Different types of lipids affect cell response and viability. However, many lipid removal methods utilize solvents, such as Freon or chloroform, while other methods use solid phases that suffer from non-specific protein binding.

This report from Biotech Support Group highlights the ability of Cleanascite lipid removal reagent to clear lipid-associated matrix effects, including extracellular vesicles, which may influence cell response assays.

Tumor-associated macrophages (TAMs) located in the tumor microenvironment (TME), predominantly display an M2 protumor phenotype, and play a significant role in cancer cell survival and progression. Recent research suggests that the polarization of macrophages is orchestrated by fatty acid metabolism. Understanding the role of lipids in the TME has therefore become an important topic in tumor biology.

This case study from Biotech Support Group highlights the use of Cleanascite suspension reagent to remove artifacts in characterizing the influence of lipids and other factors bound to lipids on cell response in cancer.

The 10x Genomics Chromium single-cell platform has contributed to basic and translational research in immunology, developmental biology, and cancer by enabling the resolution of distinct cell populations within heterogeneous samples. Single-cell resolution of biological samples has accelerated our understanding of the complexity of living organisms and has opened up new possibilities for research in fields such as cancer research, genomics, and evolutionary biology.

Similarly, next-generation sequencing is an enabling technology for single-cell analysis, providing genomic information about the cell populations. Advancements in NGS over the last decade have contributed to faster, more accurate results while driving down the cost of experiments. The G4 Sequencing Platform combined with the 10x Genomics single-cell analysis platform allows researchers to achieve faster and more flexible sequencing while profiling tens of thousands of cells.

This application note from Singular Genomics demonstrates a workflow for producing data generated using 10x Chromium Single Cell 3’ Gene Expression assay with the novel G4 Sequencing Platform, demonstrating accuracy and technical reproducibility for single-cell analysis.

Single-cell RNA sequencing (scRNA-Seq) has revolutionized basic and translational research in immunology, developmental biology, and cancer by enabling the resolution of distinct cell populations within heterogeneous samples. However, there remains a need for cost-effective, high-throughput sequencing solutions to reduce the cost of scRNA-seq studies. We previously introduced the Max Read Kit, which enables higher output of short reads for the G4 Sequencing Platform, without a significant impact on read quality.

This poster from Singular Genomics evaluates the performance of the Max Read Kit for scRNA-seq by sequencing a 10x Genomics 3’ RNA-seq library prepared from human peripheral blood mononuclear cells (PBMC) using the G4, comparing results to those from the Illumina NextSeq 2000. We demonstrate high accuracy, reproducibility, and throughput with the Max Read sequencing kit.

Accurate and reproducible quantification of DNA is essential to achieving consistent NGS sequencing results. It is important to measure both the total quantity of DNA and the distribution of fragment sizes to achieve an optimal cluster density on the Illumina flow cell. Both factors impact data quality and total sequencing output. Among the common methods of DNA quantification, qPCR has the highest sensitivity.

However, qPCR setup is time intensive, and results are highly sensitive to small differences in pipetting. Automating NGS quantification provides a streamlined approach to getting reproducible, high-precision results while minimizing hands-on time.

This application note from Opentrons describes studies performed to evaluate two methods of qPCR normalization during the NGS workflow on the Opentrons OT-2 automated liquid handling platform, demonstrating the capabilities of the platform in automating NGS quantification and normalization in preparation for Illumina sequencing.

Next-generation sequencing has achieved widespread adoption as a tool for biological research and in vitro diagnostics. Despite this success, traditional NGS systems are limited by long analysis times, labor-intensive protocols, and the need for extensive sample batching to achieve cost-effective use. To address these limitations, Singular Genomics developed the G4 Platform for rapid and flexible sequencing.

This poster from Singular Genomics describes the application of the novel, higher-density F3 flow cell to perform 30x whole genome sequencing of the human reference cell line HG002 in a single flow cell on the G4 Sequencing Platform.

Next-generation sequencing has become a central component of modern microbiome basic and translational research by enabling high-resolution assessment of species diversity and de novo genome assembly at a far lower cost than traditional methods. A key challenge to NGS-based microbiome analysis is the presence of high- and low-GC content organisms, which are traditionally underrepresented in NGS data.

This poster from Singular Genomics evaluates the performance of the novel G4 Sequencing Platform for microbial community analysis by sequencing a National Institute for Standards and Technology microbial reference material.

Single-cell RNA sequencing (scRNA-Seq) has revolutionized basic and translational research in immunology, developmental biology, and cancer by enabling the resolution of distinct cell populations within heterogeneous samples. The resolution and scale of scRNA-seq are made possible by advances in next-generation sequencing, where greater throughput and faster turnaround times have dramatically reduced the cost of experimentation. Despite these strengths, there is a growing need for scRNA-seq library preparation technologies that support greater cell throughput and sensitivity with lower background noise. To address these challenges, Parse Bioscience has developed Evercode split-pool combinatorial barcoding to enable scalable scRNA-Seq analysis.

This application note from Singular Genomics highlights the use of the Parse Biosciences Evercode WT kit in combination with the novel G4 Sequencing Platform, demonstrating accuracy and high concordance of the G4 Platform with an industry-leading NGS platform as well as a faster turnaround time.

