Stable bull fertility protein markers in seminal plasma

Willforss, Jakob; Morrell, Jane M.; Resjö, Svante; Hallap, Triin; Padrik, Peeter; Siino, Valentina; Koning, Dirk-Jan de; Andréasson, Erik; Levander, Fredrik; Humblot, P.

doi:10.1016/j.jprot.2021.104135

Cited by 20 publications

(14 citation statements)

References 57 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The LC-MS/ MS analysis of pig sperm revealed eight fertility-related proteins over-represented in Tibetan pigs having heritable adaptation to hypoxic environments (Zhao et al, 2021). In another study, analysis of seminal plasma proteins by LC-MS/MS found a consistent correlation of 1,343 proteins with fertility (Willforss et al, 2021). Thus, identifying fertility markers by proteomics can help identify fertile bulls to reduce non-return rates (NRR) and increase productivity.…”

Section: Proteomicsmentioning

confidence: 98%

Applications of Omics Technology for Livestock Selection and Improvement

et al. 2022

View full text Add to dashboard Cite

Conventional animal selection and breeding methods were based on the phenotypic performance of the animals. These methods have limitations, particularly for sex-limited traits and traits expressed later in the life cycle (e.g., carcass traits). Consequently, the genetic gain has been slow with high generation intervals. With the advent of high-throughput omics techniques and the availability of multi-omics technologies and sophisticated analytic packages, several promising tools and methods have been developed to estimate the actual genetic potential of the animals. It has now become possible to collect and access large and complex datasets comprising different genomics, transcriptomics, proteomics, metabolomics, and phonemics data as well as animal-level data (such as longevity, behavior, adaptation, etc.,), which provides new opportunities to better understand the mechanisms regulating animals’ actual performance. The cost of omics technology and expertise of several fields like biology, bioinformatics, statistics, and computational biology make these technology impediments to its use in some cases. The population size and accurate phenotypic data recordings are other significant constraints for appropriate selection and breeding strategies. Nevertheless, omics technologies can estimate more accurate breeding values (BVs) and increase the genetic gain by assisting the section of genetically superior, disease-free animals at an early stage of life for enhancing animal productivity and profitability. This manuscript provides an overview of various omics technologies and their limitations for animal genetic selection and breeding decisions.

show abstract

Section: Proteomicsmentioning

confidence: 98%

Applications of Omics Technology for Livestock Selection and Improvement

et al. 2022

View full text Add to dashboard Cite

show abstract

“…The vast majority of proteins found in spermatozoa have roles in the earliest stages of the sperm’s journey: spermatogenesis, maturation, and energy production ( Figure 1 ). Of the previously mentioned proteins, all three BSPs, SPP1, and PTGDS were again identified in association with fertility status, though here PTGDS was significantly correlated to low fertility [ 61 ].…”

Section: Proteinsmentioning

confidence: 99%

“…Earlier studies into the bull sperm proteome were performed using cryopreserved straws of semen [ 56 , 57 ], while more recent studies tend to separate seminal plasma from spermatozoa prior to snap freezing [ 58 , 59 , 61 ] or lyophilization [ 60 ]. Significant changes in abundance of proteins in both spermatozoa and seminal plasma can occur during cryopreservation, interestingly increasing the abundance of some proteins [ 62 ].…”

Section: Proteinsmentioning

confidence: 99%

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

Klein

Swegen

Gunn

et al. 2022

Biology of Reproduction

View full text Add to dashboard Cite

Breeding soundness examinations (BSEs) 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 realised 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 fertilisation and the development of the embryo. There has been a plethora of recent research characterising the many molecular attributes that can affect the functional competence of a spermatozoon. A better understanding of the molecular factors influencing fertilisation 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 BSEs 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 proposed biomarkers to be of diagnostic or predictive value.

show abstract

“…In a recent study on Tibetan pigs having heritable adaptation to hypoxic environments, eight fertility-related proteins were overexpressed by LC-MS/MS analysis ( Zhao et al., 2021 ). Analysis of seminal plasma proteins by LC-MS/MS found a significant correlation between proteins with fertility ( Willforss et al., 2021 ). The application of proteomics can help identify fertile bulls to increase productivity and reduce the non-return rate (NRR).…”

Section: Nutrigenomics In the Livestock Sectormentioning

confidence: 99%