Deciphering the genetic basis of male fertility in Italian Brown Swiss dairy cattle

Improving reproductive performance remains a major goal in dairy cattle worldwide. Several studies have demonstrated that paternal factors play a major role on pregnancy establishment. Recently, our group developed a bull fertility evaluation in the Italian Brown Swiss cattle population using confirmed pregnancy records. We evaluated more than 1200 Brown Swiss bulls based on cow field data, including 400k breeding records from 130k lactating cows. Interestingly, we found a substantial variation in conception rate among Brown Swiss bulls, with more than 20% conception rate difference between high-fertility and low-fertility bulls11. As such, the present study was specially performed to identify genetic factors that explain part of the variation observed in sire conception rate among Italian Brown Swiss bulls.

Whole genome scan: additive effects

The importance of additive effects on service sire fertility was evaluated on a genome-wide scale using a two-step mixed-model-based approach. Figure 1 shows the results of the genomic scan under the additive model. One genomic region on BTA1 showed significant effects on Brown Swiss bull fertility. The most significant marker, rs43239680is located within an intron of gene RABL3. Interestingly, RABL3 plays an important role in cell proliferation and cell motility18. It has also been shown that RABL3 is vital for embryonic development, as the complete ablation of this gene in mice leads to embryonic lethality19. Overall, our results suggest that genetic variation in RABL3 may explain part of the variation observed in male fertility in the Brown Swiss breed.

Figure 1

Manhattan plot showing the significance of additive effects on sire conception rate in Brown Swiss cattle.

Whole genome scan: non-additive effects

It is believed that non-additive effects are important for fitness-related traits such as fertility. Here, the potential role of non-additive effects on sire fertility in Brown Swiss cattle was evaluated using three different 1-degree-of-freedom tests corresponding to complete dominance, complete recessive, and pure overdominance effects. Alternatively, we could have used a genotypic model with two degree-of-freedom that fits simultaneously additive and non-additive effects. Note that if one is interested in identifying pure non-additive effects, namely complete dominance/recessive or pure overdominance, then the use of 1-degree-of-freedom tests is recommended because it maximizes the statistical power20. In addition, the 1-degree-of-freedom model facilitates the interpretation of the results because the βSNP directly estimates the expected phenotypic difference between genotypic classes.

We identified two genomic regions, located on BTA6 (57.6 Mb) and BTA26 (50.7 Mb), with significant recessive effects on sire conception rate (Fig. 2A). The distribution of sire conception rate values ​​for the two SNP loci with marked recessive effects, rs133071278 and rs41601831, is shown in Fig. 2B. Notably, these box plots show that the BB genotypes have much lower sire conception rate values ​​than the genotypes AA and AB. Each of these loci explain differences in conception rates of around 3–4%. Unsurprisingly, the BB genotypes are in low frequency in the population, 8.4% and 10% for BTA6 and BTA26, respectively. No region showed complete dominance or pure overdominance effects.

Figure 2
figure 2

The relevance of non-additive effects on male fertility in Brown Swiss cattle. (THE) Manhattan plot showing the significance of recessive effects. (B) Box plot showing the distribution of sire conception rate values ​​for the two SNP loci with marked recessive effects.

The significant region detected on BTA6 harbors the gene WDR19, a very strong candidate gene for service sire fertility in Brown Swiss cattle. Indeed, previous studies using bull fertility data from Swiss, German, and Austrian Brown Swiss cattle populations identified as synonymous variant in WDR19 significantly associated with various semen traits, including sperm motility and sperm abnormalities, and insemination success21.22. Gene WDR19 is a constituent of the intraflagellar transport complex that is essential for the physiological function of motile cilia and flagella, including sperm motility23. Moreover, the significant region on BTA26 harbors the gene ADGRA1 which encodes a protein that belongs to the adhesion family of G-protein-coupled receptors24. Of special interest, this family of receptors plays an important role in the fertilization process, inducing the acrosome reaction in bovine sperm25.

Recently, Hiltpold and collaborators reported that autosomal recessive loci contributed substantially to quantitative variation in bull fertility in Brown Swiss cattle26. Therefore, our study provides further evidence for the importance of non-additive effects in male fertility in cattle. Our findings confirm that genetic variation in WDR19 is associated with reduced male fertility in Brown Swiss cattle. In addition, our results indicate that the region on BTA26 that harbors ADGRA1 explains part of the observed variation in male reproductive performance among the Italian Brown Swiss bulls.

