Arielly O Garcia, Ashley A Mikush, John B Cole, Shogo Tsuruta, Ignacy Misztal, Simone E F Guimarães, Daniela Lourenco
{"title":"奶牛产犊容易的遗传背景。","authors":"Arielly O Garcia, Ashley A Mikush, John B Cole, Shogo Tsuruta, Ignacy Misztal, Simone E F Guimarães, Daniela Lourenco","doi":"10.3168/jds.2025-26503","DOIUrl":null,"url":null,"abstract":"<p><p>A common practice in dairy herds is to breed females not selected as replacement heifers to beef bulls. This increases the market value of the surplus calves sold for beef purposes. Some beef breed associations have built selection indices focusing mainly on carcass traits; however, calving ease (CE) is also an important trait, given that crossbreeding with beef bulls can change gestation patterns (e.g., gestation length) or calf conformation (e.g., weight and size), generating a negative effect on the health, and consequently on the production, of the cows. We used linear and threshold animal models to estimate genetic parameters and breeding values for direct and maternal additive effects for CE in beef-on-dairy crosses, considering only the first or the first 3 lactations. We analyzed 231K CE records in the first lactation and 1.2 million in the first 3 lactations from Holstein and Jersey cows inseminated with Angus, Charolais, or Simmental semen. Although CE was scored in 5 categories, we reduced this to a binary trait (1 = easy and 2, 3, 4, 5 = difficult). The average incidence of difficult calving (scores ≥2) was ∼15%. Direct and maternal heritabilities for the linear (threshold) model were 0.01 ± 0.002 (0.01 ± 0.001) and 0.02 ± 0.002 (0.04 ± 0.004), respectively, using the first lactation, and equal to 0.01 ± 0.002 (0.01 ± 0.009) and 0.19 ± 0.002 (0.26 ± 0.006), respectively, considering the first 3 lactations. Maternal heritabilities were always greater than the direct ones. Maternal heritabilities were inflated when we considered more than one lactation, most likely because of a confounding with the maternal permanent environmental effect that could not be estimated. Linear and threshold models provided similar direct EBV rankings, with a correlation of at least 0.86 when considering all different breeds; for maternal effect, it was high for dairy breeds (>0.9) and close to zero in beef breeds. Validation metrics were better for the linear model with only first lactation records. Although with the small direct heritabilities, the results showed that direct genetic variability exists, and that it would be possible to select beef bulls based on their direct EBV for CE in beef-on-dairy systems. One of the challenges in beef-on-dairy analyses is the lack of pedigree depth on the sire side. When this is the case, we suggest using linear models considering only the first lactation to evaluate CE, given that EBV are highly correlated with those obtained by the threshold model but are less biased and converge almost 10 times faster, proving to be more efficient for routine genetic evaluations.</p>","PeriodicalId":354,"journal":{"name":"Journal of Dairy Science","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Genetic background of calving ease in beef-on-dairy.\",\"authors\":\"Arielly O Garcia, Ashley A Mikush, John B Cole, Shogo Tsuruta, Ignacy Misztal, Simone E F Guimarães, Daniela Lourenco\",\"doi\":\"10.3168/jds.2025-26503\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>A common practice in dairy herds is to breed females not selected as replacement heifers to beef bulls. This increases the market value of the surplus calves sold for beef purposes. Some beef breed associations have built selection indices focusing mainly on carcass traits; however, calving ease (CE) is also an important trait, given that crossbreeding with beef bulls can change gestation patterns (e.g., gestation length) or calf conformation (e.g., weight and size), generating a negative effect on the health, and consequently on the production, of the cows. We used linear and threshold animal models to estimate genetic parameters and breeding values for direct and maternal additive effects for CE in beef-on-dairy crosses, considering only the first or the first 3 lactations. We analyzed 231K CE records in the first lactation and 1.2 million in the first 3 lactations from Holstein and Jersey cows inseminated with Angus, Charolais, or Simmental semen. Although CE was scored in 5 categories, we reduced this to a binary trait (1 = easy and 2, 3, 4, 5 = difficult). The average incidence of difficult calving (scores ≥2) was ∼15%. Direct and maternal heritabilities for the linear (threshold) model were 0.01 ± 0.002 (0.01 ± 0.001) and 0.02 ± 0.002 (0.04 ± 0.004), respectively, using the first lactation, and equal to 0.01 ± 0.002 (0.01 ± 0.009) and 0.19 ± 0.002 (0.26 ± 0.006), respectively, considering the first 3 lactations. Maternal heritabilities were always greater than the direct