Genetics and genomics of reproductive performance in dairy and beef cattle

Using expression data to fine map QTL associated with fertility in dairy cattle

BACKGROUND

Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations.

RESULTS

Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful.

CONCLUSIONS

Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.

Genome-wide association study of age at puberty and its (co)variances with fertility and stature in growing and lactating Holstein-Friesian dairy cattle

Reproductive performance is a key determinant of cow longevity in a pasture-based, seasonal dairy system. Unfortunately, direct fertility phenotypes such as intercalving interval or pregnancy rate tend to have low heritabilities and occur relatively late in an animal's life. In contrast, age at puberty (AGEP) is a moderately heritable, early-in-life trait that may be estimated using an animal's age at first measured elevation in blood plasma progesterone (AGEP4) concentrations. Understanding the genetic architecture of AGEP4 in addition to genetic relationships between AGEP4 and fertility traits in lactating cows is important, as is its relationship with body size in the growing animal. Thus, the objectives of this research were 3-fold. First, to estimate the genetic and phenotypic (co)variances between AGEP4 and subsequent fertility during first and second lactations. Second, to quantify the associations between AGEP4 and height, length, and BW measured when animals were approximately 11 mo old (standard deviation = 0.5). Third, to identify genomic regions that are likely to be associated with variation in AGEP4. We measured AGEP4, height, length, and BW in approximately 5,000 Holstein-Friesian or Holstein-Friesian × Jersey crossbred yearling heifers across 54 pasture-based herds managed in seasonal calving farm systems. We also obtained calving rate (CR42, success or failure to calve within the first 42 d of the seasonal calving period), breeding rate (PB21, success or failure to be presented for breeding within the first 21 d of the seasonal breeding period) and pregnancy rate (PR42, success or failure to become pregnant within the first 42 d of the seasonal breeding period) phenotypes from their first and second lactations. The animals were genotyped using the Weatherby's Versa 50K SNP array (Illumina, San Diego, CA). The estimated heritabilities of AGEP4, height, length, and BW were 0.34 (90% credibility interval [CRI]: 0.30, 0.37), 0.28 (90% CRI: 0.25, 0.31), 0.21 (90% CRI: 0.18, 0.23), and 0.33 (90% CRI: 0.30, 0.36), respectively. In contrast, the heritabilities of CR42, PB21 and PR42 were all <0.05 in both first and second lactations. The genetic correlations between AGEP4 and these fertility traits were generally moderate, ranging from 0.11 to 0.60, whereas genetic correlations between AGEP4 and yearling body-conformation traits ranged from 0.02 to 0.28. Our GWAS highlighted a genomic window on chromosome 5 that was strongly associated with variation in AGEP4. We also identified 4 regions, located on chromosomes 14, 6, 1, and 11 (in order of decreasing importance), that exhibited suggestive associations with AGEP4. Our results show that AGEP4 is a reasonable predictor of estimated breeding values for fertility traits in lactating cows. Although the GWAS provided insights into genetic mechanisms underpinning AGEP4, further work is required to test genomic predictions of fertility that use this information.

Genetic evaluations and genome-wide association studies for specific digital dermatitis diagnoses in dairy cows considering genotype × housing system interactions

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1, and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities.

Impact on prime animal beef merit from breeding solely for lighter dairy cows

As the proportion of prime carcasses originating from dairy herds increases, the focus is shifting to the beef merit of the progeny from dairy herds. Several dairy cow total merit indexes include a negative weight on measures of cow size. However, there is a lack of knowledge on the impact of genetic selection, solely for lighter or smaller-sized dairy cows, on the beef performance of their progeny. Therefore, the objective of this study was to quantify the genetic correlations among cow size traits (i.e., cow body weight (BW), cow carcass weight (CW)), cow body condition score (BCS), cow carcass conformation (CC), and cow carcass fat cover (CF), as well as the correlations between these cow traits and a series of beef performance slaughter-related traits (i.e., CW, CC, CF, and age at slaughter (AS)) in their progeny. After data editing, there were 52,950 cow BW and BCS records, along with 57,509 cow carcass traits (i.e., CW, CC, and CF); carcass records from 346,350 prime animals along with AS records from 316,073 prime animals were also used. Heritability estimates ranged from moderate to high (0.18 to 0.62) for all cow and prime animal traits. The same carcass trait in cows and prime animals were strongly genetically correlated with each other (0.76 to 0.85), implying that they are influenced by very similar genomic variants. Selecting exclusively for cows with higher BCS (i.e., fatter) will, on average, produce more conformed prime animals carcasses, owing to a moderate genetic correlation (0.30) between both traits. Genetic correlations revealed that selecting exclusively for lighter BW or CW cows will, on average, result in lighter prime animal carcasses of poor CC, while also delaying slaughter age. Nonetheless, selective breeding through total merit indexes should be successful in breeding for smaller dairy cows, and desirable prime animal carcass traits concurrently, because of the non-unity genetic correlations between the cow and prime animal traits; this will help to achieve a more ethical, environmentally sustainable, and economically viable dairy-beef industry.

Genetic parameters for milk yield and reproductive traits in Honduran Holstein cattle

The aim of this study was to estimate the (co)variance components and genetic parameters for milk yield adjusted to 305d (MY305), calving-to-conception interval (CCI), number of services per conception (NSC) and calving interval (CI) of Honduran Holstein cows, by fitting a bivariate animal model using Maximum Restricted Likelihood procedures. Model included the fixed effects of calving number, the contemporary calving group (farm-season-year of calving and the cow age as covariate). The estimated means and standard deviations for MY, CCI, NSC and CI were, 5098.60 ± 1564.32 kg, 168.27 ± 104.71 days, 2.46 ± 1.69 services, and 448.73 ± 109.16 days, respectively; and their estimated heritabilities were 0.21 ± 0.05, 0.03 ± 0.028, 0.02 ± 0.024 and 0.06 ± 0.04, respectively. The genetic correlations between MY305 and CCI, NSC and CI were positive and antagonist, with values of 0.64 ± 0.52, 0.99 ± 0.56, and 0.32 ± 0.24 respectively. Even though moderate to low heritability was estimated for MY305, systematic selection for milk yield, with a reduction in reproductive efficiency, if considered as the only selection criterion is important to be considered. By including reproductive traits and considering permanent environment effects into the breeding program, might yield a slow, but constant and permanent improvement over time.

Genetic evaluation for stillbirth and pre-weaning mortality in Australian dairy cattle

The welfare of calves is important to both farmers and consumers. Practices that increase the proportion of calves born alive and enable them to thrive through to weaning contribute to improved sustainability. Stillbirths (SB) are calvings where the calf dies at birth or within 24 h after birth. Pre-weaning mortality (PWM) refers to calves that die after the first day of life but before weaning based on termination data. Both SB and PWM are binary traits characterized by low heritability. Data collection for these traits is incomplete, compared with traits like milk yield in cows. Despite these challenges, genetic variation can be measured and used to produce breeding tools, such as estimated breeding values (EBV), to reduce calf mortality over time. The aim of this study was to compare the performance of various linear models to predict SB and PWM traits in Holstein and Jersey cattle and evaluate their applicability for industry-wide use in the Australian dairy industry. Calving records from around 2.25 million Holstein and Jersey dams were obtained from DataGene's Central Data Repository from 2000 onwards to calculate genetic parameters. About 7% of calves were recorded as stillborn in the period 2000-2021 (n = 1.48 million calvings). The prevalence of PWM was much lower than stillbirth during the same period at 2% (n = 0.89 million calves). Genetic parameters were estimated for SB direct, SB maternal and PWM using bivariate linear models with calving ease (CE) as the second trait in the model. The heritability of these calf traits was low and varied between 1 to 5% depending on the breed, trait and model. In Holstein cattle, heritabilities were 2% for PWM and SB direct and 1% for SB maternal while in Jersey cattle heritabilities were 5% for PWM, 2% for SB direct and 1% for SB maternal. The genetic trends for both SB direct and maternal in Holstein cattle indicate improvement in both traits whereas there was no apparent increase or decrease in PWM in the past 2 decades. The coefficient of genetic variation for SB direct and PWM was between 11.7 and 23.0% in Holstein and Jersey cattle demonstrating that there was considerable genetic variation in calf survival traits as a first step to using genetic selection to increase the proportion of calves born alive and calves weaned. A focus on improved calf and calving recording practices is expected to increase the reliability of genetic predictions.

Estimation of genetic parameters for bull conception rate and its genetic correlations with semen production traits in Japanese Black bulls

The P of achieving pregnancy is an important trait of bull fertility in beef cattle and is defined as the bull conception rate (BCR). This study aimed to clarify and better understand the genetic architecture of the BCR calculated using artificial insemination and pregnancy diagnosis records from a progeny testing program in Japanese Black bulls. In this study, we estimated the genetic parameters of the BCR and their correlation with semen production traits. In addition, we assessed the correlated responses in BCR by considering the selection of semen production traits. Nine hundred and sixteen Japanese Black bulls were selected based on fertility, with 28 869 pregnancy diagnostic records from the progeny testing program. Our results showed that the heritability estimate was 0.04 in the BCR at the first service and 0.14 in BCR for the three services, and an increase in the inbreeding coefficient led to a significant decrease in BCR. The phenotypic trend of BCR remained almost constant over the years, whereas the genetic trend increased. In addition, the changes in the progeny testing year effect showed a similar tendency to the phenotypic trends, suggesting that the phenotypic trends could be mainly due to non-genetic effects, including progeny testing year effects. The estimated genetic correlation of BCR with sperm motility traits was favorably moderate to high (ranging from 0.49 to 0.97), and those with sperm quantity traits such as semen volume were favorably low to moderate (ranging from 0.23 to 0.51). In addition, the correlated responses in BCR at the first service by selection for sperm motility traits resulted in a higher genetic gain than direct selection. This study provides new insights into the genetic factors affecting BCR and the possibility of implementing genetic selection to improve BCR by selecting sperm motility traits in Japanese Black bulls.

