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A dynamical systems treatment of transcriptomic trajectories in hematopoiesis
Inspired by Waddington's illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein exogenous signaling dynamics couple to the enormously complex signaling and transcriptional machinery of a cell to elicit qualitative transition...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Company of Biologists Ltd
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281553/ https://www.ncbi.nlm.nih.gov/pubmed/37260149 http://dx.doi.org/10.1242/dev.201280 |
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author | Freedman, Simon L. Xu, Bingxian Goyal, Sidhartha Mani, Madhav |
author_facet | Freedman, Simon L. Xu, Bingxian Goyal, Sidhartha Mani, Madhav |
author_sort | Freedman, Simon L. |
collection | PubMed |
description | Inspired by Waddington's illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein exogenous signaling dynamics couple to the enormously complex signaling and transcriptional machinery of a cell to elicit qualitative transitions in its collective state. Single-cell RNA sequencing (scRNA-seq), which measures the distributions of possible transcriptional states in large populations of differentiating cells, provides an alternate view, in which development is marked by the variations of a myriad of genes. Here, we present a mathematical formalism for rigorously evaluating, from a dynamical systems perspective, whether scRNA-seq trajectories display statistical signatures consistent with bifurcations and, as a case study, pinpoint regions of multistability along the neutrophil branch of hematopoeitic differentiation. Additionally, we leverage the geometric features of linear instability to identify the low-dimensional phase plane in gene expression space within which the multistability unfolds, highlighting novel genetic players that are crucial for neutrophil differentiation. Broadly, we show that a dynamical systems treatment of scRNA-seq data provides mechanistic insights into the high-dimensional processes of cellular differentiation, taking a step toward systematic construction of mathematical models for transcriptomic dynamics. |
format | Online Article Text |
id | pubmed-10281553 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | The Company of Biologists Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-102815532023-06-21 A dynamical systems treatment of transcriptomic trajectories in hematopoiesis Freedman, Simon L. Xu, Bingxian Goyal, Sidhartha Mani, Madhav Development Research Article Inspired by Waddington's illustration of an epigenetic landscape, cell-fate transitions have been envisioned as bifurcating dynamical systems, wherein exogenous signaling dynamics couple to the enormously complex signaling and transcriptional machinery of a cell to elicit qualitative transitions in its collective state. Single-cell RNA sequencing (scRNA-seq), which measures the distributions of possible transcriptional states in large populations of differentiating cells, provides an alternate view, in which development is marked by the variations of a myriad of genes. Here, we present a mathematical formalism for rigorously evaluating, from a dynamical systems perspective, whether scRNA-seq trajectories display statistical signatures consistent with bifurcations and, as a case study, pinpoint regions of multistability along the neutrophil branch of hematopoeitic differentiation. Additionally, we leverage the geometric features of linear instability to identify the low-dimensional phase plane in gene expression space within which the multistability unfolds, highlighting novel genetic players that are crucial for neutrophil differentiation. Broadly, we show that a dynamical systems treatment of scRNA-seq data provides mechanistic insights into the high-dimensional processes of cellular differentiation, taking a step toward systematic construction of mathematical models for transcriptomic dynamics. The Company of Biologists Ltd 2023-06-01 /pmc/articles/PMC10281553/ /pubmed/37260149 http://dx.doi.org/10.1242/dev.201280 Text en © 2023. Published by The Company of Biologists Ltd https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed. |
spellingShingle | Research Article Freedman, Simon L. Xu, Bingxian Goyal, Sidhartha Mani, Madhav A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title | A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title_full | A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title_fullStr | A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title_full_unstemmed | A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title_short | A dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
title_sort | dynamical systems treatment of transcriptomic trajectories in hematopoiesis |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10281553/ https://www.ncbi.nlm.nih.gov/pubmed/37260149 http://dx.doi.org/10.1242/dev.201280 |
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