Sequencing of expressed genes from several plant species has revealed a relatively higher level of conservation in amino acid sequence among distantly related taxonomic groups, despite the tremendous phenotypic and developmental diversity. This diversity appears to be primarily created by polymorphisms that contribute to quantitative gene expression variation, rather than protein structure modification or creation of novel transcriptional units. Genetic variation in gene expression regulation may be the basis for the diversity of plant species. Therefore, a genome-wide assessment of the genetic control of gene expression regulation could aid in explaining the morphological and developmental diversity of eukaryotes, including the higher plants. Efforts to identify the molecular basis of quantitative traits are being enhanced by genomic methodologies such as transcriptomics, metabolomics, and proteomics. The most mature of these approaches is the use of microarrays to measure global transcript levels in mapping populations and map expression quantative trait loci (eQTLs) 4.
Genetical genomics is the approach for use of gene expression data in QTL analysis. The basic idea of eQTL is to monitor the expression levels for all genes in breeding experiments, and then find association between the quantitative phenotype and defined patterns of gene expression. In other words, by developing microarray chips on mapping populations, it is now possible to map QTL involved in regulation of gene expression. QTL mapping is combined with expression profiling of individual genes in a segregating (mapping) population. Because eQTL analysis uses segregation population, it is possible to determine whether expression of a target gene is regulated in cis (mapping of the differentially regulated candidate gene within the eQTL) or trans (the candidate gene is located outside the corresponding eQTL, or in a transcription factor of the gene) (1,2).
Genetical genomics is a powerful tool for identifying candidate genes for traits of economic value in plants5. It is a strategy which relies on identifying cis-regulated eQTL that co-localize with a trait QTL. Instead of relying on the detection of anonymous markers correlated with a trait, such as in traditional QTL analysis, this approach identifies actual genes. Although this novel field is still developing, understanding the genetic basis of molecular phenotypes such as gene expression is expected to shed light on the intermediate processes that connect genotype to cellular and organismal traits and represents a critical step towards true systems biology.3
References:
1. Holloway, B. and Bailin, Li., 2010, Expression QTLs: applications for crop improvement. Mol. Breeding, 26: 381-391
2. Jansen, R. C. and Nap, J. P., 2001, Genetical genomics: the added value from segregation. Trends. Genet, 17:388–391
3. Jun, Li. and Margit, B., 2005, Genetical genomics: combining genetics with gene expression analysis. Hum. Mol. Genet., 14:163-169
4. Kirst, M and Qibin Yu., 2006, Genetical genomics: successes and prospects in plants. Genetics, 169: 2295-2303
5. Schadt, E. E., Monks, S. A., Drake, T. A., Lusis, A. J. and Che, N., 2003, Genetics of gene expression surveyed in maize, mouse and man. Nature 422: 297-302
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