» Articles » PMID: 34662394

Aging at Evolutionary Crossroads: Longitudinal Gene Co-expression Network Analyses of Proximal and Ultimate Causes of Aging in Bats

Overview
Journal Mol Biol Evol
Specialty Biology
Date 2021 Oct 18
PMID 34662394
Citations 3
Authors
Affiliations
Soon will be listed here.
Abstract

How, when, and why do organisms, their tissues, and their cells age remain challenging issues, although researchers have identified multiple mechanistic causes of aging, and three major evolutionary theories have been developed to unravel the ultimate causes of organismal aging. A central hypothesis of these theories is that the strength of natural selection decreases with age. However, empirical evidence on when, why, and how organisms age is phylogenetically limited, especially in natural populations. Here, we developed generic comparisons of gene co-expression networks that quantify and dissect the heterogeneity of gene co-expression in conspecific individuals from different age-classes to provide topological evidence about some mechanical and fundamental causes of organismal aging. We applied this approach to investigate the complexity of some proximal and ultimate causes of aging phenotypes in a natural population of the greater mouse-eared bat Myotis myotis, a remarkably long-lived species given its body size and metabolic rate, with available longitudinal blood transcriptomes. M. myotis gene co-expression networks become increasingly fragmented with age, suggesting an erosion of the strength of natural selection and a general dysregulation of gene co-expression in aging bats. However, selective pressures remain sufficiently strong to allow successive emergence of homogeneous age-specific gene co-expression patterns, for at least 7 years. Thus, older individuals from long-lived species appear to sit at an evolutionary crossroad: as they age, they experience both a decrease in the strength of natural selection and a targeted selection for very specific biological processes, further inviting to refine a central hypothesis in evolutionary aging theories.

Citing Articles

Gene co-expression networks reveal sex-biased differences in musculoskeletal ageing.

Olascoaga S, Tovar H, Espinal-Enriquez J Front Aging. 2024; 5:1469479.

PMID: 39359883 PMC: 11445131. DOI: 10.3389/fragi.2024.1469479.


Expanding evolutionary theories of ageing to better account for symbioses and interactions throughout the Web of Life.

Bapteste E, Huneman P, Keller L, Teuliere J, Lopez P, Teeling E Ageing Res Rev. 2023; 89:101982.

PMID: 37321383 PMC: 10771319. DOI: 10.1016/j.arr.2023.101982.


In search of a Drosophila core cellular network with single-cell transcriptome data.

Yang M, Harrison B, Promislow D G3 (Bethesda). 2022; 12(10).

PMID: 35976114 PMC: 9526075. DOI: 10.1093/g3journal/jkac212.

References
1.
Stone L, Simberloff D, Artzy-Randrup Y . Network motifs and their origins. PLoS Comput Biol. 2019; 15(4):e1006749. PMC: 6459481. DOI: 10.1371/journal.pcbi.1006749. View

2.
Huang Z, Jebb D, Teeling E . Blood miRNomes and transcriptomes reveal novel longevity mechanisms in the long-lived bat, Myotis myotis. BMC Genomics. 2016; 17(1):906. PMC: 5103334. DOI: 10.1186/s12864-016-3227-8. View

3.
Tarkhov A, Alla R, Ayyadevara S, Pyatnitskiy M, Menshikov L, Shmookler Reis R . A universal transcriptomic signature of age reveals the temporal scaling of Caenorhabditis elegans aging trajectories. Sci Rep. 2019; 9(1):7368. PMC: 6517414. DOI: 10.1038/s41598-019-43075-z. View

4.
Southworth L, Owen A, Kim S . Aging mice show a decreasing correlation of gene expression within genetic modules. PLoS Genet. 2009; 5(12):e1000776. PMC: 2788246. DOI: 10.1371/journal.pgen.1000776. View

5.
Enge M, Arda H, Mignardi M, Beausang J, Bottino R, Kim S . Single-Cell Analysis of Human Pancreas Reveals Transcriptional Signatures of Aging and Somatic Mutation Patterns. Cell. 2017; 171(2):321-330.e14. PMC: 6047899. DOI: 10.1016/j.cell.2017.09.004. View