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Gene expression patterns in anterior pituitary associated with quantitative measure of oestrous behaviour in dairy cows

Published online by Cambridge University Press:  04 March 2010

A. Kommadath ,
H. A. Mulder ,
A. A. C. de Wit ,
H. Woelders ,
M. A. Smits ,
B. Beerda ,
R. F. Veerkamp ,
A. C. J. Frijters  and
M. F. W. te Pas
A. Kommadath*
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
H. A. Mulder
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
A. A. C. de Wit
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
H. Woelders
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
M. A. Smits
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
B. Beerda
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
R. F. Veerkamp
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
A. C. J. Frijters
Affiliation:
CRV, Research & Development, P.O. Box 454, 6800 AL Arnhem, The Netherlands
M. F. W. te Pas
Affiliation:
Animal Breeding and Genomics Centre, Animal Sciences Group of Wageningen UR, P.O. Box 65, 8200 AB Lelystad, The Netherlands
*
†E-mail: [email protected]
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Abstract

Intensive selection for high milk yield in dairy cows has raised production levels substantially but at the cost of reduced fertility, which manifests in different ways including reduced expression of oestrous behaviour. The genomic regulation of oestrous behaviour in bovines remains largely unknown. Here, we aimed to identify and study those genes that were associated with oestrous behaviour among genes expressed in the bovine anterior pituitary either at the start of oestrous cycle or at the mid-cycle (around day 12 of cycle), or regardless of the phase of cycle. Oestrous behaviour was recorded in each of 28 primiparous cows from 30 days in milk onwards till the day of their sacrifice (between 77 and 139 days in milk) and quantified as heat scores. An average heat score value was calculated for each cow from heat scores observed during consecutive oestrous cycles excluding the cycle on the day of sacrifice. A microarray experiment was designed to measure gene expression in the anterior pituitary of these cows, 14 of which were sacrificed at the start of oestrous cycle (day 0) and 14 around day 12 of cycle (day 12). Gene expression was modelled as a function of the orthogonally transformed average heat score values using a Bayesian hierarchical mixed model on data from day 0 cows alone (analysis 1), day 12 cows alone (analysis 2) and the combined data from day 0 and day 12 cows (analysis 3). Genes whose expression patterns showed significant linear or non-linear relationships with average heat scores were identified in all three analyses (177, 142 and 118 genes, respectively). Gene ontology terms enriched among genes identified in analysis 1 revealed processes associated with expression of oestrous behaviour whereas the terms enriched among genes identified in analysis 2 and 3 were general processes which may facilitate proper expression of oestrous behaviour at the subsequent oestrus. Studying these genes will help to improve our understanding of the genomic regulation of oestrous behaviour, ultimately leading to better management strategies and tools to improve or monitor reproductive performance in bovines.

Keywords

oestrous behaviourgene expression patternquantitative traitanterior pituitarydairy cow
Type
Full Paper
Information
animal , Volume 4 , Issue 8 , August 2010 , pp. 1297 - 1307
Copyright
Copyright © The Animal Consortium 2010

