Symposium review: The choice and collection of new relevant phenotypes for fertility selection

Advances in our understanding of the estrous cycle and applications for improving targeted reproductive management in livestock

The scientific discipline of endocrinology has been invaluable to our understanding of the estrous cycle. In the second half of the twentieth century the development of immunoassay technologies provided a rapid and sensitive method to quantify circulating concentrations of reproductive hormones and relate them to stage of the estrous cycle and physiological status of the animal. Ovarian ultrasonography provided the ability to track the growth and regression of ovarian structures within the same animal across the estrous cycle in real time and, in combination with hormonal profiling, accurately identify mechanisms regulating the estrous cycle and early pregnancy. Before this, the best technique had been serial collections with each animal being a single endpoint. The availability of continuous data such as daily hormone concentrations and daily follicular measurements within animals led to the improvement of methods to synchronize estrus in each of the species. Unfortunately, the use of radio-immunoassays has been declining for two decades. While enzyme-linked immunosorbent assays have been developed for many endocrine, paracrine, and autocrine factors, their primary market is human medicine and rodent models of human health, leaving those available for livestock species economically infeasible. Automated sensors such as accelerometers apply the knowledge attained through decades of endocrinology and ultrasonography studies to identify females in estrus and measure parameters of the estrous cycle that are related to fertility. The ability of automated sensors to centralize and assimilate large amounts of behavioral and physiological data from numerous animals will enhance targeted reproductive management in livestock production systems.

Genomic prediction and validation strategies for reproductive traits in Holstein cattle across different Chinese regions and climatic conditions

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.

Invited review: Phenotyping strategies and genetic background of dairy cattle behavior in intensive production systems-From trait definition to genomic selection

Understanding and assessing dairy cattle behavior is critical for developing sustainable breeding programs and management practices. The behavior of individual animals can provide valuable information on their health and welfare status, improve reproductive management, and predict efficiency traits such as feed efficiency and milking efficiency. Routine genetic evaluations of animal behavior traits can contribute to optimizing breeding and management strategies for dairy cattle but require the identification of traits that capture the most important biological processes involved in behavioral responses. These traits should be heritable, repeatable, and measured in noninvasive and cost-effective ways in many individuals from the breeding populations or related reference populations. Although behavior traits are heritable in dairy cattle populations, they are highly polygenic, with no known major genes influencing their phenotypic expression. Genetically selecting dairy cattle based on their behavior can be advantageous because of their relationship with other key traits such as animal health, welfare, and productive efficiency, as well as animal and handler safety. Trait definition and longitudinal data collection are still key challenges for breeding for behavioral responses in dairy cattle. However, the more recent developments and adoption of precision technologies in dairy farms provide avenues for more objective phenotyping and genetic selection of behavior traits. Furthermore, there is still a need to standardize phenotyping protocols for existing traits and develop guidelines for recording novel behavioral traits and integrating multiple data sources. This review gives an overview of the most common indicators of dairy cattle behavior, summarizes the main methods used for analyzing animal behavior in commercial settings, describes the genetic and genomic background of previously defined behavioral traits, and discusses strategies for breeding and improving behavior traits coupled with future opportunities for genetic selection for improved behavioral responses.

A comprehensive meta-analysis of genetic parameters for resilience and productivity indicator traits in Holstein cattle

Selection for resilience indicator (RIND) traits in Holstein cattle is becoming an important breeding objective as the worldwide population is expected to be exposed to increased environmental stressors due to both climate change and changing industry standards. However, genetic correlations between RIND and productivity indicator (PIND) traits, which are already being selected for and have the most economic value, are often unfavorable. As a result, it is necessary to fully understand these genetic relationships when incorporating novel traits into selection indices, so that informed decisions can be made to fully optimize selection for both groups of traits. In the past 2 decades, there have been many estimates of RIND traits published in the literature, albeit in small populations. To provide valuable pooled summary estimates, a random-effects meta-analysis was conducted for heritability and genetic correlation estimates for PIND and RIND traits in worldwide Holstein cattle. In total, 926 heritability estimates for 9 PIND and 27 RIND traits, along with 362 estimates of genetic correlation (PIND × RIND traits) were collected. Resilience indicator traits were grouped into the following subgroups: Metabolic Diseases, Hoof Health, Udder Health, Fertility, Heat Tolerance, Longevity, and Other. Pooled estimates of heritability for PIND traits ranged from 0.201 ± 0.05 (energy-corrected milk) to 0.377 ± 0.06 (protein content), while pooled estimates of heritability for RIND traits ranged from 0.032 ± 0.02 (incidence of lameness, incidence of milk fever) to 0.497 ± 0.05 (measures of body weight). Pooled estimates of genetic correlations ranged from -0.360 ± 0.25 (protein content vs. milk acetone concentration) to 0.535 ± 0.72 (measures of fat-to-protein ratio vs. milk acetone concentration). Additionally, out of 243 potential genetic correlations between PIND and RIND traits that could have been reported, only 40 had enough published estimates to implement the meta-analysis model. Our results confirmed that the interactions between PIND and RIND traits are complex, and all relationships should be evaluated when incorporating novel traits into selection indices. This study provides a valuable reference for breeders looking to incorporate RIND traits for Holstein cattle into selection indices.

Mapping Expression Quantitative Trait Loci Targeting Candidate Genes for Pregnancy in Beef Cows

Despite collective efforts to understand the complex regulation of reproductive traits, no causative genes and/or mutations have been reported yet. By integrating genomics and transcriptomics data, potential regulatory mechanisms may be unveiled, providing opportunities to dissect the genetic factors governing fertility. Herein, we identified regulatory variants from RNA-Seq data associated with gene expression regulation in the uterine luminal epithelial cells of beef cows. We identified 4676 cis and 7682 trans eQTLs (expression quantitative trait loci) affecting the expression of 1120 and 2503 genes, respectively (FDR < 0.05). These variants affected the expression of transcription factor coding genes (71 cis and 193 trans eQTLs) and genes previously reported as differentially expressed between pregnant and nonpregnant cows. Functional over-representation analysis highlighted pathways related to metabolism, immune response, and hormone signaling (estrogen and GnRH) affected by eQTL-regulated genes (p-value ≤ 0.01). Furthermore, eQTLs were enriched in QTL regions for 13 reproduction-related traits from the CattleQTLdb (FDR ≤ 0.05). Our study provides novel insights into the genetic basis of reproductive processes in cattle. The underlying causal mechanisms modulating the expression of uterine genes warrant further investigation.

