Heritability, reliability of genetic evaluations and response to selection in proportional hazard models

Genetic evaluation for survival traits in Japanese quail line selected for fast growth rate

The main objectives of this study were to estimate genetic parameters for the survival, longevity and evaluate risk factors for the occurrence of mortality in a Japanese quail line selected for high growth rate during the period from hatch to 21 days of age (GR1-21) for eight generations and its control. Total number of 1095, 2289 and 16,506 for sires, dams and progeny, respectively, was used to estimate genetic parameters, a separate hatch of 687 chicks was used to examine the risk factors of quails in the selected (SL, 438) and control (CL, 249) lines. The proportion of censored quails until 42 days of age was 82.20 and 87.14 for SL and CL, respectively. The CL showed higher longevity than SL (38.42 vs. 36.86 days). In the two tested lines, mortality% significantly declined when body weight at death increased, however, the CL had a higher reduction of mortality% than the SL (50 vs. 42%). Survival and longevity had low heritability values, low genetic and phenotypic correlations between survival and longevity with GR1-21 and ranging from 0.025 to 0.208. The survival tended to be less correlated with GR1-21 and body weight at marketing age than the longevity.

Risk factors and genetic parameter estimates for preweaning survival of Fogera calves

This study utilised mortality records of 1 043 Fogera calves maintained at Andassa Livestock Research Center from 1984 to 2021 to investigate the factors that influence survival and estimate genetic parameters for the preweaning survival of Fogera calves. Survival was defined as the probability of surviving in a given length of time. Survival analysis was done using the Weibull proportional hazard model with Survival Kit version 6.1 software. Genetic variance and heritability estimates were estimated using the sire model. The proportion of right-censored calves up to 1, 4, and 8 months of age was 90.8, 87.8, and 83.5%, respectively. Around 55.8% of all deaths (16.5%) occurred up to one month of age. In addition to birth year, sex, season, and weight at birth were the most important risk factors for calf mortality. The heritability estimates for the survival of calves at 1, 4, and 8 months of age were 0.26 ± 0.14, 0.22 ± 0.13, and 0.38 ± 0.18, respectively. Moderate heritability was estimated at the age of eight months, implying that the inclusion of survival traits in the selection criteria and inclusion in the breeding goal will enhance the preweaning survival rate of calves. Similarly, higher differences in estimated breeding values of sires for survival suggest that the selection of sires with higher estimated breeding values could improve the survival potential of calves. The decreased genetic trend of 3.34% year-1 for the survival potential of Fogera calves during the study periods suggested that survival traits should be included in the breeding goal to reduce the mortality rate.

Germline mechanisms of immunotherapy toxicities in the era of genome-wide association studies

Cancer immunotherapy has revolutionized the treatment of advanced cancers and is quickly becoming an option for early-stage disease. By reactivating the host immune system, immunotherapy harnesses patients' innate defenses to eradicate the tumor. By putatively similar mechanisms, immunotherapy can also substantially increase the risk of toxicities or immune-related adverse events (irAEs). Severe irAEs can lead to hospitalization, treatment discontinuation, lifelong immune complications, or even death. Many irAEs present with similar symptoms to heritable autoimmune diseases, suggesting that germline genetics may contribute to their onset. Recently, genome-wide association studies (GWAS) of irAEs have identified common germline associations and putative mechanisms, lending support to this hypothesis. A wide range of well-established GWAS methods can potentially be harnessed to understand the etiology of irAEs specifically and immunotherapy outcomes broadly. This review summarizes current findings regarding germline effects on immunotherapy outcomes and discusses opportunities and challenges for leveraging germline genetics to understand, predict, and treat irAEs.

Survival analysis of productive life in Florida dairy goats using a Cox proportional hazards model

Longevity is an economically important trait, since extending the functional life of a doe would allow us to keep the most productive females in the herd as long as possible, and this could result in the increased profitability of dairy farms. Thus, the objectives of this study were to determine the most important factors that influence the length of productive life (LPL) of female Florida goats and to estimate its genetic additive variance using a Cox proportional hazards model. The data consisted of 70,695 productive life records from 25,722 Florida females kidding between 2006 and 2020. A total of 19,495 does had completed their productive life while 6227 (24.2%) does had censored information. The pedigree contained information on 56,901 animals. The average censoring age and average failure age after first kidding for LPL were 36 and 47 months respectively. The model included, as time-independent effects, the age at first kidding and the interaction between herd, year and season of birth of the doe, and as time-dependent effects, the age at kidding, the interaction between herd, year and season of kidding, the within-herd class of milk production deviation, and the interaction between the lactation number and the stage of lactation. All fixed effects had a significant effect on LPL (p < 0.05). Does with older ages at the first kidding and an earlier age at kidding were at higher risk of being culled. A large difference among herds was observed in terms of culling risk, which highlighted the importance of adequate management practices. Also, high-producing does were less likely to be culled. The estimate of the additive genetic variance was 1.844 (in genetic standard deviation), with a heritability estimate of 0.58 ± 0.012. The results of this study are expected to contribute to the development of a genetic model for genetic evaluation of the length of the productive life of Spanish dairy goat breeds.

