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Davoudi P, Do DN, Rathgeber B, Colombo S, Sargolzaei M, Plastow G, Wang Z, Miar Y. Identification of consensus homozygous regions and their associations with growth and feed efficiency traits in American mink. BMC Genom Data 2024; 25:68. [PMID: 38982354 PMCID: PMC11234557 DOI: 10.1186/s12863-024-01252-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Accepted: 07/01/2024] [Indexed: 07/11/2024] Open
Abstract
The recent chromosome-based genome assembly and the newly developed 70K single nucleotide polymorphism (SNP) array for American mink (Neogale vison) facilitate the identification of genetic variants underlying complex traits in this species. The objective of this study was to evaluate the association between consensus runs of homozygosity (ROH) with growth and feed efficiency traits in American mink. A subsample of two mink populations (n = 2,986) were genotyped using the Affymetrix Mink 70K SNP array. The identified ROH segments were included simultaneously, concatenated into consensus regions, and the ROH-based association studies were carried out with linear mixed models considering a genomic relationship matrix for 11 growth and feed efficiency traits implemented in ASReml-R version 4. In total, 298,313 ROH were identified across all individuals, with an average length and coverage of 4.16 Mb and 414.8 Mb, respectively. After merging ROH segments, 196 consensus ROH regions were detected and used for genome-wide ROH-based association analysis. Thirteen consensus ROH regions were significantly (P < 0.01) associated with growth and feed efficiency traits. Several candidate genes within the significant regions are known for their involvement in growth and body size development, including MEF2A, ADAMTS17, POU3F2, and TYRO3. In addition, we found ten consensus ROH regions, defined as ROH islands, with frequencies over 80% of the population. These islands harbored 12 annotated genes, some of which were related to immune system processes such as DTX3L, PARP9, PARP14, CD86, and HCLS1. This is the first study to explore the associations between homozygous regions with growth and feed efficiency traits in American mink. Our findings shed the light on the effects of homozygosity in the mink genome on growth and feed efficiency traits, that can be utilized in developing a sustainable breeding program for mink.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
- Select Sires Inc, Plain City, OH, USA
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, Canada
| | - Zhiquan Wang
- Department of Agricultural, Food and Nutritional Science, Livestock Gentec, University of Alberta, Edmonton, AB, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
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Davoudi P, Do DN, Colombo S, Rathgeber B, Sargolzaei M, Plastow G, Wang Z, Hu G, Valipour S, Miar Y. Genome-wide association studies for economically important traits in mink using copy number variation. Sci Rep 2024; 14:24. [PMID: 38167844 PMCID: PMC10762091 DOI: 10.1038/s41598-023-50497-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 12/20/2023] [Indexed: 01/05/2024] Open
Abstract
Copy number variations (CNVs) are structural variants consisting of duplications and deletions of DNA segments, which are known to play important roles in the genetics of complex traits in livestock species. However, CNV-based genome-wide association studies (GWAS) have remained unexplored in American mink. Therefore, the purpose of the current study was to investigate the association between CNVs and complex traits in American mink. A CNV-based GWAS was performed with the ParseCNV2 software program using deregressed estimated breeding values of 27 traits as pseudophenotypes, categorized into traits of growth and feed efficiency, reproduction, pelt quality, and Aleutian disease tests. The study identified a total of 10,137 CNVs (6968 duplications and 3169 deletions) using the Affymetrix Mink 70K single nucleotide polymorphism (SNP) array in 2986 American mink. The association analyses identified 250 CNV regions (CNVRs) associated with at least one of the studied traits. These CNVRs overlapped with a total of 320 potential candidate genes, and among them, several genes have been known to be related to the traits such as ARID1B, APPL1, TOX, and GPC5 (growth and feed efficiency traits); GRM1, RNASE10, WNT3, WNT3A, and WNT9B (reproduction traits); MYO10, and LIMS1 (pelt quality traits); and IFNGR2, APEX1, UBE3A, and STX11 (Aleutian disease tests). Overall, the results of the study provide potential candidate genes that may regulate economically important traits and therefore may be used as genetic markers in mink genomic breeding programs.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada
- Select Sires Inc., Plain City, OH, USA
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Shafagh Valipour
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada.