Genetic and genomic evaluation of age at first calving in Italian Holsteins

Age at first calving (AFC) represents the nonproductive period of ∼2 yr in Holstein cows, and thus, it has a relevant effect on the cost of rearing replacements in the dairy herd. In the present study, we aimed to evaluate genetic and genomic aspects of AFC in the Italian Holstein population. Data of 4,206,218 heifers with first calving between 1996 and 2020 were used. Age at first calving averaged 26.09 ± 3.07 mo and decreased across years. Heritability was estimated using a linear animal model which included the fixed effects of herd-year-season of birth and classes of gestation length, and the random animal additive genetic effect fitted to a pedigree-based relationship matrix. The EBV and genomically EBV (GEBV) were obtained, and they were standardized to mean 100 and standard deviation 5, where animals above the mean are those contributing to reduce AFC. Heritability estimates of AFC ranged from 0.031 to 0.045. The trend of sires' GEBV was favorable and indicated a reduced AFC across years. Approximate genetic correlations between GEBV of AFC and GEBV of other economically important traits were calculated on a subset of genotyped females born after 2015. Moderate favorable associations of AFC with production traits (0.39-0.51), udder depth (0.40), interval from first to last insemination in heifer (-0.43), and longevity (0.34) were assessed. Overall, the greatest lifetime productive performances and most favorable days open in first lactation were observed when heifers calved at 22 to 23 mo. In contrast, progeny of sires with GEBV of AFC above the mean yielded more milk, fat, and protein in first lactation, and had shorter days open than progeny of sires with GEBV of AFC below the mean. Results suggested that breeding strategies to improve AFC should be pursued, also considering genetic correlations between AFC and traits which are already part of the Italian Holstein breeding objective. The inclusion of AFC in an aggregate index is expected to contribute to enhance farm income.

Genetic covariance components for measures of nitrogen utilization in grazing dairy cows

Improved nitrogen utilization of dairy production systems should improve not only the economic output of the systems but also the environmental metrics. One strategy to improve efficiency is through breeding programs. Improving a trait through breeding is conditional on the presence of exploitable genetic variability. Using a database of 1,291 deeply phenotyped grazing dairy cows, the genetic variability for 2 definitions of nitrogen utilization was studied: nitrogen use efficiency (i.e., nitrogen output in milk and meat divided by nitrogen available) and nitrogen balance (i.e., nitrogen available less nitrogen output in milk and meat). Variance components for both variables were estimated using animal repeatability linear mixed models. Genetic variability was detected for both nitrogen utilization metrics, even though their heritability estimates were low (<0.10). Validation of genetic evaluations revealed that animals divergent for nitrogen use efficiency or nitrogen balance indeed differed phenotypically, further demonstrating that breeding for improved nitrogen efficiency should result in a shift in the population mean toward better efficiency. Nitrogen use efficiency and nitrogen balance were not genetically correlated with each other (<|0.28|), and neither metric was correlated with milk urea nitrogen (<|0.12|). Nitrogen balance was unfavorably correlated with milk yield, showing the importance of including the nitrogen utilization metrics in a breeding index to improve nitrogen utilization without negatively impacting milk yield. In conclusion, improvement of nitrogen utilization through breeding is possible, even if more nitrogen utilization phenotypic data need to be collected to improve the selection accuracy considering the low heritability estimates.

Searching for homozygous haplotype deficiency in Manech Tête Rousse dairy sheep revealed a nonsense variant in the MMUT gene affecting newborn lamb viability

BACKGROUND

Recessive deleterious variants are known to segregate in livestock populations, as in humans, and some may be lethal in the homozygous state.

RESULTS

We used phased 50 k single nucleotide polymorphism (SNP) genotypes and pedigree data to scan the genome of 6845 Manech Tête Rousse dairy sheep to search for deficiency in homozygous haplotypes (DHH). Five Manech Tête Rousse deficient homozygous haplotypes (MTRDHH1 to 5) were identified, with a homozygous deficiency ranging from 84 to 100%. These haplotypes are located on Ovis aries chromosome (OAR)1 (MTRDHH2 and 3), OAR10 (MTRDHH4), OAR13 (MTRDHH5), and OAR20 (MTRDHH1), and have carrier frequencies ranging from 7.8 to 16.6%. When comparing at-risk matings between DHH carriers to safe matings between non-carriers, two DHH (MTRDHH1 and 2) were linked with decreased insemination success and/or increased stillbirth incidence. We investigated the MTRDHH1 haplotype, which substantially increased stillbirth rate, and identified a single nucleotide variant (SNV) inducing a premature stop codon (p.Gln409*) in the methylmalonyl-CoA mutase (MMUT) gene by using a whole-genome sequencing approach. We generated homozygous lambs for the MMUT mutation by at-risk mating between heterozygous carriers, and most of them died within the first 24 h after birth without any obvious clinical symptoms. Reverse transcriptase-qPCR and western blotting on post-mortem liver and kidney biological samples showed a decreased expression of MMUT mRNA in the liver and absence of a full-length MMUT protein in the mutant homozygous lambs.

CONCLUSIONS

We identified five homozygous deficient haplotypes that are likely to harbor five independent deleterious recessive variants in sheep. One of these was detected in the MMUT gene, which is associated with lamb lethality in the homozygous state. A specific management of these haplotypes/variants in the MTR dairy sheep selection program would help enhance the overall fertility and lamb survival.

Multi-omics data integration for the identification of biomarkers for bull fertility

Bull fertility is an important economic trait, and the use of subfertile semen for artificial insemination decreases the global efficiency of the breeding sector. Although the analysis of semen functional parameters can help to identify infertile bulls, no tools are currently available to enable precise predictions and prevent the commercialization of subfertile semen. Because male fertility is a multifactorial phenotype that is dependent on genetic, epigenetic, physiological and environmental factors, we hypothesized that an integrative analysis might help to refine our knowledge and understanding of bull fertility. We combined -omics data (genotypes, sperm DNA methylation at CpGs and sperm small non-coding RNAs) and semen parameters measured on a large cohort of 98 Montbéliarde bulls with contrasting fertility levels. Multiple Factor Analysis was conducted to study the links between the datasets and fertility. Four methodologies were then considered to identify the features linked to bull fertility variation: Logistic Lasso, Random Forest, Gradient Boosting and Neural Networks. Finally, the features selected by these methods were annotated in terms of genes, to conduct functional enrichment analyses. The less relevant features in -omics data were filtered out, and MFA was run on the remaining 12,006 features, including the 11 semen parameters and a balanced proportion of each type of-omics data. The results showed that unlike the semen parameters studied the-omics datasets were related to fertility. Biomarkers related to bull fertility were selected using the four methodologies mentioned above. The most contributory CpGs, SNPs and miRNAs targeted genes were all found to be involved in development. Interestingly, fragments derived from ribosomal RNAs were overrepresented among the selected features, suggesting roles in male fertility. These markers could be used in the future to identify subfertile bulls in order to increase the global efficiency of the breeding sector.

Quantitative trait loci exploration and characterization of gestation length in Holstein cattle

Gestation length (GL) is a moderately heritable trait in cattle with economic and management implications. This study aimed to characterize the gestation length of an Argentinian Holstein cattle population, understand contributing factors, and explore the GL effect on production performance. Further objectives were to estimate direct and maternal heritabilities for this trait and to identify genomic regions affecting it. Data consisted of GL records from 45,738 births corresponding to 17,004 Holstein cows and heifers. The effects of age and calving season over GL were analyzed using a Student's t-test for homoscedastic samples. The effects of the GL category (GL shorter than 1.5 SD, within ±1.5 SD, and longer than 1.5 SD from the mean) on production performance were studied by analysis of variance. A single-step genome-wide association study was performed using the BLUPF90 suite of programs with genotypes from 654 Holstein animals on 40,339 SNP. The results showed that the younger the age at calving, the shorter the GL. Moreover, gestations ending in warmer seasons were, in general, statistically shorter than those ending in colder seasons for both heifers and cows. Regarding the effect of GL on production performance, cows with gestation periods within ±1.5 SD from the population mean exhibited the highest 305-day cumulative milk, fat, and protein productions. Direct and maternal heritabilities for GL were 0.42 and 0.03, respectively. We detected a SNP suggestively associated with direct gestation length at 57.7 Mb on Bos taurus autosome 18, a locus included in a region described in the literature as associated with the trait. The information obtained on the environmental and genetic factors affecting GL in Argentinian Holstein cows contributes to characterizing the population in pursuit of improving the performance of national dairy cattle breeding systems.

