constructed a priori from the literature and model organism databases. Gene variants that were not observed in a comparably sequenced control dataset of 5492 samples without severe CVM were then subjected to targeted validation in cases and parents. Whole exome sequencing data from 4593 individuals referred for clinical sequencing were used to bolster evidence for the role of candidate genes in CVMs and LSLs. RESULTS Our analyses revealed 28 candidate variants in 27 genes, including 17 genes not previously associated with a human CVM disorder, and revealed diverse patterns of inheritance among LOF carriers, including 9 confirmed de novo variants in both novel and newly described human CVM candidate genes (ACVR1, JARID2, NR2F2, PLRG1, SMURF1) as well as established syndromic CVM genes (KMT2D, NF1, TBX20, ZEB2). We also identified two genes (DNAH5, OFD1) with evidence of recessive and hemizygous inheritance patterns, respectively. Within our clinical cohort, we also observed heterozygous LOF variants in JARID2 and SMAD1 in individuals with cardiac phenotypes, and collectively, carriers of LOF variants in our candidate genes had a four times higher odds of having CVM (odds ratio = 4.0, 95% confidence interval 2.5-6.5). CONCLUSIONS Our analytical strategy highlights the utility of bioinformatic resources, including human disease records and model organism phenotyping, in novel gene discovery for rare human disease. The results underscore the extensive genetic heterogeneity underlying non-syndromic LSLs, and posit potential novel candidate genes and complex modes of inheritance in this important group of birth defects.
Collapse
Affiliation(s)
- Alexander H Li
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
| | - Neil A Hanchard
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Dieter Furthner
- Department of Paediatrics, Children's Hospital, Krankenhausstr. 26-30, 4020, Linz, Austria
| | - Susan Fernbach
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Mahshid Azamian
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Annarita Nicosia
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Jill Rosenfeld
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Shaine Morris
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Shalini Jhangiani
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Dhaval R Parekh
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Wayne J Franklin
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Mark Lewin
- Division of Cardiology, Seattle Children's Hospital, Seattle, WA, USA
| | - Jeffrey A Towbin
- Pediatric Cardiology, University of Tennessee Health Science Center, Memphis, TN, USA
| | - Daniel J Penny
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Charles D Fraser
- Department of Surgery, Baylor College of Medicine, Houston, TX, USA
| | - James F Martin
- Department of Molecular Physiology and Biophysics, Baylor College of Medicine, and the Texas Heart Institute, Houston, TX, USA
| | - Christine Eng
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - James R Lupski
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA.,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.,Texas Children's Hospital, Houston, TX, USA
| | - Richard A Gibbs
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA.,Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - John W Belmont
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA. .,Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA. .,, 5200 Illumina Way, San Diego, CA, USA.
| |
Collapse
|
146
|
|
147
|
Sun Y, Bao Y, Han W, Song F, Shen X, Zhao J, Zuo J, Saffen D, Chen W, Wang Z, You X, Wang Y. Autoregulation of RBM10 and cross-regulation of RBM10/RBM5 via alternative splicing-coupled nonsense-mediated decay. Nucleic Acids Res 2017; 45:8524-8540. [PMID: 28586478 PMCID: PMC5737846 DOI: 10.1093/nar/gkx508] [Citation(s) in RCA: 38] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2016] [Accepted: 05/27/2017] [Indexed: 12/15/2022] Open
Abstract
Mutations in the spliceosomal RNA binding protein RBM10 cause TARP syndrome and are frequently observed in lung adenocarcinoma (LUAD). We have previously shown that RBM10 enhances exon skipping of its target genes, including its paralog RBM5. Here, we report that RBM10 negatively regulates its own mRNA and protein expression and that of RBM5 by promoting alternative splicing-coupled nonsense-mediated mRNA decay (AS-NMD). Through computational analysis and experimental validation, we identified RBM10-promoted skipping of exon 6 or 12 in RBM10 and exon 6 or 16 in RBM5 as the underlying AS-NMD events. Importantly, we showed that LUAD-associated mutations affecting splice sites of RBM10 exons 6 or 12 abolished exon inclusion and correlated with reduced expression of RBM10 RNA. Together, our investigations have revealed novel molecular mechanisms underlying RBM10 autoregulation and cross-regulation of RBM5, thereby providing insights concerning the functions of RBM10 under various physiological and pathological conditions. Our combined computational and experimental approach should be useful for elucidating the role of AS-NMD in auto- and cross-regulation by other splicing regulators.
