Researchers at KU Leuven and other centers in Belgium and the Netherlands present a single-cell genotyping-by-sequencing (scGBS) method designed to characterize copy number in combination with genome-wide haplotypes. The approach relies on DNA amplification followed by restriction enzyme digestion-based methods for dialing down sequence size and complexity prior to sequencing, the team says, noting that the genotype-by-sequencing data for individual cells can then be fed into a copy number and haplotyping pipeline that includes an algorithm called haplarithmisis, originally designed for assessing haplotypes from SNP array profiles. The authors applied scGBS to cells from human blastomere or trophectoderm samples, before demonstrating that it could be used to profile blastomere cells from pre-implantation bovine embryos. "Our scGBS method opens up the path for single-cell haplotyping of any species with diploid genomes," they write, "and could make its way into the clinic as a [preimplantation genetic testing] application."
A research team from Sun Yat-sen Memorial Hospital and other centers in China demonstrates the feasibility of studying chromosome rearrangement in mammalian cell models with CRISPR-Cas9-based gene editing. By using CRISPR to target LINE-1 and Alu — repetitive human endogenous retrotransposons — the researchers successfully introduced double-strand breaks that led to global chromosome rearrangement (GCR) in a subset of cells. Those changes were confirmed with a combination of genome re-sequencing and karyotyping, they note, while transcriptomic and epigenetic features in the altered cells were subsequently assessed with RNA sequencing and ATAC-seq, respectively. "[O]ur study provided an easy-to-use and practical method for inducing GCR in mammalian cells," the authors write, "and resource datasets of genomics, epigenomics, and transcriptomics on the first GCR model in human cells."
Investigators at Tongji University and Sichuan University's State Key Laboratory of Oral Diseases describe a "spatial transcriptomics deconvolution by topic modeling" (STRIDE) method for teasing out cell types and cellular heterogeneity from single-cell RNA-seq profiles for spatially defined individual cells. The team applied STRIDE to simulated and real spatial scRNA-seq profiles in several mouse or human datasets, including data from developing human heart or squamous cell carcinoma samples. "Taken together, STRIDE is a versatile and extensible tool for integrated analysis of spatial and single-cell transcriptomics," they write, noting that the tool is publicly available through GitHub.