Genetic Parameters for a Weighted Analysis of Survivability in Dairy Cattle

The genetic parameters for the survival of Holstein cows, analysed in nine consecutive time periods during the first three calving intervals, were estimated. The earlier the animals are culled, the more they are informationally underestimated. This undervaluing can be remedied by using a weighted analysis that balances the amount of information. If the method of estimating breeding values changes, the genetic parameters will also change. The Holstein cattle dataset from 2005 to 2017 used in this study included 1,813,636 survival records from 298,290 cows. The pedigree with three generations of ancestors included 660,476 individuals. Linear repeatability models estimated genetic parameters for overall and functional survivability. Due to weights, heritability increased from 0.013 to 0.057. Repeatability with weights was 0.505. The standard deviations of breeding values were 1.75 and 2.18 without weights and 6.04 and 6.20 with weights. Including weights in the calculation increased the additive variance proportion and the breeding values’ reliabilities. We conclude that the main contribution of the weighted method we have presented is to compensate for the lack of records in culled individuals with a positive impact on the reliability of the breeding value.

Insight into selective breeding for robustness based on field survival records: New genetic evaluation of survival traits in pacific white shrimp (Penaeus vannamei) breeding line

Survival can be considered a relatively ‘old’ trait in animal breeding, yet commonly neglected in aquaculture breeding because of the simple binary records and generally low heritability estimates. Developing routine genetic evaluation systems for survival traits however, will be important for breeding robust strains based on valuable field survival data. In the current study, linear multivariate animal model (LMA) was used for the genetic analysis of survival records from 2-year classes (BL2019 and BL2020) of pacific white shrimp (Penaeus vannamei) breeding lines with data collection of 52, 248 individuals from 481 fullsib families. During grow-out test period, 10 days intervals of survival data were considered as separate traits. Two survival definitions, binary survivability (S) and continuous survival in days (SL), were used for the genetic analysis of survival records to investigate; 1) whether adding more survival time information could improve estimation of genetic parameters; 2) the trajectory of survival heritability across time, and 3) patterns of genetic correlations of survival traits across time. Levels of heritability estimates for both S and SL were low (0.005–0.076), while heritability for survival day number was found to be similar with that of binary records at each observation time and were highly genetically correlated (r_g > 0.8). Heritability estimates of body weight (BW) for BL2019 and BL2020 were 0.486 and 0.373, respectively. Trajectories of survival heritability showed a gradual increase across the grow-out test period but slowed or reached a plateau during the later grow-out test period. Genetic correlations among survival traits in the grow-out tests were moderate to high, and the closer the times were between estimates, the higher were their genetic correlations. In contrast, genetic correlations between both survival traits and body weight were low but positive. Here we provide the first report on the trajectory of heritability estimates for survival traits across grow-out stage in aquaculture. Results will be useful for developing robust improved pacific white shrimp culture strains in selective breeding programs based on field survival data.

Applicability of single-step genomic evaluation with a random regression model for reproductive traits in turkeys (Meleagris gallopavo)

Fertility and hatchability are economically important traits due to their effect on poult output coming from the turkey hatchery. Traditionally, fertility is recorded as the number of fertile eggs set in the incubator (FERT), defined at a time point during incubation by the identification of a developing embryo. Hatchability is recorded as either the number of fertile eggs that hatched (hatch of fertile, HOF) or the number hatched from all the eggs set (hatch of set, HOS). These traits are collected throughout the productive life of the bird and are conventionally cumulated, resulting in each bird having a single record per trait. Genetic evaluations of these traits have been estimated using pedigree relationships. However, the longitudinal nature of the traits and the availability of genomic information have renewed interest in using random regression (RR) to capture the differences in repeatedly recorded traits, as well as in the incorporation of genomic relationships. Therefore, the objectives of this study were: 1) to compare the applicability of a RR model with a cumulative model (CUM) using both pedigree and genomic information for genetic evaluation of FERT, HOF, and HOS and 2) to estimate and compare predictability from the models. For this study, a total of 63,935 biweekly FERT, HOF, and HOS records from 7,211 hens mated to 1,524 toms were available for a maternal turkey line. In total, 4,832 animals had genotypic records, and pedigree information on 11,191 animals was available. Estimated heritability from the CUM model using pedigree information was 0.11 ± 0.02, 0.24 ± 0.02, and 0.24 ± 0.02 for FERT, HOF, and HOS, respectively. With random regression using pedigree relationships, heritability estimates were in the range of 0.04–0.09, 0.11–0.17, and 0.09–0.18 for FERT, HOF, and HOS, respectively. The incorporation of genomic information increased the heritability by an average of 28 and 23% for CUM and RR models, respectively. In addition, the incorporation of genomic information caused predictability to increase by approximately 11 and 7% for HOF and HOS, respectively; however, a decrease in predictability of about 12% was observed for FERT. Our findings suggest that RR models using pedigree and genomic relationships simultaneously will achieve a higher predictability than the traditional CUM model.