Genetic Parameters for Functional Longevity, Type Traits, and Production in the Serbian Holstein

In this study, the authors focused on the evaluation of the genetic parameters of longevity, milk yield traits, and type traits in dairy cattle populations in the Republic of Serbia. The total dataset used consisted of production records and pedigree data for 32,512 Holstein cows that calved from 1981 to 2015. The animal model was applied to determine the variance and covariance components and genetic parameters of the analyzed traits by applying the restricted maximum likelihood (REML) approach and using the programs VCE6 and PEST. The heritability of longevity traits was estimated using the Survival Kit V6.0 software package. Variance and covariance were estimated for five production traits: milk yield (MY), fat yield (FY), protein yield (PY), milk fat content (MC), and protein content (PC), and three longevity traits: length of productive life (LPL), lifetime milk yield (LMY), and the number of lactations achieved (NL) as well as for 18 standard type traits. Heritabilities for the milk, fat, and protein yield traits were 0.20 (MY), 0.15 (FY), and 0.19 (PY), respectively. The estimated coefficients of heritability for the longevity traits were higher when using the Weibull proportional hazards model compared to the traditional linear methods and ranged from 0.08 for NL to 0.10 for LPL. Heritability values for the type traits varied from a low of 0.10 (RLSsv-rear legs set-side view) to medium values of 0.32 (ST-stature). Genetic correlations were found between MY and the following longevity traits: LPL, LMY, and NL with values of -0.18, -0.11, and -0.09, respectively. Genetic correlations were found between MY and a number of linear type traits and varied from 0.02 (between MY and RUH-rear udder height) to 0.28 (between MY and FUA-fore udder attachment). Genetic correlations between the 18 investigated type traits ranged from -0.33 between TL (top line) and RTP (rear teats position) to 0.71 between AN (angularity) and RUH (rear udder height). Genetic correlations between most linear type traits and longevity traits (LPL, LMY, and NL) were generally negative and very low. The highest positive genetic correlation was found between UD and LPL (r_xy = 0.38).

Genomic architecture and prediction of censored time-to-event phenotypes with a Bayesian genome-wide analysis

While recent advancements in computation and modelling have improved the analysis of complex traits, our understanding of the genetic basis of the time at symptom onset remains limited. Here, we develop a Bayesian approach (BayesW) that provides probabilistic inference of the genetic architecture of age-at-onset phenotypes in a sampling scheme that facilitates biobank-scale time-to-event analyses. We show in extensive simulation work the benefits BayesW provides in terms of number of discoveries, model performance and genomic prediction. In the UK Biobank, we find many thousands of common genomic regions underlying the age-at-onset of high blood pressure (HBP), cardiac disease (CAD), and type-2 diabetes (T2D), and for the genetic basis of onset reflecting the underlying genetic liability to disease. Age-at-menopause and age-at-menarche are also highly polygenic, but with higher variance contributed by low frequency variants. Genomic prediction into the Estonian Biobank data shows that BayesW gives higher prediction accuracy than other approaches.

Genomic Correlations Between the Gaits of Young Horses Measured by Accelerometry and Functional Longevity in Jumping Competition

Functional longevity is essential for the well-being of horses and the satisfaction of riders. Conventional selection using longevity breeding values calculated from competition results is not efficient because it takes too long to obtain reliable information. Therefore, the objective was to identify early criteria for selection. We assessed two types of early criteria: gait traits of young horses and QTLs. Thus, our aim was to estimate the genetic correlation between gait traits and longevity and to perform a genome-wide association study (GWAS) for longevity. Measurements of gaits by accelerometry were recorded on 1,477 show jumping horses that were 4 to 5 years old. Gait analysis provided 9 principal components describing trot, canter, and walk. Longevity estimated breeding values (EBVs) for stallions were calculated using a survival analysis of more than 900,000 years of performances by 179,448 show jumping horses born from 1981 onwards. Longevity was measured as the number of years spent in competition. Model included region and month of birth, age at first competition, year, and performance level. Longevity EBVs were deregressed to obtain weighted pseudo-performances for 1,968 stallions. Genomic data were available for 3,658 jumping horses. Seventy-eight percent of the horses measured for gaits and twenty-five percent of those measured for longevity were genotyped. A GWAS of longevity revealed no significant QTLs. Genetic parameters between each of the 9 principal components of the gait variables and longevity were evaluated with a bi-trait animal linear mixed model using single-step GBLUP analysis with the relationship matrix constructed from genomic data and genealogy (24,448 ancestors over four generations). The heritability of the gait traits varied from 0.11 to 0.44. The third principal component for trot (high lateral activity) and the first principal component for canter (high dorsoventral activity and low stride frequency) were moderately genetically correlated with higher longevity: r_g = 0.38 (0.15) and 0.28 (0.13), respectively. Our study revealed that functional longevity is a polygenic trait with no major genes. We found new correlations between longevity and gait traits. Before using gait characteristics in a selection plan, these correlations need to be understood better at the biomechanical level.

How Can Gene-Expression Information Improve Prognostic Prediction in TCGA Cancers: An Empirical Comparison Study on Regularization and Mixed Cox Models

Background

Previous cancer prognostic prediction models often consider only the most important transcriptomic expressions, and their power is limited. It is unknown whether prediction power can be further improved when additional transcriptomic information is incorporated.

