Gene expression profiling by cDNA-AFLP and identification of differentially expressed transcripts of bovine pituitary gland in growing bulls of dairy breeds

• Autorzy: Pareek C.S. , Pierzchala M. , Michno J. , Szymanska S. , Smoczynski R. , Jasik N. , Golebiewski M. , Tyburski J. , Urbanski P. , Goluch D. , Oprzadek J. , Zwierzchowski L. , Siriluck P. , Wimmers K.
• Języki publikacji: EN

Abstrakty

EN

The study utilized age-dependent breed-specific gene expression profiling by cDNA-AFLP technique in identification of differentially expressed (DE) candidate genes for growth and development trait. Results revealed 15579 transcript derived fragments (TDFs) expressed in bovine pituitary gland tissue using 96 unique PCR reactions with primer combinations (PC) of TaqI-MseI for Polish Holstein (PH) and Polish Red (PR) dairy breeds. Gene expression profiling by cDNA-AFLP identified 1451,2877 and 4084 identically displayed (iDD), differentially displayed (DD) and single displayed (sDD) TDFs, respectively. In all transcript profiles, frequencies of DD TDFs were higher than that of iDD TDFs. A total of 60 DD TDFs bands were excised for PH (n=40) and PR (n=20) . Direct sequencing results revealed identification of 24 and 8 DE-TDFs sequences in Polish HF and PR. Based on the significance of BLAST and sequence alignment score, analysis 12 and 4 DE-TDFs sequences of PH and PR were excluded. Overall, 12 Polish HF and 4 PR breed specific DE-TDFs sequence expressed in bovine pituitary gland tissue were identified. The identified DE-TDFs sequences were represented in all bovine chromosomes, except BTA3, 4, 6, 7, 8, 9, 11, 12, 17, 18, 21, 22, 23, 25 and 26. TDF annotation results identified eight sequences that have BLAST hits to known annotated bovine genes and eight sequences to unannotated contig regions in latest gene ensemble database Btau 4,0. Two breed-specific target genes i.e., bovine glycophorin C (PH) and bovine arachidonate 5-lipoxygenase (Alox5) isoform 1 (PR) were validated by qRT-PCR. Within breed the age-dependent qRT-PCR analysis revealed that expression levels were differed significantly high (P<0.0001) with nine folds higher expression in young bulls at the age of 6 month (glycophorin C) and 9 month (Alox5 isoform 1). Between breed the qRT-PCR analyses revealed that the expression levels were highly significant for glycophorin C gene in PR and Alox5 isoform 1 gene in both breeds. It was concluded that gene expression profiling by cDNA-AFLP is a reliable technique for identification of trait-associated DE candidate genes, and helpful in elucidating and understanding molecular basis of postnatal growth and development of cattle.

• Wydawca: -
• Czasopismo: Animal Science Papers and Reports
• Rocznik: 2012
• Tom: 30
• Numer: 2
• Opis fizyczny: p103-119,fig.,ref.

Twórcy

autor

Pareek C.S.

• Institute of General and Molecular Biology, Faculty of Biology and Earth Science, Nicolaus Copernicus University, Gagarina 9, 87-100 Toruń, Poland

autor

Pierzchala M.

autor

Michno J.

autor

Szymanska S.

autor

Smoczynski R.

autor

Jasik N.

autor

Golebiewski M.

autor

Tyburski J.

autor

Urbanski P.

autor

Goluch D.

autor

Oprzadek J.

autor

Zwierzchowski L.

autor

Siriluck P.

autor

Wimmers K.

