2011 (SBTE) 25th Annual Meeting Proceedings - International ...

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W.W .W. Tha hatcher cher. <strong>2011</strong>. Temporal Historical Observations, Rapidly Expanding Technological Tools, and Integration of Scientific Disciplines to Enhance Reproductive Performance... Acta Scientiae Veterinariae. 39(Suppl 1): s147 - s169. meters of fertility, such as commencement of luteal activity measured in repeated samples at test days, into a fertility selection index may offer the potential to improve the accuracy of estimating predicted transmitting ability for fertility. Ever evolving and exciting technological strategies are now in place for development of gene markers offered by continual advances in DNA arraying technologies, the bovine genome mapping program, and deep RNA sequencing to more extensively explore the transcriptomes of conceptus and reproductive tissues. Use of genomic technology has identified a potential gene or associated locus that is related to bull fertility [21]. A Phase I comprehensive genome wide analysis of SNPs for bull fertility identified a total of 97 SNPs that were significantly associated with fertility (P < 0.01). In Phase II, the four most significant SNPs of Phase I were tested in 101 low fertility and 100 high-fertility bulls. One of the SNPs, rs41257187 (C-T) is in the coding region of the integrin beta 5 gene on chromosome 1. The SNP rs41257187 induces a synonymous (Proline - Proline) suggesting disequilibrium with the true causative locus. However, incubation of bull spermatozoa with integrin beta 5 antibodies significantly decreased the ability to fertilize oocytes. These insightful findings indicate that the bovine sperm integrin beta 5 protein plays a role during fertilization and could serve as a positional or functional marker of bull fertility. This genomic approach enters into the tool box for strategies to improve dairy cattle fertility. Seven sequence variants (SVs) have been identified in exon 1 and in the promoter region upstream of the bovine gonadotrophin releasing hormone (GnRH) receptor gene [15]. The g.-108T > C allelic variants were associated with an approximately 0.4 day reduction in predicted transmitting ability for days to first service. This relationship infers that selection for animals carrying the g.-108T>C group of alterations may improve fertility in the dairy cow. Furthermore, cattle with the homozygous (CC) genotype for the calpastatin gene had an additional 0.82 and 0.57 PTA greater units of Daughter Pregnancy Rate (i.e., equivalent to 3.28 and 2.28 days open) compared with the TT homozygous and CT heterozygous animals [24]. The laboratory of H. Khatib at the Univerisity of Wisconsin constructed an in vitrofertilization (IVF) system that has the advantages of a unified environment and well-isolated components of the embryonic development process. Utilizing this system, SNP in several genes and interactions between them have been found to be associated with fertilization and early embryonic survival rates until day 7 [34,35,37]. In order to determine SNP genotpyes, the ovaries of origin for the oocytes and sperm from bulls were genotyped for genes of interest. The candidate genes with their SNP alleles were associated differentially with in vitrofertility of the embryos. This in vitroassessment of potential fertility genes were then examined in vivoin which bulls were genotyped for SNP alleles and fertility was assessed [36]. Estimated relative conception rate (ERCR) data from 222 young and mature Holstein bulls were obtained from April through June 2001. Estimated relative conception rate was the difference in conception rate (nonreturn rate at 70 d) of a sire compared with other AI sires used in the same herd for first insemination of lactating cows. The ERCR values for the 222 bulls ranged from 4.99 to +5.23. Semen for each of the bulls was SNP genotyped for the following genes: FGF2 = fibroblast growth factor 2; POU1F1 = pituitary-specific positive transcription factor 1; GH = growth hormone; PRL = prolactin; GHR= growth hormone receptor; PRLR = prolactin receptor; STAT5A = signal transducer and activator of transcription 5A; OPN = osteopontin; UTMP = uterine milk protein, and the data were analyzed for association with ERCR. The ERCR was associated with FGF2 and STAT5A polymorphisms. This in vivo validation of previous in vitro assessments of fertility suggests that these genes can be used in gene-assisted selection programs for reproductive performance in dairy cattle. Collectively the various studies cited identify a number of candidate genes for inclusion in a fertility array. Such strategies involving various technological approaches and cell-animal models will likely lead to development of fertility arrays that will allow for the identification of animals at a young age with potentially high fertility (i.e., male and female) and high production. The challenge will be to manage the lactating cows to achieve their reproduction and production potentials. Markers for several recessive diseases have been developed through the use of Marker Assisted Selection. Examples of diseases that severely impact s164
