Lessons from single-cell RNA sequencing of human islets
Ngara, Mtakai LU
and Wierup, Nils
LU
(2022)
In Diabetologia
65(8).
p.1241-1250
- Abstract
Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of... (More)
Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area. Graphical abstract: [Figure not available: see fulltext.].
(Less)
- author
- Ngara, Mtakai
LU
and Wierup, Nils
LU
- organization
- publishing date
- 2022
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Alpha cell, Beta cell, Differential expression analysis, Ghrelin cell, Islet, Single-cell RNA sequencing, Type 2 diabetes mechanisms
- in
- Diabetologia
- volume
- 65
- issue
- 8
- pages
- 1241 - 1250
- publisher
- Springer
- external identifiers
-
- scopus:85128904697
- pmid:35482056
- ISSN
- 0012-186X
- DOI
- 10.1007/s00125-022-05699-1
- language
- English
- LU publication?
- yes
- id
- fc332b21-c238-449c-a536-621c9f04a5c2
- date added to LUP
- 2022-06-29 14:12:37
- date last changed
- 2024-06-27 11:50:31
@article{fc332b21-c238-449c-a536-621c9f04a5c2,
abstract = {{<p>Islet dysfunction is central in type 2 diabetes and full-blown type 2 diabetes develops first when the beta cells lose their ability to secrete adequate amounts of insulin in response to raised plasma glucose. Several mechanisms behind beta cell dysfunction have been put forward but many important questions still remain. Furthermore, our understanding of the contribution of each islet cell type in type 2 diabetes pathophysiology has been limited by technical boundaries. Closing this knowledge gap will lead to a leap forward in our understanding of the islet as an organ and potentially lead to improved treatments. The development of single-cell RNA sequencing (scRNAseq) has led to a breakthrough for characterising the transcriptome of each islet cell type and several important observations on the regulation of cell-type-specific gene expression have been made. When it comes to identifying type 2 diabetes disease mechanisms, the outcome is still limited. Several studies have identified differentially expressed genes, although there is very limited consensus between the studies. As with all new techniques, scRNAseq has limitations; in addition to being extremely expensive, genes expressed at low levels may not be detected, noise may not be appropriately filtered and selection biases for certain cell types are at hand. Furthermore, recent advances suggest that commonly used computational tools may be suboptimal for analysis of scRNAseq data in small-scale studies. Fortunately, development of new computational tools holds promise for harnessing the full potential of scRNAseq data. Here we summarise how scRNAseq has contributed to increasing the understanding of various aspects of islet biology as well as type 2 diabetes disease mechanisms. We also focus on challenges that remain and propose steps to promote the utilisation of the full potential of scRNAseq in this area. Graphical abstract: [Figure not available: see fulltext.].</p>}},
author = {{Ngara, Mtakai and Wierup, Nils}},
issn = {{0012-186X}},
keywords = {{Alpha cell; Beta cell; Differential expression analysis; Ghrelin cell; Islet; Single-cell RNA sequencing; Type 2 diabetes mechanisms}},
language = {{eng}},
number = {{8}},
pages = {{1241--1250}},
publisher = {{Springer}},
series = {{Diabetologia}},
title = {{Lessons from single-cell RNA sequencing of human islets}},
url = {{http://dx.doi.org/10.1007/s00125-022-05699-1}},
doi = {{10.1007/s00125-022-05699-1}},
volume = {{65}},
year = {{2022}},
}