Estimation of direct and maternal covariance along with genetic and phenotypic trends of reproduction traits in Murrah buffalo

The research utilized data from 662 Murrah buffaloes meticulously recorded over 24 years (1996-2019) from historical pedigree sheets maintained at the buffalo farm of the Department of Livestock Production and Management (LPM) at Lala Lajpat Rai University of Veterinary and Animal Sciences (LUVAS), Hisar. A series of six univariate animal models were employed to calculate estimates of (co)variance components and heritability for first lactation reproduction traits. Among these models, Model 2 was identified as the best fit for age at first calving (AFC) and calving interval (CI), while Model 1 proved optimal for service period (SP) and conception rate (CR). The heritability estimates for AFC, SP, CR and CI across the models were ranged between 0.11 and 0.32, 0.01 and 0.03, 0.05 and 0.06, and 0.01 and 0.06, respectively. Maternal effects (m2 ) were observed in AFC and CI, ranging from 0.10 to 0.20 and 0.01 to 0.03, respectively. Across all three traits, there was a consistent negative genetic correlation (-0.75 to -0.92) between direct additive and maternal effects. The breeding values for AFC, SP, CR and CI varied within specific ranges from -32.85 to 44.33 days, -15.61 to 28.42 days, -7.41 to 6.48% and -20.64 to 35.79 days, respectively. Significantly, Spearman's rank correlation analysis revealed highly significant relationships (p < .01) between the breeding values of different models, indicating strong and consistent associations within these traits. These findings underscore the stable and reliable connections observed within the breeding values for these essential reproductive traits across the various models used in the study. The majority of reproductive traits showed favourable negative trends, indicating a positive outcome. A decrease in AFC, SP and CI suggests an extended economic life for the animals. Additionally, the upward trends in CR reflect positive indications of effective management practices and skilled operational procedures.

Transmission ratio distortion regions in the context of genomic evaluation and their effects on reproductive traits in cattle

Transmission ratio distortion (TRD), which is a deviation from Mendelian expectations, has been associated with basic mechanisms of life such as sperm and ova fertility and viability at developmental stages of the reproductive cycle. In this study different models including TRD regions were tested for different reproductive traits [days from first service to conception (FSTC), number of services, first service nonreturn rate (NRR), and stillbirth (SB)]. Thus, in addition to a basic model with systematic and random effects, including genetic effects modeled through a genomic relationship matrix, we developed 2 additional models, including a second genomic relationship matrix based on TRD regions, and TRD regions as a random effect assuming heterogeneous variances. The analyses were performed with 10,623 cows and 1,520 bulls genotyped for 47,910 SNPs, 590 TRD regions, and several records ranging from 9,587 (FSTC) to 19,667 (SB). The results of this study showed the ability of TRD regions to capture some additional genetic variance for some traits; however, this did not translate into higher accuracy for genomic prediction. This could be explained by the nature of TRD itself, which may arise in different stages of the reproductive cycle. Nevertheless, important effects of TRD regions were found on SB (31 regions) and NRR (18 regions) when comparing at-risk versus control matings, especially for regions with allelic TRD pattern. Particularly for NRR, the probability of observing nonpregnant cow increases by up to 27% for specific TRD regions, and the probability of observing stillbirth increased by up to 254%. These results support the relevance of several TRD regions on some reproductive traits, especially those with allelic patterns that have not received as much attention as recessive TRD patterns.

Harnessing Genomics and Transcriptomics Approaches to Improve Female Fertility in Beef Cattle-A Review

Female fertility is the foundation of the cow-calf industry, impacting both efficiency and profitability. Reproductive failure is the primary reason why beef cows are sold in the U.S. and the cause of an estimated annual gross loss of USD 2.8 billion. In this review, we discuss the status of the genomics, transcriptomics, and systems genomics approaches currently applied to female fertility and the tools available to cow-calf producers to maximize genetic progress. We highlight the opportunities and limitations associated with using genomic and transcriptomic approaches to discover genes and regulatory mechanisms related to beef fertility. Considering the complex nature of fertility, significant advances in precision breeding will rely on holistic, multidisciplinary approaches to further advance our ability to understand, predict, and improve reproductive performance. While these technologies have advanced our knowledge, the next step is to translate research findings from bench to on-farm applications.

Genomic prediction of fertility and calving traits in Holstein cattle based on models including epistatic genetic effects

The goal of this study was to investigate whether the inclusion of genomic information and epistatic (additive by additive) genetic effects would increase the accuracy of predicting phenotypes adjusted for known environmental effects, reduce prediction bias and minimize the confounding between additive and additive by additive epistatic effects on fertility and calving traits in Holstein cattle. Phenotypic and genotypic records were available for 6090 cows. Eight cow traits were assessed including 56-day nonreturn rate (NRR), number of services (NS), calving to first insemination (CTFS), first insemination to conception (FSTC), gestation length (GL), calving ease (CE), stillbirth (SB) and calf size (CZ). Four scenarios were assessed for their ability to predict adjusted phenotypes, which included: (1) traditional pedigree-based Best Linear Unbiased Prediction (P-BLUP) for additive genetic effects (PA); (2) P-BLUP for additive and epistatic (additive by additive) genetic effects (PAE); (3) genomic BLUP (G-BLUP) for additive genetic effects (GA); and (4) G-BLUP for additive and epistatic genetic effects (GAEn, where n = 1-3 depending on the alternative ways to construct the epistatic genomic matrix used). Constructing epistatic relationship matrix as the Hadamard product of the additive genomic relationship matrix (GAE1), which is the usual method and implicitly assumes a model that fits all pairwise interactions between markers twice and includes the interactions of the markers with themselves (dominance). Two additional constructions of the epistatic genomic relationship matrix were compared to test whether removing the double counting of interactions and the interaction of the markers with themselves (GAE2), and removing double counting of interactions between markers, but including the interaction of the markers with themselves (GAE3) would had an impact on the prediction and estimation error correlation (i.e. confounding) between additive and epistatic genetic effects. Fitting epistatic genetic effects explained up to 5.7% of the variance for NRR (GAE3), 7.7% for NS (GAE1), 11.9% for CTFS (GAE3), 11.1% for FSTC (GAE2), 25.7% for GL (GAE1), 2.3% for CE (GAE1), 14.3% for SB (GAE3) and 15.2% for CZ (GAE1). Despite a substantial proportion of variance being explained by epistatic effects for some traits, the prediction accuracies were similar or lower for GAE models compared with pedigree models and genomic models without epistatic effects. Although the prediction accuracy of direct genomic values did not change significantly between the three variations of the epistatic genetic relationship matrix used, removing the interaction of the markers with themselves reduced the confounding between additive and additive by additive epistatic effects. These results suggest that epistatic genetic effects contribute to the variance of some fertility and calving traits in Holstein cattle. However, the inclusion of epistatic genetic effects in the genomic prediction of these traits is complex and warrant further investigation.

