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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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Related in: MedlinePlus

Degradation of RNA. The effect of degradation time on calculated RNA Integrity Numbers (RINs) for the given samples P159, P160 and P162 is shown. (A) Bioanalyzer profiles of total RNA for degradation levels used in the microarray study (control, 1:45 h, 2:30 h, 3:15 h). RINs are shown next to each total RNA profile. (B) RIN-dependence of degradation time separately for all patients. An additional time point (240 Min/4:00 h) without gene expression profile is also present.
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Figure 1: Degradation of RNA. The effect of degradation time on calculated RNA Integrity Numbers (RINs) for the given samples P159, P160 and P162 is shown. (A) Bioanalyzer profiles of total RNA for degradation levels used in the microarray study (control, 1:45 h, 2:30 h, 3:15 h). RINs are shown next to each total RNA profile. (B) RIN-dependence of degradation time separately for all patients. An additional time point (240 Min/4:00 h) without gene expression profile is also present.

Mentions: To determine the integrity of the RNA starting materials for the microarray analysis at the different time-points, we evaluated the quality of each sample using the RNA integrity number (RIN). Using this tool, sample integrity is determined by the entire electrophoretic trace (Bioanalyzer profiles) of the RNA sample, including the presence or absence of degradation products. The Bioanalyzer profiles, as well as the calculated RINs of the samples, are shown in Figure 1A. The calculated RNA integrity numbers for all samples depending on degradation time are displayed in Figure 1B. A strong negative correlation between RIN-values and degradation time in all three patients is evident. The Null-Hypothesis that there is no negative correlation can be rejected using a statistical correlation test on Kendall's rank correlation (τ = -0:862, p-value = 2.530e-05).


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)

Degradation of RNA. The effect of degradation time on calculated RNA Integrity Numbers (RINs) for the given samples P159, P160 and P162 is shown. (A) Bioanalyzer profiles of total RNA for degradation levels used in the microarray study (control, 1:45 h, 2:30 h, 3:15 h). RINs are shown next to each total RNA profile. (B) RIN-dependence of degradation time separately for all patients. An additional time point (240 Min/4:00 h) without gene expression profile is also present.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 1: Degradation of RNA. The effect of degradation time on calculated RNA Integrity Numbers (RINs) for the given samples P159, P160 and P162 is shown. (A) Bioanalyzer profiles of total RNA for degradation levels used in the microarray study (control, 1:45 h, 2:30 h, 3:15 h). RINs are shown next to each total RNA profile. (B) RIN-dependence of degradation time separately for all patients. An additional time point (240 Min/4:00 h) without gene expression profile is also present.
Mentions: To determine the integrity of the RNA starting materials for the microarray analysis at the different time-points, we evaluated the quality of each sample using the RNA integrity number (RIN). Using this tool, sample integrity is determined by the entire electrophoretic trace (Bioanalyzer profiles) of the RNA sample, including the presence or absence of degradation products. The Bioanalyzer profiles, as well as the calculated RINs of the samples, are shown in Figure 1A. The calculated RNA integrity numbers for all samples depending on degradation time are displayed in Figure 1B. A strong negative correlation between RIN-values and degradation time in all three patients is evident. The Null-Hypothesis that there is no negative correlation can be rejected using a statistical correlation test on Kendall's rank correlation (τ = -0:862, p-value = 2.530e-05).

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