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Zhao CH, Wang D, Yang C, Chen Y, Teng J, Zhang XY, Cao Z, Wei XM, Ning C, Yang QE, Lv WF, Zhang Q. Population structure and breed identification of Chinese indigenous sheep breeds using whole genome SNPs and InDels. Genet Sel Evol 2024; 56:60. [PMID: 39227836 PMCID: PMC11370120 DOI: 10.1186/s12711-024-00927-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 08/23/2024] [Indexed: 09/05/2024] Open
Abstract
BACKGROUND Accurate breed identification is essential for the conservation and sustainable use of indigenous farm animal genetic resources. In this study, we evaluated the phylogenetic relationships and genomic breed compositions of 13 sheep breeds using SNP and InDel data from whole genome sequencing. The breeds included 11 Chinese indigenous and 2 foreign commercial breeds. We compared different strategies for breed identification with respect to different marker types, i.e. SNPs, InDels, and a combination of SNPs and InDels (named SIs), different breed-informative marker detection methods, and different machine learning classification methods. RESULTS Using WGS-based SNPs and InDels, we revealed the phylogenetic relationships between 11 Chinese indigenous and two foreign sheep breeds and quantified their purities through estimated genomic breed compositions. We found that the optimal strategy for identifying these breeds was the combination of DFI_union for breed-informative marker detection, which integrated the methods of Delta, Pairwise Wright's FST, and Informativeness for Assignment (namely DFI) by merging the breed-informative markers derived from the three methods, and KSR for breed assignment, which integrated the methods of K-Nearest Neighbor, Support Vector Machine, and Random Forest (namely KSR) by intersecting their results. Using SI markers improved the identification accuracy compared to using SNPs or InDels alone. We achieved accuracies over 97.5% when using at least the 1000 most breed-informative (MBI) SI markers and even 100% when using 5000 SI markers. CONCLUSIONS Our results provide not only an important foundation for conservation of these Chinese local sheep breeds, but also general approaches for breed identification of indigenous farm animal breeds.
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Affiliation(s)
- Chang-Heng Zhao
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Dan Wang
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Cheng Yang
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Yan Chen
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Jun Teng
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Xin-Yi Zhang
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Zhi Cao
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Xian-Ming Wei
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Chao Ning
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China
| | - Qi-En Yang
- CAS Key Laboratory of Adaptation and Evolution of Plateau Biota, Qinghai Key Laboratory of Animal Ecological Genomics, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, 810001, Qinghai, China.
| | - Wen-Fa Lv
- Key Lab of Animal Production, Product Quality and Security, Ministry of Education, Jilin Agricultural University, Changchun, 130118, China.
| | - Qin Zhang
- Shandong Provincial Key Laboratory for Livestock Germplasm Innovation & Utilization, College of Animal Science, Shandong Agricultural University, Tai'an, 271018, China.
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Yougbaré B, Ouédraogo D, Tapsoba ASR, Soudré A, Zoma BL, Orozco-terWengel P, Moumouni S, Ouédraogo-Koné S, Wurzinger M, Tamboura HH, Traoré A, Mwai OA, Sölkner J, Khayatzadeh N, Mészáros G, Burger PA. Local Ancestry to Identify Selection in Response to Trypanosome Infection in Baoulé x Zebu Crossbred Cattle in Burkina Faso. Front Genet 2021; 12:670390. [PMID: 34646296 PMCID: PMC8504455 DOI: 10.3389/fgene.2021.670390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 08/09/2021] [Indexed: 11/15/2022] Open
Abstract
The genomes of crossbred (admixed) individuals are a mosaic of ancestral haplotypes formed by recombination in each generation. The proportion of these ancestral haplotypes in certain genomic regions can be responsible for either susceptibility or tolerance against pathogens, and for performances in production traits. Using a medium-density genomic marker panel from the Illumina Bovine SNP50 BeadChip, we estimated individual admixture proportions for Baoulé x Zebu crossbred cattle in Burkina Faso, which were tested for trypanosome infection by direct ELISA from blood samples. Furthermore, we calculated local ancestry deviation from average for each SNP across 29 autosomes to identify potential regions under selection in the trypanotolerant Baoulé cattle and their crossbreds. We identified significant deviation from the local average ancestry (above 5 and 10% genome-wide thresholds) on chromosomes 8 and 19 in the positive animals, while the negative ones showed higher deviation on chromosomes 6, 19, 21, and 22. Some candidate genes on chromosome 6 (PDGFRA) and chromosome 19 (CDC6) have been found associated to trypanotolerance in West African taurines. Screening for FST outliers in trypanosome positive/negative animals we detected seven variants putatively under selection. Finally, we identified a minimum set of highly ancestry informative markers for routine admixture testing. The results of this study contribute to a better understanding of the genetic basis of trypanotolerance in Baoulé cattle and their crossbreeds. Furthermore, we provide a small informative marker set to monitor admixture in this valuable indigenous breed. As such, our results are important for conserving the genetic uniqueness and trypanotolerance of Baoulé cattle, as well as for the improvement of Baoulé and Zebu crossbreds in specific community-based breeding programs.
