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Nature Papers on Tool to Design FISH Experiments, Approach to Improve Single-Cell Combinatorial Indexing

A platform for the design of oligo-based fluorescence in situ hybridization (FISH) experiments at transcriptome- and genome-scale is presented in Nature Methods this week. Advances in oligo-based FISH methods have enabled researchers to study the three-dimensional organization of the genome at super-resolution and visualize the spatial patterns of gene expression for thousands of genes in individual cells, yet there has been little progress in developing computational tools that support the design of the probes and probe sets needed for such experiments. To address this, a University of Washington team developed PaintSHOP — short for paint server and homology optimization pipeline — for the design of oligo FISH experiments. PaintSHOP consists of a bioinformatic pipeline and large-scale collection of more than 298 million primary oligo probe sequences targeting the genomes and transcriptomes of nine different experimental organisms, along with an interactive web application that facilitates the automated creation of ready-to-order probe sets against any target in the genome or transcriptome using user-specified patterns. The resource "democratizes and standardizes the process of designing complex probe sets for the oligo FISH community," the scientists write.

Single-cell combinatorial indexing (sci) with transposase-based library construction increases the throughput of single-cell genomics assay but often produce sparse coverage for the genomic property of interest. Aiming to overcome this limitation, a group led by Oregon Health & Science University researchers developed symmetrical strand sci — or s3 — a uracil-based adapter switching approach that improves the rate of conversion of source DNA into viable sequencing library fragments following tagmentation. As they report in Nature Biotechnology, the researchers demonstrate the strategy by using it to produce high-coverage single-cell ATAC with high-throughput sequencing profiles of mouse brain and human cortex tissue, with the mouse datasets demonstrating a 6- to 13-fold improvement in usable reads per cell compared with other available methods. Application of s3 to single-cell whole-genome sequencing (s3-WGS) and to whole-genome plus chromatin conformation (s3-GCC), meanwhile, yields 148- and 14.8-fold improvements, respectively, in usable reads per cell compared with sci-DNA-sequencing and sci-HiC. The team also shows that s3-WGS and s3-GCC resolve subclonal genomic alterations in patient-derived pancreatic cancer cell lines.

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