Exploring Endogenous and Exogenous Factors for Successful Artificial Insemination in Sheep: A Global Overview

Artificial insemination (AI) plays a vital role in animal breeding programs. AI is applied to enhance animal genetics and facilitate the widespread integration of desirable characteristics with a high potential for productivity. However, in sheep, this biotechnology is not commonly practicable due to multi-factorial challenges, resulting in inconsistent outcomes and unpredictable results. Thoughtful selection of semen donors and recipients based on genetic merit deeply impacts ovine AI outcomes. Additionally, endogenous factors such as breed, age, fertility traits, genetic disorders, and cervical anatomy in ewes contribute to ovine AI success. Extensive research has studied exogenous influences on sexual behavior, reproductive health, and hormonal regulation, all impacting ovine AI success. These exogenous factors include techniques like estrus induction, synchronization, semen handling methods (fresh/chilled/frozen), and insemination methods (cervical/laparoscopic), as well as nutritional factors and climatic conditions. This overview of the literature highlights the endogenous and exogenous challenges facing successful ovine AI and proposes strategies and best practices for improvement. This paper will serve as a guide for understanding and optimizing the success of ovine AI.

Recording of calf diseases for potential use in breeding programs: a case study on calf respiratory illness and diarrhea

Calf diseases remain a challenge for dairy producers from both an economic and welfare perspective. Genetically selecting for disease resistance in calves is a promising approach that could contribute to sustainable dairy farming. Genetic evaluations, however, require well-defined and consistently recorded phenotypes to be successful. Therefore, this study aimed to understand the current state of calf disease recording on Ontario farms. Calf disease records of respiratory illness and diarrhea were available from the national milk recording organization (Lactanet Canada, Guelph, Ontario, Canada) from 2009 to 2020. A case study was conducted to describe calf disease diagnoses and recording practices by surveying a subset of 13 Ontario dairy producers. The percentage of milk recorded farms that recorded calf respiratory illness and calf diarrhea increased from 2.6% in 2009 to 11.1% in 2020. Potential sources of data loss were identified along the information chain from farm to genetic evaluation database. Clear definitions and thresholds to diagnose calf disease, standard operating procedures for data recording, as well as a data transfer pipeline, which includes exchange formats, are needed to facilitate the inclusion of calf health traits in genetic evaluations.

Transvaginal ultrasound-guided oocyte retrieval in cattle: State-of-the-art and its impact on the in vitro fertilization embryo production outcome

Transvaginal ultrasound-guided oocyte retrieval (commonly called OPU) and in vitro embryo production (IVP) in cattle has shown significant progress in recent years, in part, as a result of a better understanding of the full potential of these tools by end users. The combination of OPU and IVP (OPU-IVP) has been successfully and widely commercially used worldwide. The main advantages are a greater number of embryos and pregnancies per unit of time, faster genetic progress due to donor quick turn around and more elite sires mating combinations, larger spectrum of female age (calves, prepuberal, heifer, cow) and condition (open, pregnant) from which to retrieve oocytes, a reduced number of sperm (even sexed) required to fertilize the oocytes, among other benefits. OPU-IVP requires significant less donor preparation in comparison to conventional embryo transfer (<50% of usual FSH injections needed) to the extent of no stimulating hormones (FSH) are necessary. Donor synchronization, stimulation, OPU technique, oocyte competence, embryo performance, and its impact on cryopreservation and pregnancy are discussed.

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.

Identification of large offspring syndrome during pregnancy through ultrasonography and maternal blood transcriptome analyses

In vitro production (IVP) of embryos in cattle can result in large/abnormal offspring syndrome (LOS/AOS) which is characterized by macrosomia. LOS can cause dystocia and lead to the death of dam and calf. Currently, no test exists to identify LOS pregnancies. We hypothesized that fetal ultrasonography and/or maternal blood markers are useful to identify LOS. Bovine fetuses were generated by artificial insemination (control) or IVP. Fetal ultrasonographies were taken on gestation D55 (D55) and fetal collections performed on D56 or D105 (gestation in cattle ≈ D280). IVP fetuses weighing ≥ 97 percentile of the control weight were considered LOS. Ultrasonography results show that the product of six D55 measurements can be used to identify extreme cases of LOS. To determine whether maternal blood can be used to identify LOS, leukocyte mRNA from 23 females was sequenced. Unsupervised hierarchical clustering grouped the transcriptomes of the two females carrying the two largest LOS fetuses. Comparison of the leukocyte transcriptomes of these two females to the transcriptome of all other females identified several misregulated transcripts on gestation D55 and D105 with LOC783838 and PCDH1 being misregulated at both time-points. Together our data suggest that LOS is identifiable during pregnancy in cattle.

