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CoolMPS: evaluation of antibody labeling based massively parallel non-coding RNA sequencing

Li, Yongping, Fehlmann, Tobias, Borcherding, Adam, Drmanac, Snezana, Liu, Sophie, Groeger, Laura, Xu, Chongjun, Callow, Matthew, Villarosa, Christian, Jorjorian, Alexander, Kern, Fabian, Grammes, Nadja, Meese, Eckart, Jiang, Hui, Drmanac, Radoje, Ludwig, Nicole, Keller, Andreas·2021·Nucleic Acids Research
DOI 10.1093/nar/gkaa1122PMC PMC7826284
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Abstract

Results of massive parallel sequencing-by-synthesis vary depending on the sequencing approach. CoolMPS™ is a new sequencing chemistry that incorporates bases by labeled antibodies. To evaluate the performance, we sequenced 240 human non-coding RNA samples (dementia patients and controls) with and without CoolMPS. The Q30 value as indicator of the per base sequencing quality increased from 91.8 to 94%. The higher quality was reached across the whole read length. Likewise, the percentage of reads mapping to the human genome increased from 84.9 to 86.2%. For both technologies, we computed similar distributions between different RNA classes (miRNA, piRNA, tRNA, snoRNA and yRNA) and within the classes. While standard sequencing-by-synthesis allowed to recover more annotated miRNAs, CoolMPS yielded more novel miRNAs. The correlation between the two methods was 0.97. Evaluating the diagnostic performance, we observed lower minimal P-values for CoolMPS (adjusted P-value of 0.0006 versus 0.0004) and larger effect sizes (Cohen's d of 0.878 versus 0.9). Validating 19 miRNAs resulted in a correlation of 0.852 between CoolMPS and reverse transcriptase-quantitative polymerase chain reaction. Comparison to data generated with Illumina technology confirmed a known shift in the overall RNA composition. With CoolMPS we evaluated a novel sequencing-by-synthesis technology showing high performance for the analysis of non-coding RNAs.

