101
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Wang MS, Zhang JJ, Guo X, Li M, Meyer R, Ashari H, Zheng ZQ, Wang S, Peng MS, Jiang Y, Thakur M, Suwannapoom C, Esmailizadeh A, Hirimuthugoda NY, Zein MSA, Kusza S, Kharrati-Koopaee H, Zeng L, Wang YM, Yin TT, Yang MM, Li ML, Lu XM, Lasagna E, Ceccobelli S, Gunwardana HGTN, Senasig TM, Feng SH, Zhang H, Bhuiyan AKFH, Khan MS, Silva GLLP, Thuy LT, Mwai OA, Ibrahim MNM, Zhang G, Qu KX, Hanotte O, Shapiro B, Bosse M, Wu DD, Han JL, Zhang YP. Large-scale genomic analysis reveals the genetic cost of chicken domestication. BMC Biol 2021; 19:118. [PMID: 34130700 PMCID: PMC8207802 DOI: 10.1186/s12915-021-01052-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2020] [Accepted: 05/19/2021] [Indexed: 01/22/2023] Open
Abstract
BACKGROUND Species domestication is generally characterized by the exploitation of high-impact mutations through processes that involve complex shifting demographics of domesticated species. These include not only inbreeding and artificial selection that may lead to the emergence of evolutionary bottlenecks, but also post-divergence gene flow and introgression. Although domestication potentially affects the occurrence of both desired and undesired mutations, the way wild relatives of domesticated species evolve and how expensive the genetic cost underlying domestication is remain poorly understood. Here, we investigated the demographic history and genetic load of chicken domestication. RESULTS We analyzed a dataset comprising over 800 whole genomes from both indigenous chickens and wild jungle fowls. We show that despite having a higher genetic diversity than their wild counterparts (average π, 0.00326 vs. 0.00316), the red jungle fowls, the present-day domestic chickens experienced a dramatic population size decline during their early domestication. Our analyses suggest that the concomitant bottleneck induced 2.95% more deleterious mutations across chicken genomes compared with red jungle fowls, supporting the "cost of domestication" hypothesis. Particularly, we find that 62.4% of deleterious SNPs in domestic chickens are maintained in heterozygous states and masked as recessive alleles, challenging the power of modern breeding programs to effectively eliminate these genetic loads. Finally, we suggest that positive selection decreases the incidence but increases the frequency of deleterious SNPs in domestic chicken genomes. CONCLUSION This study reveals a new landscape of demographic history and genomic changes associated with chicken domestication and provides insight into the evolutionary genomic profiles of domesticated animals managed under modern human selection.
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Affiliation(s)
- Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China.,Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Jin-Jin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Xing Guo
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, 230036, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Rachel Meyer
- Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Hidayat Ashari
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Bogor, 16911, Indonesia.,CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China
| | - Zhu-Qing Zheng
- Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, The Cooperative Innovation Center for Sustainable Pig Production, Ministry of Education, Huazhong Agricultural University, Wuhan, 430070, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Mukesh Thakur
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Zoological Survey of India, New Alipore, Kolkata, West Bengal, 700053, India
| | - Chatmongkon Suwannapoom
- School of Agriculture and Natural Resources, University of Phayao, Phayao, 56000, Thailand.,Unit of Excellence on Biodiversity and Natural Resources Management, University of Phayao, Phayao, 56000, Thailand
| | - Ali Esmailizadeh
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Department of Animal Science, Shahid Bahonar University of Kerman, P.O. Box 76169133, Kerman, Iran
| | - Nalini Yasoda Hirimuthugoda
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Faculty of Agriculture, University of Ruhuna, Matara, Sri Lanka
| | - Moch Syamsul Arifin Zein
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Bogor, 16911, Indonesia
| | - Szilvia Kusza
- Institute of Animal Husbandry, Biotechnology and Nature Conservation, University of Debrecen, Debrecen, H-4032, Hungary
| | - Hamed Kharrati-Koopaee
- Department of Animal Science, Shahid Bahonar University of Kerman, P.O. Box 76169133, Kerman, Iran.,Institute of Biotechnology, School of Agriculture, Shiraz University, P.O. Box 1585, Shiraz, Iran
| | - Lin Zeng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Yun-Mei Wang
- Center for Neurobiology and Brain Restoration, Skolkovo Institute of Science and Technology, Moscow, 143026, Russia
| | - Ting-Ting Yin
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Min-Min Yang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Ming-Li Li
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China
| | - Xue-Mei Lu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650204, China
| | - Emiliano Lasagna
- Dipartimento di Scienze Agrarie, Alimentarie Ambientali, University of Perugia, 06123, Perugia, Italy
| | - Simone Ceccobelli
- Dipartimento di Scienze Agrarie, Alimentarie Ambientali, University of Perugia, 06123, Perugia, Italy
| | | | | | - Shao-Hong Feng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, 518083, China
| | - Hao Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Ministry of Agriculture of China, Beijing, 100193, China
| | | | | | | | - Le Thi Thuy
- National Institute of Animal Husbandry, Hanoi, Vietnam
| | - Okeyo A Mwai
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, 00100, Kenya
| | | | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China.,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650204, China.,China National Genebank, BGI-Shenzhen, Shenzhen, 518083, China.,Centre for Social Evolution, Department of Biology, University of Copenhagen, DK-1870, Copenhagen, Denmark
| | - Kai-Xing Qu
- Yunnan Academy of Grassland and Animal Science, Kunming, 650212, China
| | - Olivier Hanotte
- Cells, Organisms and Molecular Genetics, School of Life Sciences, University of Nottingham, Nottingham, NG7 2RD, UK.,Livestock Genetics Program, International Livestock Research Institute (ILRI), P.O. Box 5689, Addis Ababa, Ethiopia
| | - Beth Shapiro
- Howard Hughes Medical Institute, University of California Santa Cruz, Santa Cruz, CA, 95064, USA.,Department of Ecology and Evolutionary Biology, University of California Santa Cruz, Santa Cruz, CA, 95064, USA
| | - Mirte Bosse
- Wageningen University & Research - Animal Breeding and Genomics, 6708 PB, Wageningen, The Netherlands.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China. .,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650204, China.
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, 100193, China. .,Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, 00100, Kenya.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, 650223, China. .,Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, 650204, China. .,Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, 650204, China. .,State Key Laboratory for Conservation and Utilization of Bio-resource, Yunnan University, Kunming, 650091, China.
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102
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Herded and hunted goat genomes from the dawn of domestication in the Zagros Mountains. Proc Natl Acad Sci U S A 2021; 118:2100901118. [PMID: 34099576 PMCID: PMC8237664 DOI: 10.1073/pnas.2100901118] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
The Aceramic Neolithic (∼9600 to 7000 cal BC) period in the Zagros Mountains, western Iran, provides some of the earliest archaeological evidence of goat (Capra hircus) management and husbandry by circa 8200 cal BC, with detectable morphological change appearing ∼1,000 y later. To examine the genomic imprint of initial management and its implications for the goat domestication process, we analyzed 14 novel nuclear genomes (mean coverage 1.13X) and 32 mitochondrial (mtDNA) genomes (mean coverage 143X) from two such sites, Ganj Dareh and Tepe Abdul Hosein. These genomes show two distinct clusters: those with domestic affinity and a minority group with stronger wild affinity, indicating that managed goats were genetically distinct from wild goats at this early horizon. This genetic duality, the presence of long runs of homozygosity, shared ancestry with later Neolithic populations, a sex bias in archaeozoological remains, and demographic profiles from across all layers of Ganj Dareh support management of genetically domestic goat by circa 8200 cal BC, and represent the oldest to-this-date reported livestock genomes. In these sites a combination of high autosomal and mtDNA diversity, contrasting limited Y chromosomal lineage diversity, an absence of reported selection signatures for pigmentation, and the wild morphology of bone remains illustrates domestication as an extended process lacking a strong initial bottleneck, beginning with spatial control, demographic manipulation via biased male culling, captive breeding, and subsequently phenotypic and genomic selection.
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103
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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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104
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Chebii VJ, Mpolya EA, Muchadeyi FC, Domelevo Entfellner JB. Genomics of Adaptations in Ungulates. Animals (Basel) 2021; 11:1617. [PMID: 34072591 PMCID: PMC8230064 DOI: 10.3390/ani11061617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/22/2021] [Accepted: 05/23/2021] [Indexed: 11/16/2022] Open
Abstract
Ungulates are a group of hoofed animals that have long interacted with humans as essential sources of food, labor, clothing, and transportation. These consist of domesticated, feral, and wild species raised in a wide range of habitats and biomes. Given the diverse and extreme environments inhabited by ungulates, unique adaptive traits are fundamental for fitness. The documentation of genes that underlie their genomic signatures of selection is crucial in this regard. The increasing availability of advanced sequencing technologies has seen the rapid growth of ungulate genomic resources, which offers an exceptional opportunity to understand their adaptive evolution. Here, we summarize the current knowledge on evolutionary genetic signatures underlying the adaptations of ungulates to different habitats.
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Affiliation(s)
- Vivien J. Chebii
- School of Life Science and Bioengineering, Nelson Mandela Africa Institution of Science and Technology, P.O. Box 447, Arusha, Tanzania;
- Biosciences Eastern and Central Africa, International Livestock Research Institute (BecA-ILRI) Hub, P.O. Box 30709, Nairobi 00100, Kenya;
| | - Emmanuel A. Mpolya
- School of Life Science and Bioengineering, Nelson Mandela Africa Institution of Science and Technology, P.O. Box 447, Arusha, Tanzania;
| | - Farai C. Muchadeyi
- Agricultural Research Council Biotechnology Platform (ARC-BTP), Private Bag X5, Onderstepoort 0110, South Africa;
| | - Jean-Baka Domelevo Entfellner
- Biosciences Eastern and Central Africa, International Livestock Research Institute (BecA-ILRI) Hub, P.O. Box 30709, Nairobi 00100, Kenya;
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105
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Martin FJ, Gall A, Szpak M, Flicek P. Accessing Livestock Resources in Ensembl. Front Genet 2021; 12:650228. [PMID: 33995484 PMCID: PMC8115729 DOI: 10.3389/fgene.2021.650228] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 03/18/2021] [Indexed: 12/12/2022] Open
Abstract
Genome assembly is cheaper, more accurate and more automated than it has ever been. This is due to a combination of more cost-efficient chemistries, new sequencing technologies and better algorithms. The livestock community has been at the forefront of this new wave of genome assembly, generating some of the highest quality vertebrate genome sequences. Ensembl's goal is to add functional and comparative annotation to these genomes, through our gene annotation, genomic alignments, gene trees, regulatory, and variation data. We run computationally complex analyses in a high throughput and consistent manner to help accelerate downstream science. Our livestock resources are continuously growing in both breadth and depth. We annotate reference genome assemblies for newly sequenced species and regularly update annotation for existing genomes. We are the only major resource to support the annotation of breeds and other non-reference assemblies. We currently provide resources for 13 pig breeds, maternal and paternal haplotypes for hybrid cattle and various other non-reference or wild type assemblies for livestock species. Here, we describe the livestock data present in Ensembl and provide protocols for how to view data in our genome browser, download via it our FTP site, manipulate it via our tools and interact with it programmatically via our REST API.
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Affiliation(s)
- Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Astrid Gall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Michal Szpak
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Cambridge, United Kingdom
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106
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Olazcuaga L, Loiseau A, Parrinello H, Paris M, Fraimout A, Guedot C, Diepenbrock LM, Kenis M, Zhang J, Chen X, Borowiec N, Facon B, Vogt H, Price DK, Vogel H, Prud'homme B, Estoup A, Gautier M. A Whole-Genome Scan for Association with Invasion Success in the Fruit Fly Drosophila suzukii Using Contrasts of Allele Frequencies Corrected for Population Structure. Mol Biol Evol 2021; 37:2369-2385. [PMID: 32302396 PMCID: PMC7403613 DOI: 10.1093/molbev/msaa098] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Evidence is accumulating that evolutionary changes are not only common during biological invasions but may also contribute directly to invasion success. The genomic basis of such changes is still largely unexplored. Yet, understanding the genomic response to invasion may help to predict the conditions under which invasiveness can be enhanced or suppressed. Here, we characterized the genome response of the spotted wing drosophila Drosophila suzukii during the worldwide invasion of this pest insect species, by conducting a genome-wide association study to identify genes involved in adaptive processes during invasion. Genomic data from 22 population samples were analyzed to detect genetic variants associated with the status (invasive versus native) of the sampled populations based on a newly developed statistic, we called C2, that contrasts allele frequencies corrected for population structure. We evaluated this new statistical framework using simulated data sets and implemented it in an upgraded version of the program BayPass. We identified a relatively small set of single-nucleotide polymorphisms that show a highly significant association with the invasive status of D. suzukii populations. In particular, two genes, RhoGEF64C and cpo, contained single-nucleotide polymorphisms significantly associated with the invasive status in the two separate main invasion routes of D. suzukii. Our methodological approaches can be applied to any other invasive species, and more generally to any evolutionary model for species characterized by nonequilibrium demographic conditions for which binary covariables of interest can be defined at the population level.
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Affiliation(s)
- Laure Olazcuaga
- INRAE, UMR CBGP (INRAE-IRD-Cirad - Montpellier SupAgro), Montferrier-sur-Lez, France
| | - Anne Loiseau
- INRAE, UMR CBGP (INRAE-IRD-Cirad - Montpellier SupAgro), Montferrier-sur-Lez, France
| | - Hugues Parrinello
- MGX, Biocampus Montpellier, CNRS, INSERM, Universite de Montpellier, Montpellier, France
| | | | - Antoine Fraimout
- INRAE, UMR CBGP (INRAE-IRD-Cirad - Montpellier SupAgro), Montferrier-sur-Lez, France
| | | | | | | | - Jinping Zhang
- MoA-CABI Joint Laboratory for Bio-Safety, Chinese Academy of Agricultural Sciences, BeiXiaGuan, Haidian Qu, China
| | - Xiao Chen
- College of Plant Protection, Yunnan Agricultural University, Kunming, Yunnan Province, China
| | - Nicolas Borowiec
- UMR INRAE-CNRS-Université Côte d'Azur Sophia Agrobiotech Institute, Sophia Antipolis, France
| | - Benoit Facon
- UMR Peuplements Végétaux et Bioagresseurs en Milieu Tropical, INRAE, Saint-Pierre, La Réunion, France
| | - Heidrun Vogt
- Julius Kühn-Institut (JKI), Federal Research Centre for Cultivated Plants, Institute for Plant Protection in Fruit Crops and Viticulture, Dossenheim, Germany
| | - Donald K Price
- School of Life Sciences, University of Nevada, Las Vegas, Las Vegas, NV
| | - Heiko Vogel
- Department of Entomology, Max Planck Institute for Chemical Ecology, Jena, Germany
| | | | - Arnaud Estoup
- INRAE, UMR CBGP (INRAE-IRD-Cirad - Montpellier SupAgro), Montferrier-sur-Lez, France
| | - Mathieu Gautier
- INRAE, UMR CBGP (INRAE-IRD-Cirad - Montpellier SupAgro), Montferrier-sur-Lez, France
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107
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British Sheep Breeds as a Part of World Sheep Gene Pool Landscape: Looking into Genomic Applications. Animals (Basel) 2021; 11:ani11040994. [PMID: 33916207 PMCID: PMC8103502 DOI: 10.3390/ani11040994] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2021] [Revised: 03/27/2021] [Accepted: 03/29/2021] [Indexed: 01/18/2023] Open
Abstract
Sheep farming has been an important sector of the UK's economy and rural life for many centuries. It is the favored source of wool, meat and milk products. In the era of exponential progress in genomic technologies, we can now address the questions of what is special about UK sheep breed genotypes and how they differ genetically form one another and from other countries. We can reflect how their natural history has been determined at the level of their genetic code and what traces have been left in their genomes because of selection for phenotypic traits. These include adaptability to certain environmental conditions and management, as well as resistance to disease. Application of these advancements in genetics and genomics to study sheep breeds of British domestic selection has begun and will continue in order to facilitate conservation solutions and production improvement.