Genetic Parameters of Semen Traits and Their Correlations with Conformation Traits in Chinese Holstein Bulls

The elite bull plays an extremely important role in the genetic progression of the dairy cow population. The previous results indicated the potential positive relationship of large scrotal circumference (SC) with improved semen volume, concentration, and motility. In order to improve bull's semen quantity and quality by selection, it is necessary to estimate the genetic parameters of semen traits and their correlations with other conformation traits such as SC that could be used for an indirect selection. In this study, the genetic parameters of seven semen traits (n = 66,260) and nine conformation traits (n = 3,642) of Holstein bulls (n = 453) were estimated by using the bivariate repeatability animal model with the average information-restricted maximum likelihood (AI-REML) approach. The results showed that the estimated heritabilities of semen traits ranged from 0.06 (total number of motile sperm, TNMS) to 0.37 (percentage of abnormal sperm, PAS) and conformation traits ranged from 0.23 (pin width, PW) to 0.69 (hip height, HH). The highest genetic correlations were found between semen volume per ejaculation (SVPE), semen concentration per ejaculation (SCPE), total number of sperm (TNS), and TNMS traits that were 0.97, 0.98, 1.00, and 0.99, respectively. Phenotypic correlations between SC and SVPE, SCPE, TNS, and TNMS were 0.35, 0.35, 0.48, and 0.42, respectively. In summary, the moderate or high heritability of semen traits indicates that genetic improvement of semen quality by selection is feasible, where SC could be a useful trait for indirect selection or as correlated information to improve semen quantity and production in the practical bull breeding programs.

Unveiling the Genetic Landscape of Feed Efficiency in Holstein Dairy Cows: Insights into Heritability, Genetic Markers, and Pathways via Meta-Analysis

Improving the feeding efficiency of dairy cows is a key component to improve the utilization of land resources and meet the demand for high-quality protein. Advances in genomic methods and omics techniques have made it possible to breed more efficient dairy cows through genomic selection. The aim of this review is to obtain a comprehensive understanding of the biological background of feed efficiency (FE) complex traits in purebred Holstein dairy cows including heritability estimate, and genetic markers, genes, and pathways participating in FE regulation mechanism. Through a literature search, we systematically reviewed the heritability estimation, molecular genetic markers, genes, biomarkers, and pathways of traits related to feeding efficiency in Holstein dairy cows. A meta-analysis based on a random-effects model was performed to combine reported heritability estimates of FE complex. The heritability of residual feed intake, dry matter intake, and energy balance was 0.20, 0.34, and 0.22, respectively, which proved that it was reasonable to include the related traits in the selection breeding program. For molecular genetic markers, a total of 13 single-nucleotide polymorphisms and copy number variance loci, associated genes, and functions were reported to be significant across populations. A total of 169 reported candidate genes were summarized on a large scale, using a higher threshold (adjusted P value < 0.05). Then, the subsequent pathway enrichment of these genes was performed. The important genes reported in the articles were included in a gene list and the gene list was enriched by gene ontology (GO):biological process (BP), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis. Three GO:BP terms and four KEGG terms were statistically significant, which mainly focused on adenosine triphosphate (ATP) synthesis, electron transport chain, and OXPHOS pathway. Among these pathways, involved genes such as ATP5MC2, NDUFA, COX7A2, UQCR, and MMP are particularly important as they were previously reported. Twenty-nine reported biological mechanisms along with involved genes were explained mainly by four biological pathways (insulin-like growth factor axis, lipid metabolism, oxidative phosphorylation pathways, tryptophan metabolism). The information from this study will be useful for future studies of genomic selection breeding and genetic structures influencing animal FE. A better understanding of the underlying biological mechanisms would be beneficial, particularly as it might address genetic antagonism.

Proteomic Approaches to Unravel the Molecular Dynamics of Early Pregnancy in Farm Animals: An In-Depth Review

Infertility is a major problem in farm animals, which has a negative economic effect on farm industries. Infertility can be defined as the inability of animals to achieve a successful pregnancy. Early pregnancy is crucial to establish a successful pregnancy, and it is reported that 70-80% and 20-30% of total embryonic loss occur in cattle and pigs, respectively, during the first month of pregnancy. The advanced high-throughput proteomics techniques provide valuable tools for in-depth understanding of the implantation process in farm animals. In the present review, our goal was to compile, assess, and integrate the latest proteomic research on farm animals, specifically focused on female reproduction, which involves endometrial tissues, uterine fluids, oviductal fluids, and microRNAs. The series of studies has provided in-depth insights into the events of the implantation process by unfolding the molecular landscape of the uterine tract. The discussed data are related to pregnant vs. non-pregnant animals, pregnancy vs. oestrous cycle, different days of the early pregnancy phase, and animals with uterine infections affecting reproduction health. Some of the studies have utilized non-invasive methods and in vitro models to decipher the molecular events of embryo-maternal interaction. The proteomics data are valuable sources for discovering biomarkers for infertility in ruminants and new regulatory pathways governing embryo-uterine interaction, endometrium receptivity, and embryonic development. Here, we envisage that the identified protein signatures can serve as potential therapeutic targets and biomarkers to develop new therapeutics against pregnancy diseases.

Usefulness of mid-infrared spectroscopy as a tool to estimate body condition score change from milk samples in intensively fed dairy cows

Directly measuring individual cow energy balance is not trivial. Other traits such as body condition score (BCS) and BCS change (ΔBCS) can, however, be used as an indicator of cow energy status. Body condition score is a metric used worldwide to estimate cow body reserves, but the estimation of ΔBCS was, until now, conditional on the availability of multiple BCS assessments. The aim of the present study was to estimate ΔBCS from milk mid-infrared (MIR) spectra and days in milk (DIM) in intensively fed dairy cows using statistical prediction methods. Daily BCS was interpolated from cubic splines fitted through the BCS records and daily ΔBCS was calculated from these splines. The ΔBCS records were merged with milk MIR spectra recorded on the same week. The dataset comprised 37,077 ΔBCS phenotypes across 9,403 lactations from 6,988 cows in 151 herds based in Quebec, Canada. Partial least squares regression (PLSR) and a neural network (NN) were then used to estimate ΔBCS from (1) MIR spectra only, (2) DIM only, or (3) MIR spectra and DIM together. The ΔBCS data in both the first 120 and 305 DIM of lactation were used to develop the estimates. Daily ΔBCS had a standard deviation of 4.40 × 10-3 BCS units in the 120-d dataset and of 3.63 × 10-3 BCS units in the 305-d dataset. A 4-fold cross-validation was used to calibrate and test the prediction equations. External validation was also conducted using more recent years of data. Irrespective of whether based on the first 120 or 305 DIM, or when MIR spectra only, DIM only or MIR spectra and DIM were jointly used as prediction variables, NN produced the lowest root mean square error (RMSE) of cross-validation (1.81 × 10-3 BCS units and 1.51 × 10-3 BCS units, respectively, using the 120-d and 305-d dataset). Relative to predictions for the entire 305 DIM, the RMSE of cross-validation was 15.4% and 1.5% lower in the first 120 DIM when using PLSR and NN, respectively. Predictions from DIM only were more accurate than those using just MIR spectra data but, irrespective of the dataset and of the prediction model used, combining DIM information with MIR spectral data as prediction variables reduced the RMSE compared with the inclusion of DIM alone, albeit the benefit was small (the RMSE from cross-validation reduced by up to 5.5% when DIM and spectral data were jointly used as model features instead of DIM only). However, when predicting extreme ΔBCS records, the MIR spectral data were more informative than DIM. Model performance when predicting ΔBCS records in future years was similar to that from cross-validation demonstrating the ability of MIR spectra of milk and DIM combined to estimate ΔBCS, particularly in early lactation. This can be used to routinely generate estimates of ΔBCS to aid in day-to-day individual cow management.

Identification of quantitative trait loci and associated candidate genes for pregnancy success in Angus-Brahman crossbred heifers

BACKGROUND

In beef cattle, more than 50% of the energy input to produce a unit of beef is consumed by the female that produced the calf. Development of genomic tools to identify females with high genetic merit for reproductive function could increase the profitability and sustainability of beef production.

RESULTS

Genome-wide association studies (GWAS) were performed using a single-step genomic best linear unbiased prediction approach on pregnancy outcome traits from a population of Angus-Brahman crossbred heifers. Furthermore, a validation GWAS was performed using data from another farm. Heifers were genotyped with the Bovine GGP F250 array that contains 221,077 SNPs. In the discovery population, heifers were bred in winter breeding seasons involving a single round of timed artificial insemination (AI) followed by natural mating for 3 months. Two phenotypes were analyzed: pregnancy outcome to first-service AI (PAI; n = 1,481) and pregnancy status at the end of the breeding season (PEBS; n = 1,725). The heritability was estimated as 0.149 and 0.122 for PAI and PEBS, respectively. In the PAI model, one quantitative trait locus (QTL), located between 52.3 and 52.5 Mb on BTA7, explained about 3% of the genetic variation, in a region containing a cluster of γ-protocadherin genes and SLC25A2. Other QTLs explaining between 0.5% and 1% of the genetic variation were found on BTA12 and 25. In the PEBS model, a large QTL on BTA7 was synonymous with the QTL for PAI, with minor QTLs located on BTA5, 9, 10, 11, 19, and 20. The validation population for pregnancy status at the end of the breeding season were Angus-Brahman crossbred heifers bred by natural mating. In concordance with the discovery population, the large QTL on BTA7 and QTLs on BTA10 and 12 were identified.

CONCLUSIONS

In summary, QTLs and candidate SNPs identified were associated with pregnancy outcomes in beef heifers, including a large QTL associated with a group of protocadherin genes. Confirmation of these associations with larger populations could lead to the development of genomic predictions of reproductive function in beef cattle. Moreover, additional research is warranted to study the function of candidate genes associated with QTLs.

