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Gong T, Jaratlerdsiri W, Jiang J, Willet C, Chew T, Patrick SM, Lyons RJ, Haynes AM, Pasqualim G, Brum IS, Stricker PD, Mutambirwa SBA, Sadsad R, Papenfuss AT, Bornman RMS, Chan EKF, Hayes VM. Genome-wide interrogation of structural variation reveals novel African-specific prostate cancer oncogenic drivers. Genome Med 2022; 14:100. [PMID: 36045381 PMCID: PMC9434886 DOI: 10.1186/s13073-022-01096-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Accepted: 07/28/2022] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND African ancestry is a significant risk factor for advanced prostate cancer (PCa). Mortality rates in sub-Saharan Africa are 2.5-fold greater than global averages. However, the region has largely been excluded from the benefits of whole genome interrogation studies. Additionally, while structural variation (SV) is highly prevalent, PCa genomic studies are still biased towards small variant interrogation. METHODS Using whole genome sequencing and best practice workflows, we performed a comprehensive analysis of SVs for 180 (predominantly Gleason score ≥ 8) prostate tumours derived from 115 African, 61 European and four ancestrally admixed patients. We investigated the landscape and relationship of somatic SVs in driving ethnic disparity (African versus European), with a focus on African men from southern Africa. RESULTS Duplication events showed the greatest ethnic disparity, with a 1.6- (relative frequency) to 2.5-fold (count) increase in African-derived tumours. Furthermore, we found duplication events to be associated with CDK12 inactivation and MYC copy number gain, and deletion events associated with SPOP mutation. Overall, African-derived tumours were 2-fold more likely to present with a hyper-SV subtype. In addition to hyper-duplication and deletion subtypes, we describe a new hyper-translocation subtype. While we confirm a lower TMPRSS2-ERG fusion-positive rate in tumours from African cases (10% versus 33%), novel African-specific PCa ETS family member and TMPRSS2 fusion partners were identified, including LINC01525, FBXO7, GTF3C2, NTNG1 and YPEL5. Notably, we found 74 somatic SV hotspots impacting 18 new candidate driver genes, with CADM2, LSAMP, PTPRD, PDE4D and PACRG having therapeutic implications for African patients. CONCLUSIONS In this first African-inclusive SV study for high-risk PCa, we demonstrate the power of SV interrogation for the identification of novel subtypes, oncogenic drivers and therapeutic targets. Identifying a novel spectrum of SVs in tumours derived from African patients provides a mechanism that may contribute, at least in part, to the observed ethnic disparity in advanced PCa presentation in men of African ancestry.
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Affiliation(s)
- Tingting Gong
- grid.1013.30000 0004 1936 834XAncestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW Australia ,grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia ,grid.8547.e0000 0001 0125 2443Human Phenome Institute, Fudan University, Shanghai, China
| | - Weerachai Jaratlerdsiri
- grid.1013.30000 0004 1936 834XAncestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW Australia ,grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia
| | - Jue Jiang
- grid.1013.30000 0004 1936 834XAncestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW Australia ,grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia
| | - Cali Willet
- grid.1013.30000 0004 1936 834XSydney Informatics Hub, University of Sydney, Sydney, NSW Australia
| | - Tracy Chew
- grid.1013.30000 0004 1936 834XSydney Informatics Hub, University of Sydney, Sydney, NSW Australia
| | - Sean M. Patrick
- grid.49697.350000 0001 2107 2298School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Ruth J. Lyons
- grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia
| | - Anne-Maree Haynes
- grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia
| | - Gabriela Pasqualim
- grid.8532.c0000 0001 2200 7498Endocrine and Tumor Molecular Biology Laboratory, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil ,grid.411598.00000 0000 8540 6536Laboratory of Genetics, Instituto de Ciências Biológicas, Universidade Federal do Rio Grande, Rio Grande, Brazil
| | - Ilma Simoni Brum
- grid.8532.c0000 0001 2200 7498Endocrine and Tumor Molecular Biology Laboratory, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Phillip D. Stricker
- grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia ,grid.437825.f0000 0000 9119 2677Department of Urology, St. Vincent’s Hospital, Darlinghurst, NSW Australia
| | - Shingai B. A. Mutambirwa
- grid.461049.eDepartment of Urology, Sefako Makgatho Health Science University, Dr George Mukhari Academic Hospital, Medunsa, Ga-Rankuwa, South Africa
| | - Rosemarie Sadsad
- grid.1013.30000 0004 1936 834XSydney Informatics Hub, University of Sydney, Sydney, NSW Australia
| | - Anthony T. Papenfuss
- grid.1042.70000 0004 0432 4889Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria Australia ,grid.1008.90000 0001 2179 088XDepartment of Medical Biology, University of Melbourne, Melbourne, Victoria Australia
| | - Riana M. S. Bornman
- grid.49697.350000 0001 2107 2298School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Eva K. F. Chan
- grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia ,grid.416088.30000 0001 0753 1056NSW Health Pathology, Sydney, Australia
| | - Vanessa M. Hayes
- grid.1013.30000 0004 1936 834XAncestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW Australia ,grid.415306.50000 0000 9983 6924Genomics and Epigenetics Theme, Garvan Institute of Medical Research, Darlinghurst, NSW Australia ,grid.49697.350000 0001 2107 2298School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa ,grid.411732.20000 0001 2105 2799Faculty of Health Sciences, University of Limpopo, Turfloop Campus, Mankweng, South Africa
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2
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Field MA, Yadav S, Dudchenko O, Esvaran M, Rosen BD, Skvortsova K, Edwards RJ, Keilwagen J, Cochran BJ, Manandhar B, Bustamante S, Rasmussen JA, Melvin RG, Chernoff B, Omer A, Colaric Z, Chan EKF, Minoche AE, Smith TPL, Gilbert MTP, Bogdanovic O, Zammit RA, Thomas T, Aiden EL, Ballard JWO. The Australian dingo is an early offshoot of modern breed dogs. Sci Adv 2022; 8:eabm5944. [PMID: 35452284 PMCID: PMC9032958 DOI: 10.1126/sciadv.abm5944] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Accepted: 03/09/2022] [Indexed: 06/11/2023]
Abstract
Dogs are uniquely associated with human dispersal and bring transformational insight into the domestication process. Dingoes represent an intriguing case within canine evolution being geographically isolated for thousands of years. Here, we present a high-quality de novo assembly of a pure dingo (CanFam_DDS). We identified large chromosomal differences relative to the current dog reference (CanFam3.1) and confirmed no expanded pancreatic amylase gene as found in breed dogs. Phylogenetic analyses using variant pairwise matrices show that the dingo is distinct from five breed dogs with 100% bootstrap support when using Greenland wolf as the outgroup. Functionally, we observe differences in methylation patterns between the dingo and German shepherd dog genomes and differences in serum biochemistry and microbiome makeup. Our results suggest that distinct demographic and environmental conditions have shaped the dingo genome. In contrast, artificial human selection has likely shaped the genomes of domestic breed dogs after divergence from the dingo.
