Mapping gene regulatory networks from single-cell omics data
Abstract Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss...
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| Published in | Briefings in functional genomics Vol. 17; no. 4; pp. 246 - 254 |
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| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
England
Oxford University Press
01.07.2018
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| Subjects | |
| Online Access | Get full text |
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| Abstract | Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future. |
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| AbstractList | Abstract
Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future. Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future. Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future.Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs) underlying cell states provides attractive opportunities to mechanistically understand this heterogeneity. In this review, we discuss recently emerging methods to map GRNs from single-cell transcriptomics data, tackling the challenge of increased noise levels and data sparsity compared with bulk data, alongside increasing data volumes. Next, we discuss how new techniques for single-cell epigenomics, such as single-cell ATAC-seq and single-cell DNA methylation profiling, can be used to decipher gene regulatory programmes. We finally look forward to the application of single-cell multi-omics and perturbation techniques that will likely play important roles for GRN inference in the future. |
| Author | Bravo González-Blas, Carmen Aerts, Stein Fiers, Mark W E J Kalender Atak, Zeynep Minnoye, Liesbeth Aibar, Sara |
| AuthorAffiliation | 1 VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium 2 KU Leuven, Department of Human Genetics, Leuven, Belgium |
| AuthorAffiliation_xml | – name: 2 KU Leuven, Department of Human Genetics, Leuven, Belgium – name: 1 VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium |
| Author_xml | – sequence: 1 givenname: Mark W E J orcidid: 0000-0001-5694-2409 surname: Fiers fullname: Fiers, Mark W E J organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium – sequence: 2 givenname: Liesbeth surname: Minnoye fullname: Minnoye, Liesbeth organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium – sequence: 3 givenname: Sara surname: Aibar fullname: Aibar, Sara organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium – sequence: 4 givenname: Carmen surname: Bravo González-Blas fullname: Bravo González-Blas, Carmen organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium – sequence: 5 givenname: Zeynep surname: Kalender Atak fullname: Kalender Atak, Zeynep organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium – sequence: 6 givenname: Stein surname: Aerts fullname: Aerts, Stein email: stein.aerts@kuleuven.vib.be organization: VIB Center for Brain & Disease Research, Laboratory of Computational Biology, Leuven, Belgium |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/29342231$$D View this record in MEDLINE/PubMed |
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| Keywords | single-cell transcriptomics single-cell epigenomics gene regulatory networks |
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Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks... Single-cell techniques are advancing rapidly and are yielding unprecedented insight into cellular heterogeneity. Mapping the gene regulatory networks (GRNs)... |
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| SubjectTerms | DNA methylation epigenetics Epigenomics - methods Gene Expression Profiling - methods Gene Regulatory Networks Sequence Analysis, RNA - methods Single-Cell Analysis - methods transcriptomics |
| Title | Mapping gene regulatory networks from single-cell omics data |
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