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A Brassica exon array for whole-transcript gene expression profiling

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Love, Christopher G., Graham, Neil S. , Ó Lochlainn, Seosamh, Bowen, Helen C., May, Sean T., White, Philip J., Broadley, Martin R., Hammond, John P. and King , Graham J.. (2010) A Brassica exon array for whole-transcript gene expression profiling. PL o S One, Vol.5 (No.9). ISSN 1932-6203

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Official URL: http://dx.doi.org/10.1371/journal.pone.0012812

Abstract

Affymetrix GeneChip® arrays are used widely to study transcriptional changes in response to developmental and environmental stimuli. GeneChip® arrays comprise multiple 25-mer oligonucleotide probes per gene and retain certain advantages over direct sequencing. For plants, there are several public GeneChip® arrays whose probes are localised primarily in 3′ exons. Plant whole-transcript (WT) GeneChip® arrays are not yet publicly available, although WT resolution is needed to study complex crop genomes such as Brassica, which are typified by segmental duplications containing paralogous genes and/or allopolyploidy. Available sequence data were sampled from the Brassica A and C genomes, and 142,997 gene models identified. The assembled gene models were then used to establish a comprehensive public WT exon array for transcriptomics studies. The Affymetrix GeneChip® Brassica Exon 1.0 ST Array is a 5 µM feature size array, containing 2.4 million 25-base oligonucleotide probes representing 135,201 gene models, with 15 probes per gene distributed among exons. Discrimination of the gene models was based on an E-value cut-off of 1E−5, with ≤98% sequence identity. The 135 k Brassica Exon Array was validated by quantifying transcriptome differences between leaf and root tissue from a reference Brassica rapa line (R-o-18), and categorisation by Gene Ontologies (GO) based on gene orthology with Arabidopsis thaliana. Technical validation involved comparison of the exon array with a 60-mer array platform using the same starting RNA samples. The 135 k Brassica Exon Array is a robust platform. All data relating to the array design and probe identities are available in the public domain and are curated within the BrassEnsembl genome viewer at http://www.brassica.info/BrassEnsembl/index.html .

