Over the past 5 years, single-cell genomics have become a powerful technology for studying small samples and rare cells, and for dissecting complex populations such as heterogeneous tumors. Single-cell technology is enabling many new insights into diverse research areas from oncology, immunology and microbiology to neuroscience, stem cell and developmental biology. This webinar introduces single-cell technology and summarizes the newest scientific applications in various research areas, all in the context of current literature.
The study of the complete set of RNAs (transcriptome) encoded by the genome of a specific cell or organism at a specific time or under a specific set of conditions is called Transcriptomics.
Transcriptomics aims:
I. To catalogue all species of transcripts, including mRNAs, noncoding RNAs and small RNAs.
II. To determine the transcriptional structure of genes, in terms of their start sites, 5′ and 3′ ends, splicing patterns and other post-transcriptional modifications.
III. To quantify the changing expression levels of each transcript during development and under different conditions.
The study of the complete set of RNAs (transcriptome) encoded by the genome of a specific cell or organism at a specific time or under a specific set of conditions is called Transcriptomics.
Transcriptomics aims:
I. To catalogue all species of transcripts, including mRNAs, noncoding RNAs and small RNAs.
II. To determine the transcriptional structure of genes, in terms of their start sites, 5′ and 3′ ends, splicing patterns and other post-transcriptional modifications.
III. To quantify the changing expression levels of each transcript during development and under different conditions.
Step by Step, from Liquid Biopsy to a Genomic Biomarker: Liquid Biopsy Series...QIAGEN
Liquid biopsies enable us to monitor the evolution of genetic aberrations in primary tumors as they shed the tumor cells into the circulation. The limitation is the ability to detect these low frequency genetic aberrations in a consistent manner to understand short- and long-term implications and how this information will be used in the clinic. This slidedeck will cover the challenges and solutions associated with multiple steps as one starts with liquid biopsy and move towards finding a new biomarker.
The transcriptome of a cell is not fixed, but is dynamic, and reflects the function or type of the cell, the cell stage or the cell's response to intrinsic and extrinsic influences, such as signaling or stress factors. Only on a single cell level, can you eliminate the biological noise that is inherent to standard gene expression analysis – providing you the insights needed for a deeper understanding of transcription dynamics. In this presentation we delve into the different steps of RNA seq starting from a single cell.
Today it is possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). The main advantage of scRNA-seq is that the cellular resolution and the genome wide scope makes it possible to address issues that are intractable using other methods, e.g. bulk RNA-seq or single-cell RT-qPCR. However, to analyze scRNA-seq data, novel methods are required and some of the underlying assumptions for the methods developed for bulk RNA-seq experiments are no longer valid.
Applications of Single-Cell Sequencing: Innovative and Tailor-Made ServicesInsideScientific
Join Bastiaan Bijl, MSc, and Dylan Mooijman, PhD, as they provide an introduction to single-cell sequencing and its potential applications with user cases.
As a scientist, you have probably come across the use of single-cell sequencing in your field. Single-cell RNA sequencing can be used for almost every biological question that requires a detailed understanding of a cell population, and therefore has many different applications. But what is it exactly? How was it invented? How can you apply it to your research, which technology should you choose, and what do you need to think about before starting your project?
In this webinar we provide answers to these questions, discuss the single-cell sequencing technologies that we offer, and our options for custom and R&D projects. Furthermore, our head of R&D dived into some use cases to provide more insight into the applications of single-cell sequencing.
Key Topics Include:
- Understand what single-cell sequencing is and how it was invented
- How to apply single-cell sequencing with user cases
- Learn more about Single Cell Discoveries tailor-made approach and latest R&D projects
Next Generation Sequencing (NGS) Is A Modern And Cost Effective Sequencing Technology Which Enables Scientists To Sequence Nucleic Acids At Much Faster Rate. In This Presentation, You Will Learn About What is NGS, Idea Behind NGS, Methodology And Protocol, Widely Adapted NGS Protocols, Applications And References For Further Study.
Utilization of NGS to Identify Clinically-Relevant Mutations in cfDNA: Meet t...QIAGEN
Pancreatic cancer is a uniquely lethal malignancy characterized by frequent mutations in KRAS, CDKN2A, SMAD4, TP53 and many others. We have shown that KRAS mutation can be detected in cell-free, circulating tumor DNA (ctDNA) isolated from the plasma in a subset of patients and is associated with poor prognosis. The ability to simultaneously detect multiple pancreatic cancer-specific mutations in ctDNA would open a new avenue for detection of clinically-relevant mutations. In this study, we performed ultra-deep sequencing of ctDNA from advanced pancreatic cancer patients prior to treatment with Gemcitabine and Erlotinib following target enrichment. Somatic, non-synonymous variants were identified in 29 different genes at allele frequencies typically less than 0.5%. Updated results of ultra-deep NGS analysis will be presented.
Total RNA Discovery for RNA Biomarker Development WebinarQIAGEN
Precision medicine offers to transform patient care by targeting treatment to those with most to gain. To date the most significant advances have been at the level of DNA, for example, the use of somatic DNA alterations as diagnostic indicators of disease and for prediction of pharmacodynamic response. Development of RNA expression signatures as biomarkers has been more problematic. While RNA expression analysis has yielded valuable insights into the biological mechanisms of disease, RNA is a more unstable molecule than DNA, and more easily damaged or degraded during sample collection and isolation. In addition, RNA levels are inherently dynamic and gene expression signatures are extraordinarily complex. Recently, much progress has been made in identifying key changes in gene expression in cancer and other diseases, as well as identifying expression signatures in circulating nucleic acid that have the potential to be developed into diagnostic and prognostic indicators.
Noncoding RNAs in Cardiovascular Disease – Potential as Biomarkers and MoreQIAGEN
Cardiovascular diseases (CVD) are the leading cause of death worldwide, and are therefore the subject of intense, urgent research. Biomarkers could help physicians diagnose heart diseases early, for example, and better therapies could improve survival or healing following events like myocardial infarction. Small noncoding RNAs called microRNAs have recently stepped into the spotlight as circulating biomarkers for a number of diseases, and may also have utility in someday treating CVD more effectively. In this slide deck, we discuss why and how microRNAs are being investigated as biomarkers for CVD, as well as examining some recent findings in the field. Check it out to find out how scientists are investigating noncoding RNA involvement in CVD and how you can do the same in your laboratory!
Step by Step, from Liquid Biopsy to a Genomic Biomarker: Liquid Biopsy Series...QIAGEN
Liquid biopsies enable us to monitor the evolution of genetic aberrations in primary tumors as they shed the tumor cells into the circulation. The limitation is the ability to detect these low frequency genetic aberrations in a consistent manner to understand short- and long-term implications and how this information will be used in the clinic. This slidedeck will cover the challenges and solutions associated with multiple steps as one starts with liquid biopsy and move towards finding a new biomarker.
The transcriptome of a cell is not fixed, but is dynamic, and reflects the function or type of the cell, the cell stage or the cell's response to intrinsic and extrinsic influences, such as signaling or stress factors. Only on a single cell level, can you eliminate the biological noise that is inherent to standard gene expression analysis – providing you the insights needed for a deeper understanding of transcription dynamics. In this presentation we delve into the different steps of RNA seq starting from a single cell.
Today it is possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). The main advantage of scRNA-seq is that the cellular resolution and the genome wide scope makes it possible to address issues that are intractable using other methods, e.g. bulk RNA-seq or single-cell RT-qPCR. However, to analyze scRNA-seq data, novel methods are required and some of the underlying assumptions for the methods developed for bulk RNA-seq experiments are no longer valid.
Applications of Single-Cell Sequencing: Innovative and Tailor-Made ServicesInsideScientific
Join Bastiaan Bijl, MSc, and Dylan Mooijman, PhD, as they provide an introduction to single-cell sequencing and its potential applications with user cases.
As a scientist, you have probably come across the use of single-cell sequencing in your field. Single-cell RNA sequencing can be used for almost every biological question that requires a detailed understanding of a cell population, and therefore has many different applications. But what is it exactly? How was it invented? How can you apply it to your research, which technology should you choose, and what do you need to think about before starting your project?