Collapse
Affiliation(s)
- Yue Sun
- School of Life Sciences, Fudan University, Shanghai 200438, China.,Institutes of Brain Science, Fudan University, Shanghai 200032, China.,Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Yufang Bao
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Wenjian Han
- Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Science, Shanghai 200031, China
| | - Fan Song
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Xianfeng Shen
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Jiawei Zhao
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - Ji Zuo
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| | - David Saffen
- Institutes of Brain Science, Fudan University, Shanghai 200032, China.,Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China.,State Key Laboratory for Medical Neurobiology, Fudan University, Shanghai 200032, China
| | - Wei Chen
- Department of Biology, Southern University of Science and Technology, Shenzhen 518055, China
| | - Zefeng Wang
- Key Lab of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Chinese Academy of Science, Shanghai 200031, China
| | - Xintian You
- Zuse Institute Berlin, Takustrasse 7, Berlin 14195, Germany
| | - Yongbo Wang
- Department of Cellular and Genetic Medicine, School of Basic Medical Sciences, Fudan University, Shanghai 200032, China
| |
Collapse
|
148
|
Battle A, Brown CD, Engelhardt BE, Montgomery SB. Genetic effects on gene expression across human tissues. Nature 2017; 550:204-213. [PMID: 29022597 PMCID: PMC5776756 DOI: 10.1038/nature24277] [Citation(s) in RCA: 2565] [Impact Index Per Article: 366.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2016] [Accepted: 09/15/2017] [Indexed: 12/12/2022]
Abstract
Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease.
Collapse
Affiliation(s)
- Alexis Battle
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, USA
| | - Christopher D Brown
- Department of Genetics and Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA
| | - Barbara E Engelhardt
- Department of Computer Science and Center for Statistics and Machine Learning, Princeton University, Princeton, New Jersey 08540, USA
| | - Stephen B Montgomery
- Department of Genetics, Stanford University, Stanford, California 94305, USA
- Department of Pathology, Stanford University, Stanford, California 94305, USA
| |
Collapse
|
149
|
Tukiainen T, Villani AC, Yen A, Rivas MA, Marshall JL, Satija R, Aguirre M, Gauthier L, Fleharty M, Kirby A, Cummings BB, Castel SE, Karczewski KJ, Aguet F, Byrnes A, Lappalainen T, Regev A, Ardlie KG, Hacohen N, MacArthur DG. Landscape of X chromosome inactivation across human tissues. Nature 2017; 550:244-248. [PMID: 29022598 PMCID: PMC5685192 DOI: 10.1038/nature24265] [Citation(s) in RCA: 646] [Impact Index Per Article: 92.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2016] [Accepted: 09/28/2017] [Indexed: 12/16/2022]
Abstract
X chromosome inactivation (XCI) silences transcription from one of the two X chromosomes in female mammalian cells to balance expression dosage between XX females and XY males. XCI is, however, incomplete in humans: up to one-third of X-chromosomal genes are expressed from both the active and inactive X chromosomes (Xa and Xi, respectively) in female cells, with the degree of 'escape' from inactivation varying between genes and individuals. The extent to which XCI is shared between cells and tissues remains poorly characterized, as does the degree to which incomplete XCI manifests as detectable sex differences in gene expression and phenotypic traits. Here we describe a systematic survey of XCI, integrating over 5,500 transcriptomes from 449 individuals spanning 29 tissues from GTEx (v6p release) and 940 single-cell transcriptomes, combined with genomic sequence data. We show that XCI at 683 X-chromosomal genes is generally uniform across human tissues, but identify examples of heterogeneity between tissues, individuals and cells. We show that incomplete XCI affects at least 23% of X-chromosomal genes, identify seven genes that escape XCI with support from multiple lines of evidence and demonstrate that escape from XCI results in sex biases in gene expression, establishing incomplete XCI as a mechanism that is likely to introduce phenotypic diversity. Overall, this updated catalogue of XCI across human tissues helps to increase our understanding of the extent and impact of the incompleteness in the maintenance of XCI.