Item Type:	Journal Article
Subjects:	Q Science > QK Botany Q Science > QH Natural history > QH426 Genetics
Divisions:	Faculty of Science > Life Sciences (2010- ) > Warwick HRI (2004-2010)
Library of Congress Subject Headings (LCSH):	Brassica -- Genetics, Brassica -- Genome mapping, Exons (Genetics), Genetic transcription
Journal or Publication Title:	PL o S One
Publisher:	Public Library of Science
ISSN:	1932-6203
Date:	16 September 2010
Volume:	Vol.5
Number:	No.9
Identification Number:	10.1371/journal.pone.0012812
Status:	Peer Reviewed
Access rights to Published version:	Open Access
Funder:	Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Scotland. Environment and Rural Affairs Dept. (SEERAD)
Grant number:	BBG013969 (BBSRC)
References:	1. Willenbrock H, Salomon J, Søkilde R, Barken KB, Hansen TN, et al. (2009) Quantitative miRNA expression analysis: Comparing microarrays with nextgeneration sequencing. RNA 15: 2028–2034. 2. Bradford JR, Hey Y, Yates T, Li Y, Pepper SD, et al. (2010) A comparison of massively parallel nucleotide sequencing with oligonucleotide microarrays for global transcription profiling. BMC Genomics 11: 282. 3. Millenaar FF, Okyere J, May ST, van Zanten M, Voesenek LACJ, et al. (2006) How to decide? Different methods of calculating gene expression from short oligonucleotide array data will give different results. BMC Bioinformatics 7: 137. 4. Edgar R, Domrachev M, Lash AE (2002) Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Research 30: 207–210. 5. Craigon DJ, James N, Okyere J, Higgins J, Jotham J, et al. (2004) NASCArrays: a repository for microarray data generated by NASC’s transcriptomics service. Nucleic Acids Research 32: D575–D577. 6. Parkinson H, Kapushesky M, Kolesnikov N, Rustici G, Shojatalab M, et al. (2009) ArrayExpress update from an archive of functional genomics experiments to the atlas of gene expression. Nucleic Acids Research 37: D868–872. 7. Hammond JP, Bowen HC, White PJ, Mills V, Pyke KA, et al. (2006) A comparison of the Thlaspi caerulescens and T. arvense shoot transcriptomes. New Phytologist 170: 239–260. 8. Hammond JP, Broadley MR, Craigon DJ, Higgins J, Emmerson Z, et al. (2005) Using genomic DNA-based probe-selection to improve the sensitivity of highdensity oligonucleotide arrays when applied to heterologous species. Plant Methods 1: 10. 9. Morinaga S, Nagano AJ, Miyazaki S, Kubo M, Fukuda TDH, et al. (2008) Ecogenomics of cleistogamous and chasmogamous flowering: genome-wide gene expression patterns from cross-species microarray analysis in Cardamine kokaiensis (Brassicaceae). Journal of Ecology 96: 1086–1097. 10. Broadley MR, White PJ, Hammond JP, Graham NS, Bowen HC, et al. (2008) Evidence of neutral transcriptome evolution in plants. New Phytologist 180: 587–593. 11. Kapur K, Xing Y, Ouyang Z, Wong WH (2007) Exon arrays provide accurate assessments of gene expression. Genome Biology 8: R82. 12. Gardina PJ, Clark TA, Shimada B, Staples MK, Yang Q, et al. (2006) Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array. BMC Genomics 7: 325. 13. West MAL, van Leeuwen H, Kozik A, Kiebenstein DJ, Doerge RW, et al. (2006) High-density haplotyping with microarray-based expression and single feature polymorphism markers in Arabidopsis. Genome Research 16: 787–795. 14. Bernardo AN, Bradbury PJ, Ma HX, Hu SW, Bowden RL, et al. (2009) Discovery and mapping of single feature polymorphisms in wheat using Affymetrix arrays. BMC Genomics 10: 251. 15. Bruce M, Hess A, Bai J, Mauleon R, Diaz MG, et al. (2009) Detection of genomic deletions in rice using oligonucleotide microarrays. BMC Genomics 10: 129. 16. Yamada K, Lim J, Dale JM, Chen H, Shinn P, et al. (2003) Empirical analysis of transcriptome activity in the Arabidopsis genome. Science: 302: 842–846. 17. Stolc V, Samanta M P, Tongprasit W, Sethi H, Liang S, Nelson DC, et al. (2005) Identification of transcribed sequences in Arabidopsis thaliana by using highresolution genome tiling arrays. PNAS 102: 4453–4458. 18. Rehrauer H, Aquino C, Gruissem W, Henz SR, Hilson P, et al. (2010) AGRONOMICS1: A new resource for Arabidopsis transcriptome profiling. Plant Physiology 152: 487–499. 19. Parkin IAP, Gulden SM, Sharpe AG, Lukens L, Trick M, et al. (2005) Segmental structure of the Brassica napus genome based on comparative analysis with Arabidopsis thaliana. Genetics 171: 765–781. 20. Kim JS, Chung Y, King GJ, Jin M, Yang TJ, et al. (2006) A sequence-tagged linkage map of Brassica rapa. Genetics 174: 29–39. 21. Schranz ME, Song B-H, Windsor AJ, Mitchell-Olds T (2007) Comparative genomics in the Brassicaceae: a family-wide perspective. Current Opinion in Plant Biology 10: 168–175. 22. Trick M, Cheung F, Drou N, Fraser F, Lobenhofer EK, et al. (2009a) A newlydeveloped community microarray resource for transcriptome profiling in Brassica species enables the confirmation of Brassica-specific expressed sequences. BMC Plant Biology 9: 50. 23. Huang X, Madan A (1999) CAP3: A DNA sequence assembly program. Genome Research 9: 868–877. 24. Trick M, Long Y, Meng J, Bancroft I (2009b) Single nucleotide polymorphism (SNP) discovery in the polyploidy Brassica napus using Solexa transcriptome sequencing. Plant Biotechnology Journal 7: 334–346. 25. Zerbino DR, Birney E (2008) Velvet: algorithms for de novo short read assembly using de Bruijn graphs. Genome Research 18: 821–829. 26. Altschul SF, Madden TL, Scha¨ ffer AA, Zhang J, Zhang Z, et al. (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Research 25: 3389–3402. 27. The UniProt Consortium (2009) The Universal Protein Resource (UniProt) 2009. Nucleic Acids Research 37: D169–174. 28. Korf I (2004) Gene finding in novel genomes. BMC Bioinformatics 5: 59. 29. Haas BJ, Delcher AL, Mount SM, Wortman JR, Smith RK, et al. (2003) Improving the Arabidopsis genome annotation using maximal transcript alignment assemblies. Nucleic Acids Research 31: 5654–5666. 30. Stephenson P, Baker D, Girin T, Perez A, Amoah S, et al. (2010) A rich TILLING resource for studying gene function in Brassica rapa. BMC Plant Biology 10: 62. 31. Swarbreck D, Wilks C, Lamesch P, Berardini TZ, Garcia-Hernandez M, et al. (2008) The Arabidopsis Information Resource (TAIR): gene structure and function annotation. Nucleic Acids Research 36: D1009–1014. 32. Schmid M, Davison TS, Henz SR, Pape UJ, Demar M, et al. (2005) A gene expression map of Arabidopsis thaliana development. Nature Genetics 37: 501–506. 33. Yauk CL, Berndt ML, Williams A, Douglas GR (2004) Comprehensive comparison of six microarray technologies. Nucleic Acid Res 32(15): e124. 34. Allemeersch J, Durinck S, Vanderhaeghen R, Alard P, Maes R, et al. (2005) Benchmarking the CATMA microarray. A novel tool for Arabidopsis transcriptome analysis. Plant Physiology 137: 588–601. 35. Sanchez-Gralliet O, Roswell J, Langdon WB, Stalteri M, Arteaga-Salas JM, et al. (2008) Widespread existence of uncorrelated probe intensities from within the same probeset on Affymetrix GeneChips. Journal of Integrative Bioinformatics 5: 98. 36. Sanchez-Gralliet O, Stalteri M, Roswell J, Upton GJG, Harrison AP (2010) Using surveys of Affymetrix GeneChips to study antisense expression. Journal of Integrative Bioinformatics 7(2). 37. Upton GJG, Sanchez-Gralliet O, Roswell J, Arteaga-Salas JM, Graham NS, et al. (2009) On the causes of outliers in Affymetrix GeneChip data. Briefings in functional genomics and proteomics 8: 199–212.
URI:	http://wrap.warwick.ac.uk/id/eprint/3392