A Brassica Exon Array for Whole-Transcript Gene Expression Profiling
et al. (2010) A Brassica Exon Array for Whole-Transcript Gene Expression Profiling. PLoS
ONE 5(9): e12812. doi:10.1371/journal.pone.0012812
A Brassica Exon Array for Whole-Transcript Gene Expression Profiling
Christopher G. Love 0
Neil S. Graham 0
Seosamh O Lochlainn 0
Helen C. Bowen 0
Sean T. May 0
Philip J. White 0
Martin R. Broadley 0
John P. Hammond 0
Graham J. King 0
Ivan Baxter, United States Department of Agriculture, Agricultural Research Service, United States of America
0 1 Rothamsted Research , Harpenden , United Kingdom , 2 School of Biosciences, University of Nottingham , Sutton Bonington, Loughborough , United Kingdom , 3 Nottingham Arabidopsis Stock Centre (NASC), University of Nottingham , Sutton Bonington, Loughborough , United Kingdom , 4 Warwick HRI , University of Warwick , Wellesbourne, Warwick , United Kingdom , 5 Scottish Crop Research Institute, Invergowrie , Dundee , United Kingdom
Affymetrix GeneChipH arrays are used widely to study transcriptional changes in response to developmental and environmental stimuli. GeneChipH arrays comprise multiple 25-mer oligonucleotide probes per gene and retain certain advantages over direct sequencing. For plants, there are several public GeneChipH arrays whose probes are localised primarily in 39 exons. Plant whole-transcript (WT) GeneChipH 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 GeneChipH Brassica Exon 1.0 ST Array is a 5 mM 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 1E25, 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.
Funding: This work was funded by the UK Biotechnology and Biological Sciences Research Council (BBSRC, http://www.bbsrc.ac.uk/) Industry Partnering Award,
BBG013969 to MRB, JPH, GJK. Rothamsted Research is an institute of the UK BBSRC. Scottish Crop Research Institute is funded by Scottish Government Rural and
Environment Research and Analysis Directorate. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the
Competing Interests: The authors have declared that no competing interests exist.
. These authors contributed equally to this work.
Microarrays are used widely in many organisms to study how
the transcriptome varies during development, or in response to
environmental perturbations or biotic challenges. Whilst direct
sequencing of cDNAs may ultimately supplant microarray-based
platforms for transcriptome analyses, microarrays retain
advantages over next generation sequencing (NGS), including, (1) a
wider dynamic range [1,2], (2) the availability of robust
normalisation and analysis techniques , (3) large public
reference datasets , and (4) lower costs of performing a
biologically replicated experiment; the advent of multiplex array
platforms is likely to reduce these costs further.
The Affymetrix GeneChipH platform (Affymetrix, Santa Clara,
CA, USA) is a widely used microarray technology in which each
gene on the microarray is represented by multiple 25-mer
oligonucleotide probes. GeneChipH arrays have been developed
for a number of plants, including Arabidopsis thaliana, barley,
Brachypodium, Citrus, cotton, grape, maize, Medicago, poplar, rice,
soybean, sugarcane, tobacco, tomato and wheat (http://www.
affymetrix.com/). The use of GeneChipH arrays for heterologous,
or cross-species, transcriptome studies has extended the range of
species for which transcriptomics experiments have been reported
For transcriptome analyses, oligonucleotide probes on
GeneChipH arrays have often been targeted to 39 gene sequences. This
is because sequence data are typically derived from EST sequence
collections with a 39 bias, and the 39 end of genes are generally
more variable, which provides greater specificity. In addition, for
many years hybridisation probes have conventionally been
labelled from the 39 end. However, 39-biased arrays do not allow
exon level analysis of gene transcripts and their splice variants. In
contrast, whole transcript (WT) and tiling arrays allow for exon
level interrogation of transcripts and splice variants. The latest
GeneChipH arrays have probes for every exon in the genome,
which results in greater specificity and a more accurate measure of
transcript abundance . Exon GeneChipH arrays can also be
used to detect alternate splicing , sequence polymorphisms
[13,14], and for deletion mapping . Whilst high probe-density
tiling array platforms have been developed for A. thaliana ,
to date no WT exon GeneChipH array has been publicly available
The aim of this study was to develop a WT exon GeneChipH
array for Brassica. Brassica has a complex genome structure typical
of many crop plants. A series of genome duplication events leading
to the diploid species has resulted in most genes being present in
multiple paralogous and homeologous copies, which is
compounded in the allopolyploid species. The Brassicaceae are a model
system for studying plant genome evolution . The genus
Brassica includes the closest crop relatives of Arabidopsis thaliana,
with relatively recent hybridisation events between representatives
of the diploid A- genome of B. rapa (vegetable and oil crops) and
Cgenome of B. oleracea (vegetable crops) giving rise to the widely
grown amphidiploid B. napus (AC-genome; canola/oilseed rape/
colza, rutabaga/swede). Extensive genomic resources for Brassica
species have already been assembled and are available through the
ongoing Multi-national Brassica Genome Project (MBGP; www.