Bibliografia

• Afolayan R.A., 2003 – Genetics of growth and development in cattle. PhD thesis. Adelaide University, Animal Science Department, Adelaide, Australia.
• Altschul S.F., Madden T.L, Schaffer A.A., Zhang J.H., Zhang Z., Miller W.,Lipman D.J., 1997 – Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research 25, 3389-3402.
• Bachem C.W.B., Van der Hoeven R.S., de Bruijn S.M., Vreugdenhil D., Zabeau M., Visser R.G.F., 1996 – Visualization of differential gene expression using a novel method of RNA fingerprinting based on AFLP: analysis of gene expression during potato tuber development.Plant Journal 9, 745-753.
• Bachem C.W.B., Oomen R.J.F.J., Richard G.F., 1998 – Transcript imaging with cDNAAFLP: a step-by-step protocol. Plant Molecular Biology Reporter, 16, 157-173.
• Brugmans B., Fernandez del Carmen A., Bachem C.W.B., Van Os H., Van Eck H.J., Visser R.G.F., 2002 – A novel method for the construction of genome wide transcriptome maps. Plant Journal 31, 211-222.
• Cappelli K., Porceddu A., Verini -Supplizi A., Capomaccio S., De Marchis F.,Falcinelli M., Gaiti A., Silvestrelli M., 2005 – cDNA AFLP-based techniques for studying transcript profiles in horses. Research in Veterinary Science 79, 105-112.
• Cappelli K., Verini -Supplizi A., Capomaccio S., Silvestrelli M., 2007– Analysis of peripheral blood mononuclear cells gene expression in endurance horses by cDNA-AFLP technique.Research in Veterinary Science 82, 335-343.
• Casas E., Shackelford S.D., Keele J.W., Koohmaraie M., Smith T.P.L., Stone R.T.,2003 - Detection of Quantitative Trait Loci for growth and carcass composition in cattle. Journal of Animal Science 81, 2976-2983.
• Chitale M., Hawkins T., Park C., Kihara D., 2009 – extended similarity group method for automated protein function prediction. Bioinformatics 25, 1739-1745.
• Chomczynski P., Sacchi N., 1987 – Single-step method of RNA isolation by acid guanidinium thiocyanate-phenol-chloroform extraction. Analytic Biochemistry 162, 156-159.
• Dorroch U., Goldammer T., Brunner R.M., Kata S.R., Kühn C., Womack J.E.,Schwerin M., 2001 – Isolation and characterization of hepatic and intestinal expressed sequence tags potentially involved in trait differentiation between cows of different metabolic type. Mammalian Genome 12, 528-537.
• Gotz S., Garcýa-Gomez J.M., Tero J., Williams T.D., Nagaraj S.H., Nueda M.J.,Robles M., Talon M., Dopazo J., Conesa A., 2008 – High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Research 36, 3420-3435.
• Grosz M.D., Mac Neil M.D., 2001– Putative Quantitative Trait Locus Affecting Birth Weight on Bovine Chromosome 2. Journal of Animal Science 79, 68-72.
• Henriquez M.A, Daayf F., 2010 – Identification and cloning of differentially expressed genes involved in the interaction between potato and Phytophthora infestans using a subtractive hybridization and cDNA-AFLP combinational approach. Journal of Integrative Plant Biology 52,453-467.
• HIGH S., TANNER M.J., MACDONALD E.B., ANSTEE D.J., 1989 – Rearrangements of the redcell membrane glycophorin C (sialoglycoprotein beta) gene. A further study of alterations in the glycophorin C gene. Biochemical Journal, 262, 47-54.
• Hu Z., Fritz E.R., Reecy J.M., 2007 – Animal QTLdb – a livestock QTL database tool set for positional QTL information mining and beyond. Nucleic Acids Research 35, D604-D609. doi:10.1093/nar/gkl946
• Hughes L.M., Bao J., Hu Z.L., Honavar V., Reecy J.M., 2008 – Animal trait ontology:The importance and usefulness of a unified trait vocabulary for animal species. Journal of Animal Science 86, 1485-1491.
• Khan S., Situ G., Decker K., Schmidt C.J., GoFigure 2003 – Automated Gene Ontology™Annotation. Bioinformatics, 19, 2484-2485.
• Kneeland J., Li C., Basarab J., Snelling W.M., Benkel B., Murdoch B., Hansen C., Moore S.S., 2004 – Identification and fine mapping of quantitative trait loci for growth traits on bovine chromosomes 2, 6, 14, 19, 21, and 23 within one commercial line of Bos taurus. Journal of Animal Science 82, 3405-3414.
