innsikt - Evolutionary Biology - # Purifying Selection and Gene Expression in Penguins

Gene Expression Drives Purifying Selection in Penguin Populations

Q: How do other life history traits, such as generation time or reproductive strategies, influence the relationship between gene expression and purifying selection in natural populations

Life history traits such as generation time and reproductive strategies can significantly influence the relationship between gene expression and purifying selection in natural populations. For species with shorter generation times, there may be more opportunities for mutations to arise and be subjected to selection within a given timeframe. This can lead to a higher turnover of genetic variation and potentially impact the efficacy of purifying selection. On the other hand, species with longer generation times may experience slower rates of genetic turnover, allowing deleterious mutations to persist for longer periods before being removed by selection. Reproductive strategies, such as mating systems and population structure, can also play a role in shaping the dynamics of purifying selection. For example, species with high levels of inbreeding may have reduced genetic diversity, making them more susceptible to the accumulation of deleterious mutations. In contrast, species with outcrossing mating systems may have higher genetic diversity, providing more raw material for selection to act upon. Additionally, population size and structure can influence the efficiency of purifying selection, with larger populations generally experiencing stronger selection due to increased efficacy in removing deleterious mutations.

Q: What are the potential trade-offs or costs associated with maintaining high expression levels for genes under strong purifying selection

Maintaining high expression levels for genes under strong purifying selection can come with potential trade-offs and costs. One of the main trade-offs is the energy expenditure required for maintaining high levels of gene expression. Producing and maintaining proteins at high levels can be energetically costly for an organism, diverting resources that could be used for other essential biological processes. This energy cost may limit the overall fitness of an organism, especially in resource-limited environments where energy allocation is crucial for survival and reproduction. Another potential cost is the increased risk of misfolded or mis-interacting proteins in cells with high gene expression levels. High expression rates can lead to an accumulation of misfolded proteins, which can disrupt cellular functions and potentially lead to cellular toxicity. To mitigate this risk, cells may need to invest additional resources in quality control mechanisms, such as chaperones and protein degradation pathways, to ensure proper protein folding and function. These additional cellular processes can further strain the cellular machinery and impact overall cellular health and fitness.

Q: Could the insights from this study on the role of gene expression in shaping protein evolution be extended to understand the evolution of gene regulatory networks and their impact on organismal fitness

The insights from this study on the role of gene expression in shaping protein evolution can be extended to understand the evolution of gene regulatory networks and their impact on organismal fitness. Gene regulatory networks play a crucial role in coordinating gene expression patterns and responses to environmental stimuli. Changes in gene expression levels can have cascading effects on downstream biological processes, influencing phenotypic traits and ultimately organismal fitness. By understanding how gene expression levels are linked to purifying selection and protein evolution, researchers can gain insights into how changes in gene regulatory networks may impact the adaptive potential of organisms. For example, alterations in gene expression patterns in response to environmental stressors or evolutionary pressures can shape the genetic diversity within populations and drive evolutionary change. Additionally, studying the interplay between gene expression, purifying selection, and gene regulatory networks can provide valuable information on the molecular mechanisms underlying adaptation and speciation in natural populations.

Grunnleggende konsepter

Gene expression rate is a fundamental driver of purifying selection in natural populations, maintaining strong selection even in small populations.

Sammendrag

The study analyzes genomic and transcriptomic data from two closely related penguin species, the Emperor penguin and the King penguin, to investigate the relationship between gene expression and the efficiency of purifying selection.

Key highlights:

Purifying selection, as measured by the ratio of nonsynonymous to synonymous polymorphisms (πN/πS), declines with increasing gene expression rate in both penguin species.
This decline is driven by a decrease in the number of nonsynonymous variants in highly expressed genes, while the number of synonymous variants remains stable across the expression range.
The difference in nonsynonymous variants between the two penguin populations (with different effective population sizes) decreases with increasing gene expression, suggesting that highly expressed genes experience very strong selection coefficients that can buffer the effects of small population size.
Simulations show that to reproduce the low πN/πS values observed in the top 10% of highly expressed genes, selection coefficients as high as -0.1 are required, which can maintain effective purifying selection even in populations as small as 1,000 individuals.
Highly deleterious variants are found in genes with low expression, indicating that gene expression can be used as a proxy for the distribution of gene selection coefficients in natural populations.

