Identification of genome regions determining semen quality in Holstein-Friesian bulls using information theory

CFAP58 is involved in the sperm head shaping and flagellogenesis of cattle and mice

CFAP58 is a testis-enriched gene that plays an important role in the sperm flagellogenesis of humans and mice. However, the effect of CFAP58 on bull semen quality and the underlying molecular mechanisms involved in spermatogenesis remain unknown. Here, we identified two single-nucleotide polymorphisms (rs110610797, A>G and rs133760846, G>T) and one indel (g.-1811_ g.-1810 ins147bp) in the promoter of CFAP58 that were significantly associated with semen quality of bulls, including sperm deformity rate and ejaculate volume. Moreover, by generating gene knockout mice, we found for the first time that the loss of Cfap58 not only causes severe defects in the sperm tail, but also affects the manchette structure, resulting in abnormal sperm head shaping. Cfap58 deficiency causes an increase in spermatozoa apoptosis. Further experiments confirmed that CFAP58 interacts with IFT88 and CCDC42. Moreover, it may be a transported cargo protein that plays a role in stabilizing other cargo proteins, such as CCDC42, in the intra-manchette transport/intra-flagellar transport pathway. Collectively, our findings reveal that CFAP58 is required for spermatogenesis and provide genetic markers for evaluating semen quality in cattle.

Genome-Wide Association Analysis of Semen Characteristics in Piétrain Boars

Since artificial insemination is common practice in pig breeding, the quality and persistence of the semen are decisive for the usability of individual boars. In the current study, genome-wide association analyses were performed to investigate the genetic variability underlying phenotypic variations in semen characteristics. These traits comprise sperm morphology and sperm motility under different temporal and thermal storage conditions, in addition to standard semen quality parameters. Two consecutive samples of the fourth and fifth ejaculates from the same boar were comprehensively analyzed in a genotyped Piétrain boar population. A total of 13 genomic regions on different chromosomes were identified that contain single-nucleotide polymorphisms significantly associated with these traits. Subsequent analysis of the genomic regions revealed candidate genes described to be involved in spermatogenesis, such as FOXL3, GPER1, PDGFA, PRKAR1B, SNRK, SUN1, and TSPO, and sperm motility, including ARRDC4, CEP78, DNAAF5, and GPER1. Some of these genes were also associated with male fertility or infertility in mammals (e.g., CEP78, GPER1). The analyses based on these laboriously determined and valuable phenotypes contribute to a better understanding of the genetic background of male fertility traits in pigs and could prospectively contribute to the improvement of sperm quality through breeding approaches.

Identification of runs of homozygosity associated with male fertility in Italian Brown Swiss cattle

Intensive selection for improved productivity has been accompanied by an increase in inbreeding rates and a reduction in genetic diversity. The increase in inbreeding tends to impact performance, especially fitness-related traits such as male fertility. Inbreeding can be monitored using runs of homozygosity (ROH), defined as contiguous lengths of homozygous genotypes observed in an individual's chromosome. The goal of this study was to evaluate the presence of ROH in Italian Brown Swiss cattle and assess its association with bull fertility. First, we evaluated the association between ROH and male fertility using 1,102 Italian Brown Swiss bulls with sire conception rate records and 572 K SNPs spanning the entire genome. Second, we split the entire population into 100 high-fertility and 100 low-fertility bulls to investigate the potential enrichment of ROH segments in the low-fertility group. Finally, we mapped the significant ROH regions to the bovine genome to identify candidate genes associated with sperm biology and male fertility. Notably, there was a negative association between bull fertility and the amount of homozygosity. Four different ROH regions located in chromosomes 6, 10, 11, and 24 were significantly overrepresented in low-fertility bulls (Fisher's exact test, p-value <0.01). Remarkably, these four genomic regions harbor many genes such as WDR19, RPL9, LIAS, UBE2K, DPF3, 5S-rRNA, 7SK, U6, and WDR7 that are related to sperm biology and male fertility. Overall, our findings suggest that inbreeding and increased homozygosity have a negative impact on male fertility in Italian Brown Swiss cattle. The quantification of ROH can contribute to minimizing the inbreeding rate and avoid its negative effect on fitness-related traits, such as male fertility.

