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Impact of RNA degradation on gene expression profiling.

Opitz L, Salinas-Riester G, Grade M, Jung K, Jo P, Emons G, Ghadimi BM, Beissbarth T, Gaedcke J - BMC Med Genomics (2010)

Bottom Line: Only a relatively small number of probes (275 out of 41,000) show a significant effect due to degradation.A much higher biological variance between patients is observed compared to the effect that is imposed by degradation of RNA.These results are limited to the Agilent 44 k microarray platform and should be carefully interpreted when transferring to other settings.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department Medical Statistics, University Medicine Göttingen, Humboldtallee 32, 37073 Göttingen, Germany.

ABSTRACT

Background: Gene expression profiling is a highly sensitive technique which is used for profiling tumor samples for medical prognosis. RNA quality and degradation influence the analysis results of gene expression profiles. The impact of this influence on the profiles and its medical impact is not fully understood. As patient samples are very valuable for clinical studies, it is necessary to establish criteria for the RNA quality to be able to use these samples in later analysis.

Methods: To investigate the effects of RNA integrity on gene expression profiling, whole genome expression arrays were used. We used tumor biopsies from patients diagnosed with locally advanced rectal cancer. To simulate degradation, the isolated total RNA of all patients was subjected to heat-induced degradation in a time-dependent manner. Expression profiling was then performed and data were analyzed bioinformatically to assess the differences.

Results: The differences introduced by RNA degradation were largely outweighed by the biological differences between the patients. Only a relatively small number of probes (275 out of 41,000) show a significant effect due to degradation. The genes that show the strongest effect due to RNA degradation were, especially, those with short mRNAs and probe positions near the 5' end.

Conclusions: Degraded RNA from tumor samples (RIN > 5) can still be used to perform gene expression analysis. A much higher biological variance between patients is observed compared to the effect that is imposed by degradation of RNA. Nevertheless there are genes, very short ones and those with the probe binding side close to the 5' end that should be excluded from gene expression analysis when working with degraded RNA. These results are limited to the Agilent 44 k microarray platform and should be carefully interpreted when transferring to other settings.

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Comparison of Microarray and qPCR results for candidate genes. Heatmaps from microarray (left side) and qPCR (right side). Colors represent relative differences between TP3 vs. Control. 9 genes from 3 groups of representation (from top to bottom: over-represented, under-representation and normally-represented in the microarray data) are shown.
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Figure 4: Comparison of Microarray and qPCR results for candidate genes. Heatmaps from microarray (left side) and qPCR (right side). Colors represent relative differences between TP3 vs. Control. 9 genes from 3 groups of representation (from top to bottom: over-represented, under-representation and normally-represented in the microarray data) are shown.

Mentions: Validation of the microarray data was performed by qPCR using three representative candidates of under-represented, over-represented and normally-represented genes from the control group and TP3. Therefore, the degradation experiment was repeated, i.e. RNA from the same three patients was degraded again. To compare the expression levels fold changes between the two time points were assessed as illustrated in Figure 4 showing similar patterns of over- and under-representation. Only the normally-represented group showed a slight tendency to be more degraded in the qPCR experiments than in the microarray results. This might be explained by a higher stability of the house-keeping genes that were used in the qPCR experiments or by the fact that qPCR reveals the general trend of degradation, also observed on the microarray but removed due to the normalization procedure. Generally the direction of change remains consistent for the two groups of over-represented and under-represented genes.


Impact of RNA degradation on gene expression profiling.

Opitz L, Salinas-Riester G, Grade M, Jung K, Jo P, Emons G, Ghadimi BM, Beissbarth T, Gaedcke J - BMC Med Genomics (2010)

Comparison of Microarray and qPCR results for candidate genes. Heatmaps from microarray (left side) and qPCR (right side). Colors represent relative differences between TP3 vs. Control. 9 genes from 3 groups of representation (from top to bottom: over-represented, under-representation and normally-represented in the microarray data) are shown.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2927474&req=5

Figure 4: Comparison of Microarray and qPCR results for candidate genes. Heatmaps from microarray (left side) and qPCR (right side). Colors represent relative differences between TP3 vs. Control. 9 genes from 3 groups of representation (from top to bottom: over-represented, under-representation and normally-represented in the microarray data) are shown.
Mentions: Validation of the microarray data was performed by qPCR using three representative candidates of under-represented, over-represented and normally-represented genes from the control group and TP3. Therefore, the degradation experiment was repeated, i.e. RNA from the same three patients was degraded again. To compare the expression levels fold changes between the two time points were assessed as illustrated in Figure 4 showing similar patterns of over- and under-representation. Only the normally-represented group showed a slight tendency to be more degraded in the qPCR experiments than in the microarray results. This might be explained by a higher stability of the house-keeping genes that were used in the qPCR experiments or by the fact that qPCR reveals the general trend of degradation, also observed on the microarray but removed due to the normalization procedure. Generally the direction of change remains consistent for the two groups of over-represented and under-represented genes.

Bottom Line: Only a relatively small number of probes (275 out of 41,000) show a significant effect due to degradation.A much higher biological variance between patients is observed compared to the effect that is imposed by degradation of RNA.These results are limited to the Agilent 44 k microarray platform and should be carefully interpreted when transferring to other settings.

View Article: PubMed Central - HTML - PubMed

Affiliation: Department Medical Statistics, University Medicine Göttingen, Humboldtallee 32, 37073 Göttingen, Germany.

ABSTRACT

Background: Gene expression profiling is a highly sensitive technique which is used for profiling tumor samples for medical prognosis. RNA quality and degradation influence the analysis results of gene expression profiles. The impact of this influence on the profiles and its medical impact is not fully understood. As patient samples are very valuable for clinical studies, it is necessary to establish criteria for the RNA quality to be able to use these samples in later analysis.

Methods: To investigate the effects of RNA integrity on gene expression profiling, whole genome expression arrays were used. We used tumor biopsies from patients diagnosed with locally advanced rectal cancer. To simulate degradation, the isolated total RNA of all patients was subjected to heat-induced degradation in a time-dependent manner. Expression profiling was then performed and data were analyzed bioinformatically to assess the differences.

Results: The differences introduced by RNA degradation were largely outweighed by the biological differences between the patients. Only a relatively small number of probes (275 out of 41,000) show a significant effect due to degradation. The genes that show the strongest effect due to RNA degradation were, especially, those with short mRNAs and probe positions near the 5' end.

Conclusions: Degraded RNA from tumor samples (RIN > 5) can still be used to perform gene expression analysis. A much higher biological variance between patients is observed compared to the effect that is imposed by degradation of RNA. Nevertheless there are genes, very short ones and those with the probe binding side close to the 5' end that should be excluded from gene expression analysis when working with degraded RNA. These results are limited to the Agilent 44 k microarray platform and should be carefully interpreted when transferring to other settings.

Show MeSH
Related in: MedlinePlus