Read about how researchers across the world are using QIAGEN Digital Insights solutions to accelerate their work in a variety of applications
Making sense of complex 'omics data, and developing the infrastructure to compile, store, search, analyze and visualize relevant information has significant challenges and may pose a burden to researchers without bioinformatics skills. Yet powerful insights derived from 'omics data help innovate, integrate and translate scientific results into impactful discoveries. Many noteworthy papers cite QIAGEN Digital Insights solutions and demonstrate how our tools help drive research insights and discoveries. These papers use QIAGEN Ingenuity Pathway Analysis (IPA), QIAGEN CLC Genomics and/or QIAGEN OmicSoft to help drive success. The QIAGEN Digital Insights portfolio encompasses a comprehensive, easy-to-use toolbox that ensures continuity in the NGS workflow. Here, we have curated a selection of just a few recent papers to offer a sense of the diversity of the research for which QIAGEN Digital Insights solutions makes a difference.
Multi-organ proteomic landscape of COVID-19 autopsies
First author: Xui Nie
Check out this fantastic work by coronavirus researchers at Westlake University who try to understand how SARS-CoV-2 causes cellular damage in organs other than the lungs. See how the team uses QIAGEN IPA to identify upregulated molecules and activated pathways in this proteomic study of COVID-19 autopsy samples. Read their full paper here.
EGR1 is a gatekeeper of inflammatory enhancers in human macrophages
First author: Marco Trizzino
Monocytes or macrophages? See how the team at The Wistar Institute used QIAGEN IPA to understand how EGR1 drives immune cell differentiation by studying upstream regulators of the genes associated with EGR1. Read the full article here.
Wastewater-based epidemiology as a useful tool to track SARS-CoV-2 and support public health policies at the municipal level in Brazil
First author: Tatiana Prado
We’ve heard wastewater can be used for COVID-19 surveillance. Check out this QIAGEN CLC research paper on wastewater-based epidemiology as a useful tool to track SARS-CoV-2 in Brazil. Read the full article here.
KLF10 deficiency in CD4+ T cells triggers obesity, insulin resistance and fatty liver
First author: Akm Khyrul Wara
Is immune dysregulation and obesity/insulin resistance connected? Researchers at Harvard Medical use QIAGEN IPA and QIAGEN CLC Genomics to study the role of CD4+ T cells in insulin resistance and obesity to reveal how KLF10, a transcription factor and a critical regulator of CD4+ T regulatory cells, maybe be responsible. Read the full article here.
Single-cell analysis reveals distinct immune landscapes in transplant and primary sarcomas that determine response or resistance to immunotherapy
First author: Amy J. Wisdom
Does immunotherapy work differently in primary vs. transplanted tumors? See how cancer researchers at Duke University use QIAGEN OmicSoft Suite for single-cell analysis of immune cells found in transplant vs. primary tumors and how these cells play a role in the effectiveness of immunotherapy. Read the full paper here.
Get in touch with us, we would love to hear from you. To request information on our QIAGEN Digital Insight solutions, contact bioinformaticssales@qiagen.com.
Read about how researchers across the world are using QIAGEN Digital Insights solutions to accelerate their work in a variety of applications
Making sense of complex 'omics data, and developing the infrastructure to compile, store, search, analyze and visualize relevant information has significant challenges and may pose a burden to researchers without bioinformatics skills. Yet powerful insights derived from 'omics data help innovate, integrate and translate scientific results into impactful discoveries. Many noteworthy papers cite QIAGEN Digital Insights solutions and demonstrate how our tools help drive research insights and discoveries. These papers use QIAGEN Ingenuity Pathway Analysis (IPA), QIAGEN CLC and/or QIAGEN OmicSoft to help drive success. The QIAGEN Digital Insights portfolio encompasses a comprehensive, easy-to-use toolbox that ensures continuity in the NGS workflow. Here, we have curated a selection of just a few recent papers to offer a sense of the diversity of the research for which QIAGEN Digital Insights solutions makes a difference.
Aberrant (pro)renin receptor expression induces genomic instability in pancreatic ductal adenocarcinoma through upregulation of SMARCA5/SNF2H
First author: Yuki Shibayama
Did you know on average pancreatic cancer patients acquire over 67 non-synonymous mutations? The team at Kagawa University used QIAGEN IPA to study the role of (pro)renin receptor [(P)RR] in causing genomic instability. Read their full paper here.
Glioblastoma stem cells induce quiescence in surrounding neural stem cells via Notch signaling
First author: Katerina Lawlor
Did you know cancer cells are not only good at proliferating but can also suppress other cells from growing? See how the team at Imperial College London investigates this phenomenon using QIAGEN IPA to understand how cancer cells induce quiescence in glioblastomas. Read their full paper here.
