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

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.

A Single-Step Genome-Wide Association Study for Semen Traits of Egyptian Buffalo Bulls

The present study aimed to contribute to the limited research on buffalo (Bubalus bubalis) semen traits by incorporating genomic data. A total of 8465 ejaculates were collected. The genotyping procedure was conducted using the Axiom® Buffalo Genotyping 90 K array designed by the Affymetrix Expert Design Program. After conducting a quality assessment, we utilized 67,282 SNPs genotyped in 192 animals. We identified several genomic loci explaining high genetic variance by employing single-step genomic evaluation. The aforementioned regions were located on buffalo chromosomes no. 3, 4, 6, 7, 14, 16, 20, 22, and the X-chromosome. The X-chromosome exhibited substantial influence, accounting for 4.18, 4.59, 5.16, 5.19, and 4.31% of the genomic variance for ejaculate volume, mass motility, livability, abnormality, and concentration, respectively. In the examined genomic regions, we identified five novel candidate genes linked to male fertility and spermatogenesis, four in the X-chromosome and one in chromosome no. 16. Additional extensive research with larger sample sizes and datasets is imperative to validate these findings and evaluate their applicability for genomic selection.

Repair mechanism of Yishen Tongluo formula on mouse sperm DNA fragmentation caused by polystyrene microplastics

CONTEXT

Plastics can break down into millions of microplastic (MPs, < 5 mm) particles in the soil and ocean. These MPs can then affect the function of the reproductive system. There is currently no effective solution to this problem aside from traditional Chinese medicine. We have previously used Yishen Tongluo formula (YSTL) to treat sperm DNA damage caused by some toxic substances.

OBJECTIVE

To investigate the mechanism underlying the repair of mouse sperm DNA fragmentation caused by polystyrene microplastics by YSTL.

MATERIALS AND METHODS

An animal model of polystyrene microplastic (PS-MP)-induced sperm DNA damage was replicated by gavage of SPF ICR (CD1) mice PS-MPs at 1 mg/d and treated with YSTL at 11.89, 23.78 and 47.56 g/kg, respectively, for 60 days. The Sperm DNA fragmentation index (DFI) of each group was detected and compared. The target genes of YSTL identified by transcriptomic and proteomic analyses were validated by qRT-PCR and western blotting.

RESULTS

The DFI of the PS group (20.66%) was significantly higher than that of the control group (4.23%). The medium and high doses of the YSTL group (12.8% and 11.31%) exhibited a significant repairing effect. The most enriched pathway was PI3K/Akt. TBL1X, SPARC, hnRNP0, Map7D1, Eps8 and Mrpl27 were screened and SPARC was validated.

DISCUSSION AND CONCLUSIONS

The precise mechanism by which YSTL inhibits PD-MPs DNA damage may be associated with the PI3K/Akt pathway and SPARC. It provides a new direction for using traditional Chinese medicine to prevent and repair reproductive system injury caused by MPs.

Identification of candidate novel production variants on the Bos taurus chromosome X

Chromosome X is often excluded from bovine genetic studies due to complications caused by the sex specific nature of the chromosome. As chromosome X is the second largest cattle chromosome and makes up approximately 6% of the female genome, finding ways to include chromosome X in dairy genetic studies is important. Using female animals and treating chromosome X as an autosome, we performed X chromosome inclusive genome-wide association studies in the selective breeding environment of the New Zealand dairy industry, aiming to identify chromosome X variants associated with milk production traits. We report on the findings of these genome-wide association studies and their potential effect within the dairy industry. We identify missense mutations in the MOSPD1 and CCDC160 genes that are associated with decreased milk volume and protein production and increased fat production. Both of these mutations are exonic SNP that are more prevalent in the Jersey breed than in Holstein-Friesians. Of the 2 candidates proposed it is likely that only one is causal, though we have not been able to identify which is more likely.

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.

Whole-genome sequencing identifies new candidate genes for nonobstructive azoospermia

BACKGROUND

Genetic causes that lead to spermatogenetic failure in patients with nonobstructive azoospermia (NOA) have not been yet completely established.

