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QIAseq Targeted RNA Virtual Panels

Digital RNA-seq for gene expression profiling

  • Start with 25 ng cDNA or 25 ng of total RNA for each panel
  • Unique Molecular Indices (UMIs) ensure accurate expression profiling
  • Go from sample to sequence-ready library in a single day
  • Cloud-based data analysis via GeneGlobe Data Analysis Centre
  • On-site data analysis provided through CLC Biomedical Workbench

QIAseq Targeted RNA Virtual Panels have been developed as a Sample to Insight solution for quantitative gene expression profiling using RNAseq. These panels integrate molecular barcode technology and a two-stage PCR-based library preparation to deliver unbiased and accurate quantification for your digital RNA sequencing results. 

The QIAseq Targeted RNA Virtual Panels build on QIAGEN’s know-how to deliver more than 170 panels with biologically- and disease-relevant gene content. These panels have been curated over several years by mining literature and accessing QIAGEN's proprietary knowledge database.

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Adherens Junctions

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Adipogenesis

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Aging

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Allergy and Asthma

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Alzheimers Disease

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Amino Acid Metabolism I

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Amino Acid Metabolism II

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AMPK Signaling

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Androgen Receptor Signaling Targets

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Angiogenesis

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Angiogenic Growth Factors

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Antibacterial Response

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Antifungal Response

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Antiviral Response

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Apoptosis

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Apoptosis 384HT

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Atherosclerosis

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Autophagy

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Breast Cancer

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cAMP Calcium Signaling PathwayFinder

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Cancer Drug Resistance

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Cancer Drug Targets

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Cancer Inflammation and Immunity Crosstalk

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Cancer PathwayFinder

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Cancer Stem Cells

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Cardiotoxicity

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Cardiovascular Disease

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Cell Cycle

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Cell Death PathwayFinder

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Cell Junction PathwayFinder

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Cell Lineage Identification

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Cell Motility

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Cell Surface Markers

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Cellular Senescence

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Cellular Stress Responses

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Chemokines and Receptors

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Circadian Rhythms

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Common Cytokines

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Crohns Disease

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Cystic Fibrosis

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Cytokines and Chemokines

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Cytoskeleton Regulators

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Dendritic and Antigen Presenting Cell

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Diabetes

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DNA Damage Signaling Pathway

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DNA Repair

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Dopamine and Serotonin Pathway

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Drug Metabolism

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Drug Metabolism Phase I Enzymes

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Drug Metabolism Phase II Enzymes

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Drug Transporters

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EGF PDGF Signaling Pathway

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Embryonic Stem Cells

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Endothelial Cell Biology

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Epigenetic Chromatin Modification Enzymes

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Epigenetic Chromatin Remodeling Factors

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Epithelial to Mesenchymal Transition

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Estrogen Receptor Signaling

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Extracellular Matrix and Adhesion Molecules

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Fatty Acid Metabolism

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Fatty Liver

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Female Infertility

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Fibrosis

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Focal Adhesions

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GABA and Glutamate

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Gap Junctions

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Glucocorticoid Signaling

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Glucose Metabolism

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Glycosylation

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G Protein Coupled Receptors 384HT

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GPCR Signaling PathwayFinder

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Growth Factors

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Heat Shock Proteins and Chaperones

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Hedgehog Signaling Pathway

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Hematopoiesis

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Hepatotoxicity

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Hippo Signaling Pathway

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HIV Host Response

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Homeobox HOX Genes

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Huntingtons Disease

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Hypertension

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Hypoxia Signaling Pathway

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Hypoxia Signaling Pathway Plus

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IL6STAT3 Signaling Pathway

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IL6STAT3 Signaling Pathway Plus

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Immunotoxicity

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Induced Pluripotent Stem Cells

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Inflammasomes

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Inflammatory Cytokines and Receptors

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Inflammatory Response and Autoimmunity

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Inflammatory Response and Autoimmunity 384H

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Innate and Adaptive Immune Responses

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Insulin Resistance

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Insulin Signaling Pathway

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Interferons and Receptors

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JAK STAT Signaling Pathway

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let-7a Targets

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Leukemia

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Lipoprotein Signaling and Cholesterol Metabolism

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Liver Cancer

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Lung Cancer

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Lymphoma

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Macular Degeneration

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Male Infertility

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MAP Kinase Signaling Pathway

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Mesenchymal Stem Cells

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miR-1 and miR-206 Targets

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miR-146a Targets

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miR-153 Targets

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miR-155 Targets

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miR-17 and miR-20a Targets

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miR-181 Targets

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miR-21 Targets

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miR-210 Targets

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miR-221 and miR-222 Targets

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miR-29 Targets

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miR-34a Targets

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miR-4514 and miR-4692 Targets

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miR-9 Targets

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Mitochondria

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Mitochondrial Energy Metabolism

