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Cho Y, Kim JY, Kim SK, Kim SY, Kim N, Lee J, Park JL. Whole-genome sequencing analysis of soybean diversity across different countries and selection signature of Korean soybean accession. G3 (BETHESDA, MD.) 2024; 14:jkae118. [PMID: 38833595 PMCID: PMC11304964 DOI: 10.1093/g3journal/jkae118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 04/24/2024] [Accepted: 05/20/2024] [Indexed: 06/06/2024]
Abstract
Soybean is an important agricultural crop known for its high protein and oil content, contributing to essential nutritional and health benefits for humans. Domesticated in China over 5,000 years ago, soybean has since adapted to diverse environments and spread worldwide. This study aimed to investigate the genomic characteristics and population structures of 2,317 publicly available soybean whole-genome sequences from diverse geographical regions, including China, Korea, Japan, Europe, North America, and South America. We used large-scale whole-genome sequencing data to perform high-resolution analyses to reveal the genetic characteristics of soybean accessions. Soybean accessions from China and Korea exhibited landrace characteristics, indicating higher genetic diversity and adaptation to local environments. On the other hand, soybean accessions from Japan, the European Union, and South America were found to have low genetic diversity due to artificial selection and breeding for agronomic traits. We also identified key variants and genes associated with the ability to adapt to different environments. In Korean soybean accessions, we observed strong selection signals for isoflavone synthesis, an adaptive trait critical for improving soybean adaptability, survival, and reproductive success by mitigating environmental stress. Identifying specific genomic regions showing unique patterns of selective sweeps for genes such as HIDH, CYP73A11, IFS1, and CYP81E11 associated with isoflavone synthesis provided valuable insights into potential adaptation mechanisms. Our research has significantly improved our understanding of soybean diversity at the genetic level. We have identified key genetic variants and genes influencing adaptability, laying the foundation for future advances in genomics-based breeding programs and crop improvement efforts.
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Affiliation(s)
- Youngbeom Cho
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Jae-Yoon Kim
- Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Seon-Kyu Kim
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Seon-Young Kim
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
- Personalized Genomic Medicine Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Namshin Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Jinhyuk Lee
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
- Disease Target Structure Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
| | - Jong-Lyul Park
- Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
- Aging Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea
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Liu Z, Tan X, Jin Q, Zhan W, Liu G, Cui X, Wang J, Meng X, Zhu R, Wang K. Multiomics analyses of Jining Grey goat and Boer goat reveal genomic regions associated with fatty acid and amino acid metabolism and muscle development. Anim Biosci 2024; 37:982-992. [PMID: 37946414 PMCID: PMC11065957 DOI: 10.5713/ab.23.0316] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2023] [Revised: 09/30/2023] [Accepted: 10/31/2023] [Indexed: 11/12/2023] Open
Abstract
OBJECTIVE Jining Grey goat is a local Chinese goat breed that is well known for its high fertility and excellent meat quality but shows low meat production performance. Numerous studies have focused on revealing the genetic mechanism of its high fertility, but its highlighting meat quality and muscle growth mechanism still need to be studied. METHODS In this research, an integrative analysis of the genomics and transcriptomics of Jining Grey goats compared with Boer goats was performed to identify candidate genes and pathways related to the mechanisms of meat quality and muscle development. RESULTS Our results overlap among five genes (ABHD2, FN1, PGM2L1, PRKAG3, RAVER2) and detected a set of candidate genes associated with fatty acid metabolism (PRKAG3, HADHB, FASN, ACADM), amino acid metabolism (KMT2C, PLOD3, NSD2, SETDB1, STT3B, MAN1A2, BCKDHB, NAT8L, P4HA3) and muscle development (MSTN, PPARGC1A, ANKRD2). Several pathways have also been detected, such as the FoxO signaling pathway and Apelin signaling pathway that play roles in lipid metabolism, lysine degradation, N-glycan biosynthesis, valine, leucine and isoleucine degradation that involving with amino acid metabolism. CONCLUSION The comparative genomic and transcriptomic analysis of Jining Grey goat and Boer goat revealed the mechanisms underlying the meat quality and meat productive performance of goats. These results provide valuable information for future breeding of goats.
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Affiliation(s)
- Zhaohua Liu
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Xiuwen Tan
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Qing Jin
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
| | - Wangtao Zhan
- Shandong Animal Husbandry General Station, Jinan 250100,
China
| | - Gang Liu
- Shandong Animal Husbandry General Station, Jinan 250100,
China
| | - Xukui Cui
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Jianying Wang
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Xianfeng Meng
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Rongsheng Zhu
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
| | - Ke Wang
- Institute of Animal Science and Veterinary Medicine, Shandong Key Lab of Animal Disease Control and Breeding, Shandong Academy of Agricultural Sciences, Jinan 250100,
China
- Key Laboratory of Livestock and Poultry Multi-omics of MARA, Jinan 250100,
China
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Liu LL, Meng J, Ma HY, Cao H, Liu WJ. Candidate genes for litter size in Xinjiang sheep identified by Specific Locus Amplified Fragment (SLAF) sequencing. Anim Biotechnol 2023; 34:3053-3062. [PMID: 36244020 DOI: 10.1080/10495398.2022.2131561] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
The aim of this study was to investigate the selection signatures at a genome-wide level in 'Pishan' sheep using Specific Locus Amplified Fragment (SLAF)-seq. Blood samples from 126 ewes were sequenced using SLAF tags, and the ovarian tissues from 8 ewes (Bashbay sheep, a single litter size group (SG group); 'Pishan' sheep, double litter size group (DG group)) were collected to detect expression levels by quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR). Selection signature analysis was performed using global fixation index (Fst) and nucleotide diversity (π) ratio. A total of 1,192,168 high-quality SLAFs were identified. Notably, 2380 candidate regions under selection using two approaches were identified. A total of 2069 genes were identified, which were involved in dopaminergic synapses, thyroid hormone synthesis, ovarian steroidogenesis and thyroid hormone signalling pathways. Furthermore, Growth Differentiation Factor 9 (GDF9), Period Circadian Regulator 2 (PER2), Thyroid Stimulating Hormone Receptor (TSHR), and Nuclear Receptor Coactivator 1 (NCOA1) reside within these regions and pathways. The expression levels of GDF9 and PER2 genes in sheep tissue of the DG group were significantly higher than those in the SG group. These genes are interesting candidates for litter size and provide a starting point for further identification of conservation strategies for 'Pishan' sheep.