In this webinar we provide answers to these questions, discuss the single-cell sequencing technologies that we offer, and our options for custom and R&D projects. Furthermore, our head of R&D dived into some use cases to provide more insight into the applications of single-cell sequencing.
Key Topics Include:
- Understand what single-cell sequencing is and how it was invented
- How to apply single-cell sequencing with user cases
- Learn more about Single Cell Discoveries tailor-made approach and latest R&D projects
Next Generation Sequencing (NGS) Is A Modern And Cost Effective Sequencing Technology Which Enables Scientists To Sequence Nucleic Acids At Much Faster Rate. In This Presentation, You Will Learn About What is NGS, Idea Behind NGS, Methodology And Protocol, Widely Adapted NGS Protocols, Applications And References For Further Study.
Utilization of NGS to Identify Clinically-Relevant Mutations in cfDNA: Meet t...QIAGEN
Pancreatic cancer is a uniquely lethal malignancy characterized by frequent mutations in KRAS, CDKN2A, SMAD4, TP53 and many others. We have shown that KRAS mutation can be detected in cell-free, circulating tumor DNA (ctDNA) isolated from the plasma in a subset of patients and is associated with poor prognosis. The ability to simultaneously detect multiple pancreatic cancer-specific mutations in ctDNA would open a new avenue for detection of clinically-relevant mutations. In this study, we performed ultra-deep sequencing of ctDNA from advanced pancreatic cancer patients prior to treatment with Gemcitabine and Erlotinib following target enrichment. Somatic, non-synonymous variants were identified in 29 different genes at allele frequencies typically less than 0.5%. Updated results of ultra-deep NGS analysis will be presented.
Total RNA Discovery for RNA Biomarker Development WebinarQIAGEN
Precision medicine offers to transform patient care by targeting treatment to those with most to gain. To date the most significant advances have been at the level of DNA, for example, the use of somatic DNA alterations as diagnostic indicators of disease and for prediction of pharmacodynamic response. Development of RNA expression signatures as biomarkers has been more problematic. While RNA expression analysis has yielded valuable insights into the biological mechanisms of disease, RNA is a more unstable molecule than DNA, and more easily damaged or degraded during sample collection and isolation. In addition, RNA levels are inherently dynamic and gene expression signatures are extraordinarily complex. Recently, much progress has been made in identifying key changes in gene expression in cancer and other diseases, as well as identifying expression signatures in circulating nucleic acid that have the potential to be developed into diagnostic and prognostic indicators.
Noncoding RNAs in Cardiovascular Disease – Potential as Biomarkers and MoreQIAGEN
Cardiovascular diseases (CVD) are the leading cause of death worldwide, and are therefore the subject of intense, urgent research. Biomarkers could help physicians diagnose heart diseases early, for example, and better therapies could improve survival or healing following events like myocardial infarction. Small noncoding RNAs called microRNAs have recently stepped into the spotlight as circulating biomarkers for a number of diseases, and may also have utility in someday treating CVD more effectively. In this slide deck, we discuss why and how microRNAs are being investigated as biomarkers for CVD, as well as examining some recent findings in the field. Check it out to find out how scientists are investigating noncoding RNA involvement in CVD and how you can do the same in your laboratory!
RNA Integrity and Quality – Standardize RNA Quality Control QIAGEN
RNA integrity and quality are critical to obtain meaningful and reliable downstream data. This slidedeck details the challenges and considerations of handling RNA samples, the need for quality control analysis and common methods for RNA integrity and quality assessment. The QIAxcel Advanced System will be introduced to automate the process of RNA sample integrity analysis and obtain objective quality measurement. Application data will be presented.
The Presence and Persistence of Resistant and Stem Cell-Like Tumor Cells as a...QIAGEN
Epithelial ovarian cancer is the fifth leading cause of cancer-related deaths of women in the United States and Europe and ranks as the second most common type of gynecological malignancy. Most cases are diagnosed in advanced stages and although the response rates to platinum-based chemotherapy are high, the majority of patients nevertheless have poor survival rates. Although the reasons for these poor outcomes are likely to be multifactorial, one particular area of interest has recently focused on hematogenous tumor cell dissemination that has been shown to originate from disseminated tumor cells (DTCs) in the bone marrow (BM) and circulating tumor cells (CTCs) in the blood. Here, we demonstrate that the negative prognostic impact of CTCs and DTCs arise from specific cellular phenotypes and are associated with platinum-resistance and stem cell-associated proteins.
CTC Detection and Molecular Characterization – Challenges and SolutionsQIAGEN
Circulating Tumor Cells (CTCs) have been extensively explored as circulating biomarkers in various cancers. Due to their rarity, heterogeneity and stem cell-like properties, detecting and profiling CTCs from blood samples is very challenging. In this webinar, Dr. Siegfried Hauch will introduce the well-known AdnaTests, which uses the Combination of Combinations Principle (COCP) to enable enriching and detecting CTCs in whole blood with high specificity and sensitivity, and how to overcome challenges in CTC enrichment and detection. The AdnaTests combine an immunomagnetic capturing method that increases purity, and is followed by molecular profiling of the captured CTCs. In addition, leukocyte contamination is another issue in CTCs detection and may lead to false positive results due to illegitimate expression of target genes or false interpretation. The AdnaWash is developed to reduce leukocyte contamination to such a level that whole gene panels can be analyzed while maintaining the required specificity and sensitivity.
Improved Reagents & Methods for Target Enrichment in Next Generation Sequencing, presented by Dr Mark Behlke, Chief Scientific Officer at Integrated DNA Technologies
New Progress in Pyrosequencing for Automated Quantitative Analysis of Bi- or ...QIAGEN
Pyrosequencing is a highly flexible technology based on sequencing-by-synthesis for the rapid and quantitative analysis of any type of sequence variation. The real-time output delivers high-resolution sequence information, making pyrosequencing highly suitable for applications ranging from biallelic or multiallelic SNP analysis, DNA methylation quantification to complex mutation analysis of multiple sequence variations in a single run.
In this slideeck, we introduce the new PyroMark Q48 Autoprep system which enables fully automated template preparation integrated in the pyrosequencing workflow. In addition, a new Multiple Primer Dispensation (MPD) strategy is presented which allows fully automated dispensation of sequencing primer, offering a seamless workflow from samples to quantitative genotyping results.
This slidedeck focuses on the following topics
• Pyrosequencing technology and workflow in genotyping analysis
• Introduction into the new PyroMark Q48 Autoprep
• MPD strategy for a seamless automated pyrosequencing workflow
Join us and learn how you can apply the new pyrosequencing system and protocol to your variant analysis or genotyping research
Back to Basics: Fundamental Concepts and Special Considerations in gDNA Isola...QIAGEN
In this slidedeck, we provide tips for a whole range of sample types that require special consideration. Topics include the basic methods and challenges of RNA purification, special considerations for challenging sample types, and isolating miRNA and extracellular RNA.
Liquid biopsy: Overcome Challenges of Circulating DNA with Automated and Stan...QIAGEN
Circulating cell-free DNA (ccfDNA) originating from malignant tumors, a developing fetus and also from inflammatory tissues, is present in the cell-free nucleic acids in plasma, serum and other body fluids and is considered a “liquid biopsy”. Access to ccfDNA for analysis allows for specific detection of certain disease states based on a simple blood sample. Circulating cell-free DNA shows distinctive properties – it is present mostly as shorter fragments of less than 500 bp and the concentration of ccfDNA in a plasma or serum sample is low (approximately 1–100 ng/ml) compared to cellular materials and varies considerably between different individuals.
Because of their fragmented nature and low concentration, ccfDNA presents a particular challenge for efficient extraction / purification and quantification, such as by qPCR. We present data on solutions for the following critical problems concerning the purification of ccfDNA for research and molecular diagnostic applications:
• Pre-analytical workflow (blood processing) for analyzing ccfDNA
• Optimization of ccfDNA extraction from plasma samples: low target concentrations require efficient ccfDNA enrichment from larger sample volumes
• Novel automated extraction of ccfDNA using the QIAsymphony SP instrument for liquid biopsy diagnostic applications.
