1
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Xiao C, Li J, Xie T, Chen J, Zhang S, Elaksher SH, Jiang F, Jiang Y, Zhang L, Zhang W, Xiang Y, Wu Z, Zhao S, Du X. The assembly of caprine Y chromosome sequence reveals a unique paternal phylogenetic pattern and improves our understanding of the origin of domestic goat. Ecol Evol 2021; 11:7779-7795. [PMID: 34188851 PMCID: PMC8216945 DOI: 10.1002/ece3.7611] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 03/30/2021] [Accepted: 04/06/2021] [Indexed: 02/05/2023] Open
Abstract
The mammalian Y chromosome offers a unique perspective on the male reproduction and paternal evolutionary histories. However, further understanding of the Y chromosome biology for most mammals is hindered by the lack of a Y chromosome assembly. This study presents an integrated in silico strategy for identifying and assembling the goat Y-linked scaffolds using existing data. A total of 11.5 Mb Y-linked sequences were clustered into 33 scaffolds, and 187 protein-coding genes were annotated. We also identified high abundance of repetitive elements. A 5.84 Mb subset was further ordered into an assembly with the evidence from the goat radiation hybrid map (RH map). The existing whole-genome resequencing data of 96 goats (worldwide distribution) were utilized to exploit the paternal relationships among bezoars and domestic goats. Goat paternal lineages were clearly divided into two clades (Y1 and Y2), predating the goat domestication. Demographic history analyses indicated that maternal lineages experienced a bottleneck effect around 2,000 YBP (years before present), after which goats belonging to the A haplogroup spread worldwide from the Near East. As opposed to this, paternal lineages experienced a population decline around the 10,000 YBP. The evidence from the Y chromosome suggests that male goats were not affected by the A haplogroup worldwide transmission, which implies sexually unbalanced contribution to the goat trade and population expansion in post-Neolithic period.
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Affiliation(s)
- Changyi Xiao
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Jingjin Li
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
| | - Tanghui Xie
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Jianhai Chen
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
- Institutes for Systems GeneticsFrontiers Science Center for Disease‐related Molecular NetworkWest China HospitalSichuan UniversityChengduChina
| | - Sijia Zhang
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Salma Hassan Elaksher
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
- Genetics and Genetic Engineering DepartmentFaculty of AgricultureBenha UniversityMoshtohorEgypt
| | - Fan Jiang
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Yaoxin Jiang
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
| | - Lu Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
| | - Wei Zhang
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
| | - Yue Xiang
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
| | - Zhenyang Wu
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
- College of Agroforestry Engineering and PlanningTongren UniversityTongrenChina
| | - Shuhong Zhao
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
| | - Xiaoyong Du
- College of InformaticsHuazhong Agricultural UniversityWuhanChina
- Key Laboratory of Agricultural Animal Genetics, Breeding and ReproductionMinistry of EducationCollege of Animal Science and Veterinary MedicineHuazhong Agricultural UniversityWuhanChina
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2
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Donaldson B, Villagomez DAF, King WA. Classical, Molecular, and Genomic Cytogenetics of the Pig, a Clinical Perspective. Animals (Basel) 2021; 11:1257. [PMID: 33925534 PMCID: PMC8146943 DOI: 10.3390/ani11051257] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2021] [Revised: 04/16/2021] [Accepted: 04/23/2021] [Indexed: 02/06/2023] Open
Abstract
The chromosomes of the domestic pig (Sus scrofa domesticus) are known to be prone to reciprocal chromosome translocations and other balanced chromosome rearrangements with concomitant fertility impairment of carriers. In response to the remarkable prevalence of chromosome rearrangements in swine herds, clinical cytogenetics laboratories have been established in several countries in order to screen young boars for chromosome rearrangements prior to service. At present, clinical cytogenetics laboratories typically apply classical cytogenetics techniques such as giemsa-trypsin (GTG)-banding to produce high-quality karyotypes and reveal large-scale chromosome ectopic exchanges. Further refinements to clinical cytogenetics practices have led to the implementation of molecular cytogenetics techniques such as fluorescent in-situ hybridization (FISH), allowing for rearrangements to be visualized and breakpoints refined using fluorescently labelled painting probes. The next-generation of clinical cytogenetics include the implementation of DNA microarrays, and next-generation sequencing (NGS) technologies such as DNA sequencing to better explore tentative genome architecture changes. The implementation of these cytogenomics techniques allow the genomes of rearrangement carriers to be deciphered at the highest resolution, allowing rearrangements to be detected; breakpoints to be delineated; and, most importantly, potential gene implications of those chromosome rearrangements to be interrogated. Clinical cytogenetics has become an integral tool in the livestock industry, identifying rearrangements and allowing breeders to make informed breeding decisions.
