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Solano-Aguilar GI, Lakshman S, Jang S, Gupta R, Molokin A, Schroeder SG, Gillevet PM, Urban JF. The Effects of Consuming White Button Mushroom Agaricus bisporus on the Brain and Liver Metabolome Using a Targeted Metabolomic Analysis. Metabolites 2021; 11:metabo11110779. [PMID: 34822437 PMCID: PMC8625434 DOI: 10.3390/metabo11110779] [Citation(s) in RCA: 0] [Impact Index Per Article: 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: 09/21/2021] [Revised: 10/29/2021] [Accepted: 11/11/2021] [Indexed: 11/21/2022] Open
Abstract
A targeted metabolomic analysis was performed on tissues derived from pigs fed diets supplemented with white button mushrooms (WBM) to determine the effect on the liver and brain metabolome. Thirty-one pigs were fed a grower diet alone or supplemented with either three or six servings of freeze-dried WBM for six weeks. Tissue metabolomes were analyzed using targeted liquid chromatography-mass spectrometry (LC-MS) combined with chemical similarity enrichment analysis (ChemRICH) and correlated to WBM-induced changes in fecal microbiome composition. Results indicated that WBM can differentially modulate metabolites in liver, brain cortex and hippocampus of healthy pigs. Within the glycero-phospholipids, there was an increase in alkyl-acyl-phosphatidyl-cholines (PC-O 40:3) in the hippocampus of pigs fed six servings of WBM. A broader change in glycerophospholipids and sphingolipids was detected in the liver with a reduction in several lipid species in pigs fed both WBM diets but with an increase in amino acids known as precursors of neurotransmitters in the cortex of pigs fed six servings of WBM. Metabolomic changes were positively correlated with increased abundance of Cryomorphaceae, Lachnospiraceae, Flammeovirgaceae and Ruminococcaceae in the microbiome suggesting that WBM can also positively impact tissue metabolite composition.
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Affiliation(s)
- Gloria I. Solano-Aguilar
- Diet Genomics and Immunology Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA; (S.L.); (S.J.); (A.M.); (J.F.U.J.)
- Correspondence: ; Tel.: +1-301-504-8068
| | - Sukla Lakshman
- Diet Genomics and Immunology Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA; (S.L.); (S.J.); (A.M.); (J.F.U.J.)
| | - Saebyeol Jang
- Diet Genomics and Immunology Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA; (S.L.); (S.J.); (A.M.); (J.F.U.J.)
| | - Richi Gupta
- Microbiome Analysis Center, George Mason University, Science & Technology Campus, Manassas, VA 20108, USA; (R.G.); (P.M.G.)
| | - Aleksey Molokin
- Diet Genomics and Immunology Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA; (S.L.); (S.J.); (A.M.); (J.F.U.J.)
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, Beltsville Agricultural Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA;
| | - Patrick M. Gillevet
- Microbiome Analysis Center, George Mason University, Science & Technology Campus, Manassas, VA 20108, USA; (R.G.); (P.M.G.)
| | - Joseph F. Urban
- Diet Genomics and Immunology Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture Northeast Area, Beltsville, MD 20705, USA; (S.L.); (S.J.); (A.M.); (J.F.U.J.)
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2
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Zhou Y, Liu S, Hu Y, Fang L, Gao Y, Xia H, Schroeder SG, Rosen BD, Connor EE, Li CJ, Baldwin RL, Cole JB, Van Tassell CP, Yang L, Ma L, Liu GE. Comparative whole genome DNA methylation profiling across cattle tissues reveals global and tissue-specific methylation patterns. BMC Biol 2020; 18:85. [PMID: 32631327 PMCID: PMC7339546 DOI: 10.1186/s12915-020-00793-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [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: 03/04/2020] [Accepted: 05/12/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Efforts to improve animal health, and understand genetic bases for production, may benefit from a comprehensive analysis of animal genomes and epigenomes. Although DNA methylation has been well studied in humans and other model species, its distribution patterns and regulatory impacts in cattle are still largely unknown. Here, we present the largest collection of cattle DNA methylation epigenomic data to date. RESULTS Using Holstein cattle, we generated 29 whole genome bisulfite sequencing (WGBS) datasets for 16 tissues, 47 corresponding RNA-seq datasets, and 2 whole genome sequencing datasets. We did read mapping and DNA methylation calling based on two different cattle assemblies, demonstrating the high quality of the long-read-based assembly markedly improved DNA methylation results. We observed large differences across cattle tissues in the methylation patterns of global CpG sites, partially methylated domains (PMDs), hypomethylated regions (HMRs), CG islands (CGIs), and common repeats. We detected that each tissue had a distinct set of PMDs, which showed tissue-specific patterns. Similar to human PMD, cattle PMDs were often linked to a general decrease of gene expression and a decrease in active histone marks and related to long-range chromatin organizations, like topologically associated domains (TADs). We tested a classification of the HMRs based on their distributions relative to transcription start sites (TSSs) and detected tissue-specific TSS-HMRs and genes that showed strong tissue effects. When performing cross-species comparisons of paired genes (two opposite strand genes with their TSS located in the same HMR), we found out they were more consistently co-expressed among human, mouse, sheep, goat, yak, pig, and chicken, but showed lower consistent ratios in more divergent species. We further used these WGBS data to detect 50,023 experimentally supported CGIs across bovine tissues and found that they might function as a guard against C-to-T mutations for TSS-HMRs. Although common repeats were often heavily methylated, some young Bov-A2 repeats were hypomethylated in sperm and could affect the promoter structures by exposing potential transcription factor binding sites. CONCLUSIONS This study provides a comprehensive resource for bovine epigenomic research and enables new discoveries about DNA methylation and its role in complex traits.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
- National Engineering Laboratory for Animal Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, College of Animal Science and Technology, China Agricultural University, Beijing, 100193 China
| | - Yan Hu
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Lingzhao Fang
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Han Xia
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Erin E. Connor
- Department of Animal and Food Sciences, University of Delaware, Newark, DE 19716 USA
| | - Cong-jun Li
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Ransom L. Baldwin
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - John B. Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction of Ministry of Education & College of Animal Science and Technology, Huazhong Agricultural University, Wuhan, 430070 China
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742 USA
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705 USA
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3
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Warr A, Affara N, Aken B, Beiki H, Bickhart DM, Billis K, Chow W, Eory L, Finlayson HA, Flicek P, Girón CG, Griffin DK, Hall R, Hannum G, Hourlier T, Howe K, Hume DA, Izuogu O, Kim K, Koren S, Liu H, Manchanda N, Martin FJ, Nonneman DJ, O'Connor RE, Phillippy AM, Rohrer GA, Rosen BD, Rund LA, Sargent CA, Schook LB, Schroeder SG, Schwartz AS, Skinner BM, Talbot R, Tseng E, Tuggle CK, Watson M, Smith TPL, Archibald AL. An improved pig reference genome sequence to enable pig genetics and genomics research. Gigascience 2020; 9:5858065. [PMID: 32543654 PMCID: PMC7448572 DOI: 10.1093/gigascience/giaa051] [Citation(s) in RCA: 140] [Impact Index Per Article: 35.0] [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: 10/28/2019] [Revised: 03/12/2020] [Accepted: 04/22/2020] [Indexed: 01/05/2023] Open
Abstract
Background The domestic pig (Sus scrofa) is important both as a food source and
as a biomedical model given its similarity in size, anatomy, physiology, metabolism,
pathology, and pharmacology to humans. The draft reference genome (Sscrofa10.2) of a
purebred Duroc female pig established using older clone-based sequencing methods was
incomplete, and unresolved redundancies, short-range order and orientation errors, and
associated misassembled genes limited its utility. Results We present 2 annotated highly contiguous chromosome-level genome assemblies created
with more recent long-read technologies and a whole-genome shotgun strategy, 1 for the
same Duroc female (Sscrofa11.1) and 1 for an outbred, composite-breed male (USMARCv1.0).
Both assemblies are of substantially higher (>90-fold) continuity and accuracy than
Sscrofa10.2. Conclusions These highly contiguous assemblies plus annotation of a further 11 short-read
assemblies provide an unprecedented view of the genetic make-up of this important
agricultural and biomedical model species. We propose that the improved Duroc assembly
(Sscrofa11.1) become the reference genome for genomic research in pigs.
