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Sarviaho K, Uimari P, Martikainen K. Signatures of positive selection after the introduction of genomic selection in the Finnish Ayrshire population. J Dairy Sci 2024:S0022-0302(24)00548-4. [PMID: 38490540 DOI: 10.3168/jds.2024-24105] [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: 08/21/2023] [Accepted: 02/15/2024] [Indexed: 03/17/2024]
Abstract
The Finnish Ayrshire (FAY) belongs to the Nordic Red breeds and is characterized by high milk yield, high milk components, good fertility, and functional conformation. The FAY breeding program is based on genomic selection. Despite the benefits of selection on breeding values, autozygosity in the genome may increase due to selection, and increased autozygosity may cause inbreeding depression in selected traits. However, there is lack of studies concerning selection signatures in the FAY after genomic selection introduction. The aim of this study was to identify signatures of selection in FAY after the introduction of genomic selection. Genomic data included 45,834 SNPs. The genotyped animals were divided into 2 groups: animals born before genomic selection introduction (6,108 cows) and animals born after genomic selection introduction (47,361 cows). We identified the selection signatures using 3 complementary methods: 2 based on identification of selection signatures from runs of homozygosity (ROH) islands and one based on the decay of site-specific extended haplotype between populations at SNP sites (Rsb). In total, we identified 34 ROH islands on chromosomes 1, 3, 6, 8, 12-15, 17, 19, 22, and 26 in FAY animals born before genomic selection (between 1980 and 2011) and 30 ROH islands on chromosomes 1-3, 13-17, 22, and 25-26 in FAY animals born after genomic selection introduction (between 2015 and 2020). We additionally detected 22 ΔROH islands on chromosomes 2-3, 11, 13, 14, 16, 18, 20, and 25-26. Finally, a total of 31 Rsb regions on chromosomes 2, 3, 14, 18, 20, and 25 were identified. Based on the results, genomic selection has favored certain alleles and haplotypes on genomic regions related to traits relevant in the FAY breeding program: milk production, fertility, growth, beef production traits, and feed efficiency. Several genes related to these traits, e.g., PLA2G4A, MECR, CHUK, COX15, RICTOR, SHISA9, and SEMA4G overlapped or partially overlapped the observed selection signature regions. The association of genotypes within these regions and their effects on traits relevant in the FAY breeding program should be studied and genetic regions undergoing selection monitored in the FAY population.
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Affiliation(s)
- Katri Sarviaho
- Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland.
| | - Pekka Uimari
- Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland
| | - Katja Martikainen
- Department of Agricultural Sciences, University of Helsinki, Helsinki, Finland
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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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Bordonaro S, Chessari G, Mastrangelo S, Senczuk G, Chessa S, Castiglioni B, Tumino S, Marletta D, Criscione A. Genome-wide population structure, homozygosity, and heterozygosity patterns of Nero Siciliano pig in the framework of Italian and cosmopolitan breeds. Anim Genet 2023; 54:591-605. [PMID: 37381662 DOI: 10.1111/age.13344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 06/13/2023] [Accepted: 06/15/2023] [Indexed: 06/30/2023]
Abstract
Analysis of genomic data is becoming more and more common for the effective management of livestock breeding programmes, even in the case of local populations. In this work, the genome-wide data of Nero Siciliano pig breed were compared to that of wild boar, Italian local and cosmopolitan breeds to investigate its genetic structure, and runs of homozygosity (ROH) and heterozygosity patterns. The Nero Siciliano has been reported to have the highest rate of genetic diversity among the Italian breeds, and a genetic variability comparable to that of the cosmopolitan breeds. Analyses of genomic structure and relationships underlined its proximity to wild boar, and an internal substructure probably linked to different family lines. The breed showed a low value of inbreeding estimated from ROH, and the highest diversity index among the Italian breeds, even if lower than that of the cosmopolitans. Four ROH islands in three chromosomes (SSC8, SSC11, and SSC14) and one heterozygosity-rich region (SSC1) were identified in Nero Siciliano, highlighting genomic regions related to productive QTL. Across breeds, SSC8 and SSC14 were the chromosomes with most ROH islands, with Mora Romagnola and wild boar showing the highest level of autozygosity. Chromosomes SSC2, SSC6, SSC8 and SSC13 showed the majority of runs of heterozygosity regions, mainly found in the cosmopolitan pig breeds, which reported several genes associated with health-related QTL. The outlined results can help to better identify the genomic profile of this local breed in order to plan matings, maintain adequate internal diversity and exploit the production system.
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Affiliation(s)
- Salvatore Bordonaro
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Catania, Italy
| | - Giorgio Chessari
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Catania, Italy
| | - Salvatore Mastrangelo
- Dipartimento Scienze Agrarie, Alimentari e Forestali, Università di Palermo, Palermo, Italy
| | - Gabriele Senczuk
- Dipartimento di Agricoltura, Ambiente e Alimenti, Università del Molise, Campobasso, Italy
| | - Stefania Chessa
- Dipartimento di Scienze Veterinarie, Università di Torino, Torino, Italy
| | - Bianca Castiglioni
- Istituto di Biologia e Biotecnologia Agraria, National Research Council, Lodi, Italy
| | - Serena Tumino
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Catania, Italy
| | - Donata Marletta
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Catania, Italy
| | - Andrea Criscione
- Dipartimento di Agricoltura, Alimentazione e Ambiente, Università di Catania, Catania, Italy
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Niehoff T, Pook T, Gholami M, Beissinger T. Imputation of low-density marker chip data in plant breeding: Evaluation of methods based on sugar beet. THE PLANT GENOME 2022; 15:e20257. [PMID: 36258672 DOI: 10.1002/tpg2.20257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 08/02/2022] [Indexed: 06/16/2023]
Abstract
Low-density genotyping followed by imputation reduces genotyping costs while still providing high-density marker information. An increased marker density has the potential to improve the outcome of all applications that are based on genomic data. This study investigates techniques for 1k to 20k genomic marker imputation for plant breeding programs with sugar beet (Beta vulgaris L. ssp. vulgaris) as an example crop, where these are realistic marker numbers for modern breeding applications. The generally accepted 'gold standard' for imputation, Beagle 5.1, was compared with the recently developed software AlphaPlantImpute2 which is designed specifically for plant breeding. For Beagle 5.1 and AlphaPlantImpute2, the imputation strategy as well as the imputation parameters were optimized in this study. We found that the imputation accuracy of Beagle could be tremendously improved (0.22 to 0.67) by tuning parameters, mainly by lowering the values for the parameter for the effective population size and increasing the number of iterations performed. Separating the phasing and imputation steps also improved accuracies when optimized parameters were used (0.67 to 0.82). We also found that the imputation accuracy of Beagle decreased when more low-density lines were included for imputation. AlphaPlantImpute2 produced very high accuracies without optimization (0.89) and was generally less responsive to optimization. Overall, AlphaPlantImpute2 performed relatively better for imputation whereas Beagle was better for phasing. Combining both tools yielded the highest accuracies.
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Affiliation(s)
- Tobias Niehoff
- Animal Breeding and Genomics, Wageningen Univ. & Research, Postbox 338, 6700AH, Wageningen, The Netherlands
- Dep. of Crop Sciences, Division of Plant Breeding Methodology, Univ. of Göttingen, Göttingen, 37075, Germany
| | - Torsten Pook
- Animal Breeding and Genomics, Wageningen Univ. & Research, Postbox 338, 6700AH, Wageningen, The Netherlands
- Dep. of Animal Sciences, Animal Breeding and Genetics Group, Univ. of Göttingen, Göttingen, 37075, Germany
- Center for Integrated Breeding Research, Univ. of Göttingen, Göttingen, 37075, Germany
| | - Mahmood Gholami
- RD-SBCE-BTA, KWS SAAT SE & Co. KGaA, Grimsehlstr. 31, Einbeck, 37574, Germany
| | - Timothy Beissinger
- Dep. of Crop Sciences, Division of Plant Breeding Methodology, Univ. of Göttingen, Göttingen, 37075, Germany
- Center for Integrated Breeding Research, Univ. of Göttingen, Göttingen, 37075, Germany
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Ballan M, Schiavo G, Bovo S, Schiavitto M, Negrini R, Frabetti A, Fornasini D, Fontanesi L. Comparative analysis of genomic inbreeding parameters and runs of homozygosity islands in several fancy and meat rabbit breeds. Anim Genet 2022; 53:849-862. [PMID: 36073189 PMCID: PMC9826494 DOI: 10.1111/age.13264] [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: 01/24/2022] [Revised: 07/01/2022] [Accepted: 08/25/2022] [Indexed: 01/11/2023]
Abstract
Runs of homozygosity (ROH) are defined as long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROH and their length are indicators of the level and origin of inbreeding. In this study, we analysed SNP chip datasets (obtained using the Axiom OrcunSNP Array) of a total of 702 rabbits from 12 fancy breeds and four meat breeds to identify ROH with different approaches and calculate several genomic inbreeding parameters. The highest average number of ROH per animal was detected in Belgian Hare (~150) and the lowest in Italian Silver (~106). The average length of ROH ranged from 4.001 ± 0.556 Mb in Italian White to 6.268 ± 1.355 Mb in Ermine. The same two breeds had the lowest (427.9 ± 86.4 Mb, Italian White) and the highest (921.3 ± 179.8 Mb, Ermine) average values of the sum of all ROH segments. More fancy breeds had a higher level of genomic inbreeding (as defined by ROH) than meat breeds. Several ROH islands contain genes involved in body size, body length, pigmentation processes, carcass traits, growth, and reproduction traits (e.g.: AOX1, GPX5, IFRD1, ITGB8, NELL1, NR3C1, OCA2, TRIB1, TRIB2). Genomic inbreeding parameters can be useful to overcome the lack of information in the management of rabbit genetic resources. ROH provided information to understand, to some extent, the genetic history of rabbit breeds and to identify signatures of selection in the rabbit genome.