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108
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Tao L, He X, Jiang Y, Liu Y, Ouyang Y, Shen Y, Hong Q, Chu M. Genome-Wide Analyses Reveal Genetic Convergence of Prolificacy between Goats and Sheep. Genes (Basel) 2021; 12:480. [PMID: 33810234 PMCID: PMC8065816 DOI: 10.3390/genes12040480] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 03/16/2021] [Accepted: 03/23/2021] [Indexed: 12/20/2022] Open
Abstract
The litter size of domestic goats and sheep is an economically important trait that shows variation within breeds. Strenuous efforts have been made to understand the genetic mechanisms underlying prolificacy in goats and sheep. However, there has been a paucity of research on the genetic convergence of prolificacy between goats and sheep, which likely arose because of similar natural and artificial selection forces. Here, we performed comparative genomic and transcriptomic analyses to identify the genetic convergence of prolificacy between goats and sheep. By combining genomic and transcriptomic data for the first time, we identified this genetic convergence in (1) positively selected genes (CHST11 and SDCCAG8), (2) differentially expressed genes (SERPINA14, RSAD2, and PPIG at follicular phase, and IGF1, GPRIN3, LIPG, SLC7A11, and CHST15 at luteal phase), and (3) biological pathways (genomic level: osteoclast differentiation, ErbB signaling pathway, and relaxin signaling pathway; transcriptomic level: the regulation of viral genome replication at follicular phase, and protein kinase B signaling and antigen processing and presentation at luteal phase). These results indicated the potential physiological convergence and enhanced our understanding of the overlapping genetic makeup underlying litter size in goats and sheep.
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Affiliation(s)
- Lin Tao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (L.T.); (X.H.); (Y.L.)
| | - Xiaoyun He
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (L.T.); (X.H.); (Y.L.)
| | - Yanting Jiang
- Yunnan Animal Science and Veterinary Institute, Kunming 650224, China; (Y.J.); (Y.O.)
| | - Yufang Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (L.T.); (X.H.); (Y.L.)
- College of Life Science and Food Engineering, Hebei University of Engineering, Handan 056038, China
| | - Yina Ouyang
- Yunnan Animal Science and Veterinary Institute, Kunming 650224, China; (Y.J.); (Y.O.)
| | - Yezhen Shen
- Annoroad Gene Technology Co., Ltd., Beijing 100176, China;
| | - Qionghua Hong
- Yunnan Animal Science and Veterinary Institute, Kunming 650224, China; (Y.J.); (Y.O.)
| | - Mingxing Chu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Ministry of Agriculture and Rural Affairs, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing 100193, China; (L.T.); (X.H.); (Y.L.)
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109
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Fu W, Wang R, Yu J, Hu D, Cai Y, Shao J, Jiang Y. GGVD: A goat genome variation database for tracking the dynamic evolutionary process of selective signatures and ancient introgressions. J Genet Genomics 2021; 48:248-256. [PMID: 33965348 DOI: 10.1016/j.jgg.2021.03.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 03/12/2021] [Accepted: 03/13/2021] [Indexed: 11/20/2022]
Abstract
Understanding the evolutionary history and adaptive process depends on the knowledge that we can acquire from both ancient and modern genomic data. With the availability of a deluge of whole-genome sequencing data from ancient and modern goat samples, a user-friendly database making efficient reuse of these important resources is needed. Here, we use the genomes of 208 modern domestic goats, 24 bezoars, 46 wild ibexes, and 82 ancient goats to present a comprehensive goat genome variation database (GGVD). GGVD hosts a total of ∼41.44 million SNPs, ∼5.14 million indels, 6,193 selected loci, and 112 introgression regions. Users can freely visualize the frequency of genomic variations in geographical maps, selective sweeps in interactive tables, Manhattan plots, or line charts, as well as the heatmap patterns of the SNP genotype. Ancient data can be shown in haplotypes to track the state of genetic variants of selection and introgression events in the early, middle, and late stages. For facilitating access to sequence features, the UCSC Genome Browser, BLAT, BLAST, LiftOver, and pcadapt are also integrated into GGVD. GGVD will be a convenient tool for population genetic studies and molecular marker designing in goat breeding programs, and it is publicly available at http://animal.nwsuaf.edu.cn/GoatVar.
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Affiliation(s)
- Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Rui Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Jiantao Yu
- College of Information Engineering, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Dexiang Hu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Junjie Shao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi 712100, China.
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110
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Rochat E, Selmoni O, Joost S. Spatial areas of genotype probability: Predicting the spatial distribution of adaptive genetic variants under future climatic conditions. DIVERS DISTRIB 2021. [DOI: 10.1111/ddi.13256] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Affiliation(s)
- Estelle Rochat
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Oliver Selmoni
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
| | - Stéphane Joost
- Laboratory of Geographic Information Systems (LASIG) School of Architecture, Civil and Environmental Engineering (ENAC) Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland
- The NEXTGEN Consortium
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111
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Cao YH, Xu SS, Shen M, Chen ZH, Gao L, Lv FH, Xie XL, Wang XH, Yang H, Liu CB, Zhou P, Wan PC, Zhang YS, Yang JQ, Pi WH, Hehua EE, Berry DP, Barbato M, Esmailizadeh A, Nosrati M, Salehian-Dehkordi H, Dehghani-Qanatqestani M, Dotsev AV, Deniskova TE, Zinovieva NA, Brem G, Štěpánek O, Ciani E, Weimann C, Erhardt G, Mwacharo JM, Ahbara A, Han JL, Hanotte O, Miller JM, Sim Z, Coltman D, Kantanen J, Bruford MW, Lenstra JA, Kijas J, Li MH. Historical Introgression from Wild Relatives Enhanced Climatic Adaptation and Resistance to Pneumonia in Sheep. Mol Biol Evol 2021; 38:838-855. [PMID: 32941615 PMCID: PMC7947771 DOI: 10.1093/molbev/msaa236] [Citation(s) in RCA: 43] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
How animals, particularly livestock, adapt to various climates and environments over short evolutionary time is of fundamental biological interest. Further, understanding the genetic mechanisms of adaptation in indigenous livestock populations is important for designing appropriate breeding programs to cope with the impacts of changing climate. Here, we conducted a comprehensive genomic analysis of diversity, interspecies introgression, and climate-mediated selective signatures in a global sample of sheep and their wild relatives. By examining 600K and 50K genome-wide single nucleotide polymorphism data from 3,447 samples representing 111 domestic sheep populations and 403 samples from all their seven wild relatives (argali, Asiatic mouflon, European mouflon, urial, snow sheep, bighorn, and thinhorn sheep), coupled with 88 whole-genome sequences, we detected clear signals of common introgression from wild relatives into sympatric domestic populations, thereby increasing their genomic diversities. The introgressions provided beneficial genetic variants in native populations, which were significantly associated with local climatic adaptation. We observed common introgression signals of alleles in olfactory-related genes (e.g., ADCY3 and TRPV1) and the PADI gene family including in particular PADI2, which is associated with antibacterial innate immunity. Further analyses of whole-genome sequences showed that the introgressed alleles in a specific region of PADI2 (chr2: 248,302,667-248,306,614) correlate with resistance to pneumonia. We conclude that wild introgression enhanced climatic adaptation and resistance to pneumonia in sheep. This has enabled them to adapt to varying climatic and environmental conditions after domestication.
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Affiliation(s)
- Yin-Hong Cao
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Song-Song Xu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Min Shen
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Ze-Hui Chen
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Lei Gao
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Feng-Hua Lv
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | - Xin-Hua Wang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Hua Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Chang-Bin Liu
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Ping Zhou
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Peng-Cheng Wan
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Yun-Sheng Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Jing-Quan Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - Wen-Hui Pi
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- Xinjiang Academy of Agricultural and Reclamation Sciences, State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Shihezi, China
| | - EEr Hehua
- Institute of Animal Science, Ningxia Academy of Agriculture and Forestry Sciences, Hui Autonomous Region, Yinchuan, Ningxia, China
| | - Donagh P Berry
- Animal and Grassland Research and Innovation Centre, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
| | - Mario Barbato
- Department of Animal Sciences, Food and Nutrition, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Maryam Nosrati
- Department of Agriculture, Payame Noor University, Tehran, Iran
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Life Sciences, University of Chinese Academy of Sciences (UCAS), Beijing, China
| | | | - Arsen V Dotsev
- L.K. Ernst Federal Science Center for Animal Husbandry, Moscow Region, Podolsk, Russian Federation
| | - Tatiana E Deniskova
- L.K. Ernst Federal Science Center for Animal Husbandry, Moscow Region, Podolsk, Russian Federation
| | - Natalia A Zinovieva
- L.K. Ernst Federal Science Center for Animal Husbandry, Moscow Region, Podolsk, Russian Federation
| | - Gottfried Brem
- Institute of Animal Breeding and Genetics, University of Veterinary Medicine, Vienna, Austria
| | - Ondřej Štěpánek
- Department of Virology, State Veterinary Institute Jihlava, Jihlava, Czech Republic
| | - Elena Ciani
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, Università degli Studi di Bari Aldo 24, Moro, Bari, Italy
| | - Christina Weimann
- Department of Animal Breeding and Genetics, Justus-Liebig-University Giessen, Giessen, Germany
| | - Georg Erhardt
- Department of Animal Breeding and Genetics, Justus-Liebig-University Giessen, Giessen, Germany
| | - Joram M Mwacharo
- Small Ruminant Genomics, International Center for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Abulgasim Ahbara
- School of Life Sciences, University of Nottingham, University Park, Nottingham, United Kingdom
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Olivier Hanotte
- School of Life Sciences, University of Nottingham, University Park, Nottingham, United Kingdom
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Addis Abeba, Ethiopia
- Center for Tropical Livestock Genetics and Health (CTLGH), The Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, United Kingdom
| | - Joshua M Miller
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Zijian Sim
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
- Fish and Wildlife Enforcement Branch Forensic Unit, Government of Alberta, Edmonton, AB, Canada
| | - David Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Cathays Park, Cardiff, United Kingdom
- Sustainable Places Research Institute, Cardiff University, Cardiff, United Kingdom
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands
| | - James Kijas
- Commonwealth Scientific and Industrial Research Organisation Agriculture and Food, Queensland Bioscience Precinct, St Lucia, Brisbane, QLD, Australia
| | - Meng-Hua Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, China
- College of Animal Science and Technology, China Agricultural University, Beijing, China
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112
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Raoult CMC, Osthaus B, Hildebrand ACG, McElligott AG, Nawroth C. Goats show higher behavioural flexibility than sheep in a spatial detour task. ROYAL SOCIETY OPEN SCIENCE 2021; 8:201627. [PMID: 33959332 PMCID: PMC8074883 DOI: 10.1098/rsos.201627] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 02/03/2021] [Indexed: 06/12/2023]
Abstract
The ability to adapt to changing environments is crucial for survival and has evolved based on socio-ecological factors. Goats and sheep are closely related, with similar social structures, body sizes and domestication levels, but different feeding ecologies, i.e. goats are browsers and sheep are grazers. We investigated whether goats' reliance on more patchily distributed food sources predicted an increased behavioural flexibility compared to sheep. We tested 21 goats and 28 sheep in a spatial A-not-B detour task. Subjects had to navigate around a straight barrier through a gap at its edge. After one, two, three or four of these initial A trials, the gap was moved to the opposite end and subjects performed four B trials. Behaviourally more flexible individuals should move through the new gap faster, while those less behaviourally flexible should show greater perseveration. While both species showed an accuracy reduction following the change of the gap position, goats recovered from this perseveration error from the second B trial onwards, whereas sheep did so only in the fourth B trial, indicating differences in behavioural flexibility between the species. This higher degree of flexibility in goats compared to sheep could be linked to differences in their foraging strategies.
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Affiliation(s)
- C. M. C. Raoult
- Animal Husbandry and Animal Ecology, Institute of Agricultural and Nutritional Sciences, Martin-Luther University of Halle-Wittenberg, 06120 Halle, Germany
- Centre for Proper Housing of Ruminants and Pigs, FSVO, Agroscope Tänikon, 8356 Ettenhausen, Switzerland
| | - B. Osthaus
- School of Psychology and Life Sciences, Canterbury Christ Church University, Canterbury CT1 1QU, UK
| | - A. C. G. Hildebrand
- Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
| | - A. G. McElligott
- Jockey Club College of Veterinary Medicine and Life Sciences, City University of Hong Kong, Kowloon, Hong Kong SAR, People's Republic of China
| | - C. Nawroth
- Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London E1 4NS, UK
- Institute of Behavioural Physiology, Leibniz Institute for Farm Animal Biology, 18196 Dummerstorf, Germany
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113
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Bay V, Keleş M, Aymaz R, Hatipoğlu E, Öner Y, Yaman Y. Documentation of extensive genetic diversity in the Ovar- DRB1 gene in native Turkish sheep. Anim Biotechnol 2021; 32:507-518. [PMID: 33606604 DOI: 10.1080/10495398.2021.1884086] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
Indigenous breeds have a high level of genetic diversity that might contribute to develop animal breeds with desired traits such as disease resistance and high productivity. Major histocompatibility complex (MHC) is a key component of adaptive immune system and consists of highly polymorphic genes that take part in adaptive immune response and disease resistance. Exploring and understanding the effect of polymorphisms in MHC could be beneficial to future animal breeding strategies. In this study, we sequenced the highly polymorphic Exon2 of the ovine DRB1 gene using Sanger sequencing to explore the diversity of this gene in six indigenous Turkish sheep breeds and two crossbreeds. In total, 894 haplotypes from 447 sheep were investigated, and 69 different haplotypes including 27 novel ones were identified. Among the identified haplotypes there were common and breed specific haplotypes. There was a relatively high diversity of the alleles within indigenous breeds. Allelic diversity patterns were mostly associated with geographical differences. The results of this study highlight the genetic variation within indigenous breeds which has important implications for biodiversity and the adaptability of breeds to specific environments. There is value to further studies which include other genomic regions and traits, and these could guide breeding strategies.