Genetic diversity in reproductive traits of Braunvieh cattle determined with SNP markers

Braunvieh is an important dual‐purpose breed in the Mexican tropics. The study of its genetic diversity is key to implementing genetic improvement programs. This study was conducted to determine genetic diversity of reproductive traits in a Mexican Braunvieh beef cattle population using single nucleotide polymorphisms in candidate genes. Information from 24 genes with 52 intra‐genic loci reported in literature to be associated with productive life, pregnancy rate and cow and heifer conception rate of 150 Braunvieh males and females was considered. Observed heterozygosity (Ho) revealed high genetic diversity for the studied traits, Ho = 0.42 ± 0.087, relative to that of other populations of the same breed. Cluster analyses were carried out using the Ward and K‐means algorithms. These analyses revealed high genetic diversity that was observed in the biplot of non‐metric multi‐dimensional scaling. It was found that clustering strategy allowed visualisation of distant groups by genotype but not by favourable alleles in all the loci. We found that the genes CSNK1E, DNAH11, DSC2, IBSP and OCLN affected most of the traits in our study and they were highly informative. Therefore, they represent a potential resource for selection and crossbreeding programs of the traits studied in Braunvieh. The analyses showed that the Mexican Braunvieh population has a high level of genetic diversity, arguably due to decades‐long adaptation to the Mexican tropics.

Characterization of runs of homozygosity, heterozygosity-enriched regions, and population structure in cattle populations selected for different breeding goals

Background

A decline in the level of genetic diversity in livestock can result in reduced response to selection, greater incidence of genetic defects, and inbreeding depression. In this context, various metrics have been proposed to assess the level of genetic diversity in selected populations. Therefore, the main goals of this study were to: 1) investigate the population structure of 16 cattle populations from 15 different pure breeds or composite populations, which have been selected for different breeds goals; and, 2) identify and compare runs of homozygosity (ROH) and heterozygosity-enriched regions (HER) based on different single nucleotide polymorphism (SNP) panels and whole-genome sequence data (WGS), followed by functional genomic analyses.

Results

A total of 24,187 ROH were found across all cattle populations, with 55% classified in the 2-4 Mb size group. Fourteen homozygosity islands were found in five populations, where four ROH islands located on BTA1, BTA5, BTA16, and BTA19 overlapped between the Brahman (BRM) and Gyr (GIR) breeds. A functional analysis of the genes found in these islands revealed candidate genes known to play a role in the melanogenesis, prolactin signaling, and calcium signaling pathways. The correlations between inbreeding metrics ranged from 0.02 to 0.95, where the methods based on homozygous genotypes (F_HOM), uniting of gametes (F_UNI), and genotype additive variance (F_GRM) showed strong correlations among them. All methods yielded low to moderate correlations with the inbreeding coefficients based on runs of homozygosity (F_ROH). For the HER, 3576 runs and 26 islands, distributed across all autosomal chromosomes, were found in regions containing genes mainly related to the immune system, indicating potential balancing selection. Although the analyses with WGS did not enable detection of the same island patterns, it unraveled novel regions not captured when using SNP panel data.

Conclusions

The cattle populations that showed the largest amount of ROH and HER were Senepol (SEN) and Montana (MON), respectively. Overlapping ROH islands were identified between GIR and BRM breeds, indicating a possible historical connection between the populations. The distribution and pattern of ROH and HER are population specific, indicating that different breeds have experienced divergent selection processes or different genetic processes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08384-0.

Public Perceptions Regarding Genomic Technologies Applied to Breeding Farm Animals: A Qualitative Study

The societal acceptability of different applications of genomic technologies to animal production systems will determine whether their innovation trajectories will reach the commercialisation stage. Importantly, technological implementation and commercialisation trajectories, regulation, and policy development need to take account of public priorities and attitudes. More effective co-production practices will ensure the application of genomic technologies to animals aligns with public priorities and are acceptable to society. Consumer rejection of, and limited demand for, animal products developed using novel genomic technologies will determine whether they are integration into the food system. However, little is known about whether genomic technologies that accelerate breeding but do not introduce cross-species genetic changes are more acceptable to consumers than those that do. Five focus groups, held in the north east of England, were used to explore the perceptions of, and attitudes towards, the use of genomic technologies in breeding farm animals for the human food supply chain. Overall, study participants were more positive towards genomic technologies applied to promote animal welfare (e.g., improved disease resistance), environmental sustainability, and human health. Animal “disenhancement” was viewed negatively and increased food production alone was not perceived as a potential benefit. In comparison to gene editing, research participants were most negative about genetic modification and the application of gene drives, independent of the benefits delivered.