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Affiliation(s)
- Mohamad Ballan
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Giuseppina Schiavo
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Samuele Bovo
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
| | - Michele Schiavitto
- Associazione Nazionale Coniglicoltori Italiani (ANCI), Contrada Giancola SncVolturara AppulaItaly
| | | | | | | | - Luca Fontanesi
- Division of Animal Sciences, Department of Agricultural and Food SciencesUniversity of BolognaBolognaItaly
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6
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Wang H, Wang Q, Tan X, Wang J, Zhang J, Zheng M, Zhao G, Wen J. Estimation of genetic variability and identification of regions under selection based on runs of homozygosity in Beijing-You Chickens. Poult Sci 2022; 102:102342. [PMID: 36470032 PMCID: PMC9719870 DOI: 10.1016/j.psj.2022.102342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 11/08/2022] [Accepted: 11/09/2022] [Indexed: 11/16/2022] Open
Abstract
The genetic composition of populations is the result of a long-term process of selection and adaptation to specific environments and ecosystems. Runs of homozygosity (ROHs) are homozygous segments of the genome where the 2 haplotypes inherited from the parents are identical. The detection of ROH can be used to describe the genetic variability and quantify the level of inbreeding in an individual. Here, we investigated the occurrence and distribution of ROHs in 40 Beijing-You Chickens from the random breeding population (BJY_C) and 40 Beijing-You Chickens from the intramuscular fat (IMF) selection population (BJY_S). Principal component analysis (PCA) and maximum likelihood (ML) analyses showed that BJY_C was completely separated from the BJY_S. The nucleotide diversity of BJY_C was higher than that of BJY_S, and the decay rate of LD of BJY_C was faster. The ROHs were identified for a total of 7,101 in BJY_C and 9,273 in BJY_S, respectively. The ROH-based inbreeding estimate (FROH) of BJY_C was 0.079, which was significantly lower than that of BJY_S (FROH = 0.114). The results were the same as the estimates of the inbreeding coefficients calculated based on homozygosity (FHOM), the correlation between uniting gametes (FUNI), and the genomic relationship matrix (FGRM). Additionally, the distribution and number of ROH islands in chromosomes of BJY_C and BJY_S were significantly different. The ROH islands of BJY_S that included genes associated with lipid metabolism and fat deposition, such as CIDEA and S1PR1, were absent in BJY_C. However, GPR161 was detected in both populations, which is a candidate gene for the formation of the unique five-finger trait in Beijing-You chickens. Our findings contributed to the understanding of the genetic diversity of random or artificially selected populations, and allowed the accurate monitoring of population inbreeding using genomic information, as well as the detection of genomic regions that affect traits under selection.
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Affiliation(s)
- Hailong Wang
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Qiao Wang
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Xiaodong Tan
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Jie Wang
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Jin Zhang
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Maiqing Zheng
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Guiping Zhao
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China
| | - Jie Wen
- Chinese Academy of Agricultural Science, State Key Laboratory of Animal Nutrition, Beijing 100193, China.
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Addo S, Jung L. An insight into the runs of homozygosity distribution and breed differentiation in Mangalitsa pigs. Front Genet 2022; 13:909986. [DOI: 10.3389/fgene.2022.909986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 09/30/2022] [Indexed: 11/13/2022] Open
Abstract
Mangalitsa pigs exhibit three distinct coat color patterns based on which they are described as Red, Blond, and Swallow-bellied. The current study investigated genome-wide diversity and selection signatures in the three breeds using fixation index, runs of homozygosity and population structure analyses. The analyses were originally based on quality-controlled data on 77 Mangalitsa animals from Germany, including 23 Blond, 30 Swallow-bellied and 24 Red Mangalitsa genotyped with a customized version of the ProcineSNP60 v2 Genotyping Bead Chip. Also, 20 Hungarian Mangalitsa genotypes were included as outgroup data for comparison. Estimates of observed heterozygosity were 0.27, 0.28, and 0.29, and inbreeding coefficients estimated based on runs of homozygosity were 24.11%, 20.82%, and 16.34% for Blond, Swallow-bellied and Red Mangalitsa, respectively. ROH islands were detected in all breeds, however, none of these were shared amongst them. The KIF16B gene previously reported to play a role in synaptic signaling was found in a ROH island (SSC17: 16–26) in Swallow-bellied Mangalitsa. The same gene was found to harbor a significantly differentiated SNP (MARC0032380) while contrasting either Blond or Red to Swallow-belied Mangalitsa. In the Red Mangalitsa, some ROH islands were associated with genes that play a role in meat quality traits, i.e., ABCA12, VIL1, PLSCR5, and USP37. Our population structure analysis highlighted a separation of the three breeds, but also showed the closest relatedness between Red and Blond Mangalitsa pigs. Findings of this study improve our understanding of the diversity in the three breeds of Mangalitsa pigs.
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Blaj I, Tetens J, Bennewitz J, Thaller G, Falker-Gieske C. Structural variants and tandem repeats in the founder individuals of four F 2 pig crosses and implications to F 2 GWAS results. BMC Genomics 2022; 23:631. [PMID: 36057580 PMCID: PMC9440560 DOI: 10.1186/s12864-022-08716-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 06/23/2022] [Indexed: 12/03/2022] Open
Abstract
BACKGROUND Structural variants and tandem repeats are relevant sources of genomic variation that are not routinely analyzed in genome wide association studies mainly due to challenging identification and genotyping. Here, we profiled these variants via state-of-the-art strategies in the founder animals of four F2 pig crosses using whole-genome sequence data (20x coverage). The variants were compared at a founder level with the commonly screened SNPs and small indels. At the F2 level, we carried out an association study using imputed structural variants and tandem repeats with four growth and carcass traits followed by a comparison with a previously conducted SNPs and small indels based association study. RESULTS A total of 13,201 high confidence structural variants and 103,730 polymorphic tandem repeats (with a repeat length of 2-20 bp) were profiled in the founders. We observed a moderate to high (r from 0.48 to 0.57) level of co-localization between SNPs or small indels and structural variants or tandem repeats. In the association step 56.56% of the significant variants were not in high LD with significantly associated SNPs and small indels identified for the same traits in the earlier study and thus presumably not tagged in case of a standard association study. For the four growth and carcass traits investigated, many of the already proposed candidate genes in our previous studies were confirmed and additional ones were identified. Interestingly, a common pattern on how structural variants or tandem repeats regulate the phenotypic traits emerged. Many of the significant variants were embedded or nearby long non-coding RNAs drawing attention to their functional importance. Through which specific mechanisms the identified long non-coding RNAs and their associated structural variants or tandem repeats contribute to quantitative trait variation will need further investigation. CONCLUSIONS The current study provides insights into the characteristics of structural variants and tandem repeats and their role in association studies. A systematic incorporation of these variants into genome wide association studies is advised. While not of immediate interest for genomic prediction purposes, this will be particularly beneficial for elucidating biological mechanisms driving the complex trait variation.