OBJECTIVE

To identify low-frequency NOA-associated single nucleotide variants (SNVs) using whole-genome sequencing (WGS).

MATERIALS AND METHODS

Men with various types of NOA (n = 39), including samples that had been previously tested with whole-exome sequencing (WES; n = 6) and did not result in diagnostic conclusions. Variants were annotated using the Ensembl Variant Effect Predictor, utilizing frequencies from GnomAD and other databases to provide clinically relevant information (ClinVar), conservation scores (phyloP), and effect predictions (i.e., MutationTaster). Structural protein modeling was also performed.

RESULTS

Using WGS, we revealed potential NOA-associated SNVs, such as: TKTL1, IGSF1, ZFPM2, VCX3A (novel disease causing variants), ESX1, TEX13A, TEX14, DNAH1, FANCM, QRICH2, FSIP2, USP9Y, PMFBP1, MEI1, PIWIL1, WDR66, ZFX, KCND1, KIAA1210, DHRSX, ZMYM3, FAM47C, FANCB, FAM50B (genes previously known to be associated with infertility) and ALG13, BEND2, BRWD3, DDX53, TAF4, FAM47B, FAM9B, FAM9C, MAGEB6, MAP3K15, RBMXL3, SSX3 and FMR1NB genes, which may be involved in spermatogenesis.

DISCUSSION AND CONCLUSION

In this study, we identified novel potential candidate NOA-associated genes in 29 individuals out of 39 azoospermic males. Note that in 5 out of 6 patients subjected previously to WES analysis, which did not disclose potentially causative variants, the WGS analysis was successful with NOA-associated gene findings.

Integration of Multiplied Omics, a Step Forward in Systematic Dairy Research

Due to their unique multi-gastric digestion system highly adapted for rumination, dairy livestock has complicated physiology different from monogastric animals. However, the microbiome-based mechanism of the digestion system is congenial for biology approaches. Different omics and their integration have been widely applied in the dairy sciences since the previous decade for investigating their physiology, pathology, and the development of feed and management protocols. The rumen microbiome can digest dietary components into utilizable sugars, proteins, and volatile fatty acids, contributing to the energy intake and feed efficiency of dairy animals, which has become one target of the basis for omics applications in dairy science. Rumen, liver, and mammary gland are also frequently targeted in omics because of their crucial impact on dairy animals’ energy metabolism, production performance, and health status. The application of omics has made outstanding contributions to a more profound understanding of the physiology, etiology, and optimizing the management strategy of dairy animals, while the multi-omics method could draw information of different levels and organs together, providing an unprecedented broad scope on traits of dairy animals. This article reviewed recent omics and multi-omics researches on physiology, feeding, and pathology on dairy animals and also performed the potential of multi-omics on systematic dairy research.

State of the art on the physical mapping of the Y-chromosome in the <i>Bovidae</i> and comparison with other species

The next generation sequencing has significantly contributed to clarify the genome structure of many species of zootechnical interest. However, to date, some portions of the genome, especially those linked to a heterogametic nature such as the Y chromosome, are difficult to assemble and many gaps are still present. It is well known that the fluorescence in situ hybridization (FISH) is an excellent tool for identifying genes unequivocably mapped on chromosomes. Therefore, FISH can contribute to the localization of unplaced genome sequences, as well as to correct assembly errors generated by comparative bioinformatics. To this end, it is necessary to have starting points; therefore, in this study, we reviewed the physically mapped genes on the Y chromosome of cattle, buffalo, sheep, goats, pigs, horses and alpacas. A total of 208 loci were currently mapped by FISH. 89 were located in the male-specific region of the Y chromosome (MSY) and 119 were identified in the pseudoautosomal region (PAR). The loci reported in MSY and PAR were respectively: 18 and 25 in Bos taurus, 5 and 7 in Bubalus bubalis, 5 and 24 in Ovis aries, 5 and 19 in Capra hircus, 10 and 16 in Sus scrofa, 46 and 18 in Equus caballus. While in Vicugna pacos only 10 loci are reported in the PAR region. The correct knowledge and assembly of all genome sequences, including those of genes mapped on the Y chromosome, will help to elucidate their biological processes, as well as to discover and exploit potentially epistasis effects useful for selection breeding programs.

