A pathway-specific microarray analysis highlights the complex and co-ordinated transcriptional networks of the developing grain of field-grown barley

Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, University of Aarhus, Research Centre Flakkebjerg, DK-4200 Slagelse, Denmark.
Journal of Experimental Botany (Impact Factor: 5.53). 12/2008; 60(1):153-67. DOI: 10.1093/jxb/ern270
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The aim of the study was to describe the molecular and biochemical interactions associated with amino acid biosynthesis and storage protein accumulation in the developing grains of field-grown barley. Our strategy was to analyse the transcription of genes associated with the biosynthesis of storage products during the development of field-grown barley grains using a grain-specific microarray assembled in our laboratory. To identify co-regulated genes, a distance matrix was constructed which enabled the identification of three clusters corresponding to early, middle, and late grain development. The gene expression pattern associated with the clusters was investigated using pathway-specific analysis with specific reference to the temporal expression levels of a range of genes involved mainly in the photosynthesis process, amino acid and storage protein metabolism. It is concluded that the grain-specific microarray is a reliable and cost-effective tool for monitoring temporal changes in the transcriptome of the major metabolic pathways in the barley grain. Moreover, it was sensitive enough to monitor differences in the gene expression profiles of different homologues from the storage protein families. The study described here should provide a strong complement to existing knowledge assisting further understanding of grain development and thereby provide a foundation for plant breeding towards storage proteins with improved nutritional quality.

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Available from: Carsten Friis, Oct 05, 2015
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    • "We have used similar approaches to study gene expression and regulation during seed development in other crop species, flax and canola (Venglat et al., 2011, 2013) (Fig. 1). Global gene expression studies of either whole seeds or different seed components have also been documented for legumes such as Medicago , soybean and scarlet runner bean (Le et al., 2007), canola (Huang et al., 2009) and monocot crop species such as rice (Xue et al., 2012), wheat (Gillies et al., 2012), maize (Sekhon et al., 2013, 2011) and barley (Hansen et al., 2009). This in-depth view of the gene expression patterns during seed development in diverse crop species has been possible because of the rapid advances made in whole genome sequencing and the development and application of a wide range of genomics tools (Edwards et al., 2013; Flavell, 2010; Morrell et al., 2012). "
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    ABSTRACT: Seed development represents an important phase in the life cycle of flowering plants including the majority of the crop plants. During this phase, developmental and metabolic programs are coordinated to produce the seed that contains the germline information and storage reserves. Although seed developmental patterns vary significantly between the monocots and dicots, they share several conserved developmental programs. The embryo is the major component of the seed in dicots whereas the endosperm is predominant in monocot seeds. The formation of the dormant seed that protects the embryo and provides nutrition during germination is a key characteristic adaptive feature in the evolution of the angiosperms and a determining factor of yield in crop plants. From a crop perspective, the metabolites and especially the storage products deposited in the seed defines the value of the seed. Despite progress in fundamental understanding of seed development, the global genetic and metabolic programs involved in the making of the seed and their implications to genetic improvement of the seed is yet to be fully exploited in crop plants. So, the major goal of several recent studies is to develop comprehensive systems-level insights into molecular and biochemical programs associated with gene expression, protein and metabolite profiles during seed development in model and crop plants. These integrated systems approaches and studies are producing foundational and comprehensive datasets. In this review, we will present an overview of advances in the developmental, genetic and genomic studies of seed biology and their implications to improve seed characteristics in crop plants. More information:
    Biocatalysis and Agricultural Biotechnology 01/2013; 3(1). DOI:10.1016/j.bcab.2013.11.009
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    • "One approach gaining in popularity for discovering genes underpinning variation in complex traits such as NUE or responses to available N is via transcriptome analysis. This has been applied to analyze specific steps such as senescence (Gregersen and Holm, 2007; Howarth et al., 2008) or grain filling (Hansen et al., 2009; Wan et al., 2008) in cereals, and in roots and shoots in relation to nitrate supply for model plants such as tomato (Wang et al., 2001) or Arabidopsis (Wang et al., 2003). Large numbers of responsive genes have been identified, however, specific attribution of identified genes to determining traits of interest has not been generally successful; more sophisticated genotypeeenvironmentetrait correlations will be required to narrow down candidate genes. "
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    ABSTRACT: All crops require nitrogen (N) for the production of a photosynthetically active canopy, whose functionality will strongly influence yield. Cereal crops also require N for storage proteins in the grain, an important quality attribute. Optimal efficiency is achieved by the controlled remobilization of canopy-N to the developing grain during crop maturation. Whilst N will always be required for crop production, targeting efficient capture and use will optimise consumption of this valuable macronutrient. Efficient management of N through agronomic practice and use of appropriate germplasm are essential for sustainability of agricultural production. Both the economic demands of agriculture and the need to avoid negative environmental impacts of N-pollutants, such as nitrate in water courses or release of N-containing green-house gases, are important drivers to seek the most efficient use of this critical agronomic input. New cultivars optimised for traits relating to N-use efficiency rather than yield alone will be required. Targets for genetic improvement involve maximising capture, partitioning and remobilization in the canopy and to the grain, and yield per se. Whilst there is existing genetic pool amongst modern cultivars, substantial improvements may require exploitation of a wider germplasm pool, utilising land races and ancestral germplasm.
    Journal of Cereal Science 01/2013; 59(3). DOI:10.1016/j.jcs.2013.12.001 · 2.09 Impact Factor
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    • "Hansen et al. [16], using microarray derived data, reported variation in the temporal expression of genes coding for barley storage protein family members within the cultivar Barke. The data sets resulting from microarray were validated by using qRT-PCR and the primers were chosen to recognise most members of the same gene family [16]. "
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    ABSTRACT: Background Cereal storage proteins represent one of the most important sources of protein for food and feed and they are coded by multigene families. The expression of the storage protein genes exhibits a temporal fluctuation but also a response to environmental stimuli. Analysis of temporal gene expression combined with genetic variation in large multigene families with high homology among the alleles is very challenging. Results We designed a rapid qRT-PCR system with the aim of characterising the variation in the expression of hordein genes families. All the known D-, C-, B-, and γ-hordein sequences coding full length open reading frames were collected from commonly available databases. Phylogenetic analysis was performed and the members of the different hordein families were classified into subfamilies. Primer sets were designed to discriminate the gene expression level of whole families, subfamilies or individual members. The specificity of the primer sets was validated before successfully applying them to a cDNA population derived from developing grains of field grown Hordeum vulgare cv. Barke. The results quantify the number of moles of transcript contributed to a particular gene family and its subgroups. More over the results indicate the genotypic specific gene expression. Conclusions Quantitative RT-PCR with SYBR Green labelling can be a useful technique to follow gene expression levels of large gene families with highly homologues members. We showed variation in the temporal expression of genes coding for barley storage proteins. The results imply that our rapid qRT-PCR system was sensitive enough to identify the presence of alleles and their expression profiles. It can be used to check the temporal fluctuations in hordein expressions or to find differences in their response to environmental stimuli. The method could be extended for cultivar recognition as some of the sequences from the database originated from cv. Golden Promise were not expressed in the studied barley cultivar Barke although showed primer specificity with their cloned DNA sequences.
    BMC Plant Biology 10/2012; 12(1):184. DOI:10.1186/1471-2229-12-184 · 3.81 Impact Factor
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