Next-generation RNA sequencing has transformed molecular profiling for clinical research, but formalin-fixed, paraffin-embedded (FFPE) samples continue to present significant challenges.
Traditional fragmentation methods struggle with degraded RNA, cross-linking artifacts and low yields that compromise data quality and limit downstream applications.
This application note explores the latest advanced acoustic fragmentation technology, which delivers consistent, high-quality results from even the most challenging clinical specimens.
Download this application note to learn:
- How acoustic fragmentation overcomes traditional FFPE sample limitations
- Protocol optimization strategies for degraded RNA samples
- Performance comparison data from real-world clinical specimens
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Background
Transcriptomic studies using next-generation (NGS)-
based RNA sequencing (RNA-Seq) have significantly
advanced molecular profiling and diagnostic
protocols for solid tumors obtained from tumor
resection, biopsy, or cytological specimens that have
been formalin-fixed, paraffin-embedded (FFPE) [1].
Similarly, researchers have focused on examining
complex organs and tissues at single-cell resolution
and capturing nascent RNA in RNA-Seq assays to
uncover coordinated global transcription across the
genome [2]. The presence of numerous variants of
uncertain clinical significance and the challenges in
interpreting noncoding variants are significant gaps
in genomic analysis. These gaps can be addressed
by providing functional evidence through RNA
sequencing assays, which complement genomic
data.
RNA-Seq data not only reveal gene expression
levels but also provide insight into RNA processing
patterns and allele-specific expression. However,
due to the variable quality and quantity of RNA
obtained from FFPE and single-cell samples,
the library preparation process often presents
challenges and requires significant improvements.
To address these challenges, Covaris Adaptive
Focused Acoustics (AFA) Technology offers a flexible
solution for customers with varying throughput,
batch, and automation needs. This technology
enables the routine implementation of large-scale
RNA sequencing for degraded samples by using a
novel method of RNA fragmentation combined with
reduced sample volumes for library preparation.
Challenges in RNA Quality and Fragmentation in
FFPE Samples
There are several challenges associated with nucleic
acid quality and fragmentation in FFPE samples.
These hurdles arise from the nature of FFPE
samples, and the various steps involved in the FFPE
process and subsequent library prep. Some common
challenges include:
• Fragmentation: Formalin fixation may cause
fragmentation of RNA, leading to shorter
fragment lengths. These shorter fragments
can impact downstream applications, such
as sequencing, resulting in reduced
amplification efficiency or sequence coverage.
• Low Yield: FFPE samples typically yield lower
amounts of nucleic acids compared to fresh or
frozen tissue samples. The fixation and
embedding processes can result in loss,
making it challenging to obtain sufficient RNA
for fragmentation and downstream library prep.
• Cross-linking: Formalin fixation can induce
cross-links between DNA and proteins or other
molecules, making it difficult to extract intact
RNA from FFPE samples.
• Contaminants and Impurities: FFPE samples
may contain contaminants, such as formalin
residues, paraffin, or other chemicals used
during the preservation process. These
contaminants can affect RNA purity and
interfere with downstream analysis, including
cDNA conversion and PCR amplification.
High-throughput RNA-Seq of Low Input and
Clinically Derived FFPE Samples using Covaris
Adaptive Focused Acoustics® (AFA®) Technology
Authors: 1 - Madan Ambavaram, Sameer Vasantgadkar, Vanessa Process, Martina Werner, Ulrich Thomann,
Eugenio Daviso & 2 - Vincent Butty, Alexei Stortchevoi, Stuart Levine
Affiliation: 1 - Covaris, LLC, Woburn, MA, 01801 USA & 2 - MIT BioMicro Center, Cambridge, MA, 02139 USA
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• Heterogeneity: FFPE samples can exhibit
tissue heterogeneity, where different regions of
the tissue may undergo varying degrees of
fixation and preservation. This heterogeneity
can lead to variations in quality and yield within
a single FFPE sample, potentially affecting the
reliability and reproducibility of results.