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Affiliation(s)
- Brendan Donaldson
- Department of Biomedical Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada;
| | | | - W. Allan King
- Department of Biomedical Sciences, University of Guelph, Guelph, ON N1G 2W1, Canada;
- Karyotekk Inc., Box 363 OVC, University of Guelph, Guelph, ON N1G 2W1, Canada
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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: 167] [Impact Index Per Article: 41.8] [Reference Citation Analysis] [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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Perelman PL, Pichler R, Gaggl A, Larkin DM, Raudsepp T, Alshanbari F, Holl HM, Brooks SA, Burger PA, Periasamy K. Construction of two whole genome radiation hybrid panels for dromedary (Camelus dromedarius): 5000 RAD and 15000 RAD. Sci Rep 2018; 8:1982. [PMID: 29386528 PMCID: PMC5792482 DOI: 10.1038/s41598-018-20223-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2017] [Accepted: 01/11/2018] [Indexed: 01/08/2023] Open
Abstract
The availability of genomic resources including linkage information for camelids has been very limited. Here, we describe the construction of a set of two radiation hybrid (RH) panels (5000RAD and 15000RAD) for the dromedary (Camelus dromedarius) as a permanent genetic resource for camel genome researchers worldwide. For the 5000RAD panel, a total of 245 female camel-hamster radiation hybrid clones were collected, of which 186 were screened with 44 custom designed marker loci distributed throughout camel genome. The overall mean retention frequency (RF) of the final set of 93 hybrids was 47.7%. For the 15000RAD panel, 238 male dromedary-hamster radiation hybrid clones were collected, of which 93 were tested using 44 PCR markers. The final set of 90 clones had a mean RF of 39.9%. This 15000RAD panel is an important high-resolution complement to the main 5000RAD panel and an indispensable tool for resolving complex genomic regions. This valuable genetic resource of dromedary RH panels is expected to be instrumental for constructing a high resolution camel genome map. Construction of the set of RH panels is essential step toward chromosome level reference quality genome assembly that is critical for advancing camelid genomics and the development of custom genomic tools.
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Affiliation(s)
- Polina L Perelman
- Animal Production and Health Laboratory, Joint FAO/IAEA Division, International Atomic Energy Agency, Vienna, Austria
- Institute of Molecular and Cellular Biology and Novosibirsk State University, Novosibirsk, Russia
| | - Rudolf Pichler
- Animal Production and Health Laboratory, Joint FAO/IAEA Division, International Atomic Energy Agency, Vienna, Austria
| | - Anna Gaggl
- Animal Production and Health Laboratory, Joint FAO/IAEA Division, International Atomic Energy Agency, Vienna, Austria
| | - Denis M Larkin
- Department of Comparative Biomedical Sciences, Royal Veterinary College, University of London, London, NW1 0TU, United Kingdom
| | | | | | | | | | - Pamela A Burger
- Research Institute of Wildlife Ecology, Vetmeduni, Vienna, Austria
| | - Kathiravan Periasamy
- Animal Production and Health Laboratory, Joint FAO/IAEA Division, International Atomic Energy Agency, Vienna, Austria.
