Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions
ABSTRACT: Accurate genomic predictions of breeding values for traits included in the selection indexes are paramount for optimizing genetic progress in populations under selection. The size of the reference populations is a major factor influencing the accuracy of genomic predictions, which is even...
Saved in:
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-01-01
|
| Series: | Journal of Dairy Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0022030224012451 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1846107932073132032 |
|---|---|
| author | Rui Shi Luiz F. Brito Shanshan Li Liyun Han Gang Guo Wan Wen Qingxia Yan Shaohu Chen Yachun Wang |
| author_facet | Rui Shi Luiz F. Brito Shanshan Li Liyun Han Gang Guo Wan Wen Qingxia Yan Shaohu Chen Yachun Wang |
| author_sort | Rui Shi |
| collection | DOAJ |
| description | ABSTRACT: Accurate genomic predictions of breeding values for traits included in the selection indexes are paramount for optimizing genetic progress in populations under selection. The size of the reference populations is a major factor influencing the accuracy of genomic predictions, which is even more important for lowly heritable traits, such as fertility and reproduction indicators. Combining data from different geographical regions or countries can be beneficial for genomic prediction of these lowly heritable traits. Therefore, the objectives of this study were to (1) evaluate the benefits of performing across-regional genomic evaluations for reproduction traits in Chinese Holstein cattle and (2) assess the feasibility of validating genomic predictions across environments based on reaction norm models (RNM) and the linear regression (LR) method after accounting for genotype-by-environment interactions. Phenotypic records from 194,574 cows collected across 47 farms located in 2 regions of China were used for this study. The reference and validation populations were defined based on birth year for applying the LR validation method. The traits evaluated included: interval from first to last insemination (IFL), conception rate at the first insemination (CR_f), and number of inseminations (NS) recorded in heifers and first-parity cows. The results indicated that combining data from different regions resulted in greater genomic prediction accuracies compared with using data from single regions, with increases ranging from 2.74% to 93.81%. This improvement was particularly notable for the region with the least amount of available data, where the increases ranged from 26.49% to 93.81%. Furthermore, the predictive abilities could be validated for all studied traits based on the LR method across different environments when fitting RNM. The prediction accuracies and bias of genomic breeding values based on RNM were better than regular single-trait animal models in extreme climatic conditions for IFL and NS, whereas limited increases in predictive abilities were observed for CR_f. Across-regional genomic prediction by RNM can account for genotype-by-environment interactions, potentially increase the accuracy of genomic prediction, and predict the performances of individuals in the environments with limited phenotypic data available. |
| format | Article |
| id | doaj-art-640cadba51f94c9f97a9261aa83bdc93 |
| institution | Kabale University |
| issn | 0022-0302 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Dairy Science |
| spelling | doaj-art-640cadba51f94c9f97a9261aa83bdc932024-12-26T08:52:18ZengElsevierJournal of Dairy Science0022-03022025-01-011081707725Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditionsRui Shi0Luiz F. Brito1Shanshan Li2Liyun Han3Gang Guo4Wan Wen5Qingxia Yan6Shaohu Chen7Yachun Wang8State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Animal Breeding and Genomics Group, Wageningen University & Research, 6700 AH Wageningen, the NetherlandsDepartment of Animal Sciences, Purdue University, West Lafayette, IN 47907State Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, ChinaNingxia State Farm Dairy Co. Ltd., Yinchuan 750021, ChinaBeijing Sunlon Livestock Development Co. Ltd., Beijing 100176, ChinaNingxia Animal Husbandry and Veterinary Station, Yinchuan 750105, ChinaDairy Association of China, Beijing 100193, ChinaDairy Association of China, Beijing 100193, ChinaState Key Laboratory of Animal Biotech Breeding, Key Laboratory of Animal Genetics, Breeding and Reproduction, MARA, National Engineering Laboratory of Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Corresponding authorABSTRACT: Accurate genomic predictions of breeding values for traits included in the selection indexes are paramount for optimizing genetic progress in populations under selection. The size of the reference populations is a major factor influencing the accuracy of genomic predictions, which is even more important for lowly heritable traits, such as fertility and reproduction indicators. Combining data from different geographical regions or countries can be beneficial for genomic prediction of these lowly heritable traits. Therefore, the objectives of this study were to (1) evaluate the benefits of performing across-regional genomic evaluations for reproduction traits in Chinese Holstein cattle and (2) assess the feasibility of validating genomic predictions across environments based on reaction norm models (RNM) and the linear regression (LR) method after accounting for genotype-by-environment interactions. Phenotypic records from 194,574 cows collected across 47 farms located in 2 regions of China were used for this study. The reference and validation populations were defined based on birth year for applying the LR validation method. The traits evaluated included: interval from first to last insemination (IFL), conception rate at the first insemination (CR_f), and number of inseminations (NS) recorded in heifers and first-parity cows. The results indicated that combining data from different regions resulted in greater genomic prediction accuracies compared with using data from single regions, with increases ranging from 2.74% to 93.81%. This improvement was particularly notable for the region with the least amount of available data, where the increases ranged from 26.49% to 93.81%. Furthermore, the predictive abilities could be validated for all studied traits based on the LR method across different environments when fitting RNM. The prediction accuracies and bias of genomic breeding values based on RNM were better than regular single-trait animal models in extreme climatic conditions for IFL and NS, whereas limited increases in predictive abilities were observed for CR_f. Across-regional genomic prediction by RNM can account for genotype-by-environment interactions, potentially increase the accuracy of genomic prediction, and predict the performances of individuals in the environments with limited phenotypic data available.http://www.sciencedirect.com/science/article/pii/S0022030224012451genomic predictionreaction normgenotype-by-environment interactionreproductiondairy cows |
| spellingShingle | Rui Shi Luiz F. Brito Shanshan Li Liyun Han Gang Guo Wan Wen Qingxia Yan Shaohu Chen Yachun Wang Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions Journal of Dairy Science genomic prediction reaction norm genotype-by-environment interaction reproduction dairy cows |
| title | Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions |
| title_full | Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions |
| title_fullStr | Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions |
| title_full_unstemmed | Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions |
| title_short | Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions |
| title_sort | genomic prediction and validation strategies for reproductive traits in holstein cattle across different chinese regions and climatic conditions |
| topic | genomic prediction reaction norm genotype-by-environment interaction reproduction dairy cows |
| url | http://www.sciencedirect.com/science/article/pii/S0022030224012451 |
| work_keys_str_mv | AT ruishi genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT luizfbrito genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT shanshanli genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT liyunhan genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT gangguo genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT wanwen genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT qingxiayan genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT shaohuchen genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions AT yachunwang genomicpredictionandvalidationstrategiesforreproductivetraitsinholsteincattleacrossdifferentchineseregionsandclimaticconditions |