For our standard projects we provide a detailed, interactive analysis report that includes summary metrics and detailed analyses. Example analyses include the identification of differential enrichment of RNA-binding protein activity with RBP-eCLIP, identification of upstream ORFs with eRibo Pro, and locating differential UTR usage with End-Seq.

For our partners developing RNA-based therapeutics we perform specialized analyses in a comprehensive report.

In addition to our standard analyses, our team of bioinformatics scientists can provide custom analysis solutions. This is typically provided as part of our platform partnerships where partners are paired with a dedicated bioinformatics scientist. Contact us to learn what support we can provide to accomplish your goals.

To support our partners and the RNA community at large, we provide information on our analysis methods as part of our eBlog education series. Learn how we identify where RNA-binding proteins bind and how to use genome browser tools directly from our team of analysis experts.

Different disease states can lead to the expression of different isoforms with specific UTR usage. End-Seq reveals which UTRs are active in a given disease state, providing small molecule developers with lists of druggable regions selectively active in the disease and cell type of interest.

To be effective, many mRNA therapeutics require UTRs that are active in the target cell type, have low endogenous regulation, and high stability. With End-Seq, we identify active UTRs with the cellular machinery in place to drive protein production. When paired with our other technologies, we can further refine UTR selection to minimize unwanted miRNA regulation while maximizing stability and translation.

Ribosome occupancy, also called translation efficiency or TE, is a relative measure of the amount of ribosomes on a given gene. This metric is often used to detect target-specific changes in translation with small molecules, or to rank mRNA vaccine candidates for optimal protein production.

Ribosome stalling can lead to decreased protein production or frameshifted proteins. This makes identification of ribosome stalls critical for mRNA therapeutic development and the comprehensive evaluation of small molecule candidates. eRibo Pro provides per codon measurements of ribosome enrichment, enabling the robust identification of where ribosome stalls occur.

All therapeutics have a risk of off-target effects, which can halt a clinical trial. By measuring both RNA levels and translation, eRibo Pro provides a more comprehensive view of therapeutic effects, allowing developers to move to the clinic with increased confidence.

Micropeptides are emerging as powerful regulators of health and disease, yet many remain undiscovered due to their small size and non-canonical translation. eRibo Pro precisely maps active translation across the transcriptome, enabling sensitive detection of small open reading frames (sORFs) that produce these overlooked proteins. By capturing ribosome footprints with high resolution, eRibo Pro helps researchers uncover novel ORFs, expanding the known functional proteome and revealing new biomarkers and therapeutic targets.

Antibody-based dot blots and ELISAs are typically used to quantify dsRNA but struggle with reproducibly issues and cannot measure short stretches of dsRNA that can trigger innate immune responses. eSENSE dsRNA quantification is highly correlated with antibody-based methods, while also capturing short stretches of dsRNA.

J2- and K1-based assays only identify that dsRNA is present. They don’t reveal where the polymerase runoff begins and ends, limiting their utility during sequence and manufacturing optimization. Through next-generation sequencing, eSENSE dsRNA reveals where dsRNA is located along the therapeutic without sequence bias.

Polymerase runoff can occur due to specific sequences and RNA secondary structures. We pair eSENSE dsRNA with our eSHAPE assay for structure profiling to identify specific structural features that contribute to dsRNA generation, providing actionable insights for RNA optimization.

Like traditional MeRIP-Seq, eSENSE m6A maps regions of elevated methylation across expressed genes with low input requirements. This provides researchers and drug developers with critical information on where RNA modifications are deposited across the transcriptome. For increased resolution, our m6A-eCLIP assay provides base-level mapping of methylation.

For transcriptome-wide studies of methylation, we perform gene ontology analyses to determine if specific categories of genes are preferentially methylated in a given disease state or after a therapeutic treatment.

eSENSE m6A provides detailed information on methylated RNA regions, such as which specific genes have increased methylation at stop codons or UTRs. As part of our standard analyses for eSENSE m6A we identify which gene features are methylated, providing researchers with key insights into how methylation patterns change with specific disease or drug treatments.

