Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation
© 2020 The Author(s). Published by Oxford University Press. All rights reserved. Motivation: The advent of in vivo automated techniques for single-cell lineaging, sequencing and analysis of gene expression has begun to dramatically increase our understanding of organismal development. We applied nov...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Oxford University Press (OUP)
2021
|
| Online Access: | https://hdl.handle.net/1721.1/136663 |
| _version_ | 1826194653462921216 |
|---|---|
| author | Hutchison, Luke AD Berger, Bonnie Kohane, Isaac S |
| author_facet | Hutchison, Luke AD Berger, Bonnie Kohane, Isaac S |
| author_sort | Hutchison, Luke AD |
| collection | MIT |
| description | © 2020 The Author(s). Published by Oxford University Press. All rights reserved. Motivation: The advent of in vivo automated techniques for single-cell lineaging, sequencing and analysis of gene expression has begun to dramatically increase our understanding of organismal development. We applied novel meta-analysis and visualization techniques to the EPIC single-cell-resolution developmental gene expression dataset for Caenorhabditis elegans from Bao, Murray, Waterston et al. to gain insights into regulatory mechanisms governing the timing of development. Results: Our meta-analysis of the EPIC dataset revealed that a simple linear combination of the expression levels of the developmental genes is strongly correlated with the developmental age of the organism, irrespective of the cell division rate of different cell lineages. We uncovered a pattern of collective sinusoidal oscillation in gene activation, in multiple dominant frequencies and in multiple orthogonal axes of gene expression, pointing to the existence of a coordinated, multi-frequency global timing mechanism. We developed a novel method based on Fisher's Discriminant Analysis to identify gene expression weightings that maximally separate traits of interest, and found that remarkably, simple linear gene expression weightings are capable of producing sinusoidal oscillations of any frequency and phase, adding to the growing body of evidence that oscillatory mechanisms likely play an important role in the timing of development. We cross-linked EPIC with gene ontology and anatomy ontology terms, employing Fisher's Discriminant Analysis methods to identify previously unknown positive and negative genetic contributions to developmental processes and cell phenotypes. This meta-analysis demonstrates new evidence for direct linear and/or sinusoidal mechanisms regulating the timing of development. We uncovered a number of previously unknown positive and negative correlations between developmental genes and developmental processes or cell phenotypes. Our results highlight both the continued relevance of the EPIC technique, and the value of metaanalysis of previously published results. The presented analysis and visualization techniques are broadly applicable across developmental and systems biology. Availability and implementation: Analysis software available upon request. |
| first_indexed | 2024-09-23T09:59:52Z |
| format | Article |
| id | mit-1721.1/136663 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T09:59:52Z |
| publishDate | 2021 |
| publisher | Oxford University Press (OUP) |
| record_format | dspace |
| spelling | mit-1721.1/1366632021-10-28T04:37:03Z Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation Hutchison, Luke AD Berger, Bonnie Kohane, Isaac S © 2020 The Author(s). Published by Oxford University Press. All rights reserved. Motivation: The advent of in vivo automated techniques for single-cell lineaging, sequencing and analysis of gene expression has begun to dramatically increase our understanding of organismal development. We applied novel meta-analysis and visualization techniques to the EPIC single-cell-resolution developmental gene expression dataset for Caenorhabditis elegans from Bao, Murray, Waterston et al. to gain insights into regulatory mechanisms governing the timing of development. Results: Our meta-analysis of the EPIC dataset revealed that a simple linear combination of the expression levels of the developmental genes is strongly correlated with the developmental age of the organism, irrespective of the cell division rate of different cell lineages. We uncovered a pattern of collective sinusoidal oscillation in gene activation, in multiple dominant frequencies and in multiple orthogonal axes of gene expression, pointing to the existence of a coordinated, multi-frequency global timing mechanism. We developed a novel method based on Fisher's Discriminant Analysis to identify gene expression weightings that maximally separate traits of interest, and found that remarkably, simple linear gene expression weightings are capable of producing sinusoidal oscillations of any frequency and phase, adding to the growing body of evidence that oscillatory mechanisms likely play an important role in the timing of development. We cross-linked EPIC with gene ontology and anatomy ontology terms, employing Fisher's Discriminant Analysis methods to identify previously unknown positive and negative genetic contributions to developmental processes and cell phenotypes. This meta-analysis demonstrates new evidence for direct linear and/or sinusoidal mechanisms regulating the timing of development. We uncovered a number of previously unknown positive and negative correlations between developmental genes and developmental processes or cell phenotypes. Our results highlight both the continued relevance of the EPIC technique, and the value of metaanalysis of previously published results. The presented analysis and visualization techniques are broadly applicable across developmental and systems biology. Availability and implementation: Analysis software available upon request. 2021-10-27T20:36:31Z 2021-10-27T20:36:31Z 2020 2021-05-17T17:45:26Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/136663 en 10.1093/BIOINFORMATICS/BTZ864 Bioinformatics Creative Commons Attribution NonCommercial License 4.0 https://creativecommons.org/licenses/by-nc/4.0/ application/pdf Oxford University Press (OUP) Oxford University Press |
| spellingShingle | Hutchison, Luke AD Berger, Bonnie Kohane, Isaac S Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title | Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title_full | Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title_fullStr | Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title_full_unstemmed | Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title_short | Meta-analysis of Caenorhabditis elegans single-cell developmental data reveals multi-frequency oscillation in gene activation |
| title_sort | meta analysis of caenorhabditis elegans single cell developmental data reveals multi frequency oscillation in gene activation |
| url | https://hdl.handle.net/1721.1/136663 |
| work_keys_str_mv | AT hutchisonlukead metaanalysisofcaenorhabditiseleganssinglecelldevelopmentaldatarevealsmultifrequencyoscillationingeneactivation AT bergerbonnie metaanalysisofcaenorhabditiseleganssinglecelldevelopmentaldatarevealsmultifrequencyoscillationingeneactivation AT kohaneisaacs metaanalysisofcaenorhabditiseleganssinglecelldevelopmentaldatarevealsmultifrequencyoscillationingeneactivation |