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White Papers and Videos

Responding to a Pandemic

White Paper

ABC Labs, based at the Karolinska Institute campus in Stockholm, Sweden, was founded soon after the start of the pandemic to establish large-scale PCR and ELISA COVID-19 testing. The laboratory analyzes thousands of tests daily in partnership with Sweden’s Public Health Agency and regional and private healthcare providers.

This case study brief from Tecan describes how ABC Labs employed robotic workstations to scale up their PCR and serology testing over the course of the pandemic from hundreds of samples a day to nearly 20,000.

Semiconductor Technologies and System Concepts to Revolutionize Genomics

White Paper

This whitepaper from imec, one of the world’s leading R&D hubs with a strong track record in using its semiconductor expertise for developing next generation sequencing technologies, describes examples and concepts of how semiconductor technology can be utilized in genomics, transcriptomics, and proteomics to bring value to sample preparation, sequencing, and analysis.

Concepts include improving sample preparation with smart precision fluidics, improving sequencing with nanopore-based concepts for sensing and multi-electrode chips for spatial omics, and improving analysis with amalgamated machine learning for population genomics. These applications are integrated into a concept for a fast, inexpensive DNA sequencer that could eventually be used for point-of-care diagnostics.



From Panels to Exomes - Automating NGS Data Analysis at Veritas Genetics

White Paper

This white paper describes three clinical use cases in which Veritas Genetics, a personal genomics company, used Congenica next-generation sequencing (NGS) data analysis software to determine the genetic causes of patients’ conditions. These include the case of a 17-year-old patient with suspected Stickler syndrome, a 15-year-old patient with a history of developmental delay, and a 59-year-old visually impaired patient.

Single-Cell DNA Sequencing Resolves the Genetic Complexity Underlying Chronic Lymphocytic Leukemia Progression

White Paper

High-count monoclonal B-cell lymphocytosis (MBL) is an asymptomatic state that can evolve into chronic lymphocytic leukemia (CLL) when B-cells gain a cancer-inducing combination of driver mutations. In a recently published study, MBL patient samples were analyzed using bulk targeted deep sequencing. The researchers found that in a subset of cases, there were a significant number of mutations — in many cases, affecting the same genes.

To further gain insights into these MBL patient samples, single-cell DNA sequencing was performed on them using the Mission Bio Tapestri Platform and a 33-gene CLL amplicon panel. This application note shows that previously generated data from bulk sequencing were highly correlative to the newly generated single-cell data. The researchers unambiguously resolved co-occurrence and zygosity of all detected mutations to track clonal evolution and population expansion over time. These results show that single-cell DNA sequencing is a powerful tool for resolving clonal heterogeneity.

Single-Cell DNA Analysis With the Tapestri Platform and Nuclei From Metastatic Melanoma Tissue

White Paper

Recent advancements in genomic analysis of tumors have revealed that cancer disease evolves by a reiterative process of somatic variation, clonal expansion, and selection. Therefore, intra- and inter-tumor genomic heterogeneity has become a major area of investigation. While bulk next-generation sequencing methods have significantly contributed to our understanding of cancer biology and genomics, they overlook the genetic heterogeneity of a tumor at the level of the individual cell.

Here, the use of the Mission Bio Tapestri Platform demonstrates the power of single-cell, targeted DNA sequencing in characterizing solid tumor tissue samples and understanding disease evolution. Single-cell targeted DNA analysis was performed with the Tapestri Platform using sectioned melanoma metastatic tissues and normal liver tissue. An analysis of samples from separate metastatic sites in a single subject revealed unique genomic signatures in each sample.

Single-Cell DNA Analysis of Myelodysplastic Syndrome Using the Tapestri Single-Cell DNA AML Panel

White Paper

Myelodysplastic syndrome (MDS) is brought on by an accumulation of somatic mutations in hematopoietic stem cells resulting in ineffective hematopoiesis. Distinguishing mutational status at the single-cell level offers precision in diagnosis and informs treatment options, and clonal lineage reconstruction provides a comprehensive picture of the disease progression. MDS and acute myeloid leukemia (AML) are both myeloid disorders and can share overlapping molecular signatures.

In this technical note, the Tapestri Single-cell DNA AML Panel was used to analyze the mutational landscape of two patients with myelodysplastic syndrome (MDS). The results showed high sensitivity, clonal resolution, and concordance of variant allele frequency between single-cell and bulk next-generation sequencing data. Additionally, clonal variant co-occurrence was resolved, allowing for clonal lineage reconstruction and a more comprehensive picture of the patients’ disease.

Measuring the Efficiency of CRISPR Genome Editing Systems Using the Tapestri Platform and Tapestri Single-Cell DNA Custom Panels

White Paper

Genome editing systems are increasingly used to advance cell therapies, but edited cellular systems need to be thoroughly characterized to fully understand the nature of induced mutations and lower the risk of utilizing genome editing technologies. Both on- and off-target effects must be measured through high-sensitivity detection methods.

Single-cell resolution supports genome editing system optimization by enabling the detection of low-frequency events in as few as 0.1 percent of cells. Furthermore, single-cell data resolves the complexities of mutation zygosity and co-occurrence in genome-editing experiments targeting multiple loci. This technical note demonstrates the Tapestri Platform’s ability to characterize edited cells with single-cell DNA analysis to help optimize genome editing systems.