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5
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Hérault F, Damon M, Cherel P, Le Roy P. Combined GWAS and LDLA approaches to improve genome-wide quantitative trait loci detection affecting carcass and meat quality traits in pig. Meat Sci 2017; 135:148-158. [PMID: 29035812 DOI: 10.1016/j.meatsci.2017.09.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2017] [Revised: 09/08/2017] [Accepted: 09/27/2017] [Indexed: 01/15/2023]
Abstract
Many QTL affecting meat quality and carcass traits have been reported. However, in most of the cases these QTL have been detected in non-commercial populations. Therefore, a family structured population of 457 F2 pigs issued from an inter-cross between 2 commercial sire lines was used to detect QTL affecting meat quality and carcass traits. All animals were genotyped using the Illumina PorcineSNP60 BeadChip platform. Genome-wide association studies were used in combination with linkage disequilibrium-linkage analysis to identify QTL. A total of 32 QTL were detected. Nine of these QTL exceeded the genome-wide 5% significance threshold. We detected 18 QTL affecting carcass composition traits and 16 QTL affecting meat quality traits. Using post-QTL bioinformatics analysis we highlighted 26 functional candidate genes related to fatness, muscle development, meat color and meat pH. Finally, our results shed light on the advantage of using different QTL detection methodologies to get a global overview of the QTL present in the studied population.
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Affiliation(s)
- Frédéric Hérault
- INRA, UMR1348 PEGASE, 16 le Clos, 35590 Saint-Gilles, France; Agrocampus Ouest, UMR1348 PEGASE, 65 rue de Saint Brieuc, 35042 Rennes, France.
| | - Marie Damon
- INRA, UMR1348 PEGASE, 16 le Clos, 35590 Saint-Gilles, France; Agrocampus Ouest, UMR1348 PEGASE, 65 rue de Saint Brieuc, 35042 Rennes, France
| | - Pierre Cherel
- iBV-institut de Biologie Valrose, Université Nice-Sophia Antipolis, UMR CNRS 7277, Inserm U1091, Parc Valrose, F-06108 Nice, France
| | - Pascale Le Roy
- INRA, UMR1348 PEGASE, 16 le Clos, 35590 Saint-Gilles, France; Agrocampus Ouest, UMR1348 PEGASE, 65 rue de Saint Brieuc, 35042 Rennes, France.
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6
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Abstract
Models of codon evolution have attracted particular interest because of their unique capabilities to detect selection forces and their high fit when applied to sequence evolution. We described here a novel approach for modeling codon evolution, which is based on Kronecker product of matrices. The 61 × 61 codon substitution rate matrix is created using Kronecker product of three 4 × 4 nucleotide substitution matrices, the equilibrium frequency of codons, and the selection rate parameter. The entities of the nucleotide substitution matrices and selection rate are considered as parameters of the model, which are optimized by maximum likelihood. Our fully mechanistic model allows the instantaneous substitution matrix between codons to be fully estimated with only 19 parameters instead of 3,721, by using the biological interdependence existing between positions within codons. We illustrate the properties of our models using computer simulations and assessed its relevance by comparing the AICc measures of our model and other models of codon evolution on simulations and a large range of empirical data sets. We show that our model fits most biological data better compared with the current codon models. Furthermore, the parameters in our model can be interpreted in a similar way as the exchangeability rates found in empirical codon models.
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Affiliation(s)
- Maryam Zaheri
- Department of Ecology and Evolution, Biophore, University of Lausanne, 1015 Lausanne, SwitzerlandSwiss Institute of Bioinformatics, Genopode, Quartier Sorge, 1015 Lausanne, Switzerland
| | - Linda Dib
- Department of Ecology and Evolution, Biophore, University of Lausanne, 1015 Lausanne, SwitzerlandSwiss Institute of Bioinformatics, Genopode, Quartier Sorge, 1015 Lausanne, Switzerland
| | - Nicolas Salamin
- Department of Ecology and Evolution, Biophore, University of Lausanne, 1015 Lausanne, SwitzerlandSwiss Institute of Bioinformatics, Genopode, Quartier Sorge, 1015 Lausanne, Switzerland
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7
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Du X, Servin B, Womack JE, Cao J, Yu M, Dong Y, Wang W, Zhao S. An update of the goat genome assembly using dense radiation hybrid maps allows detailed analysis of evolutionary rearrangements in Bovidae. BMC Genomics 2014; 15:625. [PMID: 25052253 PMCID: PMC4141111 DOI: 10.1186/1471-2164-15-625] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Accepted: 07/10/2014] [Indexed: 01/02/2023] Open
