Immunosuppression, sialic acid, and sialyltransferase of bovine serum as a function of progesterone concentration

Sherblom, Anne P.; Smagula, Rosalita M; Moody, Charles E.; Anderson, Gary

doi:10.1530/jrf.0.0740509

Cited by 11 publications

(3 citation statements)

References 15 publications

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“…As mentioned in the previous section, the oestrogen and progesterone have previously been shown to increase sialylation in the rat and bovine models (Rajalakshmi et al 1969, Sherblom et al 1985; thus, comparisons of the serum oestrogen levels in our model indicated that the oestrogen levels were low at selection, increased at differentiation and then decreased at luteinisation (Walsh et al 2012b). This was evident in both the cow and heifer; however, the heifer exhibited approximately twofold higher serum oestrogen concentrations than the cow.…”

Section: Ff Glycan Characterisationsupporting

confidence: 61%

“…However, the analysis indicated a higher proportion of nonsialylated glycans and a corresponding decrease in sialylated glycan structures in lactating cows when compared with heifers. An increase in uterine sialic acid, which was induced by oestrogen, has been reported in the rat (Rajalakshmi et al 1969) and increases in sialic acid and sialyltransferase activity correlate with increased circulating progesterone concentrations in the bovine model (Sherblom et al 1985). The concentrations of oestrogen and progesterone are also linked with fertility in heifers and lactating dairy cows, where heifers display higher circulating progesterone concentrations and this has been linked to their higher fertility in comparison with lactating dairy cows (Crowe 2008).…”

Section: Ff Glycan Characterisationmentioning

confidence: 90%

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N-glycan profiling of bovine follicular fluid at key dominant follicle developmental stages

Tharmalingam-Jaikaran

Walsh

McGettigan

et al. 2014

Reproduction

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Follicular fluid (FF), an important microenvironment for the development of oocytes, contains many proteins that are glycosylated with N-linked glycans. This study aimed i) to present an initial analysis of the N-linked glycan profile of bovine FF using hydrophilic interaction liquid chromatography, anion exchange chromatography, high performance liquid chromatography (HPLC)-based separations and subsequent liquid chromatography-mass spectrometry/mass spectrometry analysis; ii) to determine differences in the N-glycan profile between FF from dominant and subordinate follicles from dairy heifers and lactating dairy cows and iii) to identify alterations in the N-glycan profile of FF during preovulatory follicle development using newly selected, differentiated (preovulatory) and luteinised dominant follicles from dairy heifers and lactating cows. We found that the majority of glycans on bovine FF are based on biantennary hypersialylated structures, where the glycans are sialylated on both the galactose and N-acetylglucosamine terminal sugars. A comparison of FF N-glycans from cows and heifers indicated higher levels of nonsialylated glycans with a lower proportion of sialylated glycans in cows than in heifers. Overall, as the follicle develops from Selection, Differentiation and Luteinisation in both cows and heifers, there is an overall decrease in sialylated structures on FF N-glycans.

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Section: Ff Glycan Characterisationsupporting

confidence: 61%

Section: Ff Glycan Characterisationmentioning

confidence: 90%

N-glycan profiling of bovine follicular fluid at key dominant follicle developmental stages

Tharmalingam-Jaikaran

Walsh

McGettigan

et al. 2014

Reproduction

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“…Only MeSH analysis was able to uncover ST3 beta‐galactoside alpha‐2,3‐sialyltransferase 1 ( ST3GAL1 ), a gene member of the sialyltransferases family (MeSH:D012799) known to be influenced by level of progesterone in cyclic and pregnant female cattle (Sherblom et al . ).…”

Section: Resultsmentioning

confidence: 97%

An application of Me SH enrichment analysis in livestock

et al. 2015

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SummaryAn integral part of functional genomics studies is to assess the enrichment of specific biological terms in lists of genes found to be playing an important role in biological phenomena. Contrasting the observed frequency of annotated terms with those of the background is at the core of overrepresentation analysis (ORA). Gene Ontology (GO) is a means to consistently classify and annotate gene products and has become a mainstay in ORA. Alternatively, Medical Subject Headings (MeSH) offers a comprehensive life science vocabulary including additional categories that are not covered by GO. Although MeSH is applied predominantly in human and model organism research, its full potential in livestock genetics is yet to be explored. In this study, MeSH ORA was evaluated to discern biological properties of identified genes and contrast them with the results obtained from GO enrichment analysis. Three published datasets were employed for this purpose, representing a gene expression study in dairy cattle, the use of SNPs for genome‐wide prediction in swine and the identification of genomic regions targeted by selection in horses. We found that several overrepresented MeSH annotations linked to these gene sets share similar concepts with those of GO terms. Moreover, MeSH yielded unique annotations, which are not directly provided by GO terms, suggesting that MeSH has the potential to refine and enrich the representation of biological knowledge. We demonstrated that MeSH can be regarded as another choice of annotation to draw biological inferences from genes identified via experimental analyses. When used in combination with GO terms, our results indicate that MeSH can enhance our functional interpretations for specific biological conditions or the genetic basis of complex traits in livestock species.

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