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Hengwei Y, Raza SHA, Wang S, Khan R, Ayari-Akkari A, El Moneim Ahmed DA, Ahmad I, Shaoib M, Abd El-Aziz AH, Rahman SU, Jahejo AR, Zan L. The growth curve determination and economic trait correlation for Qinchuan bull population. Anim Biotechnol 2023; 34:2649-2656. [PMID: 35980325 DOI: 10.1080/10495398.2022.2111309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/01/2022]
Abstract
Carcass weight, as a measure of meat yield, and body measurements are directly correlated traits in livestock. However, longitudinally collected phenotype records of local breeds are not comprehensive. The research was performed on Qinchuan bull population to understand their growth and development, and data from Qinchuan bull that was weighed and measured at birth, 6, 12, 18, and 24 months of age was analyzed. Furthermore, Logistic, Brody, Gompertz, and Bertallanffy were used to fit the growth curves for weight and body size traits. The results showed that the four curve models have good fitting degrees for the weight and body size (R2 > 0.99), and the Bertallanffy model exhibited a good fit to the measured data of body weight, and the model estimated the inflection point of body weight as (5.43 months of age, 122.01 kg). Particularly, the limited mature body weight can reach 557.8 kg by the Brody model. Body weight was significantly positively correlated with body height, hip height, body length, chest circumference, abdominal girth, and calf girth (p < 0.0001), and the correlation between body weight and body length was the highest (r = 0.975). The regression equation predicting body weight was Y = -275.691 + 3.28 X3 + 1.311 X4 - 0.397 X5.
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Affiliation(s)
- Yu Hengwei
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | | | - Sihu Wang
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
| | - Rajwali Khan
- Department of Livestock Management, Breeding and Genetic, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Amel Ayari-Akkari
- Biology Department, College of Sciences, King Khaled University, Abha, Saudi Arabia
- Laboratory of Diversity, Management and Conservation of Biological Systems, Faculty of Sciences of Tunis, University of Tunis El Manar, Tunis, Tunisia
| | | | - Ijaz Ahmad
- Department of Livestock Management, Breeding and Genetic, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Muhammad Shaoib
- College of Veterinary Science, The University of Agriculture Peshawar, Peshawar, Pakistan
| | - Ayman H Abd El-Aziz
- Department of Animal and Poultry Production, Faculty of Agriculture, Damanhour University, Damanhour, Egypt
| | - Siddiq Ur Rahman
- Department of Computer science and Bioinformatics, Khushal Khan Khattak University, Karak, Pakistan
| | - Ali Raza Jahejo
- College of Veterinary Medicine, Shanxi Agricultural University, Jinzhong, China
| | - Linsen Zan
- College of Animal Science and Technology, Northwest A&F University, Yangling, China
- National Beef Cattle Improvement Center, Yangling, China
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Hu G, Do DN, Davoudi P, Manafiazar G, Kelvin AA, Plastow G, Wang Z, Sargolzaei M, Miar Y. Genetic and phenotypic correlations between Aleutian disease tests with body weight, growth, and feed efficiency traits in mink. J Anim Sci 2022; 100:skac346. [PMID: 36250683 PMCID: PMC9733502 DOI: 10.1093/jas/skac346] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 10/15/2022] [Indexed: 12/15/2022] Open
Abstract
The ineffectiveness of vaccination, medicine, and culling strategy leads mink farmers to control Aleutian disease (AD) by selecting AD-resilient mink based on AD tests. However, the genetic background of AD tests and their correlations with economically important or AD-resilient traits are limited. This study estimated the genetic and phenotypic correlations between four AD tests and seven body weight (BW) traits, six growth parameters from the Richards growth model, and eight feed-related traits. Univariate models were used to test the significance (P < 0.05) of fixed effects (sex, color type, AD test year, birth year, and row-by-year), random effects (additive genetic, maternal genetic, and permanent environmental), and a covariate of age using ASReml 4.1. Likewise, pairwise bivariate analyses were conducted to estimate the phenotypic and genetic correlations among the studied traits. Both antigen- and virus capsid protein-based enzyme-linked immunosorbent assay tests (ELISA-G and ELISA-P) showed significant (P < 0.05) moderate positive genetic correlations (±SE) with maturation rate (from 0.36 ± 0.18 to 0.38 ± 0.19). ELISA-G showed a significant negative genetic correlation (±SE) with average daily gain (ADG, -0.37 ± 0.16). ELISA-P showed a significant positive moderate genetic correlation (±SE) with off-feed days (DOF, 