Since methods involving the capture of single cells in microfluidic droplets along with barcoded mRNA capture beads [1, 2, 3] were first published in 2015, the number of published papers reporting the use of single-cell RNA-Seq (scRNA-Seq) has grown exponentially. Over the last two years, experience in single-cell analysis using high-throughput microfluidic techniques was consolidated and numerous studies were carried out on mammalian cells [4, 5] as well as on non-mammalian cell types, such as insect [6] and plant cells [7].
Further methods were also combined with scRNA-Seq to not only obtain information about the transcriptome but also on protein expression [8] and chromatin configuration [9]. In most cases, except in liquid samples such as blood, performing scRNA-Seq involves tissue dissociation to obtain a suspension of truly single cells. Some tissues may however be difficult to dissociate or some cell types, e.g. neurons, might be too fragile to survive as single cells. This problem was addressed through the development of the DroNc-Seq method whereby single nuclei are encapsulated instead of single cells [10].
The potential of single-cell analysis along with recent in advances in computational algorithms was harnessed through the initial launch of the Human Cell Atlas (HCA) in October 2016 and the launch of its Phase 1 a year later [11]. The HCA is an international consortium, which has the objective to comprehensively map all human cell types and their properties with a view to use this information to monitor health and diagnose and treat diseases. Single-cell analysis is indeed proving particularly valuable in the field of medical research, especially cancer research. 2018 saw the publication of numerous new studies in scRNA-Seq of human tumours that will lead the way to the production of high-resolution maps of all cell types in such tumours [12]. Such maps are expected to help with understanding the mechanisms associated with disease development and progression, as well as diagnosis and therapy after functional validation in vitro and in vivo.
Functional validation is indeed an important next step in the field of single-cell research. The various cell types, cell states, lineages and biological markers identified through single-cell analysis, i.e. through statistical analysis and correlation, now require experimental validation [13]. The objective will be to find evidence that a predicted cell type exists in a tissue and has unique properties differentiating it from other cell types. The combination of scRNA-Seq with other methods, so called “multi-omics”, is expected to gain momentum in the future. This will lead to a more complete profiling of a cell by obtaining information about its transcriptome, chromatin accessibility, epigenome and cellular ancestry simultaneously [14]. Such abundance of information will promote clinical advances, particularly in oncology, through the identification of cell types associated with drug resistance [15]. The ability to detect drug-resistant cell types will help develop novel treatment methods specifically targeted at them. It will also help detecting the emergence of drug-resistant clones in patients and inform the decision for the next stage of treatment, paving the way for the development of personalised medicine [16]. In the field of plant biology, single-cell research is gaining interest despite specific challenges associated with cell isolation from plants [17]. Through the identification of cell types and cell lineages, single-cell analysis will be helpful to better understanding the development dynamics of plant tissues as well as plant stress signalling and responses. Such research will provide data to support selective breeding of crops and produce high-yielding, stress-tolerant cultivars in a world that is facing ever growing challenges to feed its human population [18].
References
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