Methods

To integrate transcriptomes, four models are compared based on 32 types of cancer in the Cancer Genome Atlas, including the general Cox model with only clinical covariates, the Cox model with a lasso penalty (coxlasso), the Cox model with an elastic net penalty (coxenet), and the mixed-effects Cox model (coxlmm). Furthermore, we partition the survival variance into the relative contribution of clinical and transcriptomic components within the framework of coxlmm. Finally, the influence of different numbers of genes was evaluated in the context of coxlmm.

Results

Compared with the clinical covariates–only Cox model, the average prediction gain was 2.4% for coxlasso, 4.2% for coxenet, and 7.2% for coxlmm across 16 low-censored cancers; a significant elevation of prediction power was observed for SARC, SKCM, LGG, PAAD, and HNSC. Similar findings were observed for all 32 cancers with the average prediction gain of 2.7, 3.8, and 5.8% for coxlasso, coxenet, and coxlmm. Coxlmm always had comparable or better prediction performance relative to coxlasso and coxenet with an average of 2.8% prediction improvement across the 16 low-censored cancers. In addition, it is shown that the predictive accuracy of coxlmm generally increases with the number of genes included. The survival variance partition analysis demonstrates that the transcriptomic contribution was higher for some cancers (e.g., LGG, CESC, PAAD, SKCM, and SARC) and lower for others (e.g., BRCA, COAD, KIRC, and STAD).

Conclusion

This study demonstrates that the integration of transcriptomic information can substantially improve prognostic prediction accuracy, but the prediction performance is cancer-specific and varies across cancer types. It further reveals that gene expression exhibits distinct contributions to survival variation across cancers.

Fast Algorithms for Conducting Large-Scale GWAS of Age-at-Onset Traits Using Cox Mixed-Effects Models

Age-at-onset is one of the critical traits in cohort studies of age-related diseases. Large-scale genome-wide association studies (GWAS) of age-at-onset traits can provide more insights into genetic effects on disease progression and transitions between stages. Moreover, proportional hazards (or Cox) regression models can achieve higher statistical power in a cohort study than a case-control trait using logistic regression. Although mixed-effects models are widely used in GWAS to correct for sample dependence, application of Cox mixed-effects models (CMEMs) to large-scale GWAS is so far hindered by intractable computational cost. In this work, we propose COXMEG, an efficient R package for conducting GWAS of age-at-onset traits using CMEMs. COXMEG introduces fast estimation algorithms for general sparse relatedness matrices including, but not limited to, block-diagonal pedigree-based matrices. COXMEG also introduces a fast and powerful score test for dense relatedness matrices, accounting for both population stratification and family structure. In addition, COXMEG generalizes existing algorithms to support positive semidefinite relatedness matrices, which are common in twin and family studies. Our simulation studies suggest that COXMEG, depending on the structure of the relatedness matrix, is orders of magnitude computationally more efficient than coxme and coxph with frailty for GWAS. We found that using sparse approximation of relatedness matrices yielded highly comparable results in controlling false-positive rate and retaining statistical power for an ethnically homogeneous family-based sample. By applying COXMEG to a study of Alzheimer's disease (AD) with a Late-Onset Alzheimer's Disease Family Study from the National Institute on Aging sample comprising 3456 non-Hispanic whites and 287 African Americans, we identified the APOE ε4 variant with strong statistical power (P = 1e-101), far more significant than that reported in a previous study using a transformed variable and a marginal Cox model. Furthermore, we identified novel SNP rs36051450 (P = 2e-9) near GRAMD1B, the minor allele of which significantly reduced the hazards of AD in both genders. These results demonstrated that COXMEG greatly facilitates the application of CMEMs in GWAS of age-at-onset traits.

Disentangling Genetic Variation for Resistance and Endurance to Scuticociliatosis in Turbot Using Pedigree and Genomic Information

Selective breeding for improving host responses to infectious pathogens is a promising option for disease control. In fact, disease resilience, the ability of a host to survive or cope with infectious challenge, has become a highly desirable breeding goal. However, resilience is a complex trait composed of two different host defence mechanisms, namely resistance (the ability of a host to avoid becoming infected or diseased) and endurance (the ability of an infected host to survive the infection). While both could be targeted for genetic improvement, it is currently unknown how they contribute to survival, as reliable estimates of genetic parameters for both traits obtained simultaneously are scarce. A difficulty lies in obtaining endurance phenotypes for genetic analyses. In this study, we present the results from an innovative challenge test carried out in turbot whose design allowed disentangling the genetic basis of resistance and endurance to Philasterides dicentrarchi, a parasite causing scuticociliatosis that leads to substantial economic losses in the aquaculture industry. A noticeable characteristic of the parasite is that it causes visual signs that can be used for disentangling resistance and endurance. Our results showed the existence of genetic variation for both traits (heritability = 0.26 and 0.12 for resistance and endurance, respectively) and for the composite trait resilience (heritability = 0.15). The genetic correlation between resistance and resilience was very high (0.90) indicating that both are at a large extent the same trait, but no significant genetic correlation was found between resistance and endurance. A total of 18,125 SNPs obtained from 2b-RAD sequencing enabled genome-wide association analyses for detecting QTLs controlling the three traits. A candidate QTL region on linkage group 19 that explains 33% of the additive genetic variance was identified for resilience. The region contains relevant genes related to immune response and defence mechanisms. Although no significant associations were found for resistance, the pattern of association was the same as for resilience. For endurance, one significant association was found on linkage group 2. The accuracy of genomic breeding values was also explored for resilience, showing that it increased by 12% when compared with the accuracy of pedigree-based breeding values. To our knowledge, this is the first study in turbot disentangling the genetic basis of resistance and endurance to scuticociliatosis.