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Affiliation(s)
- Ling-Ling Liu
- Department of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Jun Meng
- Department of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Hai-Yu Ma
- Department of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Hang Cao
- Department of Animal Science, Xinjiang Agricultural University, Urumqi, China
| | - Wu-Jun Liu
- Department of Animal Science, Xinjiang Agricultural University, Urumqi, China
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Ghildiyal K, Nayak SS, Rajawat D, Sharma A, Chhotaray S, Bhushan B, Dutt T, Panigrahi M. Genomic insights into the conservation of wild and domestic animal diversity: A review. Gene 2023; 886:147719. [PMID: 37597708 DOI: 10.1016/j.gene.2023.147719] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 06/20/2023] [Accepted: 08/16/2023] [Indexed: 08/21/2023]
Abstract
Due to environmental change and anthropogenic activities, global biodiversity has suffered an unprecedented loss, and the world is now heading toward the sixth mass extinction event. This urges the need to step up our efforts to promote the sustainable use of animal genetic resources and plan effective strategies for their conservation. Although habitat preservation and restoration are the primary means of conserving biodiversity, genomic technologies offer a variety of novel tools for identifying biodiversity hotspots and thus, support conservation efforts. Conservation genomics is a broad area of science that encompasses the application of genomic data from thousands or tens of thousands of genome-wide markers to address important conservation biology concerns. Genomic approaches have revolutionized the way we understand and manage animal populations, providing tools to identify and preserve unique genetic variants and alleles responsible for adaptive genetic variation, reducing the deleterious consequences of inbreeding, and increasing the adaptive potential of threatened species. The advancement of genomic technologies, particularly comparative genomic approaches, and the increased accessibility of genomic resources in the form of genome-enabled taxa for non-model organisms, provides a distinct advantage in defining conservation units over traditional genetics approaches. The objective of this review is to provide an exhaustive overview of the concept of conservation genomics, discuss the rationale behind the transition from conservation genetics to genomic approaches, and emphasize the potential applications of genomic techniques for conservation purposes. We also highlight interesting case studies in both livestock and wildlife species where genomic techniques have been used to accomplish conservation goals. Finally, we address some challenges and future perspectives in this field.
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Affiliation(s)
- Kanika Ghildiyal
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sonali Sonejita Nayak
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Divya Rajawat
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Anurodh Sharma
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Supriya Chhotaray
- Animal Genetics and Breeding Division, ICAR-National Dairy Research Institute, Karnal, Haryana, India
| | - Bharat Bhushan
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Triveni Dutt
- Livestock Production and Management Section, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
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Gao C, Wang K, Hu X, Lei Y, Xu C, Tian Y, Sun G, Tian Y, Kang X, Li W. Conservation priority and run of homozygosity pattern assessment of global chicken genetic resources. Poult Sci 2023; 102:103030. [PMID: 37716234 PMCID: PMC10511814 DOI: 10.1016/j.psj.2023.103030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Revised: 07/30/2023] [Accepted: 08/11/2023] [Indexed: 09/18/2023] Open
Abstract
The conservation of genetic resources is becoming increasingly important for the sustainable development of the poultry industry. In the present study, we systematically analyzed the population structure, conservation priority, runs of homozygosity (ROH) of chicken breeds globally, and proposed rational conservation strategies. We used a 600K Affymetrix Axiom HD genotyping SNP array dataset of 2,429 chickens from 134 populations. The chickens were divided into 5 groups based on their country of origin and sampling location: Asian chickens (AS-LOC), African chickens (AF), European local chickens (EU-LOC), Asian breeds sampled in Germany (AS-DE), and European breeds sampled in Germany (EU-DE). The results indicated that the population structure was consistent with the actual geographical distribution of the populations. AS-LOC had the highest positive contribution to the total gene (HT, 1.00%,) and allelic diversity (AT, 0.0014%), the lowest inbreeding degree and the fastest linkage disequilibrium (LD) decay rate; the lowest contribution are derived by European ex situ chicken breeds (EU-DE:HT = -0.072%, AT = -0.0014%), which showed the highest inbreeding and slowest LD decay. Breeds farmed in ex situ (AS-DE, EU-DE) conditions exhibited reduced genetic diversity and increased inbreeding due to small population size. Given limited funds, it is a better choice for government to conserve the breeds with the highest contribution to genetic diversity in each group. Therefore, we evaluated the contribution of each breed to genetic and allelic diversity in 5 groups. Among each group, KUR(AF), BANG(AS-LOC), ALxx(EU-LOC), BHwsch(AS-DE), and ARw(EU-DE) had the highest contribution to gene diversity in the order of the above grouping. Similarly, according to the allelic diversity standard (in the same order), ZIMxx, PIxx, ALxx, SHsch, and ARsch had the highest contribution. After analyzing ROH, we found a total of 144,708 fragments and 27 islands. The gene and genome regions identified by the ROH islands and QTLs indicate that chicken breeds have potential for adaptation to different production systems. Based on these findings, it is recommended to prioritize the conservation of breeds with the highest genetic diversity in each group, while paying more attention to the conservation of Asian and African breeds. Furthermore, providing a valuable reference for the conservation and utilization of chicken.
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Affiliation(s)
- Chaoqun Gao
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Kejun Wang
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Xiaoyu Hu
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Yanru Lei
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Chunhong Xu
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Yixiang Tian
- College of Animal Science and Veterinary Medicine, Henan Institute of Science and Technology, Xinxiang 453003, Henan, China
| | - Guirong Sun
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Yadong Tian
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Xiangtao Kang
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China
| | - Wenting Li
- Henan Innovative Engineering Research Center of Poultry Germplasm Resource, College of Animal Science and Technology, Henan Agricultural University, Zhengzhou 450046, Henan, China; The Shennong Laboratory, Zhengzhou 450046, Henan, China.