Why Choose Covaris for RNA Shearing?
One promising solution to these challenges is the
use of Adaptive Focused Acoustics (AFA) technology,
available through Covaris Focused-ultrasonicators.
This technique utilizes focused ultrasound to shear
RNA with precise bursts of high-frequency acoustic
energy, which can be used to process samples of
varying quality.
Additionally, this workflow offers a robust and
seamless solution for both manual and automated
library preparation, ensuring reliable sequencing
results. By employing AFA-based sample preparation
and integrated shearing, this approach allows for
the comprehensive characterization of the entire
transcriptome, or a significant portion of it, in a single
experiment.
The Advantages of AFA-based RNA Shearing:
• Covaris shearing is agnostic to sample type and
quality, including highly degraded samples, and
shows minimal risk of over-fragmentation.
• Integrates into a broad spectrum of RNA-Seq
protocols with no observed trade-off to data
fidelity.
• Provides high-throughput preparation of
clinically derived samples with significant
reduction in hands-on time.
• Covaris shearing is suitable for low-input RNA
(≤2 ng) and supports a wide range of input
volumes and concentrations, providing reliable
sequencing data.
Novel RNA-Seq Workflow Using AFA-based RNA
Shearing
To assess the quality control metrics of AFA-based
RNA shearing, RNA libraries were prepared from
UHR RNA aliquots degraded to varying levels (RIN
range 1-9) using heat, as well as from 69 ‘real-world’
FFPE clinical samples, as described by Moiso et al
[3]. Briefly, 100 ng of RNA at 10 ng/μL from liver and
uterus tumor tissue was sonicated using a pulsing
protocol according to the Covaris R230 Quick Guide
(PN 010528) [4], following the specific settings and
sample volumes outlined in Table 1. The generalized
RNA-Seq workflow is illustrated in Figure 1A. After
sonication and library preparation, fragment sizes
were confirmed using gel electrophoresis (Figure 1B).
Libraries were prepared using RNA fragmented by
three different methods: Cation-based chemical
processing (Manual), Covaris with heat pre-treatment
at room temperature (Covaris R230 RT) and Covaris
with heat pre-treatment at 70 ˚C (Covaris R230 70 ˚C).
As shown by Pearson correlation analysis, no biases
were observed between replicates using Covaris
R230-prepared samples at room temperature and
at 70 ˚C (Figure 1B). Additionally, libraries prepared
with a minimum of 2 ng of sonicated RNA input were
highly homogenous and well correlated (Pearson >
0.99).
A key sequencing metric to assess RNA-Seq quality
is the average transcript length. Covaris sheared
libraries showed equivalent average transcript length
(Mean Log2 TPMs) compared to the manual method.
RNA-Seq data (Figure 1C) clearly demonstrated that
the 5’ and 3’ UTR coverage was similar or better to
standard RNA-Seq library prep methodologies, with
robustness across a range of GC content and no
evident bias against any RNA species (e.g. lncRNA,
protein coding genes, etc., unpublished data).
In summary, Covaris AFA technology is agnostic to
sample quality, making it ideal for processing RNA
from FFPE and low-input samples. This facilitates
easier and more cost-effective analysis of large
numbers of clinically derived samples, significantly
reducing hands-on time.
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Figure 1. A novel RNA-Seq workflow using Covaris AFA-based RNA fragmentation. Panel A shows a generalized RNA-Seq
workflow depicting various steps involved, from the source of samples to sequencing. Panel B shows the pre- and postshearing (heat and AFA based) of RNA from FFPE plus library prep profiles analyzed by gel-electrophoresis; the Pearson
correlation shows the high consistency among the replicates using Covaris shearing. Panel C shows the sequencing data
bar graphs for the average transcript length and UTR coverage.