Context-dependent costs and benefits of tuberculosis resistance traits in a wild mammalian host

Disease acts as a powerful driver of evolution in natural host populations, yet individuals in a population often vary in their susceptibility to infection. Energetic trade-offs between immune and reproductive investment lead to the evolution of distinct life history strategies, driven by the relative fitness costs and benefits of resisting infection. However, examples quantifying the cost of resistance outside of the laboratory are rare. Here, we observe two distinct forms of resistance to bovine tuberculosis (bTB), an important zoonotic pathogen, in a free-ranging African buffalo (Syncerus caffer) population. We characterize these phenotypes as "infection resistance," in which hosts delay or prevent infection, and "proliferation resistance," in which the host limits the spread of lesions caused by the pathogen after infection has occurred. We found weak evidence that infection resistance to bTB may be heritable in this buffalo population (h 2 = 0.10) and comes at the cost of reduced body condition and marginally reduced survival once infected, but also associates with an overall higher reproductive rate. Infection-resistant animals thus appear to follow a "fast" pace-of-life syndrome, in that they reproduce more quickly but die upon infection. In contrast, proliferation resistance had no apparent costs and was associated with measures of positive host health-such as having a higher body condition and reproductive rate. This study quantifies striking phenotypic variation in pathogen resistance and provides evidence for a link between life history variation and a disease resistance trait in a wild mammalian host population.

Genetic evaluation of age at first calving for Guzerá beef cattle using linear, threshold, and survival Bayesian models

Age at first calving (AFC) is characterized as a censored trait due to missing values provided by recording mistakes and nonoccurrence or delay in calving communication. In this context, we aimed to compare several statistical methods for genetic evaluation of AFC in Guzerá beef cattle under a Bayesian approach. Seven different methods were used for this purpose. The traditional linear mixed model (LM), which considers only uncensored records; the LM with simulated records (SM), which is based on data augmentation framework; the penalty method, in which a constant of 21 d was added to censored records; the bivariate threshold-linear method considering (TLcens) or not (TLmiss) censored information; and the piecewise Weibull proportional hazards model considering (PWPHcens) or not (PWPH) censored records. Heritability estimates ranged from 0.19 (TLcens) to 0.28 (SM) in nonsurvival approaches; and 0.40 and 0.46 to PWPH and PWPHcens methods, respectively. In general, breeding values correlations between different methods and the percentage of selected bulls in common indicated reranking, with these correlation ranging from -0.28 (between SM and PWPH) to 0.99 (between TLmiss and LM). The traditional LM, which considers only uncensored records, should be preferred due to its robustness and simplicity. Based on cross-validation analyses, we conclude that the TLmiss could be also a suitable alternative for breeding value prediction, and censored methods did not improve the analysis.

Technical note: PaGELL v.1.5: A flexible parametric program for the Bayesian analysis of longevity data within the context of animal breeding

This technical note presents the program PaGELL v.1.5 (Parametric Genetic Evaluation of Lifespan in Livestock), a flexible software program to analyze (right-censored) longevity data in livestock populations, with a special emphasis on the genetic evaluation of the breeding stock. This software relies on a parametric generalization of the proportional hazard model; more specifically, the baseline hazard function follows a Weibull process and flexibility is gained by including an additional time-dependent effect with the number of change points defined by the user. The program can accommodate 3 different sources of variation (i.e., systematic, permanent environmental, and additive genetic effects) and both fixed and time-dependent patterns (only for systematic and permanent environmental effects). Analyses are performed within a Bayesian context by sampling from the joint posterior distribution of the model, and model fit can be easily determined by the calculation of the deviance information criterion. Although this software has already been used on field data sets, its performance has been double-checked on simulated data set, and results are presented in this technical note. PaGELL v.1.5 was written in Fortran 95 language and, after compiling with the GNU Fortran Compiler v.4.7 and later, it has been tested in Windows, Linux, and MacOS operating systems (both 32- and 64-bit platforms). This program is available at http://www.casellas.info/files/pageII.zip.

Evaluation of longevity modeling censored records in Nellore

The aim of the present study was to evaluate the prediction ability of models that cope with longevity phenotypic expression as uncensored and censored in Nellore cattle. Longevity was defined as the difference between the dates of last weaned calf and cow birth. There were information of 77 353 females, being 61 097 cows with uncensored phenotypic information and 16 256 cows with censored records. These data were analyzed considering three different models: (1) Gaussian linear model (LM), in which only uncensored records were considered; and two models that consider both uncensored and censored records: (2) Censored Gaussian linear model (CLM); and (3) Weibull frailty hazard model (WM). For the model prediction ability comparisons, the data set was randomly divided into training and validation sets, containing 80% and 20% of the records, respectively. There were considered 10 repetitions applying the following restrictions: (a) at least three animals per contemporary group in the training set; and (b) sires with more than 10 progenies with uncensored records (352 sires) should have daughters in the training and validation sets. The variance components estimated using the whole data set in each model were used as true values in the prediction of breeding values of the animals in the training set. The WM model showed the best prediction ability, providing the lowest χ 2 average and the highest number of sets in which a model had the smallest value of χ 2 statistics. The CLM and LM models showed prediction abilities 2.6% and 3.7% less efficient than WM, respectively. In addition, the accuracies of sire breeding values for LM and CLM were lower than those obtained for WM. The percentages of bulls in common, considering only 10% of sires with the highest breeding values, were around 75% and 54%, respectively, between LM-CLM and LM-WM models, considering all sires, and 75% between LM-CLM and LM-WM, when only sires with more than 10 progenies with uncensored records were taken into account. These results are indicative of reranking of animals in terms of genetic merit between LM, CLM and WM. The model in which censored records of longevity were excluded from the analysis showed the lowest prediction ability. The WM provides the best predictive performance, therefore this model would be recommended to perform genetic evaluation of longevity in this population.