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Saif R, Mahmood T, Zia S, Henkel J, Ejaz A. Genomic selection pressure discovery using site-frequency spectrum and reduced local variability statistics in Pakistani Dera-Din-Panah goat. Trop Anim Health Prod 2023; 55:331. [PMID: 37750990 DOI: 10.1007/s11250-023-03758-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 09/12/2023] [Indexed: 09/27/2023]
Abstract
BACKGROUND Population geneticists have long sought to comprehend various selection traces accumulated in the goat genome due to natural or human driven artificial selection through breeding practices, which led the wild animals to domestication, so understanding evolutionary process may helpful to utilize the full genetic potential of goat genome. METHODS AND RESULTS As a step forward to pinpoint the selection signals in Pakistani Dera-Din-Panah (DDP) goat, whole-genome pooled sequencing (n = 12) was performed, and 618,236,192 clean paired-end reads were mapped against ARS1 reference goat assembly. Five different selection signature statistics were applied using four site-frequency spectrum (SFS) methods (Tajima's D ([Formula: see text]), Fay and Wu's H ([Formula: see text]), Zeng's E ([Formula: see text]), [Formula: see text]) and one reduced local variability approach named pooled heterozygosity ([Formula: see text]). The under-selection regions were annotated with significant threshold values of [Formula: see text]≥4.7, [Formula: see text]≥6, [Formula: see text]≥2.5, Pool-HMM ≥ 12, and [Formula: see text]≥5 that resulted in accumulative 364 candidate gene hits. The highest genomic selection signals were observed on Chr. 4, 6, 10, 12, 15, 16, 18, 20, and 27 and harbor ADAMTS6, CWC27, RELN, MYCBP2, FGF14, STIM1, CFAP74, GNB1, CALML6, TMEM52, FAM149A, NADK, MMP23B, OPN3, FH, MFHAS1, KLKB1, RRM1, KMO, SPEF2, F11, KIT, KMO, ERI1, ATP8B4, and RHOG genes. Next, the validation of our captured genomic hits was also performed by more than one applied statistics which harbor meat production, immunity, and reproduction associated genes to strengthen our hypothesis of under-selection traits in this Pakistani goat breed. Furthermore, common candidate genes captured by more than one statistical method were subjected to gene ontology and KEGG pathway analysis to get insights of particular biological processes associated with this goat breed. CONCLUSION Current perception of genomic architecture of DDP goat provides a better understanding to improve its genetic potential and other economically important traits of medium to large body size, milk, and fiber production by updating the genomic insight driven breeding strategies to boost the livestock and agriculture-based economy of the country.
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Affiliation(s)
- Rashid Saif
- Department of Biotechnology, Qarshi University, Lahore, Pakistan.
- Decode Genomics, Punjab University Employees Housing Scheme, Lahore, Pakistan.
| | - Tania Mahmood
- Decode Genomics, Punjab University Employees Housing Scheme, Lahore, Pakistan
| | - Saeeda Zia
- Department of Sciences and Humanities, National University of Computer and Emerging Sciences, Lahore, Pakistan
| | - Jan Henkel
- MGZ-Medical Genetics Center, Munich, Germany
| | - Aniqa Ejaz
- Decode Genomics, Punjab University Employees Housing Scheme, Lahore, Pakistan
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Amiri Ghanatsaman Z, Ayatolahi Mehrgardi A, Asadollahpour Nanaei H, Esmailizadeh A. Comparative genomic analysis uncovers candidate genes related with milk production and adaptive traits in goat breeds. Sci Rep 2023; 13:8722. [PMID: 37253766 DOI: 10.1038/s41598-023-35973-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2022] [Accepted: 05/26/2023] [Indexed: 06/01/2023] Open
Abstract
During the process of animal domestication, both natural and artificial selection cause variation in allele frequencies among populations. Identifying genomic areas of selection in domestic animals may aid in the detection of genomic areas linked to ecological and economic traits. We studied genomic variation in 140 worldwide goat individuals, including 75 Asian, 30 African and 35 European goats. We further carried out comparative population genomics to detect genomic regions under selection for adaptability to harsh conditions in local Asian ecotypes and also milk production traits in European commercial breeds. In addition, we estimated the genetic distances among 140 goat individuals. The results showed that among all studied goat groups, local breeds from West and South Asia emerged as an independent group. Our search for selection signatures in local goats from West and South Asia revealed candidate genes related to adaptation to hot climate (HSPB6, HSF4, VPS13A and NBEA genes) and immune response (IL7, IL5, IL23A and LRFN5) traits. Furthermore, selection signatures in European commercial goats involved several milk production related genes, such as VPS13C, NCAM2, TMPRSS15, CSN3 and ABCG2. The identified candidate genes could be the fundamental genetic resource for enhancement of goat production and environmental-adaptive traits, and as such they should be used in goat breeding programs to select more efficient breeds.
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Affiliation(s)
- Zeinab Amiri Ghanatsaman
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, PB, Iran
- Animal Science Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran
| | - Ahmad Ayatolahi Mehrgardi
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, PB, Iran.
| | - 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
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, 76169-133, PB, Iran.