High male specific contribution of the X-chromosome to individual global recombination rate in dairy cattle

Background

Meiotic recombination plays an important role in reproduction and evolution. The individual global recombination rate (GRR), measured as the number of crossovers (CO) per gametes, is a complex trait that has been shown to be heritable. The sex chromosomes play an important role in reproduction and fertility related traits. Therefore, variants present on the X-chromosome might have a high contribution to the genetic variation of GRR that is related to meiosis and to reproduction.

Results

We herein used genotyping data from 58,474 New Zealand dairy cattle to estimate the contribution of the X-chromosome to male and female GRR levels. Based on the pedigree-based relationships, we first estimated that the X-chromosome accounted for 30% of the total additive genetic variance for male GRR. This percentage was equal to 19.9% when the estimation relied on a SNP-BLUP approach assuming each SNP has a small contribution. We then carried out a haplotype-based association study to map X-linked QTL, and subsequently fine-mapped the identified QTL with imputed sequence variants. With this approach we identified three QTL with large effect accounting for 7.7% of the additive genetic variance of male GRR. The associated effects were equal to + 0.79, − 1.16 and + 1.18 CO for the alternate alleles. In females, the estimated contribution of the X-chromosome to GRR was null and no significant association with X-linked loci was found. Interestingly, two of the male GRR QTL were associated with candidate genes preferentially expressed in testis, in agreement with a male-specific effect. Finally, the most significant QTL was associated with PPP4R3C, further supporting the important role of protein phosphatase in double-strand break repair by homologous recombination.

Conclusions

Our study illustrates the important role the X-chromosome can have on traits such as individual recombination rate, associated with testis in males. We also show that contribution of the X-chromosome to such a trait might be sex dependent.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08328-8.

The future of assessing bull fertility: Can the 'omics fields identify usable biomarkers?

Breeding soundness examinations for bulls rely heavily on the subjective, visual assessment of sperm motility and morphology. Although these criteria have the potential to identify infertile males, they cannot be used to guarantee fertility or provide information about varying degrees of bull fertility. Male factor fertility is complex, and the success of the male gamete is not necessarily realized until well after the spermatozoon enters the oocyte. This paper reviews our existing knowledge of the bull’s contribution from a standpoint of the sperm’s cargo and the impact that this can have on fertilization and the development of the embryo. There has been a plethora of recent research characterizing the many molecular attributes that can affect the functional competence of a spermatozoon. A better understanding of the molecular factors influencing fertilization and embryo development in cattle will lead to the identification of biomarkers for the selection of bulls of superior fertility, which will have major implications for livestock production. To see this improvement in reproductive performance, we believe incorporation of modern technology into breeding soundness examinations will be necessary—although many of the discussed technologies are not ready for large-scale field application. Each of the ‘omics fields discussed in this review have shown promise for the identification of biomarkers of fertility, with certain families of biomarkers appearing to be better suited to different evaluations throughout a bull’s lifetime. Further research is needed for the proposed biomarkers to be of diagnostic or predictive value.

Evaluation of bull fertility in Italian Brown Swiss dairy cattle using cow field data

Dairy bull fertility is traditionally evaluated using semen production and quality traits; however, these attributes explain only part of the differences observed in fertility among bulls. Alternatively, bull fertility can be directly evaluated using cow field data. The main objective of this study was to investigate bull fertility in the Italian Brown Swiss dairy cattle population using confirmed pregnancy records. The data set included a total of 397,926 breeding records from 1,228 bulls and 129,858 lactating cows between first and fifth lactation from 2000 to 2019. We first evaluated cow pregnancy success, including factors related to the bull under evaluation, such as bull age, bull inbreeding, and AI organization, and factors associated with the cow that receives the dose of semen, including herd-year-season, cow age, parity, and milk yield. We then estimated sire conception rate using only factors related to the bull. Model predictive ability was evaluated using 10-fold cross-validation with 10 replicates. Interestingly, our analyses revealed that there is a substantial variation in conception rate among Brown Swiss bulls, with more than 20% conception rate difference between high-fertility and low-fertility bulls. We also showed that the prediction of bull fertility is feasible as our cross-validation analyses achieved predictive correlations equal to 0.30 for sire conception rate. Improving reproduction performance is one of the major challenges of the dairy industry worldwide, and for this, it is essential to have accurate predictions of service sire fertility. This study represents the foundation for the development of novel tools that will allow dairy producers, breeders, and artificial insemination companies to make enhanced management and selection decisions on Brown Swiss male fertility.