Research on timed AI in beef cattle: Past, present and future, a 27-year perspective

This review aimed to (1) summarize the results from fixed-timed artificial insemination (TAI) fertility studies performed during the last 27 years; (2) compile and evaluate, as examples from the literature base, the direct comparisons made of specific manipulations to synchronization protocols; (3) evaluate the impact of the TAI programs on the reproductive performance during the breeding season, and (4) provide perspective on the future of TAI programs in beef cattle. A search of the literature published from 1995 to 2021 was conducted to identify experiments in which synchronization of ovulation and TAI in beef cattle was performed. The primary outcome of interest was fertility expressed as pregnancies per TAI. The literature included two search engines, the SIS Web of Science and the US National Library of Medicine Institutes of Health through PubMed. After the initial search and screening, a total of 228 manuscripts were selected containing a total of 272,668 TAI. A dramatic increase in the number of publications and TAIs occurred throughout the years. Most of them were from Brazil and United States, followed by Canada, Argentina, Uruguay, and Australia. Two main types of TAI programs were identified: GnRH-based and E2/P4-based protocols. In terms of GnRH-based programs, two variations were evaluated in the present manuscript. First, we evaluated the effect of the progesterone implant during the protocol. The progesterone implant increased pregnancy/TAI (P/TAI) from 44.3 to 54.3%. Second, the use of a second prostaglandin F2α treatment in 5-d CO-synch program increased the P/TAI from 53.2 to 60.9%. In E2/P4-based programs, use of GnRH at TAI increased P/TAI from 54.7 to 59.2% in cows. However, no increase was detected in heifers. Other research showed that use of TAI can increase the overall proportion of the cows pregnant at end of the breeding season and produce earlier calvings compared with bulls. In conclusion, there have been a large number of excellent research studies that have been performed during the last 27 years on TAI in beef cattle. This technology is being utilized successfully in the beef cattle industry. This success is largely because of the valid research that underlies the application of the technology and the economic value of the technology.

Genome-wide association study of anogenital distance and its (co)variances with fertility in growing and lactating Holstein-Friesian dairy cattle

Anogenital distance (AGD) is a moderately heritable trait that can be measured at a young age that may provide an opportunity to indirectly select for improved fertility in dairy cattle. In this study, we characterized AGD and its genetic and phenotypic relationships with a range of body stature and fertility traits. We measured AGD, shoulder height, body length, and body weight in a population of 5,010 Holstein-Friesian and Holstein-Friesian × Jersey crossbred heifers at approximately 11 mo of age (AGD1). These animals were born in 2018 across 54 seasonal calving, pasture-based dairy herds. A second measure of AGD was collected in a subset of herds (n = 17; 1,956 animals) when the animals averaged 29 mo of age (AGD2). Fertility measures included age at puberty (AGEP), then time of calving, breeding, and pregnancy during the first and second lactations. We constructed binary traits reflecting the animal's ability to calve during the first 42 d of their herd's seasonal calving period (CR42), be presented for breeding during the first 21 d of the seasonal breeding period (PB21) and become pregnant during the first 42 d of the seasonal breeding period (PR42). The posterior mean of sampled heritabilities for AGD1 was 0.23, with 90% of samples falling within a credibility interval (90% CRI) of 0.20 to 0.26, whereas the heritability of AGD2 was 0.29 (90% CRI 0.24 to 0.34). The relationship between AGD1 and AGD2 was highly positive, with a genetic correlation of 0.89 (90% CRI 0.82 to 0.94). Using a GWAS analysis of 2,460 genomic windows based on 50k genotype data, we detected a region on chromosome 20 that was highly associated with variation in AGD1, and a second region on chromosome 13 that was moderately associated with variation in AGD1. We did not detect any genomic regions associated with AGD2 which was measured in fewer animals. The genetic correlation between AGD1 and AGEP was 0.10 (90% CRI 0.00 to 0.19), whereas the genetic correlation between AGD2 and AGEP was 0.30 (90% CRI 0.15 to 0.44). The timing of calving, breeding, and pregnancy (CR42, PB21, and PR42) during first or second lactations exhibited moderate genetic relationships with AGD1 (0.19 to 0.52) and AGD2 (0.46 to 0.63). Genetic correlations between AGD and body stature traits were weak (≤0.16). We conclude that AGD is a moderately heritable trait, which may have value as an early-in-life genetic predictor for reproductive success during lactation.

Discovering Genomic Regions Associated with Reproductive Traits and Frame Score in Mexican Simmental and Simbrah Cattle Using Individual SNP and Haplotype Markers

Reproductive efficiency stands as a critical determinant of profitability within beef production systems. The incorporation of molecular markers can expedite advancements in reproductive performance. While the use of SNPs in association analysis is prevalent, approaches centered on haplotypes can offer a more comprehensive insight. The study used registered Simmental and Simbrah cattle genotyped with the GGP Bovine 150 k panel. Phenotypes included scrotal circumference (SC), heifer fertility (HF), stayability (STAY), and frame score (FS). After quality control, 105,129 autosomal SNPs from 967 animals were used. Haplotype blocks were defined based on linkage disequilibrium. Comparison between haplotypes and SNPs for reproductive traits and FS was conducted using Bayesian and frequentist models. 23, 13, 7, and 2 SNPs exhibited associations with FS, SC, HF, and STAY, respectively. In addition, seven, eight, seven, and one haplotypes displayed associations with FS, SC, HF, and STAY, respectively. Within these delineated genomic segments, potential candidate genes were associated.

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.

Genetic parameters of pregnancy loss in dairy cows estimated from pregnancy-associated glycoproteins in milk

This study examined the feasibility of using pregnancy-associated glycoproteins (PAG) in milk within breeding for pregnancy maintenance and assessed the genetic variation in pregnancy loss traits. A total of 374,206 PAG samples from 41,889 Swedish Red (SR) and 82,187 Swedish Holstein (SH) cows were collected at monthly test-day milkings in 1,119 Swedish herds. Pregnancy status was defined based on PAG levels and confirmed by data on artificial insemination (AI), calving, and culling from d 1 postinsemination to calving. Pregnancy loss traits were defined as embryonic loss (diagnosed 28 d to 41 d after AI), fetal loss (42 d after AI until calving), and total pregnancy loss. Least squares means (± standard error, %) and genetic parameters were estimated using mixed linear models. Heritability was estimated to be 0.02, 0.02, and 0.03 for embryonic loss, fetal loss, and total pregnancy loss, respectively. Cows with pregnancy loss had lower PAG concentrations than cows which successfully maintained pregnancy and calved. PAG recording was limited to monthly test-day milking, resulting in low estimated embryonic loss (17.5 ± 0.4 and 18.7 ± 0.4 in SR and SH, respectively) and higher fetal loss (32.8 ± 0.5 and 35.1 ± 0.5 in SR and SH, respectively). Pregnancy loss might have occurred earlier but remained undetected until the next test-day milking, when it was recorded as fetal loss rather than embryonic loss. Estimated genetic correlation between embryonic and fetal pregnancy loss traits and classical fertility traits were in general high. Identification of novel genetic traits from PAG data can be highly specific, as PAG are only secreted by the placenta. Thus, PAG could be useful indicators in selection to genetically improve pregnancy maintenance and reduce reproductive losses in milk production. Further studies are needed to clarify how these results could be applied in breeding programs concurrent with selection for classical fertility traits.

Effect of reproductive management programs that prioritized artificial insemination at detected estrus or timed artificial insemination on the economic performance of primiparous Holstein cows of different genetic merit for fertility

The objective of this randomized controlled experiment was to evaluate the effect of reproductive management programs that prioritized artificial insemination (AI) at detected estrus (AIE) or timed AI (TAI) during the first lactation on the economic performance of dairy cows of different genomically enhanced predicted transmitting ability for fertility. Lactating primiparous Holstein cows from 6 commercial farms were stratified into high, medium, and low fertility groups based on a reproduction index value calculated from multiple genomically enhanced predicted transmitting abilities to predict the number of days to achieve pregnancy. Within herd and fertility group, cows were randomly assigned either to a program that prioritized AIE (P-AIE; n = 1,416) and used TAI for cows not AIE for all AI services or another that prioritized TAI and had an extended voluntary waiting period for first service and prioritized TAI for second and greater AI services (P-TAI; n = 1,338). Cash flow (CF) per cow accumulated for the experimental (first) and second calving interval (CIN) and cash flow per slot per 28 mo after calving in the experimental lactation were calculated. Market and rearing heifer cost values were used for estimating CF. For cows in the high fertility group, a positive effect of delayed pregnancy on milk income during the first lactation was observed (+$248 for P-TAI) but was insufficient to generate significant differences in CF between treatments mainly because of milk income compensation in the second lactation (+$125 for P-AIE) and minor reductions in reproductive cost and gains in calf value for the P-AIE treatment. In this regard, CF for 2 CIN was greater for the P-TAI treatment by $61 and $86 for market and rearing replacement heifer cost, respectively. Similarly, CF per slot was favorable to the P-TAI treatment but only by $13 and $47 for market and rearing replacement heifer cost, respectively. For cows in the low fertility group, CF was numerically in favor of the P-AIE treatment due to a pregnancy and herd exit dynamics that resulted in gains in milk income over feed cost during the first ($29) and second ($113) lactation. Differences in CF for the 2 CIN were $58 and $47 for market or rearing heifer value, respectively, and $77 and $19 for market and rearing heifer values, respectively for the slot analysis. Differences in CF between cows of different genetic merit for fertility were consistent across treatment and estimation method. Of note, cows in the low fertility group had greater CF than cows in the high fertility group in all comparisons, ranging from $198 per cow for 2 CIN to as much as $427 per slot. For the low fertility group, greater milk production contributed directly (milk income over feed cost) and indirectly (reduced culling) to increased CF. We concluded that genetic merit for fertility and CF are associated because cows of inferior genetic potential for fertility had greater CF than cows of superior genetic for fertility despite some increased costs and reduced revenues. Also, the magnitude of the CF differences observed for cows of different genetic merit for fertility managed with the P-AIE or P-TAI program may be valuable to commercial dairy farms but did not allow to conclusively support the choice of a type of reproductive management strategy for cows of different genetic merit for fertility.