Abstract
Background The domestic goat (Capra hircus), an important livestock species, belongs to a clade of Ruminantia, Bovidae, together with cattle, buffalo and sheep. The history of genome evolution and chromosomal rearrangements on a small scale in ruminants remain speculative. Recently completed goat genome sequence was released but is still in a draft stage. The draft sequence used a variety of assembly packages, as well as a radiation hybrid (RH) map of chromosome 1 as part of its validation. Results Using an improved RH mapping pipeline, whole-genome dense maps of 45,953 SNP markers were constructed with statistical confidence measures and the saturated maps provided a fine map resolution of approximate 65 kb. Linking RH maps to the goat sequences showed that the assemblies of scaffolds/super-scaffolds were globally accurate. However, we observed certain flaws linked to the process of anchoring chromosome using conserved synteny with cattle. Chromosome assignments, long-range order, and orientation of the scaffolds were reassessed in an updated genome sequence version. We also present new results exploiting the updated goat genome sequence to understand genomic rearrangements and chromosome evolution between mammals during species radiations. The sequence architecture of rearrangement sites between the goat and cattle genomes presented abundant segmental duplication on regions of goat chromosome 9 and 14, as well as new insertions in homologous cattle genome regions. This complex interplay between duplicated sequences and Robertsonian translocations highlights the rearrangement mechanism of centromeric nonallelic homologous recombination (NAHR) in mammals. We observed that species-specific shifts in ANKRD26 gene duplication are coincident with breakpoint reuse in divergent lineages and this gene family may play a role in chromosome stabilization in chromosome evolution. Conclusions We generated dense maps of the complete whole goat genome. The chromosomal maps allowed us to anchor and orientate assembled genome scaffolds along the chromosomes, annotate chromosome rearrangements and thereby get a better understanding of the genome evolution of ruminants and other mammals. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-625) contains supplementary material, which is available to authorized users.
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Affiliation(s)
| | | | | | | | | | | | - Wen Wang
- Key lab of animal genetics, breeding and reproduction of ministry education, College of Animal Science and Technology, Huazhong Agricultural University, Wuhan 430070, People's Republic of China.
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8
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Jiang Y, Xie M, Chen W, Talbot R, Maddox JF, Faraut T, Wu C, Muzny DM, Li Y, Zhang W, Stanton JA, Brauning R, Barris WC, Hourlier T, Aken BL, Searle SMJ, Adelson DL, Bian C, Cam GR, Chen Y, Cheng S, DeSilva U, Dixen K, Dong Y, Fan G, Franklin IR, Fu S, Guan R, Highland MA, Holder ME, Huang G, Ingham AB, Jhangiani SN, Kalra D, Kovar CL, Lee SL, Liu W, Liu X, Lu C, Lv T, Mathew T, McWilliam S, Menzies M, Pan S, Robelin D, Servin B, Townley D, Wang W, Wei B, White SN, Yang X, Ye C, Yue Y, Zeng P, Zhou Q, Hansen JB, Kristensen K, Gibbs RA, Flicek P, Warkup CC, Jones HE, Oddy VH, Nicholas FW, McEwan JC, Kijas J, Wang J, Worley KC, Archibald AL, Cockett N, Xu X, Wang W, Dalrymple BP. The sheep genome illuminates biology of the rumen and lipid metabolism. Science 2014; 344:1168-1173. [PMID: 24904168 DOI: 10.1126/science.1252806] [Citation(s) in RCA: 321] [Impact Index Per Article: 32.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Sheep (Ovis aries) are a major source of meat, milk, and fiber in the form of wool and represent a distinct class of animals that have a specialized digestive organ, the rumen, that carries out the initial digestion of plant material. We have developed and analyzed a high-quality reference sheep genome and transcriptomes from 40 different tissues. We identified highly expressed genes encoding keratin cross-linking proteins associated with rumen evolution. We also identified genes involved in lipid metabolism that had been amplified and/or had altered tissue expression patterns. This may be in response to changes in the barrier lipids of the skin, an interaction between lipid metabolism and wool synthesis, and an increased role of volatile fatty acids in ruminants compared with nonruminant animals.