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Affiliation(s)
- Iulia Blaj
- Institute of Animal Breeding and Husbandry, Kiel University, Kiel, Germany.
| | - Jens Tetens
- Department of Animal Sciences, Georg-August-University, Göttingen, Germany
- Center for Integrated Breeding Research, Georg-August-University, Göttingen, Germany
| | - Jörn Bennewitz
- Institute of Animal Husbandry and Breeding, University of Hohenheim, Stuttgart, Germany
| | - Georg Thaller
- Institute of Animal Breeding and Husbandry, Kiel University, Kiel, Germany
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Berghöfer J, Khaveh N, Mundlos S, Metzger J. Simultaneous testing of rule- and model-based approaches for runs of homozygosity detection opens up a window into genomic footprints of selection in pigs. BMC Genomics 2022; 23:564. [PMID: 35933356 PMCID: PMC9357325 DOI: 10.1186/s12864-022-08801-4] [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: 04/22/2022] [Accepted: 07/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Past selection events left footprints in the genome of domestic animals, which can be traced back by stretches of homozygous genotypes, designated as runs of homozygosity (ROHs). The analysis of common ROH regions within groups or populations displaying potential signatures of selection requires high-quality SNP data as well as carefully adjusted ROH-defining parameters. In this study, we used a simultaneous testing of rule- and model-based approaches to perform strategic ROH calling in genomic data from different pig populations to detect genomic regions under selection for specific phenotypes. RESULTS Our ROH analysis using a rule-based approach offered by PLINK, as well as a model-based approach run by RZooRoH demonstrated a high efficiency of both methods. It underlined the importance of providing a high-quality SNP set as input as well as adjusting parameters based on dataset and population for ROH calling. Particularly, ROHs ≤ 20 kb were called in a high frequency by both tools, but to some extent covered different gene sets in subsequent analysis of ROH regions common for investigated pig groups. Phenotype associated ROH analysis resulted in regions under potential selection characterizing heritage pig breeds, known to harbour a long-established breeding history. In particular, the selection focus on fitness-related traits was underlined by various ROHs harbouring disease resistance or tolerance-associated genes. Moreover, we identified potential selection signatures associated with ear morphology, which confirmed known candidate genes as well as uncovered a missense mutation in the ABCA6 gene potentially supporting ear cartilage formation. CONCLUSIONS The results of this study highlight the strengths and unique features of rule- and model-based approaches as well as demonstrate their potential for ROH analysis in animal populations. We provide a workflow for ROH detection, evaluating the major steps from filtering for high-quality SNP sets to intersecting ROH regions. Formula-based estimations defining ROHs for rule-based method show its limits, particularly for efficient detection of smaller ROHs. Moreover, we emphasize the role of ROH detection for the identification of potential footprints of selection in pigs, displaying their breed-specific characteristics or favourable phenotypes.
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Affiliation(s)
- Jan Berghöfer
- Research Group Veterinary Functional Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany.,Department of Biology, Chemistry and Pharmacy, Institute of Chemistry and Biochemistry, Freie Universität Berlin, Berlin, Germany
| | - Nadia Khaveh
- Research Group Veterinary Functional Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany.,Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Hannover, Germany
| | - Stefan Mundlos
- Research Group Development & Disease, Max Planck Institute for Molecular Genetics, Berlin, Germany.,Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Berlin, Germany.,Charité-Universitätsmedizin Berlin, BCRT, Berlin Institute of Health Center for Regenerative Therapies, Berlin, Germany
| | - Julia Metzger
- Research Group Veterinary Functional Genomics, Max Planck Institute for Molecular Genetics, Berlin, Germany. .,Institute of Animal Breeding and Genetics, University of Veterinary Medicine Hannover, Hannover, Germany.
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Colpitts J, McLoughlin PD, Poissant J. Runs of homozygosity in Sable Island feral horses reveal the genomic consequences of inbreeding and divergence from domestic breeds. BMC Genomics 2022; 23:501. [PMID: 35820826 PMCID: PMC9275264 DOI: 10.1186/s12864-022-08729-9] [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: 02/16/2022] [Accepted: 06/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Understanding inbreeding and its impact on fitness and evolutionary potential is fundamental to species conservation and agriculture. Long stretches of homozygous genotypes, known as runs of homozygosity (ROH), result from inbreeding and their number and length can provide useful population-level information on inbreeding characteristics and locations of signatures of selection. However, the utility of ROH for conservation is limited for natural populations where baseline data and genomic tools are lacking. Comparing ROH metrics in recently feral vs. domestic populations of well understood species like the horse could provide information on the genetic health of those populations and offer insight into how such metrics compare between managed and unmanaged populations. Here we characterized ROH, inbreeding coefficients, and ROH islands in a feral horse population from Sable Island, Canada, using ~41 000 SNPs and contrasted results with those from 33 domestic breeds to assess the impacts of isolation on ROH abundance, length, distribution, and ROH islands. RESULTS ROH number, length, and ROH-based inbreeding coefficients (FROH) in Sable Island horses were generally greater than in domestic breeds. Short runs, which typically coalesce many generations prior, were more abundant than long runs in all populations, but run length distributions indicated more recent population bottlenecks in Sable Island horses. Nine ROH islands were detected in Sable Island horses, exhibiting very little overlap with those found in domestic breeds. Gene ontology (GO) enrichment analysis for Sable Island ROH islands revealed enrichment for genes associated with 3 clusters of biological pathways largely associated with metabolism and immune function. CONCLUSIONS This study indicates that Sable Island horses tend to be more inbred than their domestic counterparts and that most of this inbreeding is due to historical bottlenecks and founder effects rather than recent mating between close relatives. Unique ROH islands in the Sable Island population suggest adaptation to local selective pressures and/or strong genetic drift and highlight the value of this population as a reservoir of equine genetic variation. This research illustrates how ROH analyses can be applied to gain insights into the population history, genetic health, and divergence of wild or feral populations of conservation concern.
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Affiliation(s)
- Julie Colpitts
- Department of Biology, University of Saskatchewan, Saskatchewan, Canada.
| | | | - Jocelyn Poissant
- Faculty of Veterinary Medicine, University of Calgary, Calgary, Alberta, Canada.
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Wang W, Fang D, Shi Y, He F, Gan J, Fu M, Deng X, Zhang T, Shen H, Zhong S, Aguo Y, Chen L, An N, Zhang Z, Yi J. Genome-wide SNP analysis reveals the selection signatures of two indigenous buffalo breeds in Sichuan. CONSERV GENET RESOUR 2022. [DOI: 10.1007/s12686-022-01275-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
AbstractSichuan Province spawned abundant of indigenous buffalo varieties, which probably harbor valuable gene resources beneficial to the genetic improvement of buffalo. However, limited genetic information was publicly available. To better understand their selection signatures between different populations, we performed a restriction site-associated DNA sequencing (RADseq) to explore genome-wide SNPs among two indigenous breeds of Sichuan buffaloes. As a result, a total of 2,110,077 high-quality SNPs were finally obtained. Population genetic analysis indicated a obviously genetic differentiation between two breeds. The detection of selective genes showed that 995 and 910 protein-coding genes underwent positive selection in Yibin buffalo (GYBS) and Dechang buffalo (XCS). Further functional analysis revealed distinctly discrepant selection in two breeds. Candidate genes that positively selected from Yibin buffaloes have mainly occurred in functions closely related to meat quality, complex living environment adaption capability, and disease resistance. While they were significantly enriched in cell proliferation and cell components in Dechang buffalo, indicating the selection pressure primarily derived from the requirement of organism growth and development speed during breed formation. Our dataset constitutes a promising reservoir of genome-wide SNP markers of Sichuan buffaloes and provides potentially traits selected in different local populations. Such comprehensive genetic resources offer an unprecedented opportunity for genetic association analysis of economically important traits and precision breeding programs in buffaloes.
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12
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Genetic Differentiation among Livestock Breeds—Values for Fst. Animals (Basel) 2022; 12:ani12091115. [PMID: 35565543 PMCID: PMC9103131 DOI: 10.3390/ani12091115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Revised: 04/19/2022] [Accepted: 04/25/2022] [Indexed: 12/02/2022] Open
Abstract
Simple Summary The degree of relationship among livestock breeds can be quantified by the Fst statistic, which measures the extent of genetic differentiation between them. An Fst value of 0.1 has often been taken as indicating that two breeds are indeed genetically distinct, but this concept has not been evaluated critically. Here, Fst values have been collated for the six major livestock species: cattle, sheep, goats, pigs, horses, and chickens. These values are remarkably variable both within and between species, demonstrating that Fst > 0.1 is not a reliable criterion for breed distinctiveness. However, the large body of Fst data accumulated in the last 20–30 years represents an untapped database that could contribute to the development of interdisciplinary research involving livestock breeds. Abstract (1) Background: The Fst statistic is widely used to characterize between-breed relationships. Fst = 0.1 has frequently been taken as indicating genetic distinctiveness between breeds. This study investigates whether this is justified. (2) Methods: A database was created of 35,080 breed pairs and their corresponding Fst values, deduced from microsatellite and SNP studies covering cattle, sheep, goats, pigs, horses, and chickens. Overall, 6560 (19%) of breed pairs were between breeds located in the same country, 7395 (21%) between breeds of different countries within the same region, 20,563 (59%) between breeds located far apart, and 562 (1%) between a breed and the supposed wild ancestor of the species. (3) Results: General values for between-breed Fst were as follows, cattle: microsatellite 0.06–0.12, SNP 0.08–0.15; sheep: microsatellite 0.06–0.10, SNP 0.06–0.17; horses: microsatellite 0.04–0.11, SNP 0.08–0.12; goats: microsatellite 0.04–0.14, SNP 0.08–0.16; pigs: microsatellite 0.06–0.27, SNP 0.15–0.22; chickens: microsatellite 0.05–0.28, SNP 0.08–0.26. (4) Conclusions: (1) Large amounts of Fst data are available for a substantial proportion of the world’s livestock breeds, (2) the value for between-breed Fst of 0.1 is not appropriate owing to its considerable variability, and (3) accumulated Fst data may have value for interdisciplinary research.