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Xiong J, Bao J, Hu W, Shang M, Zhang L. Whole-genome resequencing reveals genetic diversity and selection characteristics of dairy goat. Front Genet 2023; 13:1044017. [PMID: 36685859 PMCID: PMC9852865 DOI: 10.3389/fgene.2022.1044017] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 12/13/2022] [Indexed: 01/09/2023] Open
Abstract
The dairy goat is one of the earliest dairy livestock species, which plays an important role in the economic development, especially for developing countries. With the development of agricultural civilization, dairy goats have been widely distributed across the world. However, few studies have been conducted on the specific characteristics of dairy goat. In this study, we collected the whole-genome data of 89 goat individuals by sequencing 48 goats and employing 41 publicly available goats, including five dairy goat breeds (Saanen, Nubian, Alpine, Toggenburg, and Guanzhong dairy goat; n = 24, 15, 11, 6, 6), and three goat breeds (Guishan goat, Longlin goat, Yunshang Black goat; n = 6, 15, 6). Through compared the genomes of dairy goat and non-dairy goat to analyze genetic diversity and selection characteristics of dairy goat. The results show that the eight goats could be divided into three subgroups of European, African, and Chinese indigenous goat populations, and we also found that Australian Nubian, Toggenburg, and Australian Alpine had the highest linkage disequilibrium, the lowest level of nucleotide diversity, and a higher inbreeding coefficient, indicating that they were strongly artificially selected. In addition, we identified several candidate genes related to the specificity of dairy goat, particularly genes associated with milk production traits (GHR, DGAT2, ELF5, GLYCAM1, ACSBG2, ACSS2), reproduction traits (TSHR, TSHB, PTGS2, ESR2), immunity traits (JAK1, POU2F2, LRRC66). Our results provide not only insights into the evolutionary history and breed characteristics of dairy goat, but also valuable information for the implementation and improvement of dairy goat cross breeding program.
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Consortium VG, Nijman IJ, Rosen BD, Bardou P, Faraut T, Cumer T, Daly KG, Zheng Z, Cai Y, Asadollahpour H, Kul BÇ, Zhang WY, Guangxin E, Ayin A, Baird H, Bakhtin M, Bâlteanu VA, Barfield D, Berger B, Blichfeldt T, Boink G, Bugiwati SRA, Cai Z, Carolan S, Clark E, Cubric-Curik V, Dagong MIA, Dorji T, Drew L, Guo J, Hallsson J, Horvat S, Kantanen J, Kawaguchi F, Kazymbet P, Khayatzadeh N, Kim N, Shah MK, Liao Y, Martínez A, Masangkay JS, Masaoka M, Mazza R, McEwan J, Milanesi M, Faruque MO, Nomura Y, Ouchene-Khelifi NA, Pereira F, Sahana G, Salavati M, Sasazaki S, Da Silva A, Simčič M, Sölkner J, Sutherland A, Tigchelaar J, Zhang H, Consortium E, Ajmone-Marsan P, Bradley DG, Colli L, Drögemüller C, Jiang Y, Lei C, Mannen H, Pompanon F, Tosser-Klopp G, Lenstra JA. Geographical contrasts of Y-chromosomal haplogroups from wild and domestic goats reveal ancient migrations and recent introgressions. Mol Ecol 2022; 31:4364-4380. [PMID: 35751552 DOI: 10.1111/mec.16579] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 06/12/2022] [Accepted: 06/20/2022] [Indexed: 11/29/2022]
Abstract
By their paternal transmission, Y-chromosomal haplotypes are sensitive markers of population history and male-mediated introgression. Previous studies identified biallelic single-nucleotide variants in the SRY, ZFY, DDX3Y genes, which in domestic goats identified four major Y-chromosomal haplotypes Y1A, Y1B, Y2A and Y2B with a marked geographic partitioning. Here, we extracted goat Y-chromosomal variants from whole-genome sequences of 386 domestic goats (75 breeds) and 7 wild goat species, which were generated by the VarGoats goat genome project. Phylogenetic analyses indicated domestic haplogroups corresponding to Y1B, Y2A and Y2B, respectively, whereas Y1A is split into Y1AA and Y1AB. All five haplogroups were detected in 26 ancient DNA samples from southeast Europe or Asia. Haplotypes from present-day bezoars are not shared with domestic goats and are attached to deep nodes of the trees and networks. Haplogroup distributions for 186 domestic breeds indicate ancient paternal population bottlenecks and expansions during the migrations into northern Europe, eastern and southern Asia and Africa south of the Sahara. In addition, sharing of haplogroups indicates male-mediated introgressions, most notably an early gene flow from Asian goats into Madagascar and the crossbreeding that in the 19th century resulted in the popular Boer and Anglo-Nubian breeds. More recent introgressions are those from European goats into the native Korean goat population and from Boer goat into Uganda, Kenya, Tanzania, Malawi and Zimbabwe. This study illustrates the power of the Y-chromosomal variants for reconstructing the history of domestic species with a wide geographic range.