Understanding the underlying genetic mechanisms for age at first calving, inter-calving period and scrotal circumference in Bonsmara cattle

BACKGROUND

Reproduction is a key feature of the sustainability of a species and thus represents an important component in livestock genetic improvement programs. Most reproductive traits are lowly heritable. In order to gain a better understanding of the underlying genetic basis of these traits, a genome-wide association was conducted for age at first calving (AFC), first inter-calving period (ICP) and scrotal circumference (SC) within the South African Bonsmara breed. Phenotypes and genotypes (120,692 single nucleotide polymorphisms (SNPs) post editing) were available on 7,128 South African Bonsmara cattle; the association analyses were undertaken using linear mixed models.

RESULTS

Genomic restricted maximum likelihood analysis of the 7,128 SA Bonsmara cattle yielded genomic heritability's of 0.183 (SE = 0.021) for AFC, 0.207 (SE = 0.022) for ICP and 0.209 (SE = 0.019) for SC. A total of 16, 23 and 51 suggestive (P ≤ 4 × 10-6) SNPs were associated with AFC, ICP and SC, while 11, 11 and 44 significant (P ≤ 4 × 10-7) SNPs were associated with AFC, ICP and SC respectively. A total of 11 quantitative trait loci (QTL) and 11 candidate genes were co-located with these associated SNPs for AFC, with 10 QTL harbouring 11 candidate genes for ICP and 41 QTL containing 40 candidate genes for SC. The QTL identified were close to genes previously associated with carcass, fertility, growth and milk-related traits. The biological pathways influenced by these genes include carbohydrate catabolic processes, cellular development, iron homeostasis, lipid metabolism and storage, immune response, ovarian follicle development and the regulation of DNA transcription and RNA translation.

CONCLUSIONS

This was the first attempt to study the underlying polymorphisms associated with reproduction in South African beef cattle. Genes previously reported in cattle breeds for numerous traits bar AFC, ICP or SC were detected in this study. Over 20 different genes have not been previously reported in beef cattle populations and may have been associated due to the unique genetic composite background of the SA Bonsmara breed.

Exploring molecular dynamic indicators associated with reproductive performance of Bos indicus cattle in blood plasma samples through data-independent acquisition mass spectrometry

Improving reproductive performance of cattle is of paramount importance for sustainable dairy farming. Poor reproduction performance (RP) hinders the genetic improvement of important Bos indicus cattle breeds. It is well known that incorporation of molecular information along with conventional breeding method is far better than use of conventional method alone for the genetic improvement of reproductive performance traits in cattle. Therefore, the present study sought to investigate the plasma proteome of the Deoni cows in cyclical (n = 6) and pregnant (n = 6) reproductive phases with varying reproductive performance (high and low). High-throughput data independent acquisition (DIA) based proteomics was performed to understand corresponding proteome. We identified a total of 430 plasma proteins. Among cyclic cows, twenty proteins were differentially regulated in low RP as compared to high RP. BARD1 and AFP proteins were observed upregulated in cyclical cows whose upregulation reported to affect reproductive performance in cattle. Among the pregnant cows, thirty-five proteins were differentially regulated, including the downregulation of FGL2 and ZNFX1 that modulates the maternal immune response mechanism which is required for successful implantation of the embryo. Also, proteins such as AHSG, CLU and SERPINA6 were upregulated in the pregnant cows whose upregulation reported to reduced reproductive performance. The results of this study will be helpful in establishing a framework for future research on the aspect of improving reproductive performance in Bos indicus cattle breeds. SIGNIFICANCE: The Indian subcontinent is the center of domestication for Bos indicus cattle breeds and they are known for their disease resistance, heat tolerance, ability to survive in low input regime and harsh climatic conditions. In recent times, population of many important Bos indicus breeds including Deoni cattle is declining due to various factors, especially due to reproductive performance. Traditional breeding methods are not sufficient enough to understand and improve the reproductive performance traits in important Bos indicus cattle breeds. Proteomics approach is a promising technology to understand the complex biological factors which leads to poor reproductive performance in cattle. The present study utilized DIA based LC- MS/MS analysis to identify the plasma proteins associated with reproductive performance in cyclical and pregnant cows. This study if improved further, can be used to develop potential protein markers associated with reproductive performance which is useful for the selection and genetic improvement of important Bos indicus breeds.

Association of plasma miRNAs with early life performance and aging in dairy cattle

Early life performance traits in dairy cattle can have important influences on lifetime productivity. Poor health and fertility are of great economical and animal welfare concern. Circulating miRNAs have been linked to several livestock traits, including resistance to infection, fertility, and muscle development. This study aimed to identify circulating miRNAs associated with early life performance traits and aging in dairy cattle. Plasma samples from female calves (n = 12) identified retrospectively as differing in health, growth, and fertility outcomes prior to first calving were analyzed using PCR arrays detecting 378 miRNAs. Levels of 6 miRNAs differed significantly in calves with poor growth/fertility relative to controls (t-test: P<0.05). Additionally, general(ized) (non)linear mixed models identified 1 miRNA associated with average daily gain until weaning, 22 with live bodyweight at one year of age, 47 with age at first service, and 19 with number of infections before first calving. Out of 85 distinct miRNAs that were associated with at least one animal trait, 9 miRNAs were validated by RT-qPCR in a larger cohort (n = 91 animals), which included longitudinal plasma samples (calf, heifer, first lactation cow). Significant associations (P<0.05) involving individual miRNAs or ratios between miRNAs and early-life performance traits were identified, but did not retain significance after multiple testing adjustment. However, levels of 8 plasma miRNAs (miR-126-3p, miR-127, miR-142-5p, miR-154b, miR-27b, miR-30c-5p, miR-34a, miR-363) changed significantly with age, most prominently during the calf-to-heifer transition. Comparative RT-qPCR analyses of these miRNAs across 19 calf tissues showed that most were ubiquitously expressed. Online database mining identified several pathways involved in metabolism and cell signaling as putative biological targets of these miRNAs. These results suggest that miR-126-3p, miR-127, miR-142-5p, miR-154b, miR-27b, miR-30c-5p, miR-34a, miR-363 are involved in regulating growth and development from birth to first lactation (~2 years old) and could provide useful biomarkers of aging in cattle.

Estimation of genetic parameters for semen traits in Egyptian buffalo bulls

This study was conducted to characterize semen traits (ejaculate volume (VOL), mass motility (MM), sperm livability (LS), percentage of abnormal sperms (AS), and sperm concentration (CONC)) of Egyptian buffalo bulls and evaluate the importance of some nongenetic factors (year (YC) and season (SC) of semen collection and age of bull genetically and environmentally at collection (ABC)) affecting the investigated traits. A total of 7761 normal semen ejaculates were collected from 26 bulls from 2009 to 2019. Single-trait and bivariate repeatability animal models using Bayesian methods were used to estimate variance components, heritability, repeatability, and genetic correlations among the investigated semen traits. YC and ABC exerted significant effects on most semen traits, whereas SC exerted no significant effect on all the investigated semen traits. Heritability estimates were 0.08, 0.52, 0.51, 0.04, and 0.49 for VOL, MM, LS, AS, and CONC, respectively. Repeatability estimates were 0.14, 0.82, 0.79, 0.06, and 0.78 for VOL, MM, LS, AS, and CONC, respectively. The genetic correlations between MM and each of LS and CONC were highly significant (0.99 ± 0.01 and 0.95 ± 0.14, respectively), and that between LS and CONC was also highly significant (0.92 ± 0.20). The high heritability estimates for MM, LS, and CONC combined with the favorable high significant genetic correlations between these traits indicated that direct selection for MM may be an effective method to enhance semen quality in Egyptian buffalo bulls and consequently improve fertility.

The trend of breeding value research in animal science: bibliometric analysis

This study aims to identify trends and hot topics in breeding value to support researchers in finding new directions for future research in that area. The data of this study consist of 7072 academic studies on breeding value in the Web of Science database. Network visualizations and in-depth bibliometric analysis were performed on cited references, authors, countries, institutions, journals, and keywords through CiteSpace. VanRaden (2008) is the most cited work and has an essential place in the field. The most prolific writer is Ignacy Misztal. While the most productive country in breeding value studies is the United States, the People's Republic of China is an influential country that has experienced a strong citation burst in the last 3 years. The National Institute for Agricultural Research and Wageningen University are important institutions that play a critical role in connecting other institutions. Also, these two institutions have the highest centrality values. "Genomic prediction" is the outstanding sub-study field in the active clusters appearing in the analysis results. We have summarized the literature on breeding value, including publication information, country, institution, author, and journal. We can say that hot topics today are "genome-wide association", "feed efficiency", and "genomic prediction". While the studies conducted in the past years have focused on economic value and accuracy, the studies conducted in recent years have started to be studies that consider technological developments and changing world conditions such as global warming and carbon emission.

Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

BACKGROUND

The reduction in phenotypic performance of a population due to mating between close relatives is called inbreeding depression. The genetic background of inbreeding depression for semen traits is poorly understood. Thus, the objectives were to estimate the effect of inbreeding and to identify genomic regions underlying inbreeding depression of semen traits including ejaculate volume (EV), sperm concentration (SC), and sperm motility (SM). The dataset comprised ~ 330 K semen records from ~ 1.5 K Holstein bulls genotyped with 50 K single nucleotide polymorphism (SNP) BeadChip. Genomic inbreeding coefficients were estimated using runs of homozygosity (i.e., F_ROH > 1 Mb) and excess of SNP homozygosity (F_SNP). The effect of inbreeding was estimated by regressing phenotypes of semen traits on inbreeding coefficients. Associated variants with inbreeding depression were also detected by regressing phenotypes on ROH state of the variants.

RESULTS

Significant inbreeding depression was observed for SC and SM (p < 0.01). A 1% increase in F_ROH reduced SM and SC by 0.28% and 0.42% of the population mean, respectively. By splitting F_ROH into different lengths, we found significant reduction in SC and SM due to longer ROH, which is indicative of more recent inbreeding. A genome-wide association study revealed two signals positioned on BTA 8 associated with inbreeding depression of SC (p < 0.00001; FDR < 0.02). Three candidate genes of GALNTL6, HMGB2, and ADAM29, located in these regions, have established and conserved connections with reproduction and/or male fertility. Moreover, six genomic regions on BTA 3, 9, 21 and 28 were associated with SM (p < 0.0001; FDR < 0.08). These genomic regions contained genes including PRMT6, SCAPER, EDC3, and LIN28B with established connections to spermatogenesis or fertility.

CONCLUSIONS

Inbreeding depression adversely affects SC and SM, with evidence that longer ROH, or more recent inbreeding, being especially detrimental. There are genomic regions associated with semen traits that seems to be especially sensitive to homozygosity, and evidence to support some from other studies. Breeding companies may wish to consider avoiding homozygosity in these regions for potential artificial insemination sires.

Review: The ovarian follicular reserve - implications for fertility in ruminants

Ruminants are born with a finite number of healthy ovarian follicles and oocytes (ovarian reserve) and germ cell proliferation in the developing foetal gonad predominantly occurs during early gestation. Two markers have been established to reliably estimate the size of the ovarian reserve in cattle: the number of antral follicles ≤3 mm in diameter recruited per follicular wave (Antral Follicle Count, AFC) and peripheral concentrations of the Anti-Müllerian hormone (AMH). Studies that used one or both indicators show that the size of ovarian reserve varies greatly among age-matched individuals, but is highly repeatable in the same animal. Conditions during prenatal life are likely among the causes of such variation in the ovarian reserve. In addition, the size of the ovarian reserve is a moderately heritable trait in cattle. The association between ovarian reserve and fertility is controversial. Several studies indicate that cattle with a low ovarian reserve have phenotypic characteristics that are associated with suboptimal fertility. On the contrary, the presence and absence of a positive association between AFC and/or AMH and fertility measures (i.e. no. on services/conception, pregnancy rates, pregnancy loss) have been equally reported in cattle. In conclusion, the size of the ovarian reserve in the progeny can be enhanced by improving management of the dam from preconception to early gestation and also through genetic selection. However, although the ovarian reserve may be among the determinants of reproductive success in ruminants, the use of AFC/AMH as reliable predictors of fertility is yet to be established. Furthermore, the possibility that there is a complex interaction of AFC, AMH and reproduction has yet to be fully characterised and exploited to improve fertility in cattle.

Review: Genetic mutations affecting bull fertility

Cattle are a well-suited "model organism" to study the genetic underpinnings of variation in male reproductive performance. The adoption of artificial insemination and genomic prediction in many cattle breeds provide access to microarray-derived genotypes and repeated measurements for semen quality and insemination success in several thousand bulls. Similar-sized mapping cohorts with phenotypes for male fertility are not available for most other species precluding powerful association testing. The repeated measurements of the artificial insemination bulls' semen quality enable the differentiation between transient and biologically relevant trait fluctuations, and thus, are an ideal source of phenotypes for variance components estimation and genome-wide association testing. Genome-wide case-control association testing involving bulls with either aberrant sperm quality or low insemination success revealed several causal recessive loss-of-function alleles underpinning monogenic reproductive disorders. These variants are routinely monitored with customised genotyping arrays in the male selection candidates to avoid the use of subfertile or infertile bulls for artificial insemination and natural service. Genome-wide association studies with quantitative measurements of semen quality and insemination success revealed quantitative trait loci for male fertility, but the underlying causal variants remain largely unknown. Moreover, these loci explain only a small part of the heritability of male fertility. Integrating genome-wide association studies with gene expression and other omics data from male reproductive tissues is required for the fine-mapping of candidate causal variants underlying variation in male reproductive performance in cattle.

Heritability Estimation Approaches Utilizing Genome-Wide Data

Prior to the development of genome-wide arrays and whole genome sequencing technologies, heritability estimation mainly relied on the study of related individuals. Over the past decade, various approaches have been developed to estimate SNP-based narrow-sense heritability (h SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ ) in unrelated individuals. These latter approaches use either individual-level genetic variations or summary results from genome-wide association studies (GWAS). Recently, several studies compared these approaches using extensive simulations and empirical datasets. However, sparse information on hands-on training necessitates revisiting these approaches from the perspective of a stepwise guide for practical applications. Here, we provide an overview of the commonly used SNP-heritability estimation approaches utilizing genome-wide array, imputed or whole genome data from unrelated individuals, or summary results. We not only discuss these approaches based on their statistical concepts, utility, advantages, and limitations, but also provide step-by-step protocols to apply these approaches. For illustration purposes, we estimateh SNP 2 ${\rm{h}}_{{\rm{SNP}}}^2$ of height and BMI utilizing individual-level data from The Northern Finland Birth Cohort (NFBC) and summary results from the Genetic Investigation of ANthropometric Traits (GIANT;) consortium. We present this review as a template for the researchers who estimate and use heritability in their studies and as a reference for geneticists who develop or extend heritability estimation approaches. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: GREML (GCTA) Alternate Protocol 1: Stratified GREML Basic Protocol 2: LDAK Alternate Protocol 2: Stratified LDAK Basic Protocol 3: Threshold GREML Basic Protocol 4: LD score (LDSC) regression Basic Protocol 5: SumHer.

Genomic dominance variance analysis of health and milk production traits in German Holstein cattle

Genomic analyses commonly explore the additive genetic variance of traits. The non-additive variance, however, is usually small but often significant in dairy cattle. This study aimed at dissecting the genetic variance of eight health traits that recently entered the total merit index in Germany and the somatic cell score (SCS), as well as four milk production traits by analysing additive and dominance variance components. The heritabilities were low for all health traits (between 0.033 for mastitis and 0.099 for SCS), and moderate for the milk production traits (between 0.261 for milk energy yield and 0.351 for milk yield). For all traits, the contribution of dominance variance to the phenotypic variance was low, varying between 0.018 for ovarian cysts and 0.078 for milk yield. Inbreeding depression, inferred from the SNP-based observed homozygosity, was significant only for the milk production traits. The contribution of dominance variance to the genetic variance was larger for the health traits, ranging from 0.233 for ovarian cysts to 0.551 for mastitis, encouraging further studies that aim at discovering QTLs based on their additive and dominance effects.

Genomic prediction of service sire effect on female reproductive performance in Holstein cattle: A comparison between different methods, validation population and marker densities

Reproductive traits of dairy cattle are bound to the actual efficiency of farm operation, which therefore show great economic importance. Among them, some traits were deemed to be simultaneously affected by service sire and mating cow. Service sires are proved to play an important role in reproduction process of cows. However, limited study explored the genetic effect of service sire (GESS), let alone the genomic prediction of this effect. In the present study, 2244 genotyped bulls together with phenotypic records were used to predict the GESS on conception rate, 56-day non-return rate, calving ease, stillbirth and gestation length. The feasibilities of multi-step genomic best linear unbiased predictor (msGBLUP) and single-step genomic best linear unbiased predictor (ssGBLUP) were investigated under different scenarios, that is, different marker densities and validation population. The predictive accuracies and unbiasedness for GESS ranged from 0.159 to 0.647 and from 0.202 to 2.018, respectively, when validated on young bulls, while the accuracies and unbiasedness ranged from 0.409 to 0.802 and 0.333 to 1.146 when validated on random split data sets. It is feasible to predict GESS on reproductive traits by using a linear mixed model and genomic data, and high-density marker panel had limited contribution to the prediction. This research investigated the potential factors that influence the genomic prediction of GESS on reproductive traits and indicated the possibility of genomic selection on GESS, both in ideal and practical circumstances.

