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Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study.

Cao W, Epstein C, Liu H, DeLoughery C, Ge N, Lin J, Diao R, Cao H, Long F, Zhang X, Chen Y, Wright PS, Busch S, Wenck M, Wong K, Saltzman AG, Tang Z, Liu L, Zilberstein A - BMC Genomics (2004)

Bottom Line: About 2000 transcripts were identified for each library from 8000 successful sequences.This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results.This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays, especially in identifying novel genes and transcripts of low abundance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Aventis Pharmaceuticals, Bridgewater, NJ 08887, USA. wuxiong.cao@aventis.com

ABSTRACT

Background: Several high throughput technologies have been employed to identify differentially regulated genes that may be molecular targets for drug discovery. Here we compared the sets of differentially regulated genes discovered using two experimental approaches: a subtracted suppressive hybridization (SSH) cDNA library methodology and Affymetrix GeneChip technology. In this "case study" we explored the transcriptional pattern changes during the in vitro differentiation of human monocytes to myeloid dendritic cells (DC), and evaluated the potential for novel gene discovery using the SSH methodology.

Results: The same RNA samples isolated from peripheral blood monocyte precursors and immature DC (iDC) were used for GeneChip microarray probing and SSH cDNA library construction. 10,000 clones from each of the two-way SSH libraries (iDC-monocytes and monocytes-iDC) were picked for sequencing. About 2000 transcripts were identified for each library from 8000 successful sequences. Only 70% to 75% of these transcripts were represented on the U95 series GeneChip microarrays, implying that 25% to 30% of these transcripts might not have been identified in a study based only on GeneChip microarrays. In addition, about 10% of these transcripts appeared to be "novel", although these have not yet been closely examined. Among the transcripts that are also represented on the chips, about a third were concordantly discovered as differentially regulated between iDC and monocytes by GeneChip microarray transcript profiling. The remaining two thirds were either not inferred as differentially regulated from GeneChip microarray data, or were called differentially regulated but in the opposite direction. This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results.

Conclusions: This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays, especially in identifying novel genes and transcripts of low abundance.

Show MeSH
Comparing the SSH data with GeneChip microarray data using subtracted samples as targets. The GeneChip microarrays were screened with cRNA targets made from the same subtracted cDNA used for SSH. (a) Number of transcripts in the H56 SSH library identified as "present" or "absent" on the GeneChip microarrays. (b) The copy number of each transcript in the SSH library plotted against its detectability on the GeneChip microarrays. Each dot represents a distinct transcript identified in the H56 SSH cDNA library. The transcripts that can be detected by the GeneChip microarrays were given "present" calls, while the transcripts that cannot be detected by the GeneChip microarrays were given "absent" calls.
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Figure 3: Comparing the SSH data with GeneChip microarray data using subtracted samples as targets. The GeneChip microarrays were screened with cRNA targets made from the same subtracted cDNA used for SSH. (a) Number of transcripts in the H56 SSH library identified as "present" or "absent" on the GeneChip microarrays. (b) The copy number of each transcript in the SSH library plotted against its detectability on the GeneChip microarrays. Each dot represents a distinct transcript identified in the H56 SSH cDNA library. The transcripts that can be detected by the GeneChip microarrays were given "present" calls, while the transcripts that cannot be detected by the GeneChip microarrays were given "absent" calls.

Mentions: To find out how many of the SSH detected genes with probes on the GeneChip microarrays can actually be detected by the Affymetrix technology, we used the subtracted cDNA to synthesize labeled complimentary RNA (cRNA) targets for the GeneChip microarrays. A T7 promoter in the SSH PCR primers allows us to perform in vitro transcription with the SSH cDNA. Since the SSH library is derived from cDNA primed from the 3' end, we assume that any transcripts detected by sequencing the library are potentially represented by 3' fragments, whether or not the sequenced fragment is localized to the 3' end of the transcript. This is critical because Affymetrix probes are designed to interact with the 3' regions of the targeted transcripts. When the GeneChip microarrays were screened with targets made from the SSH cDNA, 571 out of the 1409 transcripts were given "absent" calls, suggesting that no positive signals can be detected on the GeneChip microarrays for these transcripts, even though the presence of these 571 transcripts had been confirmed by sequencing (Figure 3a). Next we asked the question whether the transcripts undetectable by the GeneChip microarrays were limited only to transcripts of low abundance. Although the abundance of genes had been normalized in the SSH, the frequency of each gene in the SSH cDNA library can still be used as a relative indicator for its abundance because the same SSH cDNA samples were used to label the cRNA targets for the GeneChip microarrays. Here we used the number of sequenced cDNA clones belonging to each transcript as a measurement of the copy number of this transcript in the SSH cDNA library. As shown in Figure 3b, the transcripts scored as "absent" using GeneChip microarrays include genes with high and low copy numbers. The distribution pattern of the copy numbers of this group was very similar to the group of transcripts scored as "present" by the GeneChip microarrays. This suggests that there are some inefficiencies in the GeneChip microarray technology that are independent of transcript abundance.


Comparing gene discovery from Affymetrix GeneChip microarrays and Clontech PCR-select cDNA subtraction: a case study.

