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Cardinali I, Giontella A, Tommasi A, Silvestrelli M, Lancioni H. Unlocking Horse Y Chromosome Diversity. Genes (Basel) 2022; 13:genes13122272. [PMID: 36553539 PMCID: PMC9777570 DOI: 10.3390/genes13122272] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2022] [Revised: 11/30/2022] [Accepted: 11/30/2022] [Indexed: 12/11/2022] Open
Abstract
The present equine genetic variation mirrors the deep influence of intensive breeding programs during the last 200 years. Here, we provide a comprehensive current state of knowledge on the trends and prospects on the variation in the equine male-specific region of the Y chromosome (MSY), which was assembled for the first time in 2018. In comparison with the other 12 mammalian species, horses are now the most represented, with 56 documented MSY genes. However, in contrast to the high variability in mitochondrial DNA observed in many horse breeds from different geographic areas, modern horse populations demonstrate extremely low genetic Y-chromosome diversity. The selective pressures employed by breeders using pedigree data (which are not always error-free) as a predictive tool represent the main cause of this lack of variation in the Y-chromosome. Nevertheless, the detailed phylogenies obtained by recent fine-scaled Y-chromosomal genotyping in many horse breeds worldwide have contributed to addressing the genealogical, forensic, and population questions leading to the reappraisal of the Y-chromosome as a powerful genetic marker to avoid the loss of biodiversity as a result of selective breeding practices, and to better understand the historical development of horse breeds.
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Affiliation(s)
- Irene Cardinali
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123 Perugia, Italy
- Correspondence: (I.C.); (A.G.)
| | - Andrea Giontella
- Department of Veterinary Medicine, University of Perugia, 06126 Perugia, Italy
- Correspondence: (I.C.); (A.G.)
| | - Anna Tommasi
- Department of Biology and Biotechnology “L. Spallanzani”, University of Pavia, 27100 Pavia, Italy
| | | | - Hovirag Lancioni
- Department of Chemistry, Biology and Biotechnology, University of Perugia, 06123 Perugia, Italy
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Spasskaya N, Voronkova V, Letarov A, Ermilina Y, Nikolaeva E, Konorov E, Stolpovsky Y, Naidenko S. Features of reproduction in an isolated island population of the feral horses of the Lake Manych-Gudilo (Rostov Region, Russia). Appl Anim Behav Sci 2022. [DOI: 10.1016/j.applanim.2022.105712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Kalashnikov V, Khrabrova L, Blohina N, Zaitcev A, Kalashnikova T. Dynamics of the Inbreeding Coefficient and Homozygosity in Thoroughbred Horses in Russia. Animals (Basel) 2020; 10:ani10071217. [PMID: 32708952 PMCID: PMC7401591 DOI: 10.3390/ani10071217] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Revised: 07/09/2020] [Accepted: 07/14/2020] [Indexed: 11/16/2022] Open
Abstract
The Thoroughbred (TB) horse has hugely impacted the development of horse breeding around the world. This breed has unique genetic qualities due to having had a closed studbook for approximately 300 years. In Russia, TBs have been bred since the second half of the 18th century. Here, we analyzed the genetic diversity and the inbreeding level in TB horses (n = 9680) for the period from 1990 to 2018 using polymorphisms of 17 microsatellite loci. We found that the genetic structure of the TB breed in Russia is represented by 100 alleles of panel STR (short tandem repeat) loci and has been stable for the past three decades. The conducted monitoring revealed a slight increase in the Wright's inbreeding coefficient in all age and sex groups of TB horses (stallions, broodmares, and foals) from 0.68% to 0.90%, which was followed by a decrease in the degree of heterozygosity, Ho, from 68.5% to 67.6%. The Spearman's rank correlation coefficient between the level of inbreeding and the degree of homozygosity was estimated (r = 0.022; p > 0.05). The obtained data on the DNA genotypes of horses of different breeds provide a unique base for the evaluation of genetic variability and the control of genetic variability of horses in selection programs.