Candidate genes for mastitis resistance in dairy cattle: a data integration approach

BACKGROUND

Inflammation of the mammary tissue (mastitis) is one of the most detrimental health conditions in dairy ruminants and is considered the most economically important infectious disease of the dairy sector. Improving mastitis resistance is becoming an important goal in dairy ruminant breeding programmes. However, mastitis resistance is a complex trait and identification of mastitis-associated alleles in livestock is difficult. Currently, the only applicable approach to identify candidate loci for complex traits in large farm animals is to combine different information that supports the functionality of the identified genomic regions with respect to a complex trait.

METHODS

To identify the most promising candidate loci for mastitis resistance we integrated heterogeneous data from multiple sources and compiled the information into a comprehensive database of mastitis-associated candidate loci. Mastitis-associated candidate genes reported in association, expression, and mouse model studies were collected by searching the relevant literature and databases. The collected data were integrated into a single database, screened for overlaps, and used for gene set enrichment analysis.

RESULTS

The database contains candidate genes from association and expression studies and relevant transgenic mouse models. The 2448 collected candidate loci are evenly distributed across bovine chromosomes. Data integration and analysis revealed overlaps between different studies and/or with mastitis-associated QTL, revealing promising candidate genes for mastitis resistance.

CONCLUSION

Mastitis resistance is a complex trait influenced by numerous alleles. Based on the number of independent studies, we were able to prioritise candidate genes and propose a list of the 22 most promising. To our knowledge this is the most comprehensive database of mastitis associated candidate genes and could be helpful in selecting genes for functional validation studies.

Age-dependent genetic and environmental variance of semen quality in Nordic Holstein bulls

The aim of this study was to estimate genetic and environmental parameters, across bull's age, for semen quality traits including pre- and postcryopreservation semen concentration, sperm motility, and sperm viability as well as ejaculate volume and number of doses per ejaculate. A data set on 96,595 ejaculates from 2,831 Nordic Holstein bulls collected between 2006 and 2019 was used. Genetic and environmental parameters were estimated using a random regression model and applying the average-information REML approach. Spline functions were chosen to fit the additive genetic and permanent environmental effects across bull's age, and the optimal number of knots was chosen using cross validation. Residual variance heterogeneity was assumed in different bull age classes. The estimated repeatabilities of semen quality traits ranged from 0.16 to 0.85 across different ages of bulls. The estimated heritabilities of semen quality traits ranged from 0.02 to 0.56 across different ages of bulls. The results indicate possibilities for genetic improvement of semen quality traits through selective breeding.

Estimation of the Genetic Components of (Co)variance and Preliminary Genome-Wide Association Study for Reproductive Efficiency in Retinta Beef Cattle

In this study, we analyzed the variation of reproductive efficiency, estimated as the deviation between the optimal and real parity number of females at each stage of the cow's life, in 12,554 cows belonging to the Retinta Spanish cattle breed, using classical repeatability and random regression models. The results of the analyses using repeatability model and the random regression model suggest that reproductive efficiency is not homogeneous throughout the cow's life. The h² estimate for this model was 0.30, while for the random regression model it increased across the parities, from 0.24 at the first calving to 0.51 at calving number 9. Additionally, we performed a preliminary genome-wide association study for this trait in a population of 252 Retinta cows genotyped using the Axiom Bovine Genotyping v3 Array. The results showed 5 SNPs significantly associated with reproductive efficiency, located in two genomic regions (BTA4 and BTA28). The functional analysis revealed the presence of 5 candidate genes located within these regions, which were previously involved in different aspects related to fertility in cattle and mice models. This new information could give us a better understanding of the genetic architecture of reproductive traits in this species, as well as allow us to accurately select more fertile cows.

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.

Machine Learning-Based Co-Expression Network Analysis Unravels Potential Fertility-Related Genes in Beef Cows

Simple Summary

Female reproductive failure is still a challenge for the beef industry. Several biological processes that underlie fertility-related traits, such as the establishment of pregnancy and embryo survival, are still unclear. Increased availability of transcriptomic data has allowed a deep investigation of the potential mechanisms involved in fertility. This study investigated candidate gene biomarkers predictive of pregnancy status and underlying fertility-related networks. To this end, we integrated gene expression profiles through supervised machine learning and gene network modeling. We identified nine biologically relevant endometrial gene biomarkers that could discriminate against pregnancy status in cows. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. This study outlined key pathways involved with pregnancy success and provided predictive candidate biomarkers for pregnancy outcome in cows.

Abstract

Reproductive failure is still a challenge for beef producers and a significant cause of economic loss. The increased availability of transcriptomic data has shed light on the mechanisms modulating pregnancy success. Furthermore, new analytical tools, such as machine learning (ML), provide opportunities for data mining and uncovering new biological events that explain or predict reproductive outcomes. Herein, we identified potential biomarkers underlying pregnancy status and fertility-related networks by integrating gene expression profiles through ML and gene network modeling. We used public transcriptomic data from uterine luminal epithelial cells of cows retrospectively classified as pregnant (P, n = 25) and non-pregnant (NP, n = 18). First, we used a feature selection function from BioDiscML and identified SERPINE3, PDCD1, FNDC1, MRTFA, ARHGEF7, MEF2B, NAA16, ENSBTAG00000019474, and ENSBTAG00000054585 as candidate biomarker predictors of pregnancy status. Then, based on co-expression networks, we identified seven genes significantly rewired (gaining or losing connections) between the P and NP networks. These biomarkers were co-expressed with genes critical for uterine receptivity, including endometrial tissue remodeling, focal adhesion, and embryo development. We provided insights into the regulatory networks of fertility-related processes and demonstrated the potential of combining different analytical tools to prioritize candidate genes.

The impact of using different ancestral reference populations in assessing crossbred population admixture and influence on performance

Crossbreeding is a process in which animals from different breeds are mated together. The animals produced will exhibit a combination of both additive and non-additive genetic improvement from parental breeds that increase heterozygosity and negate inbreeding depression. However, crossbreeding may also break up the unique and often beneficial gene combinations in parental breeds, possibly reducing performance potential as the benefits of heterosis depends on the type of crossbreeding systems used and heritability of the traits. This effect of crossbreeding, especially on the genome architecture, is still poorly understood with respect to 3-breed crossbreeding systems. Thus, this study examined variation in genomic ancestry estimations relative to pedigree-based estimations and correlated breed composition to key production and health traits. Two rotational crossbred populations, referenced as ProCROSS and Grazecross were assessed and totaled 607 crossbred cattle. ProCROSS is a product of rotational crossbreeding of Viking Red (VKR), Holstein (HOL), and Montbeliarde (MON). In contrast, Grazecross consists of Viking Red (VKR), Normande (NOR), and Jersey (JER). Both breeding programs were aimed at capitalizing on the positive effect of heterosis. The VKR is a marketing term for Swedish Red, Danish Red, and Finnish Ayrshire breed which complicated breed determination. Therefore, genomic breed composition estimates were compared using two different representations of VKR, one of which was based on parents used in the crossing system and a second based on genotypes from the ancestral breeds that comprise VKR. Variation of breed composition estimates were assessed between pedigree and genome-based predictions. Lastly, Genomic estimations were correlated with production and health traits by comparing extreme performance groups to identify the relationship between breed ancestry and performance. With the exception of the JER breed composition in Grazecross, all other estimates of the purebred contribution to the ProCROSS and Grazecross showed a significant difference in their genomic breed estimation when using the VKR ancestral versus the VKR parental reference populations for admixture analysis. These observations were expected given the different relationship of each VKR representation to the crossbred cattle. Further analysis showed that regardless of which VKR reference population was used, the degree of MON and HOL breed composition plays a significant role in milk and fat production in ProCROSS, while the degree of VKR and NOR ancestry were related to improved health performance in Grazecross. In all, identifying the most appropriate and informative animals to use as reference animals in admixture analysis is an important factor when interpreting results of relationship and population structure, but some degree of uncertainty exists when assessing the relationship of breed composition to phenotypic performance.

Roles of MEF2A and MyoG in the transcriptional regulation of bovine LATS2 gene

As an important downstream effector gene in the hippo signaling pathway, large tumor suppressor gene 2 (LATS2) is involved in cell proliferation and differentiation, organ size and tissue regeneration, and plays an important role in regulating the growth and development of animal muscles. The purpose of this study is to explore the temporal expression of bovine LATS2 gene, and determine the key transcription factors for regulating bovine LATS2 gene. The result showed that bovine LATS2 gene was highly expressed in liver and longissimus dorsi, and was up-regulated in infancy muscle. In addition, it was highly expressed on the 2th day during the differentiation stage of myoblast. The upstream 1.7 Kb sequence of the 5 'translation region of bovine LATS2 gene was cloned, and 7 different deletion fragments were amplified by the upstream primers. These fragments were constructed into double luciferase reporter vectors and transfected into myoblasts and myotubes cells, respectively to detect the core promoter regions. In addition, the key transcription factors of the core promoter sequence of the bovine LATS2 gene were analyzed and predicted by online software. Combining with site-directed mutations, siRNA interference and chromatin immunoprecipitation technology, it was identified that MEF2A and MyoG combined in core promoter region (-248/-56) to regulate the transcription activity of bovine LATS2 gene. The results have laid a theoretical foundation for exploring the molecular regulation mechanism of LATS2 gene in the process of muscle growth.