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Mitochondrial Energy Metabolism Plus

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Molecular Toxicology PathwayFinder

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Molecular Toxicology PathwayFinder 384HT

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mTOR Signaling

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Multiple Sclerosis

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MYC Targets

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Necrosis

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Nephrotoxicity

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Neurogenesis

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Neuronal Ion Channels

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Neurotoxicity

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Neurotransmitter Receptors

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Neurotrophins and Receptors

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NFkB Signaling Pathway

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NFkB Signaling Pathway Plus

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NFkB Signaling Targets

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Nitric Oxide Signaling Pathway

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Notch Signaling Pathway

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Notch Signaling Pathway Plus

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Notch Signaling Targets

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Nuclear Receptors and Coregulators

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Obesity

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Oncogenes and Tumor Suppressor Genes

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Osmotic Stress

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Osteogenesis

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Osteoporosis

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Oxidative Stress

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Oxidative Stress Plus

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p53 Signaling Pathway

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Pain Neuropathic and Inflammatory

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Parkinsons Disease

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Phagocytosis

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PI3K-AKT Signaling Pathway

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Polycomb and Trithorax Complexes

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Polycomb and Trithorax Target Genes

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Polycystic Kidney Disease

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PPAR Targets

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Pre-Eclampsia

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Primary Cilia

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Prostate Cancer

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Protease Activated Receptor Signaling

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Protein Phosphatases

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Retinoic Acid Signaling

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Signal Transduction PathwayFinder

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Skeletal Muscle Myogenesis and Myopathy

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Stem Cell

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Stem Cell Signaling

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Stem Cell Transcription Factors

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Stress and Toxicity PathwayFinder

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Synaptic Plasticity

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T Cell Anergy and Immune Tolerance

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T-Cell and B-Cell Activation

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Telomeres and Telomerase

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Terminal Differentiation Markers

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TGFb BMP Signaling Pathway

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TGFb Signaling Targets

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T Helper Cell Differentiation

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Th1 and Th2 Responses

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Th17 Response

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Tight Junctions

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TNF Signaling Pathway

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Toll-Like Receptor Signaling Pathway

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Transcription Factors

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Transplant Rejection

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Tumor Metastasis

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Type I Interferon Response

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Tyrosine Kinases

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Ubiquitin Ligases

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Ubiquitination Ubiquitinylation

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Unfolded Protein Response

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Unfolded Protein Response Plus

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VEGF Signaling

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WNT Signaling Pathway

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WNT Signaling Pathway Plus

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WNT Signaling Targets

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Wound Healing

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QIAseq Targeted RNA Virtual Panels are intended for molecular biology applications. These products are not intended for the diagnosis, prevention, or treatment of a disease.


0
Digital sequencing (molecular barcodes) principle

QIAseq Targeted RNA Panels use a digital sequencing method, whereby a unique 12-base random molecular barcode incorporated into the gene-specific primers (GSP1) is used in the first extension step (after mRNA is converted to cDNA). Thus, every extension event yields a unique combination of molecular barcode and target sequence. At the end of sequencing, the relative amount of each mRNA target is determined by the number of unique molecular barcode-target combinations that were sequenced, thereby eliminating PCR duplicates and amplification bias, resulting in more accurate, unbiased gene expression analysis.

1
One solution to overcome the challenges of gene expression profiling

The QIAseq Targeted RNA Panels have been developed as a Sample to Insight solution for quantitative gene expression profiling using RNAseq. The panels use molecular barcodes and a two-stage PCR-based integrated library preparation to overcome the challenge of PCR duplicates and amplification bias to deliver unbiased, accurate and reproducible gene expression results.

2
Unbiased and accurate gene quantification (A)

Different amounts (20 ng, 5 ng or 1.25 ng) of universal reference RNA were used to determine expression levels of three genes (BNIP1, CTNND2 and DAPK1) using targeted RNAseq. QIAseq digital RNA sequencing method (A; molecular barcode counts) showed accurate quantification of all three genes corresponding to different RNA input, whereas traditional targeted RNAseq (B; read counts) revealed PCR duplication limitation and yielded inaccurate quantification.

3
Unbiased and accurate gene quantification (B)
Different amounts (20 ng, 5 ng or 1.25 ng) of universal reference RNA were used to determine expression levels of three genes (BNIP1, CTNND2 and DAPK1) using targeted RNAseq. QIAseq digital RNA sequencing method (A; molecular barcode counts) showed accurate quantification of all three genes corresponding to different RNA input, whereas traditional targeted RNAseq (B; read counts) revealed PCR duplication limitation and yielded inaccurate quantification.
4
Proprietary primer design delivers gene-specific amplicons (>97% specificity)

Sequencing libraries were prepared using 1.25, 5 or 20 ng universal reference RNA and QIAseq Targeted RNA Panels, ranging from 12-plex to 1000-plex. Sequencing was performed on the Illumina MiSeq, dedicating 1 million reads per sample. Specificity is calculated as percent of trimmed and mapped reads that map to intended targets.