Genome-wide assessment and mapping of inbreeding depression identifies candidate genes associated with semen traits in Holstein bulls

BACKGROUND

The reduction in phenotypic performance of a population due to mating between close relatives is called inbreeding depression. The genetic background of inbreeding depression for semen traits is poorly understood. Thus, the objectives were to estimate the effect of inbreeding and to identify genomic regions underlying inbreeding depression of semen traits including ejaculate volume (EV), sperm concentration (SC), and sperm motility (SM). The dataset comprised ~ 330 K semen records from ~ 1.5 K Holstein bulls genotyped with 50 K single nucleotide polymorphism (SNP) BeadChip. Genomic inbreeding coefficients were estimated using runs of homozygosity (i.e., F_ROH > 1 Mb) and excess of SNP homozygosity (F_SNP). The effect of inbreeding was estimated by regressing phenotypes of semen traits on inbreeding coefficients. Associated variants with inbreeding depression were also detected by regressing phenotypes on ROH state of the variants.

RESULTS

Significant inbreeding depression was observed for SC and SM (p < 0.01). A 1% increase in F_ROH reduced SM and SC by 0.28% and 0.42% of the population mean, respectively. By splitting F_ROH into different lengths, we found significant reduction in SC and SM due to longer ROH, which is indicative of more recent inbreeding. A genome-wide association study revealed two signals positioned on BTA 8 associated with inbreeding depression of SC (p < 0.00001; FDR < 0.02). Three candidate genes of GALNTL6, HMGB2, and ADAM29, located in these regions, have established and conserved connections with reproduction and/or male fertility. Moreover, six genomic regions on BTA 3, 9, 21 and 28 were associated with SM (p < 0.0001; FDR < 0.08). These genomic regions contained genes including PRMT6, SCAPER, EDC3, and LIN28B with established connections to spermatogenesis or fertility.

CONCLUSIONS

Inbreeding depression adversely affects SC and SM, with evidence that longer ROH, or more recent inbreeding, being especially detrimental. There are genomic regions associated with semen traits that seems to be especially sensitive to homozygosity, and evidence to support some from other studies. Breeding companies may wish to consider avoiding homozygosity in these regions for potential artificial insemination sires.

Genetic analysis of production traits and body size measurements and their relationships with metabolic diseases in German Holstein cattle

This study sheds light on the genetic complexity and interplay of production, body size, and metabolic health in dairy cattle. Phenotypes for body size-related traits from conformation classification (130,166 animals) and production (101,562 animals) of primiparous German Holstein cows were available. Additionally, 21,992, 16,641, and 7,096 animals were from herds with recordings of the metabolic diseases ketosis, displaced abomasum, and milk fever in first, second, and third lactation. Moreover, all animals were genotyped. Heritabilities of traits and genetic correlations between all traits were estimated and GWAS were performed. Heritability was between 0.240 and 0.333 for production and between 0.149 and 0.368 for body size traits. Metabolic diseases were lowly heritable, with estimates ranging from 0.011 to 0.029 in primiparous cows, from 0.008 to 0.031 in second lactation, and from 0.037 to 0.052 in third lactation. Production was found to have negative genetic correlations with body condition score (BCS; -0.279 to -0.343) and udder depth (-0.348 to -0.419). Positive correlations were observed for production and body depth (0.138-0.228), dairy character (DCH) (0.334-0.422), and stature (STAT) (0.084-0.158). In first parity cows, metabolic disease traits were unfavorably correlated with production, with genetic correlations varying from 0.111 to 0.224, implying that higher yielding cows have more metabolic problems. Genetic correlations of disease traits in second and third lactation with production in primiparous cows were low to moderate and in most cases unfavorable. While BCS was negatively correlated with metabolic diseases (-0.255 to -0.470), positive correlations were found between disease traits and DCH (0.269-0.469) as well as STAT (0.172-0.242). Thus, the results indicate that larger and sharper animals with low BCS are more susceptible to metabolic disorders. Genome-wide association studies revealed several significantly associated SNPs for production and conformation traits, confirming previous findings from literature. Moreover, for production and conformation traits, shared significant signals on Bos taurus autosome (BTA) 5 (88.36 Mb) and BTA 6 (86.40 to 87.27 Mb) were found, implying pleiotropy. Additionally, significant SNPs were observed for metabolic diseases on BTA 3, 10, 14, 17, and 26 in first lactation and on BTA 2, 6, 8, 17, and 23 in third lactation. Overall, this study provides important insights into the genetic basis and interrelations of relevant traits in today's Holstein cattle breeding programs, and findings may help to improve selection decisions.