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Affiliation(s)
- Amanda Warr
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Nabeel Affara
- Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK
| | - Bronwen Aken
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Hamid Beiki
- Department of Animal Science, 2255 Kildee Hall, Iowa State University, Ames, IA 50011-3150, USA
| | - Derek M Bickhart
- Dairy Forage Research Center, USDA-ARS, 1925 Linden Drive, Madison, WI 53706, USA
| | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - William Chow
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - Lel Eory
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Heather A Finlayson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Carlos G Girón
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Darren K Griffin
- School of Biosciences, University of Kent, Giles Lane, Canterbury CT2 7NJ, UK
| | - Richard Hall
- Pacific Biosciences, 1305 O'Brien Drive, Menlo Park, CA 94025, USA
| | | | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Kerstin Howe
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge CB10 1SA, UK
| | - David A Hume
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK.,Mater Research Institute-University of Queensland, Translational Research Institute, Brisbane QLD 4104, Australia
| | - Osagie Izuogu
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Kristi Kim
- Pacific Biosciences, 1305 O'Brien Drive, Menlo Park, CA 94025, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Haibou Liu
- Department of Animal Science, 2255 Kildee Hall, Iowa State University, Ames, IA 50011-3150, USA
| | - Nancy Manchanda
- Bioinformatics and Computational Biology Program, Iowa State University, 2014 Molecular Biology Building, Ames, IA 50011, USA
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton CB10 1SD, UK
| | - Dan J Nonneman
- USDA-ARS U.S. Meat Animal Research Center, 844 Road 313, Clay Center, NE 68933, USA
| | - Rebecca E O'Connor
- School of Biosciences, University of Kent, Giles Lane, Canterbury CT2 7NJ, UK
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Gary A Rohrer
- USDA-ARS U.S. Meat Animal Research Center, 844 Road 313, Clay Center, NE 68933, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Avenue, Beltsville, MD 20705-2350, USA
| | - Laurie A Rund
- Department of Animal Sciences, University of Illinois, 1201 West Gregory Drive, Urbana, IL 61801, USA
| | - Carole A Sargent
- Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK
| | - Lawrence B Schook
- Department of Animal Sciences, University of Illinois, 1201 West Gregory Drive, Urbana, IL 61801, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Avenue, Beltsville, MD 20705-2350, USA
| | | | - Ben M Skinner
- Department of Pathology, University of Cambridge, Tennis Court Road, Cambridge CB2 1QP, UK
| | - Richard Talbot
- Edinburgh Genomics, University of Edinburgh, Charlotte Auerbach Road, Edinburgh EH9 3FL, UK
| | - Elizabeth Tseng
- Pacific Biosciences, 1305 O'Brien Drive, Menlo Park, CA 94025, USA
| | - Christopher K Tuggle
- Department of Animal Science, 2255 Kildee Hall, Iowa State University, Ames, IA 50011-3150, USA.,Bioinformatics and Computational Biology Program, Iowa State University, 2014 Molecular Biology Building, Ames, IA 50011, USA
| | - Mick Watson
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
| | - Timothy P L Smith
- USDA-ARS U.S. Meat Animal Research Center, 844 Road 313, Clay Center, NE 68933, USA
| | - Alan L Archibald
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Easter Bush Campus, Midlothian EH25 9RG, UK
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4
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Fang L, Cai W, Liu S, Canela-Xandri O, Gao Y, Jiang J, Rawlik K, Li B, Schroeder SG, Rosen BD, Li CJ, Sonstegard TS, Alexander LJ, Van Tassell CP, VanRaden PM, Cole JB, Yu Y, Zhang S, Tenesa A, Ma L, Liu GE. Comprehensive analyses of 723 transcriptomes enhance genetic and biological interpretations for complex traits in cattle. Genome Res 2020; 30:790-801. [PMID: 32424068 PMCID: PMC7263193 DOI: 10.1101/gr.250704.119] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Accepted: 05/01/2020] [Indexed: 12/13/2022]
Abstract
By uniformly analyzing 723 RNA-seq data from 91 tissues and cell types, we built a comprehensive gene atlas and studied tissue specificity of genes in cattle. We demonstrated that tissue-specific genes significantly reflected the tissue-relevant biology, showing distinct promoter methylation and evolution patterns (e.g., brain-specific genes evolve slowest, whereas testis-specific genes evolve fastest). Through integrative analyses of those tissue-specific genes with large-scale genome-wide association studies, we detected relevant tissues/cell types and candidate genes for 45 economically important traits in cattle, including blood/immune system (e.g., CCDC88C) for male fertility, brain (e.g., TRIM46 and RAB6A) for milk production, and multiple growth-related tissues (e.g., FGF6 and CCND2) for body conformation. We validated these findings by using epigenomic data across major somatic tissues and sperm. Collectively, our findings provided novel insights into the genetic and biological mechanisms underlying complex traits in cattle, and our transcriptome atlas can serve as a primary source for biological interpretation, functional validation, studies of adaptive evolution, and genomic improvement in livestock.
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Affiliation(s)
- Lingzhao Fang
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Wentao Cai
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Oriol Canela-Xandri
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Yahui Gao
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Jicai Jiang
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - Konrad Rawlik
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
| | - Bingjie Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Cong-Jun Li
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | | | - Leeson J Alexander
- Fort Keogh Livestock and Range Research Laboratory, Agricultural Research Service, USDA, Miles City, Montana 59301, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Paul M VanRaden
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
| | - Ying Yu
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Shengli Zhang
- College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Albert Tenesa
- The Roslin Institute, Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Midlothian EH25 9RG, United Kingdom
- Medical Research Council Human Genetics Unit at the Medical Research Council Institute of Genetics and Molecular Medicine, The University of Edinburgh, Edinburgh EH4 2XU, United Kingdom
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland 20742, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Henry A. Wallace Beltsville Agricultural Research Center, Agricultural Research Service, USDA, Beltsville, Maryland 20705, USA
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5
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Rosen BD, Bickhart DM, Schnabel RD, Koren S, Elsik CG, Tseng E, Rowan TN, Low WY, Zimin A, Couldrey C, Hall R, Li W, Rhie A, Ghurye J, McKay SD, Thibaud-Nissen F, Hoffman J, Murdoch BM, Snelling WM, McDaneld TG, Hammond JA, Schwartz JC, Nandolo W, Hagen DE, Dreischer C, Schultheiss SJ, Schroeder SG, Phillippy AM, Cole JB, Van Tassell CP, Liu G, Smith TPL, Medrano JF. De novo assembly of the cattle reference genome with single-molecule sequencing. Gigascience 2020; 9:5810242. [PMID: 32191811 PMCID: PMC7081964 DOI: 10.1093/gigascience/giaa021] [Citation(s) in RCA: 299] [Impact Index Per Article: 74.8] [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: 09/24/2019] [Revised: 01/31/2020] [Accepted: 02/14/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. RESULTS We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. CONCLUSIONS We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.
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Affiliation(s)
- Benjamin D Rosen
- USDA-ARS, Beltsville, MD, 20705-2350 , Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Ave, Beltsville, MD 20705-2350, USA
| | - Derek M Bickhart
- Dairy Forage Research Center, USDA-ARS, 1925 Linden Drive, Madison, WI, 53706, USA
| | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, 162 Animal Science Research Center, Columbia, MO 65211, USA
| | - Sergey Koren
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Christine G Elsik
- Division of Animal Sciences, University of Missouri, 162 Animal Science Research Center, Columbia, MO 65211, USA
| | - Elizabeth Tseng
- Pacific Biosciences, 1305 O'Brien Drive, Menlo Park, CA 94025, USA
| | - Troy N Rowan
- Division of Animal Sciences, University of Missouri, 162 Animal Science Research Center, Columbia, MO 65211, USA
| | - Wai Y Low
- The Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA 5371, Australia
| | - Aleksey Zimin
- Johns Hopkins University, Welch Library of Medicine, Ste 105, 1900 E. Monument St., Baltimore, MD 21205, USA
| | - Christine Couldrey
- Livestock Improvement Corporation, Private Bag 3016, Hamilton 3240, New Zealand
| | - Richard Hall
- Pacific Biosciences, 1305 O'Brien Drive, Menlo Park, CA 94025, USA
| | - Wenli Li
- Dairy Forage Research Center, USDA-ARS, 1925 Linden Drive, Madison, WI, 53706, USA
| | - Arang Rhie
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - Jay Ghurye
- Department of Computer Science, University of Maryland, 8125 Paint Branch Drive, College Park, MD 20742 USA
| | - Stephanie D McKay
- Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT 05405, USA
| | - Françoise Thibaud-Nissen
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Jinna Hoffman
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Bethesda, MD 20894, USA
| | - Brenda M Murdoch
- Department of Animal and Veterinary Science, University of Idaho, 875 Perimeter Drive MS 2330, Moscow, ID 83844-2330, USA
| | - Warren M Snelling
- U.S. Meat Animal Research Center, USDA-ARS, 844 Road 313, Clay Center, NE 68933, USA
| | - Tara G McDaneld
- U.S. Meat Animal Research Center, USDA-ARS, 844 Road 313, Clay Center, NE 68933, USA
| | | | | | - Wilson Nandolo
- Division of Livestock Sciences, University of Natural Resources and Life Sciences, Gregor Mendel str. 33, A-1180, Vienna, Austria.,Animal Science Department, Lilongwe University of Agriculture and Natural Resources, P.O. Box 219, Lilongwe, Malawi
| | - Darren E Hagen
- Department of Animal and Food Sciences, Oklahoma State University, 101 Animal Science Building, Stillwater, OK 74078, USA
| | | | | | - Steven G Schroeder
- USDA-ARS, Beltsville, MD, 20705-2350 , Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Ave, Beltsville, MD 20705-2350, USA
| | - Adam M Phillippy
- Genome Informatics Section, Computational and Statistical Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 9000 Rockville Pike, Bethesda, MD 20892, USA
| | - John B Cole
- USDA-ARS, Beltsville, MD, 20705-2350 , Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Ave, Beltsville, MD 20705-2350, USA
| | - Curtis P Van Tassell
- USDA-ARS, Beltsville, MD, 20705-2350 , Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Ave, Beltsville, MD 20705-2350, USA
| | - George Liu
- USDA-ARS, Beltsville, MD, 20705-2350 , Animal Genomics and Improvement Laboratory, USDA-ARS, 10300 Baltimore Ave, Beltsville, MD 20705-2350, USA
| | - Timothy P L Smith
- U.S. Meat Animal Research Center, USDA-ARS, 844 Road 313, Clay Center, NE 68933, USA
| | - Juan F Medrano
- Department of Animal Science, University of California, Davis, One Shields Avenue, Davis, CA 95616, USA
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6
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Fang L, Zhou Y, Liu S, Jiang J, Bickhart DM, Null DJ, Li B, Schroeder SG, Rosen BD, Cole JB, Van Tassell CP, Ma L, Liu GE. Integrating Signals from Sperm Methylome Analysis and Genome-Wide Association Study for a Better Understanding of Male Fertility in Cattle. Epigenomes 2019; 3:epigenomes3020010. [PMID: 34968233 PMCID: PMC8594688 DOI: 10.3390/epigenomes3020010] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [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: 03/27/2019] [Revised: 05/03/2019] [Accepted: 05/11/2019] [Indexed: 01/18/2023] Open
Abstract
Decreased male fertility is a big concern in both human society and the livestock industry. Sperm DNA methylation is commonly believed to be associated with male fertility. However, due to the lack of accurate male fertility records (i.e., limited mating times), few studies have investigated the comprehensive impacts of sperm DNA methylation on male fertility in mammals. In this study, we generated 10 sperm DNA methylomes and performed a preliminary correlation analysis between signals from sperm DNA methylation and signals from large-scale (n = 27,214) genome-wide association studies (GWAS) of 35 complex traits (including 12 male fertility-related traits). We detected genomic regions, which experienced DNA methylation alterations in sperm and were associated with aging and extreme fertility phenotypes (e.g., sire-conception rate or SCR). In dynamic hypomethylated regions (HMRs) and partially methylated domains (PMDs), we found genes (e.g., HOX gene clusters and microRNAs) that were involved in the embryonic development. We demonstrated that genomic regions, which gained rather than lost methylations during aging, and in animals with low SCR were significantly and selectively enriched for GWAS signals of male fertility traits. Our study discovered 16 genes as the potential candidate markers for male fertility, including SAMD5 and PDE5A. Collectively, this initial effort supported a hypothesis that sperm DNA methylation may contribute to male fertility in cattle and revealed the usefulness of functional annotations in enhancing biological interpretation and genomic prediction for complex traits and diseases.