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Affiliation(s)
- Veysel Bay
- Department of Biometrics and Genetics, Sheep Breeding and Research Institute, Bandirma, Balıkesir, Turkey
| | - Murat Keleş
- Department of Biometrics and Genetics, Sheep Breeding and Research Institute, Bandirma, Balıkesir, Turkey
| | - Ramazan Aymaz
- Department of Biometrics and Genetics, Sheep Breeding and Research Institute, Bandirma, Balıkesir, Turkey
| | - Ecem Hatipoğlu
- Department of Biometrics and Genetics, Sheep Breeding and Research Institute, Bandirma, Balıkesir, Turkey
| | - Yasemin Öner
- Department of Biometry and Genetics, Faculty of Agriculture, Uludağ University, Bursa, Turkey
| | - Yalçın Yaman
- Department of Biometrics and Genetics, Sheep Breeding and Research Institute, Bandirma, Balıkesir, Turkey
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114
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Pacheco G, van Grouw H, Shapiro MD, Gilbert MTP, Vieira FG. Darwin's Fancy Revised: An Updated Understanding of the Genomic Constitution of Pigeon Breeds. Genome Biol Evol 2021; 12:136-150. [PMID: 32053199 PMCID: PMC7144551 DOI: 10.1093/gbe/evaa027] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/05/2020] [Indexed: 12/14/2022] Open
Abstract
Through its long history of artificial selection, the rock pigeon (Columba livia Gmelin 1789) was forged into a large number of domestic breeds. The incredible amount of phenotypic diversity exhibited in these breeds has long held the fascination of scholars, particularly those interested in biological inheritance and evolution. However, exploiting them as a model system is challenging, as unlike with many other domestic species, few reliable records exist about the origins of, and relationships between, each of the breeds. Therefore, in order to broaden our understanding of the complex evolutionary relationships among pigeon breeds, we generated genome-wide data by performing the genotyping-by-sequencing (GBS) method on close to 200 domestic individuals representing over 60 breeds. We analyzed these GBS data alongside previously published whole-genome sequencing data, and this combined analysis allowed us to conduct the most extensive phylogenetic analysis of the group, including two feral pigeons and one outgroup. We improve previous phylogenies, find considerable population structure across the different breeds, and identify unreported interbreed admixture events. Despite the reduced number of loci relative to whole-genome sequencing, we demonstrate that GBS data provide sufficient analytical power to investigate intertwined evolutionary relationships, such as those that are characteristic of animal domestic breeds. Thus, we argue that future studies should consider sequencing methods akin to the GBS approach as an optimal cost-effective approach for addressing complex phylogenies.
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Affiliation(s)
- George Pacheco
- Natural History Museum of Denmark, Faculty of Science, University of Copenhagen, Denmark.,The GLOBE Institute, Faculty of Health and Biomedical Sciences, University of Copenhagen, Denmark
| | - Hein van Grouw
- Bird Group, Department of Life Sciences, Natural History Museum, Tring, Hertfordshire, United Kingdom
| | | | - Marcus Thomas P Gilbert
- Natural History Museum of Denmark, Faculty of Science, University of Copenhagen, Denmark.,The GLOBE Institute, Faculty of Health and Biomedical Sciences, University of Copenhagen, Denmark.,NTNU University Museum, Norwegian University of Science and Technology, Trondheim, Norway
| | - Filipe Garrett Vieira
- Natural History Museum of Denmark, Faculty of Science, University of Copenhagen, Denmark
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115
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Eydivandi S, Roudbar MA, Karimi MO, Sahana G. Genomic scans for selective sweeps through haplotype homozygosity and allelic fixation in 14 indigenous sheep breeds from Middle East and South Asia. Sci Rep 2021; 11:2834. [PMID: 33531649 PMCID: PMC7854752 DOI: 10.1038/s41598-021-82625-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 01/22/2021] [Indexed: 01/30/2023] Open
Abstract
The performance and productivity of livestock have consistently improved by natural and artificial selection over the centuries. Both these selections are expected to leave patterns on the genome and lead to changes in allele frequencies, but natural selection has played the major role among indigenous populations. Detecting selective sweeps in livestock may assist in understanding the processes involved in domestication, genome evolution and discovery of genomic regions associated with economically important traits. We investigated population genetic diversity and selection signals in this study using SNP genotype data of 14 indigenous sheep breeds from Middle East and South Asia, including six breeds from Iran, namely Iranian Balochi, Afshari, Moghani, Qezel, Zel, and Lori-Bakhtiari, three breeds from Afghanistan, namely Afghan Balochi, Arabi, and Gadik, three breeds from India, namely Indian Garole, Changthangi, and Deccani, and two breeds from Bangladesh, namely Bangladeshi Garole and Bangladesh East. The SNP genotype data were generated by the Illumina OvineSNP50 Genotyping BeadChip array. To detect genetic diversity and population structure, we used principal component analysis (PCA), admixture, phylogenetic analyses, and Runs of homozygosity. We applied four complementary statistical tests, FST (fixation index), xp-EHH (cross-population extended haplotype homozygosity), Rsb (extended haplotype homozygosity between-populations), and FLK (the extension of the Lewontin and Krakauer) to detect selective sweeps. Our results not only confirm the previous studies but also provide a suite of novel candidate genes involved in different traits in sheep. On average, FST, xp-EHH, Rsb, and FLK detected 128, 207, 222, and 252 genomic regions as candidates for selective sweeps, respectively. Furthermore, nine overlapping candidate genes were detected by these four tests, especially TNIK, DOCK1, USH2A, and TYW1B which associate with resistance to diseases and climate adaptation. Knowledge of candidate genomic regions in sheep populations may facilitate the identification and potential exploitation of the underlying genes in sheep breeding.
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Affiliation(s)
- Sirous Eydivandi
- Department of Animal Science, Behbahan Branch, Islamic Azad University, Behbahan, Iran.
- Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830, Tjele, Denmark.
| | - Mahmoud Amiri Roudbar
- Department of Animal Science, Safiabad-Dezful Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Dezful, Iran
| | - Mohammad Osman Karimi
- Department of Animal Science, Faculty of Agriculture, Herat University, Herat, Afghanistan
| | - Goutam Sahana
- Center for Quantitative Genetics and Genomics, Faculty of Technical Sciences, Aarhus University, 8830, Tjele, Denmark
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116
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Genome-wide comparative analyses reveal selection signatures underlying adaptation and production in Tibetan and Poll Dorset sheep. Sci Rep 2021; 11:2466. [PMID: 33510350 PMCID: PMC7844035 DOI: 10.1038/s41598-021-81932-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2020] [Accepted: 01/11/2021] [Indexed: 12/14/2022] Open
Abstract
The identification of genome-wide selection signatures can provide insights on the mechanisms of natural and/or artificial selection and uncover genes related to biological functions and/or phenotypes. Tibetan sheep are an important livestock in Tibet, providing meat and wool for Tibetans who are renown for breeding livestock that adapt well to high altitudes. Using whole-genome sequences with an effective sequencing depth of 5×, we investigated the genomic diversity and structure and, identified selection signatures of White Tibetan, Oula and Poll Dorset sheep. We obtained 30,163,679 Single Nucleotide Polymorphisms (SNPs) and 5,388,372 indels benchmarked against the ovine Oar_v4.0 genome assembly. Next, using FST, ZHp and XP-EHH approaches, we identified selection signatures spanning a set of candidate genes, including HIF1A, CAPN3, PRKAA1, RXFP2, TRHR and HOXA10 that are associated with pathways and GO categories putatively related to hypoxia responses, meat traits and disease resistance. Candidate genes and GO terms associated with coat color were also identified. Finally, quantification of blood physiological parameters, revealed higher levels of mean corpuscular hemoglobin measurement and mean corpuscular hemoglobin concentration in Tibetan sheep compared with Poll Dorset, suggesting a greater oxygen-carrying capacity in the Tibetan sheep and thus better adaptation to high-altitude hypoxia. In conclusion, this study provides a greater understanding of genome diversity and variations associated with adaptive and production traits in sheep.
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117
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Huang Y, Li Y, Wang X, Yu J, Cai Y, Zheng Z, Li R, Zhang S, Chen N, Asadollahpour Nanaei H, Hanif Q, Chen Q, Fu W, Li C, Cao X, Zhou G, Liu S, He S, Li W, Chen Y, Chen H, Lei C, Liu M, Jiang Y. An atlas of CNV maps in cattle, goat and sheep. SCIENCE CHINA-LIFE SCIENCES 2021; 64:1747-1764. [PMID: 33486588 DOI: 10.1007/s11427-020-1850-x] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2020] [Accepted: 11/16/2020] [Indexed: 11/26/2022]
Abstract
Copy number variation (CNV) is the most prevalent type of genetic structural variation that has been recognized as an important source of phenotypic variation in humans, animals and plants. However, the mechanisms underlying the evolution of CNVs and their function in natural or artificial selection remain unknown. Here, we generated CNV region (CNVR) datasets which were diverged or shared among cattle, goat, and sheep, including 886 individuals from 171 diverse populations. Using 9 environmental factors for genome-wide association study (GWAS), we identified a series of candidate CNVRs, including genes relating to immunity, tick resistance, multi-drug resistance, and muscle development. The number of CNVRs shared between species is significantly higher than expected (P<0.00001), and these CNVRs may be more persist than the single nucleotide polymorphisms (SNPs) shared between species. We also identified genomic regions under long-term balancing selection and uncovered the potential diversity of the selected CNVRs close to the important functional genes. This study provides the evidence that balancing selection might be more common in mammals than previously considered, and might play an important role in the daily activities of these ruminant species.
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Affiliation(s)
- Yongzhen Huang
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Yunjia Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xihong Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Jiantao Yu
- College of Information Engineering, Northwest A&F University, Yangling, 712100, China
| | - Yudong Cai
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Zhuqing Zheng
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Ran Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Shunjin Zhang
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Ningbo Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | | | - Quratulain Hanif
- National Institute for Biotechnology and Genetic Engineering (NIBGE), Faisalabad, Punjab, 577, Pakistan
- Pakistan Institute of Engineering & Applied Sciences (PIEAS), Nilore, 45650, Islamabad, Pakistan
| | - Qiuming Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Weiwei Fu
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Chao Li
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xiukai Cao
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Guangxian Zhou
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Shudong Liu
- College of Information Engineering, Northwest A&F University, Yangling, 712100, China
| | - Sangang He
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Biotechnology Research Institute, Xinjiang Academy of Animal Sciences, Urumqi, 830026, China
| | - Wenrong Li
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Biotechnology Research Institute, Xinjiang Academy of Animal Sciences, Urumqi, 830026, China
| | - Yulin Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Hong Chen
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Chuzhao Lei
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Mingjun Liu
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Biotechnology Research Institute, Xinjiang Academy of Animal Sciences, Urumqi, 830026, China
| | - Yu Jiang
- College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China.
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Eydivandi S, Roudbar MA, Ardestani SS, Momen M, Sahana G. A selection signatures study among Middle Eastern and European sheep breeds. J Anim Breed Genet 2021; 138:574-588. [PMID: 33453096 DOI: 10.1111/jbg.12536] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 11/25/2020] [Accepted: 12/26/2020] [Indexed: 01/26/2023]
Abstract
Selection, both natural and artificial, leaves patterns on the genome during domestication of animals and leads to changes in allele frequencies among populations. Detecting genomic regions influenced by selection in livestock may assist in understanding the processes involved in genome evolution and discovering genomic regions related to traits of economic and ecological interests. In the current study, genetic diversity analyses were conducted on 34,206 quality-filtered SNP positions from 450 individuals in 15 sheep breeds, including six indigenous breeds from the Middle East, namely Iranian Balouchi, Afshari, Moghani, Qezel, Karakas and Norduz, and nine breeds from Europe, namely East Friesian Sheep, Ile de France, Mourerous, Romane, Swiss Mirror, Spaelsau, Suffolk, Comisana and Engadine Red Sheep. The SNP genotype data generated by the Illumina OvineSNP50 Genotyping BeadChip array were used in this analysis. We applied two complementary statistical analyses, FST (fixation index) and xp-EHH (cross-population extended haplotype homozygosity), to detect selection signatures in Middle Eastern and European sheep populations. FST and xp-EHH detected 629 and 256 genes indicating signatures of selection, respectively. Genomic regions identified using FST and xp-EHH contained the CIDEA, HHATL, MGST1, FADS1, RTL1 and DGKG genes, which were reported earlier to influence a number of economic traits. Both FST and xp-EHH approaches identified 60 shared genes as the signatures of selection, including four candidate genes (NT5E, ADA2, C8A and C8B) that were enriched for two significant Gene Ontology (GO) terms associated with the adenosine metabolic procedure. Knowledge about the candidate genomic regions under selective pressure in sheep breeds may facilitate identification of the underlying genes and enhance our understanding on these genes role in local adaptation.
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Affiliation(s)
- Sirous Eydivandi
- Department of Animal Science, Behbahan Branch, Islamic Azad University, Behbahan, Iran.,Faculty of Technical Sciences, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
| | - Mahmoud Amiri Roudbar
- Department of Animal Science, Safiabad-Dezful Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization (AREEO), Dezful, Iran
| | | | - Mehdi Momen
- Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Goutam Sahana
- Faculty of Technical Sciences, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, Denmark
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119
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Dzomba EF, Chimonyo M, Pierneef R, Muchadeyi FC. Runs of homozygosity analysis of South African sheep breeds from various production systems investigated using OvineSNP50k data. BMC Genomics 2021; 22:7. [PMID: 33407115 PMCID: PMC7788743 DOI: 10.1186/s12864-020-07314-2] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 12/07/2020] [Indexed: 12/28/2022] Open
Abstract
Background Population history, production system and within-breed selection pressure impacts the genome architecture resulting in reduced genetic diversity and increased frequency of runs of homozygosity islands. This study tested the hypothesis that production systems geared towards specific traits of importance or natural or artificial selection pressures influenced the occurrence and distribution of runs of homozygosity (ROH) in the South African sheep population. The Illumina OvineSNP50 BeadChip was used to genotype 400 sheep belonging to 13 breeds from South Africa representing mutton, pelt and mutton and wool dual-purpose breeds, including indigenous non-descript breeds that are reared by smallholder farmers. To get more insight into the autozygosity and distribution of ROH islands of South African breeds relative to global populations, 623 genotypes of sheep from worldwide populations were included in the analysis. Runs of homozygosity were computed at cut-offs of 1–6 Mb, 6–12 Mb, 12–24 Mb, 24–48 Mb and > 48 Mb, using the R package detectRUNS. The Golden Helix SVS program was used to investigate the ROH islands. Results A total of 121,399 ROH with mean number of ROH per animal per breed ranging from 800 (African White Dorper) to 15,097 (Australian Poll Dorset) were obtained. Analysis of the distribution of ROH according to their size showed that, for all breeds, the majority of the detected ROH were in the short (1–6 Mb) category (88.2%). Most animals had no ROH > 48 Mb. Of the South African breeds, the Nguni and the Blackhead Persian displayed high ROH based inbreeding (FROH) of 0.31 ± 0.05 and 0.31 ± 0.04, respectively. Highest incidence of common runs per SNP across breeds was observed on chromosome 10 with over 250 incidences of common ROHs. Mean proportion of SNPs per breed per ROH island ranged from 0.02 ± 0.15 (island ROH224 on chromosome 23) to 0.13 ± 0.29 (island ROH175 on chromosome 15). Seventeen (17) of the islands had SNPs observed in single populations (unique ROH islands). The MacArthur Merino (MCM) population had five unique ROH islands followed by Blackhead Persian and Nguni with three each whilst the South African Mutton Merino, SA Merino, White Vital Swakara, Karakul, Dorset Horn and Chinese Merino each had one unique ROH island. Genes within ROH islands were associated with predominantly metabolic and immune response traits and predomestic selection for traits such as presence or absence of horns. Conclusions Overall, the frequency and patterns of distribution of ROH observed in this study corresponds to the breed history and implied selection pressures exposed to the sheep populations under study. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-020-07314-2.