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

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

Detection of copy number variants in African goats using whole genome sequence data

Background

Copy number variations (CNV) are a significant source of variation in the genome and are therefore essential to the understanding of genetic characterization. The aim of this study was to develop a fine-scaled copy number variation map for African goats. We used sequence data from multiple breeds and from multiple African countries.

Results

A total of 253,553 CNV (244,876 deletions and 8677 duplications) were identified, corresponding to an overall average of 1393 CNV per animal. The mean CNV length was 3.3 kb, with a median of 1.3 kb. There was substantial differentiation between the populations for some CNV, suggestive of the effect of population-specific selective pressures. A total of 6231 global CNV regions (CNVR) were found across all animals, representing 59.2 Mb (2.4%) of the goat genome. About 1.6% of the CNVR were present in all 34 breeds and 28.7% were present in all 5 geographical areas across Africa, where animals had been sampled. The CNVR had genes that were highly enriched in important biological functions, molecular functions, and cellular components including retrograde endocannabinoid signaling, glutamatergic synapse and circadian entrainment.

Conclusions

This study presents the first fine CNV map of African goat based on WGS data and adds to the growing body of knowledge on the genetic characterization of goats.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07703-1.

Sperm Methylome Profiling Can Discern Fertility Levels in the Porcine Biomedical Model

A combined Genotyping By Sequencing (GBS) and methylated DNA immunoprecipitation (MeDIP) protocol was used to identify—in parallel—genetic variation (Genomic-Wide Association Studies (GWAS) and epigenetic differences of Differentially Methylated Regions (DMR) in the genome of spermatozoa from the porcine animal model. Breeding boars with good semen quality (n = 11) and specific and well-documented differences in fertility (farrowing rate, FR) and prolificacy (litter size, LS) (n = 7) in artificial insemination programs, using combined FR and LS, were categorized as High Fertile (HF, n = 4) or Low Fertile (LF, n = 3), and boars with Unknown Fertility (UF, n = 4) were tested for eventual epigenetical similarity with those fertility-proven. We identified 165,944 Single Nucleotide Polymorphisms (SNPs) that explained 14–15% of variance among selection lines. Between HF and LF individuals (n = 7, 4 HF and 3 LF), we identified 169 SNPs with p ≤ 0.00015, which explained 58% of the variance. For the epigenetic analyses, we considered fertility and period of ejaculate collection (late-summer and mid-autumn). Approximately three times more DMRs were observed in HF than in LF boars across these periods. Interestingly, UF boars were clearly clustered with one of the other HF or LF groups. The highest differences in DMRs between HF and LF experimental groups across the pig genome were located in the chr 3, 9, 13, and 16, with most DMRs being hypermethylated in LF boars. In both HF and LF boars, DMRs were mostly hypermethylated in late-summer compared to mid-autumn. Three overlaps were detected between SNPs (p ≤ 0.0005, n = 1318) and CpG sites within DMRs. In conclusion, fertility levels in breeding males including FR and LS can be discerned using methylome analyses. The findings in this biomedical animal model ought to be applied besides sire selection for andrological diagnosis of idiopathic sub/infertility.