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Solé M, Ablondi M, Binzer-Panchal A, Velie BD, Hollfelder N, Buys N, Ducro BJ, François L, Janssens S, Schurink A, Viklund Å, Eriksson S, Isaksson A, Kultima H, Mikko S, Lindgren G. Inter- and intra-breed genome-wide copy number diversity in a large cohort of European equine breeds. BMC Genomics 2019; 20:759. [PMID: 31640551 PMCID: PMC6805398 DOI: 10.1186/s12864-019-6141-z] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 09/25/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Copy Number Variation (CNV) is a common form of genetic variation underlying animal evolution and phenotypic diversity across a wide range of species. In the mammalian genome, high frequency of CNV differentiation between breeds may be candidates for population-specific selection. However, CNV differentiation, selection and its population genetics have been poorly explored in horses. RESULTS We investigated the patterns, population variation and gene annotation of CNV using the Axiom® Equine Genotyping Array (670,796 SNPs) from a large cohort of individuals (N = 1755) belonging to eight European horse breeds, varying from draught horses to several warmblood populations. After quality control, 152,640 SNP CNVs (individual markers), 18,800 segment CNVs (consecutive SNP CNVs of same gain/loss state or both) and 939 CNV regions (CNVRs; overlapping segment CNVs by at least 1 bp) compared to the average signal of the reference (Belgian draught horse) were identified. Our analyses showed that Equus caballus chromosome 12 (ECA12) was the most enriched in segment CNV gains and losses (~ 3% average proportion of the genome covered), but the highest number of segment CNVs were detected on ECA1 and ECA20 (regardless of size). The Friesian horses showed private SNP CNV gains (> 20% of the samples) on ECA1 and Exmoor ponies displayed private SNP CNV losses on ECA25 (> 20% of the samples). The Warmblood cluster showed private SNP CNV gains located in ECA9 and Draught cluster showed private SNP CNV losses located in ECA7. The length of the CNVRs ranged from 1 kb to 21.3 Mb. A total of 10,612 genes were annotated within the CNVRs. The PANTHER annotation of these genes showed significantly under- and overrepresented gene ontology biological terms related to cellular processes and immunity (Bonferroni P-value < 0.05). We identified 80 CNVRs overlapping with known QTL for fertility, coat colour, conformation and temperament. We also report 67 novel CNVRs. CONCLUSIONS This work revealed that CNV patterns, in the genome of some European horse breeds, occurred in specific genomic regions. The results provide support to the hypothesis that high frequency private CNVs residing in genes may potentially be responsible for the diverse phenotypes seen between horse breeds.
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Affiliation(s)
- Marina Solé
- Department of Animal Breeding & Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.
| | - Michela Ablondi
- Department of Veterinary Science, Università di Parma, Parma, Italy
| | - Amrei Binzer-Panchal
- Department of Medical Sciences, Array and Analysis Facility, Uppsala University, Uppsala, Sweden
| | - Brandon D Velie
- Faculty of Life and Environmental Science, University of Sydney, Sydney, NSW, Australia
| | - Nina Hollfelder
- Department of Medical Sciences, Array and Analysis Facility, Uppsala University, Uppsala, Sweden
| | - Nadine Buys
- Livestock Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Bart J Ducro
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands
| | - Liesbeth François
- Livestock Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Steven Janssens
- Livestock Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
| | - Anouk Schurink
- Animal Breeding and Genomics, Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands.,Centre for Genetic Resources, the Netherlands (CGN), Wageningen University & Research, P.O. Box 338, 6700 AH, Wageningen, the Netherlands
| | - Åsa Viklund
- Department of Animal Breeding & Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Susanne Eriksson
- Department of Animal Breeding & Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Anders Isaksson
- Department of Medical Sciences, Array and Analysis Facility, Uppsala University, Uppsala, Sweden
| | - Hanna Kultima
- Department of Medical Sciences, Array and Analysis Facility, Uppsala University, Uppsala, Sweden
| | - Sofia Mikko
- Department of Animal Breeding & Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden
| | - Gabriella Lindgren
- Department of Animal Breeding & Genetics, Swedish University of Agricultural Sciences, Uppsala, Sweden.,Livestock Genetics, Department of Biosystems, KU Leuven, 3001, Leuven, Belgium