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Wang X, Li G, Ruan D, Zhuang Z, Ding R, Quan J, Wang S, Jiang Y, Huang J, Gu T, Hong L, Zheng E, Li Z, Cai G, Wu Z, Yang J. Runs of Homozygosity Uncover Potential Functional-Altering Mutation Associated With Body Weight and Length in Two Duroc Pig Lines. Front Vet Sci 2022; 9:832633. [PMID: 35350434 PMCID: PMC8957889 DOI: 10.3389/fvets.2022.832633] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 01/24/2022] [Indexed: 12/29/2022] Open
Abstract
Runs of homozygosity (ROH) are widely used to investigate genetic diversity, demographic history, and positive selection signatures of livestock. Commercial breeds provide excellent materials to reveal the landscape of ROH shaped during the intense selection process. Here, we used the GeneSeek Porcine 50K single-nucleotide polymorphism (SNP) Chip data of 3,770 American Duroc (AD) and 2,096 Canadian Duroc (CD) pigs to analyze the genome-wide ROH. First, we showed that AD had a moderate genetic differentiation with CD pigs, and AD had more abundant genetic diversity and significantly lower level of inbreeding than CD pigs. In addition, sows had larger levels of homozygosity than boars in AD pigs. These differences may be caused by differences in the selective intensity. Next, ROH hotspots revealed that many candidate genes are putatively under selection for growth, sperm, and muscle development in two lines. Population-specific ROHs inferred that AD pigs may have a special selection for female reproduction, while CD pigs may have a special selection for immunity. Moreover, in the overlapping ROH hotspots of two Duroc populations, we observed a missense mutation (rs81216249) located in the growth and fat deposition-related supergene (ARSB-DMGDH-BHMT) region. The derived allele of this variant originated from European pigs and was nearly fixed in Duroc pigs. Further selective sweep and association analyses indicated that this supergene was subjected to strong selection and probably contributed to the improvement of body weight and length in Duroc pigs. These findings will enhance our understanding of ROH patterns in different Duroc lines and provide promising trait-related genes and a functional-altering marker that can be used for genetic improvement of pigs.
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Affiliation(s)
- Xiaopeng Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Guixin Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Donglin Ruan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Shiyuan Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Yongchuang Jiang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Jinyan Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Ting Gu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Linjun Hong
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Zicong Li
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- *Correspondence: Zhenfang Wu
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, China
- Guangdong Provincial Laboratory of Lingnan Modern Agricultural Science and Technology, Guangzhou, China
- Jie Yang
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Kim YM, Seong HS, Kim YS, Hong JK, Sa SJ, Lee J, Lee JH, Cho KH, Chung WH, Choi JW, Cho ES. Genome-Wide Assessment of a Korean Composite Pig Breed, Woori-Heukdon. Front Genet 2022; 13:779152. [PMID: 35186025 PMCID: PMC8847790 DOI: 10.3389/fgene.2022.779152] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2021] [Accepted: 01/07/2022] [Indexed: 02/03/2023] Open
Abstract
A Korean synthetic pig breed, Woori-Heukdon (WRH; F3), was developed by crossing parental breeds (Korean native pig [KNP] and Korean Duroc [DUC]) with their crossbred populations (F1 and F2). This study in genome-wide assessed a total of 2,074 pigs which include the crossbred and the parental populations using the Illumina PorcineSNP60 BeadChip. After quality control of the initial datasets, we performed population structure, genetic diversity, and runs of homozygosity (ROH) analyses. Population structure analyses showed that crossbred populations were genetically influenced by the parental breeds according to their generation stage in the crossbreeding scheme. Moreover, principal component analysis showed the dispersed cluster of WRH, which might reflect introducing a new breeding group into the previous one. Expected heterozygosity values, which were used to assess genetic diversity, were .365, .349, .336, .330, and .211 for WRH, F2, F1, DUC, and KNP, respectively. The inbreeding coefficient based on ROH was the highest in KNP (.409), followed by WRH (.186), DUC (.178), F2 (.107), and F1 (.035). Moreover, the frequency of short ROH decreased according to the crossing stage (from F1 to WRH). Alternatively, the frequency of medium and long ROH increased, which indicated recent inbreeding in F2 and WRH. Furthermore, gene annotation of the ROH islands in WRH that might be inherited from their parental breeds revealed several interesting candidate genes that may be associated with adaptation, meat quality, production, and reproduction traits in pigs.
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Affiliation(s)
- Yong-Min Kim
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea.,Department of Animal Science, College of Animal Life Sciences, Kangwon National University, Chuncheon, South Korea
| | - Ha-Seung Seong
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea.,Department of Animal Science, College of Animal Life Sciences, Kangwon National University, Chuncheon, South Korea
| | - Young-Sin Kim
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea
| | - Joon-Ki Hong
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea
| | - Soo-Jin Sa
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea
| | - Jungjae Lee
- Department of Animal Science and Technology, College of Biotechnology and Natural Resources, Chung-Ang University, Anseong, South Korea
| | - Jun-Hee Lee
- Institute of Agriculture and Life Science, College of Agriculture and Life Sciences, Gyeongsang National University, Jinju, South Korea
| | - Kyu-Ho Cho
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea
| | - Won-Hyong Chung
- Research Group of Healthcare, Korea Food Research Institute, Wanju, South Korea
| | - Jung-Woo Choi
- Department of Animal Science, College of Animal Life Sciences, Kangwon National University, Chuncheon, South Korea
| | - Eun-Seok Cho
- Swine Science Division, National Institute of Animal Science, Rural Development Administration, Cheonan, South Korea
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15
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Selection and Drift: A Comparison between Historic and Recent Dutch Friesian Cattle and Recent Holstein Friesian Using WGS Data. Animals (Basel) 2022; 12:ani12030329. [PMID: 35158654 PMCID: PMC8833835 DOI: 10.3390/ani12030329] [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: 11/29/2021] [Revised: 01/21/2022] [Accepted: 01/26/2022] [Indexed: 12/13/2022] Open
Abstract
Simple Summary Over the last century, genetic diversity in the cattle species has been affected by the replacement of many local, dual-purpose breeds with a few specialized, high-output dairy breeds. This replacement caused a sharp decline in the population size of local breeds. In the Netherlands, the local Dutch Friesian breed has gradually been replaced by the Holstein Friesian. This resulted in a rapid decrease in numbers of the Dutch Friesian breed with an associated risk of loss of genetic diversity due to drift. The objective of this study is to investigate genomewide genetic diversity between a group of historic and recent Dutch Friesian bulls and a group of recently used Holstein Friesian bulls. Our findings showed that a large amount of diversity is shared between the three groups, but each of them has some unique genetic identity (12% of the single nucleotide polymorphism were group-specific). The genetic diversity of the Dutch Friesians reduced over time, but this did not lead to higher inbreeding levels—especially, inbreeding due to recent ancestors has not increased. Genetically, the recent Dutch Friesians were slightly more different from Holstein Friesians than the historic Dutch Friesians. Our results also highlighted the presence of several genomic regions that differentiated between the groups. Abstract Over the last century, genetic diversity in many cattle breeds has been affected by the replacement of traditional local breeds with just a few milk-producing breeds. In the Netherlands, the local Dutch Friesian breed (DF) has gradually been replaced by the Holstein Friesian breed (HF). The objective of this study is to investigate genomewide genetic diversity between a group of historically and recently used DF bulls and a group of recently used HF bulls. Genetic material of 12 historic (hDF), 12 recent DF bulls (rDF), and 12 recent HF bulls (rHF) in the Netherlands was sequenced. Based on the genomic information, different parameters—e.g., allele frequencies, inbreeding coefficient, and runs of homozygosity (ROH)—were calculated. Our findings showed that a large amount of diversity is shared between the three groups, but each of them has a unique genetic identity (12% of the single nucleotide polymorphisms were group-specific). The rDF is slightly more diverged from rHF than hDF. The inbreeding coefficient based on runs of homozygosity (Froh) was higher for rDF (0.24) than for hDF (0.17) or rHF (0.13). Our results also displayed the presence of several genomic regions that differentiated between the groups. In addition, thirteen, forty-five, and six ROH islands were identified in hDF, rDF, and rHF, respectively. The genetic diversity of the DF breed reduced over time, but this did not lead to higher inbreeding levels—especially, inbreeding due to recent ancestors was not increased.