Analysis and Interpretation of Cell-free DNAQIAGEN
Identification and monitoring of cancer mutations from cell free DNA-Seq data is a key application in liquid biopsy. In this part of the webinar we will show how mutations can be best identified from this type of data and how they can be interpreted. Furthermore, potential challenges when analyzing this type of data will be discussed together with relevant strategies.
The Molecular Analysis on Circulating Tumor Cells to Determine Prognostic and...QIAGEN
Circulating tumor cells (CTCs) is an emerging source used molecular cancer diagnostics. Through expression profiling of CTCs, it allows a deeper understanding about which metabolic pathways enable tumor cells to survive in the circulation, how they become resistant to a drug regimen, how they transform and adapt and, finally, which cellular markers should targeted for future therapies.
This webinar will introduce the AdnaTest CTC detection platform which has been proven in several clinical trials to provide prognostic and predictive information in breast, ovarian and prostate cancer. The platform by itself is still open for research and allows access to any potential target of interest. Join us to learn more about this novel platform, its technology and applications in liquid biopsy.
Liquid Biopsy Overview, Challenges and New Solutions: Liquid Biopsy Series Pa...QIAGEN
A liquid biopsy is often described as a sensitive and specific blood test to detect circulating tumor cells (CTCs). CTCs, shed by both the primary and metastasized tumors, carry specific information about their origins and markers that will enable us to discover new diagnosis, prognosis and therapeutic targets. This slidedeck gives an overview of the recent progress in exploring the predictive potential of circulating biomarkers, including circulating tumor cells, circulating tumor DNA, microRNAs, long non-coding RNAs (lncRNAs) and exosomes. Addressing both biological and technical aspects, we detail the isolation and characterization of circulating biomarkers. Challenges and solutions are also featured.
Single-Cell Analysis - Powered by REPLI-g: Single Cell Analysis Series Part 1QIAGEN
What can you do from a single cell? Actually, quite a lot! Beginning with the genome, you can discover new biomarkers by identifying new genetic variances and their association with specific diseases, including cancers. Moving on to RNA, the recent advances in RNA sequencing technology have made single-cell transcriptomics a possibility. Along with these possibilities, come challenges that start from the moment you get the sample to the final step of gaining insights into the cell. This slidedeck will provide an overview on the multiple steps involved as you move from sample acquisition to analysis and data interpretation in different sample types.
The Main Advantage
The main advantages of flow cytometry over histology and IHC is the possibility to precisely measure the quantities of antigens and the possibility to stain each cell with multiple antibodies-fluorophores, in current laboratories around 10 antibodies can be bound to each cell. This is much less than mass cytometer where up to 40 can be currently measured, but at a higher and slower pace.
Aquatic research
In aquatic systems, flow cytometry is used for the analysis of autofluorescing cells or cells that are fluorescently-labeled with added stains.
This research started in 1981 when Clarice Yentsch used flow cytometry to measure the fluorescence in a red tide producing dinoflagellates
Marine scientists use the sorting ability of flow cytometers to make discrete measurements of cellular activity and diversity, to conduct investigations into the mutualistic relationships between microorganisms that live in close proximity,and to measure biogeochemical rates of multiple processes in the ocean
Cell Proliferation assay
Cell proliferation is the major function in the immune system. Often it is required to analyse the proliferative nature of the cells in order to make some conclusions. One such assay to determine the cell proliferation is the tracking dye carboxyfluorescein diacetate succinimidyl ester (CFSE). It helps to monitor proliferative cells. This assay gives quantitative as well as qualitative data during time-series experiments
Cell counting
Cell sorting
Determining cell characteristics and function
Detecting microorganisms
Biomarker detection
Protein engineering detection
Diagnosis of health disorders such as blood cancers
Flow cytometry can be used for cell cycle analysis to estimate the percentages of a cell population in the different phases of the cell cycle, or it can be used with other reagents to analyze just the S phase.
Why flow cytometry is ideal for cell cycle analysis
Live-cell cycle analysis stains—Vybrant DyeCycle stains
Classic DNA cell cycle stains such as Hoechst 33342 and DRAQ5 for cell cycle analysis, but most of these have limitations that have to be considered when using them in an experiment which is why the Invitrogen Vybrant DyeCycle stains for live-cell cycle analysis were developed.
Fixed-cell cycle analysis stains FxCycle reagents
We offer classic DNA cell cycle stains such as DAPI, PI, and 7-AAD for fixed cell cycle analysis, but these reagents do not cover the full spectrum of laser excitation available.
The FxCycle reagents offer options for the 405 nm (violet) and 633 nm (red) laser thereby increasing the ability to multiplex by freeing up the 488 nm and 633 nm lasers for other cellular analyses such as immunophenotyping, apoptosis analysis, and dead cell discrimination.
Precise—Accurate cell cycle analysis in living cells
Safe—Low cytotoxicity for combining with additional live cell experiments
Cell sort compatible—Easily sort cells based on phase of the cell cycle
Single cell analysis has exploded recently mainly due to the development of high-throughput technologies such as NGS. Single cell analysis is being pursued by researchers in many areas including developmental science, cancer, biomarker discovery and more. This presentation covers some of the recent applications from developed by QIAGEN customers.
Analysis of Single-Cell Sequencing Data by CLC/Ingenuity: Single Cell Analysi...QIAGEN
Single-cell analysis is useful to study genetic heterogeneity between individual cells and can help in result interpretation by looking at the average behavior of a large number of cells. Applications include circulating tumor cells, cells from small biopsies and cells from in vitro fertilized embryos. In this slidedeck, we show how single cell next-generation sequencing data can be analyzed and what challenges needs to be overcome. One of the examples we use is single cell data from two colorectal cancer cell lines.
DNA sequence analysis and genotyping of biological samples using innovative instrumentation, such as next-generation sequencing (NGS) platforms, is often limited by the small amount of sample available. The REPLI-g Single Cell Kit is specially designed to uniformly amplify genomic DNA from single cells (1 to <1000 bacterial or tumor cells) or purified genomic DNA with complete genome coverage. Additional protocols are also available for use with fresh or dried blood or fresh or frozen tissue. Dedicated buffers and reagents undergo a unique, controlled decontamination procedure to avoid amplification of contaminating DNA, ensuring highly reliable results every time. Accurate amplification of genomes with negligible sequence bias and no genomic drop-outs is achieved with innovative Multiple Displacement Amplification (MDA) technology. In contrast to PCR-based WGA technologies, high fidelity rates are increased up to 1000-fold, avoiding costly false positive or negative results.
DNA fingerprint methods. • The locations for genes for specific traits such as egg number, body weight or carcass quality can be identified using markers and then they can be selected directly.
From Panels to Genomes with VarSeq: The Complete Tertiary Platform for Short ...Golden Helix
From gene panels to whole genome, from short to long-read sequencing, the VarSeq suite is the solution for NGS analysis and reporting in a modern clinical lab. VarSeq handles the spectrum of variant types (SNV, Indel, CNV, Fusions) and provides automated classification and reporting capabilities following the ACMG and AMP guidelines. With our new PacBio partnership, we are more adaptable than ever with creating a spectrum of custom workflows to suit our unique user needs.
This webcast will review:
-Data analysis scaling from Gene Panel to Genome analysis with VarSeq and VSWarehouse.
-Analysis and annotation of SNVs, Indels, CNVs, and fusions.
-A close look at a PacBio long-read trio analysis.
Come join us for this showcase in modern VarSeq analysis capabilities.
Using methylation patterns to determine origin of biological material and ageQIAGEN
In this QIAGEN sponsored webinar, our guest speakers from the San Francisco Police Department (SFPD) Crime Lab and Florida International University (FIU) discuss their research on the potential of epigenetic methylation as a procedure for body fluid identification and age estimation from DNA left at crime scenes. Several approaches have been studied, including an analysis of methyl array data and an initial validation of procedures such as pyrosequencing and real-time PCR. The presentation focuses on a number of tissue-specific epigenetic markers for body fluid and age determination with a promise of future integration of these markers into the forensic lab due to the simplicity of analysis and the ease of application.