Genetic parameters for various semen production and quality traits and indicators of male and female reproductive performance in Nellore cattle

BACKGROUND

Given the economic relevance of fertility and reproductive traits for the beef cattle industry, investigating their genetic background and developing effective breeding strategies are paramount. Considering their late and sex-dependent phenotypic expression, genomic information can contribute to speed up the rates of genetic progress per year. In this context, the main objectives of this study were to estimate variance components and genetic parameters, including heritability and genetic correlations, for fertility, female precocity, and semen production and quality (andrological attributes) traits in Nellore cattle incorporating genomic information.

RESULTS

The heritability estimates of semen quality traits were low-to-moderate, while moderate-to-high estimates were observed for semen morphological traits. The heritability of semen defects ranged from low (0.04 for minor semen defects) to moderate (0.30 for total semen defects). For seminal aspect (SMN_ASPC) and bull reproductive fitness (BULL_FIT), low (0.19) and high (0.69) heritabilities were observed, respectively. The heritability estimates for female reproductive traits ranged from 0.16 to 0.39 for rebreeding of precocious females (REBA) and probability of pregnancy at 14 months (PP14), respectively. Semen quality traits were highly genetically correlated among themselves. Moderate-to-high genetic correlations were observed between the ability to remain productive in the herd until four years of age (stayability; STAY) and the other reproductive traits, indicating that selection for female reproductive performance will indirectly contribute to increasing fertility rates. High genetic correlations between BULL_FIT and female reproductive traits related to precocity (REBA and PP14) and STAY were observed. The genetic correlations between semen quality and spermatic morphology with female reproductive traits ranged from -0.22 (REBA and scrotal circumference) to 0.48 (REBA and sperm vigor). In addition, the genetic correlations between REBA with semen quality traits ranged from -0.23 to 0.48, and with the spermatic morphology traits it ranged from -0.22 to 0.19.

CONCLUSIONS

All male and female fertility and reproduction traits evaluated are heritable and can be improved through direct genetic or genomic selection. Selection for better sperm quality will positively influence the fertility and precocity of Nellore females. The findings of this study will serve as background information for designing breeding programs for genetically improving semen production and quality and reproductive performance in Nellore cattle.

Fertility and survival of Swedish Red and White × Holstein crossbred cows and purebred Holstein cows

Swedish Red and White × Holstein (S×H) cows were compared with pure Holstein (HOL) cows for fertility and survival traits in 2 commercial dairy farms in central-southern Córdoba province, Argentina, over 6 years (2008-2013). The following traits were evaluated: first service conception rate (FSCR), overall conception rate (CR), number of services per conception (SC), days open (DO), mortality rate, culling rate, survival to subsequent calvings, and length of productive life (LPL). The data set consisted of 506 lactations from 240 S×H crossbred cows and 1,331 lactations from 576 HOL cows. The FSCR and CR were analyzed using logistic regression, DO and LPL were analyzed using a Cox's proportional hazards regression model, and differences of proportions were calculated for mortality rate, culling rate, and survival to subsequent calvings. The S×H cows were superior to HOL cows in overall lactations for all the fertility traits (+10.5% FSCR, +7.7% CR, -0.5 SC, and 35 fewer DO). During the first lactation, S×H cows were superior to HOL cows for all fertility traits (+12.8% FSCR, +8.0% CR, -0.4 SC, and 34 fewer DO). In the second lactation, S×H cows exhibited lower SC (-0.5) and 21 fewer DO than HOL cows. In the third or greater lactations, S×H cows showed higher FSCR (+11.0%) and CR (+12.2%), lower SC (-0.8), and 44 fewer DO than pure HOL cows. In addition, S×H cows had a lower mortality rate (-4.7%) and a lower culling rate (-13.7%) than HOL cows. Due to the higher fertility and lower mortality and culling rates, the S×H cows had higher survival to the second (+9.2%), third (+16.9%), and fourth (+18.7%) calvings than HOL cows. Because of these results, S×H cows had longer LPL (+10.3 mo) than HOL cows. These results indicate that S×H cows had higher fertility and survival than HOL cows on commercial dairy farms in Argentina.

Genetic and nongenetic variation of heifer fertility in Italian Holstein cattle

Excellent fertility performance is important to maximize farmers' profit and to reduce the number of culled animals. Although female fertility of adult cows has been included in Italian Holstein breeding objectives since 2009, little has been done to quantify genetic variation of heifer fertility characteristics so far. The aim of the present study was to estimate genetic parameters of 4 fertility traits in nulliparous Italian Holstein heifers and to develop an aggregate selection index to improve heifer fertility. Data were retrieved from the national fertility database and included information on insemination, calving, and pregnancy diagnosis dates. The investigated phenotypes (mean ± standard deviation) were age at first insemination (AFI, mo; 17.25 ± 2.89), nonreturn rate at 56 d from the first insemination (NRR56, binary; 0.78 ± 0.41), conception rate at first insemination (CR, binary; 0.61 ± 0.49), and interval from first to last insemination (IFL, d; 26.09 ± 51.85). Genetic parameters were estimated using a 4-trait animal model that included the following fixed effects: herd-year of birth and month of birth for AFI, and herd-year-season of birth and month-year of insemination for IFL, NRR56, and CR; the animal additive genetic effect (fitted to the pedigree-based relationship matrix) was considered as a random term. An aggregate index was developed from the estimated additive genetic (co)variance matrix by considering CR as the breeding goal and AFI, NRR56, and IFL as selection criteria. Heritability estimates from average covariance matrices ranged from 0.012 (CR) to 0.015 (IFL), with the exception of AFI (0.071). Conception rate at first insemination was strongly correlated with both IFL (-0.730) and NRR56 (0.668), and weakly to AFI (-0.065), and the relative emphasis placed on each selection criteria in the aggregate index was 10%, 47%, and 43% for AFI, IFL, and NRR56, respectively. The results of the present study suggest that heifer fertility should be considered as an additional trait in the breeding objectives of Italian Holstein.