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Figure 1. Study setup and quality control. (A) In the study we measured 240 individual blood samples using two fundamentally different sequencing approaches and compare the data by bioinformatics approaches before we compute the concordance to RT-qPCR profiles. The 240 samples include one part that has been used only for assessment of technical properties (6 and 17 samples in blue and gray) as well as a second part to evaluate performance related to biomarker discovery (176 controls in green and 38 dementia cases in orange). (B) Distribution of the age of the individuals included in the study, shown as violin plot. The black box spans the first to the third quartile and the white dot shows the median. (C) Distribution of the average Q30 value per sample for the two technologies, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (D) Q30 value over all samples per technology as function of the position in the read. The smoothed curve is fitted by a generalized additive model using a cubic regression spline. The gray area represents the confidence interval of the fit. (E) Distribution of the percentage of reads mapping to the human reference genome hg38 without mismatch per technology, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (F) Scatter plot of the average expression of all miRNAs in all samples for the two technologies. The blue line is the regression line. The Pearson correlation is shown in the upper left part of the plot. MiRNAs with a fold change larger than two between both technologies are highlighted. (G) Heat map of the clustered expression z-scores of miRNAs (rows) and technical replicates (columns). The color code for the columns represents the technology. The dendrogram shows the hierarchical clustering of the samples with Euclidean distance and complete linkage. (H) Distribution of all 12*11/2 = 66 pairwise Pearson correlation coefficients, shown as violin plot. The black box spans the first to the third quartile and the white dot shows the median. (I) Correlation matrix of the expression values of all miRNAs for all technical replicates. The dendrogram shows the hierarchical clustering of the samples with Euclidean distance and complete linkage. (J) Scatter plot of miRNAs for the best correlation between two technical replicates. The dotted line represents the angle bisector. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood. (K) Scatter plot of miRNAs for the worst correlation between two technical replicates. The dotted line represents the angle bisector. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood.
Figure 1. Study setup and quality control. (A) In the study we measured 240 individual blood samples using two fundamentally different sequencing approaches and compare the data by bioinformatics approaches before we compute the concordance to RT-qPCR profiles. The 240 samples include one part that has been used only for assessment of technical properties (6 and 17 samples in blue and gray) as well as a second part to evaluate performance related to biomarker discovery (176 controls in green and 38 dementia cases in orange). (B) Distribution of the age of the individuals included in the study, shown as violin plot. The black box spans the first to the third quartile and the white dot shows the median. (C) Distribution of the average Q30 value per sample for the two technologies, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (D) Q30 value over all samples per technology as function of the position in the read. The smoothed curve is fitted by a generalized additive model using a cubic regression spline. The gray area represents the confidence interval of the fit. (E) Distribution of the percentage of reads mapping to the human reference genome hg38 without mismatch per technology, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (F) Scatter plot of the average expression of all miRNAs in all samples for the two technologies. The blue line is the regression line. The Pearson correlation is shown in the upper left part of the plot. MiRNAs with a fold change larger than two between both technologies are highlighted. (G) Heat map of the clustered expression z-scores of miRNAs (rows) and technical replicates (columns). The color code for the columns represents the technology. The dendrogram shows the hierarchical clustering of the samples with Euclidean distance and complete linkage. (H) Distribution of all 12*11/2 = 66 pairwise Pearson correlation coefficients, shown as violin plot. The black box spans the first to the third quartile and the white dot shows the median. (I) Correlation matrix of the expression values of all miRNAs for all technical replicates. The dendrogram shows the hierarchical clustering of the samples with Euclidean distance and complete linkage. (J) Scatter plot of miRNAs for the best correlation between two technical replicates. The dotted line represents the angle bisector. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood. (K) Scatter plot of miRNAs for the worst correlation between two technical replicates. The dotted line represents the angle bisector. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood.CC BY · PubMed Central
Figure 2. Distribution to the different sncRNAs classes. (A) Donut plot comparing the distribution of all RNA classes and intergenic regions that were covered by reads from CoolMPS and BGISEQ. (B) Scatter plot that shows the percentage of reads mapping to the RNA classes and intergenic regions for BGISEQ (x-axis) and CoolMPS (y-axis) on a logarithmic scale.
Figure 2. Distribution to the different sncRNAs classes. (A) Donut plot comparing the distribution of all RNA classes and intergenic regions that were covered by reads from CoolMPS and BGISEQ. (B) Scatter plot that shows the percentage of reads mapping to the RNA classes and intergenic regions for BGISEQ (x-axis) and CoolMPS (y-axis) on a logarithmic scale.CC BY · PubMed Central