Autosomal recessive loci contribute significantly to quantitative variation of male fertility in a dairy cattle population

BACKGROUND

Cattle are ideally suited to investigate the genetics of male fertility. Semen from individual bulls is used for thousands of artificial inseminations for which the fertilization success is monitored. Results from the breeding soundness examination and repeated observations of semen quality complement the fertility evaluation for each bull.

RESULTS

In a cohort of 3881 Brown Swiss bulls that had genotypes at 683,609 SNPs, we reveal four novel recessive QTL for male fertility on BTA1, 18, 25, and 26 using haplotype-based association testing. A QTL for bull fertility on BTA1 is also associated with sperm head shape anomalies. All other QTL are not associated with any of the semen quality traits investigated. We perform complementary fine-mapping approaches using publicly available transcriptomes as well as whole-genome sequencing data of 125 Brown Swiss bulls to reveal candidate causal variants. We show that missense or nonsense variants in SPATA16, VWA3A, ENSBTAG00000006717 and ENSBTAG00000019919 are in linkage disequilibrium with the QTL. Using whole-genome sequence data, we detect strong association (P = 4.83 × 10^- 12) of a missense variant (p.Ile193Met) in SPATA16 with male fertility. However, non-coding variants exhibit stronger association at all QTL suggesting that variants in regulatory regions contribute to variation in bull fertility.

CONCLUSION

Our findings in a dairy cattle population provide evidence that recessive variants may contribute substantially to quantitative variation in male fertility in mammals. Detecting causal variants that underpin variation in male fertility remains difficult because the most strongly associated variants reside in poorly annotated non-coding regions.

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.

Mapping genomic regions for reproductive traits in beef cattle: Inclusion of the X chromosome

Although the second largest chromosome of the genome, the X chromosome is usually excluded from genome-wide association studies (GWAS). Considering the presence and importance of genes on this chromosome that are involved in reproduction, the aim of this study was to evaluate the effect of its inclusion in GWAS on reproductive traits (scrotal circumference [SC], early pregnancy [P16] and age at first calving [AFC]) in a Nelore herd. Genotype data from 3,263 animals with the above-mentioned phenotypes were used. The results showed an increase in the variances explained by the autosomal markers for all traits when the X chromosome was not included. For SC, there was an increase of more than 10% for the windows on chromosomes 2 and 6. For P16, the effect was increased by almost 20% for windows on chromosome 5. The same pattern was found for AFC, with an increase of more than 10% for the most important windows. The results indicate that the noninclusion of the X chromosome can overestimate the effects of autosomes on SC, P16 and AFC not only because of the additive effect of the X chromosome itself but also because of its epistatic effect on autosomal genes.