Learn more about the Pyrosequencing technology and our solutions at
https://www.qiagen.com/resources/technologies/pyrosequencing-resource-center/
Take lung cancer research to a new molecular dimensionQIAGEN
Circulating Tumor Cells (CTCs) can provide researchers with important new discoveries on the mechanism of cancer. Find out more about the latest technology that provides researchers the necessary tools to conduct CTC research in lung cancer.
Circulating Tumor Cells (CTCs) can provide researchers with important new discoveries on the mechanism of cancer. Find out more about the latest technology that provides researchers the necessary tools to conduct CTC research in AR-V7 related prostate cancer.
Learn about the power of LNA (Locked Nucleic Acid) technology and QIAGEN's LNA enhanced product portfolio for RNA and DNA research. Download the slide deck!
Take your RNA research to the next level with QIAGEN LNA tools!QIAGEN
Download the flyer!
Experience truly exceptional RNA research with QIAGEN's next-generation, LNA®-enhanced tools. LNA (Locked Nucleic Acid) oligos bind with much higher affinity and specificity to RNA targets than standard DNA and RNA oligos – This enables specific and sensitive detection of small RNAs and discrimination between highly similar
sequences.
An Approach to De-convolution of Mixtures in Touch DNA Samples. Download now!QIAGEN
7th QIAGEN Investigator Forum - Lisbon, March 8, 2018 . An Approach to De-convolution of Mixtures in Touch DNA Samples. Presenter: Lisa Dierig, Institute of Legal Medicine, Ulm
Assessment of Y chromosome degradation level using the Investigator® Quantipl...QIAGEN
Assessment of Y chromosome degradation level using the Investigator® Quantiplex® Pro RGQ Kit, presented by Dr. Tomasz Kupiec, Head of the Forensic Genetics Section, Institute of Forensic Research, Krakow, Poland on June 14, 2018.
ICMP MPS SNP Panel for Missing Persons - Michelle Peck et al.QIAGEN
Optimization and Performance of a Very Large MGS SNP Panel for Missing Persons, by Michelle Peck et al., International Commission on Mission Persons. Presented May 3, 2018, at the QIAGEN Investigator Forum, San Antonio, TX.
Exploring the Temperate Leaf Microbiome: From Natural Forests to Controlled E...QIAGEN
The aerial surfaces of plants, the phyllosphere, harbors a diverse community of microorganisms. The increasing awareness of the potential roles of phyllosphere microbial communities calls for a greater understanding of their structure and dynamics in natural and urban ecosystems. To do so, we characterized the community structure and assembly dynamics of leaf bacterial communities in natural temperate forests of Quebec by comparing the relative influence of host species identity, site, and time on phyllosphere bacterial community structure. Second, we tested the value of characterizing a tree’s complete phyllosphere microbial community through a single sample by measuring the intra-individual, inter-individual and interspecific variation in leaf bacterial communities. Third, we quantified the relationships among phyllosphere bacterial diversity, plant species richness, plant functional diversity and identity, and plant community productivity in a biodiversity-ecosystem function experiment with trees. Finally, we compared tree leaf bacterial communities in natural and urban environments, as well as along a gradient of increasing anthropogenic pressures. The work presented here thus offers an original assessment of the dynamics at play in the tree phyllosphere.
Cancer Research & the Challenges of FFPE Samples – An IntroductionQIAGEN
A cascade of complex genetic and epigenetic changes regulate tumor formation and progression. Gene expression analyses can shed light on these changes at a molecular level and identify the key genes and associated pathways involved in cancer. Often the samples used in cancer research are FFPE samples, which pose a significant challenge in terms of nucleic acid quality. The quality of nucleic acids extracted from FFPE samples depends on a number of factors, including how the samples were handled before, during and after fixation and embedding.
Dr. Vishwadeepak Tripathi describes the variability of sample purification from FFPE samples – in particular, samples to be used in cancer research. What are the challenges and solutions, and what quality control approach can ensure credible results? This webinar will focus on sample purification and the quality control of FFPE samples and compare different automated purification procedures.
Introduction to real-Time Quantitative PCR (qPCR) - Download the slidesQIAGEN
This slidedeck introduces the concepts of real-time PCR and how to conduct a real-time PCR assay. The topics that are covered include an overview of real-time PCR chemistries, protocols, quantification methods, real-time PCR applications and factors for success.
The Microbiome of Research Animals : Implications for Reproducibility, Transl...QIAGEN
The human gut microbiota (GM) has emerged as a key factor in susceptibility to, as well as a potential biomarker of, several diseases and conditions. Similarly, researchers now appreciate that the GM of laboratory animals could affect the reproducibility and translatability of many disease models, including a complete loss of phenotype. While associations between characteristics of the GM and differential disease model phenotypes are of concern, they can also be viewed as sources of discovery related to disease pathogenesis. As such, there is considerable interest in factors that inadvertently influence the composition of the GM and methods of manipulating the GM prospectively to investigate such associations and standardize or optimize disease models. The webinar will present data on variables capable of influencing the GM of laboratory rodents citing several examples and animal models, considerations related to manipulation of the GM in mice and rats, and recent data supporting the use of “dirty” mice in biomedical research.
Building a large-scale missing persons ID SNP panel - Download the studyQIAGEN
In this webinar, we will take a look at a large-scale SNP-based forensic identification panel for DNA analysis with massively parallel sequencing (MPS). The panel was specifically designed for the challenges of identifying missing persons; where DNA is frequently highly degraded, and relationship tests may involve reference samples from across several generations and in a deficient pedigree.
Rapid DNA isolation from diverse plant material for use in Next Generation Se...QIAGEN
Isolation of DNA from plant material is often a tedious process which involves significant hands on time and leads to varying results due to the diverse nature of the material. Different parts of the plants as well as the plants themselves differ in both consistency of material and presence of inhibitory substances, making dependable isolation of DNA difficult.
Here, we developed a method for the efficient extraction of DNA from different plant types, including strawberry leaf, pine needle, grape leaf, and cotton and coffee seeds (workflow at right). A novel bead beating method and lysis chemistry led to more efficient sample lysis with minimal hands-on time and significantly increased DNA yield compared to conventional methods. Through the use of multiple technologies to improve removal of secondary metabolites, such as polyphenols, complex polysaccharides, alkaloids and tannins that may inhibit downstream applications, the isolated DNA was of high quality and purity.
The resulting DNA is suitable for immediate use in downstream reactions, including PCR, qPCR and Next Generation Sequencing based applications. Using this method we were further able to design a workflow that included DNA isolation, library preparation and bioinformatics analyses for the efficient detection of plant pathogens isolated from infected samples. With this, our protocol is a substantial improvement within workflows used for plant microbiome and plant pathology studies as well as in plant breeding and engineering.
Rapid extraction of high yield, high quality DNA from tissue samples - Downlo...QIAGEN
Genetic and genomic analysis from tissue samples requires the extraction of high quality DNA. Mechanical disruption methods such as bead milling provide high yield from tissue samples, but cause damage to the nucleic acids. Purely enzymatic methods such as proteinase K digestion can extract nucleic acid without damage, but require long incubation times, often proceeding overnight, and without approaching the yields achieved by mechanical disruption techniques. Thus a method is needed which can provide a rapid extraction of high yield, high quality DNA from tissue samples. See the new method.
Critical Factors for Successful Real-Time PCR: Multiplex PCRQIAGEN
Multiplex end-point PCR is a powerful tool for genotyping and many other applications. QIAGEN’s multiplex PCR chemistry is optimized for reliable amplification of many different templates with high variability in copy numbers. Thus it enables very quick establishment of a new lab routine and instant success for your multiplex PCR strategy.
There is a set of critical factors which we recommend to be regarded for planning and performing this kind of PCR. These will be discussed in detail in the webinar. Additionally, our multiplex PCR chemistry has recently been gaining increasing popularity among scientists who are utilizing it for their next-generation sequencing workflows.