Multiparametric profiling of engineered nanomaterials: Unmasking the surface coating effect
First author: Audrey Gallud
Discover this fascinating research by scientists at the Karolinska Institutet who study the cytotoxic effects of engineered nanomaterials (ENMs). See how the team uses QIAGEN IPA to understand the mechanism behind the cytotoxic effects of ENMs and how to mitigate the risks. Read the full article here.
Innate immune training of granulopoiesis promotes anti-tumor activity
First author: Lydia Kalafati
Check out this exciting research by L. Kalafati and colleagues at TU Dresden, who try to promote the anti-tumor activity of trained neutrophils. See how the team uses QIAGEN IPA to understand the molecular mechanism behind reprogramming caused by trained immunity agonists. Read the paper here.
Liver-expressed cd302 and cr1l limit hepatitis C virus cross-species transmission to mice
First author: Richard J. P. Brown
Did you know the hepatitis C virus (HCV) affects 71 million people worldwide but only infects humans? Read how researchers at Paul Ehrlich Institute (PEI) use QIAGEN IPA and QIAGEN CLC Genomics Workbench to understand how mice are able to prevent HCV infection. Read their full paper here.
Vascular disease and thrombosis in SARS-CoV-2-infected rhesus macaques
First author: Malika Aid
Is there a connection between thrombosis and SARS-CoV-2 infection? Read how the team at Beth Israel Deaconess Medical Center uses QIAGEN IPA to understand the critical interactions between various pathways that lead to SARS-CoV-2-induced blood clotting in rhesus macaques. Read their full paper here.
Imbalance of regulatory and cytotoxic SARS-CoV-2-reactive CD4+ T cells in COVID-19
First author: Benjamin Meckiff
Check out this critical coronavirus research by B. Meckiff and colleagues at the La Jolla Institute for Immunology, who study the role of CD4+ T cells in COVID-19. See how the team uses QIAGEN IPA to understand how different subsets of CD4+ T cells play a role in pathogenic immune responses to SARS-CoV-2 infection. Read the full article here.
Potentially adaptive SARS-CoV-2 mutations discovered with novel spatiotemporal and explainable AI models
First author: Michael R. Garvin
Can mutations in coronavirus spike proteins help it escape current vaccines? See how a group at Oak Ridge National Laboratory predicts mutational hotspots in the viral genome using QIAGEN CLC Genomics and AI models. Read the full article here.
Genomic evidence for reinfection with SARS-CoV-2: A case study
Co-author: Joel Sevinsky
Is SARS-COV-2 reinfection possible? Joel Sevinsky and his colleagues in the Nevada public health arena report the first SARS-Cov-2 reinfection case in the US. See how the team uses QIAGEN CLC Genomics Workbench for bioinformatics analysis of their SARS-CoV-2 samples to discover whether it was the same virus or a genetically different specimen. Read the full article here.
Two distinct immunopathological profiles in autopsy lungs of COVID-19
First author: Ronny Nienhold
Is unlocking differences in immune response the key to treating ARDS in COVID-19? Dig into this important coronavirus research from R. Nienhold and colleagues at Cantonal Hospital Baselland who study different immunopathological profiles in COVID-19 patients. See how the team uses QIAGEN CLC Genomics Workbench to understand the different immune patterns observed in post mortem COVID-19 lung tissue. See their full article here.
A mouse-adapted SARS-CoV-2 induces acute lung injury and mortality in standard laboratory mice
First author: Sarah R. Leist
Did you know coronaviruses are responsible for three epidemics in the 21st century? Great work by S. Leist and colleagues at the University of North Carolina at Chapel Hill, who created a mouse-adapted SARS-CoV-2 to understand the virus better. See how the team uses QIAGEN CLC Genomics Workbench to characterize this animal model and discover mechanisms for SARS-CoV-2 pathogenesis to test potential therapeutics. Read their full paper here.
Single-cell transcriptomics implicate novel monocyte and T cell immune dysregulation in sarcoidosis
First author: Lori Garman
Single-cell analysis improves our understanding of multimodal diseases. Don't miss this exciting cancer research by L. Garman and colleagues, who study the role of immune cells in sarcoidosis. The team uses QIAGEN IPA and QIAGEN OmicSoft DiseaseLand to identify dysregulated pathways using single-cell analysis. Read the full paper here.