Table 1. RNA from 69 FFPE tumor tissues of unknown origin sheared on the R230 using the 96 AFA-TUBE TPX Plate with
SonoLab 10.0.1. A time course is used to determine the optimal fragment sizes as needed for the library prep. The shearing
buffer and sample volumes are used as specified in the table.
Sample Type Instrument Sample Volume Sample Buffer Fragment size (nt) Vessel Plate Definition
RNA from FFPE
& UHR
R230 Focusedultrasonicator 10 µL 10 mM
Tris pH 8.0 300 PN 520291
R230_520291
96 AFA-TUBE TPX plate
+0.5 offset
Temp. PIP Duty Factor Cycles per Burst Dithering Total Treatment Time Delay Time Repeats
10 °C 200 W 25% 50 3 mm Y at
20 mm/s 60 seconds 10 seconds 6
Manual
Covaris R230 RT
Covaris R230 70 ˚C
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www.covaris.com | 2024© Covaris, LLC
M020183_RevA_Aug2024
Covaris and AFA are registered trademarks of Covaris, LLC. All other trademarks are the property of their respective owners. Information subject to change without notice.
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Learn more at covaris.com/application-technical-notes/
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Conclusion
Covaris and the MIT BioMicro center have developed
a novel approach for preparing RNA-Seq libraries
from clinically degraded samples using Adaptive
Focused Acoustics (AFA) for RNA sonication to
standardize fragment sizes. Shearing RNA using the
Covaris R230 enables high-throughput, unbiased
quantification of transcripts, whether degraded or
intact, without being limited to specific species.
This versatile technique can be used upstream
of standard ribosomal depletion-based RNA-Seq
library preparation. In contrast, other methods, such
as divalent cation-mediated RNA degradation (e.g.
Mg2+[5] and zinc-mediated RNA cleavage [6]), rely
on hydrolysis, resulting in a mix of 2′ or 3′ phosphate
ends on mononucleotides.
Expanding chemical-based fragmentation to a wide
array of non-uniform or clinical samples requires
significant time on a sample-by-sample basis or
the use of probes to capture only a subset of the
transcriptome. Our results demonstrate that Covaris
AFA-based RNA shearing provides equivalent
performance to cation-based fragmentation, without
the need for sample-specific tuning. This makes
Covaris shearing compatible with low-input RNASeq and high throughput workflows, offering less
hands-on time, faster turnaround, and high-quality
sequencing data.
References
1. Conroy JA, Stewart J, O’Rourke DM, Smith
MT, Hannon E, Murphy J. 2021. A scalable
high-throughput targeted next-generation
sequencing assay for comprehensive genomic
profiling of solid tumors. PLoS One. 16(4).
https://doi.org/10.1371/journal.pone.0260089
2. Mahat DB, Salamanca HH, Duarte FM, Lis JT.
2024. Single-cell nascent RNA sequencing
unveils coordinated global transcription. Nature.
616:98-107. https://www.nature.com/articles/
s41586-024-07517-7
3. Moiso E, Bagnato A, Di Vito C, Muratore M.
2022. Developmental deconvolution for
classification of cancer origin. Cancer Discov.
12(1):1-16. https://doi.org/10.1158/2159-8290.
CD-21-1443
4. Covaris. 2023. Covaris quick guide: DNA
shearing with R230 focused-ultrasonicator.
https://www.covaris.com/wp/wp-content/
uploads/resources_pdf/pn_010528.pdf
5. Guth-Metzler E, Tan H, Liu Y, Gomez A. 2023.
Goldilocks and RNA: where Mg2+ concentration
is just right. PubMed. https://pubmed.ncbi.nlm.
nih.gov/36987860/
6. Wery M, Lambert M, Guillemette B. 2013.
Zinc-mediated RNA fragmentation allows robust
transcript reassembly upon whole
transcriptome RNA-Seq. J Biomed Sci. 21(1):1-
9. https://www.sciencedirect.com/science/
article/abs/pii/S1046202313000789?via%3Dihub