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Affiliation(s)
| | - Isaäc J Nijman
- Utrecht Univ., Netherlands.,Univ. Medical Center Utrecht, Utrecht Univ, The Netherlands
| | | | - Philippe Bardou
- GenPhySE, Univ. Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Thomas Faraut
- GenPhySE, Univ. Toulouse, INRA, INPT, ENVT, Castanet Tolosan, France
| | - Tristan Cumer
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
| | | | - Zhuqing Zheng
- College of Animal Science & Technology, Northwest A&F Univ., Yangling, China
| | - Yudong Cai
- College of Animal Science & Technology, Northwest A&F Univ., Yangling, China
| | | | | | | | | | | | - Hayley Baird
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | | | - Valentin A Bâlteanu
- Inst. of Life SciencesUniv. Agricultural Sciences and Veterinary Medicine of Cluj-Napoca, Cluj-Napoca, Romania
| | | | - Beate Berger
- Univ. Natural Resources and Life Sciences Vienna (BOKU)
| | - Thor Blichfeldt
- Norwegian Association of Sheep and Goat Breeders, Aas, Norway
| | - Geert Boink
- Stichting Zeldzame Huisdierrassen, Wageningen, The Netherlands
| | | | | | | | | | | | | | - Tashi Dorji
- International Centre for Integrated Mountain Development, Kathmandu, Nepal
| | | | | | | | - Simon Horvat
- Univ. Ljubljana, Biotechnical Faculty, Ljubljana, Slovenia
| | - Juha Kantanen
- Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | | | | | | | - Namshin Kim
- Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, South Korea
| | | | - Yuying Liao
- Guangxi Key Laboratory of Livestock Genetic Improvement, Guangxi, China
| | | | | | | | - Raffaele Mazza
- Laboratorio Genetica e Servizi, Agrotis srl, Cremona, Italy
| | - John McEwan
- AgResearch, Invermay Agricultural Centre, Mosgiel, New Zealand
| | | | | | | | | | - Filipe Pereira
- IDENTIFICA Genetic Testing Maia & Centre for Functional Ecology, Porto, Portugal
| | | | | | | | | | - Mojca Simčič
- Univ. Ljubljana, Biotechnical Faculty, Ljubljana, Slovenia
| | | | | | | | | | | | - Paolo Ajmone-Marsan
- Univ. Cattolica del S. Cuore di Piacenza and BioDNA Biodiversity and Ancient DNA Res. Centre, Piacenza, Italy.,UCSC PRONUTRIGEN Nutrigenomics Res. Centre, Piacenza, Italy
| | | | - Licia Colli
- Univ. Cattolica del S. Cuore di Piacenza and BioDNA Biodiversity and Ancient DNA Res. Centre, Piacenza, Italy.,UCSC BioDNA Biodiversity and Ancient DNA Res. Centre, Piacenza, Italy
| | | | - Yu Jiang
- College of Animal Science & Technology, Northwest A&F Univ., Yangling, China
| | - Chuzhao Lei
- College of Animal Science & Technology, Northwest A&F Univ., Yangling, China
| | | | - François Pompanon
- Université Grenoble Alpes, Université Savoie Mont Blanc, CNRS, LECA, Grenoble, France
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10
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Genome-Wide Selective Analysis of Boer Goat to Investigate the Dynamic Heredity Evolution under Different Stages. Animals (Basel) 2022; 12:ani12111356. [PMID: 35681821 PMCID: PMC9204547 DOI: 10.3390/ani12111356] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2022] [Revised: 05/07/2022] [Accepted: 05/23/2022] [Indexed: 12/16/2022] Open
Abstract
Boer goats, as kemp in meat-type goats, are selected and bred from African indigenous goats under a long period of artificial selection. Their advantages in multiple economic traits, particularly their plump growth, have attracted worldwide attention. The current study displayed the genome-wide selection signature analyses of South African indigenous goat (AF), African Boer (BH), and Australian Boer (AS) to investigate the hereditary basis of artificial selection in different stages. Four methods (principal component analysis, nucleotide diversity, linkage disequilibrium decay, and neighbor-joining tree) implied the genomic diversity changes with different artificial selection intensities in Boer goats. In addition, the θπ, FST, and XP-CLR methods were used to search for the candidate signatures of positive selection in Boer goats. Consequently, 339 (BH vs. AF) and 295 (AS vs. BH) candidate genes were obtained from SNP data. Especially, 10 genes (e.g., BMPR1B, DNER, ITGAL, and KIT) under selection in both groups were identified. Functional annotation analysis revealed that these genes are potentially responsible for reproduction, metabolism, growth, and development. This study used genome-wide sequencing data to identify inheritance by artificial selection. The results of the current study are valuable for future molecular-assisted breeding and genetic improvement of goats.
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11
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Torres-Hernández G, Maldonado-Jáquez JA, Granados-Rivera LD, Salinas-González H, Castillo-Hernández G. Status quo of genetic improvement in local goats: a review. Arch Anim Breed 2022; 65:207-221. [PMID: 35693297 PMCID: PMC9176210 DOI: 10.5194/aab-65-207-2022] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Accepted: 04/14/2022] [Indexed: 11/26/2022] Open
Abstract
This review aims to summarize and synthesize the
fragmented information available on the genetic improvement of local goats
(criollo, indigenous, native) on the American and other continents, where
populations with these goats have an important role in food security and the
economy of rural communities, as well as in conservation of biodiversity and
productivity improvement. Topics such as the current state of goat
production globally, conservation programs, resistance to parasites and
diseases, use of phenotypical characteristics and genomic information, and
molecular markers for genetic improvement are addressed. The main
challenges, opportunities, and limitations described in recent literature
concerning local goats in the immediate future are discussed.
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Affiliation(s)
| | - Jorge Alonso Maldonado-Jáquez
- Colegio de Postgraduados-Campus Montecillo, 56230 Montecillo, Estado
de México, México
- Instituto Nacional de Investigaciones Forestales, Agrícolas y
Pecuarias, Centro de Investigación Regional Norte Centro, Campo
Experimental La Laguna, 27440 Matamoros, Coahuila, México
| | - Lorenzo Danilo Granados-Rivera
- Instituto Nacional de Investigaciones Forestales, Agrícolas y
Pecuarias, Centro de Investigación Regional Noreste, Campo Experimental
General Terán, 67400 General Terán, Nuevo León, México
| | | | - Gabriela Castillo-Hernández
- Colegio de Postgraduados-Campus Montecillo, 56230 Montecillo, Estado
de México, México
- Facultad de Estudios
Superiores Cuautitlán, Universidad Nacional Autónoma de México, 54714 Cuautitlán Izcalli, Estado de
México, México
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12
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Cho Y, Kim JY, Kim N. Comparative genomics and selection analysis of Yeonsan Ogye black chicken with whole-genome sequencing. Genomics 2022; 114:110298. [PMID: 35134497 DOI: 10.1016/j.ygeno.2022.110298] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Revised: 12/24/2021] [Accepted: 02/01/2022] [Indexed: 11/30/2022]
Abstract
Yeonsan Ogye (OGYE; Gallus gallus domesticus) is a rare indigenous chicken breed that inhabits the Korean Peninsula. This breed has completely black coloring, including plumage, skin, eyes, beak, and internal organs. Despite these unique morphological characteristics, the population of OGYE has declined without in-depth research into their genome research. Therefore, this study aimed to compare the whole genome of OGYE to 12 other chicken populations, including ancestral breed, commercial breeds, Chinese indigenous breeds, and Korean native chickens. We focused on revealing the selection signature of OGYE, which has occurred through environmental pressures in the Korean Peninsula. Genome-wide selection analysis has identified local adaptation traits, such as egg development, that contribute to fetal viability and innate immune response to prevent viral and microbes infection in OGYE. In particular, SPP1 (Secreted Phosphoprotein 1), HSP90AA1 (Heat Shock Protein 90 Alpha Family Class A Member 1), and P2RX4 (Purinergic Receptor P2X 4) could have considerable involvement in egg development and RNASEL (Ribonuclease L), BRIP1 (BRCA1 Interacting Protein C-terminal Helicase 1), and TLR4 (Toll-Like Receptor 4) are crucial for the determination of the innate immune response. This study revealed the unique genetic diversity of OGYE at the genome-wide level. Furthermore, we emphasized the sustainable management of genetic resources and formulated breeding strategies for livestock on the Korean Peninsula.