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Genetic Diversity, Admixture and Analysis of Homozygous-by-Descent (HBD) Segments of Russian Wild Boar. BIOLOGY 2022; 11:biology11020203. [PMID: 35205070 PMCID: PMC8869248 DOI: 10.3390/biology11020203] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Revised: 01/25/2022] [Accepted: 01/25/2022] [Indexed: 02/04/2023]
Abstract
The wild boar is the wild ancestor of the domestic pig and one of the most common species of ungulates. At the beginning of the 20th century, the wild boar was practically exterminated in the European part of Russia. In the period 1935-1988, 7705 boars were caught in various regions of the European part of Russia, the Far East, Ukraine, Belarus, Kyrgyzstan, Kazakhstan, Latvia, Lithuania, Estonia, Tajikistan and resettled in the territory of Russia. Asian and European wild boars dwell the territory of Russia. The aim of our research was to study the genetic diversity and structure of wild boar populations in different regions of Russia using genome-wide genotyping. We have determined the genetic distances, population structure, parameters of genetic diversity and significantly expanded our understanding of the genetic state of the Russian wild boar. For the first time, we calculated autozygosity of the wild boar of the European and Asian subspecies using Homozygous-by-Descent (HBD) Segments analysis, which is important in terms of population recovery. We also found evidence of hybridization between Russian wild boar and domestic pigs. A group of European wild boars showed introgression of the Asian boar into population. The mean level of the inbreeding coefficient in European wild boar was higher than in Asian wild boar, and combined groups of the European boar had higher inbreeding coefficient than Russian wild boars. These results obtained can be used in population management.
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Zhao Y, Pu Y, Liang B, Bai T, Liu Y, Jiang L, Ma Y. A study using single-locus and multi-locus genome-wide association study to identify genes associated with teat number in Hu sheep. Anim Genet 2022; 53:203-211. [PMID: 35040155 PMCID: PMC9303709 DOI: 10.1111/age.13169] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2021] [Revised: 11/08/2021] [Accepted: 12/24/2021] [Indexed: 01/19/2023]
Abstract
The multiple teats trait is common in many species of mammals and is considered related to lactation ability in swine. However, in Hu sheep, related gene research is still relatively limited. In this study, a genome‐wide association study was used to identify genetic markers and genes related to the number of teats in the Hu sheep population, a native Chinese sheep breed. A single marker method and several multi‐locus methods were utilized. A total of 61 SNPs were found to be related to the number of teats. Among these, 11 SNPs and one SNP were consistently detected by two and three multi‐locus models respectively. Four SNPs were concordantly identified between the single marker and multi‐locus methods. We also performed quantitative real‐time PCR testing of these identified candidate genes, identifying three genes with significantly different expression. Our study suggested that the LHFP, DPYSL2, and TDP‐43 genes may be related to the number of teats in sheep. The combination of single and multi‐locus GWAS detected additional SNPs not found with only one model. Our results provide new and important insights into the genetic mechanisms of the mammalian multiparous teat phenotype. These findings may be useful for future breeding and understanding the genetics of sheep and other livestock.
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Affiliation(s)
- Yuhetian Zhao
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Yabin Pu
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Benmeng Liang
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Tianyou Bai
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Yue Liu
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Lin Jiang
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
| | - Yuehui Ma
- National Germplasm Center of Domestic Animal Resources, Institute of Animal Science (IAS), Chinese Academy of Agricultural Sciences (CAAS), Haidian, Beijing, China
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Genomics Confirm an Alarming Status of the Genetic Diversity of Belgian Red and Belgian White Red Cattle. Animals (Basel) 2021; 11:ani11123574. [PMID: 34944349 PMCID: PMC8697887 DOI: 10.3390/ani11123574] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2021] [Revised: 12/10/2021] [Accepted: 12/13/2021] [Indexed: 11/17/2022] Open
Abstract
Simple Summary Genetic diversity of livestock is vitally important as it enables the adaptation of future populations to changing environments. Therefore, preserving a sufficiently large genetic diversity is key. However, for many local cattle populations, little is known about their genetic diversity such as inbreeding level, effective size etc. We studied the genetic diversity of two local Belgian red cattle populations (Belgian Red and Belgian White Red cattle) using state-of-the-art genomic techniques. These tools assessed diversity at the population and individual level, and allowed the positioning of these two breeds in an international context of 52 other (European) cattle breeds. Accordingly, we contribute to the general knowledge of European red cattle, and more specifically we help the breeders, breed organization and the government to manage the genetic diversity of both breeds. Abstract Genetic diversity is increasingly important for researchers and society. Small and local populations deserve more attention especially, as they may harbor important characteristics. Moreover, small populations are at greater risk and their genetic management is often more challenging. Likewise, European red cattle populations are threatened, as they are outcompeted by more specialized cattle breeds. In this study, we investigate the genetic diversity of two local Belgian red cattle breeds: Belgian Red and Belgian White Red cattle. A total of 270 animals were genotyped via medium density SNP arrays. Genetic diversity was assessed using runs of homozygosity screening, effective population size estimation and Fst analyses. Genomic inbreeding coefficients based on runs of homozygosity were estimated at 7.0% for Belgian Red and 6.1% for Belgian White Red cattle, and both populations had a low effective population size (68 and 86, respectively). PCA, Fst and admixture analyses revealed the relationship to 52 other international breeds, where they were closest related to some Belgian, French, Scandinavian and Dutch breeds. Moreover, Fst analyses revealed for Belgian Red cattle a signature of selection on BTA6, adjacent to the KIT gene. This study gains important knowledge on the genetic diversity of these two small local red cattle breeds, and will aid in their (genetic) management.
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Tsartsianidou V, Sánchez-Molano E, Kapsona VV, Basdagianni Z, Chatziplis D, Arsenos G, Triantafyllidis A, Banos G. A comprehensive genome-wide scan detects genomic regions related to local adaptation and climate resilience in Mediterranean domestic sheep. Genet Sel Evol 2021; 53:90. [PMID: 34856922 PMCID: PMC8641236 DOI: 10.1186/s12711-021-00682-7] [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: 05/26/2021] [Accepted: 11/09/2021] [Indexed: 02/07/2023] Open
Abstract
Background The management of farm animal genetic resources and the adaptation of animals to climate change will probably have major effects on the long-term sustainability of the livestock sector. Genomic data harbour useful relevant information that needs to be harnessed for effectively managing genetic resources. In this paper, we report the genome characterization of the highly productive Mediterranean Chios dairy sheep and focus on genetic diversity measures related with local adaptation and selection and the genetic architecture of animal resilience to weather fluctuations as a novel adaptative trait linked to climate change. Results We detected runs of homozygosity (ROH) and heterozygosity (ROHet) that revealed multiple highly homozygous and heterozygous hotspots across the Chios sheep genome. A particularly highly homozygous region was identified on chromosome 13 as a candidate of directional genetic selection associated with milk traits, which includes annotated genes that were previously shown to be linked to local adaptation to harsh environmental conditions. Favourable heterozygosity related with a potentially protective role against livestock diseases and enhanced overall fitness was revealed in heterozygous-rich regions on sheep chromosomes 3, 10, 13 and 19. Furthermore, genomic analyses were conducted on sheep resilience phenotypes that display changes in milk production in response to weather variation. Sheep resilience to heat stress was a significantly heritable trait (h2 = 0.26) and genetically antagonistic to milk production. Genome-wide association and regional heritability mapping analyses revealed novel genomic markers and regions on chromosome 5 that were significantly associated with sheep resilience to climate change. Subsequently, an annotation analysis detected a set of genes on chromosome 5 that were associated with olfactory receptor complexes that could participate in heat stress mitigation through changes in respiration rate and respiratory evaporation. Other genes were grouped in previously reported biological processes relevant to livestock heat dissipation, including stress and immune response. Conclusions Our results may contribute to the optimal management of sheep genetic resources and inform modern selective breeding programmes that aim at mitigating future environmental challenges towards sustainable farming, while better balancing animal adaptation and productivity. Our results are directly relevant to the studied breed and the respective environmental conditions; however, the methodology may be extended to other livestock species of interest. Supplementary Information The online version contains supplementary material available at 10.1186/s12711-021-00682-7.