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Affiliation(s)
- Yu Jiang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia.,College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Min Xie
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Richard Talbot
- Ediburgh Genomics, University of Edinburgh, Easter Bush, Midlothian EH 25 9RG, UK
| | - Jillian F Maddox
- Department of Veterinary Science, University of Melbourne, Victoria 3010, Australia
| | - Thomas Faraut
- INRA, Laboratoire de Génétique Cellulaire, UMR 444, Castanet-Tolosan F-31326, France
| | - Chunhua Wu
- Utah State University, Logan, UT 84322-1435-1435, USA
| | - Donna M Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Wenguang Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China.,Inner Mongolia Agricultural University, Hohhot 010018, China.,Institute of ATCG, Nei Mongol Bio-Information, Hohhot, China
| | - Jo-Ann Stanton
- Department of Anatomy, University of Otago, Dunedin 9054, New Zealand
| | - Rudiger Brauning
- AgResearch, Invermay Agricultural Centre, Mosgiel 9053, New Zealand
| | - Wesley C Barris
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Thibaut Hourlier
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Bronwen L Aken
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK.,European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | - Stephen M J Searle
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - David L Adelson
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Chao Bian
- BGI-Shenzhen, Shenzhen 518083, China
| | - Graham R Cam
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Yulin Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | | | - Udaya DeSilva
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Karen Dixen
- Department of Biology, University of Copenhagen, DK-2100 Copenhagen Ø, Denmark
| | - Yang Dong
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | | | - Ian R Franklin
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Shaoyin Fu
- Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Rui Guan
- BGI-Shenzhen, Shenzhen 518083, China
| | - Margaret A Highland
- USDA-ARS Animal Disease Research Unit, Pullman, WA 99164 USA.,Department of Veterinary Microbiology & Pathology, Washington State University, Pullman, WA 99164 USA
| | - Michael E Holder
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Aaron B Ingham
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Shalini N Jhangiani
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Christie L Kovar
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Sandra L Lee
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | | | - Xin Liu
- BGI-Shenzhen, Shenzhen 518083, China
| | | | - Tian Lv
- BGI-Shenzhen, Shenzhen 518083, China
| | - Tittu Mathew
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Sean McWilliam
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Moira Menzies
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | | | - David Robelin
- INRA, Laboratoire de Génétique Cellulaire, UMR 444, Castanet-Tolosan F-31326, France
| | - Bertrand Servin
- INRA, Laboratoire de Génétique Cellulaire, UMR 444, Castanet-Tolosan F-31326, France
| | - David Townley
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | | | - Bin Wei
- BGI-Shenzhen, Shenzhen 518083, China.,Maize Research Institute, Sichuan Agricultural University, Chengdu 611130, China
| | - Stephen N White
- USDA-ARS Animal Disease Research Unit, Pullman, WA 99164 USA.,Department of Veterinary Microbiology & Pathology, Washington State University, Pullman, WA 99164 USA
| | | | - Chen Ye
- BGI-Shenzhen, Shenzhen 518083, China
| | - Yaojing Yue
- Lanzhou Institute of Husbandry and Pharmaceutical Science, Lanzhou,730050,China
| | - Peng Zeng
- BGI-Shenzhen, Shenzhen 518083, China
| | - Qing Zhou
- BGI-Shenzhen, Shenzhen 518083, China
| | - Jacob B Hansen
- Department of Biology, University of Copenhagen, DK-2100 Copenhagen Ø, Denmark
| | - Karsten Kristensen
- Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark
| | - Richard A Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SA, United Kingdom
| | | | - Huw E Jones
- Biosciences KTN, The Roslin Institute, Easter Bush, Midlothian, EH25 9RG, UK
| | - V Hutton Oddy
- School of Environmental and Rural Science, University of New England, Armidale, NSW 2351, Australia
| | - Frank W Nicholas
- Faculty of Veterinary Science, University of Sydney, NSW 2006, Australia
| | - John C McEwan
- AgResearch, Invermay Agricultural Centre, Mosgiel 9053, New Zealand
| | - James Kijas
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
| | - Jun Wang
- BGI-Shenzhen, Shenzhen 518083, China.,Department of Biology, University of Copenhagen, DK-2200 Copenhagen N, Denmark.,Princess Al Jawhara Center of Excellence in the Research of Hereditary Disorders, King Abdulaziz University, Jeddah 21589, Saudi Arabia.,Macau University of Science and Technology, Macau 999078, China
| | - Kim C Worley
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Alan L Archibald
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian EH 25 9RG, UK
| | | | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
| | - Brian P Dalrymple
- CSIRO Animal Food and Health Sciences, St Lucia, QLD 4067, Australia
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9
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Rowe SJ, Karacaören B, de Koning DJ, Lukic B, Hastings-Clark N, Velander I, Haley CS, Archibald AL. Analysis of the genetics of boar taint reveals both single SNPs and regional effects. BMC Genomics 2014; 15:424. [PMID: 24894739 PMCID: PMC4059876 DOI: 10.1186/1471-2164-15-424] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2013] [Accepted: 05/09/2014] [Indexed: 12/23/2022] Open
