Integrated multi-omics analyses reveals molecules governing sperm metabolism potentially influence bull fertility

Abstract

Bull fertility is of paramount importance in bovine industry because semen from a single bull is used to breed several thousands of cows; however, so far, no reliable test is available for bull fertility prediction. In the present study, spermatozoa from high- and low-fertility bulls were subjected to high-throughput transcriptomic, proteomic and metabolomic analysis. Using an integrated multi-omics approach the molecular differences between high- and low-fertility bulls were identified. We identified a total of 18,068 transcripts, 5041 proteins and 3704 metabolites in bull spermatozoa, of which the expression of 4766 transcripts, 785 proteins and 33 metabolites were dysregulated between high- and low-fertility bulls. At transcript level, several genes involved in oxidative phosphorylation pathway were found to be downregulated, while at protein level genes involved in metabolic pathways were significantly downregulated in low-fertility bulls. We found that metabolites involved in Taurine and hypotaurine metabolism were significantly downregulated in low-fertility bulls. Integrated multi-omics analysis revealed the interaction of dysregulated transcripts, proteins and metabolites in major metabolic pathways, including Butanoate metabolism, Glycolysis and gluconeogenesis, Methionine and cysteine metabolism, Phosphatidyl inositol phosphate, pyrimidine metabolism and saturated fatty acid beta oxidation. These findings collectively indicate that molecules governing sperm metabolism potentially influence bull fertility.

QTLs and Candidate Genes Associated with Semen Traits in Merino Sheep

“…As time of year influences semen quality in both pigs [60,61] and sheep [10,11], ACTRT2 may be a key gene modulating semen quality during the breeding and non-breeding seasons. Another gene, RPL12, is known to be significantly downregulated in bulls with low fertility, as assessed via conception rate following artificial insemination [62]. RPL12 has also been found to be upregulated in ram testes [63].…”

Bull Sperm SWATH-MS-Based Proteomics Reveals Link between High Fertility and Energy Production, Motility Structures, and Sperm–Oocyte Interaction

“…New advances in technology have improved proteomics techniques in the last years, and mass spectrometry (MS) has become the method of choice due to its unrivaled ability to analyze complex protein mixtures like spermatozoa. Data-dependent acquisition (DDA) is a widely used mode of data collection in tandem with mass spectrometry (MS/MS) sperm proteins from Holstein Friesian − or crossbreed bulls. − In 2013, Gillet et al proposed a new proteomic strategy using a data-independent acquisition (DIA) method called SWATH-MS (sequential window acquisition of all theoretical mass spectra). The SWATH-MS method is particularly innovative among the DIA methods and presents several advantages (reproducibility and consistency, data acquisition, and quantifiable proteins) compared with DDA-based methods and targeted proteomics. , Sperm proteomic analysis using SWATH-MS provides highly valuable information on cellular components or sperm function, which, together with the data obtained from the in vitro parameters obtained by FC or CASA, offers a more complete picture of biological events.…”

DMXL1 could be a potential candidate gene for semen quality in Holstein Friesian bulls

“…However, numerous bulls that appear phenotypically healthy end up producing unsatisfactory ejaculates [20] , resulting in the rejection of the ejaculates for AI. These issues could potentially arise from molecular defects within the DNA, RNA, and proteins of the spermatozoa (Prakash et al, 2021;Talluri et al, 2022;Elango et al, 2023;Kumaresan et al, 2023) [20,23,4,11] . The existing method for selecting bulls does not provide a comprehensive evaluation of semen quality since it primarily concentrates on physical characteristics and neglects genetic traits.…”

“…There are several techniques available for SNP identification within species, with RNA sequencing-next-generation sequencing (NGS) being the most commonly employed method. NGS produces substantial volumes of sequencing data, facilitating the identification of SNPs within a species (Podnar et al, 2014; [19,23] . Additionally, it allows for the determination of the SNP's location within the coding region associated with the gene trait.…”