Across-country genomic prediction of bull fertility in Jersey dairy cattle

The use of information across populations is an attractive approach to increase the accuracy of genomic predictions for numerically small breeds and traits that are time-consuming and difficult to measure, such as male fertility in cattle. This study was conducted to evaluate genomic prediction of Jersey bull fertility using an across-country reference population combining records from the United States and Australia. The data set consisted of 1,570 US Jersey bulls with sire conception rate (SCR) records, 603 Australian Jersey bulls with semen fertility value (SFV) records and SNP genotypes for roughly 90,000 loci. Both SCR and SFV are evaluations of service sire fertility based on cow field data, and both are intended as phenotypic evaluations because the estimates include genetic and nongenetic effects. Within- and across-country genomic predictions were evaluated using univariate and bivariate genomic best linear unbiased prediction models. Predictive ability was assessed in 5-fold cross-validation using the correlation between observed and predicted fertility values and mean squared error of prediction. Within-country genomic predictions exhibited predictive correlations of around 0.28 and 0.02 for the United States and Australia, respectively. The Australian Jersey population is genetically diverse and small in size, so careful selection of the reference population by including only closely related animals (e.g., excluding New Zealand bulls, which is a less-related population) increased the predictive correlations up to 0.20. Notably, the use of bivariate models fitting all US Jersey records and the optimized Australian population resulted in predictive correlations around of 0.24 for SFV values, which is a relative increase in predictive ability of 20%. Conversely, for predicting SCR values, the use of an across-country reference population did not outperform the standard approach using pure US Jersey reference data set. Our findings indicate that genomic prediction of male fertility in dairy cattle is feasible, and the use of an across-country reference population would be beneficial when local populations are small and genetically diverse.

Theoretical and empirical comparisons of expected and realized relationships for the X-chromosome

Background

X-chromosomal loci present different inheritance patterns compared to autosomal loci and must be modeled accordingly. Sexual chromosomes are not systematically considered in whole-genome relationship matrices although rules based on genealogical or marker information have been derived. Loci on the X-chromosome could have a significant contribution to the additive genetic variance, in particular for some traits such as those related to reproduction. Thus, accounting for the X-chromosome relationship matrix might be informative to better understand the architecture of complex traits (e.g., by estimating the variance associated to this chromosome) and to improve their genomic prediction. For such applications, previous studies have shown the benefits of combining information from genotyped and ungenotyped individuals.

Results

In this paper, we start by presenting rules to compute a genomic relationship matrix (GRM) for the X-chromosome (G^X) without making any assumption on dosage compensation, and based on coding of gene content with 0/1 for males and 0/1/2 for females. This coding adjusts naturally to previously derived pedigree-based relationships (S) for the X-chromosome. When needed, we propose to accommodate and estimate dosage compensation and genetic heterogeneity across sexes via multiple trait models. Using a Holstein dairy cattle dataset, including males and females, we then empirically illustrate that realized relationships (G^X) matches expectations (S). However, G^X presents high deviations from S. G^X has also a lower dimensionality compared to the autosomal GRM. In particular, individuals are frequently identical along the entire chromosome. Finally, we confirm that the heritability of gene content for markers on the X-chromosome that are estimated by using S is 1, further demonstrating that S and G^X can be combined. For the pseudo-autosomal region, we demonstrate that the expected relationships vary according to position because of the sex-gradient. We end by presenting the rules to construct the 'H matrix’ by combining both relationship matrices.

Conclusions

This work shows theoretically and empirically that a pedigree-based relationship matrix built with rules specifically developed for the X-chromosome (S) matches the realized GRM for the X-chromosome. Therefore, applications that combine expected relationships and genotypes for markers on the X-chromosome should use S and G^X.

Genetic architecture of individual variation in recombination rate on the X chromosome in cattle

Meiotic recombination is an essential biological process that ensures proper chromosome segregation and creates genetic diversity. Individual variation in global recombination rates has been shown to be heritable in several species, and variants significantly associated with this trait have been identified. Recombination on the sex chromosome has often been ignored in these studies although this trait may be particularly interesting as it may correspond to a biological process distinct from that on autosomes. For instance, recombination in males is restricted to the pseudo-autosomal region (PAR). We herein used a large cattle pedigree with more than 100,000 genotyped animals to improve the genetic map of the X chromosome and to study the genetic architecture of individual variation in recombination rate on the sex chromosome (XRR). The length of the genetic map was 46.4 and 121.2 cM in males and females, respectively, but the recombination rate in the PAR was six times higher in males. The heritability of CO counts on the X chromosome was comparable to that of autosomes in males (0.011) but larger than that of autosomes in females (0.024). XRR was highly correlated (0.76) with global recombination rate (GRR) in females, suggesting that both traits might be governed by shared variants. In agreement, a set of eleven previously identified variants associated with GRR had correlated effects on female XRR (0.86). In males, XRR and GRR appeared to be distinct traits, although more accurate CO counts on the PAR would be valuable to confirm these results.