brassica.info). In addition to .1.9 m Brassica sequences in
Genbank, the B. rapa genome sequence is being released in
2010, alongside other reference genome and re-sequencing
Efforts to study genome evolution and to underpin crop
improvement will therefore benefit from a robust WT exon GeneChipH
array for transcriptomics.
Materials and Methods
Selection of unigenes
The pipeline leading to the final array design included an initial
collation of Brassica gene model and transcript data available in
December 2009. The source data used are summarised in Table 1.
The starting point was a pre-existing Unigene set containing
94,558 sequences defined at the J. Craig Venter Institute (JCVI) in
August 2007, which had been used to develop a 95 k oligo array
based on 60-mers (95 k Brassica 60-mer array). Since this set
was composed of assemblies of ESTs from different Brassica
species, a detailed breakdown of unique genes by species is not
possible. The dataset was processed through a number of filtering
steps to avoid redundancy, and where possible to orientate
transcripts in consistent 59 to 39 direction (Fig. 1). Additional
transcriptome sequence datasets were added to the JCVI unigene
set where they were deemed to be unrepresented. Datasets
included 1,085 contigs formed from 2,122 assembled EST
sequences downloaded from GenBank in May 2009. These reads
were vector trimmed using CrossMatch (http://www.phrap.org/
phredphrap/phrap.html) and sequences with a length of .100 bp
were assembled using CAP3 (94% identity). A set of 7,434 B.
oleracea (A12DHd) ESTs not present within GenBank at that date
were also vector trimmed and assembled with parameters
previously stated providing an additional 2,253 unigenes.
Approximately 40 million Solexa (Illumina Inc., San Diego, CA,
USA) sequenced ESTs were also included from the digital
transcriptome of B. napus lines TapidorDH and Ningyou7 ,
which was assembled using Velvet  with minimum contig
length of 100 bp, coverage cut-off of five and k-mer value of 23,
producing 29,956 contigs.
Transcript redundancy within the combined datasets was
eliminated based on empirically determined criteria, using BLAST
. Thus unigenes were eliminated where they aligned with
.98% identity over .75% of the query sequence, with an Expect
(E-) value ,1E25. This reduction in sequence redundancy resulted
in a unigene dataset of 105,481 (Table 1).
The orientation of the combined unigene set was also
established using defined criteria. Firstly, 76,687 unigenes were
orientated by alignment using BLAST to Uniref100 , with
Evalue cut-off 1E25. Those unigenes not aligning significantly to
Uniref100 were aligned to Brassica genomic scaffolds and A.
thaliana genomic sequence using the TimeLogicH
GeneDetectiveTM algorithm (Active Motif Inc., Carlsbad, CA, USA), which
orientated a further 36,170 unigenes. An additional 4,124
unigenes were orientated using available signal information from
another Affymetrix GeneChipH array (courtesy of Biogemma,
Paris, France) based on the 95 k JCVI unigene set. This enabled us
to determine where the transcript generated a signal through
hybridisation with Brassica cDNA, and so was in the correct
orientation. In addition, the longest open reading frame was used
to orientate a further 5,183, and the presence of a poly-A (Poly-T)
tail was used to orientate 908 unigenes. The remaining 9,712
unigenes could not be orientated with confidence.