W.W .W. Tha hatcher cher. <strong>2011</strong>. Temporal Historical Observations, Rapidly Expanding Technological Tools, and Integration of Scientific Disciplines to Enhance Reproductive Performance... Acta Scientiae Veterinariae. 39(Suppl 1): s147 - s169. reproductive performance, but that have been reduced to minor concerns because of the use of genetic markers, are BLAD (Bovine Leukocyte Adhesion Deficiency), DUMPS (Deficiency of Uridine - 5-Monophosphate Synthase) and CVM (Complex Vertebral Malformation). Sequencing the bovine genome and further advances in functional genomics promises great benefits to the dairy industry. As genes for production traits are identified, genetic selection strategies can be improved. One can envision making improvements in milk yields and milk fat and protein composition, as well as herd health and reproductive performance. As genes for production traits are identified, gene selection will be reduced to simply running a genetic test for the complement of gene alleles associated with the characteristics of interest. V. CONCLUSION Epidemiological data analyses are a powerful tool to identify reproductive inefficiencies and potential causative associations, but do not prove cause and effect. Healthy postpartum lactating dairy cows are indeed fertile. Induction of ovarian quiescence in response to chronic exposure of a GnRH agonist induced postpartum uterine atrophy and warrants additional investigation relative to potential impacts on improved uterine health. Dietary supplementation with polyunsaturated omega-6 and omega-3 fatty acids improves postpartum innate immune function and subsequent reproductive performance. Colostrum feeding contains lactocrine secretions that influence uterine developmental programming in the immediate postpartum period and neonatal exposure to estrogens/progesterone alters early programming of the uterus leading to dysfunctional reproductive tract consequences in the adult. Reproductive management programs that optimize ovarian and uterine function permit a single timed insemination to an induced ovulation that increases pregnancy per insemination to both first insemination and resynchronized inseminations of cows diagnosed non-pregnant. The sequencing of the bovine genome has led to thorough characterizations of the endometrium and conceptus transcriptomes in response to key physiological periods such as pregnancy and lactation. Early expression of PAG genes within the conceptus and endometrium of pregnant cows and their association with other genes determined by standard partial correlation analyses infer a possible role of PAG in pregnancy maintenance and implantation by regulation of embryo development, trophoblast cell invasion, immune regulation, and prostaglandin metabolism. Candidate genes have been identified that are related to fertility based upon in vitro and in vivo approaches. The array of SNPs across the bovine genome and specific SNPs within candidate genes related to reproductive processes and fertility will enhance genetic selection for fertility. Genomic selection for production, health and reproductive traits will be the wave of the future as genomic and bioinformatic tools continue to be expanded and refined. Acknowledgments. author is indebted to the following students and colleagues who have contributed too many of the research projects described in this manuscript over N the last 40 years and who are my mentors. Their intellectual contributions and dedicated efforts are the foundation of an interdisciplinary program that has sustained my commitment to science: Students and Trainees. Francis C. Gwasdauskas, John R. Chenault, Heriberto Roman Ponce, Luis C. Fernandes, Robert M. Eley, Frank F. Bartol, Louis A. Guilbault, Jeffrey F. Knickerbocker, LokengaBadinga, Joan S. Curl, Stephen D. Helmer, Matthew Lucy, GuenahelDanet-Desnoyers, Rodolfo de la Sota, Eric J.-P. Schmitt, Thais Diaz Zambrano, Mario Binelli, Frederico Moreira, Ricardo Mattos, SukruMetinPancarci, AydinGuzeloglu, Julian Bartolome, Todd Bilby, Flavio T. Silvestre, Leonidas A. Chow, Juan F. Troconiz, Elveria O. Valdivia, Diann S. Eley, John M. McDermott, Judy Van Cleeff, Monte Meyer, Daniel Arnold, Flavia Lopes, Isabella Thompson, Gregory S. Lewis, David Wolfenson, Timothy S. Gross, Jorge Savio, Joan Burke, Divakar Ambrose and Ronaldo Luís Aoki Cerri. Colleagues. Fuller W. Bazer, R. Michael Roberts, Charles J. Wilcox, Peter J. Hansen, Charles R.Staples, Robert J. Collier, Jose E.P. Santos, T.R. Hansen. REFERENCES 1 Austin K.J., King C.P., Vierk J.E., Sasser R.G. & Hansen T.R. 1999. Pregnancy-specific protein B induces release of an alpha chemokine in bovine endometrium. Endocrinology. 140(1): 542-545. s165
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