Copy Number Variants and Single Nucleotide Variants Simultaneously Detected in Single Cells

White Paper

Cancer begins with mutations in the DNA of a single cell. These mutations are often caused by single nucleotide variants (SNVs) and gene copy number variants (CNVs). Differences in SNVs and CNVs contribute to cancer heterogeneity, making some clonal populations more virulent and drug-resistant than others. Accurately defining clonal populations and reconstructing clonal phylogenies can only be achieved through single-cell analysis and is critical for informed clinical research. This application note describes a study demonstrating the ability of the Tapestri Platform to detect CNVs and SNVs simultaneously in single cells from cancer cell lines.

Tapestri Platform Resolves Clonality of Heterogeneous Mouse Organoid Cancer Model Through Single-Cell DNA Sequencing of Lentiviral Barcodes

White Paper

Bladder cancer exhibits high genomic heterogeneity, with an average of five mutations or more in the same tumor. Studying diverse higher-order genetic interactions that drive bladder cancer is difficult with current models of tumorigenesis, and it is limited by bulk sequencing which fails to directly discern clonality and resolve mutational co-occurrence patterns.

Dr. John Lee, of Fred Hutchinson Cancer Center, sought to better understand which combinations of mutations were critical by leveraging a mouse model, organoids, and gene-editing approaches. Using single-cell DNA sequencing, the Lee lab developed a system for investigating the functional impact of higher-order genetic interactions in cancer.

RNA and 5-Methylcytosine Epitranscriptomics

White Paper

Post-transcriptional modification of RNA adds a layer of information on top of the RNA sequence analogous to epigenetic changes in DNA. Some “epitranscriptomic” modifications can have profound effects on RNA stability, molecular recognition, and regulation of gene expression.

This application note from Glen Research describes advances in the study of epitranscriptomics, major types of RNA modifications, their roles in biology, and their implications in disease. The note examines a publication on the underlying mechanism of cytosine methylation in eliminating the tumor suppressor function of miRNA-181a-5p in a glioblastoma cell line. The results of the study may impact glioblastoma multiforme (GBM) patients since the loss of the tumor suppressor function of miRNA-181a-5p is associated with a poor prognosis.

Lifebit Powers Collaborative Research Environment for Genomics England on AWS

White Paper

During the COVID-19 pandemic, biobank Genomics England (GEL) launched an initiative with the UK government to deliver a cohort to eight leading pharmaceutical companies — as well as research organizations — to fuel vaccine, treatment, and early-detection research. The cohort included sequenced genomes from 20,000 COVID-19 patients with severe cases and 15,000 patients with mild cases, plus data from the GEL’s 100,000 Genomes Project.

Lifebit Biotech Ltd. uses Amazon Web Services (AWS) to power its federated research environment that enables collaborative research on disparate genomic datasets worldwide, maintains compliance with data privacy regulations, and processes more than 100 petabytes of project data. This whitepaper from AWS describes how Lifebit launched a research environment to study COVID-19 for GEL. Now, Lifebit CloudOS also powers GEL’s 100,000 Genomes Project on cancer and rare diseases.

Genomics on AWS: Accelerating Scientific Discoveries and Powering Business Agility

White Paper

The genomics landscape is rapidly evolving with the accelerated adoption of genomics by biopharma organizations, infectious disease tracing programs, and healthcare systems.

Amazon Web Services (AWS) helps genomics organizations transfer, store, aggregate, and interpret data as well as automate workflows and translate for clinical applications.

This whitepaper from AWS describes use cases in which genomics organizations such as Ancestry, DNAnexus, Grail, and Illumina employed AWS to reduce time to discovery, scale operations according to need, and reduce costs while operating securely, achieving regulatory compliance, and maintaining data sovereignty.

What You Always Wanted to Know About Single-Cell Sequencing


Single-cell RNA sequencing gives unprecedented insight into functions of individual cells in health and disease. Although single-cell sequencing is applicable for many biological systems, it lacks adoption in many fields. This is partially due to limiting factors such as cell size incompatibility, poly-A capture chemistry, or lack of customization options on high-throughput commercial single-cell isolation systems.

In this on-demand webinar, experts from Dolomite Bio and Illumina discussed the potential applications of high-throughput, single-cell RNA analysis across sample types and fields of biology.

High Throughput Analysis of Single-Cell Transcriptomes with Dolomite Bio’s Nadia Instrument

White Paper

Single-cell RNA sequencing enables simple and robust access to the transcriptomes of thousands of single cells — giving insight into tissues at single-cell resolution. This offers vital information about heterogeneity and cell-specific dynamics, which is key to understanding many diseases, immunity, development, and more.

The Dolomite Bio Nadia Instrument uses automation and flexibility to generate reproducible, high-quality single-cell data at high throughput to assay tens of thousands of cells whilst maintaining a low cost per cell. This application note describes results obtained from the encapsulation of single cells with barcoded mRNA capture beads for single-cell RNA sequencing using the Drop-seq protocol on the Nadia Instrument.

Optimizing Performance of Whole Transcriptome RNA-Seq Reference Materials

White Paper

Whole-transcriptome RNA-seq is one of the most effective methods for detecting genomic rearrangements in cancer. Enriching RNA samples with messenger RNA (mRNA) is an important step in sample preparation to avoid the muddling effects of less relevant RNAs. Poly-A selection targets the poly-A tails of mRNAs by binding them to oligo-dT sequences, but capture is not always optimal.

This whitepaper describes a study investigating whether extending the poly-A tails of clinically relevant fusion mRNAs in the Seraseq Fusion RNA Mix v4 reference material improves how efficiently they bind to oligo-dT columns during poly-A selection. The researchers found modest improvements in performance of reference materials after increasing the poly-A tail length.