scholarly journals Associations between SNPs in the bovine GnRH receptor gene and breeding values for fertility traits in dairy cattle

2010 ◽  
Vol 1 (1) ◽  
pp. 214-214
Author(s):  
K Derecka ◽  
S Ahmad ◽  
TC Hodgman ◽  
N Hastings ◽  
MD Royal ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Receptor Gene ◽  
Gnrh Receptor ◽  
Breeding Values ◽  
Fertility Traits

21 GENETIC APPROACH TO IMPROVE FERTILITY IN CATTLE

2010 ◽  
Vol 22 (1) ◽  
pp. 168
Author(s):  
F. A. Di Croce ◽  
A. M. Saxton ◽  
D. Casanova ◽  
F. N. Schrick
Keyword(s):  
Dairy Cattle ◽  
Pregnancy Rate ◽  
Selection Index ◽  
Genetic Selection ◽  
Calving Interval ◽  
Breeding Values ◽  
Improvement Programs ◽  
Days Open ◽  
Fertility Traits ◽  
Holstein Population

In spite of the economic importance of fertility and increased knowledge of reproductive biology in the cow, efficiency of reproductive performance has continued to decline in dairy cattle. Improvements in fertility through genetic selection may be a possible approach to increase reproductive efficiency in dairy cattle. Although progress may be slow because of low heritabilities, ignoring fertility in genetic improvement programs has contributed to the current fertility problems. The objectives of this study were to (1) estimate genetic parameters and breeding values for fertility traits based on data from milk recording programs on a Holstein population and (2) develop a multi-trait selection index (dollar fertility value; $F) based on estimated breeding values. Data representing 3,282,843 lactations and 1,622,088 animals (cows and bulls from 1936 to 2007) were used for the analysis and obtained from official records maintained by the Argentinean Holstein Association (ACHA). Data were collected from official milk records, and lactations were standardized to 305 DIM for milk, protein, and fat. Gestation period was considered to be 282 days and restrictions were applied to ensure the quality of data (days open <40 and >350 days; calving interval <300 and >600 days; and contemporary groups with <25 lactations were eliminated). Days open (DO), calving interval (CI), age to first calving (AFC), and daughter pregnancy rate (DPR) were traits chosen for genetic parameter estimation. Daughter pregnancy rate was calculated from DO as PR = 0.25 × (233 DO); Kuhn et al. 2004 J. Dairy Sci. 87, 2277-2284. Animal models by lactation for each fertility trait included contemporary group (dairy herd and calving year), calving month, animal effect, milk production as a covariate and error term. Multiple-trait derivative-free restricted maximum likelihood (MTDFREML) was used to estimate covariance components (Boldman et al. 1995 ARS, USDA). Solutions for fixed effects, breeding values, and sampling variances (accuracies) were obtained for each trait. The proposed selection index ($F) included AFC and CI, with economic weights from -0.28 and -4.9 $/year per cow for AFC and CI, respectively (Gonzalez-Recio et al. 2004 J. Dairy Sci. 87, 3053-3061). Heritabilities for DO and DPR ranged from 2 to 7%; CI ranged from 3 to 8%; and AFC was 16%. Predicted transmitting ability values across different lactations ranged from -18.5 to 15.8 days, -23.15 to 16.0 days, -4.0 to 4.6%, and -120.3 to 76.2 days for DO, CI, DPR, and AFC, respectively. Values for $F ranged from -$89.16 to $147.12 in this Holstein population. Results indicate substantial variation in fertility traits, suggesting that genetic selection may be effective in improving declines in fertility. Asociacion Criadores Holando Argentino (ACHA).

scholarly journals Genotype-by-environment interaction in Holstein heifer fertility traits using single-step genomic reaction norm models

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Rui Shi ◽  
Luiz Fernando Brito ◽  
Aoxing Liu ◽  
Hanpeng Luo ◽  
Ziwei Chen ◽  
...  
Keyword(s):  
Heat Stress ◽  
Dairy Cattle ◽  
Candidate Genes ◽  
Heat Tolerance ◽  
Reaction Norm ◽  
Single Step ◽  
Conception Rate ◽  
Critical Periods ◽  
Genotype By Environment ◽  
Fertility Traits