The potential for mitigation of methane emissions in ruminants through the application of metagenomics, metabolomics, and other -OMICS technologies

Ruminant supply chains contribute 5.7 gigatons of CO_2-eq per annum, which represents approximately 80% of the livestock sector emissions. One of the largest sources of emission in the ruminant sector is methane (CH₄), accounting for approximately 40% of the sectors total emissions. With climate change being a growing concern, emphasis is being put on reducing greenhouse gas emissions, including those from ruminant production. Various genetic and environmental factors influence cattle CH₄ production, such as breed, genetic makeup, diet, management practices, and physiological status of the host. The influence of genetic variability on CH₄ yield in ruminants indicates that genomic selection for reduced CH₄ emissions is possible. Although the microbiology of CH₄ production has been studied, further research is needed to identify key differences in the host and microbiome genomes and how they interact with one another. The advancement of “-omics” technologies, such as metabolomics and metagenomics, may provide valuable information in this regard. Improved understanding of genetic mechanisms associated with CH₄ production and the interaction between the microbiome profile and host genetics will increase the rate of genetic progress for reduced CH₄ emissions. Through a systems biology approach, various “-omics” technologies can be combined to unravel genomic regions and genetic markers associated with CH₄ production, which can then be used in selective breeding programs. This comprehensive review discusses current challenges in applying genomic selection for reduced CH₄ emissions, and the potential for “-omics” technologies, especially metabolomics and metagenomics, to minimize such challenges. The integration and evaluation of different levels of biological information using a systems biology approach is also discussed, which can assist in understanding the underlying genetic mechanisms and biology of CH₄ production traits in ruminants and aid in reducing agriculture’s overall environmental footprint.

Evaluation of candidate genotype of leptin gene associated with fertility and production traits in Hardhenu (Bos taurus × Bos indicus) cattle

The present study was conducted on Hardhenu cattle to screen genomic region of leptin gene with an objective to find the association of genotypes with fertility and production traits. The association analysis with traits under study was analysed by least squares analysis of variance by taking SNPs genotype as fixed effects in the statistical model. The genotypic frequencies with respect to targeted loci g.92450765 G > A indicated that AG (0.54) genotype was highest in Hardhenu cattle. Chi-squared tests showed that g.92450765G > A SNP meet with the Hardy-Weinberg equilibrium (p > .05).The association analysis revealed significant association of genotypes with total milk yield (TMY) and 305 days milk yield (MY) (p < .05). Service period (SP) and calving interval (CI) were also found significantly associated with genotypes (p < .05). Whereas, lactation length (LL), dry days (DD) and age at first calving (AFC) did not divulge any significant association with genotype. The AG and GG genotypes were associated with higher milk yields as compared to AA genotype, indicating that allele G was associated with superior milk performance. However, AA genotyped cattle found to be favourable with SP, CI and artificial insemination (AI) per conception compared to AG and GG genotyped cows. Chi-square analysis revealed that genetic variants of g.92450765 G > A SNP of leptin gene differ significantly with regard to reproductive disorders incidence (p < .05). The frequency of GG genotype (88.89%) in the affected animal group was very high followed by AG. The animals with GG genotype were found to be more susceptible to reproductive disorders as suggested by the higher odd ratio value (16.00) in logistic model. These observations and their differential association with the fertility and production traits can be utilized as an aid to selection for genetic improvement of antagonistic traits in dairy cows.

Symposium review: How to implement genomic selection

Genomic selection was adopted very quickly in the 10 yr after first implementation, and breeders continue to find new uses for genomic testing. Breeding values with higher reliability earlier in life are estimated by combining DNA genotypes for many thousands of loci using existing identification, pedigree, and phenotype databases for millions of animals. Quality control for both new and previous data is greatly improved by comparing genomic and pedigree relationships to correct parent-progeny conflicts and discover many additional ancestors. Many quantitative trait loci and gene tests have been added to previous assays that used only evenly spaced, highly polymorphic markers. Imputation now combines genotypes from many assays of differing marker densities. Prediction models have gradually advanced from normal or Bayesian distributions within trait and breed to single-step, multitrait, or other more complex models, such as multibreed models that may be needed for crossbred prediction. Genomic selection was initially applied to males to predict progeny performance but is now widely applied to females or even embryos to predict their own later performance. The initial focus on additive merit has expanded to include mating programs, genomic inbreeding, and recessive alleles. Many producers now use DNA testing to decide which heifers should be inseminated with elite dairy, beef, or sex-sorted semen, which should be embryo donors or recipients, or which should be sold or kept for breeding. Because some of these decisions are expensive to delay, predictions are now provided weekly instead of every few months. Predictions from international genomic databases are often more accurate and cost-effective than those from within-country databases that were previously designed for progeny testing unless local breeds, conditions, or traits differ greatly from the larger database. Selection indexes include many new traits, often with lower heritability or requiring large initial investments to obtain phenotypes, which provide further incentive to cooperate internationally. The genomic prediction methods developed for dairy cattle are now applied widely to many animal, human, and plant populations and could be applied to many more.