Synchronization of breeding and its impact on genetic parameters and evaluation of female fertility traits

Achieving an acceptable level of fertility in herds is difficult for many dairy producers because identifying cows in estrus has become challenging owing to poor estrus expression, increased herd size, and lack of time and skilled labor for estrus detection. As a result, synchronization of estrus is often used to manage reproduction. The aims of this study were (1) to identify artificial inseminations (AI) that were performed following synchronization and (2) to assess the effect of synchronization on genetic parameters and evaluation of fertility traits. This study used breeding data collected between 1995 and 2021 from over 4,600 Australian dairy herds that had at least 30 matings per year. Because breeding methods were not reported, the recording pattern of breeding dates showing a large proportion of the total AI being recorded on a single date of the year served as an indicator of synchronization. First, the proportion of AI recorded on each day of the year was calculated for each herd-year. Subsequently, synchronization was defined when a herd with, for instance, only 30 matings in a year, had at least 0.20 or more AI on the same day. As the number of breedings in a herd-year increased, the threshold for classifying AI was continuously reduced from 0.20 to as low as 0.03 under the assumption that mating of many cows on a single date becomes increasingly difficult without synchronization. From the current data, we deduced that 0.11 of all AI were possibly performed following synchronization (i.e., timed AI, TAI). The proportion of AI classified as TAI increased over time and with herd size. Although the deviation from equal numbers of mating on 7 d of the week was not used for classifying AI, 0.44 of AI being categorized as TAI were performed on just 2 d of the week. When data classified as TAI were used for estimating genetic parameters and breeding values, the interval between calving and first service (CFS) was found to be the most affected trait. The phenotypic and additive genetic variance and heritability, as well as variability and reliability of estimated breeding values of bulls and cows for CFS were lower for TAI than for AI performed following detected estrus (i.e., estrus-detected AI, EAI). For calving interval, first service nonreturn rate (FNRR), and successful calving rate to first service, genetic correlations between the same trait measured in TAI and EAI were close to 1, in contrast to 0.55 for CFS. The lower genetic variances and heritabilities for FNRR and calving interval in TAI than in EAI suggests that synchronization reduces the genetic variability of fertility. In conclusion, TAI makes CFS an ineffective measure of fertility. One approach to minimize this effect on genetic evaluations is to identify TAI (using the method described for example) and then set the CFS of these cows as missing records when running multitrait genetic evaluations of fertility traits that include CFS. In the long term, the most practical and accurate way to reduce the effect of synchronization on genetic evaluations is to record TAI along with mating data.

Predicting fertility from sperm motility landscapes

Understanding the organisational principles of sperm motility has both evolutionary and applied impact. The emergence of computer aided systems in this field came with the promise of automated quantification and classification, potentially improving our understanding of the determinants of reproductive success. Yet, nowadays the relationship between sperm variability and fertility remains unclear. Here, we characterize pig sperm motility using t-SNE, an embedding method adequate to study behavioural variability. T-SNE reveals a hierarchical organization of sperm motility across ejaculates and individuals, enabling accurate fertility predictions by means of Bayesian logistic regression. Our results show that sperm motility features, like high-speed and straight-lined motion, correlate positively with fertility and are more relevant than other sources of variability. We propose the combined use of embedding methods with Bayesian inference frameworks in order to achieve a better understanding of the relationship between fertility and sperm motility in animals, including humans.

Dimension reduction methods on porcine sperm motility landscapes reveal heterogeneity and hierarchy in sperm movement behavior and show high-speed and straight-lined motion as predictive features of fertility.

Reproductive tract size and position score: Estimation of genetic parameters for a novel fertility trait in dairy cows

The dairy industry is moving toward selecting animals with better fertility to decrease the economic losses linked to reproductive issues. The reproductive tract size and position score (SPS) was recently developed in physiological studies as an indicator of pregnancy rate and the number of services to conception. Cows are scored as SPS 1, 2, or 3 based on the size of their reproductive tract and its position in the pelvis, as determined by transrectal palpation. The objective of this study was to estimate genetic parameters for SPS to assess its potential as a novel fertility trait. Phenotypes were collected at the University of British Columbia's research herd from 2017 to 2020, consisting of 3,247 within- and across-lactation SPS records from 490 Holstein cows. A univariate animal model was used to estimate the variance components for SPS. Both threshold and linear models were fit under a Bayesian approach and the results were compared using the Spearman rank correlation (r) between the estimated breeding values. The 2 models ranked the animals very similarly (r = 0.99), and the linear model was selected for further analysis. Genetic correlations with other currently evaluated traits were estimated using a bivariate animal model. The posterior means (± posterior standard deviation) for heritability and repeatability within- and across-lactation were 0.113 (± 0.013), 0.242 (± 0.012), and 0.134 (± 0.014), respectively. The SPS showed null correlations with production traits and favorable correlations with traditional fertility traits, varying from -0.730 (nonreturn rate) to 0.931 (number of services). Although preliminary, these results are encouraging because SPS seems to be more heritable than and strongly genetically correlated with number of services, nonreturn rate, and first service to conception, indicating potential for effective indirect selection response on these traits from SPS genetic selection. Therefore, further studies with larger data sets to validate these findings are warranted.

Cow activity measurements can be used to define new fertility traits for use in genetic evaluation

Cow activity measurements are widely used in herd management tools for estrus detection. The aim of this study was to examine whether a new trait based on activity measures can be useful for genetic evaluation of cow fertility in Norwegian Red dairy cattle. Data from 284 herds with Lely milking robot were collected. Daily measurements of cow activity level were available from Lely activity tags and included data from 13,224 lactations of 8,139 Norwegian Red cows. We analyzed daily activity and included records from 10 to 150 d in milk for cows with at least 50 records. The trait analyzed was interval from calving to first high activity (CFHA). In total 87% of the cows had at least one episode of high activity recorded. The mean (standard deviation) of CFHA was 42 (28) days. A linear animal repeatability model with fixed effects of month-year of calving, age-parity, and herd, and random animal and permanent environment effects was used for estimation of variance components. The trait CFHA showed significant genetic variation with a heritability of 0.05 (0.01). This trait reflects the cow's ability to return to estrus cycle and show estrus after calving, which are important aspects of cow fertility.