Predicted genes were also included in the array design, derived
from 974 publicly available B. rapa Chiifu-401 KBr BAC
sequences (BrGSP) using SNAP  and PASA  programs,
with 15,817 and 17,558 genes identified respectively. A total of
4,913 unigenes were removed due to redundancy between the
combined unigene set and predicted genes by the same criteria as
previously, with preference for retention of the gene prediction
over a redundant unigene alignment. An additional 2,073 gene
models were included from preliminary annotation of B. rapa
JCVI unigene set not represented by gene predictions
PASA gene predictions from B. rapa KBr BACs
SNAP gene predictions from B. rapa KBr BACs
Brassica napus N/T digital transcriptome (Velvet) assemblies
Arabidopsis thaliana gene models
B. oleracea A12DHd EST assemblies (cap3 94%id)
B. rapa gene models from sequence scaffolds
ESTs not represented in JCVI unigene set extracted from Genbank on 14/05/09 (assembled with cap3 94% id)
Number of gene models
Chiifu-401 sequence scaffolds generated from high throughput
sequencing. This sequencing project is led by Xiaowu Wang
(Institute of Vegetables and Flowers, Chinese Academy of
Agricultural Sciences, Beijing) who kindly provided
pre-publication comparative analysis to identify gene models where these did
not correspond to genes identified above. A subset of candidate A.
thaliana gene models (4,517) that were not otherwise represented by
Brassica orthologs were also included in the design. Three Brassica
and 176 A. thaliana controls were also included within the design.
The final unigene set available totalled 142,997 (Table 1).
The selected Affymetrix GeneChipH format for the Brassica
Exon 1.0 ST Array (135 k Brassica exon array) had capacity for
2.44 million 25 bp oligonucleotide probes of 5 mm (49-7875
format). The total unigene dataset was further filtered using the
Affymetrix probe selection pipeline. Standard Affymetrix A.
thaliana control and reporter sequences were added (89 genes).
Probe sets were selected based on 15 probes per gene. In order to
maximise the ability of the Affymetrix exon array to resolve
paralogous genes which may differ at the exon level, and to detect
alternative splicing, it was necessary to determine, where possible,
the exon boundaries for each identified unigene or gene
prediction. Since not all the unigenes had defined exon
boundaries, this was achieved using the exon predictions derived
from the TimeLogicH GeneDetectiveTM algorithm (Active Motif
Inc.), where significant alignments (E-value,1E215) existed
between A. thaliana genomic sequence and B. rapa genomic
scaffolds. Where exon boundary information could not be
obtained, probes were evenly distributed over the length of the
In total, 1,043 unigenes were excluded as they did not pass
quality filtering due to (1) the unigene being too small to design
any probes of high enough quality, (2) potential probe
crosshybridisation, or (3) too low complexity. For 6,733 unigenes, probe
sets could not be designed in a way that would distinguish them
from other probe sets, and so these are not represented. In total
there were 338,195 probe sets marked for tiling, containing a total
of 2,416,447 probes that represented 135,201 unigenes.
Plant growth and tissue preparation
Plants of the homozygous B. rapa line R-o-18  were grown
for 23 d in 13 cm diameter pots containing 1 L of an unmodified
high-nutrient, peat-based substrate (Levington M3 Pot and
Bedding Compost, Scotts Professional, UK; pH 5.35.7, N:P:K;
280:160:350 g m23). Plants were grown under glasshouse
conditions in May 2009 (16 hr photoperiod, 22.3uC and 13.3uC
mean day and night temperatures respectively, irrigated with
mains water). Two full leaves, including petioles and midribs, from
three replicate plants, were harvested and frozen in liquid
nitrogen. Root tissue samples were obtained from plants grown
on agar plates. Surface sterilised seed were sown in large square
(20620 cm) tissue culture plates (QTray X6024, Genetix Ltd.,
New Milton, UK) containing 250 mL 0.8% agar (A1296,
SigmaAldrich Company Ltd., Dorset, UK) and 16 MS salts (M5524,
Sigma), adjusted to pH 5.6 with NaOH, under the conditions
described previously . Ten days after sowing, root tissue from
38 plants was pooled and snap-frozen at 270uC for each
independent biological replicate.
