Review: Genomics of bull fertility

Biomarker-based high-throughput sperm phenotyping: Andrology in the age of precision medicine and agriculture

Reproductive efficiency is crucial for animal agriculture. This economically important aspect can be influenced by environmental burdens, nutritional imbalance, and gonadal or gametic malformations of genetic origin. Successful implementation of genomic-driven selective breeding in cattle depends on the reproductive performance of artificial insemination (AI) sires with valuable genomic production traits. Reproduction is traditionally viewed as a complex set of polygenic traits that are negatively impacted by using a small number of often closely related sires selected for AI due to their superior genetics. Despite recent progress, it remains difficult to define relationships between sire genome and variation in sperm phenotypes, even though several types of heritable, non-compensable sperm defects have been identified. In this review, we discuss the concept of sperm quality biomarker discovery and genomics of male fertility. We also outline a multidisciplinary genome-to-phenome approach for investigating heritable mutations and their impacts on bull fertility, sperm phenotypes and paternal contributions to early pregnancy. High-precision phenotyping requires novel, state-of-the-art instrumentation for sperm quality evaluation and development of new biomarkers of sperm quality in farm animals, with potential for incorporation into andrology-specific machine learning protocols and translation to human andrology. We conclude that reproduction is a complex phenotype that can be deciphered and explored for more precise male fertility evaluation and higher reproductive efficiency.

North American perspectives for cattle production and reproduction for the next 20 years

Ruminant species are important to human society due to their ability to convert human-inedible sources of energy and protein to human-edible food. Greater efficiency of meat and milk production will require the management of the complex reproductive biology of many cattle with a limited capacity and limited budget within a smaller, hotter, and more climatically erratic land area. The over-riding drivers of new reproductive technologies in North America will be smaller economic margins, larger herd size, fewer agricultural workers per farm, and a greater reliance on automation to offset the reduced agricultural labor force. Climate change and the possibility that consumers may dictate the procedures used for animal reproductive management may present additional challenges. The successes of the past 20 years (timed AI, genomic selection for fertility in both bulls and cows, automated estrus detection, chemical and ultrasonographic pregnancy diagnosis, and gender selected semen) will be improved upon in the next 20 years as most of these technologies can be optimized further. Improving embryo technologies and increasing our understanding of embryonic loss may provide the greatest challenges for the future. Researchers must attempt to devise practical methods to release more follicles from the primordial follicle pool so that a greater number of oocytes and embryos can be harvested from individual animals. Embryonic loss continues to be an unsolved question that cuts the total number of potential offspring by nearly one-third. The identification of fertile embryos in vitro, better methods of cryopreservation, and the optimization of methods of transfer into recipient animals may improve the efficiency of advanced embryo technologies. The derivation of oocytes, sperm, and embryos from pluripotent stem cells may yield a vast supply of gametes and embryos from genetically superior animals and radically change the reproductive management in the future.

Advancing Dairy and Beef Genetics Through Genomic Technologies

The US beef and dairy industries have made remarkable advances in sustainability and productivity through technological advancements, including selective breeding. Yet, challenges persist due to the complex nature of quantitative traits. While the beef industry has progressed in adopting genomic technologies, the availability of phenotypic data remains an obstacle. To meet the need for sustainable production systems, novel traits are being targeted for selection. Additionally, emerging approaches such as genome editing and high-throughput phenotyping hold promise for further genetic progress. Future research should address the challenges of translating functional genomic findings into practical applications, while simultaneously harnessing analytical methods.

Genomic and transcriptomic evaluations of infertile or subfertile Arunachali yak sperm

Sperm infertility or subfertility is detrimental to the precious highland germplasm like yak whose population has been gradually declining in India. Understanding the 'omic' landscape of infertile or subfertile yak sperm can reveal some interesting insights. In an attempt to do the same, this study considered the semen of infertile or subfertile yak bulls for whole-genome and transcriptome evaluations. DNA sequencing revealed that the yak sperm genome contains the necessary genes to carry out all the important biological processes related to the growth, development, survival and multiplication of an organism. Interestingly, RNA Seq results highlighted that genes like VAMP7, MYLK, ARAP2 and MARCH6 showed increased expression, while biological processes related to immune response (GO:0043308, GO:0002447, GO:0002278, GO:0043307, GO:0043312, GO:0002283, GO:0043299 and GO:0002446) were significantly overrepresented. These findings hint at a possible role played by immune system in regulating infertility or subfertility in yaks. Further, in-depth studies can validate these findings and help in improving our biological understanding in this area.

Biomarker-based human and animal sperm phenotyping: the good, the bad and the ugly†

Conventional, brightfield-microscopic semen analysis provides important baseline information about sperm quality of an individual; however, it falls short of identifying subtle subcellular and molecular defects in cohorts of "bad," defective human and animal spermatozoa with seemingly normal phenotypes. To bridge this gap, it is desirable to increase the precision of andrological evaluation in humans and livestock animals by pursuing advanced biomarker-based imaging methods. This review, spiced up with occasional classic movie references but seriously scholastic at the same time, focuses mainly on the biomarkers of altered male germ cell proteostasis resulting in post-testicular carryovers of proteins associated with ubiquitin-proteasome system. Also addressed are sperm redox homeostasis, epididymal sperm maturation, sperm-seminal plasma interactions, and sperm surface glycosylation. Zinc ion homeostasis-associated biomarkers and sperm-borne components, including the elements of neurodegenerative pathways such as Huntington and Alzheimer disease, are discussed. Such spectrum of biomarkers, imaged by highly specific vital fluorescent molecular probes, lectins, and antibodies, reveals both obvious and subtle defects of sperm chromatin, deoxyribonucleic acid, and accessory structures of the sperm head and tail. Introduction of next-generation image-based flow cytometry into research and clinical andrology will soon enable the incorporation of machine and deep learning algorithms with the end point of developing simple, label-free methods for clinical diagnostics and high-throughput phenotyping of spermatozoa in humans and economically important livestock animals.

Factors influencing pregnancy per artificial insemination (AI) and embryonic mortality in Nelore females subjected to timed-AI in Brazil

A greater understanding of factors influencing fertility is essential to improve pregnancy rates and reduce the occurrence of embryonic mortality in beef herds. The objective of the current study was to evaluate retrospective data of pregnancy per artificial insemination (P/AI) and pregnancy loss in Nelore females subjected to timed-AI (TAI) in Brazil. Data from 40,104 TAI collected from six breeding seasons (2016-2022) were analyzed, and the effects of animal category (e.g., classification based on age and parity), farm, month of parturition, sire, sire breed (Nelore vs Angus), estrus expression at TAI, animal temperament, and body condition scores (BCS) were evaluated. P/AI and pregnancy loss were affected (P < 0.001) by animal category. There was also an effect of farm (P = 0.0013) on P/AI and pregnancy loss (P = 0.001), as P/AI ranged from 49.28% and 55.58% and pregnancy loss from 3.37% to 6.89% across the herds evaluated. Month of parturition also affected (P < 0.001) P/AI and was higher for cows that became pregnant at the beginning of the previous breeding season. Calmer animals, presenting lower velocity scores while exiting the chute following TAI, achieved higher P/AI (P < 0.001). Lower BCS at TAI was associated (P < 0.001) with increased pregnancy loss, and BCS gain following AI was associated (P < 0.001) with reduced rates of embryonic mortality. There was a major effect (P < 0.001) of sire on P/AI and pregnancy loss, as P/AI ranged from 11% to 79%, and embryonic mortality from 0% to 40% for the bulls used in the study, highlighting the importance of the sire fertility on overall pregnancy success. Results from the current study reinforce the idea that animal age and parity at the beginning of the breeding season, BCS at the onset of estrous synchronization, BCS gain following AI, estrus expression at TAI, sire, and month of parturition are important factors influencing P/AI and rates of embryonic mortality in beef herds.

Population dynamics of potentially harmful haplotypes: a pedigree analysis

BACKGROUND

The identification of low-frequency haplotypes, never observed in homozygous state in a population, is considered informative on the presence of potentially harmful alleles (candidate alleles), putatively involved in inbreeding depression. Although identification of candidate alleles is challenging, studies analyzing the dynamics of potentially harmful alleles are lacking. A pedigree of the highly endangered Gochu Asturcelta pig breed, including 471 individuals belonging to 51 different families with at least 5 offspring each, was genotyped using the Axiom PigHDv1 Array (658,692 SNPs). Analyses were carried out on four different cohorts defined according to pedigree depth and at the whole population (WP) level.