Associations between anogenital distance and measures of fertility in lactating North American Holstein cows: A validation study

Anogenital distance (AGD) has been defined in dairy cows as the distance from the center of the anus to the base of the clitoris. Initial reports on nulliparous Holstein heifers and first- and second-parity Holstein cows have found inverse relationships between AGD and measures of fertility. Our primary objective was to determine the relationship between AGD and measures of fertility in a larger population of North American Holstein cows to validate our previous finding that AGD is inversely related to fertility. Secondary objectives were to determine the associations between AGD and parity, and milk yield. Using digital calipers, we measured AGD in 4,709 Holstein cows [mean ± standard deviation (SD); parity 2.3 ± 1.4; days in milk (DIM) 154 ± 94; 305-d mature equivalent (ME) milk yield 13,759 ± 2,188 kg] from 18 herds in Western Canada and 1 herd in the USA. Anogenital distance (mm) was normally distributed with a mean (±SD) of 132 ± 12, ranging from 95 to 177, and a median of 133. Anogenital distance was linearly but inversely associated with pregnancy to first artificial insemination (P/AI1). For every 1-mm increase in AGD, the estimated probability of P/AI1 decreased by 0.8%. The optimum AGD cut-point that predicted probability of P/AI1 with sensitivity and specificity of 45 and 55%, respectively, was 129 mm. Consequently, data were categorized into either short (≤129) or long (>129) AGD groups across parities, and associations between AGD, parity (first, second, and third+), and fertility measures were determined. Rates of P/AI1 were greater (36 vs. 30%) in short- than in long-AGD cows; short-AGD cows required fewer AI per conception (2.3 vs. 2.4) and had fewer days open (137 vs. 142), and a greater proportion of short-AGD cows (67 vs. 64%) was pregnant by 150 DIM compared with long-AGD cows. The rates of pregnancy up to 150 (hazard ratio of 0.91) and 250 DIM (hazard ratio of 0.93) were smaller in long- than in short-AGD cows. Anogenital distance had a weak positive association with both parity (r = 0.22) and 305-d ME milk yield (r = 0.04). Results indicate an inverse relationship between AGD and measures of fertility in lactating cows, validating our earlier report. We infer that although selecting cows for short AGD is expected to have an adverse effect on milk yield, the anticipated gain in fertility will outweigh the small decline in milk yield, strengthening the potential of AGD as a novel reproductive phenotype for use in future breeding programs to improve fertility.

Identifying pleiotropic variants and candidate genes for fertility and reproduction traits in Holstein cattle via association studies based on imputed whole-genome sequence genotypes

Background

Genetic progress for fertility and reproduction traits in dairy cattle has been limited due to the low heritability of most indicator traits. Moreover, most of the quantitative trait loci (QTL) and candidate genes associated with these traits remain unknown. In this study, we used 5.6 million imputed DNA sequence variants (single nucleotide polymorphisms, SNPs) for genome-wide association studies (GWAS) of 18 fertility and reproduction traits in Holstein cattle. Aiming to identify pleiotropic variants and increase detection power, multiple-trait analyses were performed using a method to efficiently combine the estimated SNP effects of single-trait GWAS based on a chi-square statistic.

Results

There were 87, 72, and 84 significant SNPs identified for heifer, cow, and sire traits, respectively, which showed a wide and distinct distribution across the genome, suggesting that they have relatively distinct polygenic nature. The biological functions of immune response and fatty acid metabolism were significantly enriched for the 184 and 124 positional candidate genes identified for heifer and cow traits, respectively. No known biological function was significantly enriched for the 147 positional candidate genes found for sire traits. The most important chromosomes that had three or more significant QTL identified are BTA22 and BTA23 for heifer traits, BTA8 and BTA17 for cow traits, and BTA4, BTA7, BTA17, BTA22, BTA25, and BTA28 for sire traits. Several novel and biologically important positional candidate genes were strongly suggested for heifer (SOD2, WTAP, DLEC1, PFKFB4, TRIM27, HECW1, DNAH17, and ADAM3A), cow (ANXA1, PCSK5, SPESP1, and JMJD1C), and sire (ELMO1, CFAP70, SOX30, DGCR8, SEPTIN14, PAPOLB, JMJD1C, and NELL2) traits.

Conclusions

These findings contribute to better understand the underlying biological mechanisms of fertility and reproduction traits measured in heifers, cows, and sires, which may contribute to improve genomic evaluation for these traits in dairy cattle.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08555-z.

Genetic and Genomic Analyses of Service Sire Effect on Female Reproductive Traits in Holstein Cattle

Fertility and reproductive performance are key drivers of dairy farm profitability. Hence, reproduction traits have been included in a large majority of worldwide dairy cattle selection indexes. The reproductive traits are lowly heritable but can be improved through direct genetic selection. However, most scientific studies and dairy cattle breeding programs have focused solely on the genetic effects of the dam (GED) on reproductive performance and, therefore, ignored the contribution of the service sire in the phenotypic outcomes. This study aimed to investigate the service sire effects on female reproductive traits in Holstein cattle from a genomic perspective. Genetic parameter estimation and genome-wide association studies (GWAS) were performed for the genetic effect of service sire (GESS) on conception rate (CR), 56-day non-return rate (NRR56), calving ease (CE), stillbirth (SB), and gestation length (GL). Our findings indicate that the additive genetic effects of both sire and dam contribute to the phenotypic variance of reproductive traits measured in females (0.0196 vs. 0.0109, 0.0237 vs. 0.0133, 0.0040 vs. 0.0289, 0.0782 vs. 0.0083, and 0.1024 vs. 0.1020 for GESS and GED heritability estimates for CR, NRR56, CE, SB, and GL, respectively), and these two genetic effects are positively correlated for SB (0.1394) and GL (0.7871). Interestingly, the breeding values for GESS on insemination success traits (CR and NRR56) are unfavorably and significantly correlated with some production, health, and type breeding values (ranging from -0.449 to 0.274), while the GESS values on calving traits (CE, SB, and GL) are usually favorably associated with those traits (ranging from -0.493 to 0.313). One hundred sixty-two significant single-nucleotide polymorphisms (SNPs) and their surrounding protein-coding genes were identified as significantly associated with GESS and GED, respectively. Six genes overlapped between GESS and GED for calving traits and 10 genes overlapped between GESS for success traits and calving traits. Our findings indicate the importance of considering the GESS when genetically evaluating the female reproductive traits in Holstein cattle.

Associations between the breeding values of Holstein-Friesian bulls and longevity and culling reasons of their daughters

Taking into account functional traits in the breeding practice should lead to a longer productive life of cows. However, despite the increased contribution of these traits in bull selection indices, their daughters are frequently culled as early as the 2nd or 3rd lactation. The problem is whether and to what extent the genetic potential of animals is realized in the production practice. Therefore, the purpose of this study was to determine the associations between the breeding value (BV) of bulls and their daughters for cow longevity and culling reasons in the Holstein-Friesian cattle population in Poland. Data for 532 062 cows culled in 2012, 2015, and 2018 were analyzed. A majority of 5 045 cow sires originated from Poland, Germany, France, the Netherlands, and the United States. The highest variation in the contribution of culling reasons was for the cows culled at the age of 2-4 years. The contribution of the culling reasons, analyzed in relation to the cow culling age, remained similar and the only exception was culling because of old age, for which a significant increase was observed only for the culling age of at least 9 years (13.8%), which was reached by only 7.3% of the cows. The sires were characterized by generally high BV for conformation and reproductive traits. However, they had, at most, the average genetic potential for functional longevity. There were a number of beneficial associations found between the BV of bulls and the distribution of culling reasons in their daughters. For example, it concerns relations between the somatic cell score in milk and culling due to udder diseases and low milk yield, between the interval from calving to first insemination and low milk yield, between the protein yield and old age, or between the BV for certain conformation traits (size, udder) and cow culling due to age. In these cases, as the BV increased for a given trait, the contribution of the corresponding cow culling reason tended to decrease. Our study showed that it seems reasonable to consider Holstein-Friesian cows aged at least 9 years at culling to be long-living animals. This is primarily evidenced by the rapid increase in the culling due to old age in relation to younger cows. Nowadays the above age limit can be suggested as a criterion of longevity for Holstein-Friesian cows but the criterion should be updated to the relation genotype-environment-economy that tends to change over time.

