10 years of QuantSeq: applications of 3’ mRNA-Seq in inspiring scientific discoveries

This year, Lexogen celebrates the 10th anniversary of QuantSeq, our flagship product and pioneering kit for 3′ mRNA sequencing library generation. In 2014, QuantSeq was featured in the Nature Application Note and has since gained its own momentum as the most cost-effective, reliable, and easy-to-use 3’ mRNA-Seq library preparation kit perfect for gene expression analysis. To date, QuantSeq has been used for RNA-Seq library preparation in more than 1600 publications, contributing to some pretty amazing discoveries. At Lexogen, we have always been passionate about providing useful and innovative transcriptomics solutions to the scientific community, and while we celebrate our QuantSeq, we also want to celebrate the work of our dear customers, our fellow scientists!

The QuantSeq family consists of several products all based on the innovative, well-established Lexogen technology: QuantSeq FWD, the perfect kit for gene expression profiling, QuantSeq REV, ideal for studying alternative polyadenylation, QuantSeq-Pool, the optimal solution for gene expression profiling for large screening projects, and QuantSeq FLEX, which allows generation of targeted RNA-Seq libraries from any RNA sample using custom primers.

We took a stroll down QuantSeq’s memory lane and delved into our collection of publications and webinars and selected some of the most inspiring and exciting scientific stories that showcase the power of QuantSeq and its various applications.

3′ end cleavage and polyadenylation of nascent RNA is an essential step in the maturation of most mRNAs, but also serves as an important regulatory mechanism of post-transcriptional gene expression. Genome-wide studies have estimated that more than 70% of mammalian genes undergo alternative polyadenylation (APA), in which mRNA transcripts from the same gene locus can have multiple 3′ ends. APA could alter the 3′ UTR by using different polyadenylation sites (pAs) in the terminal exon or result in different protein isoforms with different properties by using pAs in the upstream exonic/intronic regions or by splicing an altered last exon.

One of the first publications using QuantSeq was published in 2016, on the very topic of APA.

APA is regulated by both cis-elements and trans-factors. However, compared to the extensively studied transcription and alternative splicing, the extent of APA divergence during evolution and the relative cis- and trans-contribution were largely unexplored. To directly address these questions for the first time in mammals, the authors used deep sequencing-based methods to measure APA divergence between two different mouse strains. QuantSeq was used for 3′ mRNA-Seq to quantify APA usage by counting the number of reads with the 5′ end within the reference APA cluster.

In 2016, we also hosted one of our first Lexogen webinars on the topic of mapping nuclear-exosome targeted poly(A) tails with 3′ mRNA-Seq (and advantages of 3′ mRNA-Seq over a standard RNA-Seq approach), presented by Kevin Roy, PhD, at the time a postdoctoral researcher at Stanford University School of Medicine.

In 2017, we have had a very exciting webinar, on how the analysis of the transcriptome of carriers of pathological variants that cause Alzheimer’s Disease was used to deepen the understanding of this disease.

Alzheimer’s disease is a neurodegenerative disease and the cause of 60–70% of cases of dementia. In its essence, it is a multifactorial disease, the result of complex interactions between risk factors that cause pleiotropic changes in molecular networks between various biological processes. The identification of mutations in the amyloid-beta precursor protein (APP), and PSEN1 and PSEN2 genes that cause Mendelian forms of Alzheimer’s disease, represented key milestones for understanding the initial mechanisms and pathways involved in the pathogenesis of this disease. Remarkably, variants in these genes confer different transcriptomic profiles, and mutation carriers clustered separately from their non-carrier siblings. New evidence provide support for both neuronal and glial specific pathways contributing to pathogenesis, still little is understood about how the genetic loci and molecular changes are organized into common networks.

Dr. Oscar Harari, PhD from the Department of Psychiatry at Washington University in St Louis, talked about his lab’s research, where they combined transcriptomic cell-type profiling and network co-expression analyses to study postmortem brains of carriers of Alzheimer’s disease Mendelian mutations in PSEN1, PSEN2 and APP genes. Using digital deconvolution approaches, researchers obtained cell-type specific expressions, and confirmed the distribution of neuros, microglia, oligodendrocytes, and astrocytes in a collection of more than 1500 Alzheimer’s disease and non-demented subjects. As a result, they mapped gene regulatory networks employing the expression corrected for the distinct cell-type distributions, and identified modules that cluster genes that harbor variants usually associated with both early-onset autosomal dominant (PSEN1) and late-onset sporadic classifications of Alzheimer’s disease (SOD1, BACE1, PICALM, SLC4A2).

QuantSeq was used to prepare 3′ mRNA-Seq libraries for gene expression profiling prior to applying correction for the distinct cell-type distributions.