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Affiliation(s)
- E F Dzomba
- Discipline of Genetics, School of Life Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa.
| | - M Chimonyo
- Discipline of Animal & Poultry Science; School of Agricultural, Earth & Environmental Sciences, University of KwaZulu-Natal, Private Bag X01, Scottsville, 3209, South Africa
| | - R Pierneef
- Agricultural Research Council, Biotechnology Platform, Private Bag X5, Onderstepoort, 0110, South Africa
| | - F C Muchadeyi
- Agricultural Research Council, Biotechnology Platform, Private Bag X5, Onderstepoort, 0110, South Africa
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120
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Association of TMEM8B and SPAG8 with Mature Weight in Sheep. Animals (Basel) 2020; 10:ani10122391. [PMID: 33333720 PMCID: PMC7765121 DOI: 10.3390/ani10122391] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 12/08/2020] [Accepted: 12/13/2020] [Indexed: 01/08/2023] Open
Abstract
Simple Summary Domestication and the subsequent selection of animals for either economic or morphological features can impact the legacy genome of a population in myriad ways. In sheep, the rs426272889 single nucleotide polymorphism (SNP) was identified as the peak of a signature of selection. We examined phenotypic data and identified associations for the Transmembrane protein 8B (TMEM8B) rs426272889 SNP and its genetically linked Sperm-associated antigen 8 (SPAG8) rs160159557 SNP with ewe mature weight in four sheep breeds. These data provided the first production-relevant phenotypes, as well as the first organism-level (as opposed to cellular or tumor-derived) phenotypes, associated with TMEM8B, and in so doing, improved the annotation of this gene and genomic region by adding body weight implications. Once validated, these data can be applied in genetic or genomic selection aiming to achieve desired mature body weight. Abstract Signature of selection studies have identified many genomic regions with known functional importance and some without verified functional roles. Multiple studies have identified Transmembrane protein 8B (TMEM8B)rs426272889 as having been recently under extreme selection pressure in domesticated sheep, but no study has provided sheep phenotypic data clarifying a reason for extreme selection. We tested rs426272889 for production trait association in 770 U.S. Rambouillet, Targhee, Polypay, and Suffolk sheep. TMEM8Brs426272889 was associated with mature weight at 3 and 4 years (p < 0.05). This suggested selection for sheep growth and body size might explain the historical extreme selection pressure in this genomic region. We also tested Sperm-associated antigen 8 (SPAG8) rs160159557 encoding a G493C substitution. While this variant was associated with mature weights at ages 3 and 4, it was not as strongly associated as TMEM8Brs426272889. Transmembrane protein 8B has little functional information except as an inhibitor of cancer cell proliferation. To our knowledge, this is the first study linking TMEM8B to whole organism growth and body size under standard conditions. Additional work will be necessary to identify the underlying functional variant(s). Once identified, such variants could be used to improve sheep production through selective breeding.
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121
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Donkey genomes provide new insights into domestication and selection for coat color. Nat Commun 2020; 11:6014. [PMID: 33293529 PMCID: PMC7723042 DOI: 10.1038/s41467-020-19813-7] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2019] [Accepted: 10/29/2020] [Indexed: 11/08/2022] Open
Abstract
Current knowledge about the evolutionary history of donkeys is still incomplete due to the lack of archeological and whole-genome diversity data. To fill this gap, we have de novo assembled a chromosome-level reference genome of one male Dezhou donkey and analyzed the genomes of 126 domestic donkeys and seven wild asses. Population genomics analyses indicate that donkeys were domesticated in Africa and conclusively show reduced levels of Y chromosome variability and discordant paternal and maternal histories, possibly reflecting the consequences of reproductive management. We also investigate the genetic basis of coat color. While wild asses show diluted gray pigmentation (Dun phenotype), domestic donkeys display non-diluted black or chestnut coat colors (non-Dun) that were probably established during domestication. Here, we show that the non-Dun phenotype is caused by a 1 bp deletion downstream of the TBX3 gene, which decreases the expression of this gene and its inhibitory effect on pigment deposition. A new donkey reference genome and comparisons with wild asses yields insights into the evolutionary history of donkey domestication and identifies a genetic variant that results in the non-Dun coat colours of domestic donkeys.
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122
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Schaffer A, Caicoya AL, Colell M, Holland R, Ensenyat C, Amici F. Gaze Following in Ungulates: Domesticated and Non-domesticated Species Follow the Gaze of Both Humans and Conspecifics in an Experimental Context. Front Psychol 2020; 11:604904. [PMID: 33329278 PMCID: PMC7711155 DOI: 10.3389/fpsyg.2020.604904] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2020] [Accepted: 10/16/2020] [Indexed: 01/08/2023] Open
Abstract
Gaze following is the ability to use others' gaze to obtain information about the environment (e.g., food location, predators, and social interactions). As such, it may be highly adaptive in a variety of socio-ecological contexts, and thus be widespread across animal taxa. To date, gaze following has been mostly studied in primates, and partially in birds, but little is known on the gaze following abilities of other taxa and, especially, on the evolutionary pressures that led to their emergence. In this study, we used an experimental approach to test gaze following skills in a still understudied taxon, ungulates. Across four species (i.e., domestic goats and lamas, and non-domestic guanacos and mouflons), we assessed the individual ability to spontaneously follow the gaze of both conspecifics and human experimenters in different conditions. In line with our predictions, species followed the model's gaze both with human and conspecific models, but more likely with the latter. Except for guanacos, all species showed gaze following significantly more in the experimental conditions (than in the control ones). Despite the relative low number of study subjects, our study provides the first experimental evidence of gaze following skills in non-domesticated ungulates, and contributes to understanding how gaze following skills are distributed in another taxon-an essential endeavor to identify the evolutionary pressures leading to the emergence of gaze following skills across taxa.
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Affiliation(s)
- Alina Schaffer
- Behavioral Ecology Research Group, Institute of Biology, University of Leipzig, Leipzig, Germany
| | - Alvaro L Caicoya
- Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Montserrat Colell
- Department of Clinical Psychology and Psychobiology, Faculty of Psychology, University of Barcelona, Barcelona, Spain.,Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | | | | | - Federica Amici
- Behavioral Ecology Research Group, Institute of Biology, University of Leipzig, Leipzig, Germany.,Research Group "Primate Behavioral Ecology," Department of Human Behavior, Ecology and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany
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Janowicz A, De Massis F, Zilli K, Ancora M, Tittarelli M, Sacchini F, Di Giannatale E, Sahl JW, Foster JT, Garofolo G. Evolutionary history and current distribution of the West Mediterranean lineage of Brucella melitensis in Italy. Microb Genom 2020; 6. [PMID: 33030422 PMCID: PMC7725330 DOI: 10.1099/mgen.0.000446] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Ovine and caprine brucellosis, caused by Brucella melitensis, is one of the world’s most widespread zoonoses and is a major cause of economic losses in domestic ruminant production. In Italy, the disease remains endemic in several southern provinces, despite an ongoing brucellosis eradication programme. In this study, we used whole-genome sequencing to detail the genetic diversity of circulating strains, and to examine the origins of the predominant sub-lineages of B. melitensis in Italy. We reconstructed a global phylogeny of B. melitensis, strengthened by 339 new whole-genome sequences, from Italian isolates collected from 2011 to 2018 as part of a national livestock surveillance programme. All Italian strains belonged to the West Mediterranean lineage, which further divided into two major clades that diverged roughly between the 5th and 7th centuries. We observed that Sicily serves as a brucellosis burden hotspot, giving rise to several distinct sub-lineages. More than 20 putative outbreak clusters of ovine and caprine brucellosis were identified, several of which persisted over the 8 year survey period despite an aggressive brucellosis eradication campaign. While the outbreaks in Central and Northern Italy were generally associated with introductions of single clones of B. melitensis and their subsequent dissemination within neighbouring territories, we observed weak geographical segregation of genotypes in the southern regions. Biovar determination, recommended in routine analysis of all Brucella strains by the World Organisation for Animal Health (OIE), could not discriminate among the four main global clades. This demonstrates a need for updating the guidelines used for monitoring B. melitensis transmission and spread, both at the national and international level, and to include whole-genome-based typing as the principal method for identification and tracing of brucellosis outbreaks.
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Affiliation(s)
- Anna Janowicz
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Fabrizio De Massis
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Katiuscia Zilli
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Massimo Ancora
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Manuela Tittarelli
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Flavio Sacchini
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Elisabetta Di Giannatale
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
| | - Jason W Sahl
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA
| | - Jeffrey T Foster
- Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, AZ 86011, USA
| | - Giuliano Garofolo
- National and OIE Reference Laboratory for Brucellosis, Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise "G. Caporale", via Campo Boario, 64100 Teramo, Italy
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125
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Li R, Yang P, Li M, Fang W, Yue X, Nanaei HA, Gan S, Du D, Cai Y, Dai X, Yang Q, Cao C, Deng W, He S, Li W, Ma R, Liu M, Jiang Y. A Hu sheep genome with the first ovine Y chromosome reveal introgression history after sheep domestication. SCIENCE CHINA-LIFE SCIENCES 2020; 64:1116-1130. [PMID: 32997330 DOI: 10.1007/s11427-020-1807-0] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2020] [Accepted: 08/25/2020] [Indexed: 01/21/2023]
Abstract
The Y chromosome plays key roles in male fertility and reflects the evolutionary history of paternal lineages. Here, we present a de novo genome assembly of the Hu sheep with the first draft assembly of ovine Y chromosome (oMSY), using nanopore sequencing and Hi-C technologies. The oMSY that we generated spans 10.6 Mb from which 775 Y-SNPs were identified by applying a large panel of whole genome sequences from worldwide sheep and wild Iranian mouflons. Three major paternal lineages (HY1a, HY1b and HY2) were defined across domestic sheep, of which HY2 was newly detected. Surprisingly, HY2 forms a monophyletic clade with the Iranian mouflons and is highly divergent from both HY1a and HY1b. Demographic analysis of Y chromosomes, mitochondrial and nuclear genomes confirmed that HY2 and the maternal counterpart of lineage C represented a distinct wild mouflon population in Iran that diverge from the direct ancestor of domestic sheep, the wild mouflons in Southeastern Anatolia. Our results suggest that wild Iranian mouflons had introgressed into domestic sheep and thereby introduced this Iranian mouflon specific lineage carrying HY2 to both East Asian and Africa sheep populations.
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Affiliation(s)
- Ran Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Peng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Wenwen Fang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xiangpeng Yue
- State Key Laboratory of Grassland Agro-ecosystems, Key Laboratory of Grassland Livestock Industry Innovation, Ministry of Agriculture and Rural Affairs, Engineering Research Center of Grassland Industry, Ministry of Education, College of Pastoral Agriculture Science and Technology, Lanzhou University, Lanzhou, 730020, China
| | - Hojjat Asadollahpour Nanaei
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Shangquan Gan
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Duo Du
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Xuelei Dai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Qimeng Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Chunna Cao
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China
| | - Weidong Deng
- Faculty of Animal Science and Technology, Yunan Agricultural University, Kunming, 650201, China
| | - Sangang He
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Animal Biotechnology Research Institute, Xinjiang Academy of Animal Science, Urumqi, 830026, China
| | - Wenrong Li
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Animal Biotechnology Research Institute, Xinjiang Academy of Animal Science, Urumqi, 830026, China
| | - Runlin Ma
- State Key Laboratory of Molecular Developmental Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, 100101, China
| | - Mingjun Liu
- Key Laboratory of Genetics Breeding and Reproduction of Grass feeding Livestock, Ministry of Agriculture, Animal Biotechnology Research Institute, Xinjiang Academy of Animal Science, Urumqi, 830026, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, 712100, China.
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Whole genome analysis of water buffalo and global cattle breeds highlights convergent signatures of domestication. Nat Commun 2020; 11:4739. [PMID: 32958756 PMCID: PMC7505982 DOI: 10.1038/s41467-020-18550-1] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 08/26/2020] [Indexed: 12/30/2022] Open
Abstract
More people globally depend on the water buffalo than any other domesticated species, and as the most closely related domesticated species to cattle they can provide important insights into the shared evolutionary basis of domestication. Here, we sequence the genomes of 79 water buffalo across seven breeds and compare patterns of between breed selective sweeps with those seen for 294 cattle genomes representing 13 global breeds. The genomic regions under selection between cattle breeds significantly overlap regions linked to stature in human genetic studies, with a disproportionate number of these loci also shown to be under selection between water buffalo breeds. Investigation of potential functional variants in the water buffalo genome identifies a rare example of convergent domestication down to the same mutation having independently occurred and been selected for across domesticated species. Cross-species comparisons of recent selective sweeps can consequently help identify and refine important loci linked to domestication. The comparative genomics of domesticated lineages can yield insights into the signatures of artificial selection. This study sequences 79 water buffalo genomes from 7 breeds and reveals examples of convergent domestication at the genetic level between water buffalo and cattle.
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127
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Brunner N, Kühleitner M. The growth of domestic goats and sheep: A meta study with Bertalanffy-Pütter models. Vet Anim Sci 2020; 10:100135. [PMID: 32885092 PMCID: PMC7451746 DOI: 10.1016/j.vas.2020.100135] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Revised: 07/08/2020] [Accepted: 07/18/2020] [Indexed: 01/06/2023] Open
Abstract
We studied 122 mass-at-age data for goats, sheep, and wildlife. We used Bertalanffy-Pütter models to obtain better fitting growth curves. The Brody model had an acceptable fit to 70% of the data. For 39% of data the best-fitting BP-model had a discernable inflection-point. For these models, maximal weight gain per day was 55% higher than natal weight gain.
Growth literature often uses the Brody, Gompertz, Verhulst, and von Bertalanffy models. Is there a rationale for the preference of these classical named models? The versatile five-parameter Bertalanffy-Pütter (BP) model generalizes these models. We revisited peer-reviewed publications from the years 1970–2019 that fitted growth models to together 122 mass-at-age data of sheep and goats from 19 countries and studied the best-fit BP-models using the least-squares method. None of the named models was ever best-fitting. However, for 70% of the data a single non-sigmoidal model had an acceptable fit (normalized root mean squared error 〈 5% and F-ratio test 〉 5% in comparison to the best-fit): the Brody model. The inherently non-sigmoidal character was further underlined, as there were only 39% of the data, where the best-fitting BP-model had a discernible inflection point. For these data, conclusions of biological interest could be drawn from the sigmoidal best-fit BP-models: the maximal weight gain per day was about 55% higher than the natal weight gain per day.
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Affiliation(s)
- Norbert Brunner
- University of Natural Resources and Life Sciences (BOKU), Department of Integrative Biology and Biodiversity Research (DIBB), A-1180 Vienna, Austria
| | - Manfred Kühleitner
- University of Natural Resources and Life Sciences (BOKU), Department of Integrative Biology and Biodiversity Research (DIBB), A-1180 Vienna, Austria
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Wang MS, Thakur M, Peng MS, Jiang Y, Frantz LAF, Li M, Zhang JJ, Wang S, Peters J, Otecko NO, Suwannapoom C, Guo X, Zheng ZQ, Esmailizadeh A, Hirimuthugoda NY, Ashari H, Suladari S, Zein MSA, Kusza S, Sohrabi S, Kharrati-Koopaee H, Shen QK, Zeng L, Yang MM, Wu YJ, Yang XY, Lu XM, Jia XZ, Nie QH, Lamont SJ, Lasagna E, Ceccobelli S, Gunwardana HGTN, Senasige TM, Feng SH, Si JF, Zhang H, Jin JQ, Li ML, Liu YH, Chen HM, Ma C, Dai SS, Bhuiyan AKFH, Khan MS, Silva GLLP, Le TT, Mwai OA, Ibrahim MNM, Supple M, Shapiro B, Hanotte O, Zhang G, Larson G, Han JL, Wu DD, Zhang YP. 863 genomes reveal the origin and domestication of chicken. Cell Res 2020; 30:693-701. [PMID: 32581344 PMCID: PMC7395088 DOI: 10.1038/s41422-020-0349-y] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Accepted: 05/20/2020] [Indexed: 01/10/2023] Open
Abstract
Despite the substantial role that chickens have played in human societies across the world, both the geographic and temporal origins of their domestication remain controversial. To address this issue, we analyzed 863 genomes from a worldwide sampling of chickens and representatives of all four species of wild jungle fowl and each of the five subspecies of red jungle fowl (RJF). Our study suggests that domestic chickens were initially derived from the RJF subspecies Gallus gallus spadiceus whose present-day distribution is predominantly in southwestern China, northern Thailand and Myanmar. Following their domestication, chickens were translocated across Southeast and South Asia where they interbred locally with both RJF subspecies and other jungle fowl species. In addition, our results show that the White Leghorn chicken breed possesses a mosaic of divergent ancestries inherited from other subspecies of RJF. Despite the strong episodic gene flow from geographically divergent lineages of jungle fowls, our analyses show that domestic chickens undergo genetic adaptations that underlie their unique behavioral, morphological and reproductive traits. Our study provides novel insights into the evolutionary history of domestic chickens and a valuable resource to facilitate ongoing genetic and functional investigations of the world's most numerous domestic animal.