RNA folding is a complex process that depends on the sequence of the RNA, the rate of transcription, the presence of RNA-binding proteins, and other factors. Typical in silico prediction methods cannot account for cellular effects, limiting their utility for drug development. eSHAPE directly measures RNA structure in the natural environment, increasing accuracy of structure predictions for the effective design of small molecule and small oligonucleotide therapeutics.

RNA structure is not fixed, with different confirmations occurring after in vitro transcription (IVT), in LNPs, and in the cell. Our optimized eSHAPE assay allow us to measure structure across different conditions, revealing how an RNA changes as it moves from manufacturing to cell entry. This allows mRNA therapeutic developers to determine if LNP formulations lead to less base pairing and instability, or if entry into the cell makes protein binding sites accessible.

In this dataset, we have performed both in vitro (without cellular factors) and in cellulo (with cellular factors) eSHAPE. By comparing the difference in reactivity of these two conditions with ΔSHAPE, we can detect nucleotides that interact with cellular factors such as RNA-binding proteins.

IVT errors can generate double-stranded RNA (dsRNA) that activates the innate immune system. Locating the sequence origins of dsRNA, however, is challenging. We have developed a unique, next-generation sequencing-based approach to

• Quantify dsRNA including lengths below antibody detection limits
• Identify where IVT runoff begins and ends
• Evaluate the effects of different manufacturing optimizations or base changes on dsRNA production

RNA structure is critical for stability. RNA structure is critical for stability, yet computational predictions can be inaccurate in the context of LNPs or the cellular environment. With our proprietary approach we:

• Directly measure RNA structure in LNPs
• Evaluate secondary structure in cells
• Determine changes in structure during drug product formulation

Efficient translation is critical for RNA efficacy, yet ribosome stalls and frameshifts can limit protein output. We use empirical data from target cell types to:

• Locate ribosome stalls and optimize sequences to improve translation
• Measure translation over time to identify optimal candidates for therapeutic efficacy
• Select optimal codons that are cell- and tissue-specific

eMERGE uses multiple sequencing-based approaches to fully characterize RNA therapeutic quality. These analytics can be paired with our AI design and manufacturing capabilities to deliver complete preclinical drug development support.

We have optimized our in-house capabilities to produce challenging RNA constructs, including linear mRNAs greater than 5 kb. This enables rapid iteration across designs until the optimal candidate is identified.

One of the biggest challenges after identifying a lead candidate is selecting the right partner for scale-up and GMP manufacturing. Through our network of validated manufacturing partners, we help pair you with the optimal vendor to produce your therapy for the clinic.

m6A-eCLIP reveals methylation patterns across multiple scales: from identifying regions where methylation is elevated (similar to MeRIP-Seq) to providing identification of which specific adenosines are methylated. This provides researchers and drug developers with an unparalleled view into where RNA modifications are deposited across the transcriptome and transfected sequences.

For transcriptome-wide studies of methylation, we perform gene ontology analyses to determine if specific categories of genes are preferentially methylated in a given disease state or after a therapeutic treatment.

m6A-eCLIP provides per-base and per-region measurements of methylation. This allows us to examine changes in methylation on multiple scales, providing deeper insights into how a condition or drug treatment affects methylation patterns. This type of analysis can be used to confirm if a therapeutic has changed methylation at a specific target and if off-target changes are occurring.

Computational predictions are often used to identify miRNA activity, but the end result is a prediction that still requires validation. With miR-eCLIP+, we use ligation to directly map where miRNAs are binding. This allows researchers to gain mechanistic insights into miRNA biology, and the developers of anti-miRs to validate that miRNA binding has been lost after treatment.

siRNAs are an effective class of RNA therapeutics for regulating mRNA levels and treating disease. However, off-target binding can lead to clinical trial failure. With miR-eCLIP+, we directly measure where and how siRNAs bind transcriptome-wide. When paired with eRibo Pro, our ribosome profiling technology, the effects of off-target binding on gene expression and translation can be determined as well. The results of these analyses provide siRNA developers with the data needed for candidate selection and siRNA optimization.