In 2018 we have hosted a webinar presented by Dr. Adriana Zingone from the National Cancer Institute, Center for Cancer Research, on the characterization of alternative polyadenylation in the lung cancer transcriptome, testing a hypothesis that smoking modulates differential usage of polyadenylation sites within mRNA transcripts. Namely, in cancer, APA is emerging as an alternative mechanism for proto-oncogene activation in the absence of somatic mutations, and studies at that time suggested a correlation of APA profiles with cancer prognosis. In addition, global shortening of the 3’UTR appears to be a hallmark of many types of cancer.

To be able to study APA in lung tumor tissue, the authors have utilized the power of QuantSeq REV, that enables so called 3’UTR mRNA-Seq by generating 3’ mRNA-Seq libraries directly targeting the 3’ end of polyadenylated transcripts.

Staying with the topic of the lungs, but this time focusing on the pulmonary fibrosis, a complex and challenging disease involving the progressive replacement of alveolar tissue with fibrotic scars, that adversely affect breathing, we have selected a study where the authors focus on single-cell RNA sequencing (scRNA-Seq) to provide insights into the pathobiology of pulmonary fibrosis. As we explain in one of our recent blog articles, scRNA-Seq is a method of choice to study cell heterogeneity, which is exactly what the authors wanted to focus on. Their aim was to understand if there is a disease-related heterogeneity within alveolar macrophages, epithelial cells, or other cell types in lung tissue from patients with pulmonary fibrosis compared with control subjects. To create a detailed molecular atlas of the pathobiology of pulmonary fibrosis, they have combined data stemming from scRNA-Seq, bulk RNA-Seq of whole-lung tissue and flow cytometry–sorted alveolar macrophages and alveolar type II cells (using our QuantSeq FWD) and in situ RNA hybridization (i.e. a method used to localize a specific RNA sequence in a part or section of tissue).

Automation of RNA-Seq protocols saves hands-on time, maximizes throughput, and avoids pipetting and sample tracking errors.

To provide educational content on how to set up an automation protocol for RNA-Seq, we have hosted a webinar with Dr. Michael D. Wilson, from the Canada Research Chair in Comparative Genomics, University of Toronto, who talked about:

• how to establish and evaluate automated RNA-Seq library methods,
• how to take advantage of automated 3’ UTR-Seq library preparation to scale up the gene expression studies in model organisms, and
• all the important considerations when implementing automated RNA-Seq library methods in a clinical setting.

In addition, we get a lot of questions on automation of QuantSeq protocols. Lexogen supports the implementation of automated QuantSeq protocols for 3’ mRNA-Seq library preparation.

QuantSeq is already successfully implemented on the following platforms / liquid handlers:

• Perkin Elmer: Sciclone®/ Zephyr®;
• Hamilton: Microlab STAR / STARlet;
• Agilent: NGS Workstation (NGS Bravo Option B);
• Beckman Coulter: Biomek FXP, Biomek i5, Biomek i7;
• Eppendorf: EpMotion® 5075;
• Opentrons® OT-2.

Automation on other platforms is also possible. If you are interested in automation, please get in touch with us at support@lexogen.com, and our amazing Technical Support team will advise you.

In cancer research, the analysis of formalin-fixed paraffin-embedded (FFPE) cancer tissues sampled from cancer patients, is an extremely valuable source of gene expression information, especially since fresh tissues are only available for only a short time, and not to many researchers. However, it is important to understand if, and in what way, transcription profiles differ between freshly isolated cancer tissues and those flesh frozen or FFPE ones. Our webinar “Unlocking the Transcriptomic Potential of FFPE Cancer Samples: A Cross-Platform Comparison Study”, held by Dr Arran K. Turnbull, deals with exactly this topic. The webinar focuses on a study that compared nine different transcriptomic analysis technologies, including our QuantSeq, with matched fresh-frozen (FF) and formalin-fixed paraffin-embedded (FFPE) cancer tissues.

QuantSeq is a well established technology for gene expression analysis from FFPE samples as outlined in many cancer research studies, for example, Taber, A., Christensen, E., Lamy, P. et al. (bladder cancer FFPE tissue), Mehine, M., Khamaiseh, S., Ahvenainen, T. et al. (uterine leiomyomas), Quintela-Fandino, M., Holgado, E., Manso, L. et al. (breast cancer tissue), Haughey, C.M., Mukherjee, D., Steel, R.E., et al. (prostate cancer tissue), and many more.

We have developed a special protocol for QuantSeq 3′ mRNA-Seq FWD and REV kits for FFPE samples.

In their groundbreaking publication in Nature Genetics, Jaeger, M.G et al., showed that the human Mediator is a general coactivator that facilitates transcription globally but is strictly required for the functionality of cell-type-specifying gene regulatory circuits.

