Integration of whole-genome DNA methylation data with RNA sequencing data to identify markers for bull fertility

Genomics and Dairy Bull Fertility

Current evidence suggests that dairy bull fertility is influenced by genetic factors, and hence, it could be managed and improved by genetic means. There are major mutations that explain about 4% to 8% of the observed differences in conception rate between bulls segregating in most dairy breeds. Research has shown that genomic prediction of bull fertility is possible, and this could be used to make accurate genome-guided selection decisions, such as early culling of predicted subfertile bull calves. Inbreeding negatively influences bull fertility, and the increase in homozygosity seems an important risk factor for dairy bull subfertility.

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.

Comparative RNA isolation methods from fresh ejaculated spermatozoa in Sahiwal cattle (Bos indicus) and Murrah buffalo (Bubalus bubalis) bulls for high quality and enhanced RNA yield

Sperm mRNA transcriptional profiling can be used to evaluate the fertility of breeding bulls. The aim of the study was to compare the modified RNA isolation methods for higher RNA yield and quality from freshly ejaculated sperm of cattle and buffalo bulls. Ten fresh ejaculates from each Sahiwal (n = 10 bulls × 10 ejaculates) and Murrah bulls (n = 10 bulls x 10 ejaculates) were used for RNA isolation. From the recovered live sperm, total sperm RNA was isolated by conventional methods (TRIzol, Double TRIzol), membrane-based methods combined with TRIzol (RNeasy + TRIzol) with the addition of β-mercaptoethanol (BME) and Kit (RNeasy mini) methods in fresh semen. Among different isolation methods; the membrane-based modified methods combined with TRIzol (RNeasy + TRIzol) with the addition of β-mercaptoethanol (BME) resulted significantly (p < .05) higher total RNA quantity (300-340 ng/µL) and better purity in different concentrations of spermatozoa viz., 30-40 million, 70-80 million and 300-400 million sperm. The study concluded that the inclusion of BME to the combined membrane-based methods with somatic cell lysis buffer solution was best for constant increased yield and purity of RNA isolation from Sahiwal cattle and Murrah buffalo bull sperm.

Effects of DNA Methylation on Gene Expression and Phenotypic Traits in Cattle: A Review

Gene expression in cells is determined by the epigenetic state of chromatin. Therefore, the study of epigenetic changes is very important to understand the regulatory mechanism of genes at the molecular, cellular, tissue and organ levels. DNA methylation is one of the most studied epigenetic modifications, which plays an important role in maintaining genome stability and ensuring normal growth and development. Studies have shown that methylation levels in bovine primordial germ cells, the rearrangement of methylation during embryonic development and abnormal methylation during placental development are all closely related to their reproductive processes. In addition, the application of bovine male sterility and assisted reproductive technology is also related to DNA methylation. This review introduces the principle, development of detection methods and application conditions of DNA methylation, with emphasis on the relationship between DNA methylation dynamics and bovine spermatogenesis, embryonic development, disease resistance and muscle and fat development, in order to provide theoretical basis for the application of DNA methylation in cattle breeding in the future.

Testicular hypoplasia in Nellore Cattle: Genetic analysis and functional analysis of genome-wide association study results

Characterized by the incomplete development of the germinal epithelium of the seminiferous tubules, Testicular hypoplasia (TH) leads to decreased sperm concentration, increased morphological changes in sperm and azoospermia. Economic losses resulting from the disposal of affected bulls reduce the efficiency of meat production systems. A genome-wide association study and functional analysis were performed to identify genomic windows and the underlying positional candidate genes associated with TH in Nellore cattle. Phenotypic and pedigree data from 207,195 animals and genotypes (461,057 single nucleotide polymorphism, SNP) from 17,326 sires were used in this study. TH was evaluated as a binary trait measured at 18 months of age. A possible correlated response on TH resulting from the selection for scrotal circumference was evaluated by using a two-trait analysis. Thus, estimated breeding values were calculated by fitting a linear-threshold animal model in a Bayesian approach. The SNP effects were estimated using the weighted single-step genomic BLUP method. Twelve non-overlapping windows of 20 adjacent SNP that explained more than 1% of the additive genetic variance were selected for candidate gene annotation. Functional and gene prioritization analysis of the candidate genes identified genes (KHDRBS3, GPX5, STAR, ERLIN2), which might play an important role in the expression of TH due to their known roles in the spermatogenesis process, synthesis of steroids and lipid metabolism.