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Affiliation(s)
- Matt A. Field
- Centre for Tropical Bioinformatics and Molecular Biology, College of Public Health, Medical and Veterinary Sciences, James Cook University, Cairns, QLD 4878, Australia
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Sonu Yadav
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Olga Dudchenko
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
| | - Meera Esvaran
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Ksenia Skvortsova
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Richard J. Edwards
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Jens Keilwagen
- Julius Kühn-Institut, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany
| | - Blake J. Cochran
- School of Medical Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Bikash Manandhar
- School of Medical Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Sonia Bustamante
- Bioanalytical Mass Spectrometry Facility, Mark Wainwright Analytical Centre, University of New South Wales, Sydney, NSW 2052, Australia
| | - Jacob Agerbo Rasmussen
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
- Center for Evolutionary Hologenomics, Faculty of Health and Medical Sciences, The GLOBE Institute University of Copenhagen, Copenhagen, Denmark
| | - Richard G. Melvin
- Department of Biomedical Sciences, University of Minnesota Medical School, 1035 University Drive, Duluth, MN 55812, USA
| | - Barry Chernoff
- College of the Environment, Departments of Biology, and Earth and Environmental Sciences, Wesleyan University, Middletown, CT 06459, USA
| | - Arina Omer
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA
| | - Zane Colaric
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eva K. F. Chan
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- Statewide Genomics, New South Wales Health Pathology, 45 Watt St, Newcastle, NSW 2300, Australia
| | - Andre E. Minoche
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Timothy P. L. Smith
- U.S. Meat Animal Research Center, Agricultural Research Service, USDA, Rd 313, Clay Center, NE 68933, USA
| | - M. Thomas P. Gilbert
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen 2100, Denmark
- University Museum, NTNU, Trondheim, Norway
| | - Ozren Bogdanovic
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Robert A. Zammit
- Vineyard Veterinary Hospital, 703 Windsor Rd, Vineyard, NSW 2765, Australia
| | - Torsten Thomas
- School of Biological, Earth and Environmental Sciences, University of New South Wales, Sydney, NSW 2052, Australia
| | - Erez L. Aiden
- The Center for Genome Architecture, Baylor College of Medicine, Houston, TX 77030, USA
- Center for Theoretical Biological Physics, Rice University, Houston, TX 77005, USA
- UWA School of Agriculture and Environment, The University of Western Australia, Perth, WA 6009, Australia
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Pudong 201210, China
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - J. William O. Ballard
- Department of Environment and Genetics, SABE, La Trobe University, Melbourne, VIC 3086, Australia
- School of Biosciences, University of Melbourne, Royal Parade, Parkville, VIC 3052, Australia
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3
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Crumbaker M, Chan EKF, Gong T, Corcoran N, Jaratlerdsiri W, Lyons RJ, Haynes AM, Kulidjian AA, Kalsbeek AMF, Petersen DC, Stricker PD, Jamieson CAM, Croucher PI, Hovens CM, Joshua AM, Hayes VM. The Impact of Whole Genome Data on Therapeutic Decision-Making in Metastatic Prostate Cancer: A Retrospective Analysis. Cancers (Basel) 2020; 12:E1178. [PMID: 32392735 PMCID: PMC7280976 DOI: 10.3390/cancers12051178] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Revised: 04/21/2020] [Accepted: 04/28/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND While critical insights have been gained from evaluating the genomic landscape of metastatic prostate cancer, utilizing this information to inform personalized treatment is in its infancy. We performed a retrospective pilot study to assess the current impact of precision medicine for locally advanced and metastatic prostate adenocarcinoma and evaluate how genomic data could be harnessed to individualize treatment. METHODS Deep whole genome-sequencing was performed on 16 tumour-blood pairs from 13 prostate cancer patients; whole genome optical mapping was performed in a subset of 9 patients to further identify large structural variants. Tumour samples were derived from prostate, lymph nodes, bone and brain. RESULTS Most samples had acquired genomic alterations in multiple therapeutically relevant pathways, including DNA damage response (11/13 cases), PI3K (7/13), MAPK (10/13) and Wnt (9/13). Five patients had somatic copy number losses in genes that may indicate sensitivity to immunotherapy (LRP1B, CDK12, MLH1) and one patient had germline and somatic BRCA2 alterations. CONCLUSIONS Most cases, whether primary or metastatic, harboured therapeutically relevant alterations, including those associated with PARP inhibitor sensitivity, immunotherapy sensitivity and resistance to androgen pathway targeting agents. The observed intra-patient heterogeneity and presence of genomic alterations in multiple growth pathways in individual cases suggests that a precision medicine model in prostate cancer needs to simultaneously incorporate multiple pathway-targeting agents. Our whole genome approach allowed for structural variant assessment in addition to the ability to rapidly reassess an individual's molecular landscape as knowledge of relevant biomarkers evolve. This retrospective oncological assessment highlights the genomic complexity of prostate cancer and the potential impact of assessing genomic data for an individual at any stage of the disease.
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Affiliation(s)
- Megan Crumbaker
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Randwick, NSW 2031, Australia
- Kinghorn Cancer Centre, Department of Medical Oncology, St. Vincent’s Hospital, Darlinghurst, NSW 2010, Australia
| | - Eva K. F. Chan
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Randwick, NSW 2031, Australia
| | - Tingting Gong
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- Central Clinical School, University of Sydney, Sydney, Camperdown, NSW 2050, Australia
| | - Niall Corcoran
- Australian Prostate Cancer Research Centre Epworth, Richmond, VIC 3121, Australia;
- Department of Surgery, University of Melbourne, Melbourne, VIC 3010, Australia
- Division of Urology, Royal Melbourne Hospital, Melbourne, VIC 3050, Australia
| | - Weerachai Jaratlerdsiri
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
| | - Ruth J. Lyons
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
| | - Anne-Maree Haynes
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
| | - Anna A. Kulidjian
- Department of Orthopedic Surgery, Scripps Clinic, La Jolla, CA 92037, USA.;
- Orthopedic Oncology Program, Scripps MD Anderson Cancer Center, La Jolla, CA 92037, USA
| | - Anton M. F. Kalsbeek
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
| | - Desiree C. Petersen
- The Centre for Proteomic and Genomic Research, Cape Town 7925, South Africa;
| | - Phillip D. Stricker
- Department of Urology, St. Vincent’s Hospital, Darlinghurst, NSW 2010, Australia;
| | - Christina A. M. Jamieson
- Department of Urology, Moores Cancer Center, University of California, San Diego, La Jolla, CA 92037, USA;
| | - Peter I. Croucher
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, Randwick, NSW 2031, Australia
| | - Christopher M. Hovens
- Australian Prostate Cancer Research Centre Epworth, Richmond, VIC 3121, Australia;
- Department of Surgery, University of Melbourne, Melbourne, VIC 3010, Australia
| | - Anthony M. Joshua
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Randwick, NSW 2031, Australia
- Kinghorn Cancer Centre, Department of Medical Oncology, St. Vincent’s Hospital, Darlinghurst, NSW 2010, Australia
| | - Vanessa M. Hayes
- Garvan Institute of Medical Research, Darlinghurst, NSW 2010, Australia; (M.C.); (E.K.F.C.); (T.G.); (W.J.); (R.J.L.); (A.-M.H.); (A.M.F.K.); (P.I.C.)
- St. Vincent’s Clinical School, University of New South Wales, Sydney, Randwick, NSW 2031, Australia
- Central Clinical School, University of Sydney, Sydney, Camperdown, NSW 2050, Australia
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4
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Gong T, Hayes VM, Chan EKF. Detection of somatic structural variants from short-read next-generation sequencing data. Brief Bioinform 2020; 22:5831479. [PMID: 32379294 PMCID: PMC8138798 DOI: 10.1093/bib/bbaa056] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2019] [Revised: 03/05/2020] [Accepted: 03/29/2020] [Indexed: 01/09/2023] Open
Abstract
Somatic structural variants (SVs), which are variants that typically impact >50 nucleotides, play a significant role in cancer development and evolution but are notoriously more difficult to detect than small variants from short-read next-generation sequencing (NGS) data. This is due to a combination of challenges attributed to the purity of tumour samples, tumour heterogeneity, limitations of short-read information from NGS and sequence alignment ambiguities. In spite of active development of SV detection tools (callers) over the past few years, each method has inherent advantages and limitations. In this review, we highlight some of the important factors affecting somatic SV detection and compared the performance of seven commonly used SV callers. In particular, we focus on the extent of change in sensitivity and precision for detecting different SV types and size ranges from samples with differing variant allele frequencies and sequencing depths of coverage. We highlight the reasons for why some SV callers perform well in some settings but not others, allowing our evaluation findings to be extended beyond the seven SV callers examined in this paper. As the importance of large SVs become increasingly recognized in cancer genomics, this paper provides a timely review on some of the most impactful factors influencing somatic SV detection that should be considered when choosing SV callers.