Non-human primate blood–brain barrier and in vitro brain endothelium: From transcriptome to the establishment of a new model
First author: Catarina Chaves
Congratulations to the researchers at Sanofi for publishing their findings on a comparative model for the human blood-brain barrier (hBBB). See how the team uses QIAGEN IPA and QIAGEN OmicSoft Studio to investigate the transcriptome of brain capillaries from a non-human primate, and compare it to the hBBB. Read the full paper here.
Preclinical validation of therapeutic targets predicted by tensor factorization on heterogeneous graphs
First author: Saee Paliwal
Do we need better models for validating preclinical drug target candidates? How can we test these models? Read how researchers at BenevolentAI use QIAGEN OmicSoft DiseaseLand to evaluate the robustness of their computational model, Rosalind. Read the full paper here.
Get in touch with us! To request information on our QIAGEN Digital Insight solutions, contact bioinformaticssales@qiagen.com.
Our recent Variant Analysis update includes several key features, most notably, improved data export (now completed offline to improve performance) and better handling of uploaded VCF files. The Allele Frequency Community (AFC) now features CentoMD data, with details about 155,000 sequenced individuals whose genotypes offer a more comprehensive view of population genomics. We also updated the statistics available in AFC, which contains summary statistics from public, private and users from QIAGEN’s community. These statistics are now based on more than 750,000 samples that were analyzed through our platforms—including more than 38,000 whole genomes, and more than 358,000 exome samples. The new Variant Analysis release inspired us to look at how our customers are putting it to use it in their workflows. Read on for more details—and possibly some inspiration!
Oligogenic genetic variation of neurodegenerative disease genes in 980 postmortem human brains
First author: Michael J. Keogh
The Journal of Neurology, Neurosurgery and Psychiatry recently published a study developed by an UK-based team that analyzed genetic variants of three neurodegenerative diseases in 980 postmortem human brains. They used Variant Analysis to study 49 genes known to be associated with three neurodegenerative disorders: Alzheimer’s disease (AD), Parkinson’s disease-dementia with Lewy bodies (PD-DLB), and frontotemporal dementia-amyotrophic lateral sclerosis (FTD-ALS), and investigated whether synergistic interaction between two or more functional genetic variants contributed to increased likelihood of early onset. They determined that the presence of oligogenic variants did not influence the age of onset or disease severity, which they noted is an important a priori bias to guard against in future research.
Mutational landscape of radiation-associated angiosarcoma of the breast
First author: Bryan J. Thibodeau
A team of scientists from Michigan, California, and Alberta, Canada recently investigated genomic variation in biospecimens from radiation-associated breast angiosarcomas—a rare complication of radiation therapy for breast carcinoma. In their report, which was published in Oncotarget, the team mentioned using Variant Analysis to characterize variants and to investigate signaling pathways preferentially affected in radiation-association angiosarcomas. Due to the relative rarity of this type of tumor, the team recommended further investigation, using whole genome or exome sequencing, to further the discovery and confirmation of potential drug targets and to identify potential radiation-associated signatures.
Pediatric dilated cardiomyopathy‐associated LRRC10 (Leucine‐Rich Repeat–Containing 10) variant reveals LRRC10 as an auxiliary subunit of cardiac L‐type Ca2+ channels
First Author: Marites T. Woon
A group of researchers from Madison, Wisc., and Rochester, Minn. sought to further understand the genetic causes of dilated cardiomyopathy (DCM). Their report, published in the Journal of the American Heart Association, details their work and includes mention of Variant Analysis to analyze variant call format files. The team found a rare, homozygous variant in a cardiac‐specific protein, which provides evidence that variants in LRRC10 can serve as a genetic cause of DCM. This research deepens our burgeoning understanding of the condition and provides a potential link to its pathophysiology.
ARL6IP1 mutation causes congenital insensitivity to pain, acromutilation and spastic paraplegia
First Author: M. Nizon
A team from Nantes, France, reported in Clinical Genetics about their research on the role of ARL6IP1 in the pathophysiology of insensitivity to pain and spastic paraplegia, which are symptoms of hereditary sensory and autonomic neuropathies (HSAN) type II. They used Variant Analysis to generate variant annotation and interpretation analyses, enabling them to identify a homozygous variant in ARL6IP1, which they determined as a key factor in hereditary spastic paraplegia and sensorimotor neuropathy.
We’re not only honored to understand how our solutions are helping a range of researchers learn more about their fields, we’re also keen to learn more. If you’d like your work to be featured in one of our blog posts, we’d love to hear from you. To test out Variant Analysis for yourself, simply request it here.