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References

Bancroft, J 2005. The endocrinology of sexual arousal. Journal of Endocrinology 186, 411–427.Google Scholar
Bauer, S, Grossmann, S, Vingron, M, Robinson, PN 2008. Ontologizer 2.0 – a multifunctional tool for GO term enrichment analysis and data exploration. Bioinformatics 24, 1650–1651.Google Scholar
Beerda, B, Wyszynska-Koko, J, te Pas, MFW, de Wit, AAC, Veerkamp, RF 2008. Expression profiles of genes regulating dairy cow fertility: recent findings, ongoing activities and future possibilities. Animal 2, 1158–1167.CrossRefGoogle ScholarPubMed
Blalock, EM, Geddes, JW, Chen, KC, Porter, NM, Markesbery, WR, Landfield, PW 2004. Incipient Alzheimer’s disease: microarray correlation analyses reveal major transcriptional and tumor suppressor responses. Proceedings of the National Academy of Sciences of the United States of America 101, 2173–2178.CrossRefGoogle ScholarPubMed
Chiocchio, SR, Gallardo, MGP, Louzan, P, Gutnisky, V, Tramezzani, JH 2001. Melanin-concentrating hormone stimulates the release of luteinizing hormone-releasing hormone and gonadotropins in the female rat acting at both median eminence and pituitary levels. Biol Reprod 64, 1466–1472.Google Scholar
de Carvalho Aguiar, P, Sweadner, KJ, Penniston, JT, Zaremba, J, Liu, L, Caton, M, Linazasoro, G, Borg, M, Tijssen, MAJ, Bressman, SB, Dobyns, WB, Brashear, A, Ozelius, LJ 2004. Mutations in the Na+/K+-ATPase [alpha]3 gene ATP1A3 are associated with rapid-onset dystonia Parkinsonism. Neuron 43, 169–175.Google Scholar
Gentleman, R, Carey, V, Bates, D, Bolstad, B, Dettling, M, Dudoit, S, Ellis, B, Gautier, L, Ge, Y, Gentry, J, Hornik, K, Hothorn, T, Huber, W, Iacus, S, Irizarry, R, Leisch, F, Li, C, Maechler, M, Rossini, A, Sawitzki, G, Smith, C, Smyth, G, Tierney, L, Yang, J, Zhang, J 2004. Bioconductor: open software development for computational biology and bioinformatics. Genome Biology 5, R80.CrossRefGoogle ScholarPubMed
George, EI, McCulloch, RE 1993. Variable Selection Via Gibbs Sampling. Journal of the American Statistical Association 88, 881–889.Google Scholar
Gonzalez, MI, Vaziri, S, Wilson, CA 1996. Behavioral effects of [alpha]-MSH and MCH after central administration in the female rat. Peptides 17, 171–177.Google Scholar
Grossmann, S, Bauer, S, Robinson, PN, Vingron, M 2007. Improved detection of overrepresentation of Gene-Ontology annotations with parent child analysis. Bioinformatics 23, 3024–3031.CrossRefGoogle ScholarPubMed
Jia, Z, Tang, S, Mercola, D, Xu, S 2008. Detection of quantitative trait associated genes using cluster analysis. In Evolutionary computation, machine learning and data mining in bioinformatics (ed. E Marchiori and JH Moore), pp. 83–94. Springer-Verlag, Berlin Heidelberg.CrossRefGoogle Scholar
Jia, Z, Xu, S 2005. Clustering expressed genes on the basis of their association with a quantitative phenotype. Genetical Research 86, 193–207.Google Scholar
Jia, Z, Xu, S 2007. Mapping quantitative trait loci for expression abundance. Genetics 176, 611–623.Google Scholar
Lee, SL, Sadovsky, Y, Swirnoff, AH, Polish, JA, Goda, P, Gavrilina, G, Milbrandt, J 1996. Luteinizing hormone deficiency and female infertility in mice lacking the transcription factor NGFI-A (Egr-1). Science 273, 1219–1221.CrossRefGoogle Scholar
Lopez, H, Satter, LD, Wiltbank, MC 2004. Relationship between level of milk production and estrous behavior of lactating dairy cows. Animal Reproduction Science 81, 209–223.Google Scholar
Mihm, M, Austin, EJ 2002. The final stages of dominant follicle selection in cattle. Domestic Animal Endocrinology 23, 155–166.CrossRefGoogle ScholarPubMed
Niewold, TA, Veldhuizen, EJA, van der Meulen, J, Haagsman, HP, de Wit, AAC, Smits, MA, Tersteeg, MHG, Hulst, MM 2007. The early transcriptional response of pig small intestinal mucosa to invasion by Salmonella enterica serovar typhimurium DT104. Molecular Immunology 44, 1316–1322.Google Scholar
NRS 2009. The Royal Dutch Cattle Syndicate (NRS) Handbook. Retrieved, from https://www.cr-delta.nl/nl/fokwaarden/pdf/E17.pdf.Google Scholar
Pfaff, D 2005. Hormone-driven mechanisms in the central nervous system facilitate the analysis of mammalian behaviours. Journal of Endocrinology 184, 447–453.Google Scholar
Qu, Y, Xu, S 2006. Quantitative trait associated microarray gene expression data analysis. Molecular Biology and Evolution 23, 1558–1573.CrossRefGoogle ScholarPubMed
Reimand, J, Kull, M, Peterson, H, Hansen, J, Vilo, J 2007. g:Profiler – a web-based toolset for functional profiling of gene lists from large-scale experiments. Nucleic Acids Research 35, W193–W200.Google Scholar
Reiner-Benaim, A, Yekutieli, D, Letwin, NE, Elmer, GI, Lee, NH, Kafkafi, N, Benjamini, Y 2007. Associating quantitative behavioral traits with gene expression in the brain: searching for diamonds in the hay. Bioinformatics 23, 2239–2246.CrossRefGoogle ScholarPubMed
Ritchie, ME, Silver, J, Oshlack, A, Holmes, M, Diyagama, D, Holloway, A, Smyth, GK 2007. A comparison of background correction methods for two-colour microarrays. Bioinformatics 23, 2700–2707.Google Scholar
Rougon, G, Hobert, O 2003. New insights into the diversity and function of neuronal immunoglobulin superfamily molecules. Annual Review of Neuroscience 26, 207–238.CrossRefGoogle ScholarPubMed
Roxstrom, A, Strandberg, E, Berglund, B, Emanuelson, U, Philipsson, J 2001. Genetic and environmental correlations among female fertility traits and milk production in different parities of Swedish Red and White dairy cattle. Acta Agriculturae Scandinavica, A 51, 7–14.Google Scholar
Royal, MD, Darwash, AO, Flint, APF, Webb, R, Woolliams, JA, Lamming, GE 2000. Declining fertility in dairy cattle: changes in traditional and endocrine parameters of fertility. Animal Science 70, 487–501.Google Scholar
Smyth, GK 2005. Limma: linear models for microarray data. In Bioinformatics and computational biology solutions using R and bioconductor (ed. R Gentleman, V Carey, S Dudoit, R Irizarry and W Huber), pp. 397–420. Springer, New York, NY, USA.CrossRefGoogle Scholar
Van Eerdenburg, FJCM 2006. Estrus detection in dairy cattle: how to beat the bull. Vlaams Diergeneeskundig Tijdschrift 75, 61–69.CrossRefGoogle Scholar
Veerkamp, RF, Beerda, B 2007. Genetics and genomics to improve fertility in high producing dairy cows. Theriogenology 68, S266–S273.Google Scholar
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