Progress in Discovering Transcriptional Noise in Aging

Josh Bartz, Hannim Jung, Karen Wasiluk, Lei Zhang, Xiao Dong

Research output: Contribution to journalReview articlepeer-review

5 Scopus citations

Abstract

Increasing stochasticity is a key feature in the aging process. At the molecular level, in addition to genome instability, a well-recognized hallmark of aging, cell-to-cell variation in gene expression was first identified in mouse hearts. With the technological breakthrough in single-cell RNA sequencing, most studies performed in recent years have demonstrated a positive correlation between cell-to-cell variation and age in human pancreatic cells, as well as mouse lymphocytes, lung cells, and muscle stem cells during senescence in vitro. This phenomenon is known as the “transcriptional noise” of aging. In addition to the increasing evidence in experimental observations, progress also has been made to better define transcriptional noise. Traditionally, transcriptional noise is measured using simple statistical measurements, such as the coefficient of variation, Fano factor, and correlation coefficient. Recently, multiple novel methods have been proposed, e.g., global coordination level analysis, to define transcriptional noise based on network analysis of gene-to-gene coordination. However, remaining challenges include a limited number of wet-lab observations, technical noise in single-cell RNA sequencing, and the lack of a standard and/or optimal data analytical measurement of transcriptional noise. Here, we review the recent technological progress, current knowledge, and challenges to better understand transcriptional noise in aging.

Original languageEnglish (US)
Article number3701
JournalInternational journal of molecular sciences
Volume24
Issue number4
DOIs
StatePublished - Feb 2023

Bibliographical note

Funding Information:
X.D. is supported by the NIH awards (R00 AG056656, U54 AG076041, and U54 AG079754) and L.Z. by the American Federation for Aging Research (the Sagol Network GerOmic Award for Junior Faculty).

Publisher Copyright:
© 2023 by the authors.

Keywords

  • aging
  • single-cell RNA sequencing
  • transcriptional noise

PubMed: MeSH publication types

  • Journal Article
  • Review

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