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Affiliation(s)
- Bernadette Yougbaré
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Dominique Ouédraogo
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Arnaud S R Tapsoba
- Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | - Albert Soudré
- Unité de Formation et de Recherche en Sciences et Technologies, Université Norbert Zongo, Koudougou, Burkina Faso
| | - Bienvenue L Zoma
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,Institut du Développement Rural, Université Nazi Boni, Bobo-Dioulasso, Burkina Faso
| | | | - Sanou Moumouni
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | | | - Maria Wurzinger
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Hamidou H Tamboura
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Amadou Traoré
- Institut de l'Environnement et de Recherches Agricoles (INERA), Ouagadougou, Burkina Faso
| | - Okeyo Ally Mwai
- International Livestock Research Institute (ILRI), Nairobi, Kenya
| | - Johann Sölkner
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Negar Khayatzadeh
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria.,SUISAG, Sempach, Switzerland
| | - Gábor Mészáros
- Department of Sustainable Agricultural Systems, University of Natural Resources and Life Sciences Vienna (BOKU), Vienna, Austria
| | - Pamela A Burger
- Research Institute of Wildlife Ecology, Vetmeduni Vienna, Savoyenstraße 1, Vienna, Austria
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3
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Yang HC, Chen CW, Lin YT, Chu SK. Genetic ancestry plays a central role in population pharmacogenomics. Commun Biol 2021; 4:171. [PMID: 33547344 PMCID: PMC7864978 DOI: 10.1038/s42003-021-01681-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Accepted: 01/06/2021] [Indexed: 12/12/2022] Open
Abstract
Recent studies have pointed out the essential role of genetic ancestry in population pharmacogenetics. In this study, we analyzed the whole-genome sequencing data from The 1000 Genomes Project (Phase 3) and the pharmacogenetic information from Drug Bank, PharmGKB, PharmaADME, and Biotransformation. Here we show that ancestry-informative markers are enriched in pharmacogenetic loci, suggesting that trans-ancestry differentiation must be carefully considered in population pharmacogenetics studies. Ancestry-informative pharmacogenetic loci are located in both protein-coding and non-protein-coding regions, illustrating that a whole-genome analysis is necessary for an unbiased examination over pharmacogenetic loci. Finally, those ancestry-informative pharmacogenetic loci that target multiple drugs are often a functional variant, which reflects their importance in biological functions and pathways. In summary, we develop an efficient algorithm for an ultrahigh-dimensional principal component analysis. We create genetic catalogs of ancestry-informative markers and genes. We explore pharmacogenetic patterns and establish a high-accuracy prediction panel of genetic ancestry. Moreover, we construct a genetic ancestry pharmacogenomic database Genetic Ancestry PhD (http://hcyang.stat.sinica.edu.tw/databases/genetic_ancestry_phd/). Hsin-Chou Yang et al. examine population structure in several genomic databases and identify that pharmacogenetic loci are enriched for markers of genetic ancestry. Their results suggest that genetic ancestry must be carefully considered in population pharmacogenetics studies.
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Affiliation(s)
- Hsin-Chou Yang
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan. .,Institute of Statistics, National Cheng Kung University, Tainan, Taiwan. .,Institute of Public Health, National Yang-Ming University, Taipei, Taiwan.