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Affiliation(s)
- Lingzhao Fang
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, Wuhan 430070, China
| | - Shuli Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Jicai Jiang
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Derek M. Bickhart
- Dairy Forage Research Center, Agricultural Research Service, USDA, Madison, WI 53718, USA
| | - Daniel J. Null
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Bingjie Li
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Benjamin D. Rosen
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - John B. Cole
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Li Ma
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
- Correspondence: (L.M.); (G.E.L.); Tel.: +1-301-405-1389 (L.M.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (G.E.L.)
| | - George E. Liu
- Animal Genomics and Improvement Laboratory, BARC, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
- Correspondence: (L.M.); (G.E.L.); Tel.: +1-301-405-1389 (L.M.); +1-301-504-9843 (G.E.L.); Fax: +1-301-504-8414 (G.E.L.)
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7
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Fang L, Zhou Y, Liu S, Jiang J, Bickhart DM, Null DJ, Li B, Schroeder SG, Rosen BD, Cole JB, Van Tassell CP, Ma L, Liu GE. Comparative analyses of sperm DNA methylomes among human, mouse and cattle provide insights into epigenomic evolution and complex traits. Epigenetics 2019; 14:260-276. [PMID: 30810461 PMCID: PMC6557555 DOI: 10.1080/15592294.2019.1582217] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [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] [Indexed: 12/26/2022] Open
Abstract
Sperm DNA methylation is crucial for fertility and viability of offspring but epigenome evolution in mammals is largely understudied. By comparing sperm DNA methylomes and large-scale genome-wide association study (GWAS) signals between human and cattle, we aimed to examine the DNA methylome evolution and its associations with complex phenotypes in mammals. Our analysis revealed that genes with conserved non-methylated promoters (e.g., ANKS1A and WNT7A) among human and cattle were involved in common system and embryo development, and enriched for GWAS signals of body conformation traits in both species, while genes with conserved hypermethylated promoters (e.g., TCAP and CD80) were engaged in immune responses and highlighted by immune-related traits. On the other hand, genes with human-specific hypomethylated promoters (e.g., FOXP2 and HYDIN) were engaged in neuron system development and enriched for GWAS signals of brain-related traits, while genes with cattle-specific hypomethylated promoters (e.g., LDHB and DGAT2) mainly participated in lipid storage and metabolism. We validated our findings using sperm-retained nucleosome, preimplantation transcriptome, and adult tissue transcriptome data, as well as sequence evolutionary features, including motif binding sites, mutation rates, recombination rates and evolution signatures. In conclusion, our results demonstrate important roles of epigenome evolution in shaping the genetic architecture underlying complex phenotypes, hence enhance signal prioritization in GWAS and provide valuable information for human neurological disorders and livestock genetic improvement.
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Affiliation(s)
- Lingzhao Fang
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA.,b Department of Animal and Avian Sciences , University of Maryland , College Park , MD , USA
| | - Yang Zhou
- c Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China , Huazhong Agricultural University , Wuhan , Hubei , China
| | - Shuli Liu
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA.,d Key Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture & National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology , China Agricultural University , Beijing , China
| | - Jicai Jiang
- b Department of Animal and Avian Sciences , University of Maryland , College Park , MD , USA
| | - Derek M Bickhart
- e Dairy Forage Research Center , Agricultural Research Service, USDA , Madison , WI , USA
| | - Daniel J Null
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - Bingjie Li
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - Steven G Schroeder
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - Benjamin D Rosen
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - John B Cole
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - Curtis P Van Tassell
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
| | - Li Ma
- b Department of Animal and Avian Sciences , University of Maryland , College Park , MD , USA
| | - George E Liu
- a Animal Genomics and Improvement Laboratory, BARC , Agricultural Research Service, USDA , Beltsville , MD , USA
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8
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Liu S, Kang X, Catacchio CR, Liu M, Fang L, Schroeder SG, Li W, Rosen BD, Iamartino D, Iannuzzi L, Sonstegard TS, Van Tassell CP, Ventura M, Low WY, Williams JL, Bickhart DM, Liu GE. Computational detection and experimental validation of segmental duplications and associated copy number variations in water buffalo ( Bubalus bubalis ). Funct Integr Genomics 2019; 19:409-419. [PMID: 30734132 DOI: 10.1007/s10142-019-00657-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 12/13/2018] [Accepted: 01/09/2019] [Indexed: 01/25/2023]
Abstract
Duplicated sequences are an important source of gene evolution and structural variation within mammalian genomes. Using a read depth approach based on next-generation sequencing, we performed a genome-wide analysis of segmental duplications (SDs) and associated copy number variations (CNVs) in the water buffalo (Bubalus bubalis). By aligning short reads of Olimpia (the reference water buffalo) to the UMD3.1 cattle genome, we identified 1,038 segmental duplications comprising 44.6 Mb (equivalent to ~1.73% of the cattle genome) of the autosomal and X chromosomal sequence in the buffalo genome. We experimentally validated 70.3% (71/101) of these duplications using fluorescent in situ hybridization. We also detected a total of 1,344 CNV regions across 14 additional water buffaloes, amounting to 59.8 Mb of variable sequence or the equivalent of 2.2% of the cattle genome. The CNV regions overlap 1,245 genes that are significantly enriched for specific biological functions including immune response, oxygen transport, sensory system and signal transduction. Additionally, we performed array Comparative Genomic Hybridization (aCGH) experiments using the 14 water buffaloes as test samples and Olimpia as the reference. Using a linear regression model, a high Pearson correlation (r = 0.781) was observed between the log2 ratios between copy number estimates and the log2 ratios of aCGH probes. We further designed Quantitative PCR assays to confirm CNV regions within or near annotated genes and found 74.2% agreement with our CNV predictions. These results confirm sub-chromosome-scale structural rearrangements present in the cattle and water buffalo. The information on genome variation that will be of value for evolutionary and phenotypic studies, and may be useful for selective breeding of both species.
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Affiliation(s)
- Shuli Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Xiaolong Kang
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Agriculture, Ningxia University, Yinchuan, 750021, China
| | | | - Mei Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- College of Animal Science and Technology, Shaanxi Key Laboratory of Agricultural Molecular Biology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - Lingzhao Fang
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
- Department of Animal and Avian Sciences, University of Maryland, College Park, Maryland, 20742, USA
| | - Steven G Schroeder
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Wenli Li
- The Cell Wall Utilization and Biology Laboratory, US Dairy Forage Research Center, USDA, ARS, Madison, WI 53706, USA
| | - Benjamin D Rosen
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Daniela Iamartino
- AIA-LGS, Associazione Italiana Allevatori - Laboratorio Genetica e Servizi, Via Bergamo 292, 26100 (CR), Cremona, Italy
- Parco Tecnologico Padano, Via Einstein, Polo Universitario, 26900, Lodi, Italy
| | - Leopoldo Iannuzzi
- Laboratory of Animal Cytogenetics and Gene Mapping, Nationa Research Council (CNR), ISPAAM, Via Argine 1085, 80147, Naples, Italy
| | | | - Curtis P Van Tassell
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA
| | - Mario Ventura
- Department of Biology, University of Bari, 70126, Bari, Italy
| | - Wai Yee Low
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - John L Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, 5371, Australia
| | - Derek M Bickhart
- The Cell Wall Utilization and Biology Laboratory, US Dairy Forage Research Center, USDA, ARS, Madison, WI 53706, USA.
| | - George E Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, Maryland, 20705, USA.