0.42 ± 0.17). These findings indicated that selection for low ELISA scores would reduce the maturation rate, increase ADG (by ELISA-G), and minimize DOF (by ELISA-P). The iodine agglutination test (IAT) showed significant genetic correlations with DOF (0.73 ± 0.16), BW at 16 weeks of age (BW16, 0.45 ± 0.23), and BW at harvest (HW, -0.47 ± 0.20), indicating that selection for lower IAT scores would lead to lower DOF and BW16, and higher HW. These estimated genetic correlations suggested that the selection of AD tests would not cause adverse effects on the growth, feed efficiency, and feed intake of mink. The estimates from this study might strengthen the previous finding that ELISA-G could be applied as a reliable and practical indicator trait in the genetic selection of AD-resilient mink in AD-positive farms.
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Affiliation(s)
- Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N 5E3, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N 5E3, Canada
| | - Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N 5E3, Canada
| | - Ghader Manafiazar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N 5E3, Canada
| | - Alyson A Kelvin
- Vaccine and Infectious Disease Organization (VIDO), University of Saskatchewan, Saskatoon, SK, S7N 5E3, Canada
| | - Graham Plastow
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Zhiquan Wang
- Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB T6G 2P5, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, N1G 2W1, Canada
- Select Sires Inc., Plain City, OH 43064, USA
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, B2N 5E3, Canada
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Do DN, Hu G, Davoudi P, Shirzadifar A, Manafiazar G, Miar Y. Applying Machine Learning Algorithms for the Classification of Mink Infected with Aleutian Disease Using Different Data Sources. Animals (Basel) 2022; 12:ani12182386. [PMID: 36139246 PMCID: PMC9495069 DOI: 10.3390/ani12182386] [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: 06/13/2022] [Revised: 09/08/2022] [Accepted: 09/10/2022] [Indexed: 11/16/2022] Open
Abstract
Simple Summary Aleutian disease (AD) is a major infectious disease found in mink farms, and it causes financial losses to the mink industry. Controlling AD often requires a counterimmunoelectrophoresis (CIEP) method, which is relatively expensive for mink farmers. Therefore, predicting AD infected mink without using CIEP records will be important for controlling AD in mink farms. In the current study, we applied nine machine learning algorithms to classify AD-infected mink. We indicated that the random forest could be used to classify AD-infected mink (accuracy of 0.962) accurately. This result could be used for implementing machine learning in controlling AD in the mink farms. Abstract American mink (Neogale vison) is one of the major sources of fur for the fur industries worldwide, whereas Aleutian disease (AD) is causing severe financial losses to the mink industry. A counterimmunoelectrophoresis (CIEP) method is commonly employed in a test-and-remove strategy and has been considered a gold standard for AD tests. Although machine learning is widely used in livestock species, little has been implemented in the mink industry. Therefore, predicting AD without using CIEP records will be important for controlling AD in mink farms. This research presented the assessments of the CIEP classification using machine learning algorithms. The Aleutian disease was tested on 1157 individuals using CIEP in an AD-positive mink farm (Nova Scotia, Canada). The comprehensive data collection of 33 different features was used for the classification of AD-infected mink. The specificity, sensitivity, accuracy, and F1 measure of nine machine learning algorithms were evaluated for the classification of AD-infected mink. The nine models were artificial neural networks, decision tree, extreme gradient boosting, gradient boosting method, K-nearest neighbors, linear discriminant analysis, support vector machines, naive bayes, and random forest. Among the 33 tested features, the Aleutian mink disease virus capsid protein-based enzyme-linked immunosorbent assay was found to be the most important feature for classifying AD-infected mink. Overall, random forest was the best-performing algorithm for the current dataset with a mean sensitivity of 0.938 ± 0.003, specificity of 0.986 ± 0.005, accuracy of 0.962 ± 0.002, and F1 value of 0.961 ± 0.088, and across tenfold of the cross-validation. Our work demonstrated that it is possible to use the random forest algorithm to classify AD-infected mink accurately. It is recommended that further model tests in other farms need to be performed and the genomic information needs to be used to optimize the model for implementing machine learning methods for AD detection.