Integrating sperm cell transcriptome and seminal plasma metabolome to analyze the molecular regulatory mechanism of sperm motility in Holstein stud bulls

Considering that artificial insemination is the most widely used assisted reproductive technique in the dairy industry, the semen quality of bulls is very important for selecting excellent stud bulls. Sperm motility is one of the important traits of semen quality, and related genes may be regulated by environmental factors. Seminal plasma can affect sperm cell transcriptome and further affect sperm motility through exosome or other processes. However, the molecular regulation mechanism of bull sperm motility has not been studied by combining the sperm cell transcriptome with seminal plasma metabolome. The number of motile sperm per ejaculate (NMSPE) is an integrated indicator for assessing sperm motility in stud bulls. In the present study, we selected 7 bulls with higher NMSPE (5,698.55 million +/- 945.40 million) as group H and 7 bulls with lower NMSPE (2,279.76 million +/- 1,305.69 million) as group L from 53 Holstein stud bulls. The differentially expressed genes (DEGs) in sperm cells were evaluated between the two groups (H vs. L). We conducted gene co-expression network analysis (WGCNA) on H and L groups of bulls, as well as two monozygotic twin Holstein bulls with different NMSPE values, to screen candidate genes for NMSPE. The regulatory effect of seminal plasma metabolome on the candidate genes of NMSPE was also investigated. A total of 1,099 DEGs were identified in the sperm cells of H and L groups. These DEGs were primarily concentrated in energy metabolism and sperm cell transcription. The significantly enriched Kyoto encyclopedia of genes and genomes (KEGG) pathways of the 57 differential metabolites were the aminoacyl-tRNA biosynthesis pathway and vitamin B6 metabolism pathway. Our study discovered 14 genes as the potential candidate markers for sperm motility, including FBXO39. We observed a broad correlation between transcriptome of sperm cells and seminal plasma metabolome, such as three metabolites, namely, mesaconic acid, 2-coumaric acid, and 4-formylaminoantipyrine, might regulate FBXO39 expression through potential pathways. The genes related to seminal plasma metabolites expressed in sperm cells are not only located near the quantitative trait loci of reproductive traits, but also enriched in the genome-wide association study signal of sire conception rate. Collectively, this study was the first to investigate the interplays among transcriptome of sperm cells and seminal plasma metabolome from Holstein stud bulls with different sperm motility.

Integrated analyses of the methylome and transcriptome to unravel sex differences in the perirenal fat from suckling lambs

In sheep, differences were observed regarding fat accumulation and fatty acid (FA) composition between males and females, which may impact the quality and organoleptic characteristics of the meat. The integration of different omics technologies is a relevant approach for investigating biological and genetic mechanisms associated with complex traits. Here, the perirenal tissue of six male and six female Assaf suckling lambs was evaluated using RNA sequencing and whole-genome bisulfite sequencing (WGBS). A multiomic discriminant analysis using multiblock (s)PLS-DA allowed the identification of 314 genes and 627 differentially methylated regions (within these genes), which perfectly discriminate between males and females. These candidate genes overlapped with previously reported QTLs for carcass fat volume and percentage of different FAs in milk and meat from sheep. Additionally, differentially coexpressed (DcoExp) modules of genes between males (nine) and females (three) were identified that harbour 22 of these selected genes. Interestingly, these DcoExp were significantly correlated with fat percentage in different deposits (renal, pelvic, subcutaneous and intramuscular) and were associated with relevant biological processes for adipogenesis, adipocyte differentiation, fat volume and FA composition. Consequently, these genes may potentially impact adiposity and meat quality traits in a sex-specific manner, such as juiciness, tenderness and flavour.

Identification of differentially expressed mRNAs and miRNAs in spermatozoa of bulls of varying fertility

Bulls used in artificial insemination, with apparently normal semen quality, can vary significantly in their field fertility. This study aimed to characterize the transcriptome of spermatozoa from high (HF) and low (LF) fertility bulls at the mRNA and miRNA level in order to identify potential novel markers of fertility. Holstein-Friesian bulls were assigned to either the HF or LF group (n = 10 per group) based on an adjusted national fertility index from a minimum of 500 inseminations. Total RNA was extracted from a pool of frozen-thawed spermatozoa from three different ejaculates per bull, following which mRNA-seq and miRNA-seq were performed. Six mRNAs and 13 miRNAs were found differentially expressed (P < 0.05, FC > 1.5) between HF and LF bulls. Of particular interest, the gene pathways targeted by the 13 differentially expressed miRNAs were related to embryonic development and gene expression regulation. Previous studies reported that disruptions to protamine 1 mRNA (PRM1) had deleterious consequences for sperm chromatin structure and fertilizing ability. Notably, PRM1 exhibited a higher expression in spermatozoa from LF than HF bulls. In contrast, Western Blot analysis revealed a decrease in PRM1 protein abundance for spermatozoa from LF bulls; this was not associated with increased protamine deficiency (measured by the degree of chromatin compaction) or DNA fragmentation, as assessed by flow cytometry analyses. However, protamine deficiency was positively and moderately correlated with the percentage of spermatozoa with DNA fragmentation, irrespective of fertility group. This study has identified potential biomarkers that could be used for improving semen quality assessments of bull fertility.