We were delighted to read about the success of a former PhD student who spent three years working in our Aarhus office. Elizabeth Sollars of the School of Biological and Chemical Sciences at Queen Mary University of London was the first author of a paper recently published in Nature. Titled “Genome Sequence and Genetic Diversity of European Ash Trees,” the paper describes the team’s genomic investigation into the genetics behind susceptibility of ash trees to the ash dieback disease, caused by the fungus Hymenoscyphus fraxineus. In addition, the genome sequence will aid researchers in North America investigating ash tree susceptibility to the Emerald Ash Borer beetle, Agrilus planipennus.
Sollars and her team have published the first genome sequence of an ash tree, using a sample from Gloucestershire in the UK, and they have resequenced a further 37 specimens gathered from around Europe. After annotating protein coding genes and mapping genetic variants, they then identified improved markers for reduced susceptibility to H. fraxineus and posited that their findings might help mitigate the epidemic of the ash tree dieback; in particular they found the metabolite iridoid glycosides were a factor in the disease susceptibility. The team used CLC Genomics Workbench for a wide variety of tasks throughout the project, including the trimming of NGS data, de novo assembly of chromosomes and organellar genomes, the annotation of the organellar genomes, and detection and analysis of genomic variants.
We are always proud to learn about how our solutions pave the way to greater understanding of the world around us, and even more so when the efforts are led by an esteemed former colleague. Congratulations to Elizabeth and the whole team!
A recent paper presents the ChIP-seq analysis tool available in CLC Genomics Workbench and CLC Genomics Server (version 7.5 and later).
Some of the main requirements for the development of our peak calling toolset were generality, specificity, robustness, and simplicity. This resulted in the CLC shape-based peak caller which implements all the steps of signal detection, quality control, normalisation, discovering obvious peaks, learning the peak shape, peak shape score, and peak detection in a single, easy-to-use algorithm. The algorithm delivers a QC report containing metrics about the quality of the ChIP-seq experiment, a peak shape score value for every genomic position, and a list of all called peaks.
We have showed from a performance evaluation that the CLC shape-based peak caller ranks well among popular state-of-the-art peak callers while requiring a minimum of intervention and parameterization from the user.
Read the whole article: Identifying peaks in *-seq data using shape information (Lappe and Strino, 2016)
Get more on our solution for epigenomics analysis
We’re always on the lookout for new and interesting ways in which researchers are using our solutions. Here is a quick recap of a few recent papers that included gene expression data analysis from our Ingenuity® Pathway Analysis™ (IPA) customers.
Network Topology Analysis of Post-Mortem Brain Microarrays Identifies More Alzheimer’s Related Genes and MicroRNAs and Points to Novel Routes for Fighting with the Disease
First author: Sreedevi Chandrasekaran
PLoS One recently published new findings about the battle against Alzheimer’s disease from a research team based at Virginia Commonwealth University. This study is part of a larger effort to understand neurodegenerative disorders, including Parkinson’s and Huntington’s, with the aim of identifying a unified underlying molecular mechanism for all three diseases. Using what may be the first-ever network-based approach to study Alzheimer’s, the team attempted to single out new drug targets by using IPA core analysis in one stage of gene expression to delve into the underlying cellular mechanisms and molecular factors of the disease. They looked at deregulated genes, biological processes, and the interactions between them to decipher the complexity of the condition, enabling them to identify patterns and heterogeneous datasets.
Blood Genome-Wide Transcriptional Profiles of HER2 Negative Breast Cancer Patients
First author: Ovidiu Balacescu
A Romanian research team recently reported using IPA to identify which biological processes and pathways were affected by gene expression changes in triple-negative breast cancer, which is also known as TNBC/ER−PR−HER2−. Triple-negative breast cancer is currently only treated with chemotherapy. Unlike ER+ and HER2+ tumors, it does not have a validated target therapy, which means that it typically has a poor clinical outcome as well as greater risk of recurrence and distant metastasis. The study showed that targeted immunotherapy could feasibly be used in conjunction with chemotherapy to treat triple-negative breast cancer and improve clinical outcomes.
Transcriptome Profiling of Musculus Longissimus Dorsi in Two Cattle Breeds with Different Intramuscular Fat Deposition
First author: Elke Albrecht
Agricultural genomics is a significant topic for today’s science community, and this paper in Genomics Data sheds new light on potential paths to improve meat quality. The authors discuss how gene expression provides details about the different intramuscular fat depositions — also known as marbling, which dictates quality and flavor — in two cattle breeds. The team compared transcriptomes of muscle cells in both breeds, identifying 569 differentially expressed genes in Japanese Black cattle. They then used IPA to locate a gene network that links parameters of cell morphology and maintenance with lipid metabolism.