Mediator complex was identified over 30 years ago as a molecular connector that allows transcription factors to communicate with the cellular gene-copying machine RNA polymerase II (Pol II), to activate target genes by initiating transcription at tens of thousands of sites in human cells. Mediator is organized into biochemically separable functional modules/subunits. To understand the direct role of the Mediator complex in the process of transcription technologies that rapidly block Mediator function and measure changes in Pol II activity within the subsequent minutes are required. Using targeted protein degradation, and generating endogenously tagged, degradation-sensitive Mediator subunits in human cell line, researchers managed to rapidly remove individual parts of the Mediator complex. Like this, they could get access to transcriptional fingerprints of individual subunit degradation and allowed them to determine whether the copying of all human genes depends to the same extent on Mediator integrity.

QuantSeq (along with SIRV-Set 3 spike-in RNA-Seq controls) was used for spike-in-normalized 3′ mRNA sequencing, that served to obtain transcriptional fingerprints of individual subunits.

In 2020, Dr Andrew Beggs gave a very interesting webinar on how whole transcriptome sequencing combined with 3′ mRNA-Seq can be used to gain many interesting insights into the underlying disease processes in colorectal cancer. In the webinar a project that performed stratified analysis of patients as a pre-pilot for the 100,000 Genomes project was presented, and the importance of RNA-Seq in the multi-omics approach in clinical cancer diagnostics was discussed.

From publications featuring QuantSeq published in 2021, we have chosen a study by Hallegger M, Chakrabarti AM, Lee FCY, et al., published in Cell, where the role of RNA binding protein (RBP) condensation in the specificity and function of protein-RNA complexes was explored in a context of amyotrophic lateral sclerosis (ALS).

ALS is a fatal motor neuron disease, characterized by progressive degeneration of nerve cells in the spinal cord and brain. A viral social media challenge initiated in 2014, the famous “Ice Bucket Challenge”, brought wide awareness to this debilitating disease, and became a great example on how popularization of a disease in the mass public can, not just bring awareness, but fuel scientific research. Namely, donations collected because of the challenge enabled The ALS Association to tremendously increase its annual funding for research. During this time, ALS researchers made scientific advances, care for people living with ALS expanded, and investment in disease research from the federal government grew.

Conducting basic research and answering basic research questions is at the core of the fight against human diseases. Hallegger and colleagues focused on one of the basic research aspects, on studying the involvement of TDP-43, a central RBP involved in the pathogenesis of ALS. Researchers created TDP-43 variants in several different cell systems, introducing mutations into TDP-43 that change the condensation properties of this RBP. Using UV crosslinking and immunoprecipitation (iCLIP) and 3′ mRNA-Seq, the authors showed that TDP-43 condensation promotes its efficient assembly on a subset of RBPs characterized by unique sequence features, including a highly multivalent arrangement of GU-rich motifs. Martina Hallegger gave a Lexogen webinar in 2022, diving deep into this publication, and her research that helps the fight against ALS.

Astrocytes are specialized cell type of the central nervous system (CNS). They become reactive in response to various insults to the CNS, however, the understanding of underlying molecular mechanisms was lacking. Understanding of these mechanisms would prompt development of therapeutics to selectively modulate different aspects of inflammatory astrocyte reactivity.

In the publication we chose to feature, authors used CRISPR interference screening in human induced pluripotent stem cell (hiPSC)-derived astrocytes, combined with single-cell transcriptomics to investigate inflammatory astrocyte reactivity induced by various cytokines (i.e. signaling proteins of the immune system). By doing so, they could identify two distinct inflammatory reactive signatures, one promoted by STAT3 (i.e. transcriptional factor important in the inflammatory signaling) and the other inhibited by STAT3. QuantSeq was used for bulk RNA-Seq library prep in iAstrocytes (hiPSC-derived astrocytes) and iNeurons (hiPSC-derived neurons), to look at the transcriptional signature of these cell types upon stimulation with different cytokines.

2023 was a great year for QuantSeq-featured publications! We have decided to feature the publication by Villanueva, E. et al. (published in Nature Methods) that was presented last year as Lexogen’s on-demand webinar (RNA-Protein Interactions in space and time). The authors have developed an integrative approach that enables a cell-wide mapping of RNA and protein subcellular localization, by combining localization of RNA (LoRNA) and a streamlined density-based localization of proteins by isotope tagging (dLOPIT) methods. These multi-omics technologies were used to generate the most comprehensive system-wide quantitative map of both RNA and protein subcellular localization so far and to study reorganization of the transcriptome and proteome after activation of the unfolded protein response.

Since launching QuantSeq, Lexogen has developed many innovative products to help researchers to study the transcriptome. Lexogen’s products have a lot of synergies and can be used in a holistic approach as seen in the study by Villanueva, E. et al. In this study, a whole array of Lexogen’s products was used:

• CORALL, a whole transcriptome library preparation kit in combination with RiboCop, to deplete ribosomal RNA, to map the RBP network.
• SIRVs, spike-in RNA variants for normalization, and
• QuantSeq for differential sedimentation speed-based cell fractionation experiment

Lexogen continues to innovate RNA sequencing technologies, always working on bringing new products to the market and developing add-ons for the existing ones. Stay tuned!