ones. Maternal heritabilities were inflated when we considered more than one lactation, most likely because of a confounding with the maternal permanent environmental effect that could not be estimated. Linear and threshold models provided similar direct EBV rankings, with a correlation of at least 0.86 when considering all different breeds; for maternal effect, it was high for dairy breeds (>0.9) and close to zero in beef breeds. Validation metrics were better for the linear model with only first lactation records. Although with the small direct heritabilities, the results showed that direct genetic variability exists, and that it would be possible to select beef bulls based on their direct EBV for CE in beef-on-dairy systems. One of the challenges in beef-on-dairy analyses is the lack of pedigree depth on the sire side. When this is the case, we suggest using linear models considering only the first lactation to evaluate CE, given that EBV are highly correlated with those obtained by the threshold model but are less biased and converge almost 10 times faster, proving to be more efficient for routine genetic evaluations.</p>\",\"PeriodicalId\":354,\"journal\":{\"name\":\"Journal of Dairy Science\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Dairy Science\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://doi.org/10.3168/jds.2025-26503\",\"RegionNum\":1,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"AGRICULTURE, DAIRY & ANIMAL SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Dairy Science","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.3168/jds.2025-26503","RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURE, DAIRY & ANIMAL SCIENCE","Score":null,"Total":0}
Genetic background of calving ease in beef-on-dairy.
A common practice in dairy herds is to breed females not selected as replacement heifers to beef bulls. This increases the market value of the surplus calves sold for beef purposes. Some beef breed associations have built selection indices focusing mainly on carcass traits; however, calving ease (CE) is also an important trait, given that crossbreeding with beef bulls can change gestation patterns (e.g., gestation length) or calf conformation (e.g., weight and size), generating a negative effect on the health, and consequently on the production, of the cows. We used linear and threshold animal models to estimate genetic parameters and breeding values for direct and maternal additive effects for CE in beef-on-dairy crosses, considering only the first or the first 3 lactations. We analyzed 231K CE records in the first lactation and 1.2 million in the first 3 lactations from Holstein and Jersey cows inseminated with Angus, Charolais, or Simmental semen. Although CE was scored in 5 categories, we reduced this to a binary trait (1 = easy and 2, 3, 4, 5 = difficult). The average incidence of difficult calving (scores ≥2) was ∼15%. Direct and maternal heritabilities for the linear (threshold) model were 0.01 ± 0.002 (0.01 ± 0.001) and 0.02 ± 0.002 (0.04 ± 0.004), respectively, using the first lactation, and equal to 0.01 ± 0.002 (0.01 ± 0.009) and 0.19 ± 0.002 (0.26 ± 0.006), respectively, considering the first 3 lactations. Maternal heritabilities were always greater than the direct ones. Maternal heritabilities were inflated when we considered more than one lactation, most likely because of a confounding with the maternal permanent environmental effect that could not be estimated. Linear and threshold models provided similar direct EBV rankings, with a correlation of at least 0.86 when considering all different breeds; for maternal effect, it was high for dairy breeds (>0.9) and close to zero in beef breeds. Validation metrics were better for the linear model with only first lactation records. Although with the small direct heritabilities, the results showed that direct genetic variability exists, and that it would be possible to select beef bulls based on their direct EBV for CE in beef-on-dairy systems. One of the challenges in beef-on-dairy analyses is the lack of pedigree depth on the sire side. When this is the case, we suggest using linear models considering only the first lactation to evaluate CE, given that EBV are highly correlated with those obtained by the threshold model but are less biased and converge almost 10 times faster, proving to be more efficient for routine genetic evaluations.
期刊介绍:
The official journal of the American Dairy Science Association®, Journal of Dairy Science® (JDS) is the leading peer-reviewed general dairy research journal in the world. JDS readers represent education, industry, and government agencies in more than 70 countries with interests in biochemistry, breeding, economics, engineering, environment, food science, genetics, microbiology, nutrition, pathology, physiology, processing, public health, quality assurance, and sanitation.