Estimated genetic parameters for all genetically evaluated traits in Canadian Holsteins

Genetic improvement is a crucial tool to deal with the increasing demand for high quality, sustainably produced dairy. Breeding programs are based on genetic parameters, such as heritability and genetic correlations, for economically important traits in a population. In this study, we estimated population genetic parameters and genetic trends for 67 traits evaluated on heifers and first-lactation Canadian Holstein cows. The data consisted of approximately 500,000 records with pedigree information collected from 1980 to 2019. Genetic parameters were estimated using bivariate linear animal models under a Bayesian approach. Analyses for the 67 traits resulted in 2,211 bivariate combinations, from which the estimated genetic parameters are reported here. The most highly heritable traits were fat percent (0.66) and protein percent (0.69), followed by stature (0.47). Lowest heritabilities (0.01) were observed for disease-related traits, such as lameness and toe ulcer, and calf survival. The genetic correlations between gestation length, calf size, and calving ease measured on both heifer and cows were close to unity. On the other hand, traits such as body condition score and pin width, cystic ovaries and sole ulcer, rear teat placement, and toe ulcer were genetically unrelated. This study reports genetic parameters that have not been previously published for Canadian Holstein cows, and provides updates of those previously estimated. These estimates are useful for building new indexes, updating existing selection indexes, and for predicting correlated responses due to inclusion of novel traits in the breeding programs.

Relationship of anogenital distance with fertility in nulliparous Holstein heifers

Anogenital distance (AGD), defined as the distance from the center of the anus to the base of the clitoris, in lactating dairy cows of first and second parity, has been reported to be inversely related to fertility and moderately heritable. Thus, AGD may be a useful reproductive phenotype for future genetic selection to improve fertility. The objectives of this study were to (1) characterize AGD in nulliparous dairy heifers; and (2) determine if the inverse relationship between AGD and fertility, found in lactating dairy cows, is also evident in nulliparous heifers. We measured AGD in 1,692 Holstein heifers from 16 herds in Western Canada (Alberta and British Columbia) and one herd in the United States (Washington State). Data were analyzed using MEANS, UNIVARIATE, LOGISTIC, ROC, GLIMMIX, and LIFETEST procedures of SAS (SAS Institute Inc.). Mean (±standard deviation) age at AGD measurement was 13.9 ± 1.5 mo, and AGD was normally distributed with a mean of 107.3 ± 10.5 mm, ranging from 69 to 142 mm. With every 1-mm increase in AGD, the predicted probability of pregnancy was reduced by 1.9%. Receiver operating characteristic curve analysis was used to determine the optimum threshold AGD that predicted the probability of pregnancy. Based on the optimum threshold AGD, data from heifers were categorized into short (≤110 mm) and long (>110 mm) AGD groups, and associations between AGD groups and fertility measures were determined. Heifers with short AGD required fewer services per conception (1.5 vs. 1.7) than heifers with long AGD. Consequently, heifers with short AGD conceived earlier (448.4 vs. 454.3 d) and had greater pregnancy to first AI than those with long AGD (58.3 vs. 49.6%). Moreover, heifers with long AGD had reduced hazard (hazard ratio of 0.59) for pregnancy up to 450 d of life compared with those with short AGD. In summary, AGD was normally distributed and highly variable in the population. In addition, an inverse relationship between AGD and fertility measures in nulliparous heifers was evident, confirming an earlier report of a similar relationship in lactating dairy cows. These findings strengthen the potential for AGD to be used as a fertility trait and management tool in future selection programs.

Herd manager attitudes and intentions regarding the selection of high-fertility EBV sires in Australia

Reproductive performance in dairy cattle has declined over the last 50 years as an unintended consequence of selection for high milk yield. Since the early 2000s, dairy geneticists have released successive versions of fertility estimated breeding values (EBV) to assist in reversing this trend. At the herd level, fertility EBV can help managers accelerate improvements in reproductive performance by acting as a second selection criteria when used in tandem with a breeding index. However, use of the fertility EBV in sire selection currently varies between herd managers. The aim of this study was to better understand the reasons why herd managers choose or do not choose to select high-fertility EBV sires, using the Theory of Planned Behavior (TPB) as a social research framework. Thirty-five Victorian dairy herd managers were recruited as part of a larger study investigating the daughter fertility Australian Breeding Value and interviewed using a series of questions examining TPB constructs. The interviews were recorded and transcribed using template analysis. A wide range of herd manager types were enrolled into the study, with representation from diverse systems. Out of the 35 herd managers, 27 included fertility in their list of high-priority breeding objectives. A wide variation in results was consistent with previous studies that have demonstrated marked heterogeneity in herd manager attitudes toward bull selection. Herd manager-perceived barriers to selection of sires with high daughter fertility EBV included a lack of high daughter fertility bulls with other desirable traits, a lack of trust in the fertility EBV or in the Australian EBV system, difficulty in interpreting international proofs, information overload, semen prices, low bull reliability, and difficulty in understanding bull catalogs. Not all herd managers found the process problematic, however, particularly if a breeding consultant was employed to select all or most of the sires. Herd manager-perceived barriers for choosing to select daughter fertility as a breeding objective include a lack of awareness of the EBV, a lack of interest in genetics in general, low confidence in the impact of genetic selection for fertility, and a feeling that fertility was not important for their production system. The results of this study suggest that animal geneticists and on-farm service providers need to work together to allow the opportunities arising from appropriate use of fertility EBV to be realized more broadly across the dairy industry.