Transcriptomic Sequencing Reveals a Set of Unique Genes Activated by Butyrate-Induced Histone Modification
First author: Cong-Jun Li
In this paper published by the NIH’s Gene Regulation and Systems Biology journal, a research team studied the role of butyrate, a mammalian nutritional element produced by bacterial fermentation of dietary fibers. Using normal bovine cells, the team used IPA to analyze genetic networks of differentially expressed genes as well as molecular processes and functions, ultimately discovering butyrate-induced differential expression of genes and unique genes, which are related to major cellular functions. This is a step toward understanding epigenomic regulation at the molecular level.
Post-weaning Blood Transcriptomic Differences between Yorkshire Pigs Divergently Selected for Residual Feed Intake
First author: Haibo Liu
In this BMC Genomics study, researchers from Iowa State University used IPA to help them understand variations of global gene expression in the blood transcriptome of two separate lines of recently-weaned pigs to potentially inform the development of predictive biomarkers for residual feed intake, or RFI — a standard measure for feed efficiency. The team found a difference between the low and high RFI classifications of pigs, potentially leading to improved feed efficiency through genetic selection.
To try Ingenuity Pathway Analysis, please request a trial. If you’re working on something interesting with a QIAGEN Bioinformatics solution, let us know … you could be featured on our blog!
TRANSFAC is a unique knowledge-base containing published data on eukaryotic transcription factors and miRNAs, their experimentally-proven binding sites, and regulated genes. Here we've identified a few papers referencing the use of TRANSFAC.
The handedness-associated PCSK6 locus spans an intronic promoter regulating novel transcripts
Shore et al.
Following up on their previously published GWAS study which looked at genetic signatures of handedness in individuals with dyslexia, the authors performed a detailed analysis of the PCSK6 locus and specifically SNP rs11855145. TRANSFAC was used for in silico analysis of transcription factor binding at this site, predicting an allelic effect on binding of several HOX transcription factors which have been shown to be involved in anterior/posterior developmental patterning. In vitro EMSA confirmed an allelic difference for transcription factor binding site affinity.
Erosion of conserved binding sites in personal genomes points to medical histories
Guturu et al.
The authors of this study used matrices from TRANSFAC to perform an analysis of variants that fall within conserved predicted transcription factor binding sites and are predicted to significantly decrease transcription factor binding affinity compared to the ancestral reference nucleotide. Their work suggests that these variants, which they call conserved binding site eroding loci (CoBELs), tend to congregate near functionally related genes and influence heritable phenotypes providing new insight into disease penetrance.
Antagonistic effects of IL-17 and D-resolvins on endothelial Del-1 expression through a GSK-3β-C/EBPβ pathway
Maekawa et al.
In this study, the authors sought to characterize the mechanism of regulation of Del-1, an endothelial cell-secreted anti-inflammatory protein whose expression is inversely related to IL-17 expression. Based on prior knowledge of IL-17 stimulation resulting in phosphorylation and inactivation of the transcription factor C/EBPβ, coupled with parallel knowledge that IFNγ stimulation simultaneously enhances transcriptional activity of C/EBPβ and increases Del-1 expression, the authors hypothesized that C/EBPβ may in fact be a regulator of Del-1 expression. Promoter analysis of the Del-1 encoding gene (EDIL3) using TRANSFAC identified two predicted binding sites for C/EBPβ. The relevance of these binding sites was confirmed using ChIP-seq data provided within TRANSFAC suggesting that C/EBPβ is indeed a positive regulator of Del-1 expression.
A novel, dynamic pattern-based analysis of NF-κB binding during the priming phase of liver regeneration reveals switch-like functional regulation of target genes
Cook et al.
The authors of this study sought to characterize the role of transcriptional regulation by NF-κB during liver regeneration. They used ChIP-chip analysis to isolate NF-κB binding sites, followed by de novo motif discovery to identify other transcription factors associated with transcriptional regulation during this process. TRANSFAC was used to analyze the de novo motifs, identifying potential co-regulators including AP-1, AP-2, SMAD3, TAL1 and more. Validation of NF-κB targets was performed by ChIP qPCR with primers designed using TRANSFAC.
Activation of the Nrf2 response by intrinsic hepatotoxic drugs correlates with suppression of NF-κB activation and sensitizes toward TNFα-induced cytotoxicity
Herpers et al.
The aim of this study was to better understand Nrf2 and NF-κB signaling in the context of response to drug-induced liver injury. Common sources for protein-protein interaction data were used to assemble the list of genes involved in these two pathways. TRANSFAC was used to uniquely provide the set of genes bound by the terminal NFE2L2 and RELA transcription factors at the end of the respective signaling cascades. The resulting list of genes was analyzed for differential expression upon exposure to compounds associated with drug-induced liver injury.
Read more about TRANSFAC