Genome-wide evaluation of copy gain and loss variations in three Afghan sheep breeds

Copy number variation (CNV) is one of the main sources of variation between different individuals that has recently attracted much researcher interest as a major source for heritable variation in complex traits. The aim of this study was to identify CNVs in Afghan indigenous sheep consisting of three Arab, Baluchi, and Gadik breeds using genomic arrays containing 53,862 single nucleotide polymorphism (SNP) markers. Data were analyzed using the Hidden Markov Model (HMM) of PennCNV software. In this study, out of 45 sheep studied, 97.8% (44 animals) have shown CNVs. In total, 411 CNVs were observed for autosomal chromosomes and the entire sequence length of around 144 Mb was identified across the genome. The average number of CNVs per each sheep was 9.13. The identified CNVs for Arab, Baluchi, and Gadik breeds were 306, 62, and 43, respectively. After merging overlapped regions, a total of 376 copy number variation regions (CNVR) were identified, which are 286, 50, and 40 for Arab, Baluchi, and Gadik breeds, respectively. Bioinformatics analysis was performed to identify the genes and QTLs reported in these regions and the biochemical pathways involved by these genes. The results showed that many of these CNVRs overlapped with the genes or QTLs that are associated with various pathways such as immune system development, growth, reproduction, and environmental adaptions. Furthermore, to determine a genome-wide pattern of selection signatures in Afghan sheep breeds, the unbiased estimates of FST was calculated and the results indicated that 37 of the 376 CNVRs (~ 10%) have been also under selection signature, most of those overlapped with the genes influencing production, reproduction and immune system. Finally, the statistical methods used in this study was applied in an external dataset including 96 individuals of the Iranian sheep breed. The results indicated that 20 of the 114 CNVRs (18%) identified in Iranian sheep breed were also identified in our study, most of those overlapped with the genes influencing production, reproduction and immune system. Overall, this is the first attempts to develop the genomic map of loss and gain variation in the genome of Afghan indigenous sheep breeds, and may be important to shed some light on the genomic regions associated with some economically important traits in these breeds.

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.

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.

Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records

BACKGROUND

Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad dissemination of bull semen considerably alleviates confounding factors and enables the precise assessment of male fertility. This study was therefore designed to assess the potential for sperm DNA methylation to predict bull fertility.

RESULTS

A unique collection of 100 sperm samples was constituted by pooling 2-5 ejaculates per bull from 100 Montbéliarde bulls of comparable ages, assessed as fertile (n = 57) or subfertile (n = 43) based on non-return rates 56 days after insemination. The DNA methylation profiles of these samples were obtained using reduced representation bisulfite sequencing. After excluding putative sequence polymorphisms, 490 fertility-related differentially methylated cytosines (DMCs) were identified, most of which were hypermethylated in subfertile bulls. Interestingly, 46 genes targeted by DMCs are involved in embryonic and fetal development, sperm function and maturation, or have been related to fertility in genome-wide association studies; five of these were further analyzed by pyrosequencing. In order to evaluate the prognostic value of fertility-related DMCs, the sperm samples were split between training (n = 67) and testing (n = 33) sets. Using a Random Forest approach, a predictive model was built from the methylation values obtained on the training set. The predictive accuracy of this model was 72% on the testing set and 72% on individual ejaculates collected from an independent cohort of 20 bulls.

CONCLUSION

This study, conducted on the largest set of bull sperm samples so far examined in epigenetic analyses, demonstrated that the sperm methylome is a valuable source of male fertility biomarkers. The next challenge is to combine these results with other data on the same sperm samples in order to improve the quality of the model and better understand the interplay between DNA methylation and other molecular features in the regulation of fertility. This research may have potential applications in human medicine, where infertility affects the interaction between a male and a female, thus making it difficult to isolate the male factor.