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Affiliation(s)
- Youngbeom Cho
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea; Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
| | - Jae-Yoon Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea; Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea
| | - Namshin Kim
- Genome Editing Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon 34141, Republic of Korea; Department of Bioinformatics, KRIBB School of Bioscience, University of Science and Technology (UST), Daejeon 34141, Republic of Korea.
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13
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Lv FH, Cao YH, Liu GJ, Luo LY, Lu R, Liu MJ, Li WR, Zhou P, Wang XH, Shen M, Gao L, Yang JQ, Yang H, Yang YL, Liu CB, Wan PC, Zhang YS, Pi WH, Ren YL, Shen ZQ, Wang F, Wang YT, Li JQ, Salehian-Dehkordi H, Hehua E, Liu YG, Chen JF, Wang JK, Deng XM, Esmailizadeh A, Dehghani-Qanatqestani M, Charati H, Nosrati M, Štěpánek O, Rushdi HE, Olsaker I, Curik I, Gorkhali NA, Paiva SR, Caetano AR, Ciani E, Amills M, Weimann C, Erhardt G, Amane A, Mwacharo JM, Han JL, Hanotte O, Periasamy K, Johansson AM, Hallsson JH, Kantanen J, Coltman DW, Bruford MW, Lenstra JA, Li MH. Whole-genome resequencing of worldwide wild and domestic sheep elucidates genetic diversity, introgression and agronomically important loci. Mol Biol Evol 2021; 39:6459180. [PMID: 34893856 PMCID: PMC8826587 DOI: 10.1093/molbev/msab353] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Domestic sheep and their wild relatives harbor substantial genetic variants that can form the backbone of molecular breeding, but their genome landscapes remain understudied. Here, we present a comprehensive genome resource for wild ovine species, landraces and improved breeds of domestic sheep, comprising high-coverage (∼16.10×) whole genomes of 810 samples from 7 wild species and 158 diverse domestic populations. We detected, in total, ∼121.2 million single nucleotide polymorphisms, ∼61 million of which are novel. Some display significant (P < 0.001) differences in frequency between wild and domestic species, or are private to continent-wide or individual sheep populations. Retained or introgressed wild gene variants in domestic populations have contributed to local adaptation, such as the variation in the HBB associated with plateau adaptation. We identified novel and previously reported targets of selection on morphological and agronomic traits such as stature, horn, tail configuration, and wool fineness. We explored the genetic basis of wool fineness and unveiled a novel mutation (chr25: T7,068,586C) in the 3′-UTR of IRF2BP2 as plausible causal variant for fleece fiber diameter. We reconstructed prehistorical migrations from the Near Eastern domestication center to South-and-Southeast Asia and found two main waves of migrations across the Eurasian Steppe and the Iranian Plateau in the Early and Late Bronze Ages. Our findings refine our understanding of genome variation as shaped by continental migrations, introgression, adaptation, and selection of sheep.
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Affiliation(s)
- Feng-Hua Lv
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - 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
| | | | - Ling-Yun Luo
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ran Lu
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ming-Jun Liu
- Animal Biotechnological Research Center, Xinjiang Academy of Animal Science, Urumqi, China
| | - Wen-Rong Li
- Animal Biotechnological Research Center, Xinjiang Academy of Animal Science, Urumqi, China
| | - Ping Zhou
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Xin-Hua Wang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Min Shen
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Lei Gao
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Jing-Quan Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Hua Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Yong-Lin Yang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Chang-Bin Liu
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Peng-Cheng Wan
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Yun-Sheng Zhang
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Wen-Hui Pi
- Institute of Animal Husbandry and Veterinary Medicine, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
- State Key Laboratory of Sheep Genetic Improvement and Healthy Production, Xinjiang Academy of Agricultural and Reclamation Sciences, Shihezi, China
| | - Yan-Ling Ren
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, China
| | - Zhi-Qiang Shen
- Shandong Binzhou Academy of Animal Science and Veterinary Medicine, Binzhou, China
| | - Feng Wang
- Institute of Sheep and Goat Science, Nanjing Agricultural University, Nanjing, China
| | - Yu-Tao Wang
- College of Life and Geographic Sciences, Kashi University, Kashi, China
| | - Jin-Quan Li
- College of Animal Science, Inner Mongolia Agricultural University, Hohhot, China
| | - 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
| | - Eer Hehua
- Grass-Feeding Livestock Engineering Technology Research Center, Ningxia Academy of Agriculture and Forestry Sciences, Yinchuan, China
| | - Yong-Gang Liu
- College of Animal Science and Technology, Yunnan Agricultural University, Kunming, China
| | - Jian-Fei Chen
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Jian-Kui Wang
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Xue-Mei Deng
- College of Animal Science and Technology, China Agricultural University, Beijing, China
| | - Ali Esmailizadeh
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | | | - Hadi Charati
- Department of Animal Science, Faculty of Agriculture, Shahid Bahonar University of Kerman, Kerman, Iran
| | - Maryam Nosrati
- Department of Agriculture, Payame Noor University, Tehran, Iran
| | - Ondřej Štěpánek
- Department of Virology, State Veterinary Institute Jihlava, Jihlava, Czech Republic
| | - Hossam E Rushdi
- Department of Animal Production, Faculty of Agriculture, Cairo University, 12613 Giza, Egypt
| | - Ingrid Olsaker
- Department of Preclinical Sciences and Pathology, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Ås, Norway
| | - Ino Curik
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Zagreb, Croatia
| | - Neena A Gorkhali
- Animal Breeding Division, National Animal Science Institute, Nepal Agriculture Research Council (NARC), Kathmandu, Nepal
| | - Samuel R Paiva