Bivariate threshold models for genetic evaluation of susceptibility to and ability to recover from mastitis in Danish Holstein cows

Mastitis in dairy cows is an unavoidable problem and genetic variation in recovery from mastitis, in addition to susceptibility, is therefore of interest. Genetic parameters for susceptibility to and recovery from mastitis were estimated for Danish Holstein-Friesian cows using data from automatic milking systems equipped with online somatic cell count measuring units. The somatic cell count measurements were converted to elevated mastitis risk, a continuous variable [on a (0-1) scale] indicating the risk of mastitis. Risk values >0.6 were assumed to indicate that a cow had mastitis. For each cow and lactation, the sequence of health states (mastitic or healthy) was converted to a weekly transition: 0 if the cow stayed within the same state and 1 if the cow changed state. The result was 2 series of transitions: one for healthy to diseased (HD, to model mastitis susceptibility) and the other for diseased to healthy (DH, to model recovery ability). The 2 series of transitions were analyzed with bivariate threshold models, including several systematic effects and a function of time. The model included effects of herd, parity, herd-test-week, permanent environment (to account for the repetitive nature of transition records from a cow) plus two time-varying effects (lactation stage and time within episode). In early lactation, there was an increased risk of getting mastitis but the risk remained stable afterwards. Mean recovery rate was 45% per lactation. Heritabilities were 0.07 [posterior mean of standard deviations (PSD) = 0.03] for HD and 0.08 (PSD = 0.03) for DH. The genetic correlation between HD and DH has a posterior mean of -0.83 (PSD = 0.13). Although susceptibility and recovery from mastitis are strongly negatively correlated, recovery can be considered as a new trait for selection.

Estimation of genetic parameters for functional longevity in the South African Holstein cattle using a piecewise Weibull proportional hazards model

Non-genetic factors influencing functional longevity and the heritability of the trait were estimated in South African Holsteins using a piecewise Weibull proportional hazards model. Data consisted of records of 161,222 of daughters of 2,051 sires calving between 1995 and 2013. The reference model included fixed time-independent age at first calving and time-dependent interactions involving lactation number, region, season and age of calving, within-herd class of milk production, fat and protein content, class of annual variation in herd size and the random herd-year effect. Random sire and maternal grandsire effects were added to the model to estimate genetic parameters. The within-lactation Weibull baseline hazards were assumed to change at 0, 270, 380 days and at drying date. Within-herd milk production class had the largest contribution to the relative risk of culling. Relative culling risk increased with lower protein and fat per cent production classes and late age at first calving. Cows in large shrinking herds also had high relative risk of culling. The estimate of the sire genetic variance was 0.0472 ± 0.0017 giving a theoretical heritability estimate of 0.11 in the complete absence of censoring. Genetic trends indicated an overall decrease in functional longevity of 0.014 standard deviation from 1995 to 2007. There are opportunities for including the trait in the breeding objective for South African Holstein cattle.

Genetic analysis of productive life length in Holstein dairy cows using Weibull proportional risk model

Abstract. In recent decades, there has been a downward trend in length of productive life (LPL) in Holstein cows across industrial dairy herds. This study examined the factors that might influence LPL and estimated the genetic parameters of LPL in Holstein dairy herds in Isfahan province, Iran. LPL is defined as the number of days between the first calving and the end of recording. Data consisted of 35 137 records of productive life from registered cows that started first calving between 1991 and 2012. Cows that remained alive at the end of the study were considered right-censored. The average lifetime for culled and censored cows was 938 and 1003 days, respectively. A survival analysis was applied using a proportional risk model with a Weibull distribution. Milk production was divided into five groups, where the culling risk of cows with a milk yield of less than 1.5 standard deviations (SD) of the mean was 3.5 times greater than the culling risk of high-producing cows producing more than 1.5 SD above the mean. Results showed that culling risk increased almost linearly beyond the milk production groups. Furthermore, somatic cell count and age at first calving significantly increased the culling risk across the herds. The results for the combined effect of parity  ×  stage of lactation showed a decrease in culling risk during the first calving, and an increase during the further parities. Moreover, a higher age at first calving was observed, reflecting a lower risk of culling. Estimated heritability were 0.074 and 0.18 based on a logarithmic scale and original scale, respectively. According to the results, use of Weibull models showed that the proportional culling risk was higher in low-production cows, but a higher risk ratio was revealed in high-milk-production cows. However, there were some fluctuations in genetic trends, but an overall increase was observed in LPL which will lead to a longer LPL of Holstein cows in Isfahan province.

