In the realm of genetic research, DNA FISH has long been a stalwart technique for unraveling chromosomal mysteries, shedding light on chromatin organization, and diagnosing clinical abnormalities. However, its reliance on heat denaturation and the need for lengthy target regions have posed significant obstacles, particularly when dissecting fine chromatin structures below 10 kilobases (kb), such as those introduced by exogenous genes during cell and gene therapy.

Do you have a set of genes whose expression needs to be validated after RNA sequencing or microarray? Do you want to visualize multiple cell types in a tumor microenvironment? NovaFISH is here to help.

NovaFISH is a new kind of single-molecule FISH (smFISH) technique that enables you to quantify gene expression with spatial information and digital quantification. Due to the intrinsic low signal of smFISH (dozens of fluorophores on each stained RNA dot), we have several suggestions on the image acquisition of smFISH samples, including NovaFISH, to get high-quality images for accurate and reliable NovaFISH quantification.

Over the past few decades, advancements in cultivation methods and the rapid development of new and advancing technologies has been the driving force behind the “-omics era” and has greatly enhanced the rate of discovery for a myriad of microorganisms. However, applications of microarray and Next Generation Sequencing (NGS) technologies typically are very limited in determining the relative abundances of individual targets and visualization of cells, which are features of which fluorescence in situ hybridization (FISH) excels. For that reason, scientists have frequently turned to FISH as an effective methodology for driving microbiome research around the world.

Several FISH-,qPCR- or RNA sequencing-based methods can measureRNA expression at the single-cell level. One technique that is suitablefor high-throughput analysis is flow cytometry-based fluorescence in situ hybridization, or Flow-FISH.

Analyzing microscopic image datasets is difficult. It is even more so with the rapid increase of PixelBiotech’s customer base. We are con-stantly receiving requests for HuluREAD to analyze datasets that are acquired using different microscopes, under various imaging conditions and on different species. In this article,we discuss important lessons we learned in building HuluREAD into an efficient and scalable algorith-mic platform for customized HuluFISH image data analysis.