Collapse
Affiliation(s)
- Taru Tukiainen
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Alexandra-Chloé Villani
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Angela Yen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - Manuel A. Rivas
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biomedical Data Science, Stanford University, Stanford, CA 94305, USA
| | - Jamie L. Marshall
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Rahul Satija
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- New York Genome Center, New York, NY 10013, USA
- Center for Genomics and Systems Biology, Department of Biology, New York University, New York, NY 10003, USA
| | - Matt Aguirre
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Laura Gauthier
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Mark Fleharty
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Andrew Kirby
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Beryl B. Cummings
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Stephane E. Castel
- New York Genome Center, New York, NY 10013, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Konrad J. Karczewski
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - François Aguet
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Andrea Byrnes
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Tuuli Lappalainen
- New York Genome Center, New York, NY 10013, USA
- Department of Systems Biology, Columbia University, New York, NY 10032, USA
| | - Aviv Regev
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | | | - Nir Hacohen
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
- Center for Immunology and Inflammatory Diseases, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Daniel G. MacArthur
- Analytic and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| |
Collapse
|
150
|
Wang H, Bender A, Wang P, Karakose E, Inabnet WB, Libutti SK, Arnold A, Lambertini L, Stang M, Chen H, Kasai Y, Mahajan M, Kinoshita Y, Fernandez-Ranvier G, Becker TC, Takane KK, Walker LA, Saul S, Chen R, Scott DK, Ferrer J, Antipin Y, Donovan M, Uzilov AV, Reva B, Schadt EE, Losic B, Argmann C, Stewart AF. Insights into beta cell regeneration for diabetes via integration of molecular landscapes in human insulinomas. Nat Commun 2017; 8:767. [PMID: 28974674 PMCID: PMC5626682 DOI: 10.1038/s41467-017-00992-9] [Citation(s) in RCA: 63] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2017] [Accepted: 08/10/2017] [Indexed: 12/19/2022] Open
Abstract
Although diabetes results in part from a deficiency of normal pancreatic beta cells, inducing human beta cells to regenerate is difficult. Reasoning that insulinomas hold the “genomic recipe” for beta cell expansion, we surveyed 38 human insulinomas to obtain insights into therapeutic pathways for beta cell regeneration. An integrative analysis of whole-exome and RNA-sequencing data was employed to extensively characterize the genomic and molecular landscape of insulinomas relative to normal beta cells. Here, we show at the pathway level that the majority of the insulinomas display mutations, copy number variants and/or dysregulation of epigenetic modifying genes, most prominently in the polycomb and trithorax families. Importantly, these processes are coupled to co-expression network modules associated with cell proliferation, revealing candidates for inducing beta cell regeneration. Validation of key computational predictions supports the concept that understanding the molecular complexity of insulinoma may be a valuable approach to diabetes drug discovery. Diabetes results in part from a deficiency of functional pancreatic beta cells. Here, the authors study the genomic and epigenetic landscapes of human insulinomas to gain insight into possible pathways for therapeutic beta cell regeneration, highlighting epigenetic genes and pathways.
Collapse
Affiliation(s)
- Huan Wang
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,The Graduate School, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT, 06902, USA
| | - Aaron Bender
- The Graduate School, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Peng Wang
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Esra Karakose
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - William B Inabnet
- The Department of Surgery, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Steven K Libutti
- The Cancer Institute of New Jersey, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Andrew Arnold
- Center for Molecular Medicine, University of Connecticut School of Medicine, Farmington, CT, 06030, USA
| | - Luca Lambertini
- The Departments of Environmental Medicine and Public Health and Obstetrics, Gynecology, and Reproductive Sciences, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Micheal Stang
- The Department of Surgery, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Herbert Chen
- The Department of Surgery, University of Alabama at Birmingham, Birmingham, AL, 35233, USA
| | - Yumi Kasai
- The New York Genome Center, New York, NY, 10013, USA
| | - Milind Mahajan
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Yayoi Kinoshita
- The Department of Pathology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | | | - Thomas C Becker
- The Sarah W. Stedman Center for Nutrition and Metabolism, Duke University School of Medicine, Durham, NC, 27710, USA
| | - Karen K Takane
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Laura A Walker
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Shira Saul
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Rong Chen
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT, 06902, USA
| | - Donald K Scott
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Jorge Ferrer
- The Department of Genetics in Medicine, Imperial College, London, W12 0NN, UK
| | - Yevgeniy Antipin
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT, 06902, USA
| | - Michael Donovan
- The Department of Pathology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Andrew V Uzilov
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT, 06902, USA
| | - Boris Reva
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Eric E Schadt
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,Sema4, a Mount Sinai venture, Stamford, CT, 06902, USA
| | - Bojan Losic
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Carmen Argmann
- The Department of Genetics and Genomic Sciences and The Icahn Institute for Genomics and Multiscale Biology, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Andrew F Stewart
- The Diabetes Obesity and Metabolism Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| |
Collapse
|