An atlas of gene expression from seed to seed through barley development
- 802 Downloads
Assaying relative and absolute levels of gene expression in a diverse series of tissues is a central step in the process of characterizing gene function and a necessary component of almost all publications describing individual genes or gene family members. However, throughout the literature, such studies lack consistency in genotype, tissues analyzed, and growth conditions applied, and, as a result, the body of information that is currently assembled is fragmented and difficult to compare between different studies. The development of a comprehensive platform for assaying gene expression that is available to the entire research community provides a major opportunity to assess whole biological systems in a single experiment. It also integrates detailed knowledge and information on individual genes into a unified framework that provides both context and resource to explore their contributions in a broader biological system. We have established a data set that describes the expression of 21,439 barley genes in 15 tissues sampled throughout the development of the barley cv. Morex grown under highly controlled conditions. Rather than attempting to address a specific biological question, our experiment was designed to provide a reference gene expression data set for barley researchers; a gene expression atlas and a comparative data set for those investigating genes or regulatory networks in other plant species. In this paper we describe the tissues sampled and their transcriptomes, and provide summary information on genes that are either specifically expressed in certain tissues or show correlated expression patterns across all 15 tissue samples. Using specific examples and an online tutorial, we describe how the data set can be interrogated for patterns and levels of barley gene expression and how the resulting information can be used to generate and/or test specific biological hypotheses.
KeywordsBarley Development Gene expression
We thank Alvis Brazma, Dan Nettleton, Tom Freeman, and John Quakenbush for valuable conceptual input on the art of microarray data analysis; Julie Dickerson and Lishuang Shen for help with submission to the BarleyBase; Philippe Rocca-Serra for help with submission in ArrayExpress; and Doreen Ware and Pankaj Jaiswal for assistance with plant ontologies. Sarah Jackson and Yusuke Komishi from GeneSpring are acknowledged for helpful advice and excellent technical support during the data analysis and presentation. Funding for this experiment was provided by Scottish Executive Environment and Rural Affairs Department (Grant No. IGD12397 to RW); BBSRC (Grant No. ISIS 1107 to RW and GJM); USDA Initiative for Future Agriculture and Food Systems (IFAFS) 01-52100-11346 to AK, RPW, TJC, and GJM; USDA-NRI 02-35300-12619 to RPW; USDA-NRI 02-35300-12548 to TJC; USDA-CSREES North American Barley Genome Project funds to RPW, GJM, AK, TJC, and PH; McKnight Landgrant Professorship (University of Minnesota) for sabbatical leave to GJM; BMBF Plant Genome Program ‘GABI’ (Grants No. 0312282 and 0312271) to AG; and TEKES (National Technology Agency of Finland) and Boreal Plant Breeding to AS.
- Brazma A, Hingamp P, Quackenbush J, Sherlock G, Spellman P, Stoeckert C, Aach J, Ansorge W, Ball CA, Causton HC, Gaasterland T, Glenisson P, Holstege FC, Kim IF, Markowitz V, Matese JC, Parkinson H, Robinson A, Sarkans U, Schulze-Kremer S, Stewart J, Taylor R, Vilo J, Vingron M (2001) Minimum information about a microarray experiment (MIAME)—toward standards for microarray data. Nat Genet 29:365–371CrossRefPubMedGoogle Scholar
- Chen W, Provart NJ, Glazebrook J, Katagiri F, Chang HS, Eulgem T, Mauch F, Luan S, Zou G, Whitham SA, Budworth PR, Tao Y, Xie Z, Chen X, Lam S, Kreps JA, Harper JF, Si-Ammour A, Mauch-Mani B, Heinlein M, Kobayashi K, Hohn T, Dangl JL, Wang X, Zhu T (2002) Expression profile matrix of Arabidopsis transcription factor genes suggests their putative functions in response to environmental stresses. Plant Cell 14:559–574CrossRefPubMedGoogle Scholar
- Dudoit S, Fridlyand J (2003) Rules classification in microarray experiments. In: Speed T (ed) Statistical analysis of gene expression. Chapman & Hall/CRC, pp 93–158Google Scholar
- Parkinson H, Sarkans U, Shojatalab M, Abeygunawardena N, Contrino S, Coulson R, Farne A, Lara GG, Holloway E, Kapushesky M, Lilja P, Mukherjee G, Oezcimen A, Rayner T, Rocca-Serra P, Sharma A, Sansone S, Brazma A (2005) ArrayExpress—a public repository for microarray gene expression data at the EBI. Nucleic Acids Res 33:D553–D555 (Database issue)CrossRefPubMedGoogle Scholar