#single-cell

Single-cell RNA-sequencing (scRNA-seq) is a contemporary next-generation sequencing (NGS) approach designed for the genome-wide measurement of transcriptomic information in individual cells.

The improvements in molecular profiling technologies such as next-generation sequencing have reached the level of characterization of individual cells .

Difficult to study pure immune cell subsets in species other than mice and humans - lack of commercially-available/reliable FACS antibodies - consequently little is known about counterparts to mouse/human immune cell types [Surely this is possible to overcome in a dedicated lab?]

Single ‘lymphocytes’ isolated based on lck-driven GFP - mostly T cells + NK + small population of myeloid [No B cells identified though - zebrafish do have them?]

Findings match well what is known in humans/mice:

- T cells (CD4/CD8-expressing), NK cells (nitr/dicp expressing), myeloid cells (spi1b-expressing) form distinct clusters from ‘multidimensional scaling’ clustering - Clusters also exhibit expected transcriptional profiles: CD4/CD8 mutually exclusive expression, T cell lineage markers (CTLA-4, CD28, TCF7, CCR7, IL-10R etc etc) highly differentially expressed in T cell cluster; perforin/granzyme pathway and FasL pathway genes etc differentially expressed in NK cluster; Fc receptors, CSFRb etc in myeloid clusters - NK genes evolve faster than T cell genes (inavailability of somatic mutation --> population-level evolution), myeloid cells potentially somewhere in between (immune cells in generally evolve faster than other cells)

Fig 2.

INTERESTING: Demonstration of single-cell seq as a technique to perform both population discovery and population characterisation. 

QUESTION: Considering sequence divergence, how robust is direct comparison with mouse/human genes? How do we know the proteins or the cells do the same thing?