Survival of Red Maasai, Dorper and crossbred lambs in the sub-humid tropics

The survival rates of Dorper, Red Maasai and crossbred lambs born over a period of 6 years at Diani Estate, Coast Province, Kenya were compared using the Cox mixed proportional hazards model with a random (frailty) term for sire. Of the 1785 lambs born, proportionately 0·44 died before they were 1 year old. Almost half of these deaths occurred before weaning; a third were associated with mis-mothering and a fifth with gastro-intestinal nematode parasite (endoparasite) infections. Half of the deaths post weaning were associated with endoparasite infections, predominantly Haemonchus contortus. The Red Maasai lambs had a lower risk of death than the Dorper lambs with a relative hazard of 0·27 pre-weaning and 0·25 post weaning. Other crosses and back crosses had relative hazards in between these values and 1; there was no evidence of heterosis. Survival rates were different among years and appeared to be associated to some degree with variations in rainfall. There were highly significant effects of both birth weight and weaning weight on survival. Body weight, together with packed red cell volume and faecal egg count, were also introduced into the proportional hazard model as time-varying covariates. All three variables had major influences on survival. The risk of death over the following month in animals individually treated with an anthelmintic drug pre weaning was reduced by 0·61 compared with those not treated. The sire frailty variance estimate was similar to its standard error pre-weaning but larger post weaning. When adjusted for lamb body weight the sire variance post weaning increased to three times its standard error.

Estimation of genetic parameters for longevity considering the cow's age at last calving

The aim of this study was to estimate heritability and predict breeding values for longevity among cows in herds of Nellore breed, considering the trait cow's age at last calving (ALC), by means of survival analysis methodology. The records of 11,791 animals from 22 farms were used. The variable ALC has been used by a criterion that made it possible to include cows not only at their first calving but also at their ninth calving. The criterion used was the difference between the date of each cow's last calving and the date of the last calving on each farm. If this difference was greater than 36 months, the cow was considered to have failed and uncensored. If not, this cow was censored, thus indicating that future calving remained possible for this cow. The survival model used for the analyses was the proportional hazards model, and the base risk was given by a Weibull distribution. The heritability estimate obtained was equal to 0.25. It was found that the ALC variable had the capacity to respond to selection for the purpose of increasing the longevity of the cows in the herds.

Comparison between linear and proportional hazard models for the analysis of age at first lambing in the Ripollesa breed

Age at first lambing (AFL) plays a key role on the reproductive performance of sheep flocks, although there are no genetic selection programs accounting for this trait in the sheep industry. This could be due to the non-Gaussian distribution pattern of AFL data, which must be properly accounted for by the analytical model. In this manuscript, two different parameterizations were implemented to analyze AFL in the Ripollesa sheep breed, that is, the skew-Gaussian mixed linear model (sGML) and the piecewise Weibull proportional hazards model (PWPH). Data were available from 10 235 ewes born between 1972 and 2013 in 14 purebred Ripollesa flocks located in the north-east region of Spain. On average, ewes gave their first lambing short after their first year and a half of life (590.9 days), and within-flock averages ranged between 523.4 days and 696.6 days. Model fit was compared using the deviance information criterion (DIC; the smaller the DIC statistic, the better the model fit). Model sGML was clearly penalized (DIC=200 059), whereas model PWPH provided smaller estimates and reached the minimum DIC when one cut point was added to the initial Weibull model (DIC=132 545). The pure Weibull baseline and parameterizations with two or more cut points were discarded due to larger DIC estimates (>134 200). The only systematic effect influencing AFL was the season of birth, where summer- and fall-born ewes showed a remarkable shortening of their AFL, whereas neither birth type nor birth weight had a relevant impact on this reproductive trait. On the other hand, heritability on the original scale derived from model PWPH was high, with a model estimate place at 0.114 and its highest posterior density region ranging from 0.079 and 0.143. As conclusion, Gaussian-related mixed linear models should be avoided when analyzing AFL, whereas model PWPH must be viewed as better alternative with superior goodness of fit; moreover, the additive genetic background underlying this reproductive trait supports its inclusion into current genetic selection programs given its economic importance.

Phenotypic and genetic variation in longevity of Polish Landrace sows

The influence of some production traits on the longevity of Polish Landrace sows was evaluated using survival analysis. Estimates of genetic parameters were obtained from the sire and animal components in linear and survival methodologies. Comparison between survival and linear models was based on heritabilities and ranking of estimated breeding values of sires. The same data set, 13,031 sows, was used for both methodologies, even in the presence of censored observations. The effects of herd*year and year*season of the first farrowing had the largest influence on the risk of culling of sows. Sows born in spring season (March-May) had a 24% (p < 0.001) lower hazard for removal than those born in winter (December-February). The age at first farrowing had a small but significant effect on culling: the hazard regression coefficient for this trait was 0.002 per day. Sows that had more piglets born alive and fewer stillborn in the first litter had a decreased risk of being culled. Within a contemporary group, slower growing gilts had decreased removal risk. The relative risk ratios show a marginal decreased rate of culling for sows with backfat thickness between 9.5 and 11 mm compared to the leaner sows. Loin depth had no effect on sow longevity. Heritability estimates ranged from 0.09 to 0.38 depending on the model and type of analysis. In survival analysis, all heritabilities for longevity were higher when analysed with sire models (0.21 and 0.38) compared to animal models (0.09 and 0.16). The use of animal or sire models in the linear analysis gave similar heritability estimates (0.12 and 0.10). Correlations between breeding values for sires were moderate and high, with absolute values from 0.51 to 0.99, depending on the model fitted and methodology. A stronger correlations within methodologies (0.83-0.99) than within models with different methodologies (0.51-0.63) were obtained.