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Khrabrova LA, Blohina NV, Suleymanov OI, Rozhdestvenskaya GА, Pustovoy VF. Assessment of line differentiation in the Thoroughbred horse breed using DNA microsatellite loci. Vavilovskii Zhurnal Genet Selektsii 2019. [DOI: 10.18699/vj19.526] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
Abstract
The Thoroughbred (TB) horse is the best racehorse breed used in the racing industry. This breed has had a closed studbook for about 300 years. In Russia TB horses have been bred since the second half of the XVIII century. The modern Russian Stud Book register of TB horses is partially presented by stallions and broodmares imported from different countries. The genealogical structure of the breed is represented by 17 lines, among which the Northern Dancer line dominates (30.9 %). The study of features of different lines of TB was carried out on 17 loci of DNA microsatellites (VHL20, HTG4, AHT4, HMS7, HTG6, AHT5, HMS6, ASB23, ASB2, HTG10, HTG7, HMS3, HMS2, ASB17, LEX3, HMS1 and CA425) to assess genetic differentiation of the genealogical structure. The results of the DNA typing of 8091 Thoroughbred horses across microsatellite loci show that the gene pool of the domestic population is represented by 100 alleles typical of the breed. A comparative analysis of the genotypes of horses representing different lines indicates that they differ in the number of alleles (85–99), allele frequencies, the level of polymorphism Ae (2.93–3.48) and the degree of the observed heterozygosity Ho (0.653–0.739). The genetic distances between the lines varied in a wide range from 0.014 (Nasrullah – Northern Dancer) to 0.125 (Massine – Teddy). The correspondence to HWE was maintained in most lines, which is confirmed by the negative values of Fis. Cluster analysis demonstrated the correspondence of the obtained dendrogram of Nei’s genetic distances to its genealogical scheme of lines. Genetic differentiation of lines by index Fst varied in a range 0.005–0.073 at the mean value Fst = 0.024. The data indicate genetic differentiation of lines of TB at the STR markers and confirm the effectiveness of the system of linear breeding for the maintenance of interbreed biodiversity.
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Putnová L, Štohl R. Comparing assignment-based approaches to breed identification within a large set of horses. J Appl Genet 2019; 60:187-198. [PMID: 30963515 DOI: 10.1007/s13353-019-00495-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Accepted: 03/25/2019] [Indexed: 10/27/2022]
Abstract
Considering the extensive data sets and statistical techniques, animal breeding embodies a branch of machine learning that has a constantly increasing impact on breeding. In our study, information regarding the potential of machine learning and data mining within a large set of horses and breeds is presented. The individual assignment methods and factors influencing the success rate of the procedure are compared at the Czech population scale. The fixation index values ranged from 0.057 (HMS1) to 0.144 (HTG6), and the overall genetic differentiation amounted to 8.9% among the breeds. The highest genetic divergence (FST = 0.378) was established between the Friesian and Equus przewalskii; the highest degree of gene migration was obtained between the Czech and Bavarian Warmblood (Nm = 14,302); and the overall global heterozygote deficit across the populations was 10.4%. The eight standard methods (Bayesian, frequency, and distance) using GeneClass software and almost all mainstream classification algorithms (Bayes Net, Naive Bayes, IB1, IB5, KStar, JRip, J48, Random Forest, Random Tree, PART, MLP, and SVM) from the WEKA machine learning workbench were compared by utilizing 314,874 real allelic data sets. The Bayesian method (GeneClass, 89.9%) and Bayesian network algorithm (WEKA, 84.8%) outperformed the other techniques. The breed genomic prediction accuracy reached the highest value in the cold-blooded horses. The overall proportion of individuals correctly assigned to a population depended mainly on the breed number and genetic divergence. These statistical tools could be used to assess breed traceability systems, and they exhibit the potential to assist managers in decision-making as regards breeding and registration.
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Affiliation(s)
- Lenka Putnová
- Laboratory of Agrogenomics, Department of Morphology, Physiology and Animal Genetics, Faculty of Agronomy, Mendel University in Brno, Zemědělská 1665/1, 613 00, Brno, Czech Republic.
| | - Radek Štohl
- Department of Control and Instrumentation, Faculty of Electrical Engineering and Communication, Brno University of Technology, Technická 3082/12, 616 00, Brno, Czech Republic
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