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Affiliation(s)
| | - Vanessa M Hayes
- Corresponding authors: Eva K.F. Chan, New South Wales Health Pathology, Newcastle, NSW 2300, Australia. E-mail: ; Vanessa M. Hayes, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia. Tel.: +61-2-9355-5841; Fax: +61 2-2-9295-8151; E-mail:
| | - Eva K F Chan
- Corresponding authors: Eva K.F. Chan, New South Wales Health Pathology, Newcastle, NSW 2300, Australia. E-mail: ; Vanessa M. Hayes, Garvan Institute of Medical Research, Sydney, NSW 2010, Australia. Tel.: +61-2-9355-5841; Fax: +61 2-2-9295-8151; E-mail:
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5
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Field MA, Rosen BD, Dudchenko O, Chan EKF, Minoche AE, Edwards RJ, Barton K, Lyons RJ, Tuipulotu DE, Hayes VM, D. Omer A, Colaric Z, Keilwagen J, Skvortsova K, Bogdanovic O, Smith MA, Aiden EL, Smith TPL, Zammit RA, Ballard JWO. Canfam_GSD: De novo chromosome-length genome assembly of the German Shepherd Dog (Canis lupus familiaris) using a combination of long reads, optical mapping, and Hi-C. Gigascience 2020; 9:giaa027. [PMID: 32236524 PMCID: PMC7111595 DOI: 10.1093/gigascience/giaa027] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2019] [Revised: 01/29/2020] [Accepted: 02/20/2020] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND The German Shepherd Dog (GSD) is one of the most common breeds on earth and has been bred for its utility and intelligence. It is often first choice for police and military work, as well as protection, disability assistance, and search-and-rescue. Yet, GSDs are well known to be susceptible to a range of genetic diseases that can interfere with their training. Such diseases are of particular concern when they occur later in life, and fully trained animals are not able to continue their duties. FINDINGS Here, we provide the draft genome sequence of a healthy German Shepherd female as a reference for future disease and evolutionary studies. We generated this improved canid reference genome (CanFam_GSD) utilizing a combination of Pacific Bioscience, Oxford Nanopore, 10X Genomics, Bionano, and Hi-C technologies. The GSD assembly is ∼80 times as contiguous as the current canid reference genome (20.9 vs 0.267 Mb contig N50), containing far fewer gaps (306 vs 23,876) and fewer scaffolds (429 vs 3,310) than the current canid reference genome CanFamv3.1. Two chromosomes (4 and 35) are assembled into single scaffolds with no gaps. BUSCO analyses of the genome assembly results show that 93.0% of the conserved single-copy genes are complete in the GSD assembly compared with 92.2% for CanFam v3.1. Homology-based gene annotation increases this value to ∼99%. Detailed examination of the evolutionarily important pancreatic amylase region reveals that there are most likely 7 copies of the gene, indicative of a duplication of 4 ancestral copies and the disruption of 1 copy. CONCLUSIONS GSD genome assembly and annotation were produced with major improvement in completeness, continuity, and quality over the existing canid reference. This resource will enable further research related to canine diseases, the evolutionary relationships of canids, and other aspects of canid biology.
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Affiliation(s)
- Matt A Field
- Centre for Tropical Bioinformatics and Molecular Biology, Australian Institute of Tropical Health and Medicine, James Cook University, Smithfield Road, Cairns, QLD 4878, Australia
- John Curtin School of Medical Research, Australian National University, Garran Rd, Canberra, ACT 2600, Australia
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service USDA, Baltimore Ave, Beltsville, MD 20705, USA
| | - Olga Dudchenko
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Plaza, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Main St, Houston, TX 77005, USA
- Center for Theoretical and Biological Physics, Rice University, Main St, Houston, TX 77005, USA
| | - Eva K F Chan
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- Faculty of Medicine, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Andre E Minoche
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- St Vincent’s Clinical School, University of New South Wales Sydney, Victoria Street, Darlinghurst NSW 2010, Australia
| | - Richard J Edwards
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Kirston Barton
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- Faculty of Medicine, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Ruth J Lyons
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Daniel Enosi Tuipulotu
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Vanessa M Hayes
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- Faculty of Medicine, UNSW Sydney, High St, Kensington, NSW 2052, Australia
- Central Clinical School, University of Sydney, Parramatta Road, Camperdown, NSW 2050, Australia
| | - Arina D. Omer
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Plaza, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Main St, Houston, TX 77005, USA
| | - Zane Colaric
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Plaza, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Main St, Houston, TX 77005, USA
| | - Jens Keilwagen
- Julius Kühn-Institut, Erwin-Baur-Str. 27, 06484 Quedlinburg, Germany
| | - Ksenia Skvortsova
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
| | - Ozren Bogdanovic
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Martin A Smith
- Garvan Institute of Medical Research, Victoria Street, Darlinghurst, NSW 2010, Australia
- Faculty of Medicine, UNSW Sydney, High St, Kensington, NSW 2052, Australia
| | - Erez Lieberman Aiden
- The Center for Genome Architecture, Department of Molecular and Human Genetics, Baylor College of Medicine, Baylor Plaza, Houston, TX 77030, USA
- Department of Computer Science, Rice University, Main St, Houston, TX 77005, USA
- Center for Theoretical and Biological Physics, Rice University, Main St, Houston, TX 77005, USA
- Broad Institute of MIT and Harvard, Main St, Cambridge, MA 02142, USA
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, ShanghaiTech University, Huaxia Middle Rd, Pudong 201210, China
| | - Timothy P L Smith
- US Meat Animal Research Center, Agricultural Research Service USDA, Rd 313, Clay Center, NE 68933, USA
| | - Robert A Zammit
- Vineyard Veterinary Hospital, Windsor Rd, Vineyard, NSW 2765, Australia
| | - J William O Ballard
- School of Biotechnology and Biomolecular Sciences, UNSW Sydney, High St, Kensington, NSW 2052, Australia
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6
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Chan EKF, Timmermann A, Baldi BF, Moore AE, Lyons RJ, Lee SS, Kalsbeek AMF, Petersen DC, Rautenbach H, Förtsch HEA, Bornman MSR, Hayes VM. Human origins in a southern African palaeo-wetland and first migrations. Nature 2019; 575:185-189. [PMID: 31659339 DOI: 10.1038/s41586-019-1714-1] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Accepted: 09/24/2019] [Indexed: 01/17/2023]
Abstract
Anatomically modern humans originated in Africa around 200 thousand years ago (ka)1-4. Although some of the oldest skeletal remains suggest an eastern African origin2, southern Africa is home to contemporary populations that represent the earliest branch of human genetic phylogeny5,6. Here we generate, to our knowledge, the largest resource for the poorly represented and deepest-rooting maternal L0 mitochondrial DNA branch (198 new mitogenomes for a total of 1,217 mitogenomes) from contemporary southern Africans and show the geographical isolation of L0d1'2, L0k and L0g KhoeSan descendants south of the Zambezi river in Africa. By establishing mitogenomic timelines, frequencies and dispersals, we show that the L0 lineage emerged within the residual Makgadikgadi-Okavango palaeo-wetland of southern Africa7, approximately 200 ka (95% confidence interval, 240-165 ka). Genetic divergence points to a sustained 70,000-year-long existence of the L0 lineage before an out-of-homeland northeast-southwest dispersal between 130 and 110 ka. Palaeo-climate proxy and model data suggest that increased humidity opened green corridors, first to the northeast then to the southwest. Subsequent drying of the homeland corresponds to a sustained effective population size (L0k), whereas wet-dry cycles and probable adaptation to marine foraging allowed the southwestern migrants to achieve population growth (L0d1'2), as supported by extensive south-coastal archaeological evidence8-10. Taken together, we propose a southern African origin of anatomically modern humans with sustained homeland occupation before the first migrations of people that appear to have been driven by regional climate changes.
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Affiliation(s)
- Eva K F Chan
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.,St Vincent's Clinical School, University of New South Wales, Sydney, New South Wales, Australia
| | - Axel Timmermann
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea. .,Pusan National University, Busan, South Korea.
| | - Benedetta F Baldi
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Andy E Moore
- Department of Geology, Rhodes University, Grahamstown, South Africa
| | - Ruth J Lyons
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Sun-Seon Lee
- Center for Climate Physics, Institute for Basic Science, Busan, South Korea.,Pusan National University, Busan, South Korea
| | - Anton M F Kalsbeek
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia
| | - Desiree C Petersen
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia.,The Centre for Proteomic and Genomic Research, Cape Town, South Africa
| | - Hannes Rautenbach
- Climate Change and Variability, South African Weather Service, Pretoria, South Africa.,School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa.,Akademia, Johannesburg, South Africa
| | | | - M S Riana Bornman
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Vanessa M Hayes
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, Sydney, New South Wales, Australia. .,St Vincent's Clinical School, University of New South Wales, Sydney, New South Wales, Australia. .,School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa. .,Faculty of Health Sciences, University of Limpopo, Sovenga, South Africa. .,Central Clinical School, University of Sydney, Sydney, New South Wales, Australia.
