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Identification of biomarkers for bull fertility using functional genomics
Authors:Muhammet Rasit Ugur  Denise D. Guerreiro  Arlindo A. Moura  Erdogan Memili
Affiliation:1. IVF Michigan, Bloomfield Hills, MI, USA ; 2. Departamento de Zootecnia, Universidade Federal do Ceará, Fortaleza, CE, Brasil ; 3. Núcleo de Pesquisa e Desenvolvimento de Medicamentos, Faculdade de Medicina, Universidade Federal do Ceará, Fortaleza, CE, Brasil ; 4. Department of Animal and Dairy Sciences, Mississippi State University, Starkville, MS, USA ; 5. Cooperative Agricultural Research Center, Prairie View A&M University, Prairie View, TX, USA
Abstract:Prediction of bull fertility is critical for the sustainability of both dairy and beef cattle production. Even though bulls produce ample amounts of sperm with normal parameters, some bulls may still suffer from subpar fertility. This causes major economic losses in the cattle industry because using artificial insemination, semen from one single bull can be used to inseminate hundreds of thousands of cows. Although there are several traditional methods to estimate bull fertility, such methods are not sufficient to explain and accurately predict the subfertility of individual bulls. Since fertility is a complex trait influenced by a number of factors including genetics, epigenetics, and environment, there is an urgent need for a comprehensive methodological approach to clarify uncertainty in male subfertility. The present review focuses on molecular and functional signatures of bull sperm associated with fertility. Potential roles of functional genomics (proteome, small noncoding RNAs, lipidome, metabolome) on determining male fertility and its potential as a fertility biomarker are discussed. This review provides a better understanding of the molecular signatures of viable and fertile sperm cells and their potential to be used as fertility biomarkers. This information will help uncover the underlying reasons for idiopathic subfertility.
Keywords:bull sperm   bull fertility   fertility biomarkers   functional genomics
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