RNA preparation and hybrisation
RNA was extracted from tissue samples using a modified
TRIzol extraction method . Extracted total RNA was then
purified using the RNA Cleanup protocol for RNeasy columns
with on-column DNase digestion to remove residual genomic
DNA (Qiagen, Crawley, West Sussex, UK). Samples of total RNA
were checked for integrity and quality using an Agilent
Bioanalyser (Agilent Technologies, Santa Clara CA, USA). RNA
samples were then split to allow the same RNA sample to be
labelled and hybridised to the 135 K Brassica Exon array and the
Agilent 95 k Brassica 60-mer array . For the 135 K Brassica
Exon array, RNA samples were labelled and hybridised according
the manufacturers instructions (Affymetrix, Santa Clara, CA,
USA) at Nottingham Arabidopsis Stock Centre (NASC; http://
affymetrix.arabidopsis.info). Briefly, 500 ng of total RNA from
each sample was labelled using the Ambion WT expression kit
(Ambion Inc, Austin, TX, USA). The end labelling, hybridisation,
washing and scanning were performed according to the
GeneChipH WT terminal labelling and hybridisation user manual
(www.affymetrix.com), and scanned using an Affymetrix 3000 7G
scanner. Following scanning, non-scaled RNA signal intensity files
(.cel) were generated using the Command Console software
(Affymetrix). Raw data are MIAME compliant as detailed on the
MGED Society website http://www.mged.org/Workgroups/
MIAME/miame.html and have been submitted to Gene
Expression Omnibus (GEO; http://www.ncbi.nlm.nih.gov/projects/
geo/; accessionGSE23141) and to NASC (http://arabidopsis.
info/StockInfo?NASC_id = N9903). For the 95 k Brassica 60-mer
array, RNA samples were labelled with the QuickAmp Labelling
kit (Agilent Technologies) and hybridised to the array for 17 hours
at 65uC at 10 rpm. The 95 k Brassica 60-mer arrays were washed,
and then scanned on an Agilent G2565CA scanner, according to
the manufacturers instructions, and data files generated using
Agilent Feature Extraction Software (version 10.7.3.1, Agilent
Technologies). All raw data have been submitted to Gene
Expression Omnibus (GEO;
http://www.ncbi.nlm.nih.gov/projects/geo/; accession GSE23141.
All data were analysed using GeneSpring GX (version 11.0.2,
Agilent Technologies). For the 135 k Brassica Exon arrays, six
RNA. cel files (three root and three leaf files) were normalized
using the RMA pre-processor in GeneSpring GX. For the 95 k
Brassica 60-mer array data files were imported into GeneSpring
and a quantile normalization was applied. Normalized signal
values for individual probes/probe-sets were standardized to the
median signal value for the probe/probe-set within each array
platform. All data were pre-filtered to remove genes whose
normalized fold change was between 0.77 and 1.3 i.e. not
changing. Genes with differential transcript abundance between
leaf and root tissue were identified from the pre-filtered genes
using a one-way ANOVA (GeneSpring) with a
BenjaminiHochberg corrected p-value ,0.01 and a fold-change cut-off .2.
To enrich annotation of the probes and probe-sets, A. thaliana
homologues were derived from the highest scoring alignment to A.
thaliana coding sequences (TAIR v9) using the TimeLogicH
Tera-BlastNTM algorithm (Active Motif Inc.) with E-value cut-off
at 1E25. Arabidopsis gene descriptions and Gene Ontology (GO)
annotation were obtained from TAIR (www.arabidopsis.org;
TAIR genome v9, 11/06/2010). Identification and enrichment
of GO terms within significantly differentially regulated sets of
genes were obtained using the GO Browser function in
GeneSpring GX with a Benjamini-Hochberg corrected p-value ,0.05.
For alternate splicing analysis, the data were loaded into
Genespring GX using the Affymetrix Exon splicing option, with
the exon technology provided by Agilent Technologies. The data
were normalised using the ExonRMA16 pre-processor and
normalised signal values for individual probe-sets were
standardised to the median value for the probe-set. Potential alternately
spliced transcripts were identified by filtering on the splicing index
(. = 5) and visualising them using the splicing visualization tool in
Genespring GX. The splicing index for a probe-set is defined as
the difference between gene normalized intensities for two chosen
Analysis the of 39 bias in control probes was performed in Excel.
The RMA-normalised signal values for 34 control probes
(AFFXBioB-5, AFFX-BioB-3, AFFX-BioC-5, AFFX-BioB-3,
AFFXBioDn-5, AFFX-BioDn-3, AFFX-CreX-5, AFFX-CreX-3,
AFFX-DapX-5, AFFX-DapX-3, AFFX-LysX-5, AFFX-LysX-3,
AFFX-PheX-5, AFFX-PheX-3, AFFX-ThrX-5, AFFX-ThrX-3,
AFFX-TrpnX-5, AFFX-Trpn-3, AFFX-r2-Ec-bioB-5,
AFFX-r2Ec-bioB-3, AFFX-r2-Ec-bioC-5, AFFX-r2-Ec-bioC-3,
AFFX-r2Ec-bioD-5, AFFX-r2-Ec-bioD-3, AFFX-r2-P1-cre-5,
AFFX-r2P1-cre-3, AFFX-r2-Bs-dap-5, AFFX-r2-Bs-dap-3,
AFFX-r2-Bslys-5, AFFX-r2-Bs-lys-3, AFFX-r2-Bs-phe-5, AFFX-r2-Bs-phe-3,
AFFX-r2-Bs-thr-5, AFFX-r2-Bs-thr-3) were exported from
Genespring for leaf and root from the Brassica exon and Arabidopsis
experiments. The 39 to 59 ratio was calculated for each pair of
probes for each gene and a one-tailed t-test was performed on the
The density plots were generated using the density function in
the freely available statistical package R (version 2.9.2), using
mean RMA-normalised signal values from leaf and root samples
hybridised to the Affymetrix Brassica Exon 1.0 St array and the
95 k Brassica 60-mer array.