RESULTS

The 4,470 Linkage Blocks (LB) identified in the Base Population (10 individuals), gathered a total of 16,981 alleles in the WP. Up to 5,466 (32%) haplotypes were statistically considered candidate alleles, 3,995 of them (73%) having one copy only. The number of alleles and candidate alleles varied across cohorts according to sample size. Up to 4,610 of the alleles identified in the WP (27% of the total) were present in one cohort only. Parentage analysis identified a total of 67,742 parent-offspring incompatibilities. The number of mismatches varied according to family size. Parent-offspring inconsistencies were identified in 98.2% of the candidate alleles and 100% of the LB in which they were located. Segregation analyses informed that most potential candidate alleles appeared de novo in the pedigree. Only 17 candidate alleles were identified in the boar, sow, and paternal and maternal grandparents and were considered segregants.

CONCLUSIONS

Our results suggest that neither mutation nor recombination are the major forces causing the apparition of candidate alleles. Their occurrence is more likely caused by Allele-Drop-In events due to SNP calling errors. New alleles appear when wrongly called SNPs are used to construct haplotypes. The presence of candidate alleles in either parents or grandparents of the carrier individuals does not ensure that they are true alleles. Minimum Allele Frequency thresholds may remove informative alleles. Only fully segregant candidate alleles should be considered potentially harmful alleles. A set of 16 candidate genes, potentially involved in inbreeding depression, is described.

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.

Single nucleotide polymorphisms cumulating to genetic variation for fertility in crossbred (Bos taurus × Bos indicus) bull spermatozoa

Spermatozoa from high-fertile (HF) and low-fertile (LF) breeding bulls were subjected to high-throughput next-generation sequencing to identify important Single nucleotide polymorphisms (SNPs) and novel variants associated with fertility. A total of 77,038 genome-wide SNPs were identified, among which, 10,788 were novel variants. A total of 42,290 and 34,748 variants were recorded with 6115 and 4673 novel variants in in HF and LF bulls, respectively. Higher number of SNPs were identified in HF compared to LF bulls. GO analysis of filtered genes with significant variations in HF bulls indicated their involvement in oxidative phosphorylation and metabolic pathways. GO analysis of filtered genes with significant variation in LF bulls revealed their involvement in Ca2++ ion binding, structural constituent of ribosome, and biological processes like translation and ribosomal small subunit assembly. The study identified SNPs in candidate genes including TPT1, BOLA-DRA, CD74, RPS17, RPS28, RPS29, RPL14, RPL13, and RPS27A, which are linked to sperm functionality, survival, oxidative stress, and bull fertility. The identified SNPs could be used in selection of bulls for high fertility and the variation in these genes could be established as an explanation for the fertility differences in bulls upon validation in large number of bulls.

ADAMTS Proteases: Importance in Animal Reproduction

Many reproductive physiological processes, such as folliculogenesis, ovulation, implantation, and fertilization, require the synthesis, remodeling, and degradation of the extracellular matrix (ECM). The ADAMTS (A Disintegrin and Metalloproteinase with Thrombospondin Motifs) family genes code for key metalloproteinases in the remodeling process of different ECM. Several genes of this family encode for proteins with important functions in reproductive processes; in particular, ADAMTS1, 4, 5 and 9 are genes that are differentially expressed in cell types and the physiological stages of reproductive tissues. ADAMTS enzymes degrade proteoglycans in the ECM of the follicles so that the oocytes can be released and regulate follicle development during folliculogenesis, favoring the action of essential growth factors, such as FGF-2, FGF-7 and GDF-9. The transcriptional regulation of ADAMTS1 and 9 in preovulatory follicles occurs because of the gonadotropin surge in preovulatory follicles, via the progesterone/progesterone receptor complex. In addition, in the case of ADAMTS1, pathways involving protein kinase A (PKA), extracellular signal regulated protein kinase (ERK1/2) and the epidermal growth factor receptor (EGFR) might contribute to ECM regulation. Different Omic studies indicate the importance of genes of the ADAMTS family from a reproductive aspect. ADAMTS genes could serve as biomarkers for genetic improvement and contribute to enhance fertility and animal reproduction; however, more research related to these genes, the synthesis of proteins encoded by these genes, and regulation in farm animals is needed.

Novel interpretation of sperm stress test and morphology for maturity assessment of young Norwegian Red bulls

The use of genomic selection significantly reduces the age of dairy bulls entering semen production compared to progeny testing. The study aimed to identify early indicators that could be used for screening bulls during their performance testing period and could give us insight into their future semen production performance, acceptance for the AI station, and prediction of their future fertility. The study population consisted of 142 young Norwegian Red bulls enrolled at the performance test station, followed until we received semen production data, semen doses, and, subsequently, non-return rates (NR56) from the AI station. A range of semen quality parameters were measured with computer-assisted sperm analysis and flow cytometry from ejaculates collected from 65 bulls (9-13 months). The population morphometry of normal spermatozoa was examined, showing that Norwegian Red bulls at 10 months of age have homogenous sperm morphometry. Norwegian Red bulls could be separated into 3 clusters according to their sperm's reaction patterns to stress test and cryopreservation. Results of semi-automated morphology assessment of young Norwegian Red bulls showed that 42% of bulls rejected for the AI station and 18% of bulls accepted had ejaculates with abnormal morphology scores. For the youngest age group at 10 months, the mean (SD) proportion of spermatozoa with normal morphology was 77.5% (10.6). Using novel interpretation of sperm stress test combined with sperm morphology analysis and consecutive cryopreservation at a young age allowed identification of the candidate's sperm quality status. This could help breeding companies introduce young bulls earlier to the AI stations.

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.

Review: Evaluation of bull fertility. Functional and molecular approaches

With the term "assisted reproduction technologies" in modern cattle farming, one could imply the collection of techniques that aim at the optimal use of bovine gametes to produce animals of high genetic value in a time- and cost-efficient manner. The accurate characterisation of sperm quality plays a critical role for the efficiency of several assisted reproduction-related procedures, such as sperm processing, in vitro embryo production and artificial insemination. Bull fertility is ultimately a collective projection of the ability of a series of ejaculates to endure sperm processing stress, and achieve fertilisation of the oocyte and production of a viable and well-developing embryo. In this concept, the assessment of sperm functional and molecular characteristics is key to bull fertility diagnostics and prognostics. Among others, functional features linked to sperm plasma membrane, acrosome and DNA integrity are usually assessed as a measure of the ability of sperm to express the phenotypes that will allow them to maintain their homeostasis and orchestrate-in a strict temporal manner-the course of events that will enable the delivery of their genetic content to the oocyte upon fertilisation. Nevertheless, measures of sperm functionality are not always adequate indicators of bull fertility. Nowadays, advancements in the field of molecular biology have facilitated the profiling of several biomolecules in male gametes. The molecular profiling of bovine sperm offers a deeper insight into the mechanisms underlying sperm physiology and, thus, can reveal novel candidate markers for bull fertility prognosis. In this review, the importance of three organelles (the nucleus, the plasma membrane and the acrosome) for the characterisation of sperm fertilising capacity and bull fertility is discussed at functional and molecular levels. In particular, information about sperm head morphometry, chromatin structure, viability as well as the ability of sperm to capacitate and undergo the acrosome reaction are presented in relation to the cryotolerance of male gametes and bull fertility. Finally, major spermatozoal coding and non-coding RNAs, and proteins that are involved in the above-mentioned aspects of sperm functionality are also summarised.

A potent allele marker related to low bull conception rate in Japanese Black bulls

Over the years, there has been considerable variation in the bull conception rate (BCR) of Japanese Black cattle; moreover, several Japanese Black bulls with a low BCR of ≤10% have been identified. However, the alleles responsible for the low BCR are not determined yet. Therefore, in this study, we aimed to identify single-nucleotide polymorphisms (SNPs) for predicting low BCR. To this end, the genome of Japanese Black bulls was comprehensively examined by a genome-wide association study with whole-exome sequencing (WES), and the effect of the identified marker regions on BCR was determined. The WES analysis of six sub-fertile bulls with a BCR of ≤10% and 73 normal bulls with a BCR of ≥40% identified a homozygous genotype for low BCR in Bos taurus autosome 5 in the region between 116.2 and 117.9 Mb. The g.116408653G > A SNP in this region had the most significant effect on the BCR (P-value = 1.0 × 10^-23), and the GG (55.4 ± 11.2%) and AG (54.4 ± 9.4%) genotypes in the SNP had a higher phenotype than the AA (9.5 ± 6.1%) genotype for the BCR. The mixed model analysis revealed that g.116408653G > A was related to approximately 43% of the total genetic variance. In conclusion, the AA genotype of g.116408653G > A is a useful index for identifying sub-fertile Japanese Black bulls. Some positive and negative effects of SNP on the BCR were presumed to identify the causative mutations, which can help evaluate bull fertility.

