Using single‐cell genomics to understand developmental processes and cell fate decisions

Abstract High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as the...

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Main Authors: Jonathan A Griffiths, Antonio Scialdone, John C Marioni
Format: Article
Language:English
Published: Springer Nature 2018-04-01
Series:Molecular Systems Biology
Subjects:
Online Access:https://doi.org/10.15252/msb.20178046
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author Jonathan A Griffiths
Antonio Scialdone
John C Marioni
author_facet Jonathan A Griffiths
Antonio Scialdone
John C Marioni
author_sort Jonathan A Griffiths
collection DOAJ
description Abstract High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single‐cell methods bridge this gap, allowing high‐throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single‐cell gene expression data and highlight areas of developmental biology where single‐cell techniques have made important contributions. These include understanding of cell‐to‐cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.
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spelling doaj-art-99b2514a0d244de7ae36f90f736f58492025-08-20T03:46:32ZengSpringer NatureMolecular Systems Biology1744-42922018-04-0114411210.15252/msb.20178046Using single‐cell genomics to understand developmental processes and cell fate decisionsJonathan A Griffiths0Antonio Scialdone1John C Marioni2Cancer Research UK Cambridge Institute, University of CambridgeEMBL‐European Bioinformatics Institute (EMBL‐EBI), Wellcome Genome CampusCancer Research UK Cambridge Institute, University of CambridgeAbstract High‐throughput ‐omics techniques have revolutionised biology, allowing for thorough and unbiased characterisation of the molecular states of biological systems. However, cellular decision‐making is inherently a unicellular process to which “bulk” ‐omics techniques are poorly suited, as they capture ensemble averages of cell states. Recently developed single‐cell methods bridge this gap, allowing high‐throughput molecular surveys of individual cells. In this review, we cover core concepts of analysis of single‐cell gene expression data and highlight areas of developmental biology where single‐cell techniques have made important contributions. These include understanding of cell‐to‐cell heterogeneity, the tracing of differentiation pathways, quantification of gene expression from specific alleles, and the future directions of cell lineage tracing and spatial gene expression analysis.https://doi.org/10.15252/msb.20178046cell fatedevelopmentdifferentiationsingle‐cell RNA‐seqtranscriptome
spellingShingle Jonathan A Griffiths
Antonio Scialdone
John C Marioni
Using single‐cell genomics to understand developmental processes and cell fate decisions
Molecular Systems Biology
cell fate
development
differentiation
single‐cell RNA‐seq
transcriptome
title Using single‐cell genomics to understand developmental processes and cell fate decisions
title_full Using single‐cell genomics to understand developmental processes and cell fate decisions
title_fullStr Using single‐cell genomics to understand developmental processes and cell fate decisions
title_full_unstemmed Using single‐cell genomics to understand developmental processes and cell fate decisions
title_short Using single‐cell genomics to understand developmental processes and cell fate decisions
title_sort using single cell genomics to understand developmental processes and cell fate decisions
topic cell fate
development
differentiation
single‐cell RNA‐seq
transcriptome
url https://doi.org/10.15252/msb.20178046
work_keys_str_mv AT jonathanagriffiths usingsinglecellgenomicstounderstanddevelopmentalprocessesandcellfatedecisions
AT antonioscialdone usingsinglecellgenomicstounderstanddevelopmentalprocessesandcellfatedecisions
AT johncmarioni usingsinglecellgenomicstounderstanddevelopmentalprocessesandcellfatedecisions