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9
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Zhou Y, Connor EE, Bickhart DM, Li C, Baldwin RL, Schroeder SG, Rosen BD, Yang L, Van Tassell CP, Liu GE. Comparative whole genome DNA methylation profiling of cattle sperm and somatic tissues reveals striking hypomethylated patterns in sperm. Gigascience 2018; 7:4965117. [PMID: 29635292 PMCID: PMC5928411 DOI: 10.1093/gigascience/giy039] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [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: 11/07/2017] [Accepted: 03/28/2018] [Indexed: 12/21/2022] Open
Abstract
Background Although sperm DNA methylation has been studied in humans and other species, its status in cattle is largely unknown. Results Using whole-genome bisulfite sequencing (WGBS), we profiled the DNA methylome of cattle sperm through comparison with three somatic tissues (mammary gland, brain, and blood). Large differences between cattle sperm and somatic cells were observed in the methylation patterns of global CpGs, pericentromeric satellites, partially methylated domains (PMDs), hypomethylated regions (HMRs), and common repeats. As expected, we observed low methylation in the promoter regions and high methylation in the bodies of active genes. We detected selective hypomethylation of megabase domains of centromeric satellite clusters, which may be related to chromosome segregation during meiosis and their rapid transcriptional activation upon fertilization. We found more PMDs in sperm cells than in somatic cells and identified meiosis-related genes such asKIF2B and REPIN1, which are hypomethylated in sperm but hypermethylated in somatic cells. In addition to the common HMRs around gene promoters, which showed substantial differences between sperm and somatic cells, the sperm-specific HMRs also targeted to distinct spermatogenesis-related genes, including BOLL, MAEL, ASZ1, SYCP3, CTCFL, MND1, SPATA22, PLD6, DDX4, RBBP8, FKBP6, and SYCE1. Although common repeats were heavily methylated in both sperm and somatic cells, some young Bov-A2 repeats, which belong to the SINE family, were hypomethylated in sperm and could affect the promoter structures by introducing new regulatory elements. Conclusions Our study provides a comprehensive resource for bovine sperm epigenomic research and enables new discoveries about DNA methylation and its role in male fertility.
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Affiliation(s)
- Yang Zhou
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, Wuhan, Hubei, 430070, China.,Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Erin E Connor
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Derek M Bickhart
- The Cell Wall Utilization and Biology Laboratory, US Department of Agriculture, Agriculture Research Service, Madison, WI, 53706, USA
| | - Congjun Li
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Ransom L Baldwin
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - Liguo Yang
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, Wuhan, Hubei, 430070, China
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, US Department of Agriculture, Agriculture Research Service, Beltsville, MD 20705, USA
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10
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Zhou Y, Connor EE, Wiggans GR, Lu Y, Tempelman RJ, Schroeder SG, Chen H, Liu GE. Genome-wide copy number variant analysis reveals variants associated with 10 diverse production traits in Holstein cattle. BMC Genomics 2018; 19:314. [PMID: 29716533 PMCID: PMC5930521 DOI: 10.1186/s12864-018-4699-5] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [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: 05/17/2017] [Accepted: 04/18/2018] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Copy number variation (CNV) is an important type of genetic variation contributing to phenotypic differences among mammals and may serve as an alternative molecular marker to single nucleotide polymorphism (SNP) for genome-wide association study (GWAS). Recently, GWAS analysis using CNV has been applied in livestock, although few studies have focused on Holstein cattle. RESULTS We describe 191 CNV detected using intensity data from over 700,000 SNP genotypes generated with the BovineHD Genotyping BeadChip (Illumina, San Diego, CA) in 528 Holstein cows. The CNV were used for GWAS analysis of 10 important production traits of 473 cattle related to feed intake, milk quality, and female fertility, as well as 2 composite traits of net merit and productive life. In total, we detected 57 CNV associated (P < 0.05 after false discovery rate correction) with at least one of the 10 phenotypes. Focusing on feed efficiency and intake-related phenotypes of residual feed intake and dry matter intake, we detected a single CNV associated with both traits which overlaps a predicted olfactory receptor gene OR2A2 (LOC787786). Additionally, 2 CNV within the RXFP4 (relaxin/insulin like family peptide receptor 4) and 2 additional olfactory receptor gene regions, respectively, were associated with residual feed intake. The RXFP4 gene encodes a receptor for an orexigenic peptide, insulin-like peptide 5 produced by intestinal L cells, which is expressed by enteric neurons. Olfactory receptors are critical for transmitting the effects of odorants, contributing to the sense of smell, and have been implicated in participating in appetite regulation. CONCLUSIONS Our results identify CNV for genomic evaluation in Holstein cattle, and provide candidate genes, such as RXFP4, contributing to variation in feed efficiency and feed intake-related traits. These results indicate potential novel targets for manipulating feed intake-related traits of livestock.
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Affiliation(s)
- Yang Zhou
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA.,Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China.,Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Education Ministry of China, Huazhong Agricultural University, Wuhan, 430070, Hubei, China
| | - Erin E Connor
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - George R Wiggans
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - Yongfang Lu
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Robert J Tempelman
- Department of Animal Science, Michigan State University, East Lansing, MI, 48824, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA
| | - Hong Chen
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, Shaanxi, China
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, 10300 Baltimore Avenue, Bldg. 306, BARC-East, Beltsville, MD, 20705, USA.
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11
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Porto-Neto LR, Bickhart DM, Landaeta-Hernandez AJ, Utsunomiya YT, Pagan M, Jimenez E, Hansen PJ, Dikmen S, Schroeder SG, Kim ES, Sun J, Crespo E, Amati N, Cole JB, Null DJ, Garcia JF, Reverter A, Barendse W, Sonstegard TS. Convergent Evolution of Slick Coat in Cattle through Truncation Mutations in the Prolactin Receptor. Front Genet 2018. [PMID: 29527221 PMCID: PMC5829098 DOI: 10.3389/fgene.2018.00057] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.8] [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] [Indexed: 12/12/2022] Open
Abstract
Evolutionary adaptations are occasionally convergent solutions to the same problem. A mutation contributing to a heat tolerance adaptation in Senepol cattle, a New World breed of mostly European descent, results in the distinct phenotype known as slick, where an animal has shorter hair and lower follicle density across its coat than wild type animals. The causal variant, located in the 11th exon of prolactin receptor, produces a frameshift that results in a truncated protein. However, this mutation does not explain all cases of slick coats found in criollo breeds. Here, we obtained genome sequences from slick cattle of a geographically distinct criollo breed, namely Limonero, whose ancestors were originally brought to the Americas by the Spanish. These data were used to identify new causal alleles in the 11th exon of the prolactin receptor, two of which also encode shortened proteins that remove a highly conserved tyrosine residue. These new mutations explained almost 90% of investigated cases of animals that had slick coats, but which also did not carry the Senepol slick allele. These results demonstrate convergent evolution at the molecular level in a trait important to the adaptation of an animal to its environment.
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Affiliation(s)
| | - Derek M Bickhart
- US Dairy Forage Research Center, United States Department of Agriculture, Agricultural Research Service, Madison, WI, United States
| | - Antonio J Landaeta-Hernandez
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Yuri T Utsunomiya
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University, São Paulo, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, Brazil
| | - Melvin Pagan
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, Puerto Rico
| | - Esbal Jimenez
- Department of Animal Science, University of Puerto Rico-Mayagüez, Mayagüez, Puerto Rico
| | - Peter J Hansen
- Department of Animal Sciences, University of Florida, Gainesville, FL, United States
| | - Serdal Dikmen
- Department of Animal Science, Faculty of Veterinary Medicine, Uludağ University, Bursa, Turkey
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Eui-Soo Kim
- Recombinetics, Inc., Saint Paul, MN, United States
| | - Jiajie Sun
- College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Edward Crespo
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - Norman Amati
- Unidad de Investigaciones Zootécnicas, Facultad de Ciencias Veterinarias, Universidad del Zulia, Maracaibo, Venezuela
| | - John B Cole
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Daniel J Null
- Animal Genomics and Improvement Laboratory, United States Department of Agriculture, Agricultural Research Service, Beltsville, MD, United States
| | - Jose F Garcia
- Department of Preventive Veterinary Medicine and Animal Reproduction, School of Agricultural and Veterinarian Sciences, São Paulo State University, São Paulo, Brazil.,International Atomic Energy Agency, Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, Brazil.,Department of Support, Production and Animal Health, School of Veterinary Medicine, São Paulo State University, São Paulo, Brazil
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12
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Iamartino D, Nicolazzi EL, Van Tassell CP, Reecy JM, Fritz-Waters ER, Koltes JE, Biffani S, Sonstegard TS, Schroeder SG, Ajmone-Marsan P, Negrini R, Pasquariello R, Ramelli P, Coletta A, Garcia JF, Ali A, Ramunno L, Cosenza G, de Oliveira DAA, Drummond MG, Bastianetto E, Davassi A, Pirani A, Brew F, Williams JL. Design and validation of a 90K SNP genotyping assay for the water buffalo (Bubalus bubalis). PLoS One 2017; 12:e0185220. [PMID: 28981529 PMCID: PMC5628821 DOI: 10.1371/journal.pone.0185220] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2016] [Accepted: 09/10/2017] [Indexed: 11/28/2022] Open
Abstract
Background The availability of the bovine genome sequence and SNP panels has improved various genomic analyses, from exploring genetic diversity to aiding genetic selection. However, few of the SNP on the bovine chips are polymorphic in buffalo, therefore a panel of single nucleotide DNA markers exclusive for buffalo was necessary for molecular genetic analyses and to develop genomic selection approaches for water buffalo. The creation of a 90K SNP panel for river buffalo and testing in a genome wide association study for milk production is described here. Methods The genomes of 73 buffaloes of 4 different breeds were sequenced and aligned against the bovine genome, which facilitated the identification of 22 million of sequence variants among the buffalo genomes. Based on frequencies of variants within and among buffalo breeds, and their distribution across the genome, inferred from the bovine genome sequence, 90,000 putative single nucleotide polymorphisms were selected to create an Axiom® Buffalo Genotyping Array 90K. Results This 90K “SNP-Chip” was tested in several river buffalo populations and found to have ∼70% high quality and polymorphic SNPs. Of the 90K SNPs about 24K were also found to be polymorphic in swamp buffalo. The SNP chip was used to investigate the structure of buffalo populations, and could distinguish buffalo from different farms. A Genome Wide Association Study identified genomic regions on 5 chromosomes putatively involved in milk production. Conclusion The 90K buffalo SNP chip described here is suitable for the analysis of the genomes of river buffalo breeds, and could be used for genetic diversity studies and potentially as a starting point for genome-assisted selection programmes. This SNP Chip could also be used to analyse swamp buffalo, but many loci are not informative and creation of a revised SNP set specific for swamp buffalo would be advised.