Fertility results after exocervical insemination using goat semen cryopreserved with extenders based on egg yolk, skim milk, or soybean lecithin

To evaluate the effects of four extenders on the post-thaw quality and fertility of goat semen, six Yunshang Black bucks' semen was collected, pooled, diluted with Andromed® (Andr®), Optidyl® (Opt®), P3644 Sigma l-phosphatidylcholine (l-α SL), and skim milk-based (Milk) extenders, and then cryopreserved. The sperm motilities, abnormalities, membrane and acrosome integrity, mitochondrial activity, apoptosis, and reactive oxygen species (ROS) production were evaluated after thawing. After exocervical insemination with the thawed semen, the pregnancy, lambing, and twinning rates were recorded and compared. The results showed that sperm motilities, membrane integrity, acrosome integrity, mitochondrial activity, and viable spermatozoa were significantly higher in the Andr® and Opt® groups than those in the l-α SL and Milk groups (p < .05). Furthermore, there was no difference between Andr® and Opt® (p > .05). The sperm abnormality was lower in semen frozen with the Andr® or Opt® extenders, as compared to the l-α SL or Milk extender (p < .05). Regarding, the viable cells with low ROS production, the optimal results were obtained in the semen frozen with Andr® and Opt® extenders. Following exocervical insemination, the pregnancy and lambing rates in the Milk group were significantly lower than those in the other groups (p < .05). No difference was found in the pregnancy and lambing rates between Andr®, Opt®, and l-α SL (p > .05). Furthermore, the twinning rates were similar between these four groups (p > .05). In conclusion, egg yolk or skim milk can be substituted by soybean lecithin during cryopreservation of goat semen.

Associations between insulin-like factor 3, scrotal circumference and semen characteristics in young Norwegian Red bulls

With the integration of genomic selection in the cattle artificial insemination (AI) industry, bulls are selected for their semen production capacity and fertility at a younger age than previously. Norwegian Red bull calves selected as candidates to become future AI bulls based on their genomic breeding value are kept in a performance testing station from around the age of 3-12 months, allowing for sample collection and analysis of different parameters during their pre- and peripubertal period. Insulin-like factor 3 (INSL3) is a small peptide hormone specifically secreted by the mature Leydig cells of the testes. In the foetus, it induces the first phase of testicular descent and is considered to reflect Leydig cell development during puberty; it could therefore be an interesting early indicator of future semen production capacity. The main objective of our study was to evaluate the relationship between INSL3, scrotal circumference (SC), and semen characteristics. This is the first time INSL3 was measured in the Norwegian Red population. We collected blood samples for analysis of INSL3 from 142 Norwegian Red bulls at the performance testing station and measured their SC on the same day. Altogether, measurements were made at four time points: upon arrival at the performance testing station (quarantine (Q): 2-5 months) and later at approximately 6, 9 and 12 months of age. Information on season and place of birth were made available from the database of the breeding company Geno, together with data on semen characteristics from the test station and the AI station. The median SCs for age groups Q, 6, 9, and 12 were 15, 21.5, 29, and 34 cm, respectively. INSL3 was shown to be positively correlated with SC (R = 0.4) but not with any of the semen characteristics. Similarly, we found no correlation between SC and sperm characteristics from data on ejaculates analysed at the performance testing station and AI station. The mean sperm volume for the 31 selected bulls with at least 10 ejaculates produced in the AI station increased from 2.3 ml at the performance testing station to 6.4 ml at the AI station. The corresponding increase in mean sperm concentration was from 497 million/ml to 1 049 million/ml. We conclude that INSL3 exhibits high inter-individual variability in the Norwegian Red bull population, which cannot be explained by the parameters measured in this study. At present, INSL3 cannot be used as a biomarker of sperm production in this breed.

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.

Novel insights into genome-wide associations in Bos indicus reveal genetic linkages between fertility and growth

Bos indicus breed Sahiwal, famous for its optimum performance, has so far been genetically improved for performance traits based on phenotypic records and the genomic knowhow regarding genes, regions and biological processes underlying the complex quantitative traits is lacking. In this context, a Genome-wide Association Study was performed for fertility and growth traits in Sahiwal cattle to shed light on its genomic profile. A total of 46 SNPs were found associated with the traits at genome-wide suggestive threshold of P ≤ 10^-4. USP32, LRPPRC, PLA2G10, RRN3 and ASAP1 were identified as putative candidate genes for body weight at different ages. However, several genes mapped for growth traits like GREB1, PLA2G10, RAD51C, BIRC6, TEX14 and PEBP4 had significant physiological underpinnings in determining fertility of the animals. Moreover, Quantitative trait loci (QTL) identification revealed potential overlaps with the already reported QTLs for both fertility and growth for most of the traits. Further, candidate SNP enrichment analysis revealed an enriched biological process for birth weight with a significant reproductive role. Based on the findings, genetic linkages underlying fertility and growth could be discerned in Sahiwal population and may be utilized for improving fertility traits in future.

Unravelling the genetics of non-random fertilization associated with gametic incompatibility

In the dairy industry, mate allocation is dependent on the producer's breeding goals and the parents' breeding values. The probability of pregnancy differs among sire-dam combinations, and the compatibility of a pair may vary due to the combination of gametic haplotypes. Under the hypothesis that incomplete incompatibility would reduce the odds of fertilization, and complete incompatibility would lead to a non-fertilizing or lethal combination, deviation from Mendelian inheritance expectations would be observed for incompatible pairs. By adding an interaction to a transmission ratio distortion (TRD) model, which detects departure from the Mendelian expectations, genomic regions linked to gametic incompatibility can be identified. This study aimed to determine the genetic background of gametic incompatibility in Holstein cattle. A total of 283,817 genotyped Holstein trios were used in a TRD analysis, resulting in 422 significant regions, which contained 2075 positional genes further investigated for network, overrepresentation, and guilt-by-association analyses. The identified biological pathways were associated with immunology and cellular communication and a total of 16 functional candidate genes were identified. Further investigation of gametic incompatibility will provide opportunities to improve mate allocation for the dairy cattle industry.

Genome-Wide Association Analysis Reveals Novel Loci Related with Visual Score Traits in Nellore Cattle Raised in Pasture-Based Systems

Body conformation traits assessed based on visual scores are widely used in Zebu cattle breeding programs. The aim of this study was to identify genomic regions and biological pathways associated with body conformation (CONF), finishing precocity (PREC), and muscling (MUSC) in Nellore cattle. The measurements based on visual scores were collected in 20,807 animals raised in pasture-based systems in Brazil. In addition, 2775 animals were genotyped using a 35 K SNP chip, which contained 31,737 single nucleotide polymorphisms after quality control. Single-step GWAS was performed using the BLUPF90 software while candidate genes were identified based on the Ensembl Genes 69. PANTHER and REVIGO platforms were used to identify key biological pathways and STRING to create gene networks. Novel candidate genes were revealed associated with CONF, including ALDH9A1, RXRG, RAB2A, and CYP7A1, involved in lipid metabolism. The genes associated with PREC were ELOVL5, PID1, DNER, TRIP12, and PLCB4, which are related to the synthesis of long-chain fatty acids, lipid metabolism, and muscle differentiation. For MUSC, the most important genes associated with muscle development were SEMA6A, TIAM2, UNC5A, and UIMC1. The polymorphisms identified in this study can be incorporated in commercial genotyping panels to improve the accuracy of genomic evaluations for visual scores in beef cattle.

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

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.

Extracellular vesicles in seminal plasma: A safe and relevant tool to improve fertility in livestock?

Seminal plasma (SP) is not a pre-requisite for pregnancy. Yet, this heterogeneous, composite SP has proven relevant for fertility, as mediator for cell-to-cell communication between producing cells, spermatozoa and the female internal genital tract, regulating complex reproductive processes. Bearing hormones, proteins, cytokines as well as nuclei acids in nano-sized lipid bilayer seminal extracellular vesicles (sEVs), the SP concerts signaling to the female. Signals influence timing of ovulation, sperm transport and, particularly, enable the female immune system to balance her cryptic choice to engage into pregnancy or reject an eventual fertilization. This essay, focusing on livestock in general and pigs in particular, discusses the intrinsic roles of sEVs with regards to reproductive homeostasis, while binding and internalizing their cargo in spermatozoa and female tract epithelia to regulate their functional activity. Since prior studies had inconclusive results using bulk SP or single SP-contained free molecules, argumentation is hereby provided to increase the current incipient research on livestock sEVs, where fragile molecules relevant for fertility are shielded from degradation during handling. Seminal EVs isolated from SP can be used for andrological diagnosis and perhaps to select breeders with optimal fertility. Moreover, sEVs can be laboratory-uploaded with specific molecules or even engineered as lipid nanodroplets used as additives for extenders to improve fertility after artificial insemination (AI) or reproductive biotechnologies.