Evaluation of animal models to explore the influence of maternal genetic and maternal permanent environment effect on reproductive performance of Jersey crossbred cattle

The present study was conducted on 1,002 reproductive records of 430 Jersey crossbred cattle, descended from 57 sires and 198 dams, maintained at the Eastern Regional Station of ICAR-National Dairy Research Institute, Kalyani, Nadia, West Bengal, India to investigate the influence of direct genetic, maternal genetic and maternal permanent environmental effect on three most important reproductive traits viz., number of service per conception (NSPC), days open (DO) and calving interval (CI) of Jersey crossbred cattle. Six single-trait animal models (including or excluding maternal genetic or permanent environmental effects) were fitted to analyse these traits, and the best model was chosen after testing the significant increase in the log-likelihood values when additional parameters were added in the model. Direct heritability estimates for NSPC, DO and CI from the best model were 0.10, 0.14 and 0.20, respectively. The maternal permanent environmental (c² ) effects on reproductive traits accounted for almost negligible fraction of the total phenotypic variance in this study. The maternal genetic effects (m² ) also contributed very little (0%-3%) to the total phenotypic variance except for CI where it was important and accounted for 20% of phenotypic variance. A significantly large negative genetic correlation was observed between direct and maternal genetic effects for all traits, suggesting the presence of antagonistic relationship between dam's direct additive component and daughter's additive genetic component. Results suggest that both direct and maternal effects were important only for CI but not for other traits. Therefore, both direct additive effects and maternal genetic effect need to be considered for improving this trait by selection.

Estimates of intra- and interclass correlation coefficients for rump touches and the number of steps during estrus in postpartum cows

Estrus traits have economic value in dairy production systems and could be incorporated into genetic selection indices. In an effort to further understand selection responses, 2 studies were performed to estimate the intra- and interclass correlation coefficients for estrus traits. Holstein-Friesian cows (n = 1,197; study 1) across 5 pasture-based grazing dairy herds were fitted with a capacitive touch sensing (CTS) device on the rump (FlashMate, Farmshed Labs Limited, Hamilton, New Zealand). The daily number of rump touches were subjected to a peak detection program to objectively identify periods of increased rump touches above baseline (indicative of estrus). The number of times touched and the sum of the touch duration were used to compare farms and estimate the intraclass correlation (repeatability). For study 2, postpartum Holstein (n = 85) and Guernsey (n = 5) cows in a confinement-style dairy were used. Cows were fitted with an IceQube accelerometer (IceRobotics Ltd., Edinburgh, United Kingdom) to measure steps taken per hour and a CTS device was applied to both rumps. The interclass correlation for the number of rump touches and number of steps taken during estrus was calculated. Data collected from 5 herds (study 1) demonstrated a 2- to 3-fold difference between herds in the number of rump touches and total touch time during estrus. The intraclass correlation (repeatability; estimates of maximum heritability) for rump touches during estrus was 0.22. For study 2, the number of steps and the number of rump touches during estrus increased in a synchronous manner. The intraclass correlation (repeatability) for number of steps during estrus was 0.26. The interclass correlation (r) for the number of rump touches and the number of steps was 0.46 (R² = 0.21). Based on the R², at least 20% of the variation in the number of steps during estrus was explained by the number of touches to the rump of the cow. Selecting cows for the number of steps taken during estrus could increase the number of rump touches (mounts, chin rests, and so on, received from other cows) if a genetic correlation exists for the phenotypic correlation that we observed.

Large-Scale Phenotyping of Livestock Welfare in Commercial Production Systems: A New Frontier in Animal Breeding

Genomic breeding programs have been paramount in improving the rates of genetic progress of productive efficiency traits in livestock. Such improvement has been accompanied by the intensification of production systems, use of a wider range of precision technologies in routine management practices, and high-throughput phenotyping. Simultaneously, a greater public awareness of animal welfare has influenced livestock producers to place more emphasis on welfare relative to production traits. Therefore, management practices and breeding technologies in livestock have been developed in recent years to enhance animal welfare. In particular, genomic selection can be used to improve livestock social behavior, resilience to disease and other stress factors, and ease habituation to production system changes. The main requirements for including novel behavioral and welfare traits in genomic breeding schemes are: (1) to identify traits that represent the biological mechanisms of the industry breeding goals; (2) the availability of individual phenotypic records measured on a large number of animals (ideally with genomic information); (3) the derived traits are heritable, biologically meaningful, repeatable, and (ideally) not highly correlated with other traits already included in the selection indexes; and (4) genomic information is available for a large number of individuals (or genetically close individuals) with phenotypic records. In this review, we (1) describe a potential route for development of novel welfare indicator traits (using ideal phenotypes) for both genetic and genomic selection schemes; (2) summarize key indicator variables of livestock behavior and welfare, including a detailed assessment of thermal stress in livestock; (3) describe the primary statistical and bioinformatic methods available for large-scale data analyses of animal welfare; and (4) identify major advancements, challenges, and opportunities to generate high-throughput and large-scale datasets to enable genetic and genomic selection for improved welfare in livestock. A wide variety of novel welfare indicator traits can be derived from information captured by modern technology such as sensors, automatic feeding systems, milking robots, activity monitors, video cameras, and indirect biomarkers at the cellular and physiological levels. The development of novel traits coupled with genomic selection schemes for improved welfare in livestock can be feasible and optimized based on recently developed (or developing) technologies. Efficient implementation of genetic and genomic selection for improved animal welfare also requires the integration of a multitude of scientific fields such as cell and molecular biology, neuroscience, immunology, stress physiology, computer science, engineering, quantitative genomics, and bioinformatics.

Genetic Parameters and Genome-Wide Association Studies for Anti-Müllerian Hormone Levels and Antral Follicle Populations Measured After Estrus Synchronization in Nellore Cattle

Reproductive efficiency plays a major role in the long-term sustainability of livestock industries and can be improved through genetic and genomic selection. This study aimed to estimate genetic parameters (heritability and genetic correlation) and identify genomic regions and candidate genes associated with anti-Müllerian hormone levels (AMH) and antral follicle populations measured after estrous synchronization (AFP) in Nellore cattle. The datasets included phenotypic records for 1099 and 289 Nellore females for AFP and AMH, respectively, high-density single nucleotide polymorphism (SNP) genotypes for 944 animals, and 4129 individuals in the pedigree. The heritability estimates for AMH and AFP were 0.28 ± 0.07 and 0.30 ± 0.09, and the traits were highly and positively genetically correlated (rG = 0.81 ± 0.02). These findings indicated that these traits can be improved through selective breeding, and substantial indirect genetic gains are expected by selecting for only one of the two traits. A total of 31 genomic regions were shown to be associated with AMH or AFP, and two genomic regions located on BTA1 (64.9-65.0 Mb and 109.1-109.2 Mb) overlapped between the traits. Various candidate genes were identified to be potentially linked to important biological processes such as ovulation, tissue remodeling, and the immune system. Our findings support the use of AMH and AFP as indicator traits to genetically improve fertility rates in Nellore cattle and identify better oocyte donors.