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Affiliation(s)
- Daniela Iamartino
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Fondazione Parco Tecnologico Padano, Lodi, Italy
- * E-mail:
| | | | - Curtis P. Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - James M. Reecy
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - Eric R. Fritz-Waters
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | - James E. Koltes
- Department of Animal Science, Iowa State University, Ames, IA, United States of America
| | | | - Tad S. Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Steven G. Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Beltsville, Maryland, United States of America
| | - Paolo Ajmone-Marsan
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | - Riccardo Negrini
- AIA-LGS Associazione Italiana Allevatori–Laboratorio Genetica e Servizi, Cremona, Italy
- Institute of Zootechnics, Università Cattolica del S. Cuore, Piacenza, Italy
| | | | | | - Angelo Coletta
- ANASB-Associazione Nazionale Allevatori Specie Bufalina, Centurano—Caserta, Italy
| | - José F. Garcia
- Universidade Estadual Paulista (UNESP), Câmpus de Araçatuba, Sao Paulo, Brazil
| | - Ahmad Ali
- COMSATS Institute of Information Technology, Sahiwal, Pakistan
| | - Luigi Ramunno
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | - Gianfranco Cosenza
- Dipartimento di Scienze Zootecniche ed Ispezione degli Alimenti, Facoltà di Agraria, Università degli Studi di Napoli Federico II, Portici (NA), Italy
| | | | | | | | | | - Ali Pirani
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - Fiona Brew
- Affymetrix UK Ltd, High Wycombe, United Kingdom
| | - John L. Williams
- Davies Research Centre, School of Animal and Veterinary Sciences, University of Adelaide, Roseworthy, SA, Australia
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13
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Zhou Y, Xu L, Bickhart DM, Abdel Hay EH, Schroeder SG, Connor EE, Alexander LJ, Sonstegard TS, Van Tassell CP, Chen H, Liu GE. Reduced representation bisulphite sequencing of ten bovine somatic tissues reveals DNA methylation patterns and their impacts on gene expression. BMC Genomics 2016; 17:779. [PMID: 27716143 PMCID: PMC5053184 DOI: 10.1186/s12864-016-3116-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [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: 02/16/2016] [Accepted: 09/23/2016] [Indexed: 01/16/2023] Open
Abstract
Background As a major epigenetic component, DNA methylation plays important functions in individual development and various diseases. DNA methylation has been well studied in human and model organisms, but only limited data exist in economically important animals like cattle. Results Using reduced representation bisulphite sequencing (RRBS), we obtained single-base-resolution maps of bovine DNA methylation from ten somatic tissues. In total, we evaluated 1,868,049 cytosines in CG-enriched regions. While we found slightly low methylation levels (29.87 to 38.06 %) in cattle, the methylation contexts (CGs and non-CGs) of cattle showed similar methylation patterns to other species. Non-CG methylation was detected but methylation levels in somatic tissues were significantly lower than in pluripotent cells. To study the potential function of the methylation, we detected 10,794 differentially methylated cytosines (DMCs) and 836 differentially methylated CG islands (DMIs). Further analyses in the same tissues revealed many DMCs (including non-CGs) and DMIs, which were highly correlated with the expression of genes involved in tissue development. Conclusions In summary, our study provides a baseline dataset and essential information for DNA methylation profiles of cattle. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-3116-1) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Yang Zhou
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.,Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Lingyang Xu
- Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, People's Republic of China
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - El Hamidi Abdel Hay
- USDA Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT, 59301, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Erin E Connor
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Leeson J Alexander
- USDA Agricultural Research Service, Fort Keogh Livestock and Range Research Laboratory, Miles City, MT, 59301, USA
| | | | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA
| | - Hong Chen
- Shaanxi Key Laboratory of Agricultural Molecular Biology, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, 712100, People's Republic of China.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Building 306, Room 111, BARC-East, Beltsville, MD, 20705, USA.
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14
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Zhou Y, Utsunomiya YT, Xu L, Hay EHA, Bickhart DM, Alexandre PA, Rosen BD, Schroeder SG, Carvalheiro R, de Rezende Neves HH, Sonstegard TS, Van Tassell CP, Ferraz JBS, Fukumasu H, Garcia JF, Liu GE. Genome-wide CNV analysis reveals variants associated with growth traits in Bos indicus. BMC Genomics 2016; 17:419. [PMID: 27245577 PMCID: PMC4888316 DOI: 10.1186/s12864-016-2461-4] [Citation(s) in RCA: 49] [Impact Index Per Article: 6.1] [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: 08/17/2015] [Accepted: 02/11/2016] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Apart from single nucleotide polymorphism (SNP), copy number variation (CNV) is another important type of genetic variation, which may affect growth traits and play key roles for the production of beef cattle. To date, no genome-wide association study (GWAS) for CNV and body traits in beef cattle has been reported, so the present study aimed to investigate this type of association in one of the most important cattle subspecies: Bos indicus (Nellore breed). RESULTS We have used intensity data from over 700,000 SNP probes across the bovine genome to detect common CNVs in a sample of 2230 Nellore cattle, and performed GWAS between the detected CNVs and nine growth traits. After filtering for frequency and length, a total of 231 CNVs ranging from 894 bp to 4,855,088 bp were kept and tested as predictors for each growth trait using linear regression analysis with principal components correction. There were 49 significant associations identified among 17 CNVs and seven body traits after false discovery rate correction (P < 0.05). Among the 17 CNVs, three were significant or marginally significant for all the traits. We have compared the locations of associated CNVs with quantitative trait locus and the RefGene database, and found two sets of 9 CNVs overlapping with either known QTLs or genes, respectively. The gene overlapping with CNV100, KCNJ12, is a functional candidate for muscle development and plays critical roles in muscling traits. CONCLUSION This study presents the first CNV-based GWAS of growth traits using high density SNP microarray data in cattle. We detected 17 CNVs significantly associated with seven growth traits and one of them (CNV100) may be involved in growth traits through KCNJ12.
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Affiliation(s)
- Yang Zhou
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,College of Animal Science and Technology, Northwest A&F University, Shaanxi Key Laboratory of Agricultural Molecular Biology, Yangling, Shaanxi, 712100, China
| | - Yuri T Utsunomiya
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Lingyang Xu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Institute of Animal Science, Chinese Academy of Agricultural Science, Beijing, 100193, China
| | - El Hamidi Abdel Hay
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Pamela Almeida Alexandre
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Benjamin D Rosen
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - Roberto Carvalheiro
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Haroldo Henrique de Rezende Neves
- Departamento de Zootecnia, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.,Present address: Recombinetics, Inc., St Paul, MN, 55104, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA
| | - José Bento Sterman Ferraz
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Heidge Fukumasu
- Department of Veterinary Medicine, College of Animal Science and Food Engineering, University of São Paulo, Pirassununga, SP, 13635, Brazil
| | - Jose Fernando Garcia
- Departamento de Medicina Veterinária Preventiva e Reprodução Animal, Faculdade de Ciências Agrárias e Veterinárias, UNESP - Univ Estadual Paulista, Jaboticabal, São Paulo, 14884-900, Brazil. .,Departamento de Apoio, Produção e Saúde Animal, Faculdade de Medicina Veterinária de Araçatuba, UNESP - Univ Estadual Paulista, Araçatuba, São Paulo, 16050-680, Brazil. .,International Atomic Energy Agency (IAEA) Collaborating Centre on Animal Genomics and Bioinformatics, Araçatuba, SP, Brazil.
| | - George E Liu
- Animal Genomics and Improvement Laboratory, BARC, USDA-ARS, Room 111, BARC-East, Beltsville, Maryland, 20705, USA.
