Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits
Changes in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure’s reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction t...
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MDPI AG
2022-06-01
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| Series: | Animals |
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| Online Access: | https://www.mdpi.com/2076-2615/12/13/1693 |
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| author | Artem Kabanov Ekaterina Melnikova Sergey Nikitin Maria Somova Oleg Fomenko Valeria Volkova Olga Kostyunina Tatiana Karpushkina Elena Martynova Elena Trebunskikh |
| author_facet | Artem Kabanov Ekaterina Melnikova Sergey Nikitin Maria Somova Oleg Fomenko Valeria Volkova Olga Kostyunina Tatiana Karpushkina Elena Martynova Elena Trebunskikh |
| author_sort | Artem Kabanov |
| collection | DOAJ |
| description | Changes in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure’s reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction traits in pigs. Six reference groups were formed to assess the genomic data quantity impact on the accuracy of predicted values (groups of genotyped animals). The datasets included 62,927 records of meat and fattening productivity (fat thickness over 6–7 ribs (BF1, mm)), muscle depth (MD, mm) and precocity up to 100 kg (age, days) and 16,070 observations of reproductive qualities (the number of all born piglets (TNB) and the number of live-born piglets (NBA), according to the results of the first farrowing). The wssGBLUP method has an advantage over ssGBLUP in terms of estimation reliability. When using a small reference group, the difference in the accuracy of ssGBLUP over BLUP AM is from −1.9 to +7.3 percent points, while for wssGBLUP, the change in accuracy varies from +18.2 to +87.3 percent points. Furthermore, the superiority of the wssGBLUP is also maintained for the largest group of genotyped animals: from +4.7 to +15.9 percent points for ssGBLUP and from +21.1 to +90.5 percent points for wssGBLUP. However, for all analyzed traits, the number of markers explaining 5% of genetic variability varied from 71 to 108, and the number of such SNPs varied depending on the size of the reference group (79–88 for BF1, 72–81 for MD, 71–108 for age). The results of the genetic variation distribution have the greatest similarity between groups of about 1000 and about 1500 individuals. Thus, the size of the reference group of more than 1000 individuals gives more stable results for the estimation based on the wssGBLUP method, while using the reference group of 500 individuals can lead to distorted results of GEBV. |
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| institution | Directory Open Access Journal |
| issn | 2076-2615 |
| language | English |
| last_indexed | 2024-03-09T22:10:25Z |
| publishDate | 2022-06-01 |
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| spelling | doaj.art-7986ec1c67a24648ad29e1758adf4fa62023-11-23T19:33:21ZengMDPI AGAnimals2076-26152022-06-011213169310.3390/ani12131693Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction TraitsArtem Kabanov0Ekaterina Melnikova1Sergey Nikitin2Maria Somova3Oleg Fomenko4Valeria Volkova5Olga Kostyunina6Tatiana Karpushkina7Elena Martynova8Elena Trebunskikh9L.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaAll-Russian Dairy Research Institute, 115093 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaL.K. Ernst Federal Research Center for Animal Husbandry, Dubrovitzy Estate, Podolsk District, 142132 Moscow, RussiaCenter of Life Sciences, Skolkovo Institute of Science and Technology, 143026 Moscow, RussiaLLC “TOPGEN”, Verkhnyaya Khava, 396110 Voronezh, RussiaChanges in the accuracy of the genomic estimates obtained by the ssGBLUP and wssGBLUP methods were evaluated using different reference groups. The weighting procedure’s reasonableness of application Pwas considered to improve the accuracy of genomic predictions for meat, fattening and reproduction traits in pigs. Six reference groups were formed to assess the genomic data quantity impact on the accuracy of predicted values (groups of genotyped animals). The datasets included 62,927 records of meat and fattening productivity (fat thickness over 6–7 ribs (BF1, mm)), muscle depth (MD, mm) and precocity up to 100 kg (age, days) and 16,070 observations of reproductive qualities (the number of all born piglets (TNB) and the number of live-born piglets (NBA), according to the results of the first farrowing). The wssGBLUP method has an advantage over ssGBLUP in terms of estimation reliability. When using a small reference group, the difference in the accuracy of ssGBLUP over BLUP AM is from −1.9 to +7.3 percent points, while for wssGBLUP, the change in accuracy varies from +18.2 to +87.3 percent points. Furthermore, the superiority of the wssGBLUP is also maintained for the largest group of genotyped animals: from +4.7 to +15.9 percent points for ssGBLUP and from +21.1 to +90.5 percent points for wssGBLUP. However, for all analyzed traits, the number of markers explaining 5% of genetic variability varied from 71 to 108, and the number of such SNPs varied depending on the size of the reference group (79–88 for BF1, 72–81 for MD, 71–108 for age). The results of the genetic variation distribution have the greatest similarity between groups of about 1000 and about 1500 individuals. Thus, the size of the reference group of more than 1000 individuals gives more stable results for the estimation based on the wssGBLUP method, while using the reference group of 500 individuals can lead to distorted results of GEBV.https://www.mdpi.com/2076-2615/12/13/1693genomic evaluationsingle-step GBLUPweighted single-step GBLUPpigsSNP effectsestimation reliability |
| spellingShingle | Artem Kabanov Ekaterina Melnikova Sergey Nikitin Maria Somova Oleg Fomenko Valeria Volkova Olga Kostyunina Tatiana Karpushkina Elena Martynova Elena Trebunskikh Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits Animals genomic evaluation single-step GBLUP weighted single-step GBLUP pigs SNP effects estimation reliability |
| title | Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits |
| title_full | Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits |
| title_fullStr | Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits |
| title_full_unstemmed | Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits |
| title_short | Weighted Single-Step Genomic Best Linear Unbiased Prediction Method Application for Assessing Pigs on Meat Productivity and Reproduction Traits |
| title_sort | weighted single step genomic best linear unbiased prediction method application for assessing pigs on meat productivity and reproduction traits |
| topic | genomic evaluation single-step GBLUP weighted single-step GBLUP pigs SNP effects estimation reliability |
| url | https://www.mdpi.com/2076-2615/12/13/1693 |
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