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7
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Petersen DC, Jaratlerdsiri W, van Wyk A, Chan EKF, Fernandez P, Lyons RJ, Mutambirw SBA, van der Merwe A, Venter PA, Bates W, Bornman MSR, Hayes VM. African KhoeSan ancestry linked to high-risk prostate cancer. BMC Med Genomics 2019; 12:82. [PMID: 31164124 PMCID: PMC6549381 DOI: 10.1186/s12920-019-0537-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2018] [Accepted: 05/21/2019] [Indexed: 02/08/2023] Open
Abstract
Backgrounds Genetic diversity is greatest within Africa, in particular the KhoeSan click-speaking peoples of southern Africa. South African populations represent admixture fractions including differing degrees of African, African-KhoeSan and non-African genetic ancestries. Within the United States, African ancestry has been linked to prostate cancer presentation and mortality. Together with environmental contributions, genetics is a significant risk factor for high-risk prostate cancer, defined by a pathological Gleason score ≥ 8. Methods Using genotype array data merged with ancestry informative reference data, we investigate the contribution of African ancestral fractions to high-risk prostate cancer. Our study includes 152 South African men of African (Black) or African-admixed (Coloured) ancestries, in which 40% showed high-risk prostate cancer. Results Genetic fractions were determined for averaging an equal African to non-African genetic ancestral contribution in the Coloured; we found African ancestry to be linked to high-risk prostate cancer (P-value = 0.0477). Adjusting for age, the associated African ancestral fraction was driven by a significant KhoeSan over Bantu contribution, defined by Gleason score ≥ 8 (P-value = 0.02329) or prostate specific antigen levels ≥20 ng/ml (P-value = 0.03713). Additionally, we observed the mean overall KhoeSan contribution to be increased in Black patients with high-risk (11.8%) over low-risk (10.9%) disease. Linking for the first time KhoeSan ancestry to a common modern disease, namely high-risk prostate cancer, we tested in this small study the validity of using KhoeSan ancestry as a surrogate for identifying potential high-risk prostate cancer risk loci. As such, we identified four loci within chromosomal regions 2p11.2, 3p14, 8q23 and 22q13.2 (P-value = all age-adjusted < 0.01), two of which have previously been associated with high-risk prostate cancer. Conclusions Our study suggests that ancient KhoeSan ancestry may be linked to common modern diseases, specifically those of late onset and therefore unlikely to have undergone exclusive selective pressure. As such we show within a uniquely admixed South African population a link between KhoeSan ancestry and high-risk prostate cancer, which may explain the 2-fold increase in presentation in Black South Africans compared with African Americans. Electronic supplementary material The online version of this article (10.1186/s12920-019-0537-0) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Desiree C Petersen
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria Street, Darlinghurst, NSW, 2010, Australia.,Faculty of Medicine, University of New South Wales, Randwick, NSW, Australia.,Centre for Proteomic and Genomic Research (CPGR), 1st Floor, St. Peters Mall, Cnr. Anzio and Main Road, Observatory, Cape Town, 7925, South Africa
| | - Weerachai Jaratlerdsiri
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria Street, Darlinghurst, NSW, 2010, Australia
| | - Abraham van Wyk
- Division of Anatomical Pathology, NHLS Tygerberg and Stellenbosch University, Tygerberg, South Africa
| | - Eva K F Chan
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria Street, Darlinghurst, NSW, 2010, Australia.,Faculty of Medicine, University of New South Wales, Randwick, NSW, Australia
| | - Pedro Fernandez
- Division of Urology, Department of Surgical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Ruth J Lyons
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria Street, Darlinghurst, NSW, 2010, Australia
| | - Shingai B A Mutambirw
- Department of Urology, Sefako Makgatho Health Science University, Dr George Mukhari Academic Hospital, Medunsa, South Africa
| | - Andre van der Merwe
- Division of Urology, Department of Surgical Sciences, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
| | - Philip A Venter
- Faculty of Health Sciences, University of Limpopo, Mankweng, South Africa
| | - William Bates
- Division of Anatomical Pathology, NHLS Tygerberg and Stellenbosch University, Tygerberg, South Africa
| | - M S Riana Bornman
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Vanessa M Hayes
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, The Kinghorn Cancer Centre, 370 Victoria Street, Darlinghurst, NSW, 2010, Australia. .,Faculty of Medicine, University of New South Wales, Randwick, NSW, Australia. .,Faculty of Health Sciences, University of Limpopo, Mankweng, South Africa. .,School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa. .,Central Clinical School, University of Sydney, Camperdown, NSW, Australia.
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Chan EKF, Cameron DL, Petersen DC, Lyons RJ, Baldi BF, Papenfuss AT, Thomas DM, Hayes VM. Optical mapping reveals a higher level of genomic architecture of chained fusions in cancer. Genome Res 2018; 28:726-738. [PMID: 29618486 PMCID: PMC5932612 DOI: 10.1101/gr.227975.117] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 03/21/2018] [Indexed: 01/21/2023]
Abstract
Genomic rearrangements are common in cancer, with demonstrated links to disease progression and treatment response. These rearrangements can be complex, resulting in fusions of multiple chromosomal fragments and generation of derivative chromosomes. Although methods exist for detecting individual fusions, they are generally unable to reconstruct complex chained events. To overcome these limitations, we adopted a new optical mapping approach, allowing megabase-length genome maps to be reconstructed and rearranged genomes to be visualized without loss of integrity. Whole-genome mapping (Bionano Genomics) of a well-studied highly rearranged liposarcoma cell line resulted in 3338 assembled consensus genome maps, including 72 fusion maps. These fusion maps represent 112.3 Mb of highly rearranged genomic regions, illuminating the complex architecture of chained fusions, including content, order, orientation, and size. Spanning the junction of 147 chromosomal translocations, we found a total of 28 Mb of interspersed sequences that could not be aligned to the reference genome. Traversing these interspersed sequences using short-read sequencing breakpoint calls, we were able to identify and place 399 sequencing fragments within the optical mapping gaps, thus illustrating the complementary nature of optical mapping and short-read sequencing. We demonstrate that optical mapping provides a powerful new approach for capturing a higher level of complex genomic architecture, creating a scaffold for renewed interpretation of sequencing data of particular relevance to human cancer.
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Affiliation(s)
- Eva K F Chan
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, New South Wales 2010, Australia.,St Vincent's Clinical School, University of New South Wales, New South Wales 2052, Australia
| | - Daniel L Cameron
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Victoria 3052, Australia.,Department of Medical Biology, University of Melbourne, Victoria 3010, Australia
| | - Desiree C Petersen
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, New South Wales 2010, Australia.,St Vincent's Clinical School, University of New South Wales, New South Wales 2052, Australia
| | - Ruth J Lyons
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, New South Wales 2010, Australia
| | - Benedetta F Baldi
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, New South Wales 2010, Australia
| | - Anthony T Papenfuss
- Bioinformatics Division, The Walter and Eliza Hall Institute of Medical Research, Victoria 3052, Australia.,Department of Medical Biology, University of Melbourne, Victoria 3010, Australia.,Department of Mathematics and Statistics, University of Melbourne, Victoria 3010, Australia.,Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria 3010, Australia.,Bioinformatics and Cancer Genomics, Peter MacCallum Cancer Centre, Victoria 3002, Australia
| | - David M Thomas
- The Kinghorn Cancer Centre, Garvan Institute of Medical Research, New South Wales 2010, Australia.,Cancer Division, Garvan Institute of Medical Research, New South Wales 2010, Australia
| | - Vanessa M Hayes
- Genomics and Epigenetics Division, Garvan Institute of Medical Research, New South Wales 2010, Australia.,St Vincent's Clinical School, University of New South Wales, New South Wales 2052, Australia.,School of Health Systems and Public Health, University of Pretoria, Hatfield 0002, South Africa.,Central Clinical School, University of Sydney, New South Wales 2006, Australia
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9
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Kalsbeek AMF, Chan EKF, Grogan J, Petersen DC, Jaratlerdsiri W, Gupta R, Lyons RJ, Haynes AM, Horvath LG, Kench JG, Stricker PD, Hayes VM. Altered mitochondrial genome content signals worse pathology and prognosis in prostate cancer. Prostate 2018; 78:25-31. [PMID: 29134670 DOI: 10.1002/pros.23440] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Accepted: 09/29/2017] [Indexed: 01/24/2023]
Abstract
BACKGROUND Mitochondrial genome (mtDNA) content is depleted in many cancers. In prostate cancer, there is intra-glandular as well as inter-patient mtDNA copy number variation. In this study, we determine if mtDNA content can be used as a predictor for prostate cancer staging and outcomes. METHODS Fresh prostate cancer biopsies from 115 patients were obtained at time of surgery. All cores underwent pathological review, followed by isolation of cancer and normal tissue. DNA was extracted and qPCR performed to quantify the total amount of mtDNA as a ratio to genomic DNA. Differences in mtDNA content were compared for prostate cancer pathology features and disease outcomes. RESULTS We showed a significantly reduced mtDNA content in prostate cancer compared with normal adjacent prostate tissue (mean difference 1.73-fold, P-value <0.001). Prostate cancer with increased mtDNA content showed unfavorable pathologic characteristics including, higher disease stage (PT2 vs PT3 P-value = 0.018), extracapsular extension (P-value = 0.02) and a trend toward an increased Gleason score (P-value = 0.064). No significant association was observed between changes in mtDNA content and biochemical recurrence (median follow up of 107 months). CONCLUSIONS Contrary to other cancer types, prostate cancer tissue shows no universally depleted mtDNA content. Rather, the change in mtDNA content is highly variable, mirroring known prostate cancer genome heterogeneity. Patients with high mtDNA content have an unfavorable pathology, while a high mtDNA content in normal adjacent prostate tissue is associated with worse prognosis.
