SUPR
scRNA seq ILC IBD
Dnr:

sens2017557

Type:

SNIC SENS

Principal Investigator:

Jenny Mjösberg

Affiliation:

Karolinska Institutet

Start Date:

2017-12-15

End Date:

2025-05-01

Primary Classification:

30108: Cell and Molecular Biology

Allocation

Abstract

This project tries to identify the heterogeneity of human innate lymphoid cells in a variety of tissues via single cell transcriptional profiling. The storage requirement will be around 1 TB. We currently have some data on Rackham (SNIC 2017/7-123) but was requested by bioinformatic collaborators at Scilife (WABI support team) to apply for a bigger Project on Bianca, which is supposed to handle human data. We previously assessed the heterogeneity of human tonsil ILCs with the same method (Björklund, Forkel et al, Nat Imm 2016). Our systematic comparison of single-cell transcriptional variation within and between tonsil ILCs proved very informative in terms of discovering novel genes and ILC subsets and we now aim to use a similar approach to assess the heterogeneity of other tissues, both diseased and healthy. We hypothesize that we will reveal unknown genes expressed by ILCs, subpopulations of ILCs and unexpected lineage relationships in the tissue of interest, which is altered in a diseased state. Together with the eukaryotic single cell genomics facility at Scilife we are currently setting up scRNA-seq analysis of ILCs. This method was successfully used in our previous collaboration (Björklund, Forkel et al, Nat Imm 2016). We will sor t ILCs from three patients and three controls into 384-well plates in RNA lysis buffer. RNA will then be extracted, mRNA converted to cDNA and amplified according to established methods. cDNA libraries will be generated and sequenced using the Illumina technology. For the computational analysis, we have applied for full scale WABI support during the fall of 2017. Through this work we will provide many novel insights, such as pure transcriptional profiles of human tissue ILCs which are of high value to the scientific community (currently, at least to the best of our knowledge, only microarray data for human ILC3 is available). The single-cell nature of the data will also allow us to investigate the heterogeneity within ILC populations, so to better understand this newly discovered cell type in a healthy and diseased state.