Results and Discussion
The probe selection process for the Affymetrix GeneChipH
Brassica Exon 1.0 ST Array (135 k Brassica Exon array; Fig. 1)
marked 338,195 probe sets for tiling, containing a total of
2,416,447 probes that represented 135,201 unigenes (Tables 1 and
2). All probe and design data are publicly available from
Affymetrix. The distribution of mean probe-set signals from the
135 k Brassica Exon array has large dynamic range (Fig. 2) and
detected 11,078 significantly differently expressed transcripts
(p,0.01) between leaf and root samples. Overall, there was a
good correlation in transcript abundance (r2.0.5) between
platforms, based on shared homology to A. thaliana gene models
Comparison of the 39 bias in the hybridisation of control probes
between the Brassica exon array and an Arabidopsis experiment
using the Affymetrix ATH1 array (leaf, 7 days old, ATGE_5 AC,
GEO accession GSE5630 and root, 7 days old, ATGE_3AC
GEO accession GSE5631), showed that the bias was
significantly greater in the ATH1 hybridisations (one-tailed
TTest, P = 0.022, n = 34). This demonstrates that the labelling
protocol used for the exon array produces a more consistent signal
across the whole transcript as compared to the 39 bias seen with
older labelling protocols.
Genes up and down regulated in leaves compared with roots
were found to be highly similar between the two Brassica array
platforms. Based on comparison with the Arabidopsis datasets
described above, they were also were broadly similar with a
published leaf vs root transcriptome comparison obtained using A.
thaliana. Similarity was defined by A. thaliana GO categories
common to the different platforms.
Figure 2. Dynamic range of probe set signals. Density plots of (a, b, e, f) mean probe-set signals from the 135 k exon array, and (c, d, g, h) mean
probe signal values from the 95 k 60-mer array, for (a, b, c, d) leaf and (e, f, g, h) root tissue of Brassica rapa R-o-18 (n = 3).
Figure 3. Comparison of transcript abundance on different array platforms. Relationship between mean normalised probe-set signals from
the 135 k Brassica Exon array and mean normalised probe signal values from the 95 k Brassica 60-mer array, for a) leaf and b) root tissue of Brassica
rapa R-o-18 (n = 3). Relationships between probe-sets from the 135 k Brassica Exon array and probes from the 95 k Brassica 60-mer array are based on
shared Arabidopsis thaliana gene models.
An earlier study comparing six different platforms for the mouse
transcriptome suggest a good correlation (Pearson
productmoment correlation = 0.7) between Affymetrix and Agilent
platforms . A similar result was obtained between these
platforms for Arabidopsis . Studies based on extensive survey
of many arrays indicate that not all probes within an exon
correlate and some probes may appear as outliers. This may be
due to a wide range of factors, including multiple polyadenylation
sites, antisense expression, the sequence of the probes, position of
the probe on the array . Thus the identification and
analysis of such outlier probes may be useful indicators for deteting
novel biological properties.
Among genes where transcript abundance, detected by the
135 k Brassica Exon array, was greater in leaves compared to
roots 141 GO categories were significantly (Benjamini and
Hochberg (BH) corrected p,0.05) over-represented (Fig. 4a).