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15
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Bickhart DM, Xu L, Hutchison JL, Cole JB, Null DJ, Schroeder SG, Song J, Garcia JF, Sonstegard TS, Van Tassell CP, Schnabel RD, Taylor JF, Lewin HA, Liu GE. Diversity and population-genetic properties of copy number variations and multicopy genes in cattle. DNA Res 2016; 23:253-62. [PMID: 27085184 PMCID: PMC4909312 DOI: 10.1093/dnares/dsw013] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [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: 11/05/2015] [Accepted: 02/29/2016] [Indexed: 11/14/2022] Open
Abstract
The diversity and population genetics of copy number variation (CNV) in domesticated animals are not well understood. In this study, we analysed 75 genomes of major taurine and indicine cattle breeds (including Angus, Brahman, Gir, Holstein, Jersey, Limousin, Nelore, and Romagnola), sequenced to 11-fold coverage to identify 1,853 non-redundant CNV regions. Supported by high validation rates in array comparative genomic hybridization (CGH) and qPCR experiments, these CNV regions accounted for 3.1% (87.5 Mb) of the cattle reference genome, representing a significant increase over previous estimates of the area of the genome that is copy number variable (∼2%). Further population genetics and evolutionary genomics analyses based on these CNVs revealed the population structures of the cattle taurine and indicine breeds and uncovered potential diversely selected CNVs near important functional genes, including AOX1, ASZ1, GAT, GLYAT, and KRTAP9-1. Additionally, 121 CNV gene regions were found to be either breed specific or differentially variable across breeds, such as RICTOR in dairy breeds and PNPLA3 in beef breeds. In contrast, clusters of the PRP and PAG genes were found to be duplicated in all sequenced animals, suggesting that subfunctionalization, neofunctionalization, or overdominance play roles in diversifying those fertility-related genes. These CNV results provide a new glimpse into the diverse selection histories of cattle breeds and a basis for correlating structural variation with complex traits in the future.
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Affiliation(s)
- Derek M Bickhart
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Lingyang Xu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Jana L Hutchison
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - John B Cole
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Daniel J Null
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Steven G Schroeder
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | | | - Tad S Sonstegard
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
| | | | - Robert D Schnabel
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA Informatics Institute, University of Missouri, Columbia, MO, USA
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO 65211, USA
| | - Harris A Lewin
- Department of Evolution and Ecology, University of California, Davis, CA 95616, USA
| | - George E Liu
- USDA-ARS, Animal Genomics and Improvement Laboratory, Beltsville, MD 20705, USA
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16
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Whitacre LK, Tizioto PC, Kim J, Sonstegard TS, Schroeder SG, Alexander LJ, Medrano JF, Schnabel RD, Taylor JF, Decker JE. What's in your next-generation sequence data? An exploration of unmapped DNA and RNA sequence reads from the bovine reference individual. BMC Genomics 2015; 16:1114. [PMID: 26714747 PMCID: PMC4696311 DOI: 10.1186/s12864-015-2313-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.0] [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: 08/26/2015] [Accepted: 12/15/2015] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Next-generation sequencing projects commonly commence by aligning reads to a reference genome assembly. While improvements in alignment algorithms and computational hardware have greatly enhanced the efficiency and accuracy of alignments, a significant percentage of reads often remain unmapped. RESULTS We generated de novo assemblies of unmapped reads from the DNA and RNA sequencing of the Bos taurus reference individual and identified the closest matching sequence to each contig by alignment to the NCBI non-redundant nucleotide database using BLAST. As expected, many of these contigs represent vertebrate sequence that is absent, incomplete, or misassembled in the UMD3.1 reference assembly. However, numerous additional contigs represent invertebrate species. Most prominent were several species of Spirurid nematodes and a blood-borne parasite, Babesia bigemina. These species are either not present in the US or are not known to infect taurine cattle and the reference animal appears to have been host to unsequenced sister species. CONCLUSIONS We demonstrate the importance of exploring unmapped reads to ascertain sequences that are either absent or misassembled in the reference assembly and for detecting sequences indicative of parasitic or commensal organisms.
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Affiliation(s)
- Lynsey K Whitacre
- Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. .,Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
| | - Polyana C Tizioto
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA. .,Embrapa Southeast Livestock, São Carlos, São Paulo, 13560-970, Brazil.
| | - JaeWoo Kim
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA. .,Recombinetics Inc., 1246 University Ave W #301, St Paul, MN, 55104, USA.
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, USDA-ARS, Beltsville, MD, 20705, USA.
| | | | - Juan F Medrano
- Department of Animal Science, University of California-Davis, Davis, CA, 95616, USA.
| | - Robert D Schnabel
- Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. .,Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
| | - Jeremy F Taylor
- Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
| | - Jared E Decker
- Informatics Institute, University of Missouri, Columbia, MO, 65211, USA. .,Division of Animal Sciences, University of Missouri, Columbia, MO, 65211, USA.
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17
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Sun J, Aswath K, Schroeder SG, Lippolis JD, Reinhardt TA, Sonstegard TS. MicroRNA expression profiles of bovine milk exosomes in response to Staphylococcus aureus infection. BMC Genomics 2015; 16:806. [PMID: 26475455 PMCID: PMC4609085 DOI: 10.1186/s12864-015-2044-9] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2015] [Accepted: 10/09/2015] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Milk exosomes are a rich source of microRNAs (miRNAs) that are protected from degradation. Ingestion of milk and subsequent absorption of miRNAs into recipient cells by endocytosis may play a role in the regulation of neonatal innate and adaptive immunity. In contrast, the miRNA content of milk exosomes may also be indicative of a lactating animal's health; whereby, the presence or absence of specific miRNAs could serve as biomarkers for early detection of bacterial infection that can lead to mastitis. In the present study, we therefore analyzed and compared miRNA expression profiles of milk exosomes from four Holstein cows obtained during mid-lactation prior to and after infection (48 h) of the mammary gland with Staphylococcus aureus. METHODS Milk exosomes, purified from control and S. aureus infected cows, were extracted for RNA. Following preparation indexed libraries from both groups the samples were subjected to next generation sequencing. RESULTS Next generation sequencing of eight, unpooled small RNA libraries derived from milk exosomes produced about 60.5 million high-quality, bovine-specific sequence reads for comparison of miRNA expression between treatments. Sequence identity analysis showed the miRNAs make up about 13 % of the average RNA content of these exosomes. Although 417 known bovine miRNAs were identified, miRNAs represented the least diverse class of RNA accounting for only 1 % of all unique sequences. The 20 most prevalent unique sequences within this class accounted for about 90 % of the total miRNA-associated reads across samples. Non-annotated, unique reads provided evidence for another 303 previously unknown bovine miRNAs. Expression analyses found 14 known bovine microRNAs significantly differed in frequency between exosomes from infected and control animals. CONCLUSIONS Our survey of miRNA expression from uninfected milk exosomes and those produced in response to infection provides new and comprehensive information supporting a role for delivery into milk of specific miRNAs involved in immune response. In particular, bta-miR-142-5p, and -223 are potential biomarkers for early detection of bacterial infection of the mammary gland. Additionally, 22 mammary-expressed genes involved in regulation of host immune processes and response to inflammation were identified as potential binding targets of the differentially expressed miRNAs.
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Affiliation(s)
- Jiajie Sun
- Animal Genomics and Improvement Laboratory, USDA-ARS, BARC-East, Beltsville, MD, 20705, USA.
| | - Kshama Aswath
- School of Systems Biology, George Mason University, 10900 University Boulevard, Manassas, VA, 20110, USA.
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, USDA-ARS, BARC-East, Beltsville, MD, 20705, USA.
| | - John D Lippolis
- Ruminant Diseases and Immunology Unit, National Animal Disease Center, USDA/ARS, Ames, IA, 50010, USA.
| | - Timothy A Reinhardt
- Ruminant Diseases and Immunology Unit, National Animal Disease Center, USDA/ARS, Ames, IA, 50010, USA.
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, USDA-ARS, BARC-East, Beltsville, MD, 20705, USA. .,Acceligen Inc., 1246 University Avenue W, St. Paul, MN, 55104, USA.
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18
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Song Q, Jia G, Hyten DL, Jenkins J, Hwang EY, Schroeder SG, Osorno JM, Schmutz J, Jackson SA, McClean PE, Cregan PB. SNP Assay Development for Linkage Map Construction, Anchoring Whole-Genome Sequence, and Other Genetic and Genomic Applications in Common Bean. G3 (Bethesda) 2015; 5:2285-90. [PMID: 26318155 PMCID: PMC4632048 DOI: 10.1534/g3.115.020594] [Citation(s) in RCA: 79] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/23/2015] [Accepted: 08/27/2015] [Indexed: 11/28/2022]
Abstract
A total of 992,682 single-nucleotide polymorphisms (SNPs) was identified as ideal for Illumina Infinium II BeadChip design after sequencing a diverse set of 17 common bean (Phaseolus vulgaris L) varieties with the aid of next-generation sequencing technology. From these, two BeadChips each with >5000 SNPs were designed. The BARCBean6K_1 BeadChip was selected for the purpose of optimizing polymorphism among market classes and, when possible, SNPs were targeted to sequence scaffolds in the Phaseolus vulgaris 14× genome assembly with sequence lengths >10 kb. The BARCBean6K_2 BeadChip was designed with the objective of anchoring additional scaffolds and to facilitate orientation of large scaffolds. Analysis of 267 F2 plants from a cross of varieties Stampede × Red Hawk with the two BeadChips resulted in linkage maps with a total of 7040 markers including 7015 SNPs. With the linkage map, a total of 432.3 Mb of sequence from 2766 scaffolds was anchored to create the Phaseolus vulgaris v1.0 assembly, which accounted for approximately 89% of the 487 Mb of available sequence scaffolds of the Phaseolus vulgaris v0.9 assembly. A core set of 6000 SNPs (BARCBean6K_3 BeadChip) with high genotyping quality and polymorphism was selected based on the genotyping of 365 dry bean and 134 snap bean accessions with the BARCBean6K_1 and BARCBean6K_2 BeadChips. The BARCBean6K_3 BeadChip is a useful tool for genetics and genomics research and it is widely used by breeders and geneticists in the United States and abroad.