Practical hints and new solutions for successful real-time PCR studies QIAGEN
Part 1: Practical hints and new solutions for successful real-time PCR studies
In this webinar we will cover the following topics which are critical steps for efficient and precise gene expression studies using real-time PCR technology:
- Effect of RNA integrity on real-time PCR results – tips to achieve a true RNA profiling suitable for real-time PCR studies
- Improved methods for cDNA synthesis, optimized for real-time PCR
- Real-time PCR analysis
o Real-time PCR essentials and background information on different quantification strategies
o SYBR Green real-time PCR – factors influencing specificity
o Introduction to probe technology
o New, fast and efficient real-time PCR solutions
Part 2: Critical Factors for Successful Multiplex Real-Time PCR
Multiplex real-time PCR is a powerful tool for gene expression analysis, viral load monitoring, genotyping, and many other applications. The ability to amplify and detect several genomic DNA, cDNA, or RNA targets in the same reaction offers many benefits:
• Conservation of precious samples – more quantification data per sample
• Increased throughput – more targets analyzed per run on a cycler
• Reliable results – no well-to-well variability due to co-amplification of internal control
• Reduced costs – save time and reagents
The QuantiFast Multiplex PCR and RT-PCR kits are optimized for reliable amplification of many different templates despite a high variability in abundance. Thus they enable successful amplification of multiple targets on the first attempt without optimization.
This webinar explains the principles of the QIAGEN multiplex technologies and shows data demonstrating the exceptional multiplex real-time PCR performance of the QuantiFast Multiplex kits.
Overcome the challenges of Nucleic acid isolation from PCR inhibitor-rich mic...QIAGEN
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Advances and Applications Enabled by Single Cell Technology
1. Sample to Insight
Advances and applications enabled by single cell
technology
1
Miranda Hanson-Baseler, Ph.D.
Miranda.Hanson-Baseler@qiagen.com
2. Sample to Insight
Legal disclaimer
2
QIAGEN products shown here are intended for molecular biology
applications. These products are not intended for the diagnosis,
prevention or treatment of a disease.
For up-to-date licensing information and product-specific
disclaimers, see the respective QIAGEN kit handbook or user
manual. QIAGEN kit handbooks and user manuals are available at
www.QIAGEN.com or can be requested from QIAGEN Technical
Services or your local distributor.
3. Sample to Insight
Agenda
3
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions
1
2
3
4. Sample to Insight
Agenda
4
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions
1
2
3
5. Sample to Insight
Overview of single cell technology
5
• Why study single cells?
o Scarce sample
o Genome heterogeneity
o Transcriptome heterogeneity
o Statistical power
• Basic parts of a single cell workflow
o Cell isolation
o WGA or WTA
o Analytical techniques
o Data analysis
• QIAGEN products for single cell analysis
6. Sample to Insight
You start with only one single cell
6
• A single mammalian cell
contains <0.01% the DNA
required by a typical NGS
library prep
• A single mammalian cell
contains 10–30 pg of total
RNA, only 1–5% of the
total RNA is mRNA
Standard NGS
library prep
input:
100–1000ng
Bacterium Mammalian cell 200 µl Blood
1 µg
1 ng
1 pg
1 fg
Average DNA content
This is log
scale! In linear
scale, you
would not even
see bars for the
bacterial or
mammalian cell
Limited availability of DNA or RNA requires a preamplification step
7. Sample to Insight
Cells differ on the genome level
7
Genome variations occur in health and disease
(1) Iourov, I.Y. et al. (2010) Somatic Genome Variations in Health and Disease, Curr Genomics 11(6)
• Somatic genome variations are:
o Aneuploidy
o Structural rearrangements
o Copy number variations
o Gene mutations
• Somatic genome variations
o Occur during normal development /
aging
o Contribute to pathogenesis
o Are the cause of diseases like cancer,
autoimmune, brain and other diseases
Examples (1):
• Aneuploidy in pre-implantation embryos
occurs in 15–91% of samples
• Aneuploidy in skin fibroblasts occurs in
adults
o Middle age: in 2.2% of cells
o Aged: in 4.4% of cells
• Almost all cancers are caused by
different types of genome variations
including aneuploidy/polyploidy,
structural rearrangements, gene
amplifications, gene mutations
8. Sample to Insight
Similar cells – unique transcriptional patterns
8
Cells change their transcription pattern:
• The transcriptome of a cell is not fixed but
dynamic
• The transcriptome reflects the
o Function of the cell
o Type of the cell
o Cell stage
• Gene expression is influenced by intrinsic or
extrinsic factors (signaling response, stress
response)
• Only on single cell level you get:
o Real (not average) transcriptome gene
expression data
o Allelic expression data
o A deeper understanding of the transcription
dynamics within a cell
Heat map of single cell RNA-seq data
for selected pluripotency regulators (1)
(1) Kumar L.M. et al. (2014) Deconstructing transcriptional heterogeneity in pluripotent stem cells. Nature 4;516
9. Sample to Insight
Averaging averages
9
The basic unit of research we are often interested in is the cell. But we usually analyze
populations of cells and this can:
• Lead to false positives from underestimating biological variability
• Miss important biological divisions
0 0
0 3
0 0
0 0
0 0
0 6
0 6
0 0
0,938
Biological Sample 1
Biological Sample 2
Population
Mean 2
1
Single Cell
Analysis
Population
Mean 1
Mean=0.969
Stdev=1.470
Sample Size=32
SEM=0.260
1 1
1
1 1
1 1
1 1
1 1
1 1
1 1
1
Mean=0.969
Stdev=0.048
Sample Size=2
SEM=0.031
Bulk
Approach
10. Sample to Insight
Single cell analysis enables new insights
10
CTC=Circulating tumor cells, PGD=Pre-implantation genetic diagnosis
Cellular
heterogeneity
Detection and analysis of
rare cells (example: CTC
from liquid biopsy)
Identification of cell
subpopulations based on
genomic structure or gene
expression (tumors, tissues,
immune cells, cell cultures)
Limited
availability of
cells
Analysis of limited sample
material (example: embryo
biopsy for PGD, fine-needle
aspirates)
Reasons ApplicationReason
Biological insights instead of average results
No Data
Bulk result Single cell data
11. Sample to Insight
Single cell workflow overview
11
In general, single cell molecular biology
experiments follow this workflow:
• Obtain primary sample
• Detect and isolate cell of interest
• Lyse cell (often integrated with WGA or
WTA)
• Whole genome or whole transcriptome
amplification (for DNA/RNA studies)
• Analytical technique of choice (NGS
library prep and sequencing, gene panels,
real-time PCR, microarrays, Sanger
sequencing)
• Data analysis and interpretation
12. Sample to Insight
Single cell genomics – the workflow
12
Analysis
Data
analysis
Whole genome
amplification
(WGA)
Whole
transcriptome
amplification
(WTA)
NGS
qPCR
qRT-PCR
Microarray
Arrays
Data analysis
Biological
interpretation
Preamplification
The right preamplification method in your workflow is key
13. Sample to Insight
Technologies for DNA or RNA preamplification
13
Types of preamplification technologies:
PCR-based
-Degenerative oligo-primer
PCR (DOP-PCR)
-Multiple annealing and
looping based amplification
cycles (MALBAC)
PCR-free
-Multiple displacement
amplification (MDA)
-Single primer isothermal
amplification (SPIA)
Whole Genome/Transcriptome Amplification Technologies
14. Sample to Insight
Multiple displacement amplification (MDA) by QIAGEN
14
QIAGEN’s REPLI-g technology method
• Primers (arrows) anneal to the template
• Primers are extended at 30°C as the polymerase
moves along the gDNA or cDNA strand displacing
the complementary strand while becoming a
template itself for replication.
In contrast to PCR amplification, MDA:
• Does not require different temperatures
• Ends in very long fragments with low mutation
rates
15. Sample to Insight
Comparison of WGA methods for single cell WGS(1)
15
Genome
coverage
(0,1x / 30x)
Cumulative
depth
distribution
(2)
Consensus
genotypes
detection
efficiency
(30x)
Duplication
rate in deep-
sequencing
30x
Mean depth
(x)
CNV
detection
sensitivity
CNV
detection
specificity
DOP-PCR
(5) 6 % (0,1 x)
23 % (30x)
6 % 6 % 39% 3 x 94%
(3)
94 %
(3)
MALBAC
(6) 8 % (0,1x)
82 % (30x)
47 % 52 % 13% 21x 85%
(4)
85 %
(4)
REPLI-g
Single Cell
Kit
9 % ( 0,1x)
98 % (30x)
82 % 85 % 3,6% 34 x 86%
(4)
81 %
(4)
Best in class for variations calling!