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Affiliation(s)
- Anton M F Kalsbeek
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Medical Sciences, University of New South Wales Sydney, Randwick, New South Wales, Australia
| | - Eva K F Chan
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Medical Sciences, University of New South Wales Sydney, Randwick, New South Wales, Australia
| | - Judith Grogan
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- Central Clinical School, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Desiree C Petersen
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Medical Sciences, University of New South Wales Sydney, Randwick, New South Wales, Australia
| | - Weerachai Jaratlerdsiri
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Ruta Gupta
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- Central Clinical School, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Ruth J Lyons
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Anne-Maree Haynes
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Lisa G Horvath
- Central Clinical School, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- Chris O'Brien Lifehouse, Camperdown, New South Wales, Australia
| | - James G Kench
- Department of Tissue Pathology and Diagnostic Oncology, Royal Prince Alfred Hospital, Camperdown, New South Wales, Australia
- Central Clinical School, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Phillip D Stricker
- Department of Urology, St. Vincent's Hospital, Darlinghurst, New South Wales, Australia
| | - Vanessa M Hayes
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
- School of Medical Sciences, University of New South Wales Sydney, Randwick, New South Wales, Australia
- Central Clinical School, Sydney Medical School, University of Sydney, Camperdown, New South Wales, Australia
- Cancer Research Division, The Kinghorn Cancer Center, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
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10
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Jaratlerdsiri W, Chan EKF, Petersen DC, Yang C, Croucher PI, Bornman MSR, Sheth P, Hayes VM. Next generation mapping reveals novel large genomic rearrangements in prostate cancer. Oncotarget 2017; 8:23588-23602. [PMID: 28423598 PMCID: PMC5410329 DOI: 10.18632/oncotarget.15802] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2016] [Accepted: 02/15/2017] [Indexed: 12/27/2022] Open
Abstract
Complex genomic rearrangements are common molecular events driving prostate carcinogenesis. Clinical significance, however, has yet to be fully elucidated. Detecting the full range and subtypes of large structural variants (SVs), greater than one kilobase in length, is challenging using clinically feasible next generation sequencing (NGS) technologies. Next generation mapping (NGM) is a new technology that allows for the interrogation of megabase length DNA molecules outside the detection range of single-base resolution NGS. In this study, we sought to determine the feasibility of using the Irys (Bionano Genomics Inc.) nanochannel NGM technology to generate whole genome maps of a primary prostate tumor and matched blood from a Gleason score 7 (4 + 3), ETS-fusion negative prostate cancer patient. With an effective mapped coverage of 35X and sequence coverage of 60X, and an estimated 43% tumor purity, we identified 85 large somatic structural rearrangements and 6,172 smaller somatic variants, respectively. The vast majority of the large SVs (89%), of which 73% are insertions, were not detectable ab initio using high-coverage short-read NGS. However, guided manual inspection of single NGS reads and de novo assembled scaffolds of NGM-derived candidate regions allowed for confirmation of 94% of these large SVs, with over a third impacting genes with oncogenic potential. From this single-patient study, the first cancer study to integrate NGS and NGM data, we hypothesise that there exists a novel spectrum of large genomic rearrangements in prostate cancer, that these large genomic rearrangements are likely early events in tumorigenesis, and they have potential to enhance taxonomy.
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Affiliation(s)
- Weerachai Jaratlerdsiri
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia
| | - Eva K F Chan
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia.,St Vincent's Clinical School, University of New South Wales, Randwick, Australia
| | - Desiree C Petersen
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia.,St Vincent's Clinical School, University of New South Wales, Randwick, Australia
| | - Claire Yang
- Bionano Genomics Inc., San Diego, California, USA
| | - Peter I Croucher
- St Vincent's Clinical School, University of New South Wales, Randwick, Australia.,Bone Biology Division, Garvan Institute of Medical Research, Darlinghurst, Australia.,School of Biotechnology and Biomolecular Sciences, University of New South Wales, Randwick, Australia
| | - M S Riana Bornman
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Palak Sheth
- Bionano Genomics Inc., San Diego, California, USA
| | - Vanessa M Hayes
- Laboratory for Human Comparative and Prostate Cancer Genomics, Genomics and Epigenetics Division, Garvan Institute of Medical Research, Darlinghurst, Australia.,St Vincent's Clinical School, University of New South Wales, Randwick, Australia.,School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa.,Central Clinical School, University of Sydney, Camperdown, Australia
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11
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McCrow JP, Petersen DC, Louw M, Chan EKF, Harmeyer K, Vecchiarelli S, Lyons RJ, Bornman MSR, Hayes VM. Spectrum of mitochondrial genomic variation and associated clinical presentation of prostate cancer in South African men. Prostate 2016; 76:349-58. [PMID: 26660354 PMCID: PMC4832339 DOI: 10.1002/pros.23126] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 11/05/2015] [Indexed: 01/09/2023]
Abstract
BACKGROUND Prostate cancer incidence and mortality rates are significantly increased in African-American men, but limited studies have been performed within Sub-Saharan African populations. As mitochondria control energy metabolism and apoptosis we speculate that somatic mutations within mitochondrial genomes are candidate drivers of aggressive prostate carcinogenesis. METHODS We used matched blood and prostate tissue samples from 87 South African men (77 with African ancestry) to perform deep sequencing of complete mitochondrial genomes. Clinical presentation was biased toward aggressive disease (Gleason score >7, 64%), and compared with men without prostate cancer either with or without benign prostatic hyperplasia. RESULTS We identified 144 somatic mtDNA single nucleotide variants (SNVs), of which 80 were observed in 39 men presenting with aggressive disease. Both the number and frequency of somatic mtDNA SNVs were associated with higher pathological stage. CONCLUSIONS Besides doubling the total number of somatic PCa-associated mitochondrial genome mutations identified to date, we associate mutational load with aggressive prostate cancer status in men of African ancestry.