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Davoudi P, Do DN, Colombo SM, Rathgeber B, Hu G, Sargolzaei M, Wang Z, Plastow G, Miar Y. Genetic and phenotypic parameters for feed efficiency and component traits in American mink. J Anim Sci 2022; 100:6633851. [PMID: 35801647 DOI: 10.1093/jas/skac216] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/08/2022] [Indexed: 11/15/2022] Open
Abstract
Feed cost is the largest expense of mink production systems, and therefore, improvement of feed efficiency (FE) through selection for high feed efficient mink is a practical way to increase the mink industry's sustainability. In this study, we estimated the heritability, phenotypic and genetic correlations for different FE measures and component traits, including harvest weight (HW), harvest length (HL), final body length (FBL), final body weight (FBW), average daily gain (ADG), daily feed intake (DFI), feed conversion ratio (FCR), residual feed intake (RFI), residual gain (RG), residual intake and gain (RIG), and Kleiber ratio (KR), using data from 2,288 American mink (for HW and HL), and 1,038-1,906 American mink (for other traits). Significance (P < 0.05) of fixed effects (farm, sex, and color-type), a covariate (age of animal), and random effects (additive genetic, maternal, and common litter) were evaluated through univariate models implemented in ASReml-R version 4. Genetic parameters were estimated via fitting a set of bivariate models using ASReml-R version 4. Estimates of heritabilities (±SE) were 0.28±0.06, 0.23±0.06, 0.28±0.10, 0.27±0.11, 0.25±0.09, 0.26±0.09, 0.20±0.09, 0.23±0.09, 0.21±0.10, 0.25±0.10, and 0.26±0.10 for HW, HL, FBL, FBW, ADG, DFI, FCR, RFI, RG, RIG, and KR, respectively. RIG had favorable genetic correlations with DFI (-0.62±0.24) and ADG (0.58±0.21), and non-significant (P > 0.05) genetic correlations with FBW (0.14±0.31) and FBL (-0.15±0.31). These results revealed that RIG might be superior trait as it guarantees reduced feed intake with faster-growing mink yet with no negative impacts on body weight and length. In addition, the strong positive genetic correlations (±SE) between KR with component traits (0.88±0.11 with FBW; 0.68±0.17 with FBL; and 0.97±0.02 with ADG) suggested KR as an applicable indirect measure of FE for improvement of component traits as it did not require the individual feed intake to be measured. Overall, our results confirmed the possibility of including FE traits in mink breeding programs to effectively select feed-efficient animals.
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Affiliation(s)
- Pourya Davoudi
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Duy Ngoc Do
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Stefanie M Colombo
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Bruce Rathgeber
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Guoyu Hu
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
| | - Mehdi Sargolzaei
- Department of Pathobiology, University of Guelph, Guelph, ON, Canada.,Select Sires Inc., Plain City, OH, United States
| | - Zhiquan Wang
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Graham Plastow
- Livestock Gentec, Department of Agricultural, Food and Nutritional Science, University of Alberta, Edmonton, AB, Canada
| | - Younes Miar
- Department of Animal Science and Aquaculture, Dalhousie University, Truro, NS, Canada
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