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Food, fibre and pharmaceuticals from animals
RESEARCH ARTICLE

Gene expression profiling of ovine skin and wool follicle development using a combined ovine–bovine skin cDNA microarray

B. J. Norris A B , N. I. Bower A , W. J. M. Smith A , G. R. Cam A and A. Reverter A
+ Author Affiliations
- Author Affiliations

A Co-operative Research Centre for the Australian Sheep Industry and CSIRO Livestock Industries, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, Qld 4067, Australia.

B Corresponding author. Email: belinda.norris@csiro.au

Australian Journal of Experimental Agriculture 45(8) 867-877 https://doi.org/10.1071/EA05050
Submitted: 14 February 2005  Accepted: 3 June 2005   Published: 26 August 2005

Abstract

Low fibre diameter and high fleece weight are important determinants of the economic value of the Merino fleece. The combination of these traits is found in Merino sheep with high follicle densities resulting from a high secondary to primary follicle ratio. Morphological stages in the development of primary and secondary follicles of fetal sheep skin have been well described. We have used gene expression profiling of fetal skin to identify genes that may be important in controlling these follicle developmental processes. A combined ovine (2.3 K) and bovine (6.14 K) cDNA microarray of 2 fetal and 1 adult stage skin tissues was constructed to compare gene expression levels between fetal day 82, day 105, day 120 and adult sheep skin developmental stages. The transcript profile resulted in 238 differentially expressed array elements relative to the adult expression, which represented 132 unique genes. These clustered into 50 up- and 82 down-regulated genes and distinct gene ontologies including structural constituents, phosphate transport, signal transduction and organogenesis. Northern blot analysis of 2 selected genes, S100A7LI and TAGLN, validated the microarray results. This list of genes contains candidates of interest for further investigation into the molecular control of wool follicle development.


Acknowledgments

The authors thank Dr Rob Moore for the printing of microarrays; Dr Yong Hong Wang for bovine skin ESTs and Sean McWilliam for bioinformatics support.


References


Adelson DL, Cam GR, DeSilva U, Franklin IR (2004) Gene expression in sheep skin and wool (hair) Genomics 83, 95–105.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Akaike H (1969) Fitting autoregressive models for prediction. Annals of the Institute of Statistical Mathematics 21, 243–247. open url image1

Akiyama M, Matsuo I, Shimizu H (2002) Formation of cornified cell envelope in human hair follicle development The British Journal of Dermatology 146, 968–976.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Akiyama M, Smith LT, Shimizu H (2000) Expression of transglutaminase activity in developing human epidermis The British Journal of Dermatology 142, 223–225.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. Journal of Molecular Biology 215, 403–410.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Ashburner M, Ball CA, Blake JA, Botstein D, Butler H , et al. (2000) Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nature Genetics 25, 25–29.
PubMed |
open url image1

Bawden CS, Powell BC, Walker SK, Rogers GE (1998) Expression of a wool intermediate filament keratin transgene in sheep fibre alters structure. Transgenic Research 7, 273–287.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J, Rapp BA, Wheeler DL (2002) GenBank. Nucleic Acids Research 30, 17–20.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Craig BA, Black MA, Doerge RW (2003) Gene expression data: the technology and statistical analyis. Journal of Agricultural Biological & Environmental Statistics 8, 1–28.
Crossref | GoogleScholarGoogle Scholar | open url image1

Crawford AM (2001) A review of QTL experiments in sheep. In ‘Proceedings of the XIVth congress of the association for the advancement of animal breeding and genetics’. (Ed. J Neville) pp. 33–38. (AGBU, The University of New England: Armidale, NSW)

Cui X, Churchill GA (2003) Statistical tests for differential expression in cDNA microarray experiments. Genome Biology 4, 210. Available online at: http://genomebiology.com/2003/4/4/210

Eckert RL, Broome A, Ruse M, Robinson N, Ryan D, Lee K (2004) S100 proteins in the epidermis. The Journal of Investigative Dermatology 123, 23–33.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Fraley C, Raftery AE (1998) How many clusters? Which clustering method? Answers via model-based cluster analysis. The Computer Journal 41, 578–588.
Crossref | GoogleScholarGoogle Scholar | open url image1

Fuchs E, Merrill BJ, Jamora C, Dasgupta R (2001) At the roots of a never-ending cycle. Developmental Cell 1, 13–25.
Crossref | PubMed |
open url image1

Fuchs E, Raghavan S (2002) Getting under the skin of epidermal morphogenesis. Nature Reviews. Genetics 3, 199–209.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Groeneveld E, García-Cortés LA (1998) VCE 4.0, a (co)variance components package for frequentists and Bayesians. In ‘Proceedings of the 6th world congress on genetics applied to livestock production’. pp. 455–458. (Armidale, NSW, Australia)

Hardy MH, Lynne AG (1956) The pre-natal development of wool follicles in Merino sheep. Australian Journal of Biological Sciences 9, 423–441. open url image1