(1) Hou, Y. et al. (2015) Comparison of variations detection between whole-genome amplification methods used in single cell resequencing.
GigaScience 4:37
(2) Deep-sequencing (30x) to evaluate amp bias
(3) Simulated data
(4) Real data
(5) DOP-PCR2: degenerate-oligonucleotide-primed PCR
(6) MALBAC: multiple annealing and looping-based amplification cycles
Optimal solution if SNV and CNV are of similar importance, as
in tumor heterogeneity or cell evolution research
Best performance
Medium performance
Lowest performance
16. Sample to Insight
Get the most out of a single cell with Sample to Insight solutions
16
Complete Sample to Insight Solutions for Single Cell Applications
WGA, WTA or both
• REPLI-g portfolio
Cell isolation
• Coming soon
Analytical techniques
• REPLI-g NGS Library Prep kits
• GeneRead Panels
• RT2 Profiler PCR arrays
• Wide variety of available tools
Data Analysis and Interpretation
• CLC bioinformatics software
• Ingenuity variant and pathway analysis
17. Sample to Insight
Single Cell
Multiple Cells
Tissue
Blood
gDNA
RNA
single cell DNA
Sequencing
single cell RNA
sequencing
REPLI-g Single
Cell DNA
Library Kit
REPLI-g Single
Cell RNA
Library Kit
NGS
Library
NGS
single cell DNA
analysis
single cell RNA
analysis
Comparative
analysis of DNA
and RNA
(25+ cells)
REPLI-g
Single Cell
Kit
REPLI-g
WTA Single
Cell Kit
REPLI-g Cell
WGA & WTA
Kit
Amplified
WTA-DNA or
WGA-DNA
NGS
Microarray
qPCR
17
Choosing a REPLI-g Single Cell Kit for your application
Starting material Application Q solution Kit output Analysis
19. Sample to Insight
Wide array of applications for single cell analysis
19
WGA
or
WTA
Whole Genome Sequencing
• Detect variability in genome sequence (SNV, microsatellites, etc.)
• Variability in genome structure (CNV, structural rearrangements, aneuploidy)
• De novo sequencing of new, unidentified and unculturable organisms
Targeted Resequencing
• Detect variability in a target set of genes or region of the genome
Microarrays
• Use SNP-chips to genotype thousands of loci
mRNA-seq
• Detect variability in transcript abundance for all expressed genes
• Detect variability in isoform structure and abundance
qRT-PCR profiling
• Profile gene expression for a targeted set of transcripts
• Accurately quantify specific splice-junctions, isoforms or other structural
features
20. Sample to Insight
REPLI-g advantages
20
• Minimal background
• High yield
• Integration with PCR-free NGS library prep
• Even coverage (manifests as better assembly, fewer drop-outs, better
transcript detection)
• Fewer sequence errors
21. Sample to Insight
Lower background with REPLI-g
21
Bacterial DNA (2000 copies) was spiked into
REPLI-g sc Reaction Buffer, which was then
decontaminated using the standard procedure for
all buffers and reagents provided with the REPLI-
g Single Cell Kit. In subsequent real-time PCR, no
bacterial DNA was detectable.
The PCR-free REPLI-g kits offer:
• Minimal background:
o Kits are produced to exceptionally
high standards and reagents
undergo a unique manufacturing
process which virtually eliminates
any chance of contamination
22. Sample to Insight
High yield: wide range of applications
22
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield:
o Kits produce 10 µg or more of
amplified cDNA or gDNA from a
single cell
o Library prep kits produce 2-4 nM
of PCR-free sequencer-ready
whole genome or RNAseq library
Starting Material Typical Yield
REPLI-g Single Cell RNA
Library Prep
Single cell or purified total RNA (50 pg-100 ng) 2-4 nM PCR-free NGS Library
REPLI-g Single Cell DNA
Library Prep
Single cell or purified gDNA (10 pg-10 ng)
2-4 nM PCR-free NGS Library
REPLI-g Single Cell Single cell or purified gDNA (1-10 ng) 40 µg amplified gDNA
REPLI-g WTA Single Cell Single cell or purified total RNA (10 pg-100 ng) 40 µg amplified poly(A+) cDNA
REPLI-g Cell WGA &
WTA
25+ cells
WTA: 10-20 µg, depending on
protocol
WGA: 20 µg
23. Sample to Insight
Completely PCR-free NGS workflows
23
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep:
o REPLI-g single cell DNA and RNA library kits produce NGS-
ready libraries from a single cell in as little as 5.5 hours
REPLI-g Single Cell DNA Library Kit
Cell lysis
15 min
WGA
3 h
Shearing and
purification
30-60 min
End-repair
50 min
A-addition
40 min
Adapter
ligation
10 min
Cleanup and
size selection
15 min
REPLI-g Single Cell RNA Library Kit
Cell lysis
15 min
Sequencing
Data Analysis
Interpretation
gDNA
Removal
10 min
Reverse
Transciption
1 h
Ligation
35 min
WTA
2 h
One-tube
One-tube
One-tube
24. Sample to Insight
Even coverage in whole genome sequencing
24
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS library prep
• Even Coverage:
o Superior genome coverage due to even
amplification: fewer drop-outs, missed
loci and more accurate quantification
o Important for NGS as well as traditional
applications
1 pg DH10B DNA, amplified with either REPLI-g Single Cell Kit
or by MALBAC, sequenced on MiSeq Illumina (V2, 2x150nt.)