Weak genotype x environment interaction suggests that measuring scrotal circumference at 12 and 18 months of age is helpful to select precocious Brahman cattle

The aim of this study was to evaluate the genotype x environment interaction (GxE) for scrotal circumference (SC) measured at different ages using pedigree-based (A -1) and pedigree and genomic-based (H -1) relationship matrices. Data from 1,515 Brahman bulls, from the Cooperative Research Centre for Beef Genetic Technologies (Beef CRC) experimental dataset were used in this study. SC was adjusted to age and body weight measured at 6 months (SC6), 12 months (SC12), 18 months (SC18) and 24 months of age (SC24). Body weight (BW) measured at 6 months (BW6), 12 months (BW12), 18 months (BW18) and 24 months of age (BW24) were used as criteria to describe the environment for SC in each age. All the animals measured were genotyped using medium-density SNP chips ("50k" or "70k" SNP) and their genotype were imputed using a reference panel with 729,068 SNP. The environment gradient (EG) was obtained by standardizing the solutions of the contemporary groups obtained by Animal Model with BW as the dependent variable. Then, the reaction norms (RN) were determined through a Random Regression Model. The breeding values (EBV) were estimated using either A -1 or H -1. The rank correlation was obtained using Spearman's correlation among the EBV estimated for the traits in analysis. For SC6 and SC24, higher estimates of heritability (h²) were obtained using A -1, when compared to those observed with H -1. In those ages, the improvement of the environment decreases the h² coefficient. On the other hand, the h² for SC12 and SC18 increased as the environment became more favorable, regardless of the matrix used. The RN for SC6 and SC24 estimated using A -1 and H -1 showed a decrease of variance from the worst to the best environment, an indication of existence of GxE. On the other hand, for SC12 and SC18, there were no significant differences between the EBV estimated in the lower and in the higher environments, regardless of the kinship matrix used, suggesting absence of GxE on those ages. Spearman's correlation among EBV estimated using A -1 and H -1 in different EG were practically equal to unity for all traits evaluated. In our study, there was weak evidence of GxE effect on SC in ages suitable for selection for sexual precocity. So, the absence of GxE at 12 and 18 months means these ages are advantageous for measuring SC to selection for sexual precocity. The advantage is that no changes in classification were observed when the sires were evaluated in different environments.

Genom-wide analysis identifies single nucleotide polymorphism variations and altered pathways associated with poor semen quality in breeding bulls

The reason for poor semen quality among the breeding bulls is not well understood. In the present study, we performed high-throughput RNAseq analysis of spermatozoa to identify the SNPs present in good and poor-quality semen-producing Holstein Friesian breeding bulls. A total of 21,360 and 44,650 SNPs were identified in good and poor-quality semen with a minimum read depth of 20, among which 4780 and 8710 novel variants were observed in good and poor-quality semen, respectively. Greater SNPs and indels variations were observed in poor compared to good-quality semen. In poor-quality semen, SNP variations were observed in ZNF280B, SLC26A2, DMXL1, OR52A1, MACROD2 and REV1 genes, which are associated with regulation of spermatogenesis, post-testicular maturation, Cl^- channel activity, V-ATPase-mediated intracellular vesicle acidification, a mono-ADP-ribosyl hydrolase and ATR-Chk1 checkpoint activation. GO analysis of filtered genes with significant variations between good and poor-quality semen showed enrichment in important pathways related to semen quality such as MAPK signalling pathway, Akt signalling pathway, focal adhesion, cAMP signalling pathway, and Rap1 signalling pathway. Network analysis of filtered genes in poor-quality semen showed variations in pathways of purine metabolism, pyrimidine metabolism, prolactin signalling pathway and RNA cap-binding complex. It is inferred that SNP in genes involved in maintaining sperm functions could be the reason for poor-quality semen production in bulls, and the identified SNPs hold potential to be used as biomarkers for semen quality in bulls.

Sperm DNA methylation patterns at discrete CpGs and genes involved in embryonic development are related to bull fertility

Background

Despite a multifactorial approach being taken for the evaluation of bull semen quality in many animal breeding centres worldwide, reliable prediction of bull fertility is still a challenge. Recently, attention has turned to molecular mechanisms, which could uncover potential biomarkers of fertility. One of these mechanisms is DNA methylation, which together with other epigenetic mechanisms is essential for the fertilising sperm to drive normal embryo development and establish a viable pregnancy. In this study, we hypothesised that bull sperm DNA methylation patterns are related to bull fertility. We therefore investigated DNA methylation patterns from bulls used in artificial insemination with contrasting fertility scores.

Results

The DNA methylation patterns were obtained by reduced representative bisulphite sequencing from 10 high-fertility bulls and 10 low-fertility bulls, having average fertility scores of − 6.6 and + 6.5%, respectively (mean of the population was zero). Hierarchical clustering analysis did not distinguish bulls based on fertility but did highlight individual differences. Despite this, using stringent criteria (DNA methylation difference ≥ 35% and a q-value < 0.001), we identified 661 differently methylated cytosines (DMCs). DMCs were preferentially located in intergenic regions, introns, gene downstream regions, repetitive elements, open sea, shores and shelves of CpG islands. We also identified 10 differently methylated regions, covered by 7 unique genes (SFRP1, STXBP4, BCR, PSMG4, ARSG, ATP11A, RXRA), which are involved in spermatogenesis and early embryonic development.

Conclusion

This study demonstrated that at specific CpG sites, sperm DNA methylation status is related to bull fertility, and identified seven differently methylated genes in sperm of subfertile bulls that may lead to altered gene expression and potentially influence embryo development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08614-5.

A Non-Synonymous Point Mutation in a WD-40 Domain Repeat of EML5 Leads to Decreased Bovine Sperm Quality and Fertility

This study is part of a concerted effort to identify and phenotype rare, deleterious mutations that adversely affect sperm quality, or convey high developmental and fertility potential to embryos and ensuing progeny. A rare, homozygous mutation in EML5 (EML5^R1654W), which encodes a microtubule-associated protein with high expression in testis and brain was identified in an Angus bull used extensively in artificial insemination (AI) for its outstanding progeny production traits. The bull’s fertility was low in cross-breeding timed AI (TAI) (Pregnancy/TAI = 25.2%; n = 222) and, in general, AI breeding to Nellore cows (41%; n = 822). A search of the 1,000 Bull Genomes Run9 database revealed an additional 74 heterozygous animals and 8 homozygous animals harboring this exact mutation across several different breeds (0.7% frequency within the 6,191 sequenced animals). Phenotypically, spermatozoa from the homozygous Angus bull displayed prominent piriform and tapered heads, and outwardly protruding knobbed acrosomes. Additionally, an increased retention of EML5 was also observed in the sperm head of both homozygous and heterozygous Angus bulls compared to wild-type animals. This non-synonymous point mutation is located within a WD40 signaling domain repeat of EML5 and is predicted to be detrimental to overall protein function by genomic single nucleotide polymorphism (SNP) analysis and protein modeling. Future work will examine how this rare mutation affects field AI fertility and will characterize the role of EML5 in spermatogenesis.

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

Background

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

Results

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

Conclusions

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

Supplementary Information

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

Fertility prediction in dairy goats from Murciano-Granadina breed: The role of sperm evaluation and female traits

Fertility is one of the most economically important traits in farm animals, due to the direct and indirect costs associated to low pregnancy rates. Thus, one of the priority goals in animal reproduction is to predict the performance that the semen doses will have in vivo based on the quality values obtained in laboratory assays. Attempts have been made for getting a predictive model of fertility of frozen-thawed sperm in dairy goats, but similar studies have not been conducted for chilled goat buck sperm doses that are mostly used for artificial insemination in many countries including Spain. We study how parameters of in vitro sperm quality and characteristics of Murciano-Granadina dairy goats may affect the in vivo fertility obtained after artificial insemination with semen doses chilled at 4 °C. Moreover, this information was used for obtaining predictive models of the fertility. Sixty-three ejaculates from 13 males were used to prepare chilled doses for the insemination of 495 goats over 13 sessions. Fresh and chilled sperm were evaluated for motility and plasma membrane integrity with a computer-assisted sperm analysis system and flow cytometry, respectively. Fertility was determined at parturition, according to the kidding goats. Overall fertility was 59.6%. Pearson's correlation coefficients between in vivo fertility and quality variables of fresh sperm were not significant and were low (below 0.34 in absolute value) for chilled sperm. Females' characteristics had a low negative impact on fertility (correlation coefficients of -0.19 with age, -0.20 with parturitions and -0.11 with total milk yield obtained in the best lactation). Fixed and mixed logistic regression procedures were used trying to explain the fertility results. None of the models accurately predicted fertility, but the best models included the percentage of total motile sperm or average path velocity from fresh semen, age of the females and the session effect (uncontrolled environmental effects). These analyses showed that primiparous goats were 2.42 times more likely to get pregnant than goats that had kidded four or more times. Our field assay data on fertility in Murciano-Granadina dairy goats highlighted the importance of making quality controls of sperm, of choosing the doses presenting high percentages of motile sperm exhibiting regular trajectories and of selecting the youngest goats for AI, after their first kidding. Efforts should continue to obtain better predictive models for improving fertility in goat dairy herds.

