Systems-level understanding of Single Cell technologies: Single-cell Multiomics and Ribosome Profiling

The past decade has experienced an evolution of genomics technologies. Recent developments in single-cell isolation, barcoding strategies, advanced micro-fluidic system, newer sequencing platform have enabled DNA, RNA, protein read outs possible in the single-cell level. Multimodal single-cell technologies, can simultaneously profile multiple data types, represent a new avenue for the discovery. CITE-seq for example leverages barcoded antibodies to quantify RNA and surface protein abundance in single cells at the same time. There are technological advancements in which help to capture multimodal data of RNA, protein, chromatin accessibility and spatial information. Although methods have emerged to measure single-cell multimodal read-outs of genome, transcriptome and proteome, measuring translation at the single-cell level is still challenging. Recently, VanInsberghe et al. have developed single-cell ribosome sequencing (scRibo-seq), which relies on the bulk-RiboSeq principle and readouts are at single-cell level. This is a ground-breaking method and delivers information of translation dynamics at the single-cell level.


In this research topic, we welcome manuscripts that help to address some of the following important questions:

a) What is future of single-cell technologies;

b) Measuring ribosome footprints at single-cell level;

c) Computational approaches to analyse single-cell multimodal dataset.


We welcome contributions in the form of original research, review, mini review, case report, hypothesis and theory, perspective, both experimental and computational studies that cover, but are not limited to, following themes:

a) Recent advancement of single-cell technologies;

b) Single-cell Ribosome Profile;

c) Development of new computational methods to integrate information across different data types in the single-cell field;

d) Multimodal omics measurements: future of science.