Abstract
Background Boar taint is an offensive urine or faecal-like odour, affecting the smell and taste of cooked pork from some mature non-castrated male pigs. Androstenone and skatole in fat are the molecules responsible. In most pig production systems, males, which are not required for breeding, are castrated shortly after birth to reduce the risk of boar taint. There is evidence for genetic variation in the predisposition to boar taint. A genome-wide association study (GWAS) was performed to identify loci with effects on boar taint. Five hundred Danish Landrace boars with high levels of skatole in fat (>0.3 μg/g), were each matched with a litter mate with low levels of skatole and measured for androstenone. DNA from these 1,000 non-castrated boars was genotyped using the Illumina PorcineSNP60 Beadchip. After quality control, tests for SNPs associated with boar taint were performed on 938 phenotyped individuals and 44,648 SNPs. Empirical significance thresholds were set by permutation (100,000). For androstenone, a ‘regional heritability approach’ combining information from multiple SNPs was used to estimate the genetic variation attributable to individual autosomes. Results A highly significant association was found between variation in skatole levels and SNPs within the CYP2E1 gene on chromosome 14 (SSC14), which encodes an enzyme involved in degradation of skatole. Nominal significance was found for effects on skatole associated with 4 other SNPs including a region of SSC6 reported previously. Genome-wide significance was found for an association between SNPs on SSC5 and androstenone levels and nominal significance for associations with SNPs on SSC13 and SSC17. The regional analyses confirmed large effects on SSC5 for androstenone and suggest that SSC5 explains 23% of the genetic variation in androstenone. The autosomal heritability analyses also suggest that there is a large effect associated with androstenone on SSC2, not detected using GWAS. Conclusions Significant SNP associations were found for skatole on SSC14 and for androstenone on SSC5 in Landrace pigs. The study agrees with evidence that the CYP2E1 gene has effects on skatole breakdown in the liver. Autosomal heritability estimates can uncover clusters of smaller genetic effects that individually do not exceed the threshold for GWAS significance. Electronic supplementary material The online version of this article (doi:10.1186/1471-2164-15-424) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Suzanne J Rowe
- The Roslin Institute and R(D)SVS, University of Edinburgh, Easter Bush, Midlothian, Scotland EH25 9RG, UK.
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10
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Sanchez MP, Tribout T, Iannuccelli N, Bouffaud M, Servin B, Tenghe A, Dehais P, Muller N, Del Schneider MP, Mercat MJ, Rogel-Gaillard C, Milan D, Bidanel JP, Gilbert H. A genome-wide association study of production traits in a commercial population of Large White pigs: evidence of haplotypes affecting meat quality. Genet Sel Evol 2014; 46:12. [PMID: 24528607 PMCID: PMC3975960 DOI: 10.1186/1297-9686-46-12] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2013] [Accepted: 12/13/2013] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Numerous quantitative trait loci (QTL) have been detected in pigs over the past 20 years using microsatellite markers. However, due to the low density of these markers, the accuracy of QTL location has generally been poor. Since 2009, the dense genome coverage provided by the Illumina PorcineSNP60 BeadChip has made it possible to more accurately map QTL using genome-wide association studies (GWAS). Our objective was to perform high-density GWAS in order to identify genomic regions and corresponding haplotypes associated with production traits in a French Large White population of pigs. METHODS Animals (385 Large White pigs from 106 sires) were genotyped using the PorcineSNP60 BeadChip and evaluated for 19 traits related to feed intake, growth, carcass composition and meat quality. Of the 64,432 SNPs on the chip, 44,412 were used for GWAS with an animal mixed model that included a regression coefficient for the tested SNPs and a genomic kinship matrix. SNP haplotype effects in QTL regions were then tested for association with phenotypes following phase reconstruction based on the Sscrofa10.2 pig genome assembly. RESULTS Twenty-three QTL regions were identified on autosomes and their effects ranged from 0.25 to 0.75 phenotypic standard deviation units for feed intake and feed efficiency (four QTL), carcass (12 QTL) and meat quality traits (seven QTL). The 10 most significant QTL regions had effects on carcass (chromosomes 7, 10, 16, 17 and 18) and meat quality traits (two regions on chromosome 1 and one region on chromosomes 8, 9 and 13). Thirteen of the 23 QTL regions had not been previously described. A haplotype block of 183 kb on chromosome 1 (six SNPs) was identified and displayed three distinct haplotypes with significant (0.0001 < P < 0.03) associations with all evaluated meat quality traits. CONCLUSIONS GWAS analyses with the PorcineSNP60 BeadChip enabled the detection of 23 QTL regions that affect feed consumption, carcass and meat quality traits in a LW population, of which 13 were novel QTL. The proportionally larger number of QTL found for meat quality traits suggests a specific opportunity for improving these traits in the pig by genomic selection.