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Affiliation(s)
| | - Desiree C. Petersen
- J. Craig Venter InstituteLa JollaCalifornia
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
- Faculty of MedicineUniversity of New SouthWales Australia, RandwickNSWAustralia
| | - Melanie Louw
- Department of PathologyUniversity of PretoriaSouth Africa
| | - Eva K. F. Chan
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
- Faculty of MedicineUniversity of New SouthWales Australia, RandwickNSWAustralia
| | - Katherine Harmeyer
- J. Craig Venter InstituteLa JollaCalifornia
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
| | - Stefano Vecchiarelli
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
| | - Ruth J. Lyons
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
| | - M. S. Riana Bornman
- School of Health Systems and Public HealthUniversity of PretoriaSouth Africa
| | - Vanessa M. Hayes
- J. Craig Venter InstituteLa JollaCalifornia
- Laboratory for Human Comparative and Prostate Cancer GenomicsGarvan Institute of Medical ResearchDarlinghurst, SydneyNSWAustralia
- Faculty of MedicineUniversity of New SouthWales Australia, RandwickNSWAustralia
- School of Health Systems and Public HealthUniversity of PretoriaSouth Africa
- Central Clinical SchoolUniversity of SydneyCamperdown, SydneyNSWAustralia
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12
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Chan EKF, Hardie RA, Petersen DC, Beeson K, Bornman RMS, Smith AB, Hayes VM. Revised timeline and distribution of the earliest diverged human maternal lineages in southern Africa. PLoS One 2015; 10:e0121223. [PMID: 25807545 PMCID: PMC4373779 DOI: 10.1371/journal.pone.0121223] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2014] [Accepted: 01/29/2015] [Indexed: 02/05/2023] Open
Abstract
The oldest extant human maternal lineages include mitochondrial haplogroups L0d and L0k found in the southern African click-speaking forager peoples broadly classified as Khoesan. Profiling these early mitochondrial lineages allows for better understanding of modern human evolution. In this study, we profile 77 new early-diverged complete mitochondrial genomes and sub-classify another 105 L0d/L0k individuals from southern Africa. We use this data to refine basal phylogenetic divergence, coalescence times and Khoesan prehistory. Our results confirm L0d as the earliest diverged lineage (∼172 kya, 95%CI: 149–199 kya), followed by L0k (∼159 kya, 95%CI: 136–183 kya) and a new lineage we name L0g (∼94 kya, 95%CI: 72–116 kya). We identify two new L0d1 subclades we name L0d1d and L0d1c4/L0d1e, and estimate L0d2 and L0d1 divergence at ∼93 kya (95%CI:76–112 kya). We concur the earliest emerging L0d1’2 sublineage L0d1b (∼49 kya, 95%CI:37–58 kya) is widely distributed across southern Africa. Concomitantly, we find the most recent sublineage L0d2a (∼17 kya, 95%CI:10–27 kya) to be equally common. While we agree that lineages L0d1c and L0k1a are restricted to contemporary inland Khoesan populations, our observed predominance of L0d2a and L0d1a in non-Khoesan populations suggests a once independent coastal Khoesan prehistory. The distribution of early-diverged human maternal lineages within contemporary southern Africans suggests a rich history of human existence prior to any archaeological evidence of migration into the region. For the first time, we provide a genetic-based evidence for significant modern human evolution in southern Africa at the time of the Last Glacial Maximum at between ∼21–17 kya, coinciding with the emergence of major lineages L0d1a, L0d2b, L0d2d and L0d2a.
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Affiliation(s)
- Eva K. F. Chan
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia
- Faculty of Medicine, University of New South Wales Australia, Randwick, NSW, Australia
| | - Rae-Anne Hardie
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia
- Faculty of Medicine, University of New South Wales Australia, Randwick, NSW, Australia
| | - Desiree C. Petersen
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia
- Faculty of Medicine, University of New South Wales Australia, Randwick, NSW, Australia
- J. Craig Venter Institute, 4120 Torrey Pines Road, La Jolla, California, 92037, United States of America
| | - Karen Beeson
- J. Craig Venter Institute, 4120 Torrey Pines Road, La Jolla, California, 92037, United States of America
| | - Riana M. S. Bornman
- School of Health Systems and Public Health, University of Pretoria, Hatfield, South Africa
| | - Andrew B. Smith
- Department of Archaeology, University of Cape Town, Rondebosch, South Africa
| | - Vanessa M. Hayes
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, 384 Victoria Street, Darlinghurst, NSW, 2010, Australia
- Faculty of Medicine, University of New South Wales Australia, Randwick, NSW, Australia
- J. Craig Venter Institute, 4120 Torrey Pines Road, La Jolla, California, 92037, United States of America
- School of Health Systems and Public Health, University of Pretoria, Hatfield, South Africa
- Central Clinical School, The University of Sydney, Camperdown, NSW, Australia
- * E-mail:
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Porto-Neto LR, Reverter A, Prayaga KC, Chan EKF, Johnston DJ, Hawken RJ, Fordyce G, Garcia JF, Sonstegard TS, Bolormaa S, Goddard ME, Burrow HM, Henshall JM, Lehnert SA, Barendse W. The genetic architecture of climatic adaptation of tropical cattle. PLoS One 2014; 9:e113284. [PMID: 25419663 PMCID: PMC4242650 DOI: 10.1371/journal.pone.0113284] [Citation(s) in RCA: 81] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2014] [Accepted: 10/21/2014] [Indexed: 11/18/2022] Open
Abstract
Adaptation of global food systems to climate change is essential to feed the world. Tropical cattle production, a mainstay of profitability for farmers in the developing world, is dominated by heat, lack of water, poor quality feedstuffs, parasites, and tropical diseases. In these systems European cattle suffer significant stock loss, and the cross breeding of taurine x indicine cattle is unpredictable due to the dilution of adaptation to heat and tropical diseases. We explored the genetic architecture of ten traits of tropical cattle production using genome wide association studies of 4,662 animals varying from 0% to 100% indicine. We show that nine of the ten have genetic architectures that include genes of major effect, and in one case, a single location that accounted for more than 71% of the genetic variation. One genetic region in particular had effects on parasite resistance, yearling weight, body condition score, coat colour and penile sheath score. This region, extending 20 Mb on BTA5, appeared to be under genetic selection possibly through maintenance of haplotypes by breeders. We found that the amount of genetic variation and the genetic correlations between traits did not depend upon the degree of indicine content in the animals. Climate change is expected to expand some conditions of the tropics to more temperate environments, which may impact negatively on global livestock health and production. Our results point to several important genes that have large effects on adaptation that could be introduced into more temperate cattle without detrimental effects on productivity.
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Affiliation(s)
- Laercio R. Porto-Neto
- CSIRO Food Futures Flagship, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | - Antonio Reverter
- CSIRO Food Futures Flagship, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | | | - Eva K. F. Chan
- Garvan Institute of Medical Research, Darlinghurst, Sydney, NSW, Australia
| | - David J. Johnston
- Animal Genetics and Breeding Unit, University of New England, Armidale, NSW, Australia
| | - Rachel J. Hawken
- Cobb-Vantress Inc., Siloam Springs, Arizona, United States of America
| | - Geoffry Fordyce
- Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St. Lucia, QLD, Australia
| | - Jose Fernando Garcia
- Faculdade de Medicina Veterinaria de Araçatuba, (UNESP) Univ Estadual Paulista, Araçatuba, São Paulo, Brazil
| | - Tad S. Sonstegard
- United States Department of Agriculture, Agricultural Research Service, Bovine Functional Genomics Laboratory, Beltsville, Maryland, United States of America
| | | | | | - Heather M. Burrow
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | - John M. Henshall
- CSIRO Food Futures Flagship, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | - Sigrid A. Lehnert
- CSIRO Food Futures Flagship, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
| | - William Barendse
- CSIRO Animal, Food and Health Science, Queensland Bioscience Precinct, St. Lucia, QLD, Australia
- * E-mail:
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14
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Abstract
The oldest contemporary human mitochondrial lineages arose in Africa. The earliest divergent extant maternal offshoot, namely haplogroup L0d, is represented by click-speaking forager peoples of southern Africa. Broadly defined as Khoesan, contemporary Khoesan are today largely restricted to the semidesert regions of Namibia and Botswana, whereas archeological, historical, and genetic evidence promotes a once broader southerly dispersal of click-speaking peoples including southward migrating pastoralists and indigenous marine-foragers. No genetic data have been recovered from the indigenous peoples that once sustained life along the southern coastal waters of Africa prepastoral arrival. In this study we generate a complete mitochondrial genome from a 2,330-year-old male skeleton, confirmed through osteological and archeological analysis as practicing a marine-based forager existence. The ancient mtDNA represents a new L0d2c lineage (L0d2c1c) that is today, unlike its Khoe-language based sister-clades (L0d2c1a and L0d2c1b) most closely related to contemporary indigenous San-speakers (specifically Ju). Providing the first genomic evidence that prepastoral Southern African marine foragers carried the earliest diverged maternal modern human lineages, this study emphasizes the significance of Southern African archeological remains in defining early modern human origins.