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Affiliation(s)
- Valentina Tsartsianidou
- Department of Genetics, Development & Molecular Biology, School of Biology, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece.
| | - Enrique Sánchez-Molano
- Division of Genetics and Genomics, School of Veterinary Studies, The Roslin Institute and Royal (Dick), University of Edinburgh, Easter Bush, Midlothian, EH25 9RG, UK
| | - Vanessa Varvara Kapsona
- Department of Animal and Veterinary Sciences, Scotland's Rural College, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, UK
| | - Zoitsa Basdagianni
- Department of Animal Production, School of Agriculture, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | - Dimitrios Chatziplis
- Laboratory of Agrobiotechnology and Inspection of Agricultural Products, Department of Agriculture, International Hellenic University, Alexander Campus, 57400, Sindos, Greece
| | - Georgios Arsenos
- Laboratory of Animal Husbandry, School of Veterinary Medicine, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | - Alexandros Triantafyllidis
- Department of Genetics, Development & Molecular Biology, School of Biology, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
| | - Georgios Banos
- Department of Animal and Veterinary Sciences, Scotland's Rural College, Roslin Institute Building, Easter Bush, Midlothian, EH25 9RG, UK.,Laboratory of Animal Husbandry, School of Veterinary Medicine, Aristotle University of Thessaloniki, 54124, Thessaloniki, Greece
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Duntsch L, Whibley A, Brekke P, Ewen JG, Santure AW. Genomic data of different resolutions reveal consistent inbreeding estimates but contrasting homozygosity landscapes for the threatened Aotearoa New Zealand hihi. Mol Ecol 2021; 30:6006-6020. [PMID: 34242449 DOI: 10.1111/mec.16068] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Accepted: 07/01/2021] [Indexed: 12/19/2022]
Abstract
Inbreeding can lead to a loss of heterozygosity in a population and when combined with genetic drift may reduce the adaptive potential of a species. However, there is uncertainty about whether resequencing data can provide accurate and consistent inbreeding estimates. Here, we performed an in-depth inbreeding analysis for hihi (Notiomystis cincta), an endemic and nationally vulnerable passerine bird of Aotearoa New Zealand. We first focused on subsampling variants from a reference genome male, and found that low-density data sets tend to miss runs of homozygosity (ROH) in some places and overestimate ROH length in others, resulting in contrasting homozygosity landscapes. Low-coverage resequencing and 50 K SNP array densities can yield comparable inbreeding results to high-coverage resequencing approaches, but the results for all data sets are highly dependent on the software settings employed. Second, we extended our analysis to 10 hihi where low-coverage whole genome resequencing, RAD-seq and SNP array genotypes are available. We inferred ROH and individual inbreeding to evaluate the relative effects of sequencing depth versus SNP density on estimating inbreeding coefficients and found that high rates of missingness downwardly bias both the number and length of ROH. In summary, when using genomic data to evaluate inbreeding, studies must consider that ROH estimates are heavily dependent on analysis parameters, data set density and individual sequencing depth.
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Affiliation(s)
- Laura Duntsch
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Annabel Whibley
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
| | - Patricia Brekke
- Institute of Zoology, Zoological Society of London, London, UK
| | - John G Ewen
- Institute of Zoology, Zoological Society of London, London, UK
| | - Anna W Santure
- School of Biological Sciences, University of Auckland, Auckland, New Zealand
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21
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Qiu Y, Ding R, Zhuang Z, Wu J, Yang M, Zhou S, Ye Y, Geng Q, Xu Z, Huang S, Cai G, Wu Z, Yang J. Genome-wide detection of CNV regions and their potential association with growth and fatness traits in Duroc pigs. BMC Genomics 2021; 22:332. [PMID: 33964879 PMCID: PMC8106131 DOI: 10.1186/s12864-021-07654-7] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2020] [Accepted: 04/27/2021] [Indexed: 11/19/2022] Open
Abstract
Background In the process of pig breeding, the average daily gain (ADG), days to 100 kg (AGE), and backfat thickness (BFT) are directly related to growth rate and fatness. However, the genetic mechanisms involved are not well understood. Copy number variation (CNV), an important source of genetic diversity, can affect a variety of complex traits and diseases and has gradually been thrust into the limelight. In this study, we reported the genome-wide CNVs of Duroc pigs using SNP genotyping data from 6627 animals. We also performed a copy number variation region (CNVR)-based genome-wide association studies (GWAS) for growth and fatness traits in two Duroc populations. Results Our study identified 953 nonredundant CNVRs in U.S. and Canadian Duroc pigs, covering 246.89 Mb (~ 10.90%) of the pig autosomal genome. Of these, 802 CNVRs were in U.S. Duroc pigs with 499 CNVRs were in Canadian Duroc pigs, indicating 348 CNVRs were shared by the two populations. Experimentally, 77.8% of nine randomly selected CNVRs were validated through quantitative PCR (qPCR). We also identified 35 CNVRs with significant association with growth and fatness traits using CNVR-based GWAS. Ten of these CNVRs were associated with both ADG and AGE traits in U.S. Duroc pigs. Notably, four CNVRs showed significant associations with ADG, AGE, and BFT, indicating that these CNVRs may play a pleiotropic role in regulating pig growth and fat deposition. In Canadian Duroc pigs, nine CNVRs were significantly associated with both ADG and AGE traits. Further bioinformatic analysis identified a subset of potential candidate genes, including PDGFA, GPER1, PNPLA2 and BSCL2. Conclusions The present study provides a necessary supplement to the CNV map of the Duroc genome through large-scale population genotyping. In addition, the CNVR-based GWAS results provide a meaningful way to elucidate the genetic mechanisms underlying complex traits. The identified CNVRs can be used as molecular markers for genetic improvement in the molecular-guided breeding of modern commercial pigs. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-021-07654-7.
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Affiliation(s)
- Yibin Qiu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China
| | - Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Ming Yang
- Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Qian Geng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Zheng Xu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China
| | - Sixiu Huang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China.,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. .,Guangdong Wens Breeding Swine Technology Co., Ltd., Yunfu, Guangdong, 527400, People's Republic of China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China.
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China. .,Lingnan Guangdong Laboratory of Modern Agriculture, Guangzhou, 510642, People's Republic of China.
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22
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Schiavo G, Bovo S, Muñoz M, Ribani A, Alves E, Araújo JP, Bozzi R, Čandek-Potokar M, Charneca R, Fernandez AI, Gallo M, García F, Karolyi D, Kušec G, Martins JM, Mercat MJ, Núñez Y, Quintanilla R, Radović Č, Razmaite V, Riquet J, Savić R, Usai G, Utzeri VJ, Zimmer C, Ovilo C, Fontanesi L. Runs of homozygosity provide a genome landscape picture of inbreeding and genetic history of European autochthonous and commercial pig breeds. Anim Genet 2021; 52:155-170. [PMID: 33544919 DOI: 10.1111/age.13045] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/15/2021] [Indexed: 12/12/2022]
Abstract
ROHs are long stretches of DNA homozygous at each polymorphic position. The proportion of genome covered by ROHs and their length are indicators of the level and origin of inbreeding. Frequent common ROHs within the same population define ROH islands and indicate hotspots of selection. In this work, we investigated ROHs in a total of 1131 pigs from 20 European local pig breeds and in three cosmopolitan breeds, genotyped with the GGP Porcine HD Genomic Profiler. plink software was used to identify ROHs. Size classes and genomic inbreeding parameters were evaluated. ROH islands were defined by evaluating different thresholds of homozygous SNP frequency. A functional overview of breed-specific ROH islands was obtained via over-representation analyses of GO biological processes. Mora Romagnola and Turopolje breeds had the largest proportions of genome covered with ROH (~1003 and ~955 Mb respectively), whereas Nero Siciliano and Sarda breeds had the lowest proportions (~207 and 247 Mb respectively). The highest proportion of long ROH (>16 Mb) was in Apulo-Calabrese, Mora Romagnola and Casertana. The largest number of ROH islands was identified in the Italian Landrace (n = 32), Cinta Senese (n = 26) and Lithuanian White Old Type (n = 22) breeds. Several ROH islands were in regions encompassing genes known to affect morphological traits. Comparative ROH structure analysis among breeds indicated the similar genetic structure of local breeds across Europe. This study contributed to understanding of the genetic history of the investigated pig breeds and provided information to manage these pig genetic resources.