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Affiliation(s)
- Ming-Shan Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
- Department of Ecology and Evolutionary Biology, Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Mukesh Thakur
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Zoological Survey of India, New Alipore, Kolkata, West Bengal, India
| | - Min-Sheng Peng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Laurent Alain François Frantz
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
- School of Biological and Chemical Sciences, Queen Mary University of London, London, UK
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Jin-Jin Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Sheng Wang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Joris Peters
- ArchaeoBioCenter and Department of Veterinary Sciences, Institute of Palaeoanatomy, Domestication Research and the History of Veterinary Medicine, LMU Munich, Munich, Germany
- SNSB, Bavarian State Collection of Anthropology and Palaeoanatomy, Munich, Germany
| | - Newton Otieno Otecko
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | | | - Xing Guo
- College of Animal Science and Technology, Anhui Agricultural University, Hefei, Anhui, China
| | - Zhu-Qing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, Shaanxi, China
| | - Ali Esmailizadeh
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Department of Animal Science, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Nalini Yasoda Hirimuthugoda
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Faculty of Agriculture, University of Ruhuna, Matara, Sri Lanka
| | - Hidayat Ashari
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
| | - Sri Suladari
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
| | - Moch Syamsul Arifin Zein
- Museum Zoologicum Bogoriense, Research Center for Biology, Indonesian Institute of Science (LIPI), Cibinong, Indonesia
| | - Szilvia Kusza
- Institute of Animal Husbandry, Biotechnology and Nature Conservation, University of Debrecen, Debrecen, Hungary
| | - Saeed Sohrabi
- Department of Animal Science, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Hamed Kharrati-Koopaee
- Department of Animal Science, Shahid Bahonar University of Kerman, Kerman, Iran
- Institute of Biotechnology, School of Agriculture, Shiraz University, Shiraz, Iran
| | - Quan-Kuan Shen
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Lin Zeng
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Min-Min Yang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ya-Jiang Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- State Key Laboratory for Conservation and Utilization of Bio-resource, Yunnan University, Kunming, Yunnan, China
| | - Xing-Yan Yang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- State Key Laboratory for Conservation and Utilization of Bio-resource, Yunnan University, Kunming, Yunnan, China
| | - Xue-Mei Lu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xin-Zheng Jia
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Qing-Hua Nie
- College of Animal Science, South China Agricultural University, Guangzhou, Guangdong, China
| | - Susan Joy Lamont
- Department of Animal Science, Iowa State University, Ames, IA, USA
| | - Emiliano Lasagna
- Dipartimento di Scienze Agrarie, Alimentarie Ambientali, University of Perugia, Perugia, Italy
| | - Simone Ceccobelli
- Dipartimento di Scienze Agrarie, Alimentarie Ambientali, University of Perugia, Perugia, Italy
| | | | | | - Shao-Hong Feng
- BGI-Shenzhen, Beishan Industrial Zone, Shenzhen, Guangdong, China
| | - Jing-Fang Si
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Hao Zhang
- Laboratory of Animal Genetics, Breeding and Reproduction, Ministry of Agriculture of China, National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jie-Qiong Jin
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Southeast Asia Biodiversity Research Institute, Chinese Academy of Sciences (CAS-SEABRI), Yezin, Myanmar
| | - Ming-Li Li
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yan-Hu Liu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Hong-Man Chen
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Cheng Ma
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Shan-Shan Dai
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | | | | | | | - Thi-Thuy Le
- National Institute of Animal Husbandry, Hanoi, Vietnam
| | - Okeyo Ally Mwai
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| | | | - Megan Supple
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz, Santa Cruz, CA, USA
- Howard Hughes Medical Institute, University of California, Santa Cruz, Santa Cruz, CA, USA
| | - Olivier Hanotte
- Cells, Organisms and Molecular Genetics, School of Life Sciences, University of Nottingham, Nottingham, UK
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Addis Ababa, Ethiopia
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China
- Department of Biology, Centre for Social Evolution, University of Copenhagen, Copenhagen, Denmark
- China National Genebank, BGI-Shenzhen, Shenzhen, Guangdong, China
| | - Greger Larson
- The Palaeogenomics and Bio-Archaeology Research Network, Research Laboratory for Archaeology and History of Art, University of Oxford, Oxford, UK
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China.
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya.
| | - Dong-Dong Wu
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China.
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China.
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, Yunnan, China.
- State Key Laboratory for Conservation and Utilization of Bio-resource, Yunnan University, Kunming, Yunnan, China.
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129
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Eydivandi S, Sahana G, Momen M, Moradi MH, Schönherz AA. Genetic diversity in Iranian indigenous sheep vis-à-vis selected exogenous sheep breeds and wild mouflon. Anim Genet 2020; 51:772-787. [PMID: 32729152 DOI: 10.1111/age.12985] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 06/09/2020] [Accepted: 06/22/2020] [Indexed: 11/29/2022]
Abstract
The heterogeneity of climate and different agro-ecological conditions in Iran have resulted in development of 27 indigenous sheep breeds. Wild Asiatic mouflon (Ovis orientalis) is believed to be the ancestor of Iranian sheep. Evaluation of genetic diversity and population structure within and among domestic breeds has important implications for animal breeding programs and genetic resources management. Based on 50K SNP genotype data, we studied the genetic diversity of five indigenous Iranian sheep breeds: Afshari (n = 37), Moghani (n = 34), Qezel (n = 35), Zel (n = 46) and Lori-Bakhtiari (n = 46), and Asiatic mouflon (n = 8) sampled from Iran. Furthermore, genetic diversity and the breed admixture of Iranian sheep were assessed on a larger geographic scale using a reference panel comprising: three indigenous Afghan breeds - Arabi (n = 15), Balouchi (n = 15) and Gadik (n = 15); three indigenous breeds from Turkey and Cyprus - Cyprus Fat Tail (n = 30), Karakas (n = 18) and Norduz (n = 20); and three commercial European breeds - Suffolk (n = 19), Comisana (n = 24) and Engadine Red Sheep (n = 24). The results revealed that the investigated breeds are divided into five genetically distinct clusters according to their geographic origin. Afshari was closest to the local mouflon population and showed signs of mouflon admixture. Qezel was identified as a hybrid sheep breed. Much evidence supported the Afghan breeds being identical. Inbreeding values, which were estimated based on ROHs, were highest for Suffolk (FROH = 0.0544) and lowest for Balouchi (FROH = 0.0078). In conclusion, analysis of selected breeds from neighboring countries along with Asiatic mouflon gave a deeper insight into the evolutionary history and origin of Iranian sheep with important implications for future breed management.
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Affiliation(s)
- S Eydivandi
- Department of Animal Science, Behbahan Branch, Islamic Azad University, Behbahan, 63617-13198, Iran.,Faculty of Technical Sciences, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - G Sahana
- Faculty of Technical Sciences, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
| | - M Momen
- Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - M H Moradi
- Department of Animal Science, Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran
| | - A A Schönherz
- Faculty of Technical Sciences, Center for Quantitative Genetics and Genomics, Aarhus University, Tjele, 8830, Denmark
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130
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Barrera-Redondo J, Piñero D, Eguiarte LE. Genomic, Transcriptomic and Epigenomic Tools to Study the Domestication of Plants and Animals: A Field Guide for Beginners. Front Genet 2020; 11:742. [PMID: 32760427 PMCID: PMC7373799 DOI: 10.3389/fgene.2020.00742] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2020] [Accepted: 06/22/2020] [Indexed: 01/07/2023] Open
Abstract
In the last decade, genomics and the related fields of transcriptomics and epigenomics have revolutionized the study of the domestication process in plants and animals, leading to new discoveries and new unresolved questions. Given that some domesticated taxa have been more studied than others, the extent of genomic data can range from vast to nonexistent, depending on the domesticated taxon of interest. This review is meant as a rough guide for students and academics that want to start a domestication research project using modern genomic tools, as well as for researchers already conducting domestication studies that are interested in following a genomic approach and looking for alternate strategies (cheaper or more efficient) and future directions. We summarize the theoretical and technical background needed to carry out domestication genomics, starting from the acquisition of a reference genome and genome assembly, to the sampling design for population genomics, paleogenomics, transcriptomics, epigenomics and experimental validation of domestication-related genes. We also describe some examples of the aforementioned approaches and the relevant discoveries they made to understand the domestication of the studied taxa.
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Affiliation(s)
| | | | - Luis E. Eguiarte
- Departamento de Ecología Evolutiva, Instituto de Ecología, Universidad Nacional Autónoma de México, Mexico City, Mexico
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131
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Cai Y, Fu W, Cai D, Heller R, Zheng Z, Wen J, Li H, Wang X, Alshawi A, Sun Z, Zhu S, Wang J, Yang M, Hu S, Li Y, Yang Z, Gong M, Hou Y, Lan T, Wu K, Chen Y, Jiang Y, Wang X. Ancient Genomes Reveal the Evolutionary History and Origin of Cashmere-Producing Goats in China. Mol Biol Evol 2020; 37:2099-2109. [PMID: 32324877 PMCID: PMC7306693 DOI: 10.1093/molbev/msaa103] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Goats are one of the most widespread farmed animals across the world; however, their migration route to East Asia and local evolutionary history remain poorly understood. Here, we sequenced 27 ancient Chinese goat genomes dating from the Late Neolithic period to the Iron Age. We found close genetic affinities between ancient and modern Chinese goats, demonstrating their genetic continuity. We found that Chinese goats originated from the eastern regions around the Fertile Crescent, and we estimated that the ancestors of Chinese goats diverged from this population in the Chalcolithic period. Modern Chinese goats were divided into a northern and a southern group, coinciding with the most prominent climatic division in China, and two genes related to hair follicle development, FGF5 and EDA2R, were highly divergent between these populations. We identified a likely causal de novo deletion near FGF5 in northern Chinese goats that increased to high frequency over time, whereas EDA2R harbored standing variation dating to the Neolithic. Our findings add to our understanding of the genetic composition and local evolutionary process of Chinese goats.
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Affiliation(s)
- Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Weiwei Fu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Dawei Cai
- Research Center for Chinese Frontier Archaeology, Jilin University, Changchun, China
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Zhuqing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Jia Wen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Hui Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
- State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, Guangxi University, Nanning, China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Akil Alshawi
- School of Life Sciences, Faculty of Medicine and Health Sciences, University of Nottingham, Nottingham, United Kingdom
- Department of Internal and Preventive Medicine, College of Veterinary Medicine, University of Baghdad, Iraqi Ministry of Higher Education and Scientific Research, Iraq
| | | | - Siqi Zhu
- Research Center for Chinese Frontier Archaeology, Jilin University, Changchun, China
| | - Juan Wang
- Henan Provincial Institute of Cultural Heritage and Archaeology, Zhengzhou, China
| | | | - Songmei Hu
- Shaanxi Academy of Archaeology, Xi’an, China
| | - Yan Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Zhirui Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yunan Hou
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Tianming Lan
- BGI-Shenzhen, Build 11, Beishan Industrial Zone, Yantian District, Shenzhen, China
- Laboratory of Genomics and Molecular Biomedicine, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Kui Wu
- China National GeneBank-Shenzhen, BGI-Shenzhen, China
- Cancer Institute, BGI-Research, BGI-Shenzhen, Shenzhen, China
| | - Yulin Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling, China
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132
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Zhang H, Liang Q, Wang N, Wang Q, Leng L, Mao J, Wang Y, Wang S, Zhang J, Liang H, Zhou X, Li Y, Cao Z, Luan P, Wang Z, Yuan H, Wang Z, Zhou X, Lamont SJ, Da Y, Li R, Tian S, Du Z, Li H. Microevolutionary Dynamics of Chicken Genomes under Divergent Selection for Adiposity. iScience 2020; 23:101193. [PMID: 32554187 PMCID: PMC7303556 DOI: 10.1016/j.isci.2020.101193] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2020] [Revised: 04/19/2020] [Accepted: 05/19/2020] [Indexed: 01/01/2023] Open
Abstract
Decades of artificial selection have significantly improved performance and efficiency of animal production systems. However, little is known about the microevolution of genomes due to intensive breeding. Using whole-genome sequencing, we document dynamic changes of chicken genomes under divergent selection on adiposity over 19 generations. Directional selection reduced within-line but increased between-line genomic differences. We observed that artificial selection tended to result in recruitment of preexisting variations of genes related to adipose tissue growth. In addition, novel mutations contributed to divergence of phenotypes under selection but contributed significantly less than preexisting genomic variants. Integration of 15 generations genome sequencing, genome-wide association study, and multi-omics data further identified that genes involved in signaling pathways important to adipogenesis, such as autophagy and lysosome (URI1, MBL2), neural system (CHAT), and endocrine (PCSK1) pathways, were under strong selection. Our study provides insights into the microevolutionary dynamics of domestic animal genomes under artificial selection.
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Affiliation(s)
- Hui Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Qiqi Liang
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Ning Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Qigui Wang
- Chongqing Academy of Animal Science, Chongqing 402460, P. R. China
| | - Li Leng
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Jie Mao
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Yuxiang Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Shouzhi Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Jiyang Zhang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Hao Liang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Xun Zhou
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Yumao Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhiping Cao
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Peng Luan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhipeng Wang
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Hui Yuan
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China
| | - Zhiquan Wang
- Department of Agricultural, Food and Nutritional Sciences, University of Alberta, Edmonton, AB T6G 2C8, Canada
| | - Xuming Zhou
- Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, P. R. China
| | - Susan J Lamont
- Department of Animal Science, Iowa State University, Ames 50011, USA
| | - Yang Da
- Department of Animal Science, University of Minnesota, Saint Paul, MN 55108, USA
| | - Ruiqiang Li
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China
| | - Shilin Tian
- Novogene Bioinformatics Institute, Beijing 10089, P. R. China.
| | - Zhiqiang Du
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
| | - Hui Li
- Key Laboratory of Chicken Genetics and Breeding, Ministry of Agriculture and Rural Affairs; Key Laboratory of Animal Genetics, Breeding and Reproduction, Education Department of Heilongjiang Province; College of Animal Science and Technology, Northeast Agricultural University, Harbin 150030, P. R. China.