Kerr MK, Martin M, Churchill GA (2000) Analysis of variance for gene expression microarray data. Journal of Computational Biology 7, 819–837.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Lehnert SA, Wang YH, Byrne KA (2004) Development and application of a bovine cDNA microarray for expression profiling of muscle and adipose tissue. Australian Journal of Experimental Agriculture 44, 1127–1133.
Crossref | GoogleScholarGoogle Scholar | open url image1

McLachlan GJ (1987) On bootstrapping the likelihood ratio test statistic for the number of components in a normal mixture. Applied Statistics 36, 318–324. open url image1

McLachlan GJ, Bean RW, Ben-Tovim Jones L, Zhu JX (2005) Using mixture models to detect differentially expressed genes. Australian Journal of Experimental Agriculture 45, 859–866. open url image1

McLachlan GJ, Bean RW, Peel D (2002) A mixture model-based approach to the clustering of microarray expression data. Bioinformatics (Oxford, England) 18, 413–422.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Millar SE (2002) Molecular mechanisms regulating hair follicle development. The Journal of Investigative Dermatology 118, 216–225.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Pan W, Lin J, Le CT (2002a) Model-based cluster analysis of microarray gene expression data. Genome Biology 3, 91–98. open url image1

Pan W, Lin J, Le CT (2002b) How many replicates of array are required to detect gene expression changes in microarray experiments? A mixture model approach. Genome Biology 3, 221–210. open url image1

Paus R, Nickoloff BJ, Ito T (2005) A hairy privilege. Trends in Immunology 26, 32–40.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Purvis IW, Franklin IR (2004) Major genes and QTL influencing wool production and quality: a review. Genetics, Selection, Evolution. 17(Supplement 1), S97–107. open url image1

Rekaya R (2002) Bayesian mixture models with unknown number of components: application to power calculation in microarray experiments. In ‘Proceedings of the 7th world congress on genetics applied to livestock production’. CD-ROM Communication No. 16-12. (Montpellier, France)

Reverter A, McWilliam SM, Barris W, Dalrymple BP (2005) A rapid method for computationally inferring transcriptome coverage and microarray sensitivity. Bioinformatics (Oxford, England) 21, 80–89.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Reverter A, Wang YH, Byrne KA, Tan SH, Harper GS, Lehnert SA (2004) Joint analysis of multiple cDNA microarray studies via multivariate mixed models applied to genetic improvement of beef cattle. Journal of Animal Science 82, 3430–3439.
PubMed |
open url image1

Rogers GE (2004) Hair follicle differentiation and regulation. The International Journal of Developmental Biology 48, 163–170.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Sambrook J, Fritsch EF, Maniatis T (1989) ‘Molecular cloning: a laboratory manual.’ 2nd edn. (Cold Spring Harbor Laboratory Press: Plainview, NY)

Schwartz G (1978) Estimating the dimensions of a model. The Annals of Statistics 6, 461–464. open url image1

Stenn KS, Paus R (2001) Controls of hair follicle cycling. Physiological Reviews 81, 449–494.
PubMed |
open url image1

Tran PH, Peiffer DA, Shin Y, Meek LM, Brody JP, Cho KWY (2002) Microarray optimisations: increasing spot accuracy and automated identification of true microarray signals. Nucleic Acids Research 30, e54.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Verrecchia F, Chu ML, Mauviel A (2001) Identification of novel TGF-β/Smad gene targets in dermal fibroblasts using a combined cDNA microarray/promoter transactivation approach. The Journal of Biological Chemistry 276, 17058–17062.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Wang YH, McWilliam SM, Barendse W, Kata SR, Womack JE, Moore SS, Lehnert SA (2001) Mapping of 12 bovine ribosomal protein genes using a bovine radiation hybrid panel. Animal Genetics 32, 269–273.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Watt FM (2001) Stem cell fate and patterning in mammalian epidermis. Current Opinion in Genetics & Development 11, 410–417.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Wolf R, Mirmohammadsadegh A, Walz M, Lysa B, Tartler U, Remus R, Hengge U, Michel G, Ruzicka T (2003) Molecular cloning and characterisation of alternatively spliced mRNA isoforms from psoriatic skin encoding a novel member of the S100 family. The FASEB Journal express article: 10.1096/fj.03-0148fje.

Wolfinger RD, Gibson G, Wolfinger ED, Bennett L, Hamadeh H, Bushel P, Afshari C, Paules RS (2001) Assessing gene significance from cDNA microarray expression data via mixed models. Journal of Computational Biology 8, 625–637.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1

Yeung KY, Fraley C, Murua A, Raftery AE, Ruzzo WL (2001) Model-based clustering and data transformations for gene expression data. Bioinformatics (Oxford, England) 17, 977–987.
Crossref | GoogleScholarGoogle Scholar | PubMed | open url image1