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Affiliation(s)
- Marie-Pierre Sanchez
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | - Thierry Tribout
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | - Nathalie Iannuccelli
- INRA, UMR444 Laboratoire de Génétique Cellulaire, F-31326 Castanet-Tolosan, France
| | | | - Bertrand Servin
- INRA, UMR444 Laboratoire de Génétique Cellulaire, F-31326 Castanet-Tolosan, France
| | - Amabel Tenghe
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | - Patrice Dehais
- INRA, UMR444 Laboratoire de Génétique Cellulaire, F-31326 Castanet-Tolosan, France
| | - Nelly Muller
- INRA, UE450 Testage Porcs, F-35651 Le Rheu, France
| | - Maria Pilar Del Schneider
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | | | - Claire Rogel-Gaillard
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | - Denis Milan
- INRA, UMR444 Laboratoire de Génétique Cellulaire, F-31326 Castanet-Tolosan, France
| | - Jean-Pierre Bidanel
- INRA, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
- INRA, AgroParisTech, UMR1313 Génétique Animale et Biologie Intégrative, F-78350 Jouy-en-Josas, France
| | - Hélène Gilbert
- INRA, UMR444 Laboratoire de Génétique Cellulaire, F-31326 Castanet-Tolosan, France
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11
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Wang F, Xiao J, Cong W, Li A, Wei F, Xu J, Zhang C, Fan Z, He J, Wang S. Stage-specific differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs, Sus Scrofa. BMC Genomics 2014; 15:103. [PMID: 24498892 PMCID: PMC3937075 DOI: 10.1186/1471-2164-15-103] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2013] [Accepted: 01/28/2014] [Indexed: 12/11/2022] Open
Abstract
Background Our current knowledge of tooth development derives mainly from studies in mice, which have only one set of non-replaced teeth, compared with the diphyodont dentition in humans. The miniature pig is also diphyodont, making it a valuable alternative model for understanding human tooth development and replacement. However, little is known about gene expression and function during swine odontogenesis. The goal of this study is to undertake the survey of differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs. The identification of genes related to diphyodont development should lead to a better understanding of morphogenetic patterns and the mechanisms of diphyodont replacement in large animal models and humans. Results The temporal gene expression profiles during early diphyodont development in miniature pigs were detected with the Affymetrix Porcine GeneChip. The gene expression data were further evaluated by ANOVA as well as pathway and STC analyses. A total of 2,053 genes were detected with differential expression. Several signal pathways and 151 genes were then identified through the construction of pathway and signal networks. Conclusions The gene expression profiles indicated that spatio-temporal down-regulation patterns of gene expression were predominant; while, both dynamic activation and inhibition of pathways occurred during the morphogenesis of diphyodont dentition. Our study offers a mechanistic framework for understanding dynamic gene regulation of early diphyodont development and provides a molecular basis for studying teeth development, replacement, and regeneration in miniature pigs.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | - Songlin Wang
- Molecular Laboratory for Gene Therapy & Tooth Regeneration, Beijing Key Laboratory of Tooth Regeneration and Function Reconstruction, School of Stomatology, Capital Medical University, Tian Tan Xi Li No,4, Beijing 100050, PR China.
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