| | - Chia-Wei Chen
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Yu-Ting Lin
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
| | - Shih-Kai Chu
- Institute of Statistical Science, Academia Sinica, Taipei, Taiwan
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4
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Davenport KM, Hiemke C, McKay SD, Thorne JW, Lewis RM, Taylor T, Murdoch BM. Genetic structure and admixture in sheep from terminal breeds in the United States. Anim Genet 2020; 51:284-291. [PMID: 31970815 PMCID: PMC7065203 DOI: 10.1111/age.12905] [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] [Accepted: 12/12/2019] [Indexed: 11/29/2022]
Abstract
Selection for performance in diverse production settings has resulted in variation across sheep breeds worldwide. Although sheep are an important species to the United States, the current genetic relationship among many terminal sire breeds is not well characterized. Suffolk, Hampshire, Shropshire and Oxford (terminal) and Rambouillet (dual purpose) sheep (n = 248) sampled from different flocks were genotyped using the Applied Biosystems Axiom Ovine Genotyping Array (50K), and additional Shropshire sheep (n = 26) using the Illumina Ovine SNP50 BeadChip. Relationships were investigated by calculating observed heterozygosity, inbreeding coefficients, eigenvalues, pairwise Wright’s FST estimates and an identity by state matrix. The mean observed heterozygosity for each breed ranged from 0.30 to 0.35 and was consistent with data reported in other US and Australian sheep. Suffolk from two different regions of the United States (Midwest and West) clustered separately in eigenvalue plots and the rectangular cladogram. Further, divergence was detected between Suffolk from different regions with Wright’s FST estimate. Shropshire animals showed the greatest divergence from other terminal breeds in this study. Admixture between breeds was examined using admixture, and based on cross‐validation estimates, the best fit number of populations (clusters) was K = 6. The greatest admixture was observed within Hampshire, Suffolk, and Shropshire breeds. When plotting eigenvalues, US terminal breeds clustered separately in comparison with sheep from other locations of the world. Understanding the genetic relationships between terminal sire breeds in sheep will inform us about the potential applicability of markers derived in one breed to other breeds based on relatedness.
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Affiliation(s)
- K M Davenport
- Department of Animal and Veterinary Science, University of Idaho, Moscow, ID, 83844, USA
| | - C Hiemke
- Niman Ranch and Mapleton Mynd Shropshires, Stoughton, MA, 53589, USA
| | - S D McKay
- Department of Animal and Veterinary Sciences, University of Vermont, Burlington, VT, 05405, USA
| | - J W Thorne
- Department of Animal and Veterinary Science, University of Idaho, Moscow, ID, 83844, USA.,Texas A&M AgriLife Extension, San Angelo, TX, 76901, USA
| | - R M Lewis
- Department of Animal Science, University of Nebraska-Lincoln, Lincoln, NE, 68583, USA
| | - T Taylor
- Department of Animal Science, Arlington Research Station, University of Wisconsin-Madison, Arlington, WI, 53911, USA
| | - B M Murdoch
- Department of Animal and Veterinary Science, University of Idaho, Moscow, ID, 83844, USA
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5
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Chhotaray S, Panigrahi M, Pal D, Ahmad SF, Bhushan B, Gaur GK, Mishra BP, Singh RK. Ancestry informative markers derived from discriminant analysis of principal components provide important insights into the composition of crossbred cattle. Genomics 2019; 112:1726-1733. [PMID: 31678154 DOI: 10.1016/j.ygeno.2019.10.008] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Revised: 07/06/2019] [Accepted: 10/01/2019] [Indexed: 12/19/2022]
Abstract
The cost of SNP genotyping to screen different breeds and to estimate the exact proportion of ancestry level is quite high, which can be compensated through deriving a small panel of ancestry informative markers (AIMs). Hence, we carried out the present study to provide an insight into ancestry level inferred from a panel of informative markers in the crossbred Vrindavani population developed at ICAR-IVRI, India. We have performed a new method i.e., discriminant analysis of principal components (DAPC) for the first time on the dataset of Vrindavani cattle. To confirm our method, we had performed DAPC on two other well-known crossbred cattle, i.e., Frieswal and Beefmaster. Three sets of panels (500, 1000 and 2000 markers) were tested for clustering of individuals. Among all the panels, we found the panel (1000 markers) with DAPC based contribution method was of the smallest size and comparatively of the highest accuracy.
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Affiliation(s)
- Supriya Chhotaray
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Manjit Panigrahi
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India.