Figure 3. Distribution to microRNAs. (A) Distribution of the read percentage of the 10 most abundant miRNAs in the CoolMPS and BGISEQ data, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (B) Number of novel microRNA candidates for both technologies. (C) Pie chart for the top five miRNAs on the BGISEQ. (D) Pie chart for the top five miRNAs on the CoolMPS. (E) Pie chart for the top ten miRNAs on the BGISEQ after exclusion of the most abundant miR-451a. (F) Pie chart for the top ten miRNAs using CoolMPS after exclusion of the most abundant miR-451a.
Figure 3. Distribution to microRNAs. (A) Distribution of the read percentage of the 10 most abundant miRNAs in the CoolMPS and BGISEQ data, shown as boxplot (left) and dotplot (right). Each sample is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (B) Number of novel microRNA candidates for both technologies. (C) Pie chart for the top five miRNAs on the BGISEQ. (D) Pie chart for the top five miRNAs on the CoolMPS. (E) Pie chart for the top ten miRNAs on the BGISEQ after exclusion of the most abundant miR-451a. (F) Pie chart for the top ten miRNAs using CoolMPS after exclusion of the most abundant miR-451a.CC BY · PubMed Central
Figure 4. Diagnostic performance on dementia patients. (A) Distribution of the AUC values to differentiate between dementia and controls obtained for both technologies. An AUC of 0.5 means no dys-regulation. A deviation from 0.5 toward one means an upregulation and toward zero a downregulation of the biomarkers. The distribution is shown as boxplot (left) and dotplot (right). Each miRNA is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (B) Scatter plot of the AUC values to differentiate between dementia and controls in CoolMPS (x-axis) versus BGISEQ (y-axis). The black horizontal and vertical line represent the AUC value of 0.5, respectively. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood. (C) Volcano plot showing the log2 fold change on the x-axis and the FDR adjusted negative log10 of the Wilcoxon–Mann–Whitney (WMW) P-value on the y-axis for BGISEQ. Orange dots are located above the horizontal line and are significant. Blue and green dots above the horizontal and on the left / right of the vertical lines are significant and have a fold-change above 2. (D) Same volcano plot as in Figure 4C, but for CoolMPS. (E) Result of DynaVenn that presents the negative log10 of the overlap between the two miRNA sets dependent on how many miRNAs are included. The peak of the curve represents the most significant overlap. (F) Scatter plot of the log2 CoolMPS expression (x-axis) and the negative delta CT value for the 19 miRNAs included in the validation study. The Pearson correlation coefficient is shown in the upper left part of the plot. (G) Scatter plot of the AUC values to differentiate between dementia and controls in CoolMPS (x-axis) and BGISEQ (y-axis). The dashed line represents the angle bisector.
Figure 4. Diagnostic performance on dementia patients. (A) Distribution of the AUC values to differentiate between dementia and controls obtained for both technologies. An AUC of 0.5 means no dys-regulation. A deviation from 0.5 toward one means an upregulation and toward zero a downregulation of the biomarkers. The distribution is shown as boxplot (left) and dotplot (right). Each miRNA is shown as one dot. The boxes span the first to the third quartile with the horizontal line inside the box representing the median value. The whiskers show the minimum and maximum values or values up to 1.5 times the interquartile range below or above the first or third quartile if outliers are present. (B) Scatter plot of the AUC values to differentiate between dementia and controls in CoolMPS (x-axis) versus BGISEQ (y-axis). The black horizontal and vertical line represent the AUC value of 0.5, respectively. The Pearson correlation is shown in the upper left part of the plot. The points are colored according to the point density in their neighborhood. (C) Volcano plot showing the log2 fold change on the x-axis and the FDR adjusted negative log10 of the Wilcoxon–Mann–Whitney (WMW) P-value on the y-axis for BGISEQ. Orange dots are located above the horizontal line and are significant. Blue and green dots above the horizontal and on the left / right of the vertical lines are significant and have a fold-change above 2. (D) Same volcano plot as in Figure 4C, but for CoolMPS. (E) Result of DynaVenn that presents the negative log10 of the overlap between the two miRNA sets dependent on how many miRNAs are included. The peak of the curve represents the most significant overlap. (F) Scatter plot of the log2 CoolMPS expression (x-axis) and the negative delta CT value for the 19 miRNAs included in the validation study. The Pearson correlation coefficient is shown in the upper left part of the plot. (G) Scatter plot of the AUC values to differentiate between dementia and controls in CoolMPS (x-axis) and BGISEQ (y-axis). The dashed line represents the angle bisector.CC BY · PubMed Central

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Metadata

Authors
Li, Y., Fehlmann, T., Borcherding, A., Drmanac, S., Liu, S., Groeger, L., Xu, C., Callow, M., Villarosa, C., Jorjorian, A., Kern, F., Grammes, N., Meese, E., Jiang, H., Drmanac, R., Ludwig, N., & Keller, A.
Affiliations
  • Chair for Clinical Bioinformatics, Saarland University, 66123 Saarbrücken, Germany
  • Complete Genomics Incorporated, San Jose, CA 95134, USA
  • Department of Human Genetics, Saarland University, 66421 Homburg, Germany
  • MGI, BGI-Shenzhen, Shenzhen 518083, China
ORCID
Venue
Nucleic Acids Research
Publisher
Oxford University Press (OUP)
Published
2020-12-08
Volume
49
Issue
2
Pages
e10-e10
ISSN
  • 0305-1048
  • 1362-4962
DOI
10.1093/nar/gkaa1122
PMC
PMC7826284
Cited by
21
References
1
Language
en
Licence
creativecommons.org/licenses/by/4.0/ (vor)
Funders
  • Saarland University
  • Michael J. Fox Foundation for Parkinson's Research (14446)
  • Complete Genomics

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