25. Sample to Insight
Higher fidelity: fewer sequencing errors
25
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS
library prep
• Even Coverage
• Fewer sequence errors:
o Polymerase has ~1000x better
proofreading activity than Taq
o Lack of PCR means errors
introduced aren’t propagated
26. Sample to Insight
Key for evaluating SNV
26
The PCR-free REPLI-g kits offer:
• Minimal background
• High Yield
• Integration with PCR-free NGS
library prep
• Even Coverage
• Fewer sequence errors
o Polymerase has ~1000x better
proofreading activity than Taq
o Lack of PCR means errors
introduced aren’t propagated
o ~10x better error rate than
MALBAC(1); essential for SNV
analysis
REPLI-g SC MALBAC
Total Reads 3 187 060 3 327 084
Mapped reads 3 176 341
(99,66%)
3 276 090
(98,47%)
Not mapped 10 719 (0,34%) 50 994 (1,53%)
Broken read pairs 284 017 (8,91% of
total reads)
314 550 (9,45% of
total reads)
Covered bases in
Reference
98,69% 95,82%
Insertions 6 3
Deletions 0 6
Single-nucleotide
variation
0 222
(1) Bourcy et al. (2014) PLoS ONE 9(8): e105585. doi:10.1371/journal.pone.0105585
27. Sample to Insight
Summary
27
Advantages of single cell analysis over bulk data:
• Analyze scarce materials
• Account for genomic and transcriptomic heterogeneity
Parts of a single cell workflow:
• Obtaining primary sample, detecting and isolating cells of interest
• Lysis, WGA or WTA, and variety of molecular biology methods
• Data analysis and interpretation
QIAGEN products for single cell analysis
REPLI-g enables single cell applications via:
• Minimal background
• High yield
• Integration with PCR-free NGS library prep
• Even coverage (manifests as better assembly, fewer drop-outs,
better transcript detection)
• Fewer sequence errors
28. Sample to Insight
Agenda
28
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions
1
2
3
29. Sample to Insight
Agenda
29
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions
2
1
3
30. Sample to Insight
REPLI-g : Accelerating single cell research
30
0
100
200
300
400
500
600
700
800
2009 2010 2011 2012 2013 2014 e2015
Number of
publications (1)
Year
(1) http://scholar.google.com, search term „single cell genomics“
(2) http://scholar.google.com, search term „single cell“ replig 2009– e2015
e2015: extrapolated total number for 2015 extrapolated from numbers YTD Sep 2015
Over 450 cumulative
publications featuring
QIAGEN‘s REPLI-g(2)
Number of single cell genomics
publications / year (1)
(1) Van Loo, P. and Voet, T. (2014) Single cell analysis of cancer genomes, T. Current Opinion in Genetics and Development,24:
(2) Yao, X. et al. (2014) Tumor cells are dislodged into the pulmonary vein during lobectomy., J Thorac Cardiovasc Surg.148(6)
(3) Wang, Y.. et al. (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing, Nature 512
(4) Zhang, C.-Z. et al. (2015) Chromothripsis from DNA damage in micronuclei. Nature, published online 27 May 2015
31. Sample to Insight
REPLI-g advancing research in many areas like:
31
Cancer research
Neuroscience or
stem cell research
Embryo genetic
research
Single cell
genomics
Superior variant calling, analysis of SNVs and CNVs and genomic
rearrangements. Census-based low-pass single cell seq powered by REPLI-g
Identifying clonal and mutational evolution or
structural rearrangements in cancer cells
Rare cell identification and characterization towards liquid
biopsy research
Circulating tumor
cells
Improving aneuploidy analysis, genome-wide SNP typing
and advancing NGS-based approaches
Analysis of cellular functions and mechanisms
Metagenomics
Sensitive microbial species profiling from environmental samples,
overcoming difficult to culture organisms
Infectious disease,
microbial research
Resolving multiple genotype infections, reveal information on
relatedness and drug resistance genotypes
32. Sample to Insight
Rare cell identification and characterization (2)
Identifying clonal and mutational evolution (3)
Analysis of genomic rearrangements (4)
Advancing cancer research
32
REPLI-g cited for:
(1) Van Loo, P. and Voet, T. (2014) Single cell analysis of cancer genomes, T. Current Opinion in Genetics and Development,24:
(2) Yao, X. et al. (2014) Tumor cells are dislodged into the pulmonary vein during lobectomy., J Thorac Cardiovasc Surg.148(6)
(3) Wang, Y.. et al. (2014) Clonal evolution in breast cancer revealed by single nucleus genome sequencing, Nature 512
(4) Zhang, C.-Z. et al. (2015) Chromothripsis from DNA damage in micronuclei. Nature, published online 27 May 2015
Figure Van Loo, P. and Voet, T. (1)
single cell analysis of the cancer genome
33. Sample to Insight
Advancing cancer research: REPLI-g in the literature
33
Yao, X. et al. (2014) Tumor cells are dislodged into the pulmonary vein during lobectomy. J.
Thoracic Cardiovasc. Surg. 148(6), 3224–3331
Aim: Determine the contribution of intraopertive tumor shedding to
tumor recurrence, using single cell genetic approaches to distinguish
between normal and malignant epithelial cells.
Methods:
• WGA using REPLI-g Single Cell Kit
• Amplicon sequencing
• Library prep
• Barcoded pools sequenced
• Analysis of copy number variation, nested PCR-based
mutation analysis if single cells and targeted sequencing
Findings: Single cell genetic approaches together with patient-matched
normal and tumor tissues can accurately quantify the number of shed
tumor cells.
34. Sample to Insight
Advancing cancer research: REPLI-g in the literature
34
Wang, Y. et al. (2014) Clonal evolution in breast cancer revealed by single nucleus genome
sequencing. Nature 512, 155–160.
Aim: Develop a high-coverage method for whole genome and
exome single cell sequencing to study the genomic diversity within
tumors
Methods:
• MDA was performed on FACS-sorted nuclei using REPLI-g
technology
• Sequence libraries were first sequenced at low coverage
depth
• Libraries pass QC were selected for full genome or exome
sequencing
Findings: The method shows excellent performance, with uniform
coverage, low allelic dropout rates and low false positive error rates
for point mutations
35. Sample to Insight
Advancing cancer research: REPLI-g in the literature
35
Yee, S.S. et al. (2016) A novel approach for next-generation sequencing of circulating tumor
cells. Mol. Gen. Genomic Med. 4(1) doi: 10.1002/mgg3.210
Aim: Develop a method for improved noninvasive
detection of evolving tumor mutations
Methods: REPLI-g Single Cell Kit was successfully
used for WGA when combined with a multiplex
targeted resequencing approach
Findings: Proof of concept study for real-time
monitoring of patient tumors using noninvasive
liquid biopsies
36. Sample to Insight
NGS-based strategies for improved aneuploidy
research (1) and mutation analysis (3)
Genome-wide SNP genotyping for high-resolution
molecular cytogenetic analysis (2)
Improving reproductive genetics research
36
REPLI-g cited for:
(1) Wells, D. et al. (2015) Clinical utilisation of a rapid low-pass whole genome sequencing technique for the diagnosis of aneuploidy in human
embryos prior to implantation. J Med Genet. 2014 Aug;51(8)
(2) Thornhill, A.R. et al. (2015) Karyomapping—a comprehensive means of simultaneous monogenic and cytogenetic PGD: comparison with standard
approaches in real time for Marfan syndrome, Journal of Assisted Reproduction and Genetics, Volume 32
(3) Xu, J. et al. (2015) Embryo Genome Profiling by single cell Sequencing for Preimplantation Genetic Diagnosis in a β-Thalassemia Family Clinical
Chemistry 61:4
(4) Wang, L. et al. (2014) Detection of Chromosomal Aneuploidy in Human Pre-implantation Embryos by Next Generation Sequencing, Biology of
Reproduction March 19,2014
Sequencing strategy for assessing chromosome
copy number change (4)
Figure taken from Wang, L. (4)
37. Sample to Insight
The analysis of functional mechanisms in neurons by single cell qPCR,
following single cell WTA of total RNA from neurons (1), (2)
Advances in neuroscience
37
REPLI-g cited for:
(1) Jeong, J.H. (2015) Cholinergic neurons in the dorsomedial hypothalamus regulate mouse brown adipose tissue metabolism, MOLECULAR
METABOLISM 4
(2) Lee, D. et al. (2015) Apelin-13 Enhances Arcuate POMC Neuron Activity via Inhibiting M-Curren. PLoS ONE 10(3):
e0119457.doi:10.1371/journal.pone.0119457
Both studies used REPLI-g WTA Single Cell Kit
38. Sample to Insight
Advances in metagenomics
38
Metagenomics and microbial single cell genomics
• Recently emerged due to advancements in WGA, NGS and bioinformatics
• Publicly available metagenomics data is continuously growing
o Portals: IMG/MG, EBI metagenomics, iMicrobe or MG-RAST
• Eloe-Fadrosh et al. discovered and described a new bacterial candidate phylum
(Candidatus Kryptonia) from samples collected from 4 geothermal springs
o Metagenomics data mining and single cell sampling
o REPLI-g Single Cell Kit used for WGA of isolated single bacterial cells
Eloe-Fadrosh, E.A. et al. (2016) Global metagenomic survey reveals a new bacterial candidate phylum in geothermal springs. Nat.
Commun. 7, Article number: 10476 doi:10.1038/ncomms10476
39. Sample to Insight
Resolving multiple-genotype malaria infections and revealing
information on relatedness and drug resistance genotypes (1)
Virome determination directly on clinical samples by multiplexed whole-
genome sequencing from low total virus content samples (2)
Whole genome sequencing as a tool in the diagnosis and
characterization of norovirus(3)
Infectious disease / microbial research
39
REPLI-g cited for:
(1) Nair, S. et al. (2014) single cell genomics for dissection of complex malaria infections, Genome Res. 2014. 24:1028-1038
(2) Zoll, J. et al. (2015) Direct multiplexed whole genome sequencing of respiratory tract samples reveals full viral genomic information, Journal of Clinical
Virology 66 (2015) 6–11
(3) Bavelaar, H.H. (2015) Whole genome sequencing of fecal samples as a tool for the diagnosis and genetic characterization of norovirus. J. Clin. Virol.