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133
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Evolutionary origins of genomic adaptations in an invasive copepod. Nat Ecol Evol 2020; 4:1084-1094. [DOI: 10.1038/s41559-020-1201-y] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2019] [Accepted: 04/14/2020] [Indexed: 12/18/2022]
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Karsli BA, Demir E, Fidan HG, Karsli T. Assessment of genetic diversity and differentiation among four indigenous Turkish sheep breeds using microsatellites. Arch Anim Breed 2020; 63:165-172. [PMID: 32760783 PMCID: PMC7397719 DOI: 10.5194/aab-63-165-2020] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2020] [Accepted: 05/12/2020] [Indexed: 11/13/2022] Open
Abstract
Conservation and breeding programmes of livestock species depend on determination of genetic diversity. Today in livestock species, microsatellite markers are commonly used to reveal population structure and genetic diversity in both breeds and varieties. In this study, population structure, genetic diversity, and differentiation among four native Turkish sheep breeds including Güney Karaman, Kangal, Norduz, and Karakas were assessed by using 21 microsatellite loci. By genotyping 120 individuals belonging to four sheep breeds, a total of 275 different alleles, 37 of which were private alleles, were observed across all loci. The mean number of alleles per breed ranged from 7.28 (Güney Karaman) to 8.09 (Karakas), while allelic richness ranged from 7.22 (Güney Karaman) to 7.87 (Karakas). Mean observed heterozygosity varied from 0.60 (Kangal) to 0.66 (Norduz and Karakas). The lowest pairwiseF ST value (0.084) was between Kangal and Karakas populations, while the highest pairwiseF ST value (0.142) was between Norduz and Karakas populations. Polymorphic information content (PIC) values, ranging from 0.71 (ETH10) to 0.91 (OarFCB304), were highly polymorphic (PIC > 0.5) and informative in studied populations. In the present study, the results of phylogenetic analysis were of importance, since all studied populations have been accepted as Akkaraman varieties till today. However, factorial correspondence and structure analysis, pairwiseF ST values, and an unweighted pair group method with arithmetic mean analysis (UPGMA) dendrogram revealed that Güney Karaman and Norduz populations have became genetically different from the Akkaraman breed due being raised in different parts of Turkey under different climatic conditions together with their breeding practices. Therefore, we recommend that more comprehensive molecular studies should be conducted to clarify genetic differentiation of Akkaraman sheep varieties.
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Affiliation(s)
- Bahar Argun Karsli
- Department of Animal Science, Faculty of Agriculture, Akdeniz University,
Antalya, 07058, Turkey
| | - Eymen Demir
- Department of Animal Science, Faculty of Agriculture, Akdeniz University,
Antalya, 07058, Turkey
| | - Huseyin Goktug Fidan
- Department of Animal Science, Faculty of Agriculture, Akdeniz University,
Antalya, 07058, Turkey
| | - Taki Karsli
- Department of Animal Science, Faculty of Agriculture, Akdeniz University,
Antalya, 07058, Turkey
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135
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Li X, Yang J, Shen M, Xie XL, Liu GJ, Xu YX, Lv FH, Yang H, Yang YL, Liu CB, Zhou P, Wan PC, Zhang YS, Gao L, Yang JQ, Pi WH, Ren YL, Shen ZQ, Wang F, Deng J, Xu SS, Salehian-Dehkordi H, Hehua E, Esmailizadeh A, Dehghani-Qanatqestani M, Štěpánek O, Weimann C, Erhardt G, Amane A, Mwacharo JM, Han JL, Hanotte O, Lenstra JA, Kantanen J, Coltman DW, Kijas JW, Bruford MW, Periasamy K, Wang XH, Li MH. Whole-genome resequencing of wild and domestic sheep identifies genes associated with morphological and agronomic traits. Nat Commun 2020; 11:2815. [PMID: 32499537 PMCID: PMC7272655 DOI: 10.1038/s41467-020-16485-1] [Citation(s) in RCA: 124] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2019] [Accepted: 05/04/2020] [Indexed: 01/15/2023] Open
Abstract
Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.
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Affiliation(s)
- Xin Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Ji Yang
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Min Shen
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Xing-Long Xie
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Guang-Jian Liu
- Novogene Bioinformatics Institute, Beijing, 100083, China
| | - Ya-Xi Xu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Feng-Hua Lv
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China
| | - Hua Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yong-Lin Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Chang-Bin Liu
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Ping Zhou
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Peng-Cheng Wan
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yun-Sheng Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Lei Gao
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Jing-Quan Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Wen-Hui Pi
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China
| | - Yan-Ling Ren
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, 256600, China
| | - Zhi-Qiang Shen
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, 256600, China
| | - Feng Wang
- Institute of Sheep and Goat Science, Nanjing Agricultural University, Nanjing, 210095, China
| | - Juan Deng
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130, China
| | - Song-Song Xu
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Hosein Salehian-Dehkordi
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China
- University of Chinese Academy of Sciences (UCAS), Beijing, 100049, China
| | - Eer Hehua
- Grass-Feeding Livestock Engineering Technology Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | | | - Ondřej Štěpánek
- Institute of Molecular Genetics of the ASCR, v. v. i., Vídeňská 1083, 142 20, Prague 4, Czech Republic
| | - Christina Weimann
- Institute of Animal Breeding and Genetics, Justus Liebig University, Giessen, Germany
| | - Georg Erhardt
- Institute of Animal Breeding and Genetics, Justus Liebig University, Giessen, Germany
| | - Agraw Amane
- Department of Microbial, Cellular and Molecular Biology, Addis Ababa University, Addis Ababa, Ethiopia
- LiveGene Program, International Livestock Research Institute, Addis Ababa, Ethiopia
| | - Joram M Mwacharo
- Small Ruminant Genomics, International Centre for Agricultural Research in the Dry Areas (ICARDA), Addis Ababa, Ethiopia
| | - Jian-Lin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agricultural Sciences (CAAS), Beijing, China
- Livestock Genetics Program, International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Olivier Hanotte
- LiveGene Program, International Livestock Research Institute, Addis Ababa, Ethiopia
- School of Life Sciences, University of Nottingham, University Park, Nottingham, NG7 2RD, UK
- Center for Tropical Livestock Genetics and Health (CTLGH), the Roslin Institute, University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, Scotland, UK
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), FI-31600, Jokioinen, Finland
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, T6G 2E9, Canada
| | - James W Kijas
- CSIRO Livestock Industries, St Lucia, Brisbane, QLD, Australia
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Cathays Park, Cardiff, CF10 3AX, Wales, UK
- Sustainable Places Research Institute, Cardiff University, CF10 3BA, Cardiff, Wales, UK
| | - Kathiravan Periasamy
- Animal Production and Health Laboratory, Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, Vienna, Austria
| | - Xin-Hua Wang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China.
- State Key Laboratory of Sheep Genetic Improvement and Healthy Breeding, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, 832000, China.
| | - Meng-Hua Li
- CAS Key Laboratory of Animal Ecology and Conservation Biology, Institute of Zoology, Chinese Academy of Sciences (CAS), Beijing, 100101, China.
- College of Animal Science and Technology, China Agricultural University, Beijing, 100193, China.
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136
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Li J, Xu H, Liu X, Xu H, Cai Y, Lan X. Insight into the Possible Formation Mechanism of the Intersex Phenotype of Lanzhou Fat-Tailed Sheep Using Whole-Genome Resequencing. Animals (Basel) 2020; 10:ani10060944. [PMID: 32486017 PMCID: PMC7341509 DOI: 10.3390/ani10060944] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 05/21/2020] [Accepted: 05/25/2020] [Indexed: 01/07/2023] Open
Abstract
Simple Summary Individuals with hermaphroditism are a serious hazard to animal husbandry and production due to their abnormal fertility. The molecular mechanism of sheep intersex formation was unclear. This study was the first to locate the homologous sequence of the goat polled intersex syndrome (PIS) region in sheep and found that the intersex traits of Lanzhou fat-tailed sheep were not caused by the lack of this region. By detecting the selective sweep regions, vital genes associated with androgen biosynthesis and the follicle stimulating hormone response entry were found, including steroid 5 alpha-reductase 2 (SRD5A2), and pro-apoptotic WT1 regulator (PAWR). Additionally, the copy number variations of the four regions on chr9, chr1, chr4, and chr16 may affect the expression of the gonadal development genes, zinc finger protein, FOG family member 2 (ZFPM2), LIM homeobox 8 (LHX8), inner mitochondrial membrane peptidase subunit 2 (IMMP2L) and slit guidance ligand 3 (SLIT3), respectively, and further affect the formation of intersex traits. Abstract Intersex, also known as hermaphroditism, is a serious hazard to animal husbandry and production. The mechanism of ovine intersex formation is not clear. Therefore, genome-wide resequencing on the only two intersex and two normal Lanzhou fat-tailed (LFT) sheep, an excellent but endangered Chinese indigenous sheep breed, was performed. Herein, the deletion of homologous sequences of the goat polled intersex syndrome (PIS) region (8787 bp, 247747059–247755846) on chromosome 1 of the LFT sheep was not the cause of the ovine intersex trait. By detecting the selective sweep regions, we found that the genes related to androgen biosynthesis and follicle stimulating hormone response items, such as steroid 5 alpha-reductase 2 (SRD5A2), steroid 5 alpha-reductase 3 (SRD5A3), and pro-apoptotic WT1 regulator (PAWR), may be involved in the formation of intersex traits. Furthermore, the copy number variations of the four regions, chr9: 71660801–71662800, chr1: 50776001–50778000, chr4: 58119201–58121600, and chr16: 778801–780800, may affect the expression of the zinc finger protein, FOG family member 2 (ZFPM2), LIM homeobox 8 (LHX8), inner mitochondrial membrane peptidase subunit 2 (IMMP2L) and slit guidance ligand 3 (SLIT3) genes, respectively, which contribute to the appearance of intersex traits. These results may supply a theoretical basis for the timely detection and elimination of intersex individuals in sheep, which could accelerate the healthy development of animal husbandry.
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Affiliation(s)
- Jie Li
- Animal Genome and Gene Function Laboratory, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (J.L.); (H.X.); (X.L.)
| | - Han Xu
- Animal Genome and Gene Function Laboratory, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (J.L.); (H.X.); (X.L.)
- School of Medicine, Sun Yat-sen University, Guangzhou 510275, China
| | - Xinfeng Liu
- Animal Genome and Gene Function Laboratory, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (J.L.); (H.X.); (X.L.)
| | - Hongwei Xu
- College of Life Science and Engineering, Northwest Minzu University, Lanzhou 730030, China
- Gansu Tech Innovation Center of Animal Cell, Biomedical Research Center, Northwest Minzu University, Lanzhou 730030, China
- Correspondence: (H.X.); (X.L.)
| | - Yong Cai
- Science Experimental Center, Northwest Minzu University, Lanzhou 730030, China;
- Key Laboratory of Biotechnology and Bioengineering of State Ethnic Affairs Commission, Biomedical Research Center, Northwest Minzu University, Lanzhou 730030, China
| | - Xianyong Lan
- Animal Genome and Gene Function Laboratory, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China; (J.L.); (H.X.); (X.L.)
- Correspondence: (H.X.); (X.L.)
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137
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Gao Z, Ding R, Zhai X, Wang Y, Chen Y, Yang CX, Du ZQ. Common Gene Modules Identified for Chicken Adiposity by Network Construction and Comparison. Front Genet 2020; 11:537. [PMID: 32547600 PMCID: PMC7272656 DOI: 10.3389/fgene.2020.00537] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2019] [Accepted: 05/04/2020] [Indexed: 12/12/2022] Open
Abstract
Excessive fat deposition can cause chicken health problem, and affect production efficiency by causing great economic losses to the industry. However, the molecular underpinnings of the complex adiposity trait remain elusive. In the current study, we constructed and compared the gene co-expression networks on four transcriptome profiling datasets, from two chicken lines under divergent selection for abdominal fat contents, in an attempt to dissect network compositions underlying adipose tissue growth and development. After functional enrichment analysis, nine network modules important to adipogenesis were discovered to be involved in lipid metabolism, PPAR and insulin signaling pathways, and contained hub genes related to adipogenesis, cell cycle, inflammation, and protein synthesis. Moreover, after additional functional annotation and network module comparisons, common sub-modules of similar functionality for chicken fat deposition were identified for different chicken lines, apart from modules specific to each chicken line. We further validated the lysosome pathway, and found TFEB and its downstream target genes showed similar expression patterns along with chicken preadipocyte differentiation. Our findings could provide novel insights into the genetic basis of complex adiposity traits, as well as human obesity and related metabolic diseases.
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Affiliation(s)
- Zhuoran Gao
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Ran Ding
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Xiangyun Zhai
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yuhao Wang
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yaofeng Chen
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Cai-Xia Yang
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Zhi-Qiang Du
- College of Animal Science, Yangtze University, Jingzhou, China.,College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
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138
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Ciani E, Mastrangelo S, Da Silva A, Marroni F, Ferenčaković M, Ajmone-Marsan P, Baird H, Barbato M, Colli L, Delvento C, Dovenski T, Gorjanc G, Hall SJG, Hoda A, Li MH, Marković B, McEwan J, Moradi MH, Ruiz-Larrañaga O, Ružić-Muslić D, Šalamon D, Simčič M, Stepanek O, Curik I, Cubric-Curik V, Lenstra JA. On the origin of European sheep as revealed by the diversity of the Balkan breeds and by optimizing population-genetic analysis tools. Genet Sel Evol 2020; 52:25. [PMID: 32408891 PMCID: PMC7227234 DOI: 10.1186/s12711-020-00545-7] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2019] [Accepted: 04/30/2020] [Indexed: 11/26/2022] Open
Abstract
Background In the Neolithic, domestic sheep migrated into Europe and subsequently spread in westerly and northwesterly directions. Reconstruction of these migrations and subsequent genetic events requires a more detailed characterization of the current phylogeographic differentiation. Results We collected 50 K single nucleotide polymorphism (SNP) profiles of Balkan sheep that are currently found near the major Neolithic point of entry into Europe, and combined these data with published genotypes from southwest-Asian, Mediterranean, central-European and north-European sheep and from Asian and European mouflons. We detected clines, ancestral components and admixture by using variants of common analysis tools: geography-informative supervised principal component analysis (PCA), breed-specific admixture analysis, across-breed \documentclass[12pt]{minimal}
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\begin{document}$$f_{4}$$\end{document}f4 profiles and phylogenetic analysis of regional pools of breeds. The regional Balkan sheep populations exhibit considerable genetic overlap, but are clearly distinct from the breeds in surrounding regions. The Asian mouflon did not influence the differentiation of the European domestic sheep and is only distantly related to present-day sheep, including those from Iran where the mouflons were sampled. We demonstrate the occurrence, from southeast to northwest Europe, of a continuously increasing ancestral component of up to 20% contributed by the European mouflon, which is assumed to descend from the original Neolithic domesticates. The overall patterns indicate that the Balkan region and Italy served as post-domestication migration hubs, from which wool sheep reached Spain and north Italy with subsequent migrations northwards. The documented dispersal of Tarentine wool sheep during the Roman period may have been part of this process. Our results also reproduce the documented 18th century admixture of Spanish Merino sheep into several central-European breeds. Conclusions Our results contribute to a better understanding of the events that have created the present diversity pattern, which is relevant for the management of the genetic resources represented by the European sheep population.