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Affiliation(s)
- Alan G Morris
- Department of Human Biology, University of Cape Town, South Africa
| | - Anja Heinze
- Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
| | - Eva K F Chan
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia
| | - Andrew B Smith
- Department of Archeology, University of Cape Town, South Africa
| | - Vanessa M Hayes
- Laboratory for Human Comparative and Prostate Cancer Genomics, Garvan Institute of Medical Research, Darlinghurst, New South Wales, Australia Genomeic Medicine Group, J. Craig Venter Institute, La Jolla, California Central Clinical School, The University of Sydney, Camperdown, New South Wales, Australia Department of Urology, University of Pretoria, South Africa Medical Faculty, University of New South Wales, Randwick, New South Wales, Australia
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15
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Chan EKF, Rowe HC, Corwin JA, Joseph B, Kliebenstein DJ. Combining genome-wide association mapping and transcriptional networks to identify novel genes controlling glucosinolates in Arabidopsis thaliana. PLoS Biol 2011; 9:e1001125. [PMID: 21857804 PMCID: PMC3156686 DOI: 10.1371/journal.pbio.1001125] [Citation(s) in RCA: 216] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2010] [Accepted: 07/07/2011] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Genome-wide association (GWA) is gaining popularity as a means to study the architecture of complex quantitative traits, partially due to the improvement of high-throughput low-cost genotyping and phenotyping technologies. Glucosinolate (GSL) secondary metabolites within Arabidopsis spp. can serve as a model system to understand the genomic architecture of adaptive quantitative traits. GSL are key anti-herbivory defenses that impart adaptive advantages within field trials. While little is known about how variation in the external or internal environment of an organism may influence the efficiency of GWA, GSL variation is known to be highly dependent upon the external stresses and developmental processes of the plant lending it to be an excellent model for studying conditional GWA. METHODOLOGY/PRINCIPAL FINDINGS To understand how development and environment can influence GWA, we conducted a study using 96 Arabidopsis thaliana accessions, >40 GSL phenotypes across three conditions (one developmental comparison and one environmental comparison) and ∼230,000 SNPs. Developmental stage had dramatic effects on the outcome of GWA, with each stage identifying different loci associated with GSL traits. Further, while the molecular bases of numerous quantitative trait loci (QTL) controlling GSL traits have been identified, there is currently no estimate of how many additional genes may control natural variation in these traits. We developed a novel co-expression network approach to prioritize the thousands of GWA candidates and successfully validated a large number of these genes as influencing GSL accumulation within A. thaliana using single gene isogenic lines. CONCLUSIONS/SIGNIFICANCE Together, these results suggest that complex traits imparting environmentally contingent adaptive advantages are likely influenced by up to thousands of loci that are sensitive to fluctuations in the environment or developmental state of the organism. Additionally, while GWA is highly conditional upon genetics, the use of additional genomic information can rapidly identify causal loci en masse.
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Affiliation(s)
- Eva K. F. Chan
- Department of Plant Sciences, University of California–Davis, Davis, California, United States of America
- Monsanto Company, Vegetable Seeds Division, Woodland, California, United States of America
| | - Heather C. Rowe
- Department of Plant Sciences, University of California–Davis, Davis, California, United States of America
| | - Jason A. Corwin
- Department of Plant Sciences, University of California–Davis, Davis, California, United States of America
| | - Bindu Joseph
- Department of Plant Sciences, University of California–Davis, Davis, California, United States of America
| | - Daniel J. Kliebenstein
- Department of Plant Sciences, University of California–Davis, Davis, California, United States of America
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16
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Abstract
Beef cattle breeds consist of three major genetic subdivisions. The taurine group is adapted to temperate environments, and the zebu and Sanga groups are both adapted to tropical environments. With the advent of genotyping and sequencing technologies in agriculture, genome-wide exploration of the genetic basis for the differences in tropical adaptation has only just become possible. In this study, approximately 9000 single nucleotide polymorphism markers were genotyped on 317 animals of a selection of taurine, zebu, and composite breeds to characterize any systematic differences between these groups. We identified 91 intra-breed-class markers; 78 were polymorphic only within the zebu animals, while 13 were polymorphic only in the taurine animals. There were no fixed differences (fixed for alternate alleles between the two breed types) between zebu and taurine animals. We found 14 regions with significantly different allele frequencies between zebu and taurine animals indicative of variable selection pressure or genetic drift. We also found 12 independent regions of differential extended haplotype homozygosity (EHH), indicative of recent selection or rapid fixation of the alternate allele within a short period of time in one of the two breed classes. A preliminary functional genomics analysis of these regions pointed towards signatures of tropical attributes including keratins, heat-shock proteins and heat resistance genes. We anticipate this investigation to be a stepping-stone for future studies to identify genomic regions specific to the two cattle groups, and to subsequently assist in the discrimination between temperate and tropically adapted cattle.
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Affiliation(s)
- E K F Chan
- Cooperative Research Centre for Beef Genetic Technologies. CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Rd., St. Lucia, Brisbane, Qld 4067, Australia
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Abstract
Discovering links between the genotype of an organism and its metabolite levels can increase our understanding of metabolism, its controls, and the indirect effects of metabolism on other quantitative traits. Recent technological advances in both DNA sequencing and metabolite profiling allow the use of broad-spectrum, untargeted metabolite profiling to generate phenotypic data for genome-wide association studies that investigate quantitative genetic control of metabolism within species. We conducted a genome-wide association study of natural variation in plant metabolism using the results of untargeted metabolite analyses performed on a collection of wild Arabidopsis thaliana accessions. Testing 327 metabolites against >200,000 single nucleotide polymorphisms identified numerous genotype–metabolite associations distributed non-randomly within the genome. These clusters of genotype–metabolite associations (hotspots) included regions of the A. thaliana genome previously identified as subject to recent strong positive selection (selective sweeps) and regions showing trans-linkage to these putative sweeps, suggesting that these selective forces have impacted genome-wide control of A. thaliana metabolism. Comparing the metabolic variation detected within this collection of wild accessions to a laboratory-derived population of recombinant inbred lines (derived from two of the accessions used in this study) showed that the higher level of genetic variation present within the wild accessions did not correspond to higher variance in metabolic phenotypes, suggesting that evolutionary constraints limit metabolic variation. While a major goal of genome-wide association studies is to develop catalogues of intraspecific variation, the results of multiple independent experiments performed for this study showed that the genotype–metabolite associations identified are sensitive to environmental fluctuations. Thus, studies of intraspecific variation conducted via genome-wide association will require analyses of genotype by environment interaction. Interestingly, the network structure of metabolite linkages was also sensitive to environmental differences, suggesting that key aspects of network architecture are malleable. Understanding how genetic variation can control phenotypic variation is a fundamental goal of modern biology. We combined genome-wide association mapping with metabolomics in the plant Arabidopsis thaliana to explore how species-wide genetic variation controls metabolism. We identified numerous naturally-variable genes that may influence plant metabolism, often clustering in “hotspots.” These hotspots were proximal to selective sweeps, regions of the genome showing decreased diversity possibly from a strong selective advantage of specific variants within the region. This suggests that metabolism may be connected to the selective advantage. Interestingly, metabolite variation in wild Arabidopsis is highly constrained despite the significant genetic variation, thus providing the plant un-sampled metabolic space if the environment shifts. The observed structuring of genetic and metabolic variation suggests individual convergence upon similar phenotypes via different genotypes, possibly intra-specific parallel evolution. This phenotypic convergence couples with a pattern of genotype—phenotype association consistent with metabolite variation largely controlled by numerous small effect genetic variants. This supports the supposition that large magnitude variation is likely unstable in a complex and interconnected metabolism. If this pattern proves generally applicable to other species, it could present a significant hurdle to identifying genes controlling metabolic trait variation via genome-wide association studies.