Four novel candidate causal variants for deficient homozygous haplotypes in Holstein cattle

Mendelian variants can determine both insemination success and neonatal survival and thus influence fertility and rearing success of cattle. We present 24 deficient homozygous haplotype regions in the Holstein population of Switzerland and provide an overview of the previously identified haplotypes in the global Holstein breed. This study encompasses massive genotyping, whole-genome sequencing (WGS) and phenotype association analyses. We performed haplotype screenings on almost 53 thousand genotyped animals including 114 k SNP data with two different approaches. We revealed significant haplotype associations to several survival, birth and fertility traits. Within haplotype regions, we mined WGS data of hundreds of bovine genomes for candidate causal variants, which were subsequently evaluated by using a custom genotyping array in several thousand breeding animals. With this approach, we confirmed the known deleterious SMC2:p.Phe1135Ser missense variant associated with Holstein haplotype (HH) 3. For two previously reported deficient homozygous haplotypes that show negative associations to female fertility traits, we propose candidate causative loss-of-function variants: the HH13-related KIR2DS1:p.Gln159* nonsense variant and the HH21-related NOTCH3:p.Cys44del deletion. In addition, we propose the RIOX1:p.Ala133_Glu142del deletion as well as the PCDH15:p.Leu867Val missense variant to explain the unexpected low number of homozygous haplotype carriers for HH25 and HH35, respectively. In conclusion, we demonstrate that with mining massive SNP data in combination with WGS data, we can map several haplotype regions and unravel novel recessive protein-changing variants segregating at frequencies of 1 to 5%. Our findings both confirm previously identified loci and expand the spectrum of undesired alleles impairing reproduction success in Holstein cattle, the world's most important dairy breed.

Candidate Genes in Bull Semen Production Traits: An Information Approach Review

Semen quality plays a crucial role in the successful implementation of breeding programs, especially where artificial insemination (AI) is practiced. Bulls with good semen traits have good fertility and can produce a volume of high semen per ejaculation. The aim of this review is to use an information approach to highlight candidate genes and their relation to bull semen production traits. The use of genome-wide association studies (GWAS) has been demonstrated to be successful in identifying genomic regions and individual variations associated with production traits. Studies have reported over 40 genes associated with semen traits using Illumina BeadChip single-nucleotide polymorphism (SNPs).

A 1-bp deletion in bovine QRICH2 causes low sperm count and immotile sperm with multiple morphological abnormalities

BACKGROUND

Semen quality and insemination success are monitored in artificial insemination bulls to ensure high male fertility rates. Only ejaculates that fulfill minimum quality requirements are processed and eventually used for artificial inseminations. We examined 70,990 ejaculates from 1343 Brown Swiss bulls to identify bulls from which all ejaculates were rejected due to low semen quality. This procedure identified a bull that produced 12 ejaculates with an aberrantly small number of sperm (0.2 ± 0.2 × 109 sperm per mL) which were mostly immotile due to multiple morphological abnormalities.

RESULTS

The genome of this bull was sequenced at a 12× coverage to investigate a possible genetic cause. Comparing the sequence variant genotypes of this bull with those from 397 fertile bulls revealed a 1-bp deletion in the coding sequence of the QRICH2 gene which encodes the glutamine rich 2 protein, as a compelling candidate causal variant. This 1-bp deletion causes a frameshift in translation and a premature termination codon (ENSBTAP00000018337.1:p.Cys1644AlafsTer52). The analysis of testis transcriptomes from 76 bulls showed that the transcript with the premature termination codon is subject to nonsense-mediated mRNA decay. The 1-bp deletion resides in a 675-kb haplotype that includes 181 single nucleotide polymorphisms (SNPs) from the Illumina BovineHD Bead chip. This haplotype segregates at a frequency of 5% in the Brown Swiss cattle population. Our analysis also identified another bull that carried the 1-bp deletion in the homozygous state. Semen analyses from the second bull confirmed low sperm concentration and immotile sperm with multiple morphological abnormalities that primarily affect the sperm flagellum and, to a lesser extent, the sperm head.

CONCLUSIONS

A recessive loss-of-function allele of the bovine QRICH2 gene likely causes low sperm concentration and immotile sperm with multiple morphological abnormalities. Routine sperm analyses unambiguously identify homozygous bulls for this allele. A direct gene test can be implemented to monitor the frequency of the undesired allele in cattle populations.

Genome-wide detection of non-additive quantitative trait loci for semen production traits in beef and dairy bulls

Semen production traits are important aspects of bull fertility, because semen quantity leads to direct profits for artificial insemination centres, and semen quality is associated with the probability of achieving a pregnancy. Most genome-wide association studies (GWASs) for semen production traits have assumed that each quantitative trait locus (QTL) has an additive effect. However, GWASs that account for non-additive effects are also important in fitness traits, such as bull fertility. Here, we performed a GWAS using models that accounted for additive and non-additive effects to evaluate the importance of non-additive effects on five semen production traits in beef and dairy bulls. A total of 65 463 records for 615 Japanese Black bulls (JB) and 50 734 records for 873 Holstein bulls (HOL), which were previously genotyped using the Illumina BovineSNP50 BeadChip, were used to estimate genetic parameters and perform GWAS. The heritability estimates were low (ranged from 0.11 to 0.23), and the repeatability estimates were low to moderate (ranged from 0.28 to 0.45) in both breeds. The estimated repeatability was approximately twice as high as the estimated heritability for all traits. In this study, only one significant region with an additive effect was detected in each breed, but multiple significant regions with non-additive effects were detected for each breed. In particular, the region at approximately 64 Mbp on Bos taurus autosome 17 had the highest significant non-additive effect on four semen production traits in HOL. The rs41843851 single nucleotide polymorphism (SNP) in the region had a much lower P-value for the non-additive effect (P-value = 1.1 × 10^-31) than for the additive effect (P-value = 1.1 × 10^-8) in sperm motility. The AA and AB genotypes on the SNP had a higher phenotype than the BB genotype in HOL, and there was no bull with the BB genotype in JB. Our results showed that non-additive QTLs affect semen production traits, and a novel QTL accounting for non-additive effects could be detected by GWAS. This study provides new insights into non-additive QTLs that affect fitness traits, such as semen production traits in beef and dairy bulls.

Gene Expression in Embryos From Norwegian Red Bulls With High or Low Non Return Rate: An RNA-Seq Study of in vivo-Produced Single Embryos

During the last decade, paternal effects on embryo development have been found to have greater importance than previously believed. In domestic cattle, embryo mortality is an issue of concern, causing huge economical losses for the dairy cattle industry. In attempts to reveal the paternal influence on embryo death, recent approaches have used transcriptome profiling of the embryo to find genes and pathways affected by different phenotypes in the bull. For practical and economic reasons, most such studies have used in vitro produced embryos. The aim of the present study was to investigate the differences in the global transcriptome of in vivo produced embryos, derived from sires with either high or low field fertility measured as the non-return rate (NRR) on day 56 after first AI of the inseminated cows. Superovulated heifers (n = 14) in the age span of 12–15 months were artificially inseminated with semen from either high fertility (n = 6) or low fertility (n = 6) bulls. On day seven after insemination, embryos were retrieved through uterine flushing. Embryos with first grade quality and IETS stage 5 (early blastocyst), 6 (blastocyst) or 7 (expanded blastocyst) were selected for further processing. In total, RNA extracted from 24 embryos was sequenced using Illumina sequencing, followed by differential expression analysis and gene set enrichment analysis. We found 62 genes differentially expressed between the two groups (adj.p-value<0.05), of which several genes and their linked pathways could explain the different developmental capacity. Transcripts highly expressed in the embryos from low fertility bulls were related to sterol metabolism and terpenoid backbone synthesis, while transcripts highly expressed in the high fertility embryos were linked to anti-apoptosis and the regulation of cytokine signaling. The leukocyte transendothelial migration and insulin signaling pathways were associated with enrichments in both groups. We also found some highly expressed transcripts in both groups which can be considered as new candidates in the regulation of embryo development. The present study is an important step in defining the paternal influence in embryonic development. Our results suggest that the sire’s genetic contribution affects several important processes linked to pre-and peri implantation regulation in the developing embryo.

