Arraystar Small RNA Modification Array Service quantifies your choice of 8-oxoguanine (o8G), 7-methylguanosine (m7G), N6-methyladenosine (m6A), N1-methyladenosine (m1A), Pseudouridine (Ψ), or 5-methylcytidine (m5C) modification in miRNAs, pre-miRNAs, and tRNA-derived small RNAs (tsRNAs, including tRFs and tiRNAs) on a single array. Please specify one modification per microarray experiment when you request a quote.

Benefits

•  Coverage of multiple small RNA classes, including miRNAs, pre-miRNAs, and tsRNAs (tRFs and tiRNAs)

•  Gold standard for accurate quantification of modified small RNAs
Direct RNA end labeling ensures high fidelity of quantification, without the problem of modification blocked cDNA synthesis during RNA-seq library prep.

•  High sensitivity for modified small RNAs at lower levels
Overcome the limitations of sequencing technology, excellent analytical sensitivity for small RNAs at low levels of expression or modification.  

•  Low sample amount required, starting from as little as 1 µg total RNA.

Watch Video> How to Profile Small RNA Modifications?
 

The challenges of profiling small RNA modifications

Although sequencing has been used for small RNA profiling, the influence of RNA modifications on the sequencing quantification has largely been ignored. Various RNA modifications, such as m1A, m3C and m1G, do interfere with the reverse transcription reaction during sequencing library construction, thereby making accurate quantification of small RNAs and especially their modifications impossible. For example, small RNA-seq is mostly biased toward 18-nt 3’-tsRNA rather than the more predominant 22-nt isoforms seen by northern blot. This is due to the presence of m1A in the TUC loop, which blocks reverse transcriptase from proceeding. Most of the small RNA sequencing data have been obtained from the library construction methods above, consequently the data could be misleading for modified small RNAs.

Also, small RNA profiling by small RNA-seq requires multiple PCR amplification steps, which incurs significant quantification bias/inaccuracies and therefore necessitates the use of independent, orthogonal methodologies.

In practice, most sequencing based method for modification studies requires large amount of input materials (> 100 ug total RNA), precluding many studies with only limited sample amounts.

Furthermore, small RNA-seq commonly uses Reads Per Million RNA reads (RPM) for normalization and to represent the relative RNA abundances in the sample. However, RPM depends on the composition of the small RNA population in a sample. A change in one small RNA’s RPM will adjust all the other small RNAs’ values even their actual absolute expression levels are not changed.

In order to identify and quantify the full spectrum of modified-small RNAs with high sensitivity and accurate stoichiometry, there is a need for overcoming the limitations of the sequencing technology and developing non-sequencing-based methods.

Techniques to quantify small RNA post-transcriptional modifications

Arraystar small RNA modification profiling technology (Figure 1) combines microarray with RNA immunoprecipitation (RIP) to simultaneously measure the modified and unmodified small RNA levels on the same array, providing the vital information to study regulatory impacts of the modification in small RNAs, including miRNAs, pre-miRNAs, and tsRNAs(tRFs and tiRNAs).

Figure 1. Arraystar small RNA modification profiling technology to identify and quantify small RNA post-transcriptional modifications, o8G, m7G, m6A, pseudouridine, and m5C respectively. Modified small RNAs are enriched by immunoprecipitation using a specific antibody, and then identified and quantified by using Arraystar small RNA modification microarray.

Human Small RNA Modification Array V1.0

Mouse Small RNA Modification Array V1.0

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The data analysis includes ready-to-use key measurements, useful annotations and publication quality graphics.

Differentially Modified miRNAs, pre-miRNAs, and tsRNAs (tRFs and tiRNAs)

MatureID:  miRBase ID for the mature miRNA.

Group m7G miRNA level (normalized, log2):  Group averaged, log2 transformed, normalized m7G modified miRNA level, based on the Cy5 signal intensities of the m7G-IP RNA in the sample group.

Treated, Control:  The “treated” and “Control” sample groups.

FC:  The fold change comparing the sample groups.

P:  p-value by t-test, for the statistical significance of the difference.

Regulation: Up- or down-regulation by comparing the sample groups.

Group m7G %modified miRNA: Group averaged percentage of m7G modified miRNA for the sample group. miRNA_family: miRNA family members having the same seed sequence.

m7G_motif: “RAm7GGT” motif sequence of the m7G site, where R represents G or A.

Hierarchical clustering heatmap of differentially modified miRNAs, pre-miRNAs, and tsRNAs (tRFs and tiRNAs)

Figure 1. Hierarchical clustering heatmap of differentially modified small RNAs. The modified RNA levels are represented by red-blue color scale referenced in the color key on the top left. The top dendrogram shows the relative closeness of the modification profiles among the samples. The sample group membership is indicated by the color bars above the heat map.