The Estimation of Genetic Parameters for Longevity According to Lactation Period Using a Multiple Trait Animal Model in Korean Holstein Cows

Longevity is closely related to the survival rate of dairy cattle and refers to the period during which the cow has economic value, from first calving to culling. The purpose of this study was to analyze the culling patterns and survival rates of Korean Holstein cows and evaluate genetic characteristics related to parity and longevity of each lactation by using the test day milk yield collected in South Korea. The performance data of the dairy cattle were collected from 2004 to 2019 by the Nonghyup Dairy Cattle Improvement Center. The collected 1,702,304 records were used as pedigree data through the Korea Animal Improvement Association. The lactation period was divided into early-lactation (0–90 days: L1.1, L2.1, and L3.1), mid-lactation (91–299 days: L1.2, L2.2, and L3.2), and late-lactation (300 days-next parity: L1.3, L2.3, and L3.3). The heritability of longevity for the first, second, and third parity was 0.020, 0.028, and 0.039, respectively. In all parities, the heritability in late-lactation was higher than that in early- and mid-lactation. Most genetic correlations for survival in the first parity were higher than those in the second and third parities. The results of this study may serve as a basis for developing a more accurate model for evaluating longevity traits in South Korea.

Estimation of the economic value of herd-life length based on simulated changes in survival rate

Functional traits are an important aspect of long‐term breeding strategies for dairy cattle. In this regard, it is necessary to develop simple methods for estimating the economic value of herd life. In this study, the economic daily value of herd life was estimated when survival rate varied between −0.05 and 0.05 from the basal survival rate. The extension days per survival rate were 26.5 days in Hokkaido and 20.3 days in other regions. The increases in values of annual income per day of herd life were 95.18 yen in Hokkaido and 101.80 yen in other regions. The relative economic weights of milk yield to herd life per genetic standard deviation were 0.668 in Hokkaido and 1.03 in other regions. Estimated increments in yearly profits based on young sire selection for herd life were 963 yen in Hokkaido and 1,030 yen in other regions. The estimated increments in annual profits based on young sire selection for milk yield were 1,268 yen in Hokkaido and 2,097 yen in other regions. Given that economic value was linearly correlated with herd‐life length, the linear regression coefficients between these factors could be used to estimate the economic value of herd‐life length.

Phenotypic and genetic relationships between age at first calving, its component traits, and survival of heifers up to second calving

The aim of this study was to answer the question whether models for genetic evaluations of longevity should include a correction for age at first calving (AFC). For this purpose, phenotypic and genetic relationships between AFC, its component traits age at first insemination (AFI) and interval from first to last insemination (FLI), and survival of different periods of the first lactation (S1: 0 to 49 d, S2: 50 to 249 d, S3: 250 d to second calving) were investigated. Data of 721,919 German Holstein heifers, being inseminated for the first time during the years from 2003 to 2012, were used for the analyses. Phenotypic correlations of AFI, FLI, and AFC to S1 to S3 were negative. Mean estimated heritabilities were 0.239 (AFI), 0.007 (FLI), and 0.103 (AFC) and 0.023 (S1), 0.016 (S2), and 0.028 (S3) on the observed scale. The genetic correlation between AFI and FLI was close to zero. Genetic correlations between AFI and the survival traits were -0.08 (S1), -0.02 (S2), and -0.10 (S3); those between FLI and the survival traits were -0.14 (S1), -0.20 (S2), and -0.44 (S3); and those between AFC and the survival traits were -0.09 (S1), -0.06 (S2), and -0.20 (S3). Some of these genetic correlations were different from zero, which suggests that correcting for AFC in genetic evaluations for longevity in dairy cows might remove functional genetic variance and should be reconsidered.