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

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

Use of insemination data for joint evaluation of male and female fertility in predominantly seasonal-calving dairy herds

Conception in dairy cattle is influenced by the fertility of the cow and the bull and their interaction. Despite genetic selection for female fertility in many countries, selection for male fertility is largely not practiced. The primary objective of this study was to quantify variation in male and female fertility using insemination data from predominantly seasonal-calving herds. Nonreturn rate (NRR) was derived by coding each insemination as successful (1) or failed (0) based on a minimum of at least 25 d. The NRR was treated as a trait of the bull with semen (male fertility) and the cow that is mated (female fertility). The data (805,463 cows that mated to 5,776 bulls) were used to estimate parameters using either models that only included bulls with mating data or models that fitted the genetic and permanent environmental (PE) effects of bulls and cows simultaneously. We also evaluated whether fitting genetic and PE effects of bulls as one term is better for ranking bulls based on NRR compared with a model that ignored genetic effect. The age of cows that were mated, age of the bulls with semen data, season of mating, breed of cow that mated, inbreeding of cows and bulls, and days from calving to mating date were found to have a significant effect on NRR. Only about 3% of the total variance was explained by the random effects in the model, despite fitting the genetic and PE effects of the bull and cow. The 2 components of fertility (male and fertility) were not correlated. The heritability of male fertility was low (0.001 to 0.008), and that of female fertility was also low (~0.016). The highest heritability estimate for male fertility was obtained from the model that fitted the additive genetic relationship matrix and PE component of the bull as one term. When this model was used to calculate bull solutions, the difference between bulls with at least 100 inseminations was up to 19.2% units (-9.6 to 9.6%). Bull solutions from this model were compared with bull solutions that were predicted fitting bull effects ignoring pedigree. Bull solutions that were obtained considering pedigree had (1) the highest accuracy of prediction when early insemination was used to predict yet-to-be observed insemination data of bulls, and (2) improved model stability (i.e., a higher correlation between bull solutions from 2 randomly split herds) compared with the model which fitted bull with no pedigree. For practical purposes, the model that fitted genetic and PE effect as one term can provide more accurate semen fertility values for bulls than the model without genetic effect. To conclude, insemination data from predominantly seasonal-calving herds can be used to quantify variability between bulls for male fertility, which makes their ranking on NRR feasible. Potentially this information can be used for monitoring bulls and can supplement efforts to improve herd fertility by avoiding or minimizing the use of semen from subfertile bulls.

Effect of plane of nutrition during the first 12 weeks of life on growth, metabolic and reproductive hormone concentrations, and testicular relative mRNA abundance in preweaned Holstein Friesian bull calves

The objective of this study was to examine the effect of nutrition during the first 12 wk of life on aspects of the physiological and transcriptional regulation of testicular and overall sexual development in the bull calf. Holstein Friesian bull calves with a mean (SD) age and bodyweight of 17.5 (2.85) d and 48.8 (5.30) kg, respectively, were assigned to either a high (HI; n = 15) or moderate (MOD; n = 15) plane of nutrition and were individually fed milk replacer and concentrate to achieve overall target growth rates of at least 1.0 and 0.5 kg/d, respectively. Throughout the trial, animal growth performance, feed intake, and systemic concentrations of metabolites, metabolic hormones, and reproductive hormones were assessed. Additionally, pulsatility of reproductive hormones (luteinizing hormone, follicle-stimulating hormone, and testosterone) was recorded at 15-min intervals during a 10-h period at 10 wk of age. At 87 ± 2.14 d of age, all calves were euthanized, testes were weighed, and testicular tissue was harvested. Differential expression of messenger ribonucleic acid (mRNA) candidate genes involved in testicular development was examined using quantitative polymerase chain reaction assays. All data were analyzed using the MIXED procedure in Statistical Analysis Software using terms for treatment as well as time for repeated measures. Blood metabolites and metabolic hormones generally reflected the improved metabolic status of the calves on the HI plane of nutrition though the concentrations of reproductive hormones were not affected by diet. Calves on the HI diet had greater mean (SED) slaughter weight (112.4 vs. 87.70 [2.98] kg; P < 0.0001) and testicular tissue weight (29.2 vs. 20.1 [2.21] g; P = 0.0003) than those on the MOD diet. Relative mRNA abundance data indicated advanced testicular development through upregulation of genes involved in cellular metabolism (SIRT1; P = 0.0282), cholesterol biosynthesis (EBP; P = 0.007), testicular function (INSL3; P = 0.0077), and Sertoli cell development (CLDN11; P = 0.0054) in HI compared with MOD calves. In conclusion, results demonstrate that offering dairy-bred male calves a high plane of nutrition during the first 3 mo of life not only improves growth performance and metabolic status but also advances testicular development consistent with more precocious sexual maturation.

Genetic variations of bovine PCOS-related DENND1A gene identified in GWAS significantly affect female reproductive traits

Genome-wide association studies (GWAS) have identified DENND1A as a potential candidate gene linked to the fertility-related phenotypes in dairy cows. However, to date, no studies have examined the association of the DENND1A insertion/deletions (indels) to bovine fertility on a large scale. Herein, two indel sites, including P4-del-26-bp and P8-ins-15-bp were identified in 1064 Holstein cows. The values of the minor allelic frequency (MAF) ranged between 0.471 (deletion) and 0.230 (deletion), respectively, and combined four different haplotypes by analyzing the haplotype combination. It is noteworthy that P4-del-26-bp is associated with the ovarian width (P = 0.0004) and corpus luteum diameter (P = 0.004). Meanwhile, P8-ins-15-bp was found to have a significant association with the ovarian width (P = 0.020), ovarian weight (P = 0.004), the number of mature follicles (P = 0.020), and diameter of the mature follicles (P = 0.016). Furthermore, the combinatorial analysis showed that the two indel combined-genotypes were significantly related to several reproductive traits (ovarian width, ovarian weight, etc.). Collectively, our findings indicated that these two novel indels and their combinations are correlated with the reproductive traits, and hence, they can serve in the marker-assisted selection (MAS) in cattle breeding. Nevertheless, further functional experiments are needed for understanding the mechanisms of these indels in cattle reproduction in a better way.

Boosting the potential of cattle breeding using molecular biology, genetics, and bioinformatics approaches – a review

Cattle are among the most important farm animals that underwent an intense selection with the aim to increase milk production and to improve growth and meat properties, meanwhile reducing the generation interval allowing for a faster herd turnover. Recently, a shift from traditional breeding methods to breeding based on genetic testing has been observed. In this perspective, we review the techniques of molecular biology, genetics, and bioinformatics that are expected to further boost the agricultural potential of cattle. We discuss embryo selection based on next-generation and Nanopore sequencing and in vitro embryo production, boosting the potential of genetically superior animals. Gene editing of embryos could further speed up the selection process, essentially introducing a change in a single generation. Lastly, we discuss the host-microbiome co-evolution and adaptation. For example, cattle already adapted to low-quality low-cost fodder could be bred to achieve desired properties for the beef and dairy industry. The challenge of breeding and genetic editing is to accompany the selection on desired consumer-oriented traits with the push for sustainability and the adaptation to a changing climate while remaining economically viable. We propose that we are yet to see the limits of what is possible to achieve with modern technology for the cattle of the future; the ultimate goal will be to produce and maintain genetically elite individuals that can sustain the growing demands on the production.

Sire contribution to fertilization failure and early embryo survival in cattle

Despite passing routine laboratory tests of semen quality, bulls used in artificial insemination (AI) exhibit a significant range in field fertility. The objective of this study was to determine whether subfertility in AI bulls is due to issues of sperm transport to the site of fertilization, fertilization failure, or failure of early embryo or conceptus development. In experiment 1, Holstein-Friesian bulls (3 high fertility, HF, and 3 low fertility, LF) were selected from the national population of AI bulls based on adjusted fertility scores from a minimum of 500 inseminations (HF: +4.37% and LF: -12.7%; mean = 0%). Superovulated beef heifers were blocked based on estimated number of follicles at the time of AI and inseminated with semen from HF or LF bulls (n = 3-4 heifers per bull; total 19 heifers). Following slaughter 7 d later, the number of corpora lutea was counted and the uteri were flushed. Recovered structures (oocytes/embryos) were classified according to developmental stage and stained with 4',6-diamidino-2-phenylindole to assess number of cells and accessory sperm. Overall recovery rate (total structures recovered/total corpora lutea) was 52.6% and was not different between groups. Mean (± standard error of the mean) number of embryos recovered per recipient was 8.7 ± 5.2 and 9.4 ± 5.5 for HF and LF, respectively. Overall fertilization rate of recovered structures was not different between groups. However, more embryos were at advanced stages of development (all blastocyst stages combined), reflected in a greater mean embryo cell number on d 7 for HF versus LF bulls. Number of accessory sperm was greater for embryos derived from HF than for LF bulls. The aim of experiment 2 was to evaluate the effect of sire fertility on survival of bovine embryos to d 15. Day 7 blastocysts were produced in vitro using semen from the same HF (n = 3) and LF (n = 3) bulls and transferred in groups of 5-10 to synchronized heifers (n = 7 heifers per bull; total 42 heifers). Conceptus recovery rate on d 15 was higher in HF (59.4%,) versus LF (45.0%). Mean length of recovered conceptuses for HF bulls was not affected by fertility status. In conclusion, while differences in field fertility among AI sires used in this study were not reflected in fertilization rate, differences in embryo quality were apparent as early as d 7. These differences likely contributed to the higher proportion of conceptuses surviving to d 15 in HF bulls.

