Transcript-specific expression profiles derived from sequence-based analysis of standard microarrays.
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vor 15 Jahren
Alternative mRNA processing mechanisms lead to multiple transcripts
(i.e. splice isoforms) of a given gene which may have distinct
biological functions. Microarrays like Affymetrix GeneChips measure
mRNA expression of genes using sets of nucleotide probes. Until
recently probe sets were not designed for transcript specificity.
Nevertheless, the re-analysis of established microarray data using
newly defined transcript-specific probe sets may provide
information about expression levels of specific transcripts. In the
present study alignment of probe sequences of the Affymetrix
microarray HG-U133A with Ensembl transcript sequences was performed
to define transcript-specific probe sets. Out of a total of 247,965
perfect match probes, 95,008 were designated “transcript-specific”,
i.e. showing complete sequence alignment, no cross-hybridization,
and transcript-, not only gene-specificity. These probes were
grouped into 7,941 transcript-specific probe sets and 15,619
gene-specific probe sets, respectively. The former were used to
differentiate 445 alternative transcripts of 215 genes. For
selected transcripts, predicted by this analysis to be
differentially expressed in the human kidney, confirmatory
real-time RT-PCR experiments were performed. First, the expression
of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and
P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was
determined by the transcript-specific array analysis and confirmed
by real-time RT-PCR. Secondly, disease-specific differential
expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and
Q5VYS0_HUMAN) was computed from the available array data sets and
confirmed by transcript-specific real-time RT-PCR.
Transcript-specific analysis of microarray experiments can be
employed to study gene-regulation on the transcript level using
conventional microarray data. In this study, predictions based on
sufficient probe set size and fold-change are confirmed by
independent means.
(i.e. splice isoforms) of a given gene which may have distinct
biological functions. Microarrays like Affymetrix GeneChips measure
mRNA expression of genes using sets of nucleotide probes. Until
recently probe sets were not designed for transcript specificity.
Nevertheless, the re-analysis of established microarray data using
newly defined transcript-specific probe sets may provide
information about expression levels of specific transcripts. In the
present study alignment of probe sequences of the Affymetrix
microarray HG-U133A with Ensembl transcript sequences was performed
to define transcript-specific probe sets. Out of a total of 247,965
perfect match probes, 95,008 were designated “transcript-specific”,
i.e. showing complete sequence alignment, no cross-hybridization,
and transcript-, not only gene-specificity. These probes were
grouped into 7,941 transcript-specific probe sets and 15,619
gene-specific probe sets, respectively. The former were used to
differentiate 445 alternative transcripts of 215 genes. For
selected transcripts, predicted by this analysis to be
differentially expressed in the human kidney, confirmatory
real-time RT-PCR experiments were performed. First, the expression
of two specific transcripts of the genes PPM1A (PP2CA_HUMAN and
P35813) and PLG (PLMN_HUMAN and Q5TEH5) in human kidneys was
determined by the transcript-specific array analysis and confirmed
by real-time RT-PCR. Secondly, disease-specific differential
expression of single transcripts of PLG and ABCA1 (ABCA1_HUMAN and
Q5VYS0_HUMAN) was computed from the available array data sets and
confirmed by transcript-specific real-time RT-PCR.
Transcript-specific analysis of microarray experiments can be
employed to study gene-regulation on the transcript level using
conventional microarray data. In this study, predictions based on
sufficient probe set size and fold-change are confirmed by
independent means.
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