MicroRNAs (miRNAs) are key players in nearly all normal and disease-related biological pathways and are a promising liquid biopsy-compatible biomarker type owing to their robust and stable expression in cell-free DNA and other biofluids. Next-generation sequencing has emerged as a leading method for the analysis of miRNAs owing to its high sensitivity, precision, and ability to discriminate subtle but biologically relevant differences in miRNA abundance across healthy and disease samples. However, the short ~22 nucleotide length of miRNAs poses challenges for NGS library preparation and sequencing.

This application note from Singular Genomics demonstrates the use of the QIAseq miRNA Library Prep Kit in combination with the G4 Sequencing Platform for the analysis of human miRNA, showing the high sensitivity and accuracy and seamless integration of G4 sequencing data into the Qiagen GeneGlobe Data Analysis Portal.

The G4 Sequencing Platform is a novel benchtop sequencer that delivers speed, power, and flexibility for a range of genomic applications. With the ability to run up to four flow cells, each flow cell comprising 16 independently addressable lanes, the G4 Platform maximizes efficient laboratory operations. Singular Genomics has partnered with IDT to streamline DNA-sequencing operations. The IDT xGen cfDNA and FFPE DNA Library Prep Kit is designed specifically for use with degraded samples, such as cell-free DNA (cfDNA) or DNA extracted from formalin-fixed paraffin-embedded (FFPE) samples.

This application note from Singular Genomics describes the combined benefits afforded by a workflow using the IDT xGen cfDNA and FFPE DNA Library Prep Kit on degraded samples to be sequenced with the Singular Genomics G4 benchtop sequencer.

During the bioinformatic and clinical processing of NGS data that will result in the final medical assessment, all detected variants must be checked for if and how they are annotated in genomic databases. However, the existence of significant discrepancies in variant reporting and their classification requires additional scrutiny and caution. Some of the existing discrepancies between databases can only be resolved by manually scanning conflicting journals, assessing, and reviewing supplementary materials in the articles, or directly contacting the authors.

This application note from Qiagen describes how to use Human Gene Mutation Database Professional to increase the diagnostic yield in complex neurological disorders including Alzheimer’s disease, Parkinson’s disease, and multiple sclerosis.

Numerous clinical decision support systems and knowledgebases have been developed to assist variant scientists and laboratory directors with the task of variant classification. These private and commercially available systems utilize varying degrees of software automation and manually curated literature to provide variant assessment and therapy matching for clinicians. The body of literature that must be accessed to deliver accurate variant interpretation is vast and there is debate in the field as to the most accurate and efficient approach.

This white paper from Qiagen describes a study demonstrating that clinical decision support tools can help to reliably streamline and standardize somatic variant interpretation and address the high degree of variability among experts in somatic clinical interpretation.

The vast amount of data generated by whole-exome sequencing (WES) introduces new opportunities for cancer research, but simultaneously poses challenges that require novel computational and theoretical approaches in big data analysis. While workflows for raw data processing and variant calling have improved, filtering tens of thousands of candidate genes and variants to identify a subset of relevant ones is still complex. The most challenging part of using WES is analyzing, interpreting, and filtering the large number of detected variants.

A robust, methodical WES analysis pipeline is essential to help researchers decipher which of the detected variants have functional significance and which are irrelevant to the phenotype in question. In order to pinpoint the most relevant variants, comprehensive annotation of all detected variants is necessary. With large data sets coming from WES, prioritization is crucial to reduce the list of relevant variants to a manageable set requiring further validation.

This application note from Qiagen presents a protocol for whole-exome variant annotation using QCI Interpret Translational, a next-generation sequencing variant assessment software solution that enables evidence-powered variant annotation, filtering, and triage for human exome, genome, and large cohort sequencing data.

Molecular subtyping of NSCLC tumors is critical for targeted therapies and immunotherapy success. The NanoString GeoMx DSP platform provides spatial context about cells and their interactions with a tumor along with high-plex gene expression data. NanoString’s standard morphology markers broadly target tumor and immune cells within tissue. Molecular subtyping within a tumor type requires additional stratification at the tissue level enabling meaningful subsequent gene expression analysis. Canopy Biosciences’ ROI Selection markers enable more precise morphological analysis of tissue samples, allowing for tumor subtyping, followed by comparative gene expression differences in these two tumor cell types.

This poster from Canopy Biosciences presents the analysis of non-small cell lung cancer FFPE samples using the NanoString GeoMx Digital Spatial Profiler platform using the Whole-Transcriptome Atlas panel for molecular profiling and NGS protein quantification to evaluate the platform to selectively identify tumor subtypes.

Gene expression profiling is a powerful tool that can be used to evaluate potential drug candidates in preclinical in vivo experiments. The first step in any gene expression profiling experiment is RNA isolation and quality assessment. Formalin-fixed paraffin-embedded (FFPE) samples pose a particular challenge to gene expression profiling since these samples usually contain a high amount of fragmented RNA.

This white paper from Canopy Biosciences answers questions about gene expression profiling and RNA isolation from fresh-frozen and FFPE tissues, and it discusses how the NanoString nCounter platform does not require amplification, a necessary step for many gene profiling assays, making it ideal for targeted gene profiling from FFPE samples.