Dataset Information

A Brassica exon array for whole-transcript gene expression profiling.

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.

SUBMITTER: Love CG

PROVIDER: S-EPMC2940909 | biostudies-literature | 2010 Sep

REPOSITORIES: biostudies-literature

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A Brassica exon array for whole-transcript gene expression profiling.

Love Christopher G CG Graham Neil S NS O Lochlainn Seosamh S Bowen Helen C HC May Sean T ST White Philip J PJ Broadley Martin R MR Hammond John P JP King Graham J GJ

PloS one 20100916 9

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 gen ...[more]

PMID: 20862292

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Project description:BackgroundAlternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST) that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression.ResultsWe analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported) transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays. Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic predictions of alternative splicing in cancer.ConclusionDifferential expression of high confidence transcripts correlated extremely well with known cancer genes and pathways, suggesting that the more speculative transcripts, largely based solely on computational prediction and mostly with no previous annotation, might be novel targets in colon cancer. Five of the identified splicing events affect mediators of cytoskeletal organization (ACTN1, VCL, CALD1, CTTN, TPM1), two affect extracellular matrix proteins (FN1, COL6A3) and another participates in integrin signaling (SLC3A2). Altogether they form a pattern of colon-cancer specific alterations that may particularly impact cell motility.

Project description:BACKGROUND: The emergence of isoform-sensitive microarrays has helped fuel in-depth studies of the human transcriptome. The Affymetrix GeneChip Human Exon 1.0 ST Array (Exon Array) has been previously shown to be effective in profiling gene expression at the isoform level. More recently, the Affymetrix GeneChip Human Gene 1.0 ST Array (Gene Array) has been released for measuring gene expression and interestingly contains a large subset of probes from the Exon Array. Here, we explore the potential of using Gene Array probes to assess expression variation at the sub-transcript level. Utilizing datasets of the high quality Microarray Quality Control (MAQC) RNA samples previously assayed on the Exon Array and Gene Array, we compare the expression measurements of the two platforms to determine the performance of the Gene Array in detecting isoform variations. RESULTS: Overall, we show that the Gene Array is comparable to the Exon Array in making gene expression calls. Moreover, to examine expression of different isoforms, we modify the Gene Array probe set definition file to enable summarization of probe intensity values at the exon level and show that the expression profiles between the two platforms are also highly correlated. Next, expression calls of previously known differentially spliced genes were compared and also show concordant results. Splicing index analysis, representing estimates of exon inclusion levels, shows a lower but good correlation between platforms. As the Gene Array contains a significant subset of probes from the Exon Array, we note that, in comparison, the Gene Array overlaps with fewer but still a high proportion of splicing events annotated in the Known Alt Events UCSC track, with abundant coverage of cassette exons. We discuss the ability of the Gene Array to detect alternative splicing and isoform variation and address its limitations. CONCLUSION: The Gene Array is an effective expression profiling tool at gene and exon expression level, the latter made possible by probe set annotation modifications. We demonstrate that the Gene Array is capable of detecting alternative splicing and isoform variation. As expected, in comparison to the Exon Array, it is limited by reduced gene content coverage and is not able to detect as wide a range of alternative splicing events. However, for the events that can be monitored by both platforms, we estimate that the selectivity and sensitivity levels are comparable. We hope our findings will shed light on the potential extension of the Gene Array to detect alternative splicing. It should be particularly suitable for researchers primarily interested in gene expression analysis, but who may be willing to look for splicing and isoform differences within their dataset. However, we do not suggest it to be an equivalent substitute to the more comprehensive Exon Array.

Project description:BackgroundThe upgrading of rapeseed cultivars has resulted in a substantial improvement in yield and quality in China over the past 30 years. With the selective pressure against fatty acid composition and oil content, high erucic acid- and low oil-content cultivars have been replaced by low erucic acid- and high oil-content cultivars. The high erucic acid cultivar Zhongyou 821 and its descendent, low erucic acid cultivar Zhongshuang 9, are representatives of two generations of the most outstanding Chinese rapeseed cultivars (B. napus) developed the past 2 decades. This paper compares the transcriptional profiles of Zhongshuang 9 and Zhongyou 821 for 32 genes that are principally involved in lipid biosynthesis during seed development in order to elucidate how the transcriptional profiles of these genes responded to quality improvement over the past 20 years.ResultsComparison of the cultivar Zhongyou 821 with its descendent, Zhongshuang 9, shows that the transcriptional levels of seven of the 32 genes were upregulated by 30% to 109%, including FAD3, ACCase, FAE1, GKTP, Caleosin, GAPDH, and PEPC. Of the 32 genes, 10 (KAS3, beta-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, alpha-CT and SUC1) were downregulated by at least 20% and most by 50%. The Napin gene alone accounted for over 75% of total transcription from all 32 genes assessed in both cultivars. Most of the genes showed significant correlation with fatty acid accumulation, but the correlation in ZS9 was significantly different from that in ZY821. Higher KCR2 activity is associated with higher C16:0, C18:0, and C18:2 in both cultivars, lower C22:1 and total fatty acid content in ZY821, and lower 18:1 in ZS9.ConclusionThis paper illustrates the response of the transcription levels of 32 genes to breeding in developing rapeseed seeds. Both cultivars showed similar transcription profiles, with the Napin gene predominantly transcribed. Selective pressure for zero erucic acid, low glucosinolate, high oleic acid and high oil content, as well as high yield, resulted in higher FAD3, ACCase, FAE1, GKTP, Caleosin, GAPDH, and PEPC expression levels and lower KAS3, beta-CT, BcRK6, P450, FatA, Oleosin, FAD6, FatB, alpha-CT and SUC1 expression levels. It also resulted in altered relationships between these genes during storage accumulation in seed development.

Project description:BackgroundExcessive accumulation of lipids in the adipose tissue is a major problem in the present-day broiler industry. However, few studies have analyzed the expression of adipose tissue genes that are involved in pathways and mechanisms leading to adiposity in chickens. Gene expression profiling of chicken adipose tissue could provide key information about the ontogenesis of fatness and clarify the molecular mechanisms underlying obesity. In this study, Chicken Genome Arrays were used to construct an adipose tissue gene expression profile of 7-week-old broilers, and to screen adipose tissue genes that are differentially expressed in lean and fat lines divergently selected over eight generations for high and low abdominal fat weight.ResultsThe gene expression profiles detected 13,234-16,858 probe sets in chicken adipose tissue at 7 weeks, and genes involved in lipid metabolism and immunity such as fatty acid binding protein (FABP), thyroid hormone-responsive protein (Spot14), lipoprotein lipase(LPL), insulin-like growth factor binding protein 7(IGFBP7) and major histocompatibility complex (MHC), were highly expressed. In contrast, some genes related to lipogenesis, such as leptin receptor, sterol regulatory element binding proteins1 (SREBP1), apolipoprotein B(ApoB) and insulin-like growth factor 2(IGF2), were not detected. Moreover, 230 genes that were differentially expressed between the two lines were screened out; these were mainly involved in lipid metabolism, signal transduction, energy metabolism, tumorigenesis and immunity. Subsequently, real-time RT-PCR was performed to validate fifteen differentially expressed genes screened out by the microarray approach and high consistency was observed between the two methods.ConclusionOur results establish the groundwork for further studies of the basic genetic control of growth and development of chicken adipose tissue, and will be beneficial in clarifying the molecular mechanism of obesity in chickens.

Dataset Information

A Brassica exon array for whole-transcript gene expression profiling.

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A Brassica exon array for whole-transcript gene expression profiling.

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