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Affiliation(s)
- Qijian Song
- USDA-ARS, Soybean Genomics and Improvement Lab, Beltsville, Maryland 20705
| | - Gaofeng Jia
- USDA-ARS, Soybean Genomics and Improvement Lab, Beltsville, Maryland 20705
| | - David L Hyten
- USDA-ARS, Soybean Genomics and Improvement Lab, Beltsville, Maryland 20705
| | - Jerry Jenkins
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806
| | - Eun-Young Hwang
- Department of Plant Science and Landscape Architecture, University of Maryland, College Park, Maryland 20742
| | - Steven G Schroeder
- USDA-ARS, Bovine Functional Genomics Laboratory, Animal and Natural Resources Institute, Beltsville, Maryland 20705
| | - Juan M Osorno
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota 58102
| | - Jeremy Schmutz
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama 35806 Joint Genome Institute, 2800 Mitchell Drive, Walnut Creek, California 94598
| | - Scott A Jackson
- Center for Applied Genetic Technologies, University of Georgia, Athens, Georgia 30602
| | - Phillip E McClean
- Department of Plant Sciences, North Dakota State University, Fargo, North Dakota 58102
| | - Perry B Cregan
- USDA-ARS, Soybean Genomics and Improvement Lab, Beltsville, Maryland 20705
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19
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Xu L, Bickhart DM, Cole JB, Schroeder SG, Song J, Tassell CPV, Sonstegard TS, Liu GE. Genomic signatures reveal new evidences for selection of important traits in domestic cattle. Mol Biol Evol 2014; 32:711-25. [PMID: 25431480 DOI: 10.1093/molbev/msu333] [Citation(s) in RCA: 110] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
Abstract
We investigated diverse genomic selections using high-density single nucleotide polymorphism data of five distinct cattle breeds. Based on allele frequency differences, we detected hundreds of candidate regions under positive selection across Holstein, Angus, Charolais, Brahman, and N'Dama. In addition to well-known genes such as KIT, MC1R, ASIP, GHR, LCORL, NCAPG, WIF1, and ABCA12, we found evidence for a variety of novel and less-known genes under selection in cattle, such as LAP3, SAR1B, LRIG3, FGF5, and NUDCD3. Selective sweeps near LAP3 were then validated by next-generation sequencing. Genome-wide association analysis involving 26,362 Holsteins confirmed that LAP3 and SAR1B were related to milk production traits, suggesting that our candidate regions were likely functional. In addition, haplotype network analyses further revealed distinct selective pressures and evolution patterns across these five cattle breeds. Our results provided a glimpse into diverse genomic selection during cattle domestication, breed formation, and recent genetic improvement. These findings will facilitate genome-assisted breeding to improve animal production and health.
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Affiliation(s)
- Lingyang Xu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Derek M Bickhart
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - John B Cole
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Steven G Schroeder
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Jiuzhou Song
- Department of Animal and Avian Sciences, University of Maryland, College Park, MD 20742, USA
| | - Curtis P Van Tassell
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - Tad S Sonstegard
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
| | - George E Liu
- Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705, USA
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20
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Aslam ML, Bastiaansen JW, Megens HJ, Crooijmans RP, Nasreen F, Blomberg LA, Van Tassell CP, Sonstegard TS, Schroeder SG, Groenen MA, Long JA. Genome-wide candidate regions for selective sweeps revealed through massive parallel sequencing of DNA across ten turkey populations. BMC Genet 2014; 15:117. [PMID: 25421611 PMCID: PMC4253982 DOI: 10.1186/s12863-014-0117-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2014] [Accepted: 10/22/2014] [Indexed: 12/02/2022] Open
Abstract
Background The domestic turkey (Meleagris gallopavo) is an important agricultural species that is largely used as a meat-type bird. Characterizing genetic variation in populations of domesticated species and associating these variation patterns with the evolution, domestication, and selective breeding is critical for understanding the dynamics of genomic change in these species. Intense selective breeding and population bottlenecks are expected to leave signatures in the genome of domesticated species, such as unusually low nucleotide diversity or the presence of exceptionally extended haplotype homozygosity. These patterns of variation in selected populations are highly useful to not only understand the consequences of selective breeding and population dynamics, but also to provide insights into biological mechanisms that may affect physiological processes important to bring changes in phenotype of interest. Results We observed 54 genomic regions in heritage and commercial turkey populations on 14 different chromosomes that showed statistically significant (P < 0.05) reduction in genomic variation indicating candidate selective sweeps. Areas with evidence of selective sweeps varied from 1.5 Mb to 13.8 Mb in length. Out of these 54 sweeps, 23 overlapped at least partially between two or more populations. Overlapping sweeps were found on 13 different chromosomes. The remaining 31 sweeps were population-specific and were observed on 12 different chromosomes, with 26 of these regions present only in commercial populations. Genes that are known to affect growth were enriched in the sweep regions. Conclusion The turkey genome showed large sweep regions. The relatively high number of sweep regions in commercial turkey populations compared to heritage varieties and the enrichment of genes important to growth in these regions, suggest that these sweeps are the result of intense selection in these commercial lines, moving specific haplotypes towards fixation. Electronic supplementary material The online version of this article (doi:10.1186/s12863-014-0117-4) contains supplementary material, which is available to authorized users.
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Sonstegard TS, Cole JB, VanRaden PM, Van Tassell CP, Null DJ, Schroeder SG, Bickhart D, McClure MC. Identification of a nonsense mutation in CWC15 associated with decreased reproductive efficiency in Jersey cattle. PLoS One 2013; 8:e54872. [PMID: 23349982 PMCID: PMC3551820 DOI: 10.1371/journal.pone.0054872] [Citation(s) in RCA: 74] [Impact Index Per Article: 6.7] [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: 09/28/2012] [Accepted: 12/17/2012] [Indexed: 12/22/2022] Open
Abstract
With the recent advent of genomic tools for cattle, several recessive conditions affecting fertility have been identified and selected against, such as deficiency of uridine monophosphate synthase, complex vertebral malformation, and brachyspina. The current report refines the location of a recessive haplotype affecting fertility in Jersey cattle using crossover haplotypes, discovers the causative mutation using whole genome sequencing, and examines the gene's role in embryo loss. In an attempt to identify unknown recessive lethal alleles in the current dairy population, a search using deep Mendelian sampling of 5,288 Jersey cattle was conducted for high-frequency haplotypes that have a deficit of homozygotes at the population level. This search led to the discovery of a putative recessive lethal in Jersey cattle on Bos taurus autosome 15. The haplotype, denoted JH1, was associated with reduced fertility, and further investigation identified one highly-influential Jersey bull as the putative source ancestor. By combining SNP analysis of whole-genome sequences aligned to the JH1 interval and subsequent SNP validation a nonsense mutation in CWC15 was identified as the likely causative mutation underlying the fertility phenotype. No homozygous recessive individuals were found in 749 genotyped animals, whereas all known carriers and carrier haplotypes possessed one copy of the mutant allele. This newly identified lethal has been responsible for a substantial number of spontaneous abortions in Jersey dairy cattle throughout the past half-century. With the mutation identified, selection against the deleterious allele in breeding schemes will aid in reducing the incidence of this defect in the population. These results also show that carrier status can be imputed with high accuracy. Whole-genome resequencing proved to be a powerful strategy to rapidly identify a previously mapped deleterious mutation in a known carrier of a recessive lethal allele.
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Affiliation(s)
- Tad S. Sonstegard
- Bovine Functional Genomics, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - John B. Cole
- Animal Improvement Programs Laboratories, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
- * E-mail:
| | - Paul M. VanRaden
- Animal Improvement Programs Laboratories, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Curtis P. Van Tassell
- Bovine Functional Genomics, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Daniel J. Null
- Animal Improvement Programs Laboratories, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Steven G. Schroeder
- Bovine Functional Genomics, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Derek Bickhart
- Bovine Functional Genomics, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
| | - Matthew C. McClure
- Bovine Functional Genomics, United States Department of Agriculture, Agricultural Research Service, Beltsville, Maryland, United States of America
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22
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Aslam ML, Bastiaansen JWM, Elferink MG, Megens HJ, Crooijmans RPMA, Blomberg LA, Fleischer RC, Van Tassell CP, Sonstegard TS, Schroeder SG, Groenen MAM, Long JA. Whole genome SNP discovery and analysis of genetic diversity in Turkey (Meleagris gallopavo). BMC Genomics 2012; 13:391. [PMID: 22891612 PMCID: PMC3496629 DOI: 10.1186/1471-2164-13-391] [Citation(s) in RCA: 53] [Impact Index Per Article: 4.4] [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: 03/26/2012] [Accepted: 08/09/2012] [Indexed: 11/23/2022] Open
Abstract
Background The turkey (Meleagris gallopavo) is an important agricultural species and the second largest contributor to the world’s poultry meat production. Genetic improvement is attributed largely to selective breeding programs that rely on highly heritable phenotypic traits, such as body size and breast muscle development. Commercial breeding with small effective population sizes and epistasis can result in loss of genetic diversity, which in turn can lead to reduced individual fitness and reduced response to selection. The presence of genomic diversity in domestic livestock species therefore, is of great importance and a prerequisite for rapid and accurate genetic improvement of selected breeds in various environments, as well as to facilitate rapid adaptation to potential changes in breeding goals. Genomic selection requires a large number of genetic markers such as e.g. single nucleotide polymorphisms (SNPs) the most abundant source of genetic variation within the genome. Results Alignment of next generation sequencing data of 32 individual turkeys from different populations was used for the discovery of 5.49 million SNPs, which subsequently were used for the analysis of genetic diversity among the different populations. All of the commercial lines branched from a single node relative to the heritage varieties and the South Mexican turkey population. Heterozygosity of all individuals from the different turkey populations ranged from 0.17-2.73 SNPs/Kb, while heterozygosity of populations ranged from 0.73-1.64 SNPs/Kb. The average frequency of heterozygous SNPs in individual turkeys was 1.07 SNPs/Kb. Five genomic regions with very low nucleotide variation were identified in domestic turkeys that showed state of fixation towards alleles different than wild alleles. Conclusion The turkey genome is much less diverse with a relatively low frequency of heterozygous SNPs as compared to other livestock species like chicken and pig. The whole genome SNP discovery study in turkey resulted in the detection of 5.49 million putative SNPs compared to the reference genome. All commercial lines appear to share a common origin. Presence of different alleles/haplotypes in the SM population highlights that specific haplotypes have been selected in the modern domesticated turkey.