72, 122.
40. Sample to Insight
Dissecting complex malaria infections
40
Nair, S. et al. (2014) single cell genomics for dissection of complex malaria infections, Genome
Res. 2014. 24:1028-1038
• Described an optimization of a single cell genomics approach for malaria parasites that is
applicable to both cultivable and noncultivable malaria species to reveal within-host variation
• The approach included isolation of single infected red blood cells, whole genome
amplification and then genotyping and sequencing the parasites using next-generation
sequencing
• After analysis of >260 single cell assays, the protocol was validated with coverage equivalent
to state-of-the-art single cell methods with >99% accuracy
o The high success of the method resulted from optimized procedures that included WGA
with the REPLI-g Mini and Midi Kits combined with a simple freeze-thaw step prior to
DNA extraction
41. Sample to Insight
Diagnosis and characterization of norovirus
41
Bavelaar, H.H. (2015) Whole genome sequencing of fecal samples as a tool for the diagnosis
and genetic characterization of norovirus. J. Clin. Virol. 72, 122.
• Noroviruses are classified into 5 genogroups, of which only GI, GII and GIV infect humans.
Each genogroup is further divided into multiple genotypes.
o GII.4 is extremely recombinant and new strains of this genotype replace old strains
approximately every 2–3 years
• Methods: Direct multiplexed whole genome sequencing on fecal samples from patients with
gastroenteritis
o Sufficient amounts of RNA were isolated from all samples to perform whole
transcriptome sequencing for the detection of RNA viruses using the REPLI-g WTA
Single Cell Kit
• The protocol used by the authors to detect and characterize different types of norovirus from
clinical specimens was proven reliable, and the results support the utility of NGS in routine
diagnostics.
42. Sample to Insight
Summary
42
Single cell genomics has become a powerful technology for studying small samples and rare
cells and for dissecting complex infections
• Vast numbers of uncultivable species and pathogens are now accessible for genomic
analysis
Our dedicated solutions powered by REPLI-g enable you to get the most out of your samples
• Streamlined PCR-free workflow takes you from one single cell to a high-quality NGS
library in a single day
• Bioinformatics solutions for data analysis and interpretation lets you gain meaningful
biological insights from your NGS data
Single cell analysis has made advances in a number of research areas
• Cancer
• Neuroscience
• Infectious disease
• Reproductive genetics
• Metagenomics
REPLI-g technology has made a large number of these advances possible
43. Sample to Insight
Single cell resource site: www.qiagen.com/SingleCellAnalysis
Single-cell genomics by QIAGEN, 2016 43
Visit our single cell site for application, product information and supportive material
Including a knowledge
hub with publications,
webinars, posters,
infographics & our
blog posts
44. Sample to Insight
Single cell Knowledge Hub
44
Scientific publications, webinars, videos, white papers, posters, infographics
45. Sample to Insight
Agenda
45
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions
2
1
3
46. Sample to Insight
Agenda
46
Overview of single cell technology
• Why study single cells?
• Basic parts of a single cell workflow
• QIAGEN solutions for single cell analysis
Advances enabled by single cell technology
• Cancer research
• Reproductive genetics
• Neuroscience
• Metagenomics
• Infectious disease
Questions3
1
2
47. Sample to Insight
Thank you for attending
47
Thank you for attending today’s webinar!
Contact QIAGEN
Call: 1-800-426-8157
Email: BRCsupport@QIAGEN.com
Miranda Hanson-Baseler, PhD
Miranda.Hanson-Baseler@QIAGEN.com
QIAwebinars@QIAGEN.com
Questions?
49. Sample to Insight
REPLI-g overcomes challenges in preamplification
single cell genomics by QIAGEN, 2016 49
1 pg DH10B DNA, amplified with either REPLI-g Single Cell Kit or by MALBAC, sequenced on MiSeq
Illumina (V2, 2x150nt.)
(1) J.Liang et al., single cell Sequencing Technologies: Current and FutureJournal of Genetics and Genomics 41 (2014) 513-528
• High enzyme processivity – no dissociation, pausing or slippage – long reads (>70 kb)
• Superior proofreading activity with high-fidelity enzyme – 1000-fold higher fidelity than normal
PCR enzymes (1)
• High yields – get sufficient material for your downstream applications, including NGS, PCR or
microarrays
• Optimized lysis and DNA denaturation – immediate amplification across all regions
50. Sample to Insight
Amplification yield and accuracy
single cell genomics by QIAGEN, 2016 50
Advantages of higher yield and
lower error rate
• Archive your single cell for
future experiments
• More sensitive variant
detection
• Higher confidence in your data
1 pg DH10B DNA, amplified with either REPLI-g Single Cell Kit or by MALBAC,
sequenced on MiSeq Illumina (V2, 2x150nt.)
51. Sample to Insight
Coverage uniformity
single cell genomics by QIAGEN, 2016 51
Advantages of coverage uniformity
• Better de novo genome assembly
• Higher transcript detection rate (in
WTA/RNAseq experiments)
• Lower total read number required;
higher multiplexing
• Advantageous for low-pass
sequencing strategy
1 pg DH10B DNA, amplified with either REPLI-g Single Cell Kit or by
MALBAC, sequenced on MiSeq Illumina (V2, 2x150nt.)
52. Sample to Insight
Overcoming the Challenge of gDNA Secondary Structure
single cell genomics by QIAGEN, 2016 52
• Denatured gDNA has a complex
secondary structure
• Consists of regions of ssDNA and
dsDNA that can form complicated
hairpins and loops
QIAGEN’s MDA enzyme handles complex DNA structures
generating extremely long amplicons
Editor's Notes
(2) REPLI-g Single Cell Kit + Geneseq panels
(3) REPLI-g UltraFast Mini Kit
(4) REPLI-g Single Cell Kit
Cancer is a disease caused by changes to the DNA. Tumour evolution is a series of clonal expansions that are each triggered by new driver mutations conferring a selective advantage. Analysing “bulk” samples (millions of cells within one sample) limits the number of tumour cell populations that can be differentiated or the identification of rare subclonal populations. (1)
single cell analysis of the cancer genome. (a) Cancers arise due to the acquisition of driver mutations resulting in successive clonal expansions of nascent tumour cells. Driver mutations that occur after the emergence of a most recent common ancestor will give rise to tumour subclones. Solid tumours also shed cells in a patient’s blood stream (circulating tumour cells or CTCs) and cells disseminating to distant organs (disseminated tumour cells or DTCs), which may cause overt metastases. (b) To study tumour evolution and intra-tumour genetic heterogeneity, individual tumour cells can be isolated using a variety of techniques. Furthermore, CTCs can be isolated from peripheral blood, and DTCs from the bone marrow, a frequent homing-niche of DTCs. (c) Following isolation, single cells are lysed and their DNA or RNA is amplified using whole-genome amplification (WGA) or whole-transcriptome amplification (WTA) techniques, respectively. (d) The WGA and WTA products can be profiled using microarray or massively parallel sequencing platforms, (e) providing important perspectives for future cancer research and cancer treatment
(1) REPLI-g Midi Kit
(2) REPLI-g Midi Kit
(3) REPLI-g Midi Kit
(4) REPLI-g Mini Kit
PGS= pre-implantation genetic screening (aneuploidy testing)
PGD=pre-implantatiion genetic diagnosis (detecting chromosomal and genetic abnormalities)
“ Worldwide, approximately a million assisted reproductive treatment cycles end in failure each year, emphasising the urgent need for improvement to existing techniques.”
It has been show
(1) REPLI-g WTA Single Cell Kit
(2) REPLI-g WTA Single Cell Kit
(3) NB: Modified RNAseq protocol using components of REPLI-g for MDA
REPLI-g Mini and Midi Kit
Repli-g Cell WGA and WTA kit
REPLI-g Single Cell Kit
UPGMA (Unweighted Pair Group Method with Arithmetic Mean) is a simple agglomerative (bottom-up) hierarchical clustering method. It is one of the most popular methods in ecology for the classification of sampling units (such as vegetation plots) on the basis of their pairwise similarities in relevant descriptor variables (such as species composition)