Gene-set analysis

Genomic scans are powerful tools to detect genetic variants affecting quantitative traits. However, genomic scans typically detect only major variants, while most of the genetic variation remains hidden. Thus, complementary approaches are needed to fully reveal the genetic basis underlying a complex trait such as male fertility in cattle. Here, a gene-set analysis was performed to identify biological processes and molecular mechanisms responsible for the variation in bull fertility in the Italian Brown Swiss population.

Figure 3 shows the most relevant biological terms and pathways associated with service sire fertility. A total of 231,764 of the 454,556 examined within SNP markers were located or near 22,467 annotated genes in the bovine reference genome ARS-UCD-1.2. A subset of 833 genes were defined as significantly associated with given bull fertility that contained at least one significant SNP. Our gene-set analysis interrogated different gene-set databases, including GO, KEGG, MeSH and InterPro. Across these databases, genome-wide association signals for service sire fertility were highly enriched in at least five groups of gene-sets, namely cell adhesion, cellular signaling, cellular transport, embryonic development, and immune system.

Figure 3
figure 3

Functional gene-sets significantly enriched with genes associated with sire conception rate in Brown Swiss cattle. The y-axis displays the names of the gene-sets, the size of the dots represents the significance of the enrichment (− log10 P-value, Fisher’s exact test) and x-axis represents the percentage of significant genes in each gene-set.

Our enrichment analysis revealed several significant functional terms related to cell adhesion. Note that most of the events that occur before and during the fertilization process, including gametogenesis, gamete transport, and sperm-oocyte interaction, involve cell adhesion events. Therefore, the impaired function of genes involved in cell adhesion might result in early pregnancy failures27.28. Cellular signaling and cellular transport pathways, such as activation of MAPK activity (GO:0000187) and calcium ion transport (GO:0006816), are also involved in many processes related to spermatogenesis and early embryo development29.30. Gene-sets involved in embryonic development, including muscle cell differentiation (GO:0042692) and super elongation complex (GO:0032783), were also associated with variation in bull fertility. These findings provide further evidence that paternal factors contribute to early embryo development in cattle31. Finally, gene-sets directly related to the immune system showed a significant enrichment of genes associated with bull fertility. The immune system impacts pregnancy establishment in different ways, from the spermatogenesis in the male through the fertilization in the female reproductive tract32.

Overall, a successful pregnancy establishment requires a very well-orchestrated cascade of events. Our findings show that genetic variation underlying different processes, including cell adhesion, cell motility, and the immune response, explain part of differences observed in male fertility in Brown Swiss cattle.

Functional terms in common across different dairy breeds

None of the genomic regions or individual genes identified in this study were previously reported as significantly associated with male fertility neither in Holstein nor in Jersey. This may be due to multiple causes, namely the major genetic variants affecting male fertility in Brown Swiss are not segregating in Holstein or Jersey, or these major genetic variants are segregating in these two dairy breeds but are not in high linkage disequilibrium with the markers in the SNP chips or simply false-positive/false-negative results. Notably, the gene-set analysis performed across the three dairy breeds identified a set of functional terms that are associated with male fertility in all the breeds (Fig. 4). These gene-sets are involved in cell migration, such as Fibronectin type III (IPR003961), cell–cell interaction, such as cell adhesion (GO:0007155) and beta-catenin binding (GO:0008013), cellular signaling, such as calcium ion binding (GO:0005509) and PH-like domain superfamily (IPR011993), GTPase activity, such as Guanyl-nucleotide exchange factor activity (GO:0005085) and GTPase activator activity (GO:0005096), and the immune response, such as Immunoglobulin-like fold (IPR013783). Supplementary Table 2 reports the full list of significant biological terms for each breed, including term name and ID, P-value, total number of genes, number of significant genes and database. Remarkably, these results demonstrate that biological processes and molecular pathways, rather than single genes, are the primary targets of selection.

Figure 4
figure 4

Functional gene-sets associated with male fertility across different dairy breeds. (THE) Venn diagram showing the number of gene-sets significantly associated with sire conception rate in Brown Swiss, Holstein, and Jersey cattle. (B) Significant gene-sets identified in the three dairy breeds under study. The y-axis displays the names of the gene-sets, the size of the dots represents the significance of the enrichment (− log10 P-value, Fisher’s exact test) and x-axis represents the percentage of significant genes in each gene-set.

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