Genomic Analysis, Progress and Future Perspectives in Dairy Cattle Selection: A Review

Genomics comprises a set of current and valuable technologies implemented as selection tools in dairy cattle commercial breeding programs. The intensive progeny testing for production and reproductive traits based on genomic breeding values (GEBVs) has been crucial to increasing dairy cattle productivity. The knowledge of key genes and haplotypes, including their regulation mechanisms, as markers for productivity traits, may improve the strategies on the present and future for dairy cattle selection. Genome-wide association studies (GWAS) such as quantitative trait loci (QTL), single nucleotide polymorphisms (SNPs), or single-step genomic best linear unbiased prediction (ssGBLUP) methods have already been included in global dairy programs for the estimation of marker-assisted selection-derived effects. The increase in genetic progress based on genomic predicting accuracy has also contributed to the understanding of genetic effects in dairy cattle offspring. However, the crossing within inbred-lines critically increased homozygosis with accumulated negative effects of inbreeding like a decline in reproductive performance. Thus, inaccurate-biased estimations based on empirical-conventional models of dairy production systems face an increased risk of providing suboptimal results derived from errors in the selection of candidates of high genetic merit-based just on low-heritability phenotypic traits. This extends the generation intervals and increases costs due to the significant reduction of genetic gains. The remarkable progress of genomic prediction increases the accurate selection of superior candidates. The scope of the present review is to summarize and discuss the advances and challenges of genomic tools for dairy cattle selection for optimizing breeding programs and controlling negative inbreeding depression effects on productivity and consequently, achieving economic-effective advances in food production efficiency. Particular attention is given to the potential genomic selection-derived results to facilitate precision management on modern dairy farms, including an overview of novel genome editing methodologies as perspectives toward the future.

Intracytoplasmic Sperm Injection in Cattle

Intracytoplasmic sperm injection (ICSI) involves the microinjection of sperm into a matured oocyte. Although this reproductive technology is successfully used in humans and many animal species, the efficiency of this procedure is low in the bovine species mainly due to failed oocyte activation following sperm microinjection. This review discusses various reasons for the low efficiency of ICSI in cattle, potential solutions, and future directions for research in this area, emphasizing the contributions of testis-specific isoforms of Na/K-ATPase (ATP1A4) and phospholipase C zeta (PLC ζ). Improving the efficiency of bovine ICSI would benefit the cattle breeding industries by effectively utilizing semen from elite sires at their earliest possible age.

Effect of the X chromosome in genomic evaluations of reproductive traits in beef cattle

The aim of this study was to evaluate whether there are predictive advantages for breeding values with inclusion of X chromosome genomic markers for reproductive (occurrence of early pregnancy - P16 and age at first calving - AFC) and andrological (scrotal circumference -SC) variables in beef cattle. There were 3263 genotypes of females and males evaluated. There were breeding value estimates for SC, AFC and P16 considering two scenarios: 1) only autosomal markers or 2) autosomal and X chromosome markers. To evaluate effects of inclusion of X chromosome markers on selection, responses to selection were compared including or not including genomic marker information from the X chromosome. There were greater heritability estimates for SC (0.40 and 0.31), AFC (0.11 and 0.09) and P16 (0.43 and 0.38) when analyses included, compared with not including, genomic marker information from the X chromosome. When selection is based on results from analyses that did not include information for the X chromosome, there was about a 7 % lesser mean genomic breeding value for the SC traits for selected animals. For P16, there was an approximate 4% lesser breeding value without inclusion of genomic marker information from the X chromosome, while this inclusion did not have as great an effect on the breeding value for AFC. There was an average predictive correlation of 0.79, 0.98 and 0.84 for SC, AFC and P16, respectively. These estimates indicate inclusion of the X chromosome genomic marker information in the analysis can improve prediction of genomic breeding values, especially for SC.

Marker-assisted selection vis-à-vis bull fertility: coming full circle-a review

Bull fertility is considered an indispensable trait, as far as farm economics is concerned since it is the successful conception in a cow that provides calf crop, along with the ensuing lactation. This ensures sustainability of a dairy farm. Traditionally, bull fertility did not receive much attention by the farm managers and breeding animals were solely evaluated based on phenotypic predictors, namely, sire conception rate and seminal parameters in bull. With the advent of the molecular era in animal breeding, attempts were made to unravel the genetic complexity of bull fertility by the identification of genetic markers related to the trait. Marker-Assisted Selection (MAS) is a methodology that aims at utilizing the genetic information at markers and selecting improved populations for important traits. Traditionally, MAS was pursued using a candidate gene approach for identifying markers related to genes that are already known to have a physiological function related to the trait but this approach had certain shortcomings like stringent criteria for significance testing. Now, with the availability of genome-wide data, the number of markers identified and variance explained in relation to bull fertility has gone up. So, this presents a unique opportunity to revisit MAS by selection based on the information of a large number of genome-wide markers and thus, improving the accuracy of selection.

Genomic Evaluation of Primiparous High-Producing Dairy Cows: Inbreeding Effects on Genotypic and Phenotypic Production-Reproductive Traits

Simple Summary

Improving the genomic prediction methodologies in high-producing dairy cattle is a key factor for the selection of suitable individuals to ensure better productivity. However, the most advanced prediction tools based on genotyping show ~75% reliability. Nowadays, the incorporation of new indices to genomic prediction methods, such as the Inbreeding Index (II), can significantly facilitate the selection of reliable production and reproductive traits for progeny selection. Thus, the objective of this study was to determine the impact of II (low: LI and high: HI), based on genomic analysis, and its effect on production and reproductive phenotypic traits in high-producing primiparous dairy cows. Individuals with II between ≥2.5 and ≤5.0 have shown up to a two-fold increase in negative correlations comparing LI versus HI genomic production and reproductive parameters, severely affecting important traits such as Milk Production at 305 d, Protein Production at 305 d, Fertility Index, and Daughter Pregnancy Rate. Therefore, high-producing dairy cows face an increased risk of negative II-derived effects in their selection programs, particularly at II ≥ 2.5.

Abstract

The main objective of this study was to analyze the effects of the inbreeding degree in high-producing primiparous dairy cows genotypically and phenotypically evaluated and its impacts on production and reproductive parameters. Eighty Holstein–Friesian primiparous cows (age: ~26 months; ~450 kg body weight) were previously genomically analyzed to determine the Inbreeding Index (II) and were divided into two groups: low inbreeding group (LI: <2.5; n = 40) and high inbreeding group (HI: ≥2.5 and ≤5.0; n = 40). Genomic determinations of production and reproductive parameters (14 in total), together with analyses of production (12) and reproductive (11) phenotypic parameters (23 in total) were carried out. Statistically significant differences were obtained between groups concerning the genomic parameters of Milk Production at 305 d and Protein Production at 305 d and the reproductive parameter Daughter Calving Ease, the first two being higher in cows of the HI group and the third lower in the LI group (p < 0.05). For the production phenotypic parameters, statistically significant differences were observed between both groups in the Total Fat, Total Protein, and Urea parameters, the first two being higher in the LI group (p < 0.05). Also, significant differences were observed in several reproductive phenotypic parameters, such as Number of Services per Conception, Calving to Conception Interval, Days Open Post Service, and Current Inter-Partum Period, all of which negatively influenced the HI group (p < 0.05). In addition, correlation analyses were performed between production and reproductive genomic parameters separately and in each consanguinity group. The results showed multiple positive and negative correlations between the production and reproductive parameters independently of the group analyzed, being these correlations more remarkable for the reproductive parameters in the LI group and the production parameters in the HI group (p < 0.05). In conclusion, the degree of inbreeding significantly influenced the results, affecting different genomic and phenotypic production and reproductive parameters in high-producing primiparous cows. The determination of the II in first-calf heifers is crucial to evaluate the negative effects associated with homozygosity avoiding an increase in inbreeding depression on production and reproductive traits.