Abstract Background The effect of heat stress on livestock production is a worldwide issue. Animal performance is influenced by exposure to harsh environmental conditions potentially causing genotype-by-environment interactions (G × E), especially in highproducing animals. In this context, the main objectives of this study were to (1) detect the time periods in which heifer fertility traits are more sensitive to the exposure to high environmental temperature and/or humidity, (2) investigate G × E due to heat stress in heifer fertility traits, and, (3) identify genomic regions associated with heifer fertility and heat tolerance in Holstein cattle. Results Phenotypic records for three heifer fertility traits (i.e., age at first calving, interval from first to last service, and conception rate at the first service) were collected, from 2005 to 2018, for 56,998 Holstein heifers raised in 15 herds in the Beijing area (China). By integrating environmental data, including hourly air temperature and relative humidity, the critical periods in which the heifers are more sensitive to heat stress were located in more than 30 days before the first service for age at first calving and interval from first to last service, or 10 days before and less than 60 days after the first service for conception rate. Using reaction norm models, significant G × E was detected for all three traits regarding both environmental gradients, proportion of days exceeding heat threshold, and minimum temperature-humidity index. Through single-step genome-wide association studies, PLAG1, AMHR2, SP1, KRT8, KRT18, MLH1, and EOMES were suggested as candidate genes for heifer fertility. The genes HCRTR1, AGRP, PC, and GUCY1B1 are strong candidates for association with heat tolerance. Conclusions The critical periods in which the reproductive performance of heifers is more sensitive to heat stress are trait-dependent. Thus, detailed analysis should be conducted to determine this particular period for other fertility traits. The considerable magnitude of G × E and sire re-ranking indicates the necessity to consider G × E in dairy cattle breeding schemes. This will enable selection of more heat-tolerant animals with high reproductive efficiency under harsh climatic conditions. Lastly, the candidate genes identified to be linked with response to heat stress provide a better understanding of the underlying biological mechanisms of heat tolerance in dairy cattle.

scholarly journals Animal Model Versus Polynomial Legendre Test-Day In Dairy Cattle

2020 ◽  
Vol 23 (1) ◽  
pp. 5-12
Author(s):  
Mircea Cătălin Rotar ◽  
Horia Grosu ◽  
Mihail Alexandru Gras ◽  
Rodica Ştefania Pelmuş ◽  
Cristina Lazăr ◽  
...  
Keyword(s):  
Animal Model ◽  
Dairy Cattle ◽  
Fixed Effects ◽  
Rank Correlation ◽  
Pedigree Information ◽  
Lactation Period ◽  
Data Set ◽  
Breeding Values ◽  
Normal Limits ◽  
Model Versus

AbstractThe aim of the study was to compare the classical animal model (based on total milk for 305 days) with the Test-Day model (using monthly records of milk yield from Official Records of Performances). The data set derived from a total 175 animals (cows with records, parents of these animals and the descendants) from two Romanian breeds (Romanian Black Spotted and Montbeliarde), the phenotypic and the pedigree information arisen from National Research Development Institute for Animal Biology and Nutrition (IBNA-Balotesti). The selection criteria to be included in the analysis for each cow was to have at least 3 test-days and the days in milk between 200 and 330 for the Test-Day model and the total amount of the 305- day lactation yield for classical Animal Model respectively. Both models use B.L.U.P methodology and for that reason all the estimates were adjusted for fixed effects and all the breeding values and the solution for fixed effects were estimated simultaneous. For the animal model the fixed effects used was the breed and the year of performing and for the Test-Day model was an extra one, the test day effect. The correlation calculated between test days was very high (over 90%) for consecutive tests, and was getting lower when the days between tests was higher (under 40%). Also, in terms of heritability the values were in normal limits throughout lactation, except at the beginning and end of lactation period where these values were a little bit higher. The comparison of the ranking of breeding values with Spearman rank correlation shows that in 80% of the cases the ranking was similar for both models. As the ranking correlations shows, it is certain that the two models are very similar when they are used for genetic evaluation. But, in conclusion, we can say that for a better lactation curve estimation it is recommending to use test-day model for dairy cattle.

Dairy cattle breeding.

2021 ◽  
pp. 234-291
Author(s):  
Geoff Simm ◽  
Geoff Pollott ◽  
Raphael Mrode ◽  
Ross Houston ◽  
Karen Marshall
Keyword(s):  
Genetic Analysis ◽  
Dairy Cattle ◽  
Selection Response ◽  
Animal Breeding ◽  
Technology Selection ◽  
Cattle Breeding ◽  
Breeding Values ◽  
Breeding Technology ◽  
Dairy Cattle Breeding

Abstract This chapter discussed the effects of applying the different principles in animal breeding such genetic analysis, predicting breeding values, use of tools and breeding technology, selection response within breeds, and strategies for genetic improvements in dairy cattle.