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Affiliation(s)
- Muhammad L Aslam
- Animal Breeding and Genomics Centre, Wageningen University, De Elst 1, 6708WD Wageningen, The Netherlands.
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23
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Bickhart DM, Hou Y, Schroeder SG, Alkan C, Cardone MF, Matukumalli LK, Song J, Schnabel RD, Ventura M, Taylor JF, Garcia JF, Van Tassell CP, Sonstegard TS, Eichler EE, Liu GE. Copy number variation of individual cattle genomes using next-generation sequencing. Genome Res 2012; 22:778-90. [PMID: 22300768 DOI: 10.1101/gr.133967.111] [Citation(s) in RCA: 218] [Impact Index Per Article: 18.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Copy number variations (CNVs) affect a wide range of phenotypic traits; however, CNVs in or near segmental duplication regions are often intractable. Using a read depth approach based on next-generation sequencing, we examined genome-wide copy number differences among five taurine (three Angus, one Holstein, and one Hereford) and one indicine (Nelore) cattle. Within mapped chromosomal sequence, we identified 1265 CNV regions comprising ~55.6-Mbp sequence--476 of which (~38%) have not previously been reported. We validated this sequence-based CNV call set with array comparative genomic hybridization (aCGH), quantitative PCR (qPCR), and fluorescent in situ hybridization (FISH), achieving a validation rate of 82% and a false positive rate of 8%. We further estimated absolute copy numbers for genomic segments and annotated genes in each individual. Surveys of the top 25 most variable genes revealed that the Nelore individual had the lowest copy numbers in 13 cases (~52%, χ(2) test; P-value <0.05). In contrast, genes related to pathogen- and parasite-resistance, such as CATHL4 and ULBP17, were highly duplicated in the Nelore individual relative to the taurine cattle, while genes involved in lipid transport and metabolism, including APOL3 and FABP2, were highly duplicated in the beef breeds. These CNV regions also harbor genes like BPIFA2A (BSP30A) and WC1, suggesting that some CNVs may be associated with breed-specific differences in adaptation, health, and production traits. By providing the first individualized cattle CNV and segmental duplication maps and genome-wide gene copy number estimates, we enable future CNV studies into highly duplicated regions in the cattle genome.
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Affiliation(s)
- Derek M Bickhart
- USDA-ARS, ANRI, Bovine Functional Genomics Laboratory, Beltsville, Maryland 20705, USA
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24
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Li RW, Schroeder SG. Cytoskeleton remodeling and alterations in smooth muscle contractility in the bovine jejunum during nematode infection. Funct Integr Genomics 2011; 12:35-44. [PMID: 22203460 DOI: 10.1007/s10142-011-0259-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.9] [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: 09/19/2011] [Revised: 11/28/2011] [Accepted: 12/05/2011] [Indexed: 11/27/2022]
Abstract
Gastrointestinal nematodes of the genus Cooperia are arguably the most important parasites of cattle. The bovine jejunal transcriptome was characterized in response to Cooperia oncophora infection using RNA-seq technology. Approximately 71% of the 25,670 bovine genes were detected in the jejunal transcriptome. However, 16,552 genes were expressed in all samples tested, probably representing the core component of the transcriptome. Twenty of the most abundant genes accounted for 12.7% of the sequences from the transcriptome. A 164-h infection seemingly induced a minor change in the transcriptome (162 genes). Additionally, a total of 162,412 splice junctions were identified. Among them, 1,164 appeared unique to 1 of the 2 groups: 868 splice junctions were observed only in infected animals, while 278 were only present in all 4 control animals. Biological functions associated with muscle contraction were predominant Gene Ontology terms enriched in the genes differentially expressed by infection. The primary function of two of the four regulatory networks impacted was related to skeletal and muscular systems. A total of 34 pathways were significantly impacted by infection. Several pathways were directly related to host immune responses, such as acute phase response, leukocyte extravasation, and antigen presentation, consistent with previous findings. Calcium signaling and actin cytoskeleton signaling were among the pathways most significantly impacted by infection in the bovine jejunum. Together, these data suggest that smooth muscle hypercontractility may be initiated as a result of a primary C. oncophora infection, which may represent a mechanism for host responses in the jejunum during nematode infection.
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Affiliation(s)
- Robert W Li
- Bovine Functional Genomics Laboratory, Animal and Natural Resources Institute, USDA-ARS, Beltsville, MD 20705, USA.
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25
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Dawson HD, Chen C, Perry TL, Schroeder SG, Urban JF. Transcriptome profiling of all‐trans‐retinoic acid stimulated alveolar macrophages revealed novel pathways involved in tissue inflammation. FASEB J 2011. [DOI: 10.1096/fasebj.25.1_supplement.784.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Harhay GP, Smith TP, Alexander LJ, Haudenschild CD, Keele JW, Matukumalli LK, Schroeder SG, Van Tassell CP, Gresham CR, Bridges SM, Burgess SC, Sonstegard TS. An atlas of bovine gene expression reveals novel distinctive tissue characteristics and evidence for improving genome annotation. Genome Biol 2010; 11:R102. [PMID: 20961407 PMCID: PMC3218658 DOI: 10.1186/gb-2010-11-10-r102] [Citation(s) in RCA: 38] [Impact Index Per Article: 2.7] [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: 04/20/2010] [Revised: 07/22/2010] [Accepted: 10/20/2010] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND A comprehensive transcriptome survey, or gene atlas, provides information essential for a complete understanding of the genomic biology of an organism. We present an atlas of RNA abundance for 92 adult, juvenile and fetal cattle tissues and three cattle cell lines. RESULTS The Bovine Gene Atlas was generated from 7.2 million unique digital gene expression tag sequences (300.2 million total raw tag sequences), from which 1.59 million unique tag sequences were identified that mapped to the draft bovine genome accounting for 85% of the total raw tag abundance. Filtering these tags yielded 87,764 unique tag sequences that unambiguously mapped to 16,517 annotated protein-coding loci in the draft genome accounting for 45% of the total raw tag abundance. Clustering of tissues based on tag abundance profiles generally confirmed ontology classification based on anatomy. There were 5,429 constitutively expressed loci and 3,445 constitutively expressed unique tag sequences mapping outside annotated gene boundaries that represent a resource for enhancing current gene models. Physical measures such as inferred transcript length or antisense tag abundance identified tissues with atypical transcriptional tag profiles. We report for the first time the tissue-specific variation in the proportion of mitochondrial transcriptional tag abundance. CONCLUSIONS The Bovine Gene Atlas is the deepest and broadest transcriptome survey of any livestock genome to date. Commonalities and variation in sense and antisense transcript tag profiles identified in different tissues facilitate the examination of the relationship between gene expression, tissue, and gene function.
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Affiliation(s)
- Gregory P Harhay
- USDA-ARS US Meat Animal Research Center, State Spur 18 D, Clay Center, NE 68901, USA.
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Matukumalli LK, Schroeder SG. Sequence Based Gene Expression Analysis. Bioinformatics 2009. [DOI: 10.1007/978-0-387-92738-1_9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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28
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Cone KC, McMullen MD, Bi IV, Davis GL, Yim YS, Gardiner JM, Polacco ML, Sanchez-Villeda H, Fang Z, Schroeder SG, Havermann SA, Bowers JE, Paterson AH, Soderlund CA, Engler FW, Wing RA, Coe EH. Genetic, physical, and informatics resources for maize. On the road to an integrated map. Plant Physiol 2002; 130:1598-605. [PMID: 12481043 PMCID: PMC1540265 DOI: 10.1104/pp.012245] [Citation(s) in RCA: 54] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Affiliation(s)
- Karen C Cone
- Division of Biological Sciences, University of Missouri, Columbia 65211, USA.
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Abstract
EcoRII methyltransferase (M.EcoRII) is a cytosine-C5 DNA methylating enzyme. A model of its three-dimensional structure is proposed on the basis of homology modeling. Crystal structures of two members of the same family of enzymes, HaeIII and HhaI methyltransferases (M.HaeIII and M.HhaI respectively), were used as template molecules. Molecular dynamics was used to ensure sampling of conformationally stable structures. The final model has good geometry. The DNA and cofactor binding residues are in expected positions and form proper interactions. M.EcoRII is 147 amino acids longer than the template molecules, and hence the model contains several loops that are significantly longer than those in M.HaeIII and M.HhaI. The model provides a framework for interpretation and designing site-directed mutants that have a potential to improve crystallization experiments of this enzyme, and possibly other similar enzymes.
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Affiliation(s)
- S G Schroeder
- Biochemistry Department, University of Missouri-Columbia 65211, USA
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