Activation of cryptic splicing in bovine WDR19 is associated with reduced semen quality and male fertility

Cattle are ideally suited to investigate the genetics of male reproduction, because semen quality and fertility are recorded for all ejaculates of artificial insemination bulls. We analysed 26,090 ejaculates of 794 Brown Swiss bulls to assess ejaculate volume, sperm concentration, sperm motility, sperm head and tail anomalies and insemination success. The heritability of the six semen traits was between 0 and 0.26. Genome-wide association testing on 607,511 SNPs revealed a QTL on bovine chromosome 6 that was associated with sperm motility (P = 2.5 x 10⁻²⁷), head (P = 2.0 x 10⁻⁴⁴) and tail anomalies (P = 7.2 x 10⁻⁴⁹) and insemination success (P = 9.9 x 10⁻¹³). The QTL harbors a recessive allele that compromises semen quality and male fertility. We replicated the effect of the QTL on fertility (P = 7.1 x 10⁻³²) in an independent cohort of 2481 Brown Swiss bulls. The analysis of whole-genome sequencing data revealed that a synonymous variant (BTA6:58373887C>T, rs474302732) in WDR19 encoding WD repeat-containing protein 19 was in linkage disequilibrium with the fertility-associated haplotype. WD repeat-containing protein 19 is a constituent of the intraflagellar transport complex that is essential for the physiological function of motile cilia and flagella. Bioinformatic and transcription analyses revealed that the BTA6:58373887 T-allele activates a cryptic exonic splice site that eliminates three evolutionarily conserved amino acids from WDR19. Western blot analysis demonstrated that the BTA6:58373887 T-allele decreases protein expression. We make the remarkable observation that, in spite of negative effects on semen quality and bull fertility, the BTA6:58373887 T-allele has a frequency of 24% in the Brown Swiss population. Our findings are the first to uncover a variant that is associated with quantitative variation in semen quality and male fertility in cattle.

In cattle farming, artificial insemination is the most common method of breeding. To ensure high fertilization rates, ejaculate quality and insemination success are closely monitored in artificial insemination bulls. We analyse semen quality, insemination success and microarray-called genotypes at more than 600,000 genome-wide SNP markers of 794 bulls to identify a recessive allele that compromises semen quality. We take advantage of whole-genome sequencing to pinpoint a variant in the coding sequence of WDR19 encoding WD repeat-containing protein 19 that activates a novel exonic splice site. Our results indicate that cryptic splicing in WDR19 is associated with reduced male reproductive performance. This is the first report of a variant that contributes to quantitative variation in bovine semen quality.

Gene mapping and genomic prediction of bull fertility using sex chromosome markers

Service sire has been recognized as an important factor affecting dairy herd fertility. Our group has reported promising results on gene mapping and genomic prediction of dairy bull fertility using autosomal SNP markers. Little is known, however, about the genetic contribution of sex chromosomes, which are enriched in genes related to sexual development and reproduction. As such, the main goal of this study was to investigate the effect of SNP markers on X and Y chromosomes (BTAX and BTAY, respectively) on sire conception rate (SCR) in US Holstein bulls. The analysis included a total of 5,014 bulls with SCR records and genotypes for roughly 291k SNP located on the autosomes, 1.5k SNP located on the pseudoautosomal region (PAR), 13.7k BTAX-specific SNP, and 24 BTAY-specific SNP. We first performed genomic scans of the sex chromosomes, and then we evaluated the genomic prediction of SCR including BTAX SNP markers in the predictive models. Two markers located on PAR and 3 markers located on the X-specific region showed significant associations with sire fertility. Interestingly, these regions harbor genes, such as FAM9B, TBL1X, and PIH1D3, that are directly implicated in testosterone concentration, spermatogenesis, and sperm motility. On the other hand, BTAY showed very low genetic variability, and none of the segregating markers were associated with SCR. Notably, model predictive ability was largely improved by including BTAX markers. Indeed, the combination of autosomal with BTAX SNP delivered predictive correlations around 0.343, representing an increase in accuracy of about 7.5% compared with the standard whole autosomal genome approach. Overall, this study provides evidence of the importance of both PAR and X-specific regions in male fertility in dairy cattle. These findings may help to improve conception rates in dairy herds through accurate genome-guided decisions on bull fertility.

Association of α/β-Hydrolase D16B with Bovine Conception Rate and Sperm Plasma Membrane Lipid Composition

We have identified a Holstein sire named Tarantino who had been approved for artificial insemination that is based on normal semen characteristics (i.e., morphology, thermoresistance, motility, sperm concentration), but had no progeny after 412 first inseminations, resulting in a non-return rate (NRdev) of -29. Using whole genome association analysis and next generation sequencing, an associated nonsense variant in the α/β-hydrolase domain-containing 16B gene (ABHD16B) on bovine chromosome 13 was identified. The frequency of the mutant allele in the German Holstein population was determined to be 0.0018 in 222,645 investigated cattle specimens. The mutant allele was traced back to Whirlhill Kingpin (bornFeb. 13th, 1959) as potential founder. The expression of ABHD16B was detected by Western blotting and immunohistochemistry in testis and epididymis of control bulls. A lipidome comparison of the plasma membrane of fresh semen from carriers and controls showed significant differences in the concentration of phosphatidylcholine (PC), diacylglycerol (DAG), ceramide (Cer), sphingomyelin (SM), and phosphatidylcholine (-ether) (PC O-), indicating that ABHD16B plays a role in lipid biosynthesis. The altered lipid contents may explain the reduced fertilization ability of mutated sperms.

A new Approach for Accurate Detection of Chromosome Rearrangements That Affect Fertility in Cattle

Simple Summary

Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high-genetic-merit animals. Selecting AI bulls with optimal fertility is therefore vital, as impaired fertility reduces genetic gains and reduces production, resulting in heavy financial and environmental losses. Chromosome translocations, where large parts of the genome are inappropriately attached in abnormal patterns, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our previous work, we have developed an approach for the unambiguous detection of abnormalities that affect fertility. We applied this method on the chromosomes of 39 bulls, detecting multiple abnormalities that affect fertility, including those that would be undetectable using traditional screening techniques. With UK dairy calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population.

Abstract

Globally, cattle production has more than doubled since the 1960s, with widespread use of artificial insemination (AI) and an emphasis on a small pool of high genetic merit animals. Selecting AI bulls with optimal fertility is, therefore, vital, as impaired fertility reduces genetic gains and production, resulting in heavy financial and environmental losses. Chromosome translocations, particularly the 1;29 Robertsonian translocation, are a common cause of reduced fertility; however, reciprocal translocations are significantly underreported due to the difficulties inherent in analysing cattle chromosomes. Based on our porcine work, we have developed an approach for the unambiguous detection of Robertsonian and reciprocal translocations, using a multiple-hybridization probe detection strategy. We applied this method on the chromosomes of 39 bulls, detecting heterozygous and homozygous 1;29 translocations and a 12;23 reciprocal translocation in a total of seven animals. Previously, karyotype analysis was the only method of diagnosing chromosomal rearrangements in cattle, and was time-consuming and error-prone. With calving rates of only 50–60%, it is vital to reduce further fertility loss in order to maximise productivity. The approach developed here identifies abnormalities that DNA sequencing will not, and has the potential to lead to long-term gains, delivering meat and milk products in a more cost-effective and environmentally-responsible manner to a growing population.

Selection for bull fertility: a review

Fertility is a critically important factor in cattle production because it directly relates to the ability to produce the offspring necessary to offset costs in production systems. Female fertility has received much attention and has been enhanced through assisted reproductive technologies, as well as genetic selection; however, improving bull fertility has been largely ignored. Improvements in bull reproductive performance are necessary to optimize the efficiency of cattle production. Selection and management to improve bull fertility not only have the potential to increase conception rates but also have the capacity to improve other economically relevant production traits. Bull fertility has reportedly been genetically correlated with traits such as average daily gain, heifer pregnancy, and calving interval. Published studies show that bull fertility traits are low to moderately heritable, indicating that improvements in bull fertility can be realized through selection. Although female fertility has continued to progress according to increasing conception rates, the reported correlation between male and female fertility is low, indicating that male fertility cannot be improved by selection for female fertility. Correlations between several bull fertility traits, such as concentration, number of spermatozoa, motility, and number of spermatozoa abnormalities, vary among studies. Using male fertility traits in selection indices would provide producers with more advanced selection tools. The objective of this review was to discuss current beef bull fertility measurements and to discuss the future of genetic evaluation of beef bull fertility and potential genetic improvement strategies.