Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing
Background: Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of freeze-thaw on downstream analyses is limited. The lack of common quality metrics that are sufficiently sensitive to freeze-thaw and RNA degradation, e.g. the RNA Integrity Score, makes such assessments challenging.
Results: Here we quantify the impact of repeated freeze-thaw cycles on the reliability of RNA-Seq by examining poly(A)-enriched and ribosomal RNA depleted RNA-seq from frozen leukocytes drawn from a toddler Autism cohort. To do so, we estimate the relative noise, or percentage of random counts, separating technical replicates. Using this approach we measured noise associated with RIN and freeze-thaw cycles. As expected, RIN does not fully capture sample degradation due to freeze-thaw. We further examined differential expression results and found that three freeze-thaws should extinguish the differential expression reproducibility of similar experiments. Freeze-thaw also resulted in a 3’ shift in the read coverage distribution along the gene body of poly(A)-enriched samples compared to ribosomal RNA depleted samples, suggesting that library preparation may exacerbate freeze-thaw-induced sample degradation.
Conclusion: The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility.
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Graphical abstract
Posted 12 Jan, 2021
On 31 Dec, 2020
On 27 Dec, 2020
Received 24 Dec, 2020
On 06 Dec, 2020
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On 01 Dec, 2020
Received 01 Dec, 2020
Received 01 Dec, 2020
On 09 Nov, 2020
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On 09 Nov, 2020
Received 08 Oct, 2020
On 08 Oct, 2020
Received 02 Oct, 2020
Received 22 Sep, 2020
Received 22 Sep, 2020
On 20 Sep, 2020
On 16 Sep, 2020
On 16 Sep, 2020
On 16 Sep, 2020
Invitations sent on 15 Sep, 2020
On 25 Aug, 2020
On 25 Aug, 2020
On 24 Aug, 2020
On 24 Aug, 2020
Multiple freeze-thaw cycles lead to a loss of consistency in poly(A)-enriched RNA sequencing
Posted 12 Jan, 2021
On 31 Dec, 2020
On 27 Dec, 2020
Received 24 Dec, 2020
On 06 Dec, 2020
On 01 Dec, 2020
Invitations sent on 01 Dec, 2020
On 01 Dec, 2020
Received 01 Dec, 2020
Received 01 Dec, 2020
On 09 Nov, 2020
On 09 Nov, 2020
On 09 Nov, 2020
Received 08 Oct, 2020
On 08 Oct, 2020
Received 02 Oct, 2020
Received 22 Sep, 2020
Received 22 Sep, 2020
On 20 Sep, 2020
On 16 Sep, 2020
On 16 Sep, 2020
On 16 Sep, 2020
Invitations sent on 15 Sep, 2020
On 25 Aug, 2020
On 25 Aug, 2020
On 24 Aug, 2020
On 24 Aug, 2020
Background: Both RNA-Seq and sample freeze-thaw are ubiquitous. However, knowledge about the impact of freeze-thaw on downstream analyses is limited. The lack of common quality metrics that are sufficiently sensitive to freeze-thaw and RNA degradation, e.g. the RNA Integrity Score, makes such assessments challenging.
Results: Here we quantify the impact of repeated freeze-thaw cycles on the reliability of RNA-Seq by examining poly(A)-enriched and ribosomal RNA depleted RNA-seq from frozen leukocytes drawn from a toddler Autism cohort. To do so, we estimate the relative noise, or percentage of random counts, separating technical replicates. Using this approach we measured noise associated with RIN and freeze-thaw cycles. As expected, RIN does not fully capture sample degradation due to freeze-thaw. We further examined differential expression results and found that three freeze-thaws should extinguish the differential expression reproducibility of similar experiments. Freeze-thaw also resulted in a 3’ shift in the read coverage distribution along the gene body of poly(A)-enriched samples compared to ribosomal RNA depleted samples, suggesting that library preparation may exacerbate freeze-thaw-induced sample degradation.
Conclusion: The use of poly(A)-enrichment for RNA sequencing is pervasive in library preparation of frozen tissue, and thus, it is important during experimental design and data analysis to consider the impact of repeated freeze-thaw cycles on reproducibility.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6