A Combined Flow Cytometric Semen Analysis and miRNA Profiling as a Tool to Discriminate Between High- and Low-Fertility Bulls

Predicting bull fertility is one of the main challenges for the dairy breeding industry and artificial insemination (AI) centers. Semen evaluation performed in the AI center is not fully reliable to determine the level of bull fertility. Spermatozoa are rich in active miRNA. Specific sperm-borne miRNAs can be linked to fertility. The aim of our study is to propose a combined flow cytometric analysis and miRNA profiling of semen bulls with different fertility to identify markers that can be potentially used for the prediction of field fertility. Sperm functions were analyzed in frozen-thawed semen doses (CG: control group) and high-quality sperm (HQS) fraction collected from bulls with different field fertility levels (estimated relative conception rate or ERCR) by using advanced techniques, such as the computer-assisted semen analysis system, flow cytometry, and small RNA-sequencing. Fertility groups differ for total and progressive motility and in the abnormality degree of the chromatin structure (P < 0.05). A backward, stepwise, multiple regression analysis was applied to define a model with high relation between in vivo (e.g., ERCR) and in vitro (i.e., semen quality and DE-miRNA) fertility data. The analysis produced two models that accounted for more than 78% of the variation of ERCR (CG: R² = 0.88; HQS: R² = 0.78), identifying a suitable combination of parameters useful to predict bull fertility. The predictive equation on CG samples included eight variables: four kinetic parameters and four DNA integrity indicators. For the HQS fraction, the predictive equation included five variables: three kinetic parameters and two DNA integrity indicators. A significant relationship was observed between real and predicted fertility in CG (R² = 0.88) and HQS fraction (R² = 0.82). We identified 15 differentially expressed miRNAs between high- and low-fertility bulls, nine of which are known (miR-2285n, miR-378, miR-423-3p, miR-191, miR-2904, miR-378c, miR-431, miR-486, miR-2478) while the remaining are novel. The multidimensional preference analysis model partially separates bulls according to their fertility, clustering three semen quality variable groups relative to motility, DNA integrity, and viability. A positive association between field fertility, semen quality parameters, and specific miRNAs was revealed. The integrated approach could provide a model for bull selection in AI centers, increasing the reproductive efficiency of livestock.

Seminal Plasma: Relevant for Fertility?

Seminal plasma (SP), the non-cellular component of semen, is a heterogeneous composite fluid built by secretions of the testis, the epididymis and the accessory sexual glands. Its composition, despite species-specific anatomical peculiarities, consistently contains inorganic ions, specific hormones, proteins and peptides, including cytokines and enzymes, cholesterol, DNA and RNA-the latter often protected within epididymis- or prostate-derived extracellular vesicles. It is beyond question that the SP participates in diverse aspects of sperm function pre-fertilization events. The SP also interacts with the various compartments of the tubular genital tract, triggering changes in gene function that prepares for an eventual successful pregnancy; thus, it ultimately modulates fertility. Despite these concepts, it is imperative to remember that SP-free spermatozoa (epididymal or washed ejaculated) are still fertile, so this review shall focus on the differences between the in vivo roles of the SP following semen deposition in the female and those regarding additions of SP on spermatozoa handled for artificial reproduction, including cryopreservation, from artificial insemination to in vitro fertilization. This review attempts, including our own results on model animal species, to critically summarize the current knowledge of the reproductive roles played by SP components, particularly in our own species, which is increasingly affected by infertility. The ultimate goal is to reconcile the delicate balance between the SP molecular concentration and their concerted effects after temporal exposure in vivo. We aim to appraise the functions of the SP components, their relevance as diagnostic biomarkers and their value as eventual additives to refine reproductive strategies, including biotechnologies, in livestock models and humans.

Impacts of Epigenetic Processes on the Health and Productivity of Livestock

The dynamic changes in the epigenome resulting from the intricate interactions of genetic and environmental factors play crucial roles in individual growth and development. Numerous studies in plants, rodents, and humans have provided evidence of the regulatory roles of epigenetic processes in health and disease. There is increasing pressure to increase livestock production in light of increasing food needs of an expanding human population and environment challenges, but there is limited related epigenetic data on livestock to complement genomic information and support advances in improvement breeding and health management. This review examines the recent discoveries on epigenetic processes due to DNA methylation, histone modification, and chromatin remodeling and their impacts on health and production traits in farm animals, including bovine, swine, sheep, goat, and poultry species. Most of the reports focused on epigenome profiling at the genome-wide or specific genic regions in response to developmental processes, environmental stressors, nutrition, and disease pathogens. The bulk of available data mainly characterized the epigenetic markers in tissues/organs or in relation to traits and detection of epigenetic regulatory mechanisms underlying livestock phenotype diversity. However, available data is inadequate to support gainful exploitation of epigenetic processes for improved animal health and productivity management. Increased research effort, which is vital to elucidate how epigenetic mechanisms affect the health and productivity of livestock, is currently limited due to several factors including lack of adequate analytical tools. In this review, we (1) summarize available evidence of the impacts of epigenetic processes on livestock production and health traits, (2) discuss the application of epigenetics data in livestock production, and (3) present gaps in livestock epigenetics research. Knowledge of the epigenetic factors influencing livestock health and productivity is vital for the management and improvement of livestock productivity.