Overall, the study provides evidence that gene expression is a fundamental driver of purifying selection, maintaining strong selection on highly expressed genes even in small populations.

Tilpass sammendrag

Omskriv med AI

Generer sitater

Oversett kilde

Til et annet språk

Generer tankekart

fra kildeinnhold

Besøk kilde

biorxiv.org

Statistikk

The top 10% of highly expressed genes experience an average selection coefficient of -0.1.
The top 50% of highly expressed genes experience an average selection coefficient of -0.01.

Sitater

"Gene expression rate can be regarded as a fundamental parameter of protein evolution in natural populations, maintaining selection effective even at small population size."
"We suggest it could be used as a proxy for gene selection coefficients, which are notoriously difficult to derive in non-model species under real-world conditions."

Viktige innsikter hentet fra

Gene expression is the main driver of purifying selection in large penguin populations

by Trucchi,E., ... klokken www.biorxiv.org 08-08-2023

https://www.biorxiv.org/content/10.1101/2023.08.08.552445v2

Dypere Spørsmål

How do other life history traits, such as generation time or reproductive strategies, influence the relationship between gene expression and purifying selection in natural populations

Life history traits such as generation time and reproductive strategies can significantly influence the relationship between gene expression and purifying selection in natural populations. For species with shorter generation times, there may be more opportunities for mutations to arise and be subjected to selection within a given timeframe. This can lead to a higher turnover of genetic variation and potentially impact the efficacy of purifying selection. On the other hand, species with longer generation times may experience slower rates of genetic turnover, allowing deleterious mutations to persist for longer periods before being removed by selection.
Reproductive strategies, such as mating systems and population structure, can also play a role in shaping the dynamics of purifying selection. For example, species with high levels of inbreeding may have reduced genetic diversity, making them more susceptible to the accumulation of deleterious mutations. In contrast, species with outcrossing mating systems may have higher genetic diversity, providing more raw material for selection to act upon. Additionally, population size and structure can influence the efficiency of purifying selection, with larger populations generally experiencing stronger selection due to increased efficacy in removing deleterious mutations.

What are the potential trade-offs or costs associated with maintaining high expression levels for genes under strong purifying selection

Maintaining high expression levels for genes under strong purifying selection can come with potential trade-offs and costs. One of the main trade-offs is the energy expenditure required for maintaining high levels of gene expression. Producing and maintaining proteins at high levels can be energetically costly for an organism, diverting resources that could be used for other essential biological processes. This energy cost may limit the overall fitness of an organism, especially in resource-limited environments where energy allocation is crucial for survival and reproduction.
Another potential cost is the increased risk of misfolded or mis-interacting proteins in cells with high gene expression levels. High expression rates can lead to an accumulation of misfolded proteins, which can disrupt cellular functions and potentially lead to cellular toxicity. To mitigate this risk, cells may need to invest additional resources in quality control mechanisms, such as chaperones and protein degradation pathways, to ensure proper protein folding and function. These additional cellular processes can further strain the cellular machinery and impact overall cellular health and fitness.

Could the insights from this study on the role of gene expression in shaping protein evolution be extended to understand the evolution of gene regulatory networks and their impact on organismal fitness

The insights from this study on the role of gene expression in shaping protein evolution can be extended to understand the evolution of gene regulatory networks and their impact on organismal fitness. Gene regulatory networks play a crucial role in coordinating gene expression patterns and responses to environmental stimuli. Changes in gene expression levels can have cascading effects on downstream biological processes, influencing phenotypic traits and ultimately organismal fitness.
By understanding how gene expression levels are linked to purifying selection and protein evolution, researchers can gain insights into how changes in gene regulatory networks may impact the adaptive potential of organisms. For example, alterations in gene expression patterns in response to environmental stressors or evolutionary pressures can shape the genetic diversity within populations and drive evolutionary change. Additionally, studying the interplay between gene expression, purifying selection, and gene regulatory networks can provide valuable information on the molecular mechanisms underlying adaptation and speciation in natural populations.