Implementing genomic selection in the IMB: challenges and opportunities
Single-step genomic best linear unbiased predictor (ssGBLUP) is a method for jointly estimating breeding values (BV) for genotyped and non-genotyped animals. Genomic information in the Italian Mediterranean Buffalo (IMB) is now available. Its inclusion in the genetic evaluation system could increas...
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Universidad del Zulia
2023-11-01
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| Online Access: | https://www.produccioncientificaluz.org/index.php/cientifica/article/view/43294 |
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| author | Stefano Biffani Mayra Gómez Roberta Cimmino Dario Rossi Gianluigi Zullo Riccardo Negrini Alberto Cesarani Giuseppe Campanile Gianluca Neglia |
| author_facet | Stefano Biffani Mayra Gómez Roberta Cimmino Dario Rossi Gianluigi Zullo Riccardo Negrini Alberto Cesarani Giuseppe Campanile Gianluca Neglia |
| author_sort | Stefano Biffani |
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Single-step genomic best linear unbiased predictor (ssGBLUP) is a method for jointly estimating breeding values (BV) for genotyped and non-genotyped animals. Genomic information in the Italian Mediterranean Buffalo (IMB) is now available. Its inclusion in the genetic evaluation system could increase both the accuracy and genetic progress of the traits of interest of the breed. The study aimed to test the feasibility of ssGBLUP and show the first results of implementing a genomic evaluation for production and type traits in the IMB. Phenotypic information on production (270-day milk, mozzarella yield (MY), protein and fat kg and %, respectively) and morphology: feet and legs (FL) and mammary system (MS) were used for this study. Production records included 743,904 lactations from 276,451 buffalo cows born from 1984 to 2019. Morphological traits were from 91,966 buffalo cows from 2004 to 2022. Regarding the genotypes, 2,017 buffalo cows and 133 bulls were used. Data were analyzed fitting two multi-trait animal models, a 6-trait model for production data and a 2-trait model for morphology data. According to the relationship matrix used, two models were fitted: (i) the BLUP with the numerator relationship matrix (A) and (ii) the ssGBLUP where A and the genomic relationship matrix (G) are blended into H. BVs were estimated with BLUP and ssGBLUP models. The cutoff year used to create the partial data set was 2012. The correlation, accuracy, dispersion, and bias statistics were calculated (LR method). Both bulls (N=49) and cows (N=1288) were used for validations. On average, the correlation between EBVs from partial and whole datasets estimated with BLUP and ssGBLUP increased from 6 to 49% and from 14 to 17% for production and type traits, respectively. Among the traits analyzed, the most affected by the change were protein/fat content, MY, and AM. The accuracy increase for these traits was above 20% when using the ssGBLUP. All LR statistics also improved for non-genotyped females. These results showed that implementing ssGBLUP in the breeding program can generate more accurate predictions for essential traits in dairy IMB than traditional BLUP.
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| format | Article |
| id | doaj-art-1ad39d4e1e8c455d98ce3bb0970637b4 |
| institution | Kabale University |
| issn | 0798-2259 2521-9715 |
| language | English |
| publishDate | 2023-11-01 |
| publisher | Universidad del Zulia |
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| spelling | doaj-art-1ad39d4e1e8c455d98ce3bb0970637b42025-01-17T15:36:41ZengUniversidad del ZuliaRevista Científica0798-22592521-97152023-11-0133Suplemento10.52973/rcfcv-wbc013Implementing genomic selection in the IMB: challenges and opportunitiesStefano Biffani0Mayra Gómez 1Roberta Cimmino2Dario Rossi 3Gianluigi Zullo4Riccardo Negrini5Alberto Cesarani 6Giuseppe Campanile7Gianluca Neglia8National Research Council (CNR), Institute of Agricultural Biology and Biotechnology (IBBA), Milan, ItalyItalian National Association of Buffalo Breeders, Caserta, Italy.Italian National Association of Buffalo Breeders, Caserta, Italy.Italian National Association of Buffalo Breeders, Caserta, Italy.Italian National Association of Buffalo Breeders, Caserta, Italy.Italian National Breeders Association (AIA), Rome, ItalyDipartimento di Agraria, University of Sassari, Sassari, ItalyDepartment of Veterinary Medicine and Animal Production Federico II University, Naples, ItalyDepartment of Veterinary Medicine and Animal Production Federico II University, Naples, Italy Single-step genomic best linear unbiased predictor (ssGBLUP) is a method for jointly estimating breeding values (BV) for genotyped and non-genotyped animals. Genomic information in the Italian Mediterranean Buffalo (IMB) is now available. Its inclusion in the genetic evaluation system could increase both the accuracy and genetic progress of the traits of interest of the breed. The study aimed to test the feasibility of ssGBLUP and show the first results of implementing a genomic evaluation for production and type traits in the IMB. Phenotypic information on production (270-day milk, mozzarella yield (MY), protein and fat kg and %, respectively) and morphology: feet and legs (FL) and mammary system (MS) were used for this study. Production records included 743,904 lactations from 276,451 buffalo cows born from 1984 to 2019. Morphological traits were from 91,966 buffalo cows from 2004 to 2022. Regarding the genotypes, 2,017 buffalo cows and 133 bulls were used. Data were analyzed fitting two multi-trait animal models, a 6-trait model for production data and a 2-trait model for morphology data. According to the relationship matrix used, two models were fitted: (i) the BLUP with the numerator relationship matrix (A) and (ii) the ssGBLUP where A and the genomic relationship matrix (G) are blended into H. BVs were estimated with BLUP and ssGBLUP models. The cutoff year used to create the partial data set was 2012. The correlation, accuracy, dispersion, and bias statistics were calculated (LR method). Both bulls (N=49) and cows (N=1288) were used for validations. On average, the correlation between EBVs from partial and whole datasets estimated with BLUP and ssGBLUP increased from 6 to 49% and from 14 to 17% for production and type traits, respectively. Among the traits analyzed, the most affected by the change were protein/fat content, MY, and AM. The accuracy increase for these traits was above 20% when using the ssGBLUP. All LR statistics also improved for non-genotyped females. These results showed that implementing ssGBLUP in the breeding program can generate more accurate predictions for essential traits in dairy IMB than traditional BLUP. https://www.produccioncientificaluz.org/index.php/cientifica/article/view/43294genomicsItalian Mediterranean buffaloselection |
| spellingShingle | Stefano Biffani Mayra Gómez Roberta Cimmino Dario Rossi Gianluigi Zullo Riccardo Negrini Alberto Cesarani Giuseppe Campanile Gianluca Neglia Implementing genomic selection in the IMB: challenges and opportunities Revista Científica genomics Italian Mediterranean buffalo selection |
| title | Implementing genomic selection in the IMB: challenges and opportunities |
| title_full | Implementing genomic selection in the IMB: challenges and opportunities |
| title_fullStr | Implementing genomic selection in the IMB: challenges and opportunities |
| title_full_unstemmed | Implementing genomic selection in the IMB: challenges and opportunities |
| title_short | Implementing genomic selection in the IMB: challenges and opportunities |
| title_sort | implementing genomic selection in the imb challenges and opportunities |
| topic | genomics Italian Mediterranean buffalo selection |
| url | https://www.produccioncientificaluz.org/index.php/cientifica/article/view/43294 |
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