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Affiliation(s)
- Eva K. F. Chan
- Department of Plant Sciences, University of California Davis, Davis, California, United States of America
| | - Heather C. Rowe
- Department of Plant Sciences, University of California Davis, Davis, California, United States of America
| | - Bjarne G. Hansen
- Department of Plant Biology and Biotechnology, Copenhagen University, Copenhagen, Denmark
| | - Daniel J. Kliebenstein
- Department of Plant Sciences, University of California Davis, Davis, California, United States of America
- * E-mail:
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Cowley MJ, Cotsapas CJ, Williams RBH, Chan EKF, Pulvers JN, Liu MY, Luo OJ, Nott DJ, Little PFR. Intra- and inter-individual genetic differences in gene expression. Mamm Genome 2009; 20:281-95. [PMID: 19424753 PMCID: PMC2690833 DOI: 10.1007/s00335-009-9181-x] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2008] [Accepted: 02/23/2009] [Indexed: 11/10/2022]
Abstract
Genetic variation is known to influence the amount of mRNA produced by a gene. Because molecular machines control mRNA levels of multiple genes, we expect genetic variation in components of these machines would influence multiple genes in a similar fashion. We show that this assumption is correct by using correlation of mRNA levels measured from multiple tissues in mouse strain panels to detect shared genetic influences. These correlating groups of genes (CGGs) have collective properties that on average account for 52–79% of the variability of their constituent genes and can contain genes that encode functionally related proteins. We show that the genetic influences are essentially tissue-specific and, consequently, the same genetic variations in one animal may upregulate a CGG in one tissue but downregulate the CGG in a second tissue. We further show similarly paradoxical behaviour of CGGs within the same tissues of different individuals. Thus, this class of genetic variation can result in complex inter- and intraindividual differences. This will create substantial challenges in humans, where multiple tissues are not readily available.
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Affiliation(s)
- Mark J Cowley
- School of Biotechnology and Biomolecular Sciences, The University of New South Wales, NSW, Australia
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19
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Abstract
The last decade has seen rapid improvements in high-throughput single nucleotide polymorphism (SNP) genotyping technologies that have consequently made genome-wide association studies (GWAS) possible. With tens to hundreds of thousands of SNP markers being tested simultaneously in GWAS, it is imperative to appropriately pre-process, or filter out, those SNPs that may lead to false associations. This paper explores the relationships between various SNP genotype and phenotype attributes and their effects on false associations. We show that (i) uniformly distributed ordinal data as well as binary data are more easily influenced, though not necessarily negatively, by differences in various SNP attributes compared with normally distributed data; (ii) filtering SNPs on minor allele frequency (MAF) and extent of Hardy–Weinberg equilibrium (HWE) deviation has little effect on the overall false positive rate; (iii) in some cases, filtering on MAF only serves to exclude SNPs from the analysis without reduction of the overall proportion of false associations; and (iv) HWE, MAF and heterozygosity are all dependent on minor genotype frequency, a newly proposed measure for genotype integrity.
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Affiliation(s)
- E K F Chan
- Cooperative Research Centre for Beef Genetic Technologies, CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, Qld 4067, Australia
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20
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Meadows JRS, Chan EKF, Kijas JW. Linkage disequilibrium compared between five populations of domestic sheep. BMC Genet 2008; 9:61. [PMID: 18826649 PMCID: PMC2572059 DOI: 10.1186/1471-2156-9-61] [Citation(s) in RCA: 57] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2008] [Accepted: 09/30/2008] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The success of genome-wide scans depends on the strength and magnitude of linkage disequilibrium (LD) present within the populations under investigation. High density SNP arrays are currently in development for the sheep genome, however little is known about the behaviour of LD in this livestock species. This study examined the behaviour of LD within five sheep populations using two LD metrics, D' and x2'. Four economically important Australian sheep flocks, three pure breeds (White Faced Suffolk, Poll Dorset, Merino) and a crossbred population (Merino x Border Leicester), along with an inbred Australian Merino museum flock were analysed. RESULTS Short range LD (0 - 5 cM) was observed in all five populations, however the persistence with increasing distance and magnitude of LD varied considerably between populations. Average LD (x2') for markers spaced up to 20 cM exceeded the non-syntenic average within the White Faced Suffolk, Poll Dorset and Macarthur Merino. LD decayed faster within the Merino and Merino x Border Leicester, with LD below or consistent with observed background levels. Using marker-marker LD as a guide to the behaviour of marker-QTL LD, estimates of minimum marker spacing were made. For a 95% probability of detecting QTL, a microsatellite marker would be required every 0.1 - 2.5 centimorgans, depending on the population used. CONCLUSION Sheep populations were selected which were inbred (Macarthur Merino), highly heterogeneous (Merino) or intermediate between these two extremes. This facilitated analysis and comparison of LD (x2') between populations. The strength and magnitude of LD was found to differ markedly between breeds and aligned closely with both observed levels of genetic diversity and expectations based on breed history. This confirmed that breed specific information is likely to be important for genome wide selection and during the design of successful genome scans where tens of thousands of markers will be required.
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Affiliation(s)
- Jennifer R S Meadows
- CSIRO Livestock Industries, Level 5 Queensland Bioscience Precinct, 306 Carmody Road, St Lucia 4067, Australia.
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21
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Reverter A, Chan EKF. Combining partial correlation and an information theory approach to the reversed engineering of gene co-expression networks. ACTA ACUST UNITED AC 2008; 24:2491-7. [PMID: 18784117 DOI: 10.1093/bioinformatics/btn482] [Citation(s) in RCA: 207] [Impact Index Per Article: 12.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
MOTIVATION We present PCIT, an algorithm for the reconstruction of gene co-expression networks (GCN) that combines the concept partial correlation coefficient with information theory to identify significant gene to gene associations defining edges in the reconstruction of GCN. The properties of PCIT are examined in the context of the topology of the reconstructed network including connectivity structure, clustering coefficient and sensitivity. RESULTS We apply PCIT to a series of simulated datasets with varying levels of complexity in terms of number of genes and experimental conditions, as well as to three real datasets. Results show that, as opposed to the constant cutoff approach commonly used in the literature, the PCIT algorithm can identify and allow for more moderate, yet not less significant, estimates of correlation (r) to still establish a connection in the GCN. We show that PCIT is more sensitive than established methods and capable of detecting functionally validated gene-gene interactions coming from absolute r values as low as 0.3. These bona fide associations, which often relate to genes with low variation in expression patterns, are beyond the detection limits of conventional fixed-threshold methods, and would be overlooked by studies relying on those methods. AVAILABILITY FORTRAN 90 source code to perform the PCIT algorithm is available as Supplementary File 1.
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Affiliation(s)
- Antonio Reverter
- CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, Brisbane, Queensland 4067, Australia.
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22
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Abstract
The view that changes to the control of gene expression rather than alterations to protein sequence are central to the evolution of organisms has become something of a truism in molecular biology. In reality, the direct evidence for this is limited, and only recently have we had the ability to look more globally at how genetic variation influences gene expression, focusing upon inter-individual variation in gene expression and using microarrays to test for differences in mRNA levels. Here, we review the scope of these experimental analyses, what they are designed to tell us about genetic variation, and what are their limitations from both a technical and a conceptual viewpoint. We conclude that while we are starting to understand the impact of this class of genetic variation upon steady-state mRNA levels, we are still far from identifying the potential phenotypic and evolutionary outcomes.
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Affiliation(s)
- Rohan B H Williams
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Randwick, NSW 2052, Australia
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Cotsapas CJ, Williams RBH, Pulvers JN, Nott DJ, Chan EKF, Cowley MJ, Little PFR. Genetic dissection of gene regulation in multiple mouse tissues. Mamm Genome 2006; 17:490-5. [PMID: 16783630 DOI: 10.1007/s00335-005-0186-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2005] [Accepted: 02/21/2006] [Indexed: 10/24/2022]
Abstract
The analysis of the influence of genetic variation on regulation of gene expression at a near-genome-wide level has become the focus of much recent interest. It is widely appreciated that many genes are expressed in a tissue-specific manner and that others are more ubiquitously expressed but relatively little is known about how genetic variation might influence these tissue patterns of gene expression. In this review we discuss what is known about the tissue specificity of the influence of genetic variation and review the challenges that we face in combining hugely parallel, microarray-based gene analysis with equally expensive genetic analysis. We conclude that the available data suggest that genetic variation is essentially tissue specific in its effects upon gene expression and this has important implications for experimental analysis.
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Affiliation(s)
- Chris J Cotsapas
- School of Biotechnology and Biomolecular Sciences, University of New South Wales, Botany Street, Sydney, NSW 2052, Australia
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