Among these, 88 of the GO categories were in common with GO
categories overrepresented on the 95 k Brassica 60-mer array
platform (out of a total of 126 GO categories identified as
significantly (BH corrected p,0.05) over-represented), and 73 GO
categories were in common with GO categories overrepresented
among genes whose transcript abundance was greater in leaves
compared to roots in an experiment on A. thaliana (out of a total of
272 GO categories identified as significantly (BH corrected
p,0.05) over-represented). Similarly, the 135 k Brassica Exon
array detected 59 GO categories overrepresented (BH corrected
p,0.05) among genes whose transcript abundance was less in
leaves compared to roots (Fig. 4b). Among these, 46 of the GO
categories were in common with GO categories overrepresented
on the 95 k Brassica 60-mer array platform (out of a total of 126
GO categories identified as significantly (BH corrected p,0.05)
over-represented), and 30 GO categories were in common with
Figure 4. Gene Ontology categories of tissue-specific transcripts. Gene Ontology (GO) categories of overrepresented (p,0.05) genes whose
transcript abundance was greater (a) or less (b) in leaves compared with roots of Brassica rapa R-o-18. GO categories are based on putative gene
orthology between Brassica and Arabidopsis thaliana (TAIR v9). The three portions of each Venn figure represent the Affymetrix GeneChipH Brassica
Exon 1.0 ST Array (135 k Brassica Exon array, n = 3), the Agilent 95 k Brassica 60-mer array (n = 3), and A. thaliana data from the AtGen Express data set
for leaves (leaf, 7 days old, ATGE_5 AC, GEO accession GSE5630) and roots (root, 7 days old, ATGE_3AC, GEO accession GSE5631; Schmid
et al., 2005).
GO categories overrepresented among genes whose transcript
abundance was less in leaves compared to roots in an experiment
on A. thaliana (out of a total of 76 GO categories identified as
significantly (BH corrected p,0.05) over-represented). As
expected, GO categories identified as being significantly
over-represented among genes whose transcript abundance was greater in leaves
compared with roots were dominated by those associated with
photosynthesis and chloroplasts (Table S1). For GO categories
identified as being significantly over-represented among genes
whose transcript abundance was less in leaves compared with
roots, many were associated with responses to inorganic ions and
abiotic stresses, consistent with roots role in the acquisition of
water and mineral nutrients (Table S2).
The design of the array should enable analysis of data at the
exon level as well as the whole transcript level, in order to identify
alternatively spliced transcripts. The 135 k Brassica Exon array
has an average of 15 probes per gene, so there are a variable
number of probes per exon, which may reduce the resolution of
this analysis for some genes. However, preliminary analysis at the
exon level indicates that the signal from each exon within a
transcript is consistent, and that potentially alternately spliced
transcripts can be identified (Fig. 5) using analysis by splicing
index. Interestingly the Arabidopsis best BLAST hit of these four
transcripts are also potentially alternatively spliced (as shown by
the alternative splicing visualisation tool at the Plant DGB
database; http://plantdbg.org/ASIP). These potentially
alternatively spliced transcripts need to be confirmed experimentally to
demonstrate the effectiveness of this array for alternative splicing
In conclusion, we describe the development of the Affymetrix
GeneChipH Brassica Exon 1.0 ST Array. This is a 5 mM 49-7875
format array, containing 2.4 million 25-base oligonucleotide
probes representing 135,201 gene models, with 15 probes per
gene distributed among exons. The exon array is robust based on
preliminary analyses of (1) dynamic range, (2) low CVs between
biological replicates, (3) transcriptome differences between leaf and
root tissue of a reference homozygous Brassica rapa line (R-o-18),
according to overrepresented GO categories and technical
comparison with an existing commercial array platform, (4) exon
level data show that the majority of exons with a transcript have
similar signal intensities and that potential alternatively spliced
transcripts can be identified. Further analyses and validation will
be facilitated in due course as additional datasets are released into
the public domain, sensu A. thaliana. The 135 k unigene set is
accessible as a track within the public BrassEnsembl genome
browser at http://www.brassica.info/BrassEnsembl/index.html,
and also as a Blast dataset within BrassEnsembl. In addition, the
exon sequences, probeset and best hit alignments to Arabidopsis
are available from http://www.brassica.info/resource/trancriptomics.
php. It is anticipated that the Affymetrix GeneChipH Brassica Exon
1.0 ST Array will become a valuable tool for transcriptomics and
mapping in several important crop species and will contribute to
efforts to decipher genome evolution and adaptation within the
Conceived and designed the experiments: CGL NSG SM PJW MB JPH
GJK. Performed the experiments: NSG SL HCB SM JPH. Analyzed the
data: PJW MB JPH GJK. Contributed reagents/materials/analysis tools:
CGL GJK. Wrote the paper: CGL NSG SL HCB SM PJW MB JPH GJK.
Brassica bioinformatics and annotation, Unigene design: CGL.
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