Fertility and 305-day production of Viking Red-, Montbéliarde-, and Holstein-sired crossbred cows compared with Holstein cows during their first 3 lactations in Minnesota dairy herds

Three generations of crossbred cows from a 3-breed rotation of the Viking Red (VR), Montbéliarde (MO), and Holstein (HO) breeds were compared with HO herdmates in 7 high-performance, commercial dairy herds in Minnesota. The designed study was initiated in 2008 with the enrollment of 3,550 HO females. Sires of cows were proven artificial insemination bulls and were high-ranking for genetic merit within each of the VR, MO, and HO breeds. The first generation of cows calved a first time from 2010 to 2017 and consisted of 644 VR × HO and 616 MO × HO 2-breed crossbreds and their 1,405 HO herdmates. The second generation calved a first time from 2012 to 2017 and consisted of 615 VR × MO/HO and 568 MO × VR/HO crossbreds and their 1,462 HO herdmates. The third generation calved a first time from 2014 to 2017 and was composed of 466 HO × VR/MO/HO and HO × MO/VR/HO crossbreds combined and their 736 HO herdmates. Collection of data ceased on December 31, 2017, and for the duration of study, many of the 2-breed and 3-breed crossbreds and their HO herdmates had the opportunity to complete at least 3 lactations, whereas the HO-sired crossbreds and their HO herdmates had the opportunity to complete 1 lactation. The 305-d actual (not mature equivalent) production of milk, fat, and protein was estimated from test-day observations with best prediction and cows with <305 DIM were projected to 305 d. The 2-breed and 3-breed crossbred cows had superiority over their HO herdmates for all of the fertility traits measured. The 2-breed crossbreds had -9, -17, and -15 d fewer days open than their HO herdmates during first, second, and third lactation, respectively. Also, the 3-breed crossbreds had -15, -19, and -20 d fewer days open than their HO herdmates during first, second, and third lactation, respectively. Cows in these herds had young ages at first calving of 22 to 23 mo across the breed groups, and the 3-breed crossbreds had significantly younger ages at first, second, and third calving than their HO herdmates. The 2-breed crossbreds had +2% higher fat plus protein production (kg) during first lactation, but did not differ during second and third lactation, from their HO herdmates. The 3-breed crossbreds had -3% to -4% lower fat plus protein production (kg) than their HO herdmates in each of their first 3 lactations. During first lactation, the HO-sired crossbreds did not differ for fat plus protein production (kg) from their HO herdmates.

Genetic and genomic analysis of long insemination interval in Israeli dairy cattle as an indicator of early abortions

One of the causes of observed low fertility is embryo loss after fertilization. Previous findings suggested that more than half of fertilizations result in embryo loss before pregnancy is detected. We proposed reinsemination between 49 and 100 d after the first insemination as an indicator trait for early abortion (EA) in dairy cattle based on the mean estrus interval of 21 d. This trait was compared with conception rate from first insemination and conception status, computed as the inverse of the number of inseminations to conception. Animal model variance components were estimated by REML, including parents and grandparents of cows with records. First-parity heritability for first insemination conception rate was 3%. In the multitrait analysis of parities 1 to 3 for putative EA, heritabilities ranged from 8.9% for first parity to 10.4% for second parity. All genetic correlations were >0.9, whereas all environmental correlations were <0.12. The variance component for the service sire effect for putative EA rate was less than half the variance component for conception rate. Thus, genetic control of the 2 traits is clearly different, and analysis of EA rate by a single-trait animal model is justified. Genetic evaluation for putative EA was computed using this model, including all first- through third-parity cows with freshening dates from January 1, 1985, through December 31, 2016, that either became pregnant on first insemination or were reinseminated between 49 and 100 d after the first insemination. All known parents and grandparents of cows with records were included in the analysis. The regression of the breeding value for non-abortion rate on the cows' birth year was 0.083%/yr. The genetic correlation between first-parity EA and conception status was 0.995. The genetic correlations between first-parity EA and milk, fat, and protein production were all negative, whereas the genetic correlation between EA and herd life was 0.33. Inclusion of putative EA in the selection index instead of conception status resulted in 10 to 20% greater genetic gain for both fertility traits. In a genome-wide association study based on 1,200 dairy bulls with reliabilities >50% for abortion rate genotyped for 41,000 markers, 6 markers were found with nominal probabilities of <10^-12 to reject the null hypothesis of no effect on EA rate. The markers with the lowest probabilities for EA rate were also included among the markers with the lowest probabilities for female fertility, but not vice versa. The marker explaining the most variance for abortion rate is located within the ABCA9 gene, which is found within an ATP-binding cassette (ABC) genes cluster. The ABC family is the major class of primary active transporters in the placenta.

Reproductive efficiency and survival of Holstein-Friesian cows of divergent Economic Breeding Index, evaluated under seasonal calving pasture-based management

The objective of the current study was to examine phenotypic fertility performance and survival, and to gain insight into underlying factors that may contribute to greater fertility performance in 2 divergent genetic groups (GG) of Holstein-Friesian, selected using the Irish Economic Breeding Index (EBI). The GG were evaluated across 3 spring calving pasture-based feeding treatments (FT) over 4 yr. The 2 divergent GG were (1) high EBI; representative of the top 5% nationally (elite), and (2) EBI representative of the national average (NA). In each year, 90 elite and 45 NA cows were randomly allocated to 1 of 3 FT: control, lower grass allowance, and high concentrate. No interaction between GG and FT was observed for any of the measures of fertility investigated. The elite cows achieved significantly greater pregnancy rate to first service (+14.9 percentage points), and significantly greater pregnancy rates after 21, 42, and 84 d of breeding (+17.3, +15.2, and +9.6 percentage points, respectively) compared with NA. The number of services per cow was fewer for elite (1.57) compared with NA (1.80). The interval from mating start date to pregnancy was significantly shorter for elite cows compared with NA. The elite cows maintained greater mean body condition score than NA throughout the study (2.91 vs. 2.72), and had greater body condition score at calving, artificial insemination, and drying off compared with NA. The elite cows had greater mean circulating concentrations of insulin-like growth factor-1 compared with NA. No significant effect was observed of GG on commencement of luteal activity, or progesterone profile variables. Greater survival to the start of fifth lactation was observed for elite cows. The elite cows were 43% less likely to be culled than NA by the beginning of the fifth lactation. The results highlight the success of the Economic Breeding Index to deliver reproductive performance and longevity consistent with industry targets across a range of seasonal pasture-based FT. The results also clearly demonstrate the potential of appropriate genetic selection to reverse negative fertility trends incurred during previous decades of selection for milk production alone.