- Embrapa Recursos Genéticos e Biotecnologia, Parque Estação Biológica, PqEB, Brasília, DF, Brazil
| | - Alexandre R Caetano
- Embrapa Recursos Genéticos e Biotecnologia, Parque Estação Biológica, PqEB, Brasília, DF, Brazil
| | - Elena Ciani
- Dipartimento di Bioscienze, Biotecnologie e Biofarmaceutica, Università degli Studi di Bari Aldo 24 Moro, Bari, Italy
| | - Marcel Amills
- Department of Animal Genetics, Center for Research in Agricultural Genomics (CRAG), CSIC-IRTA-UAB-UB, Campus de la Universitat Autònoma de Barcelona, Bellaterra, Spain
- Department of Animal Sciences, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - 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
| | - 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
- CTLGH and SRUC, The Roslin Institute Building, Easter Bush Campus, Edinburgh, Scotland
| | - 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, United Kingdom
| | - Kathiravan Periasamy
- Animal Production and Health Laboratory, Joint FAO/IAEA Division, International Atomic Energy Agency (IAEA), Vienna, Austria
| | - Anna M Johansson
- Department of Animal Breeding and Genetics, Faculty of Veterinary Medicine and Animal Science, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Jón H Hallsson
- Faculty of Natural Resources and Environmental Sciences, Agricultural University of Iceland, Borgarnes, Iceland
| | - Juha Kantanen
- Production Systems, Natural Resources Institute Finland (Luke), Jokioinen, Finland
| | - David W Coltman
- Department of Biological Sciences, University of Alberta, Edmonton, Alberta, Canada
| | - Michael W Bruford
- School of Biosciences, Cardiff University, Cathays Park, Cardiff, Wales, United Kingdom
- Sustainable Places Research Institute, Cardiff University, Wales, United Kingdom
| | - Johannes A Lenstra
- Faculty of Veterinary Medicine, Utrecht University, Utrecht, the Netherlands
| | - Meng-Hua Li
- College of Animal Science and Technology, China Agricultural University, Beijing, China
- Corresponding author: E-mail:
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14
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Zhao QB, López-Cortegano E, Oyelami FO, Zhang Z, Ma PP, Wang QS, Pan YC. Conservation Priorities Analysis of Chinese Indigenous Pig Breeds in the Taihu Lake Region. Front Genet 2021; 12:558873. [PMID: 33747032 PMCID: PMC7966724 DOI: 10.3389/fgene.2021.558873] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Accepted: 02/08/2021] [Indexed: 11/25/2022] Open
Abstract
Most indigenous pig resources are known to originate from China. Thus, establishing conservation priorities for these local breeds is very essential, especially in the case of limited conservation funds. Therefore, in this study, we analyzed 445 individuals belonging to six indigenous breeds from the Taihu Lake Region, using a total of 131,300 SNPs. In order to determine the long-term guidelines for the management of these breeds, we analyzed the level of diversity in the metapopulation following a partition of diversity within and between breed subpopulations, using both measures of genic and allelic diversity. From the study, we found that the middle Meishan (MMS) pig population contributes the most (22%) to the total gene diversity while the Jiaxing black (JX) pig population contributes the most (27%) to the gene diversity between subpopulations. Most importantly, when we consider one breed is removed from the meta-population, the first two breeds prioritized should be JX pig breed and Fengjing pig breed followed by small Meishan (SMS), Mizhu (MI), and Erhualian (EH) if we pay more attention to the gene diversity between subpopulations. However, if the priority focus is on the total gene diversity, then the first breed to be prioritized would be the Shawutou (SW) pig breed followed by JX, MI, EH, and Fengjing (FJ). Furthermore, we noted that if conservation priority is to be based on the allelic diversity between subpopulations, then the MI breed should be the most prioritized breed followed by SW, Erhuanlian, and MMS. Summarily, our data show that different breeds have different contributions to the gene and allelic diversity within subpopulations as well as between subpopulations. Our study provides a basis for setting conservation priorities for indigenous pig breeds with a focus on different priority criteria.
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Affiliation(s)
- Qing-Bo Zhao
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Eugenio López-Cortegano
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Favour Oluwapelumi Oyelami
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Zhe Zhang
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Pei-Pei Ma
- Department of Animal Science, School of Agriculture and Biology, Shanghai Jiao Tong University, Shanghai, China
| | - Qi-Shan Wang
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
| | - Yu-Chun Pan
- Department of Animal Breeding and Reproduction, College of Animal Science, Zhejiang University, Hangzhou, China
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15
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Chen Q, Huang Y, Wang Z, Teng S, Hanif Q, Lei C, Sun J. Whole-genome resequencing reveals diversity and selective signals in Longlin goat. Gene 2020; 771:145371. [PMID: 33346103 DOI: 10.1016/j.gene.2020.145371] [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: 08/20/2020] [Revised: 12/03/2020] [Accepted: 12/11/2020] [Indexed: 11/30/2022]
Abstract
The Longlin goat is one of the most valuable livestock species in Guangxi Autonomous Region of China, but its genomic diversity and selective signals are not clearly elucidated. Here we compared 20 genomes of Longlin goat to 66 genomes of other seven goat breeds worldwide to analyze patterns of Longlin goat genetic variation. We found the lowest linkage disequilibrium at the large distances between SNPs associated with the highest effective population size in the recent generations ago in Longlin goat. The eight goat breeds could be divided into Euro-African and East Asian goat population. Interestingly, like East Asian taurine, the same two migration phases might have occurred in the history of East Asian goat. More importantly, we identified selective signals implicated in immune resistance to disease, especially for skin disease, in Longlin goat. Our findings will not only help understand the evolutionary history and breed characteristic but can provide valuable resources for conservation of germplasm resources and implementation of crossbreeding programs.
