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Lack of evidence for increased transcriptional noise in aged tissues

Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA s...

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Autores principales: Ibañez-Solé, Olga, Ascensión, Alex M, Araúzo-Bravo, Marcos J, Izeta, Ander
Formato: Online Artículo Texto
Lenguaje:English
Publicado: eLife Sciences Publications, Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934862/
https://www.ncbi.nlm.nih.gov/pubmed/36576247
http://dx.doi.org/10.7554/eLife.80380
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author Ibañez-Solé, Olga
Ascensión, Alex M
Araúzo-Bravo, Marcos J
Izeta, Ander
author_facet Ibañez-Solé, Olga
Ascensión, Alex M
Araúzo-Bravo, Marcos J
Izeta, Ander
author_sort Ibañez-Solé, Olga
collection PubMed
description Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA sequencing (scRNAseq). However, the diverse computational methods used for the quantification of age-related loss of cellular identity have prevented reaching meaningful conclusions by direct comparison of existing scRNAseq datasets. To address these issues we created Decibel, a Python toolkit that implements side-to-side four commonly used methods for the quantification of age-related transcriptional noise in scRNAseq data. Additionally, we developed Scallop, a novel computational method for the quantification of membership of single cells to their assigned cell type cluster. Cells with a greater Scallop membership score are transcriptionally more stable. Application of these computational tools to seven aging datasets showed large variability between tissues and datasets, suggesting that increased transcriptional noise is not a universal hallmark of aging. To understand the source of apparent loss of cell type identity associated with aging, we analyzed cell type-specific changes in transcriptional noise and the changes in cell type composition of the mammalian lung. No robust pattern of cell type-specific transcriptional noise alteration was found across aging lung datasets. In contrast, age-associated changes in cell type composition of the lung were consistently found, particularly of immune cells. These results suggest that claims of increased transcriptional noise of aged tissues should be reformulated.
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spelling pubmed-99348622023-02-17 Lack of evidence for increased transcriptional noise in aged tissues Ibañez-Solé, Olga Ascensión, Alex M Araúzo-Bravo, Marcos J Izeta, Ander eLife Computational and Systems Biology Aging is often associated with a loss of cell type identity that results in an increase in transcriptional noise in aged tissues. If this phenomenon reflects a fundamental property of aging remains an open question. Transcriptional changes at the cellular level are best detected by single-cell RNA sequencing (scRNAseq). However, the diverse computational methods used for the quantification of age-related loss of cellular identity have prevented reaching meaningful conclusions by direct comparison of existing scRNAseq datasets. To address these issues we created Decibel, a Python toolkit that implements side-to-side four commonly used methods for the quantification of age-related transcriptional noise in scRNAseq data. Additionally, we developed Scallop, a novel computational method for the quantification of membership of single cells to their assigned cell type cluster. Cells with a greater Scallop membership score are transcriptionally more stable. Application of these computational tools to seven aging datasets showed large variability between tissues and datasets, suggesting that increased transcriptional noise is not a universal hallmark of aging. To understand the source of apparent loss of cell type identity associated with aging, we analyzed cell type-specific changes in transcriptional noise and the changes in cell type composition of the mammalian lung. No robust pattern of cell type-specific transcriptional noise alteration was found across aging lung datasets. In contrast, age-associated changes in cell type composition of the lung were consistently found, particularly of immune cells. These results suggest that claims of increased transcriptional noise of aged tissues should be reformulated. eLife Sciences Publications, Ltd 2022-12-28 /pmc/articles/PMC9934862/ /pubmed/36576247 http://dx.doi.org/10.7554/eLife.80380 Text en © 2022, Ibañez-Solé, Ascensión et al https://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited.
spellingShingle Computational and Systems Biology
Ibañez-Solé, Olga
Ascensión, Alex M
Araúzo-Bravo, Marcos J
Izeta, Ander
Lack of evidence for increased transcriptional noise in aged tissues
title Lack of evidence for increased transcriptional noise in aged tissues
title_full Lack of evidence for increased transcriptional noise in aged tissues
title_fullStr Lack of evidence for increased transcriptional noise in aged tissues
title_full_unstemmed Lack of evidence for increased transcriptional noise in aged tissues
title_short Lack of evidence for increased transcriptional noise in aged tissues
title_sort lack of evidence for increased transcriptional noise in aged tissues
topic Computational and Systems Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9934862/
https://www.ncbi.nlm.nih.gov/pubmed/36576247
http://dx.doi.org/10.7554/eLife.80380
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