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Affiliation(s)
- G Schiavo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, Bologna, 40127, Italy
| | - S Bovo
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, Bologna, 40127, Italy
| | - M Muñoz
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - A Ribani
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, Bologna, 40127, Italy
| | - E Alves
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - J P Araújo
- Centro de Investigação de Montanha (CIMO), Instituto Politécnico de Viana do Castelo, Escola Superior Agrária, Refóios do Lima, Ponte de Lima, 4990-706, Portugal
| | - R Bozzi
- DAGRI - Animal Science Division, Università di Firenze, Via delle Cascine 5, Firenze, 50144, Italy
| | - M Čandek-Potokar
- Kmetijski Inštitut Slovenije, Hacquetova 17, Ljubljana, SI-1000, Slovenia
| | - R Charneca
- Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, Polo da Mitra, Apartado 94, Évora, 7006-554, Portugal
| | - A I Fernandez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - M Gallo
- Associazione Nazionale Allevatori Suini, Via Nizza 53, Rome, 00198, Italy
| | - F García
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - D Karolyi
- Department of Animal Science, Faculty of Agriculture, University of Zagreb, Svetošimunska c. 25, Zagreb, 10000, Croatia
| | - G Kušec
- Faculty of Agrobiotechnical Sciences, University of Osijek, Vladimira Preloga 1, Osijek, 31000, Croatia
| | - J M Martins
- Instituto de Ciências Agrárias e Ambientais Mediterrânicas, Universidade de Évora, Polo da Mitra, Apartado 94, Évora, 7006-554, Portugal
| | - M-J Mercat
- IFIP Institut du porc, La Motte au Vicomte, BP 35104, Le Rheu Cedex, 35651, France
| | - Y Núñez
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - R Quintanilla
- Programa de Genética y Mejora Animal, IRTA, Torre Marimon, Caldes de Montbui, Barcelona, 08140, Spain
| | - Č Radović
- Department of Pig Breeding and Genetics, Institute for Animal Husbandry, Belgrade-Zemun, 11080, Serbia
| | - V Razmaite
- Animal Science Institute, Lithuanian University of Health Sciences, Baisogala, 82317, Lithuania
| | - J Riquet
- GenPhySE, Université de Toulouse, INRA, Chemin de Borde-Rouge 24, Auzeville Tolosane, Castanet Tolosan, 31326, France
| | - R Savić
- Faculty of Agriculture, University of Belgrade, Nemanjina 6, Belgrade-Zemun, 11080, Serbia
| | - G Usai
- Agris Sardegna, Loc. Bonassai, Sassari, 07100, Italy
| | - V J Utzeri
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, Bologna, 40127, Italy
| | - C Zimmer
- Bäuerliche Erzeugergemeinschaft Schwäbisch Hall, Haller Str. 20, Wolpertshausen, 74549, Germany
| | - C Ovilo
- Departamento Mejora Genética Animal, INIA, Crta. de la Coruña, km. 7,5, Madrid, 28040, Spain
| | - L Fontanesi
- Department of Agricultural and Food Sciences, Division of Animal Sciences, University of Bologna, Viale Giuseppe Fanin 46, Bologna, 40127, Italy
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23
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Ganteil A, Rodriguez-Ramilo ST, Ligonesche B, Larzul C. Characterization of Autozygosity in Pigs in Three-Way Crossbreeding. Front Genet 2021; 11:584556. [PMID: 33584790 PMCID: PMC7876413 DOI: 10.3389/fgene.2020.584556] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 12/21/2020] [Indexed: 11/16/2022] Open
Abstract
Crossbreeding in livestock can be used to increase genetic diversity. The resulting increase in variability is related to the heterozygosity of the crossbred animal. The evolution of diversity during crossbreeding can be assessed using genomic data. The objective of this study was to describe patterns of runs of homozygosity (ROH) in animals resulting from three-way crossbreeding, from parental pure lines, and in their crossbred offspring. The crossbreeding scheme consisted of a first crossbreeding Pietrain boars and Large White sows, after which the offspring of the Pietrain × Large White were crossed with Duroc boars. The offspring of the second crossbreeding are called G0, the offspring of G0 boars and G0 sows are called G1. All the animals were genotyped using the Illumina SNP60 porcine chip. After filtering, analyses were performed with 2,336 animals and 48,579 autosomal single nucleotide polymorphism (SNP). The mean ROH-based inbreeding coefficients were shown to be 0.27 ± 0.05, 0.23 ± 0.04, and 0.26 ± 0.04 for Duroc, Large White, and Pietrain, respectively. ROH were detected in the Pietrain × Large White crossbred but the homozygous segments were fewer and smaller than in their parents. Similar results were obtained in the G0 crossbred. However, in the G1 crossbreds the number and the size of ROH were higher than in G0 parents. Similar ROH hotspots were detected on SSC1, SSC4, SSC7, SSC9, SSC13, SSC14, and SSC15 in both G0 and G1 animals. Long ROH (>16 Mb) were observed in G1 animals, suggesting regions with low recombination rates. The conservation of these homozygous segments in the three crossbred populations means that some haplotypes were shared between parental breeds. Gene annotation in ROH hotspots in G0 animals identified genes related to production traits including carcass composition and reproduction. These findings advance our understanding of how to manage genetic diversity in crossbred populations.
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Affiliation(s)
- Audrey Ganteil
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France.,SAS NUCLEUS, Le Rheu, France
| | | | | | - Catherine Larzul
- GenPhySE, Université de Toulouse, INRAE, ENVT, Castanet-Tolosan, France
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24
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Gorssen W, Meyermans R, Janssens S, Buys N. A publicly available repository of ROH islands reveals signatures of selection in different livestock and pet species. Genet Sel Evol 2021; 53:2. [PMID: 33397285 PMCID: PMC7784028 DOI: 10.1186/s12711-020-00599-7] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2020] [Accepted: 12/11/2020] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND Runs of homozygosity (ROH) have become the state-of-the-art method for analysis of inbreeding in animal populations. Moreover, ROH are suited to detect signatures of selection via ROH islands and are used in other applications, such as genomic prediction and genome-wide association studies (GWAS). Currently, a vast amount of single nucleotide polymorphism (SNP) data is available online, but most of these data have never been used for ROH analysis. Therefore, we performed a ROH analysis on large medium-density SNP datasets in eight animal species (cat, cattle, dog, goat, horse, pig, sheep and water buffalo; 442 different populations) and make these results publicly available. RESULTS The results include an overview of ROH islands per population and a comparison of the incidence of these ROH islands among populations from the same species, which can assist researchers when studying other (livestock) populations or when looking for similar signatures of selection. We were able to confirm many known ROH islands, for example signatures of selection for the myostatin (MSTN) gene in sheep and horses. However, our results also included multiple other ROH islands, which are common to many populations and not identified to date (e.g. on chromosomes D4 and E2 in cats and on chromosome 6 in sheep). CONCLUSIONS We are confident that our repository of ROH islands is a valuable reference for future studies. The discovered ROH island regions represent a unique starting point for new studies or can be used as a reference for future studies. Furthermore, we encourage authors to add their population-specific ROH findings to our repository.
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Affiliation(s)
- Wim Gorssen
- Livestock Genetics, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 30, Box 2472, 3001, Leuven, Belgium
| | - Roel Meyermans
- Livestock Genetics, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 30, Box 2472, 3001, Leuven, Belgium
| | - Steven Janssens
- Livestock Genetics, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 30, Box 2472, 3001, Leuven, Belgium
| | - Nadine Buys
- Livestock Genetics, Department of Biosystems, KU Leuven, Kasteelpark Arenberg 30, Box 2472, 3001, Leuven, Belgium.
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25
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Tracing selection signatures in the pig genome gives evidence for selective pressures on a unique curly hair phenotype in Mangalitza. Sci Rep 2020; 10:22142. [PMID: 33335158 PMCID: PMC7747725 DOI: 10.1038/s41598-020-79037-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 12/02/2020] [Indexed: 12/30/2022] Open
Abstract
Selection for desirable traits and breed-specific phenotypes has left distinctive footprints in the genome of pigs. As representative of a breed with strong selective traces aiming for robustness, health and performance, the Mangalitza pig, a native curly-haired pig breed from Hungary, was investigated in this study. Whole genome sequencing and SNP chip genotyping was performed to detect runs of homozygosity (ROH) in Mangalitza and Mangalitza-crossbreeds. We identified breed specific ROH regions harboring genes associated with the development of the curly hair type and further characteristics of this breed. Further analysis of two matings of Mangalitza with straight-coated pig breeds confirmed an autosomal dominant inheritance of curly hair. Subsequent scanning of the genome for variant effects on this trait revealed two variants potentially affecting hair follicle development and differentiation. Validation in a large sample set as well as in imputed SNP data confirmed these variants to be Mangalitza-specific. Herein, we demonstrated how strong artificial selection has shaped the genome in Mangalitza pigs and left traces in the form of selection signatures. This knowledge on genomic variation promoting unique phenotypes like curly hair provides an important resource for futures studies unraveling genetic effects for special characteristics in livestock.