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Affiliation(s)
- Qiuming Chen
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China
| | - Yingfei Huang
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China
| | - Zihao Wang
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China
| | - Shaohua Teng
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China
| | - Quratulain Hanif
- Computational Biology Laboratory, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad 577, Pakistan; Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad 45650, Pakistan
| | - Chuzhao Lei
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China
| | - Junli Sun
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China.
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16
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17
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Gao J, Lyu Y, Zhang D, Reddi KK, Sun F, Yi J, Liu C, Li H, Yao H, Dai J, Xu F. Genomic Characteristics and Selection Signatures in Indigenous Chongming White Goat ( Capra hircus). Front Genet 2020; 11:901. [PMID: 32973871 PMCID: PMC7472782 DOI: 10.3389/fgene.2020.00901] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2020] [Accepted: 07/21/2020] [Indexed: 12/23/2022] Open
Abstract
The Chongming white goat (CM) is an indigenous goat breed exhibits unique traits that are adapted to the local environment and artificial selection. By performing whole-genome re-sequencing, we generated 14-20× coverage sequences from 10 domestic goat breeds to explore the genomic characteristics and selection signatures of the CM breed. We identified a total of 23,508,551 single-nucleotide polymorphisms (SNPs) and 2,830,800 insertion-deletion mutations (indels) after read mapping and variant calling. We further specifically identified 1.2% SNPs (271,713) and 0.9% indels (24,843) unique to the CM breed in comparison with the other nine goat breeds. Missense (SIFT < 0.05), frameshift, splice-site, start-loss, stop-loss, and stop-gain variants were identified in 183 protein-coding genes of the CM breed. Of the 183, 36 genes, including AP4E1, FSHR, COL11A2, and DYSF, are involved in phenotype ontology terms related to the nervous system, short stature, and skeletal muscle morphology. Moreover, based on genome-wide F ST and pooled heterozygosity (Hp) calculation, we further identified selection signature genes between the CM and the other nine goat breeds. These genes are significantly associated with the nervous system (C2CD3, DNAJB13, UCP2, ZMYND11, CEP126, SCAPER, and TSHR), growth (UCP2, UCP3, TSHR, FGFR1, ERLIN2, and ZNF703), and coat color (KITLG, ASIP, AHCY, RALY, and MC1R). Our results suggest that the CM breed may be differentiated from other goat breeds in terms of nervous system owing to natural or artificial selection. The whole-genome analysis provides an improved understanding of genetic diversity and trait exploration for this indigenous goat breed.
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Affiliation(s)
- Jun Gao
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Yuhua Lyu
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Defu Zhang
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Kiran Kumar Reddi
- Department of Bioscience Research, College of Dentistry, University of Tennessee Health Science Center, Memphis, TN, United States
| | - Fengping Sun
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Jianzhong Yi
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Chengqian Liu
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Hong Li
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Huijuan Yao
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Jianjun Dai
- Institute of Animal Husbandry and Veterinary Science, Shanghai Academy of Agricultural Sciences, Shanghai, China
| | - Fuyi Xu
- Department of Genetics, Genomics, and Informatics, University of Tennessee Health Science Center, Memphis, TN, United States
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Chen Q, Wang Z, Sun J, Huang Y, Hanif Q, Liao Y, Lei C. Identification of Genomic Characteristics and Selective Signals in a Du'an Goat Flock. Animals (Basel) 2020; 10:E994. [PMID: 32517248 PMCID: PMC7341327 DOI: 10.3390/ani10060994] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2020] [Revised: 06/03/2020] [Accepted: 06/04/2020] [Indexed: 12/21/2022] Open
Abstract
The Du'an goat is one of the most important farm animals in the Guangxi Autonomous Region of China, but the genetic basis underlying its adaptive traits has still not been investigated. Firstly, in this study, the genomes of 15 Du'an goats from a breeding farm were sequenced (mean depth: 9.50X) to analyze the patterns of genetic variation. A comparable diversity (17.3 million single nucleotide polymorphisms and 2.1 million indels) was observed to be associated with a lower runs of homozygosity-based inbreeding coefficient and smaller effective population size in comparison with other breeds. From selective sweep and gene set enrichment analyses, we revealed selective signals related to adaptive traits, including immune resistance (serpin cluster, INFGR1, TLR2, and immune-related pathways), body size (HMGA2, LCOR, ESR1, and cancer-related pathways) and heat tolerance (MTOR, ABCG2, PDE10A, and purine metabolism pathway). Our findings uncovered the unique diversity at the genomic level and will provide the opportunities for improvement of productivity in the Du'an goat.
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Affiliation(s)
- Qiuming Chen
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; (Q.C.); (Z.W.); (J.S.); (Y.H.)
- Key Laboratory of Animal Genetics, Breeding and Reproduction of Shaanxi Province, College of Animal Science and Technology, Northwest A&F University, Yangling 712100, China;
| | - Zihao Wang
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; (Q.C.); (Z.W.); (J.S.); (Y.H.)
| | - Junli Sun
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; (Q.C.); (Z.W.); (J.S.); (Y.H.)
| | - Yingfei Huang
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; (Q.C.); (Z.W.); (J.S.); (Y.H.)
| | - Quratulain Hanif
- Computational Biology Laboratory, Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering, Faisalabad 577, Pakistan;
- Department of Biotechnology, Pakistan Institute of Engineering and Applied Sciences, Nilore, Islamabad 45650, Pakistan
| | - Yuying Liao
- Guangxi Key Laboratory of Livestock Genetic Improvement, Animal Husbandry Research Institute of Guangxi Zhuang Autonomous Region, Nanning 530001, China; (Q.C.); (Z.W.); (J.S.); (Y.H.)
| | - Chuzhao Lei
- 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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