Whole-genome sequence analysis reveals candidate genomic footprints and genes associated with reproductive traits in Thoroughbred horse

The primary objective of most horse breeding operations was to maximize reproductive efficiency and minimize the cost of producing live foals. Here, we compared individual horses from the Thoroughbred population (n = 17), known as a horse breed with poor reproductive performance, with other six horse populations (n = 28), to detect genomic signatures of positive selection underlying of reproductive traits. A number of protein-coding genes with significant (p-value <.01) higher F_ST values (616 genes) and a lower value for nucleotide diversity (π) (310 genes) were identified. The results of our study revealed some candidate genes such as IGFBP2, IGFBP5, GDF9, BRINP3 and GRID1 are possibly associated with functions influencing reproductive traits. These genes may have been under selection due to their essential roles in reproduction performance in horses. The candidate selected genes identified in this work should be of great interest for future research into genetic architecture of traits relevant to horse breeding programmes.

DNA methylation pattern of the goat PITX1 gene and its effects on milk performance

Paired-like homeodomain transcription factor 1 (PITX1) is a pivotal gene in the hypothalamic–pituitary–adrenal axis, which is a well-known pathway affecting lactation performance. The aim of this study was to analyze the DNA methylation profile of the PITX1 gene and its relevance to milk performance in Xinong Saanen dairy goats; thus, potential epigenetic markers of lactation performance were identified. A total of 267 goat blood samples were divided into “low” and “high” groups according to two milk traits: the average milk yield (AMY) and the average milk density (AMD). One CpG island in the 3′-flanking region of the PITX1 gene was identified as being related to milk performance. Fisher's exact test demonstrated that the methylation rates of the overall CpG island and the 3rd and 12th CpG-dinucleotide loci in the blood were significantly associated with the AMY, and the overall methylation rate of the high AMY group was relative hypomethylation compared with the low AMY group. The overall methylation rates of this CpG island in mammary gland tissue from dry and lactation periods again exhibited a significant difference: the lactation period showed relative hypomethylation compared with the dry period. Bioinformatic transcription factor binding site prediction identified some lactation performance related transcription factors in this CpG island, such as CTCF, STAT, SMAD, CDEF, SP1, and KLFS. Briefly, overall methylation changes of the CpG island in the PITX1 gene are relevant to lactation performance, which will be valuable for future studies and epigenetic marker-assisted selection (eMAS) in the breeding of goats with respect to lactation performance.

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

In dairy production, high fertility contributes to herd profitability by achieving greater production and maintaining short calving intervals. Improved management practices and genetic selection have contributed to reversing negative trends in dairy cow fertility, but further progress is still required. Phenotypes included in current genetic evaluations are largely interval and binary traits calculated from insemination and calving date records. Several indicator traits such as calving, health, variation in body condition score, and longevity traits also apply to genetic improvement of fertility. Several fertility traits are included in the selection indices of many countries, but for improved selection, the development of novel phenotypes that more closely describe the physiology of reproduction and limit management bias could be more effective. Progesterone-based phenotypes can be determined from milk samples to describe the heritable interval from calving to corpus luteum activity, as well as additional measures of cow cyclicity. A fundamental component of artificial insemination practices is the observation of estrus. Novel phenotypes collected on estrous activity could be used to select for cows clearly displaying heat, as those cows are more likely to be inseminated at the right time and therefore have greater fertility performance. On-farm technologies, including in-line milk testing and activity monitors, may allow for phenotyping novel traits on large numbers of animals. Additionally, selection for improved fertility using traditional traits could benefit from refined and accurate recording and implementation of parameters such as pregnancy confirmation and reproductive management strategy, to differentiate embryonic or fetal loss, and to ensure selection for reproductive capability without producer intervention. Opportunities exist to achieve genetic improvement of reproductive efficiency in cattle using novel phenotypes, which is required for long-term sustainability of the dairy cattle population and industry.

Whole genome sequence analysis to detect signatures of positive selection for high fecundity in sheep

Ovulation rate and prolificacy are the most important reproductive traits that have major impact on the efficiency of lamb meat production. Here, we compared the whole genomes of the Romanov sheep, known as one of the high prolific breeds, and four other sheep breeds namely Assaf, Awassi, Cambridge and British du cher, to identify genetic mechanisms underlying prolificacy in sheep. Selection signature analysis revealed 637 and 477 protein-coding genes under positive selection from F_ST and nucleotide diversity (Pi) statistics, respectively. Further analysis showed that several candidate genes including LEPR, PDGFRL and KLF5 genes are involved in sheep prolificacy. The identified candidate genes in the selected regions are novel and provide new insights into the genetic mechanisms underlying prolificacy in sheep and can be useful in sheep breeding programmes to develop improved breeds for high reproductive efficiency.