Cao W, Epstein C, Liu H, DeLoughery C, Ge N, Lin J, Diao R, Cao H, Long F, Zhang X, Chen Y, Wright PS, Busch S, Wenck M, Wong K, Saltzman AG, Tang Z, Liu L, Zilberstein A - BMC Genomics (2004)

Comparing the SSH data with GeneChip microarray data using subtracted samples as targets. The GeneChip microarrays were screened with cRNA targets made from the same subtracted cDNA used for SSH. (a) Number of transcripts in the H56 SSH library identified as "present" or "absent" on the GeneChip microarrays. (b) The copy number of each transcript in the SSH library plotted against its detectability on the GeneChip microarrays. Each dot represents a distinct transcript identified in the H56 SSH cDNA library. The transcripts that can be detected by the GeneChip microarrays were given "present" calls, while the transcripts that cannot be detected by the GeneChip microarrays were given "absent" calls.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC415544&req=5

Figure 3: Comparing the SSH data with GeneChip microarray data using subtracted samples as targets. The GeneChip microarrays were screened with cRNA targets made from the same subtracted cDNA used for SSH. (a) Number of transcripts in the H56 SSH library identified as "present" or "absent" on the GeneChip microarrays. (b) The copy number of each transcript in the SSH library plotted against its detectability on the GeneChip microarrays. Each dot represents a distinct transcript identified in the H56 SSH cDNA library. The transcripts that can be detected by the GeneChip microarrays were given "present" calls, while the transcripts that cannot be detected by the GeneChip microarrays were given "absent" calls.
Mentions: To find out how many of the SSH detected genes with probes on the GeneChip microarrays can actually be detected by the Affymetrix technology, we used the subtracted cDNA to synthesize labeled complimentary RNA (cRNA) targets for the GeneChip microarrays. A T7 promoter in the SSH PCR primers allows us to perform in vitro transcription with the SSH cDNA. Since the SSH library is derived from cDNA primed from the 3' end, we assume that any transcripts detected by sequencing the library are potentially represented by 3' fragments, whether or not the sequenced fragment is localized to the 3' end of the transcript. This is critical because Affymetrix probes are designed to interact with the 3' regions of the targeted transcripts. When the GeneChip microarrays were screened with targets made from the SSH cDNA, 571 out of the 1409 transcripts were given "absent" calls, suggesting that no positive signals can be detected on the GeneChip microarrays for these transcripts, even though the presence of these 571 transcripts had been confirmed by sequencing (Figure 3a). Next we asked the question whether the transcripts undetectable by the GeneChip microarrays were limited only to transcripts of low abundance. Although the abundance of genes had been normalized in the SSH, the frequency of each gene in the SSH cDNA library can still be used as a relative indicator for its abundance because the same SSH cDNA samples were used to label the cRNA targets for the GeneChip microarrays. Here we used the number of sequenced cDNA clones belonging to each transcript as a measurement of the copy number of this transcript in the SSH cDNA library. As shown in Figure 3b, the transcripts scored as "absent" using GeneChip microarrays include genes with high and low copy numbers. The distribution pattern of the copy numbers of this group was very similar to the group of transcripts scored as "present" by the GeneChip microarrays. This suggests that there are some inefficiencies in the GeneChip microarray technology that are independent of transcript abundance.

Bottom Line: About 2000 transcripts were identified for each library from 8000 successful sequences.This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results.This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays, especially in identifying novel genes and transcripts of low abundance.

View Article: PubMed Central - HTML - PubMed

Affiliation: Aventis Pharmaceuticals, Bridgewater, NJ 08887, USA. wuxiong.cao@aventis.com

ABSTRACT

Background: Several high throughput technologies have been employed to identify differentially regulated genes that may be molecular targets for drug discovery. Here we compared the sets of differentially regulated genes discovered using two experimental approaches: a subtracted suppressive hybridization (SSH) cDNA library methodology and Affymetrix GeneChip technology. In this "case study" we explored the transcriptional pattern changes during the in vitro differentiation of human monocytes to myeloid dendritic cells (DC), and evaluated the potential for novel gene discovery using the SSH methodology.

Results: The same RNA samples isolated from peripheral blood monocyte precursors and immature DC (iDC) were used for GeneChip microarray probing and SSH cDNA library construction. 10,000 clones from each of the two-way SSH libraries (iDC-monocytes and monocytes-iDC) were picked for sequencing. About 2000 transcripts were identified for each library from 8000 successful sequences. Only 70% to 75% of these transcripts were represented on the U95 series GeneChip microarrays, implying that 25% to 30% of these transcripts might not have been identified in a study based only on GeneChip microarrays. In addition, about 10% of these transcripts appeared to be "novel", although these have not yet been closely examined. Among the transcripts that are also represented on the chips, about a third were concordantly discovered as differentially regulated between iDC and monocytes by GeneChip microarray transcript profiling. The remaining two thirds were either not inferred as differentially regulated from GeneChip microarray data, or were called differentially regulated but in the opposite direction. This underscores the importance both of generating reciprocal pairs of SSH libraries, and of real-time RT-PCR confirmation of the results.

Conclusions: This study suggests that SSH could be used as an alternative and complementary transcript profiling tool to GeneChip microarrays, especially in identifying novel genes and transcripts of low abundance.

Show MeSH