Linear and threshold model genetic parameters for disease, fertility and milk production in dairy cattle

2000 ◽  
Vol 27 ◽  
pp. 83-84
Author(s):  
H. N. Kadarmideen ◽  
R. Thompson ◽  
G. Simm
Keyword(s):  
Animal Models ◽  
Dairy Cattle ◽  
Milk Production ◽  
Genetic Parameters ◽  
Linear Models ◽  
Threshold Model ◽  
Genetic Selection ◽  
Good Health ◽  
Economic Loss ◽  
Fertility Traits

A combination of better management and genetic selection for good health and fertility would provide a more effective long term solution for economic loss due to diseases and poor fertility. This would also help to address public concerns about the use of medical treatment in milk production. A balance in the genetic improvement of health and fertility together with milk production could be achieved through their inclusion in national genetic selection indices, for which genetic parameters are needed. One of the main objectives of this study was to estimate genetic parameters for various disease and fertility traits in the UK dairy cattle population, using records from a national recording scheme run by Livestock Services UK Ltd. Genetic analysis of traits recorded as present or absent (binary traits; e.g. diseases) requires the use of non-linear threshold models, because linear models require normality assumptions (e.g., Gianola 1982). The other objective of this study was to estimate genetic parameters for binary disease and fertility traits based on threshold animal models and to compare results with those from linear animal models.

The relationship between fertility, rump and other type traits in Holstein Friesian cows

2005 ◽  
Vol 2005 ◽  
pp. 53-53
Author(s):  
E. Wall ◽  
I. M. S. White ◽  
M. P. Coffey ◽  
S. Brotherstone
Keyword(s):  
Significant Relationship ◽  
Phenotypic Correlation ◽  
Popular Belief ◽  
Breeding Values ◽  
Holstein Friesian ◽  
Type Traits ◽  
Cattle Breeders ◽  
The Relationship ◽  
Fertility Traits ◽  
Friesian Cows

Cattle breeders, farmers and vets believe that the decline in fertility seen in recent years can be partially attributed to changes in rump angle with selection being for more angular cows. This suggests that animals with pin bones that sit above the hip bones (high rump angle) will have poorer fertility. Few studies have shown a significant relationship between fertility and rump traits. This study investigates the popular belief that high rump angle equates to poor fertility by examining the genetic and phenotypic correlation between rump angle and fertility traits. The relationship between rump angle and fertility was also examined to see if there was an intermediate optimum or threshold of rump angle for good/bad fertility. The correlation of other type traits (udder and composite traits) with fertility was also examined to see if they had potential to add information to the estimation of fertility breeding values.

Genetic line × concentrate level interactions for milk production and feed efficiency in dairy cattle

1992 ◽  
Vol 72 (2) ◽  
pp. 227-236 ◽  
Author(s):  
S. Wang ◽  
G. L. Roy ◽  
A. J. Lee ◽  
A. J. McAllister ◽  
T. R. Batra ◽  
...  
Keyword(s):  
Dairy Cattle ◽  
Milk Production ◽  
Milk Yield ◽  
Feed Efficiency ◽  
Production Efficiency ◽  
Breeding Value ◽  
Environment Interaction ◽  
Genetic Line ◽  
Breeding Values ◽  
Concentrate Level

Early first lactation data from 2230 cows of five research herds of Agriculture Canada were used to study the interactions of genetic line by concentrate level, and sire by concentrate level and to estimate breeding values of sires. The genetic lines were defined as Holstein (H), Ayrshire (A), and H × A or A × H (C). The interactions of sire by concentrate level were studied separately using progeny of five different mating groups: G1, H sires mated to H cows; G2, H sires mated to H, A and C cows; G3, A sires mated to A cows; G4, A sires mated to H, A and C cows; and G5, C sires mated to C cows. The interactions of genetic line by concentrate were significant (P < 0.05) for 56- to 112-d milk yield (MY112), corrected 56-to 112-d milk yield (CMY112) and feed efficiency (EFMY112 = MY112/TDN consumption). H and C cows produced more milk and were more efficient than A cows when fed high levels of concentrate. The H cattle possess a greater capacity to convert the concentrate into milk, while A cattle reach maximum milk production earlier than H cattle. The interactions of sire by concentrate were statistically significant for MY112, EFMY112 and CMY112 in G1 (P < 0.01), and G2 (P < 0.01). The breeding values of sires for MY112 were estimated using BLUP for all of the H line (BLUP-T), for half of the population consuming low amounts of concentrate (BLUP-L) and for the other half consuming high amounts (BLUP-H). A significant reranking of sires was found among the three groups. Key words: Genotype × environment interaction, milk production, efficiency, breeding value, dairy cattle

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