Comparison between sire-maternal grandsire and animal models for genetic evaluation of longevity in a dairy cattle population with small herds

Survival analysis techniques for sire-maternal grandsire (MGS) and animal models were used to test the genetic evaluation of longevity in a Slovenian Brown cattle population characterized by small herds. Three genetic models were compared: a sire-MGS model for bulls and an approximate animal model based on estimated breeding values (EBV) from the sire-MGS model for cows, an animal model, and an animal model based on the estimated variance components from the sire-MGS model. In addition, modeling the contemporary group effect was defined as either a herd or a herd-year (HY) effect. With various restrictions on the minimum HY group size (from 1 to 10 cows per HY), changes in estimates of variance components, and consequently also in EBV, were observed for the sire-MGS and animal models. Variance of contemporary group effects decreased when an HY effect was fitted instead of a herd effect. In the case of a sire-MGS model, estimates of additive genetic variance were mostly robust to changes in minimum HY group size or fitting herd or HY effect, whereas they increased in the animal model when HY instead of herd effects was fitted, possibly revealing some confounding between cow EBV and contemporary group effect. Estimated heritabilities from sire-MGS models were between 0.091 and 0.119 and were mainly influenced by the restriction on the HY group size. Estimated heritabilities from animal models were higher: between 0.125 and 0.160 when herd effect was fitted and between 0.171 and 0.210 when HY effect was fitted. Rank correlations between the animal model and the approximate animal model based on EBV from the sire-MGS model were high: 0.94 for cows and 0.93 for sires when a herd effect was fitted and 0.90 for cows and 0.93 for sires when an HY effect was fitted. Validation performed on the independent validation data set revealed that the correlation between sire EBV and daughter survival were slightly higher with the approximate animal model based on EBV from the sire-MGS model compared with the animal model. The correlations between the sire EBV and daughter survival were higher when the model included an HY effect instead of a herd effect. To avoid confounding and reduce computational requirements, it is suggested that the approximate animal model based on EBV from the sire-MGS model and HY as a contemporary group effect is an interesting compromise for practical applications of genetic evaluation of longevity in cattle populations.

Estimation of genetic parameters for longevity traits in dairy cattle: a review with focus on the characteristics of analytical models

Longevity is an economically important trait of dairy cattle for increasing the profitability of dairy management. The reasons for culling can be either voluntary (primarily productivity) or involuntary (primarily health and fertility). Longevity characteristics include: (i) true longevity (all culling reasons, including productivity); and (ii) functional longevity (all culling reasons, except productivity). Improvements to longevity are made to decrease the rate of involuntary culling rather than extend the herd life (HL). The proportional hazard model is useful for evaluating genetic ability for HL. However, the differences between estimates made using the proportional hazard model and those made using linear single or multiple-trait animal models are not clear. The model commonly used for evaluation differs among countries. Productive traits, udder traits, and feet and legs traits are genetically correlated with longevity, and consequently these traits are used to indirectly evaluate longevity. The reliability of estimates of genetic ability for longevity is increased by combining direct and indirect estimates. In Japan, HL is evaluated using the multiple-traits model. The genetic correlations between HL and other traits vary with the birth year. Therefore, these genetic correlations need to be reviewed regularly.

Competing risk analyses of longevity in Duroc sows with a special emphasis on leg conformation

A competing risk approach was used to evaluate the influence of several factors on culling risk for 587 Duroc sows. Three different analyses were performed according to whether sow failure was due to death during productive life (DE) or to one of two causes for voluntary culling: low productivity (LP) and low fertility (LF). Sow survival was analyzed by the Cox model. Year at first farrowing (batch effect) significantly affected sow survival in all three analyses (P < 0.05 for DE and P < 0.001 for LP and LF) whereas farm of origin accounted for relevant variation in the LP and LF analyses. LP culling increased with backfat thickness of more than 19 mm at the end of the growth period (P < 0.05), bad teat condition (P < 0.05) and reduced piglets born alive (P < 0.001). For the LF competing risk analysis, culling increased with age at first farrowing (P < 0.1). Special emphasis was placed on the influence of leg and teat conformation on sow survivability, although they did not affect sow failure due to DE (P > 0.1). The overall leg-conformation score significantly influenced sow longevity in LP (P < 0.001) and LF competing risk analyses (P < 0.001), showing a higher hazard ratio (HR) for poorly conformed sows (1.013 and 4.366, respectively) than for well-conformed sows (0.342 and 0.246, respectively). Survival decreased with the presence of abnormal hoof growth in LP and LF analyses (HR = 3.372 and 6.002, respectively; P < 0.001) and bumps or injuries to legs (HR = 4.172 and 5.839, respectively; P < 0.01). Plantigradism reduced sow survival in the LP analysis (P < 0.05), while sickle-hooked leg (P < 0.05) impaired sow survival in the fertility-specific analysis. Estimates of heritability for longevity related to LP culling ranged from 0.008 to 0.024 depending on the estimation procedure, whereas heritability values increased to between 0.017 and 0.083 in LF analysis. These analyses highlighted substantial discrepancies in the sources of variation and genetic background of sow longevity depending on the cause of failure. The estimated heritabilities suggested that direct genetic improvement for sow longevity seemed feasible, although only a small genetic progress was expected.