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Affiliation(s)
- Elena Ciani
- Dipartamento Bioscienze, Biotecnologie, Biofarmaceutica, Universita. degli Studi di Bari "Aldo Moro", Bari, Italy
| | - Salvatore Mastrangelo
- Dipartimento Scienze Agrarie, Alimentari e Forestali, Universita Studi di Palermo, Palermo, Italy
| | - Anne Da Silva
- Université de Limoges, INRAE, Pereine EA7500, USC1061 Gamaa, 87000, Limoges, France
| | - Fabio Marroni
- Dipartamento Scienze Agroalimentari, Ambientali e Animali, Universita Udine, Udine, Italy
| | | | - Paolo Ajmone-Marsan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Universita Cattolica del S. Cuore di Piacenza, Piacenza, Italy
| | - Hayley Baird
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | - Mario Barbato
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Universita Cattolica del S. Cuore di Piacenza, Piacenza, Italy
| | - Licia Colli
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Universita Cattolica del S. Cuore di Piacenza, Piacenza, Italy
| | - Chiara Delvento
- Dipartamento Bioscienze, Biotecnologie, Biofarmaceutica, Universita. degli Studi di Bari "Aldo Moro", Bari, Italy
| | - Toni Dovenski
- Department of Reproduction and Biomedicine, Faculty of Veterinary Medicine, Ss. Cyril and Methodius University, Skopje, North Macedonia
| | - Gregor Gorjanc
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, Scotland, UK
| | | | - Anila Hoda
- Department of Animal Production, Faculty of Agriculture and Environment, Agricultural University ofTirana, Tirana, Albania
| | - Meng-Hua Li
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | | | - John McEwan
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Universita Cattolica del S. Cuore di Piacenza, Piacenza, Italy
| | - Mohammad H Moradi
- Faculty of Agriculture and Natural Resources, Arak University, Arak, Iran
| | - Otsanda Ruiz-Larrañaga
- Department of Genetics, Physical Anthropology and Animal Physiology, University of Basque Country, Leioa, Spain
| | | | - Dragica Šalamon
- Department of Animal Science, University of Zagreb, Zagreb, Croatia
| | - Mojca Simčič
- Department of Animal Science, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia
| | | | | | | | - Ino Curik
- Department of Animal Science, University of Zagreb, Zagreb, Croatia
| | | | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
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139
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Cunningham F, Achuthan P, Akanni W, Allen J, Amode MR, Armean IM, Bennett R, Bhai J, Billis K, Boddu S, Cummins C, Davidson C, Dodiya KJ, Gall A, Girón CG, Gil L, Grego T, Haggerty L, Haskell E, Hourlier T, Izuogu OG, Janacek SH, Juettemann T, Kay M, Laird MR, Lavidas I, Liu Z, Loveland JE, Marugán JC, Maurel T, McMahon AC, Moore B, Morales J, Mudge JM, Nuhn M, Ogeh D, Parker A, Parton A, Patricio M, Abdul Salam AI, Schmitt BM, Schuilenburg H, Sheppard D, Sparrow H, Stapleton E, Szuba M, Taylor K, Threadgold G, Thormann A, Vullo A, Walts B, Winterbottom A, Zadissa A, Chakiachvili M, Frankish A, Hunt SE, Kostadima M, Langridge N, Martin FJ, Muffato M, Perry E, Ruffier M, Staines DM, Trevanion SJ, Aken BL, Yates AD, Zerbino DR, Flicek P. Ensembl 2019. Nucleic Acids Res 2020; 47:D745-D751. [PMID: 30407521 PMCID: PMC6323964 DOI: 10.1093/nar/gky1113] [Citation(s) in RCA: 644] [Impact Index Per Article: 161.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Accepted: 10/23/2018] [Indexed: 01/28/2023] Open
Abstract
The Ensembl project (https://www.ensembl.org) makes key genomic data sets available to the entire scientific community without restrictions. Ensembl seeks to be a fundamental resource driving scientific progress by creating, maintaining and updating reference genome annotation and comparative genomics resources. This year we describe our new and expanded gene, variant and comparative annotation capabilities, which led to a 50% increase in the number of vertebrate genomes we support. We have also doubled the number of available human variants and added regulatory regions for many mouse cell types and developmental stages. Our data sets and tools are available via the Ensembl website as well as a through a RESTful webservice, Perl application programming interface and as data files for download.
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Affiliation(s)
- Fiona Cunningham
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Premanand Achuthan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Wasiu Akanni
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - James Allen
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - M Ridwan Amode
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Irina M Armean
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ruth Bennett
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jyothish Bhai
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Konstantinos Billis
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sanjay Boddu
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Carla Cummins
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Claire Davidson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kamalkumar Jayantilal Dodiya
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Astrid Gall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Carlos García Girón
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Laurent Gil
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Tiago Grego
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Leanne Haggerty
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Erin Haskell
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Thibaut Hourlier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Osagie G Izuogu
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sophie H Janacek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Thomas Juettemann
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Mike Kay
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Matthew R Laird
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ilias Lavidas
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Zhicheng Liu
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jane E Loveland
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - José C Marugán
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Thomas Maurel
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Aoife C McMahon
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Benjamin Moore
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Joannella Morales
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Jonathan M Mudge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Michael Nuhn
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Denye Ogeh
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Anne Parker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andrew Parton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Mateus Patricio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Ahamed Imran Abdul Salam
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Bianca M Schmitt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Helen Schuilenburg
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Dan Sheppard
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Helen Sparrow
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Eloise Stapleton
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Marek Szuba
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Kieron Taylor
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Glen Threadgold
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Anja Thormann
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Alessandro Vullo
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Brandon Walts
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andrea Winterbottom
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Amonida Zadissa
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Marc Chakiachvili
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Adam Frankish
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Sarah E Hunt
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Myrto Kostadima
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Nick Langridge
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Fergal J Martin
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Matthieu Muffato
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Emily Perry
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Magali Ruffier
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Daniel M Staines
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Stephen J Trevanion
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Bronwen L Aken
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Andrew D Yates
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Daniel R Zerbino
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge CB10 1SD, UK
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140
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Wang L, Guo J, Xi Y, Ma S, Li Y, He H, Wang J, Han C, Bai L, Mustafa A, Liu H, Li L. Understanding the Genetic Domestication History of the Jianchang Duck by Genotyping and Sequencing of Genomic Genes Under Selection. G3 (BETHESDA, MD.) 2020; 10:1469-1476. [PMID: 32165372 PMCID: PMC7202016 DOI: 10.1534/g3.119.400893] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2019] [Accepted: 03/01/2020] [Indexed: 12/11/2022]
Abstract
The Jianchang duck is mainly distributed in Southwest China, and has the characteristics of fast growth rate and strong abilities in lipid deposition in the liver. In order to investigate the effects of domestication process on formation of the unique characteristics of Jianchang duck, the whole genome of sixteen individuals and three pooling of Jianchang duck were re-sequenced, and genome data of 70 mallards and 83 domestic ducks from thirteen different places in China were obtained from NCBI. The population stratification and evolution analysis showed gene exchanges existed between the Jianchang and other domestic duck populations, as well as Jianchang ducks and mallards. Genomic comparison between mallards and Jianchang ducks showed genes, including CNTN1, CHRNA9, and SHANK2, which is involved in brain and nerve development, experienced strong positive selection in the process of Jianchang duck domestication. The genomic comparison between Jianchang and domestic duck populations showed that HSD17B12 and ESM1, which affect lipid metabolism, experienced strong positive selection during the domestication process. FST analysis among populations of Jianchang duck with different plumage colors indicated that MITF was related to the phenotype of a white feather, while MC1R was related to the phenotype of hemp feather. Our results provided a base for the domestication process of Jianchang duck and the genomic genes for unique traits.
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Affiliation(s)
- Lei Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Jiazhong Guo
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Yang Xi
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Shengchao Ma
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Yanying Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Hua He
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Jiwen Wang
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Chunchun Han
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Lili Bai
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Ahsan Mustafa
- Institute of Animal Nutrition, Key Laboratory for Animal Disease-Resistance Nutrition of China, Ministry of Education, Sichuan Agricultural University, Chengdu, P.R. China
| | - Hehe Liu
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
| | - Liang Li
- Farm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, P.R. China
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141
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Zheng Z, Wang X, Li M, Li Y, Yang Z, Wang X, Pan X, Gong M, Zhang Y, Guo Y, Wang Y, Liu J, Cai Y, Chen Q, Okpeku M, Colli L, Cai D, Wang K, Huang S, Sonstegard TS, Esmailizadeh A, Zhang W, Zhang T, Xu Y, Xu N, Yang Y, Han J, Chen L, Lesur J, Daly KG, Bradley DG, Heller R, Zhang G, Wang W, Chen Y, Jiang Y. The origin of domestication genes in goats. SCIENCE ADVANCES 2020; 6:eaaz5216. [PMID: 32671210 PMCID: PMC7314551 DOI: 10.1126/sciadv.aaz5216] [Citation(s) in RCA: 62] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 03/06/2020] [Indexed: 05/22/2023]
Abstract
Goat domestication was critical for agriculture and civilization, but its underlying genetic changes and selection regimes remain unclear. Here, we analyze the genomes of worldwide domestic goats, wild caprid species, and historical remains, providing evidence of an ancient introgression event from a West Caucasian tur-like species to the ancestor of domestic goats. One introgressed locus with a strong signature of selection harbors the MUC6 gene, which encodes a gastrointestinally secreted mucin. Experiments revealed that the nearly fixed introgressed haplotype confers enhanced immune resistance to gastrointestinal pathogens. Another locus with a strong signal of selection may be related to behavior. The selected alleles at these two loci emerged in domestic goats at least 7200 and 8100 years ago, respectively, and increased to high frequencies concurrent with the expansion of the ubiquitous modern mitochondrial haplogroup A. Tracking these archaeologically cryptic evolutionary transformations provides new insights into the mechanisms of animal domestication.
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Affiliation(s)
- Zhuqing Zheng
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xihong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Ming Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yunjia Li
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Zhirui Yang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xiaolong Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Xiangyu Pan
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Mian Gong
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yingwei Guo
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Wang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Jing Liu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yudong Cai
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Qiuming Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Moses Okpeku
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Discipline of Genetics, School of Life Science, University of Kwazulu-Natal, Durban 4000, South Africa
| | - Licia Colli
- Dipartimento di Scienze Animali, della Nutrizione e degli Alimenti, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, via Emilia Parmense n. 84, 29122, Piacenza (PC), Italy
- BioDNA–Centro di Ricerca sulla Biodiversità e sul DNA Antico, Facoltà di Scienze Agrarie, Alimentari e Ambientali, Università Cattolica del S. Cuore, via Emilia Parmense n. 84, 29122, Piacenza (PC), Italy
| | - Dawei Cai
- Research Center for Chinese Frontier Archaeology, Jilin University, Changchun 130012, China
| | - Kun Wang
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | - Shisheng Huang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | | | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, PB 76169-133, Iran
| | - Wenguang Zhang
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot 010018, China
| | - Tingting Zhang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yangbin Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Naiyi Xu
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yi Yang
- Institute of Preventive Veterinary Medicine, Zhejiang Provincial Key Laboratory of Preventive Veterinary Medicine, College of Animal Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jianlin Han
- CAAS-ILRI Joint Laboratory on Livestock and Forage Genetic Resources, Institute of Animal Science, Chinese Academy of Agriculture Sciences (CAAS), Beijing 100193, China
- International Livestock Research Institute (ILRI), Nairobi 00100, Kenya
| | - Lei Chen
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
| | | | - Kevin G. Daly
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Daniel G. Bradley
- Smurfit Institute of Genetics, Trinity College Dublin, Dublin 2, Ireland
| | - Rasmus Heller
- Section for Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen N 2200, Denmark
| | - Guojie Zhang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- China National GeneBank, BGI-Shenzhen, Shenzhen 518083, China
- Section for Ecology and Evolution, Department of Biology, University of Copenhagen, DK-2100 Copenhagen, Denmark
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Wen Wang
- State Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650223, China
- Center for Ecological and Environmental Sciences, Northwestern Polytechnical University, Xi’an 710072, China
- Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming 650223, China
| | - Yulin Chen
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yu Jiang
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
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142
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Gao G, Zhang K, Zhao X, Wu R, Zhong H, Li J, Li C, Xie Y, Wang Q. Molecular cloning of the goose GnRH gene and identification of GnRH polymorphisms associated with laying traits. Br Poult Sci 2020; 61:502-507. [PMID: 32306753 DOI: 10.1080/00071668.2020.1758298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
1. Egg-laying traits are important economic characteristics in goose production (Anser cygnoides). The gene GnRH, which encodes gonadotropin-releasing hormone, is a strong candidate gene for egg-laying traits in avian species. 2. In this study, a 3520 bp genomic sequence and a 279 bp mRNA sequence for GnRH, which encoded 92 amino acids, were determined. The GnRH DNA sequence contains four exons and three introns, and the DNA and deduced amino acid sequences were highly conserved across mammals (human, macaque, cow, and sheep) and avians (chicken, fulmar and quail). 3. Using a direct sequencing method, 46 single nucleotide polymorphisms (SNPs) were identified in the GnRH genomic sequence that were shared between two Sichuan White goose populations (217 and 208 individuals). Furthermore, 44 haplotypes were constructed using a sliding window approach. Association analysis between the SNPs and haplotypes and egg-laying traits showed that 10 SNPs affected the first egg weight, average egg weight, egg number at 48 weeks and egg number at 64 weeks. 4. These results lay the foundation for further studies of the function of GnRH in geese and provide a theoretical basis for marker-assisted selection of egg-laying traits in the Sichuan white goose population.
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Affiliation(s)
- G Gao
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - K Zhang
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - X Zhao
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - R Wu
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China
| | - H Zhong
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - J Li
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - C Li
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - Y Xie
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
| | - Q Wang
- Poultry Science Department, Chongqing Academy of Animal Science , Chongqing, China.,Poultry Science Department, Chongqing Engineering Research Center of Goose Genetic Improvement , Chongqing, China
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143
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Luigi-Sierra MG, Mármol-Sánchez E, Amills M. Comparing the diversity of the casein genes in the Asian mouflon and domestic sheep. Anim Genet 2020; 51:470-475. [PMID: 32281138 DOI: 10.1111/age.12937] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2019] [Revised: 03/09/2020] [Accepted: 03/15/2020] [Indexed: 02/06/2023]
Abstract
We aimed to determine whether casein variants that are currently segregating in ovine populations existed before the domestication of sheep or, to the contrary, if their emergence is much more recent. To this end, we have retrieved whole-genome sequences from Iranian and domestic sheep from Africa, Europe, South and East Asia and West Asia. Population structure analysis based on 55,352,935 SNPs revealed a clear separation between Iranian mouflons and domestic sheep. Moreover, we also observed a strong genetic differentiation between Iranian mouflons sampled in geographic areas close to Tehran and Tabriz. Based on sequence data, hundreds of SNPs mapping to the casein αS1 (CSN1S1, 248 SNPs), casein αS2 (CSN1S2, 268 SNPs), casein ß (CSN2, 146 SNPs) and casein κ (CSN3, 112 SNPs) genes were identified. Approximately 25-63.02% of the casein variation was shared between Iranian mouflons and domestic sheep, and the four domestic sheep populations also shared 44.2-57.4% of the casein polymorphic sites. These findings suggest that an important fraction of the casein variation present in domestic sheep was already segregating in the mouflon prior to its domestication. Genomic studies performed in horses and dogs are consistent with this view, suggesting that much of the diversity that we currently detect in domestic animals comes from standing variation already segregating in their wild ancestors.