Breeding Dairy Cattle for Female Fertility and Production in the Age of Genomics

Phenotypic and genetic changes for female fertility and production traits in the Israeli Holstein population over the last three decades were studied in order to determine if long term selection has resulted in reduced heritability and negative genetic correlations. Annual means for conception status, defined as the inverse of the number of inseminations to conception in percent, decreased from 55.6 for cows born in 1983 to 46.5 for cows born in 2018. Mean estimated breeding values increased by 1.8% for cow born in 1981 to cows born in 2018. Phenotypic records from 1988 to 2016 for the nine Israeli breeding index traits were divided into three time periods for multi-trait REML analysis by the individual animal model. For all traits, heritabilities increased or stayed the same for the later time periods. Heritability for conception status was 0.05. The first parity genetic correlation between conception status and protein yield was −0.38. Heritabilities decreased with the increase in parity for protein but remained the same for conception status. Realized genetic trends were greater than expected for cows born from 2008 through 2016 for somatic cell score, conception status and herd-life, and lower than expected for the production traits.

Estimation of Genetic Parameters for Heifer and Cow Fertility Traits Derived from On-Farm AI Service Records of South African Holstein Cattle

This study aimed to derive additional fertility traits from service data and estimate their genetic parameters for their possible inclusion in the South African Holstein cattle breeding programs. Service records (n = 64,464) were collected from 18 South African Holstein herds using on-farm automated milk recording systems. Using a multivariate model, the data were used to estimate heritabilities and correlations among several fertility traits. The pedigree data consisted of information on 18,592 animals born between 1981 and 2013. Heritability estimates observed were low to moderate (0.02 ± 0.00 to 0.24 ± 0.00), indicating that there is some genetic basis for the explored fertility traits to warrant selection. The genetic correlations observed between fertility traits were generally favorable, with some high correlations between age at first service (AFS) and services per conception for heifers (SPCh) (0.73 ± 0.00) and between days from calving to first service (CFS) and services per conception for cows (SPC) (0.90 ± 0.01). Positive genetic correlations indicate that improvement in one trait is coupled with a correlated genetic increase in another trait. The studied fertility traits could be used in addition to AFC and CI to serve as a basis for the selection of reproduction in dairy cattle to minimize selection bias.

Genetic evaluation of semen production potential in Indigenous bulls using random regression models in a Bayesian framework

Genetic potential of indigenous bulls with respect to semen production traits over the age of the bulls at semen collection was analyzed using random regression models (RRMs). Data pertaining to 59,641 ejaculates from 189 bulls of 18 indigenous breeds collected from BAIF (Bharatiya Agro Industries Foundation) was utilized for this study. Six semen production traits, viz., ejaculate volume (EV, ml), sperm concentration (SC, 10⁹/ml), initial sperm motility (ISM, %), post-thaw motility (PTM, %), the total number of spermatozoa per ejaculate (TNS, 10⁹/ejaculate), and the theoretical number of semen doses (TNSD) were studied. Univariate and RRM were used to obtain variance components and genetic parameter estimates. Two hundred thousand Gibbs samples were generated for each trait with a burn-in of 20,000 and thinning interval of 50 in a Bayesian framework. Legendre polynomials with orders of fit up to 5 for additive and permanent environmental effects were used. RRM modeled the heritability and repeatability for all ages between 3 and 10 years (productive lifespan). Heritability estimates ranged from 0.18 to 0.36, 0.18 to 0.45, 0.02 to 0.06, 0 to 0.001, 0.09 to 0.32, and 0.14 to 0.42 while the repeatability estimates ranged from 0.41 to 0.72, 0.36 to 0.79, 0.04 to 0.10, 0 to 0.001, 0.37 to 0.56, and 0.32 to 0.57 for EV, SC, ISM, PTM, TNS, and TNSD, respectively. Variability of estimates over the age of the bulls obtained through RRM could be useful to further refine the breeding program for age at selection, deciding the production period and age at culling.

Re-assessing the importance of linear type traits in predicting genetic merit for survival in an aging Holstein-Friesian dairy cow population

The cumulative improvement achieved in the genetic merit for reproductive performance in dairy populations will likely improve dairy cow longevity; therefore, it is time to reassess whether linear type traits are still suitable predictors of survival in an aging dairy cow population. The objective of the present study was therefore to estimate the genetic correlations between linear type traits and survival from one parity to the next and, in doing so, evaluate if those genetic correlations change with advancing parity. After edits, 152,894 lactation survival records (first to ninth parity) were available from 52,447 Holstein-Friesian cows, along with linear type trait records from 52,121 Holstein-Friesian cows. A series of bivariate random regression models were used to estimate the genetic covariances between survival in different parities and each linear type trait. Heritability estimates for survival per parity ranged from 0.02 (SE = 0.004; first parity) to 0.05 (SE = 0.01; ninth parity). Pairwise genetic correlations between survival among different parities varied from 0.42 (first and ninth parity) to 1.00 (eighth to ninth parity), with the strength of these genetic correlations being inversely related to the interval between the compared parities. The genetic correlations between survival and the individual linear type traits varied across parities for 9 of the 20 linear type traits examined, but the correlations with only 3 of these linear type traits strengthened as the cows aged; these 3 traits were rear udder height, teat length, and udder depth. Given that linear type traits are frequently scored in first parity and are genetically correlated with survival in older parities, they may be suitable early predictors of survival, especially for later parity cows. Additionally, the direction of the genetic correlations between survival and rear udder height, teat length, and udder depth did not change between parities; hence, selection for survival in older parities using these linear type traits should not hinder genetic improvement for survival in younger parities.

Genomic dissection of repeatability considering additive and non-additive genetic effects for semen production traits in beef and dairy bulls

The low heritability and moderate repeatability of semen production traits in beef and dairy bulls suggest that non-additive genetic effects, such as dominance and epistatic effects, play an important role in semen production and should therefore be considered in genetic improvement programs. In this study, the repeatability of semen production traits in Japanese Black bulls (JB) as beef bulls and Holstein bulls (HOL) as dairy bulls was evaluated by considering additive and non-additive genetic effects using the Illumina BovineSNP50 BeadChip. We also evaluated the advantage of using more complete models that include non-additive genetic effects by comparing the rank of genotyped animals and the phenotype prediction ability of each model. In total, 65,463 records for 615 genotyped JB and 48,653 records for 845 genotyped HOL were used to estimate additive and non-additive (dominance and epistatic) variance components for semen volume (VOL), sperm concentration (CON), sperm motility (MOT), MOT after freeze-thawing (aMOT), and sperm number (NUM). In the model including both additive and non-additive genetic effects, the broad-sense heritability (0.17-0.43) was more than twice as high as the narrow-sense heritability (0.04-0.11) for all traits and breeds, and the differences between the broad-sense heritability and repeatability were very small for VOL, NUM, and CON in both breeds. A large proportion of permanent environmental variance was explained by epistatic variance. The epistatic variance as a proportion of total phenotypic variance was 0.07-0.33 for all traits and breeds. In addition, heterozygosity showed significant positive relationships with NUM, MOT, and aMOT in JB and NUM in HOL, when the heterozygosity rate was included as a covariate. In a comparison of models, the inclusion of non-additive genetic effects resulted in a re-ranking of the top genotyped bulls for the additive effects. Adjusting for non-additive genetic effects could be expected to produce a more accurate breeding value, even if the models have similar fitting. However, including non-additive genetic effects did not improve the ability of any model to predict phenotypic values for any trait or breed compared with the predictive ability of a model that includes only additive effects. Consequently, although non-additive genetic effects, especially epistatic effects, play an important role in semen production traits, they do not improve prediction accuracy in beef and dairy bulls.

A Post-GWAS Functional Analysis Confirming Effects of Three BTA13 Genes CACNB2, SLC39A12, and ZEB1 on Dairy Cattle Reproduction

In our previous GWAS of Chinese and Nordic dairy cattle, genes CACNB2, SLC39A12, and ZEB1 locating on BTA 13 were suggested as candidate genes for reproduction. In this study, validation of these associations was performed in an independent population with records of nine reproductive traits. More importantly, functions of these genes in the reproductive process were verified by employing the expression data of ovarian follicles. The potential variants within the three genes were firstly detected in 68 Chinese Holstein bulls, and then screened in 1,588 Chinese Holstein cows using the KASP (Kompetitive allele-specific PCR) method. There were nine variants with polymorphisms in CACNB2, five in SLC39A12, and four in ZEB1, respectively, of which one SNP was in the upstream regulatory region, two in exon region, four in downstream regulatory region, and 11 SNPs in intronic regions. Amongst the 18 variants, g.33267056T/G in CACNB2 explained the largest phenotypic variance for age at first calving (0.011%), interval from first to last insemination (0.004%), and calving ease (0.002%), while g.32751518G/A in SLC39A12 contributed the most to stillbirth in heifers (0.038%). Two haplotype blocks were constructed for CACNB2 while one each for SLC39A12 and ZEB1, which were significantly associated with five reproductive traits, including age at the first service, age at the first calving, calving ease in heifers and cows, and the interval from calving to the first insemination. We then studied the profile of gene expression in granulosa cells isolated from four developmental stages of ovarian follicles from eight dairy cows. All three genes were differentially expressed between ovarian follicles with different sizes (p < 0.05), indicating their potential roles in the reproductive process of dairy cows. This study successfully demonstrated the associations of three BTA 13 genes CACNB2, SLC39A12, and ZEB1 with reproduction and further examined their expression levels in ovarian follicles directly. These findings can be beneficial for the ongoing genomic selection program for reproductive traits which have long been considered as traits that are difficult to achieve genetic improvement due to the lack of efficient genetic markers.