Genetics of crossbred sow longevity

The aim of this study was to estimate genetic parameters for longevity from Swedish crossbred sows to investigate the possibilities of selecting for this trait. Data were collected from 16 commercial piglet-producing herds, on crossbred (Landrace × Yorkshire) sows farrowing in the period 1 January 2001 to 31 December 2004. The data set with records on 10 373 sows was split into two sets according to the breed of the sire, i.e. Landrace sires (LS) or Yorkshire sires (YS). Removal hazard during productive life (PL) was analysed with survival analysis, using a sire model. Stayability from first to second litter (STAY12), stayability from first to third litter (STAY13), length of productive life (LPL) and lifetime production (LTP) were analysed with linear models, using an animal model. Females after the worst sire had 1.7 times higher (progeny of LS) and 2.4 times higher (progeny of YS) risk of removal than females after the best sire. Heritability for PL was estimated at 0.06 (LS) and 0.12 (YS). The heritabilities for the linear longevity traits ranged from 0.03 to 0.08. Genetic correlations between the four linear longevity traits were all high and positive (0.6 to 1.0), as were the phenotypic correlations (0.5 to 0.8). The correlations (Spearman rank) between the sire's estimated breeding values for all the five longevity traits were all significant (P < 0.001) and moderate to strong in both data sets. Estimated breeding value (EBV) correlations between the five longevity traits and traits included in the present Swedish breeding evaluation (Quality Genetics (QG)) were significant in a few cases. Significant and favourable EBV correlations were found between age at first farrowing and both STAY12 and STAY13 (-0.20 and -0.31), as well as between litter weight at 3 weeks and LPL and LTP (0.13 to 0.20). Significant and unfavourable EBV correlations were found between age at 100 kg and STAY12 (0.32), as well as between the exterior conformation score from testing station and PL (-0.20). The level of the estimated heritabilities for longevity indicates that genetic improvement of sow longevity would be possible. However, overall, there was no strong indirect selection for sow longevity with the current Swedish breeding evaluation (QG).

Genetic evaluation of ovulatory disorders in Austrian Fleckvieh cows: a comparison between linear models and survival analysis

The objective of this study was to compare linear models and survival analysis for genetic evaluation of ovulatory disorders, which included veterinary treatments of silent heat/anestrus and cystic ovaries. Data of 23 450 daughters of 274 Austrian Fleckvieh sires were analyzed. For linear model analyses, ovulatory disorders were defined as a binary response (presence or absence) in the time periods from calving to 150 days after calving and from calving to 300 days after calving. For survival analysis, ovulatory disorders were defined either as the number of days from calving to the day of the first treatment for an ovulatory disorder (uncensored record) or from calving to the day of culling, or the last day of the period under investigation (until 150 or 300 days after calving; censored record). Estimates of heritability were very similar (0.016 to 0.020) across methods and periods. Correlations between sire estimated breeding value from linear model and survival analysis were 0.98, whereas correlations between different time periods were somewhat lower (0.95 and 0.96). The results showed that the length of time period had a larger effect on genetic evaluation than methodology.

Comparison of linear, skewed-linear, and proportional hazard models for the analysis of lambing interval in Ripollesa ewes

Lambing interval is a relevant reproductive indicator for sheep populations under continuous mating systems, although there is a shortage of selection programs accounting for this trait in the sheep industry. Both the historical assumption of small genetic background and its unorthodox distribution pattern have limited its implementation as a breeding objective. In this manuscript, statistical performances of 3 alternative parametrizations [i.e., symmetric Gaussian mixed linear (GML) model, skew-Gaussian mixed linear (SGML) model, and piecewise Weibull proportional hazard (PWPH) model] have been compared to elucidate the preferred methodology to handle lambing interval data. More specifically, flock-by-flock analyses were performed on 31,986 lambing interval records (257.3 ± 0.2 d) from 6 purebred Ripollesa flocks. Model performances were compared in terms of deviance information criterion (DIC) and Bayes factor (BF). For all flocks, PWPH models were clearly preferred; they generated a reduction of 1,900 or more DIC units and provided BF estimates larger than 100 (i.e., PWPH models against linear models). These differences were reduced when comparing PWPH models with different number of change points for the baseline hazard function. In 4 flocks, only 2 change points were required to minimize the DIC, whereas 4 and 6 change points were needed for the 2 remaining flocks. These differences demonstrated a remarkable degree of heterogeneity across sheep flocks that must be properly accounted for in genetic evaluation models to avoid statistical biases and suboptimal genetic trends. Within this context, all 6 Ripollesa flocks revealed substantial genetic background for lambing interval with heritabilities ranging between 0.13 and 0.19. This study provides the first evidence of the suitability of PWPH models for lambing interval analysis, clearly discarding previous parametrizations focused on mixed linear models.