• Liang P., Pardee A.B., 1992 – Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. Science 257, 971-976.
• Lisowski P., Pierzchała M., Gościk J., Pareek C.S., Zwierzchowski L., 2008 –Evaluation of reference genes for studies of gene expression in the bovine liver, kidney, pituitary, and thyroid. Journal of Applied Genetice 49, 367-372.
• Maltecca C., Weigel K.A., Khatib H., Cowan M., Bagnato A., 2009 – Whole-genome scan for quantitative trait loci associated with birth weight, gestation length and passive immune transfer in a Holstein x Jersey crossbred population. Animal Genetics 40, 27-34.
• McClure M.C., Morsci N.S., Schnabel R.D., Kim J.W., Yao P., Rolf M.M., McKay S.D., Gregg S.J., Chapple R.H., Northcutt S.L., Taylor J.F., 2010 – A genome scan for quantitative trait loci influencing carcass, post-natal growth and reproductive traits in commercial Angus cattle. Animal Genetics DOI: 10.1111/j.1365-2052.2010.02063.x
• Needleman P., Turk J., Jakschik B.A., Morrison A.R., Lefkowith J.B., 1986 –Arachidonic acid metabolism. Annnual Review of Biochemistry 55, 69-102.
• Pareek C.S., 2006 – Gene expression profiling in relation to myo-genesis at different stages of muscle cell growth and development in the selected cattle breeds using cDNA-AFLP technology.Proceedings of the 30th International Conference on Animal Genetics, 20-25 August, Porto Seguro,Brazil, 63.
• Pareek C.S., Michno J., 2008 – Identification and analysis of age, tissue and breed specific transcript derived fragments (TDFs) using cDNA-AFLP technique in a panel of four selected cattle breeds. Proceedings of Third International Symposium on Animal Functional Genomics, 7-9 April,EICC, Edinburgh, Scotland; ISAFG-44, 46.
• Rozen S., Skaletsky H.J., 2000 – Primer3 on the WWW for general users and for biologist programmers. In: Krawetz S., Misener S. (eds) Bioinformatics Methods and Protocols: Methods in Molecular Biology. Humana Press, Totowa, NJ, 365-386. (http://frodo.wi.mit.edu/primer3/).
• Savage J.J., Yaden B.C., Kiratipranon P., Rhodes S.J., 2003 – Transcriptional control during mammalian anterior pituitary development. Gene 319, 1-19.
• Sadkowski T., Jank M., Zwierzchowski L., Siadkowska E., Oprządek J.,Motyl T., 2008 – Gene expression profiling in skeletal muscle of Holstein Friesian bulls with single nucleotide polymorphism in myostatin gene 5’flanking region. Journal of Applied Genetics 49, 237-250.
• Sadkowski T., Jank M., Zwierzchowski L., Oprzadek J., Motyl T., 2009 –Comparison of skeletal muscle transcriptional profiles in dairy and beef breeds bulls. Journal of Applied Genetics 50, 109-123.
• Schwerin M., Kuehn C., Wimmers S., Walz C., Goldammer T., 2006 – Trait-associated expressed hepatic and intestine genes in cattle of different metabolic type putative functional candidates for nutrient utilization. Journal of Animal Breeding and Genetics 123, 307-314.
• Tao Y., Sam L., Li J., Friedman C., Lussier Y.A., 2007 – Information theory applied to the sparse gene ontology annotation network to predict novel gene function. Bioinformatics 23, i529-i538.
• Vandeput F., Zabeau M., Maenhaut C., 2005 – Identification of differentially expressed genes in thyrotropin stimulated dog thyroid cells by the cDNA-AFLP technique. Molecular and Cellular Endocrinology 243, 58-65.
• Wang X., Tang C., Zhang G., Li Y., Wang C., Liu B., Qu Z., Zhao J., Han Q., Huang L.,Chen X., Kang Z., 2009 – cDNA-AFLP analysis reveals differential gene expression in compatible interaction of wheat challenged with Puccinia striiformis f. sp. tritici. BMC Genomics 10, 289.
• Wang X., Liu W., Chen X., Tang C., Dong Y., Ma J., Huang X., Wei G., Han Q., Huang L., Kang Z., 2010 – Differential gene expression in incompatible interaction between wheat and stripe rust fungus revealed by cDNA-AFLP and comparison to compatible interaction. BMC Plant Biology 10, 9.

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