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Background Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera Description The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid

Background Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. Description The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx webcite), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, Background Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. Description The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx webcite), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, ph

BACKGROUND: Vitis vinifera berry development is characterised by an initial phase where the fruit is small, hard and acidic, followed by a lag phase known as veraison. In the final phase, berries become larger, softer and sweeter and accumulate an array of organoleptic compounds. Since the physiological and biochemical makeup of grape berries at harvest has a profound impact on the characteristics of wine, there is great interest in characterising the molecular and biophysical changes that occur from flowering through veraison and ripening, including the coordination and temporal regulation of metabolic gene pathways. Advances in deep-sequencing technologies, combined with the availability of increasingly accurate V. vinifera genomic and transcriptomic data, have enabled us to carry out RNA-transcript expression analysis on a global scale at key points during berry development RESULTS: A total of 162 million 100-base pair reads were generated from pooled Vitis vinifera (cv. Shiraz) berries sampled at 3-weeks post-anthesis, 10- and 11-weeks post-anthesis (corresponding to early and late veraison) and at 17-weeks post-anthesis (harvest). Mapping reads from each developmental stage (36-45 million) onto the NCBI RefSeq transcriptome of 23,720 V. vinifera mRNAs revealed that at least 75% of these transcripts were detected in each sample. RNA-Seq analysis uncovered 4,185 transcripts that were significantly upregulated at a single developmental stage, including 161 transcription factors. Clustering transcripts according to distinct patterns of transcription revealed coordination in metabolic pathways such as organic acid, stilbene and terpenoid metabolism. From the phenylpropanoid/stilbene biosynthetic pathway at least 46 transcripts were upregulated in ripe berries when compared to veraison and immature berries, and 12 terpene synthases were predominantly detected only in a single sample. Quantitative real-time PCR was used to validate the expression pattern of 12 differe

Mucin-type O-glycosylation is an important post-translational modification that confers a variety of biological properties and functions to proteins. This post-translational modification has a particularly complex and differentially regulated biosynthesis rendering prediction and control of where O-glycans are attached to proteins, and which structures are formed, difficult. Because plants are devoid of GalNAc-type O-glycosylation, we have assessed requirements for establishing human GalNAc O-glycosylation de novo in plants with the aim of developing cell systems with custom-designed O-glycosylation capacity. Transient expression of a Pseudomonas aeruginosa Glc(NAc) C4-epimerase and a human polypeptide GalNAc-transferase in leaves of Nicotiana benthamiana resulted in GalNAc O-glycosylation of co-expressed human O-glycoprotein substrates. A chimeric YFP construct containing a 3.5 tandem repeat sequence of MUC1 was glycosylated with up to three and five GalNAc residues when co-expressed with GalNAc-T2 and a combination of GalNAc-T2 and GalNAc-T4, respectively, as determined by mass spectrometry. O-Glycosylation was furthermore demonstrated on a tandem repeat of MUC16 and interferon a2b. In plants, prolines in certain classes of proteins are hydroxylated and further substituted with plant-specific O-glycosylation; unsubstituted hydroxyprolines were identified in our MUC1 construct. In summary, this study demonstrates that mammalian type O-glycosylation can be established in plants and that plants may serve as a host cell for production of recombinant O-glycoproteins with custom-designed O-glycosylation. The observed hydroxyproline modifications, however, call for additional future engineering efforts.