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Affiliation(s)
- M G Luigi-Sierra
- Department of Animal Genetics, Centre for Research in Agricultural Genomics, CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain
| | - E Mármol-Sánchez
- Department of Animal Genetics, Centre for Research in Agricultural Genomics, CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain
| | - M Amills
- Department of Animal Genetics, Centre for Research in Agricultural Genomics, CSIC-IRTA-UAB-UB, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain.,Departament de Ciència Animal i dels Aliments, Facultat de Veterinària, Universitat Autònoma de Barcelona, Bellaterra, 08193, Spain
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144
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Naval-Sanchez M, McWilliam S, Evans B, Yáñez JM, Houston RD, Kijas JW. Changed Patterns of Genomic Variation Following Recent Domestication: Selection Sweeps in Farmed Atlantic Salmon. Front Genet 2020; 11:264. [PMID: 32318091 PMCID: PMC7147387 DOI: 10.3389/fgene.2020.00264] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/03/2019] [Accepted: 03/05/2020] [Indexed: 12/30/2022] Open
Abstract
The introduction of wild Atlantic salmon into captivity, and their subsequent artificial selection for production traits, has caused phenotypic differences between domesticated fish and their wild counterparts. Identification of regions of the genome underling these changes offers the promise of characterizing the early biological consequences of domestication. In the current study, we sequenced a population of farmed European Atlantic salmon and compared the observed patterns of SNP variation to those found in conspecific wild populations. This identified 139 genomic regions that contained significantly elevated SNP homozygosity in farmed fish when compared to their wild counterparts. The most extreme was adjacent to versican, a gene involved in control of neural crest cell migration. To control for false positive signals, a second and independent dataset of farmed and wild European Atlantic salmon was assessed using the same methodology. A total of 81 outlier regions detected in the first dataset showed significantly reduced homozygosity within the second one, strongly suggesting the genomic regions identified are enriched for true selection sweeps. Examination of the associated genes identified a number previously characterized as targets of selection in other domestic species and that have roles in development, behavior and olfactory system. These include arcvf, sema6, errb4, id2-like, and 6n1-like genes. Finally, we searched for evidence of parallel sweeps using a farmed population of North American origin. This failed to detect a convincing overlap to the putative sweeps present in European populations, suggesting the factors that drive patterns of variation under domestication and early artificial selection were largely independent. This is the first analysis on domestication of aquaculture species exploiting whole-genome sequence data and resulted in the identification of sweeps common to multiple independent populations of farmed European Atlantic salmon.
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Affiliation(s)
| | | | - Bradley Evans
- Salmon Enterprises of Tasmania Pty. Limited, Wayatinah, TAS, Australia
| | - José M Yáñez
- Faculty of Veterinary and Animal Sciences, University of Chile, Santiago, Chile
| | - Ross D Houston
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Midlothian, United Kingdom
| | - James W Kijas
- CSIRO Agriculture and Food, Brisbane, QLD, Australia
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145
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Perry GH. How human behavior can impact the evolution of genetically-mediated behavior in wild non-human species. J Comp Physiol A Neuroethol Sens Neural Behav Physiol 2020; 206:337-342. [PMID: 32201915 DOI: 10.1007/s00359-020-01415-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Revised: 02/24/2020] [Accepted: 02/27/2020] [Indexed: 11/29/2022]
Abstract
Humans intensely modify the ecosystems we inhabit. Many of the impacts that this behavior can have on other species also sharing these spaces are obvious. A prime example is the devastating current extinction crisis. Yet some populations of non-human, non-domesticated species survive or even appear to thrive in heavily disturbed or human-built habitats. Theoretically, this apparent paradox could be facilitated partly by the evolution of genetically-mediated trait adaptations to the impacts of human behavior. At the least, persistence in strongly modified habitats would provide requisite selection pressures for this process to potentially occur in the future. In fact, we have a growing number of well-characterized examples of morphological trait adaptations to human behavior. However, our knowledge of genetically-mediated behavioral adaptations in similar contexts is less well developed. In this review I set up and discuss several evolutionary scenarios by which human behavior might have impacted the evolution of genetically mediated behavior in non-human, non-domestic species and highlight several approaches that could be used in future studies of this process.
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Affiliation(s)
- George H Perry
- Department of Anthropology, Pennsylvania State University, University Park, PA, 16802, USA. .,Department of Biology, Pennsylvania State University, University Park, USA. .,Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, USA. .,DFG Center for Advanced Studies, University of Tübingen, Tübingen, Germany.
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146
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Molaee V, Bazzucchi M, De Mia GM, Otarod V, Abdollahi D, Rosati S, Lühken G. Phylogenetic analysis of small ruminant lentiviruses in Germany and Iran suggests their expansion with domestic sheep. Sci Rep 2020; 10:2243. [PMID: 32042070 PMCID: PMC7010740 DOI: 10.1038/s41598-020-58990-9] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2019] [Accepted: 01/21/2020] [Indexed: 11/09/2022] Open
Abstract
Small ruminant lentiviruses (SRLVs) are found in sheep in Germany and Iran. SRLVs have been classified into four genotypes: A-C and E. Genotype A has been subdivided into 20 subtypes. Previous studies suggested that, first, the ancestors of genotype A are those SRLVs found in Turkey, second, the evolution of SRLVs is related to the domestication process, and, third, SRLV infection was first observed in sheep in Iceland and the source of that infection was a flock imported from Germany. This study generated, for the first time, partial SRLV sequence data from German and Iranian sheep, enhancing our knowledge of the genetic and evolutionary relationships of SRLVs, and their associations with the domestication process. Based on 54 SRLV sequences from German and Iranian sheep, our results reveal: (1) SRLV subtypes A4, A5, A11, A16 and A21 (new) are found in German sheep and A22 (new) in Iranian sheep. (2) Genotype A has potentially an additional ancestor (A22), found in Iran, Lebanon and Jordan. (3) Subtype A22 is likely an old version of SRLVs. (4) The transmission routes of some SRLVs are compatible with domestication pathways. (5) This study found no evidence of Icelandic subtype A1 in German sheep.
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Affiliation(s)
- Vahid Molaee
- Institute of Animal Breeding and Genetics, Justus Liebig University Giessen (JLU), Ludwigstraße 21, 35390, Gießen, Germany.
| | - Moira Bazzucchi
- Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche Togo Rosati (IZSUM), Via G. Salvemini 1, 06126, Perugia, Italy
| | - Gian Mario De Mia
- Istituto Zooprofilattico Sperimentale dell'Umbria e delle Marche Togo Rosati (IZSUM), Via G. Salvemini 1, 06126, Perugia, Italy
| | - Vahid Otarod
- Quarantine and Biosafety Directorate General, Iran Veterinary Organization (IVO), Vali Asr Avenue, Seyed Jamaledin Asad Abadi Street, 6349, Tehran, Iran
| | - Darab Abdollahi
- Bureau of Animal Health and Disease Management, Iran Veterinary Organization (IVO), Vali Asr Avenue, Seyed Jamaledin Asad Abadi Street, 6349, Tehran, Iran
| | - Sergio Rosati
- Department of Veterinary Science, University of Turin (UNITO), Largo Paolo Braccini 2, 10095, Grugliasco, Torino, Italy
| | - Gesine Lühken
- Institute of Animal Breeding and Genetics, Justus Liebig University Giessen (JLU), Ludwigstraße 21, 35390, Gießen, Germany
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147
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Barbato M, Hailer F, Upadhyay M, Del Corvo M, Colli L, Negrini R, Kim ES, Crooijmans RPMA, Sonstegard T, Ajmone-Marsan P. Adaptive introgression from indicine cattle into white cattle breeds from Central Italy. Sci Rep 2020; 10:1279. [PMID: 31992729 PMCID: PMC6987186 DOI: 10.1038/s41598-020-57880-4] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Accepted: 12/26/2019] [Indexed: 11/19/2022] Open
Abstract
Cattle domestication occurred at least twice independently and gave rise to the modern taurine and indicine cattle breeds. European cattle diversity is generally dominated by taurine cattle, although elevated levels of indicine ancestry have been recorded in several breeds from southern Europe. Here we use genome-wide high-density SNP genotyping data to investigate the taurine and indicine ancestry in southern European cattle, based on a dataset comprising 508 individuals from 23 cattle breeds of taurine, indicine and mixed ancestry, including three breeds from Central Italy known to exhibit the highest levels of indicine introgression among southern European breeds. Based on local genomic ancestry analyses, we reconstruct taurine and indicine ancestry genome-wide and along chromosomes. We scrutinise local genomic introgression signals and identify genomic regions that have introgressed from indicine into taurine cattle under positive selection, harbouring genes with functions related to body size and feed efficiency. These findings suggest that indicine-derived traits helped enhance Central Italian cattle through adaptive introgression. The identified genes could provide genomic targets for selection for improved cattle performance. Our findings elucidate the key role of adaptive introgression in shaping the phenotypic features of modern cattle, aided by cultural and livestock exchange among historic human societies.
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Affiliation(s)
- Mario Barbato
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy.
| | - Frank Hailer
- School of Biosciences, Cardiff University, Cardiff, Wales, UK
| | - Maulik Upadhyay
- Animal Breeding and Genomics, Wageningen University & Research, Wageningen, The Netherlands.,Department of Animal Breeding and Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Marcello Del Corvo
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Licia Colli
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | - Riccardo Negrini
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy
| | | | | | | | - Paolo Ajmone-Marsan
- Università Cattolica del Sacro Cuore, Department of Animal Science Food and Nutrition - DIANA, Nutrigenomics and Proteomics Research Centre - PRONUTRIGEN, and Biodiversity and Ancient DNA Research Centre, Università Cattolica del Sacro Cuore, Piacenza, Italy.
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148
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Glutamate receptors in domestication and modern human evolution. Neurosci Biobehav Rev 2020; 108:341-357. [DOI: 10.1016/j.neubiorev.2019.10.004] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 09/28/2019] [Accepted: 10/07/2019] [Indexed: 02/08/2023]
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149
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Henkel J, Saif R, Jagannathan V, Schmocker C, Zeindler F, Bangerter E, Herren U, Posantzis D, Bulut Z, Ammann P, Drögemüller C, Flury C, Leeb T. Selection signatures in goats reveal copy number variants underlying breed-defining coat color phenotypes. PLoS Genet 2019; 15:e1008536. [PMID: 31841508 PMCID: PMC6936872 DOI: 10.1371/journal.pgen.1008536] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2019] [Revised: 12/30/2019] [Accepted: 11/23/2019] [Indexed: 12/16/2022] Open
Abstract
Domestication and human selection have formed diverse goat breeds with characteristic phenotypes. This process correlated with the fixation of causative genetic variants controlling breed-specific traits within regions of reduced genetic diversity, so called selection signatures or selective sweeps. Using whole genome sequencing of DNA pools (pool-seq) from 20 genetically diverse modern goat breeds and bezoars, we identified 2,239 putative selection signatures. In two Pakistani goat breeds, Pak Angora and Barbari, we found selection signatures in a region harboring KIT, a gene involved in melanoblast development, migration, and survival. The search for candidate causative variants responsible for these selective sweeps revealed two different copy number variants (CNVs) downstream of KIT that were exclusively present in white Pak Angora and white-spotted Barbari goats. Several Swiss goat breeds selected for specific coat colors showed selection signatures at the ASIP locus encoding the agouti signaling protein. Analysis of these selective sweeps revealed four different CNVs associated with the white or tan (AWt), Swiss markings (Asm), badgerface (Ab), and the newly proposed peacock (Apc) allele. RNA-seq analyses on skin samples from goats with the different CNV alleles suggest that the identified structural variants lead to an altered expression of ASIP between eumelanistic and pheomelanistic body areas. Our study yields novel insights into the genetic control of pigmentation by identifying six functionally relevant CNVs. It illustrates how structural changes of the genome have contributed to phenotypic evolution in domestic goats. Domestic animals have been selected for hundreds or sometimes even thousands of years for traits that were appreciated by their human owners. This process correlated with the fixation of causative genetic variants controlling breed-specific traits within regions of reduced genetic diversity, so called selection signatures or selective sweeps. We conducted a comprehensive screen for selection signatures in 20 phenotypically and genetically diverse modern goat breeds and identified a total of 2,239 putative selection signatures in our dataset. Follow-up experiments on selection signatures harboring known candidate genes for coat color revealed six different copy number variants (CNVs). Two of these CNVs were located in the 3’-flanking region of KIT and associated with a completely white coat color phenotype in Pak Angora goats and a white-spotted coat color phenotype in Barbari goats, respectively. The other four CNVs were located at the ASIP locus. They were associated with four different types of coat color patterning in seven Swiss goat breeds. Their functional effect is mediated by region-specific quantitative changes in ASIP mRNA expression. Our study illustrates how structural changes of the genome have contributed to phenotypic evolution in domestic goats.
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Affiliation(s)
- Jan Henkel
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- DermFocus, University of Bern, Bern, Switzerland
| | - Rashid Saif
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- Institute of Biotechnology, Gulab Devi Educational Complex, Lahore, Pakistan
| | - Vidhya Jagannathan
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- DermFocus, University of Bern, Bern, Switzerland
| | - Corinne Schmocker
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
| | - Flurina Zeindler
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, Zollikofen, Switzerland
| | | | - Ursula Herren
- Swiss Goat Breeding Association, Zollikofen, Switzerland
| | | | - Zafer Bulut
- Department of Biochemistry, Faculty of Veterinary Medicine, Selcuk University, Konya, Turkey
| | | | - Cord Drögemüller
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- DermFocus, University of Bern, Bern, Switzerland
| | - Christine Flury
- School of Agricultural, Forest and Food Sciences, Bern University of Applied Sciences, Zollikofen, Switzerland
| | - Tosso Leeb
- Institute of Genetics, Vetsuisse Faculty, University of Bern, Bern, Switzerland
- DermFocus, University of Bern, Bern, Switzerland
- * E-mail:
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150
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Guo J, Zhong J, Li L, Zhong T, Wang L, Song T, Zhang H. Comparative genome analyses reveal the unique genetic composition and selection signals underlying the phenotypic characteristics of three Chinese domestic goat breeds. Genet Sel Evol 2019; 51:70. [PMID: 31771503 PMCID: PMC6880376 DOI: 10.1186/s12711-019-0512-4] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 11/15/2019] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND As one of the important livestock species around the world, goats provide abundant meat, milk, and fiber to fulfill basic human needs. However, the genetic loci that underlie phenotypic variations in domestic goats are largely unknown, particularly for economically important traits. In this study, we sequenced the whole genome of 38 goats from three Chinese breeds (Chengdu Brown, Jintang Black, and Tibetan Cashmere) and downloaded the genome sequence data of 30 goats from five other breeds (four non-Chinese and one Chinese breed) and 21 Bezoar ibexes to investigate the genetic composition and selection signatures of the Chinese goat breeds after domestication. RESULTS Based on population structure analysis and FST values (average FST = 0.22), the genetic composition of Chengdu Brown goats differs considerably from that of Bezoar ibexes as a result of geographic isolation. Strikingly, the genes under selection that we identified in Tibetan Cashmere goats were significantly enriched in the categories hair growth and bone and nervous system development, possibly because they are involved in adaptation to high-altitude. In particular, we found a large difference in allele frequency of one novel SNP (c.-253G>A) in the 5'-UTR of FGF5 between Cashmere goats and goat breeds with short hair. The mutation at this site introduces a start codon that results in the occurrence of a premature FGF5 protein and is likely a natural causal variant that is involved in the long hair phenotype of cashmere goats. The haplotype tagged with the AGG-allele in exon 12 of DSG3, which encodes a cell adhesion molecule that is expressed mainly in the skin, was almost fixed in Tibetan Cashmere goats, whereas this locus still segregates in the lowland goat breeds. The pigmentation gene KITLG showed a strong signature of selection in Tibetan Cashmere goats. The genes ASIP and LCORL were identified as being under positive selection in Jintang Black goats. CONCLUSIONS After domestication, geographic isolation of some goat breeds has resulted in distinct genetic structures. Furthermore, our work highlights several positively selected genes that likely contributed to breed-related traits in domestic goats.
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Affiliation(s)
- Jiazhong Guo
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Jie Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Li Li
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Tao Zhong
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Linjie Wang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
| | - Tianzeng Song
- Institute of Animal Science, Tibet Academy of Agricultural and Animal Husbandry Sciences, Lhasa, 850009 China
| | - Hongping Zhang
- College of Animal Science and Technology, Sichuan Agricultural University, Chengdu, 611130 China
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