| | - Dhan Pal
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Sheikh Firdous Ahmad
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - Bharat Bhushan
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - G K Gaur
- Division of Animal Genetics, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - B P Mishra
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
| | - R K Singh
- Division of Veterinary Biotechnology, ICAR-Indian Veterinary Research Institute, Izatnagar, Bareilly 243122, UP, India
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6
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Marshall K, Gibson JP, Mwai O, Mwacharo JM, Haile A, Getachew T, Mrode R, Kemp SJ. Livestock Genomics for Developing Countries – African Examples in Practice. Front Genet 2019. [DOI: 10.10.3389/fgene.2019.00297] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
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7
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Marshall K, Gibson JP, Mwai O, Mwacharo JM, Haile A, Getachew T, Mrode R, Kemp SJ. Livestock Genomics for Developing Countries - African Examples in Practice. Front Genet 2019; 10:297. [PMID: 31105735 PMCID: PMC6491883 DOI: 10.3389/fgene.2019.00297] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2018] [Accepted: 03/19/2019] [Indexed: 01/17/2023] Open
Abstract
African livestock breeds are numerous and diverse, and typically well adapted to the harsh environment conditions under which they perform. They have been used over centuries to provide livelihoods as well as food and nutritional security. However, African livestock systems are dynamic, with many small- and medium-scale systems transforming, to varying degrees, to become more profitable. In these systems the women and men livestock keepers are often seeking new livestock breeds or genotypes - typically those that increase household income through having enhanced productivity in comparison to traditional breeds while maintaining adaptedness. In recent years genomic approaches have started to be utilized in the identification and development of such breeds, and in this article we describe a number of examples to this end from sub-Saharan Africa. These comprise case studies on: (a) dairy cattle in Kenya and Senegal, as well as sheep in Ethiopia, where genomic approaches aided the identification of the most appropriate breed-type for the local productions systems; (b) a cross-breeding program for dairy cattle in East Africa incorporating genomic selection as well as other applications of genomics; (c) ongoing work toward creating a new cattle breed for East Africa that is both productive and resistant to trypanosomiasis; and (d) the use of African cattle as resource populations to identify genomic variants of economic or ecological significance, including a specific case where the discovery data was from a community based breeding program for small ruminants in Ethiopia. Lessons learnt from the various case studies are highlighted, and the concluding section of the paper gives recommendations for African livestock systems to increasingly capitalize on genomic technologies.
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Affiliation(s)
- Karen Marshall
- Livestock Genetics Program, International Livestock Research Institute, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, Nairobi, Kenya
| | - John P. Gibson
- School of Environmental and Rural Science, University of New England, Armidale, NSW, Australia
| | - Okeyo Mwai
- Livestock Genetics Program, International Livestock Research Institute, Nairobi, Kenya
| | - Joram M. Mwacharo
- Small Ruminant Breeding and Genomics Group, International Center for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Aynalem Haile
- Small Ruminant Breeding and Genomics Group, International Center for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Tesfaye Getachew
- Small Ruminant Breeding and Genomics Group, International Center for Agricultural Research in the Dry Areas, Addis Ababa, Ethiopia
| | - Raphael Mrode
- Livestock Genetics Program, International Livestock Research Institute, Nairobi, Kenya
- Scotland’s Rural College, Edinburgh, United Kingdom
| | - Stephen J. Kemp
- Livestock Genetics Program, International Livestock Research Institute, Nairobi, Kenya
- Centre for Tropical Livestock Genetics and Health, Nairobi, Kenya
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8
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Liang Z, Bu L, Qin Y, Peng Y, Yang R, Zhao Y. Selection of Optimal Ancestry Informative Markers for Classification and Ancestry Proportion Estimation in Pigs. Front Genet 2019; 10:183. [PMID: 30915106 PMCID: PMC6421339 DOI: 10.3389/fgene.2019.00183] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 02/19/2019] [Indexed: 12/26/2022] Open
Abstract
Using small sets of ancestry informative markers (AIMs) constitutes a cost-effective method to accurately estimate the ancestry proportions of individuals. This study aimed to generate a small and effective number of AIMs from ∼60 K single nucleotide polymorphism (SNP) data of porcine and estimate three ancestry proportions [East China pig (ECHP), South China pig (SCHP), and European commercial pig (EUCP)] from Asian breeds and European domestic breeds. A total of 186 samples of 10 pure breeds were divided into three groups: ECHP, SCHP, and EUCP. Using these samples and a one-vs.-rest SVM classifier, we found that using only seven AIMs could completely separate the three groups. Subsequently, we utilized supervised ADMIXTURE to calculate ancestry proportions and found that the 129 AIMs performed well on ancestry estimates when pseudo admixed individuals were used. Furthermore, another 969 samples of 61 populations were applied to evaluate the performance of the 129 AIMs. We also observed that the 129 AIMs were highly correlated with estimates using ∼60 K SNP data for three ancestry components: ECHP (Pearson correlation coefficient (r) = 0.94), SCHP (r = 0.94), and EUCP (r = 0.99). Our results provided an example of using a small number of pig AIMs for classifications and estimating ancestry proportions with high accuracy and in a cost-effective manner.
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Affiliation(s)
- Zuoxiang Liang
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China.,State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Lina Bu
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China.,State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yidi Qin
- State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yebo Peng
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China.,State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Ruifei Yang
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China.,State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
| | - Yiqiang Zhao
- Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing, China.,State Key Laboratory of Agrobiotechnology, College of Biological Sciences, China Agricultural University, Beijing, China
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