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26
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Abstract
Runs of homozygosity (ROH) are chromosomal stretches that in a diploid genome appear in a homozygous state and display identical alleles at multiple contiguous loci. This study aimed to systematically compare the genomic distribution of the ROH islands among five populations of wild vs commercial chickens of both layer and broiler type. To this end, we analyzed whole genome sequences of 115 birds including white layer (WL, n = 25), brown layer (BL, n = 25), broiler line A (BRA, n = 20), broiler line B (BRB, n = 20) and Red Junglefowl (RJF, n = 25). The ROH segments varied in size markedly among populations, ranging from 0.3 to 21.83 Mb reflecting their past genealogy. White layers contained the largest portion of the genome in homozygous state with an average ROH length of 432.1 Mb (±18.7) per bird, despite carrying it in short segments (0.3-1 Mb). Population-wise inbreeding measures based on Wright's (Fis) and genomic (FROH) metrics revealed highly inbred genome of layer lines relative to the broilers and Red Junglefowl. We further revealed the ROH islands, among commercial lines overlapped with QTL related to limb development (GREM1, MEOX2), body weight (Meis2a.1, uc_338), eggshell color (GLCCI1, ICA1, UMAD1), antibody response to Newcastle virus (ROBO2), and feather pecking. Comparison of ROH landscape in sequencing resolution demonstrated that a sizable portion of genome of commercial lines segregates in homozygote state, reflecting many generations of assortative mating and intensive selection in their recent history. In contrary, wild birds carry shorter ROH segments, likely suggestive of older evolutionary events.
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27
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Zhan H, Zhang S, Zhang K, Peng X, Xie S, Li X, Zhao S, Ma Y. Genome-Wide Patterns of Homozygosity and Relevant Characterizations on the Population Structure in Piétrain Pigs. Genes (Basel) 2020; 11:genes11050577. [PMID: 32455573 PMCID: PMC7291003 DOI: 10.3390/genes11050577] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2020] [Revised: 05/11/2020] [Accepted: 05/11/2020] [Indexed: 01/06/2023] Open
Abstract
Investigating the patterns of homozygosity, linkage disequilibrium, effective population size and inbreeding coefficients in livestock contributes to our understanding of the genetic diversity and evolutionary history. Here we used Illumina PorcineSNP50 Bead Chip to identify the runs of homozygosity (ROH) and estimate the linkage disequilibrium (LD) across the whole genome, and then predict the effective population size. In addition, we calculated the inbreeding coefficients based on ROH in 305 Piétrain pigs and compared its effect with the other two types of inbreeding coefficients obtained by different calculation methods. A total of 23,434 ROHs were detected, and the average length of ROH per individual was about 507.27 Mb. There was no regularity on how those runs of homozygosity distributed in genome. The comparisons of different categories suggested that the formation of long ROH was probably related with recent inbreeding events. Although the density of genes located in ROH core regions is lower than that in the other genomic regions, most of them are related with Piétrain commercial traits like meat qualities. Overall, the results provide insight into the way in which ROH is produced and the identified ROH core regions can be used to map the genes associated with commercial traits in domestic animals.
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Affiliation(s)
| | | | | | | | | | | | | | - Yunlong Ma
- Correspondence: ; Tel.: +86-027-87282091
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28
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Zhuang Z, Ding R, Peng L, Wu J, Ye Y, Zhou S, Wang X, Quan J, Zheng E, Cai G, Huang W, Yang J, Wu Z. Genome-wide association analyses identify known and novel loci for teat number in Duroc pigs using single-locus and multi-locus models. BMC Genomics 2020; 21:344. [PMID: 32380955 PMCID: PMC7204245 DOI: 10.1186/s12864-020-6742-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2019] [Accepted: 04/16/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND More teats are necessary for sows to nurse larger litters to provide immunity and nutrient for piglets prior to weaning. Previous studies have reported the strong effect of an insertion mutation in the Vertebrae Development Associated (VRTN) gene on Sus scrofa chromosome 7 (SSC7) that increased the number of thoracic vertebrae and teat number in pigs. We used genome-wide association studies (GWAS) to map genetic markers and genes associated with teat number in two Duroc pig populations with different genetic backgrounds. A single marker method and several multi-locus methods were utilized. A meta-analysis that combined the effects and P-values of 34,681 single nucleotide polymorphisms (SNPs) that were common in the results of single marker GWAS of American and Canadian Duroc pigs was conducted. We also performed association tests between the VRTN insertion and teat number in the same populations. RESULTS A total of 97 SNPs were found to be associated with teat number. Among these, six, eight and seven SNPs were consistently detected with two, three and four multi-locus methods, respectively. Seven SNPs were concordantly identified between single marker and multi-locus methods. Moreover, 26 SNPs were newly found by multi-locus methods to be associated with teat number. Notably, we detected one consistent quantitative trait locus (QTL) on SSC7 for teat number using single-locus and meta-analysis of GWAS and the top SNP (rs692640845) explained 8.68% phenotypic variance of teat number in the Canadian Duroc pigs. The associations between the VRTN insertion and teat number in two Duroc pig populations were substantially weaker. Further analysis revealed that the effect of VRTN on teat number may be mediated by its LD with the true causal mutation. CONCLUSIONS Our study suggested that VRTN insertion may not be a strong or the only candidate causal mutation for the QTL on SSC7 for teat number in the analyzed Duroc pig populations. The combination of single-locus and multi-locus GWAS detected additional SNPs that were absent using only one model. The identified SNPs will be useful for the genetic improvement of teat number in pigs by assigning higher weights to associated SNPs in genomic selection.
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Affiliation(s)
- Zhanwei Zhuang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Rongrong Ding
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Longlong Peng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jie Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Yong Ye
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Shenping Zhou
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Xingwang Wang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Jianping Quan
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Enqin Zheng
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Gengyuan Cai
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China
| | - Wen Huang
- Department of animal science, Michigan State University, East Lansing, MI, USA
| | - Jie Yang
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
| | - Zhenfang Wu
- College of Animal Science and National Engineering Research Center for Breeding Swine Industry, South China Agricultural University, Guangzhou, Guangdong, 510642, People's Republic of China.
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Meyermans R, Gorssen W, Buys N, Janssens S. How to study runs of homozygosity using PLINK? A guide for analyzing medium density SNP data in livestock and pet species. BMC Genomics 2020; 21:94. [PMID: 31996125 PMCID: PMC6990544 DOI: 10.1186/s12864-020-6463-x] [Citation(s) in RCA: 108] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2019] [Accepted: 01/08/2020] [Indexed: 12/01/2022] Open
Abstract
Background PLINK is probably the most used program for analyzing SNP genotypes and runs of homozygosity (ROH), both in human and in animal populations. The last decade, ROH analyses have become the state-of-the-art method for inbreeding assessment. In PLINK, the --homozyg function is used to perform ROH analyses and relies on several input settings. These settings can have a large impact on the outcome and default values are not always appropriate for medium density SNP array data. Guidelines for a robust and uniform ROH analysis in PLINK using medium density data are lacking, albeit these guidelines are vital for comparing different ROH studies. In this study, 8 populations of different livestock and pet species are used to demonstrate the importance of PLINK input settings. Moreover, the effects of pruning SNPs for low minor allele frequencies and linkage disequilibrium on ROH detection are shown. Results We introduce the genome coverage parameter to appropriately estimate FROH and to check the validity of ROH analyses. The effect of pruning for linkage disequilibrium and low minor allele frequencies on ROH analyses is highly population dependent and such pruning may result in missed ROH. PLINK’s minimal density requirement is crucial for medium density genotypes and if set too low, genome coverage of the ROH analysis is limited. Finally, we provide recommendations for the maximal gap, scanning window length and threshold settings. Conclusions In this study, we present guidelines for an adequate and robust ROH analysis in PLINK on medium density SNP data. Furthermore, we advise to report parameter settings in publications, and to validate them prior to analysis. Moreover, we encourage authors to report genome coverage to reflect the ROH analysis’ validity. Implementing these guidelines will substantially improve the overall quality and uniformity of ROH analyses.
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Affiliation(s)
- R Meyermans
- Department of Biosystems, Livestock Genetics, KU Leuven, Kasteelpark Arenberg 30 - Box 2472, 3001, Leuven, Belgium
| | - W Gorssen
- Department of Biosystems, Livestock Genetics, KU Leuven, Kasteelpark Arenberg 30 - Box 2472, 3001, Leuven, Belgium
| | - N Buys
- Department of Biosystems, Livestock Genetics, KU Leuven, Kasteelpark Arenberg 30 - Box 2472, 3001, Leuven, Belgium
| | - S Janssens
- Department of Biosystems, Livestock Genetics, KU Leuven, Kasteelpark Arenberg 30 - Box 2472, 3001, Leuven, Belgium.
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