5
Unmatched uniformity (>97% of assays are within 20% of median molecular tag counts)
A 917-plex gene panel was used to prepare a library from 10 ng of NA12878 reference DNA. All assays were designed to be intra-exon, and are thus single copy on genomic DNA. This allows an estimation of the uniformity of amplicon performance in the library preparation step (e.g., every unique tag equals one captured copy). In terms of raw assay performance, 97.5% of assays are within 20% of mean/median molecular tag counts. For cataloged panels, any assay below 20% is redesigned and replaced. Molecular barcodes entirely remove this variation in RNAseq counting.
6
Simple procedure

Starting with 25 ng of total unfragmented RNA, cDNA is synthesized, and each cDNA molecule is tagged with a unique molecular barcode before any amplification. The uniquely tagged cDNA molecules then undergo a two-stage PCR step for enrichment and library construction. It takes only 6 hours from RNA sample to targeted library ready for sequencing.

7
Positive results with as little as 0.2 copies of RNA per cell

ERCC standards, at 86 to 705,500 copies, spiked into universal reference RNA sample and enriched using 384-plex QIASeq Targeted RNA Panel in three technical replicates. (A) Sensitivity measurement. Under standard conditions (20 ng RNA input, 0.5 million MiSeq reads), ≥~100 copies of ERCC transcripts were reliability detected, which is the equivalent of ~0.2 copies per cell. (B) Precision measurement. At >10 barcodes/gene, CV was less than 5% for all targets, indicating high technical reproducibility. This corresponds to ~100 copies target RNA in the sample.

8
High concordance with qPCR
Expression levels for 384 genes were determined by both QIAseq Targeted RNA Panel and qPCR for Human Brain Reference RNA (HBRR) and Universal Human Reference RNA (UHRR) samples. The expression levels determined by qPCR were normalized to the average of four housekeeping genes (ACTB, B2M, GAPDH and RPLP0) and fold change between the samples was calculated (HBRR/UHRR) for each gene. For QIAseq, the number of unique molecular barcodes per gene were counted and normalized to average number of molecular barcodes for the four housekeeping genes for each sample. The fold change for each gene was then calculated. The QIAseq Targeted RNA Panel and qPCR assays exhibit similar fold-changes in gene expression, highlighting the accuracy of QIAseq-results.
Performance

Principle
  • Traditional RNA sequencing methods suffer from PCR duplication and amplification bias, resulting in inaccurate gene expression analysis. By introducing molecular barcodes before any amplification takes place, QIAseq Targeted RNA Panels are able to eliminate this issue to deliver accurate and digital quantification of genes (see figure Unbiased and accurate gene quantification).
  • A unique feature of the QIAseq Targeted RNA Panels is the set of built-in control assays. The gDNA assays control for any gDNA contamination in the RNA sample to ensure reproducible results. The housekeping gene (HKG) assays are used to normalize data, thereby making sample-to-sample and run-to-run comparisons possible.

 

Procedure
  • The QIAseq Targeted RNA Panels workflow begins with converting total RNA into cDNA (see figure Simple procedure). The workflow requires minimal RNA input: as little as 25 ng total RNA can be used. No enrichment or depletion steps are necessary. The molecular barcoding step makes use of molecularly barcoded gene-specific primer (GSP1) in a multiplex primer panel (targeting 12-1000 genes) and an input of 20ng of cDNA equivalent (cDNA made from 20 ng of total RNA). After the barcoding step, the uniquely tagged cDNA is purified over beads to remove residual primers, and a PCR is set up with a second pool of gene-specific adapter primers (GSP2) and the RS2 primer, which primes off of a common tag on the GSP1 primers. This reaction insures that intended targets are enriched sufficiently to be represented in the final library. The number of cycles is kept to a minimum to keep PCR-induced variations in amplification to a low level (any variations are easily corrected and accounted for with the molecular barcodes). Another quick cleanup with beads is performed, and a universal PCR is run with RS2 and FS2 primers, which also adds sample-indexing barcodes to each sample. A final cleanup with beads is performed and the library is complete, and ready for quantification and sequencing.
  • An integral component of the QIAseq Targeted RNA Panels is data analysis and insight. Data analysis modules have been developed that are comprehensive, yet easy to use. Using these modules require no bioinformatics expertise. Starting with raw reads directly off the sequencer, the QIAseq targeted RNA data analysis tools at QIAGEN’s GeneGlobe portal, provide you with gene counts and fold changes, as well as links for pathway analysis.
Applications
  • Gene expression profiling
  • Biomarker research
  • Confirmation of whole transcriptome sequencing data
  • Confirmation of microarray data
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