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Towards a more nuanced understanding of the relationship between sex-biased gene expression and rates of protein-coding sequence evolution.

ABSTRACT: Genes that are differentially expressed between the sexes (sex-biased genes) are among the fastest evolving genes in animal genomes. The majority of sex-biased expression is attributable to genes that are primarily expressed in sex-limited reproductive tissues, and these reproductive genes are often rapidly evolving because of intra- and intersexual selection pressures. Additionally, studies of multiple taxa have revealed that genes with sex-biased expression are also expressed in a limited number of tissues. This is worth noting because narrowly expressed genes are known to evolve faster than broadly expressed genes. Therefore, it is not clear whether sex-biased genes are rapidly evolving because they have sexually dimorphic expression, because they are expressed in sex-limited reproductive tissues, or because they are narrowly expressed. To determine the extend to which other confounding variables can explain the rapid evolution of sex-biased genes, I analyzed the rates of evolution of sex-biased genes in Drosophila melanogaster and Mus musculus in light of tissue-specific measures of expression. I find that genes with sex-biased expression in somatic tissues shared by both sexes are often evolving faster than non-sex-biased genes, but this is best explained by the narrow expression profiles of sex-biased genes. Sex-biased genes in sex-limited tissues in D. melanogaster, however, evolve faster than other narrowly expressed genes. Therefore, the rapid evolution of sex-biased genes is limited only to those genes primarily expressed in sex-limited reproductive tissues.

SUBMITTER: Meisel RP

PROVIDER: S-EPMC3098513 | biostudies-literature | 2011 Jun

REPOSITORIES: biostudies-literature

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Towards a more nuanced understanding of the relationship between sex-biased gene expression and rates of protein-coding sequence evolution.

Meisel Richard P RP

Molecular biology and evolution 20110113 6

Genes that are differentially expressed between the sexes (sex-biased genes) are among the fastest evolving genes in animal genomes. The majority of sex-biased expression is attributable to genes that are primarily expressed in sex-limited reproductive tissues, and these reproductive genes are often rapidly evolving because of intra- and intersexual selection pressures. Additionally, studies of multiple taxa have revealed that genes with sex-biased expression are also expressed in a limited numb ...[more]

PMID: 21239389

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Project description:In real life, we often have to make judgements under uncertainty. One such judgement task is estimating the probability of a given event based on uncertain evidence for the event, such as estimating the chances of actual fire when the fire alarm goes off. On the one hand, previous studies have shown that human subjects often significantly misestimate the probability in such cases. On the other hand, these studies have offered divergent explanations as to the exact causes of these judgment errors (or, synonymously, biases). For instance, different studies have attributed the errors to the neglect (or underweighting) of the prevalence (or base rate) of the given event, or the overweighting of the evidence for the individual event (‘individuating information’), etc. However, whether or to what extent any such explanation can fully account for the observed errors remains unclear. To help fill this gap, we studied the probability estimation performance of non-professional subjects under four different real-world problem scenarios: (i) Estimating the probability of cancer in a mammogram given the relevant evidence from a computer-aided cancer detection system, (ii) estimating the probability of drunkenness based on breathalyzer evidence, and (iii & iv) estimating the probability of an enemy sniper based on two different sets of evidence from a drone reconnaissance system. In each case, we quantitatively characterized the contributions of the various potential explanatory variables to the subjects’ probability judgements. We found that while the various explanatory variables together accounted for about 30 to 45% of the overall variance of the subjects’ responses depending on the problem scenario, no single factor was sufficient to account for more than 53% of the explainable variance (or about 16 to 24% of the overall variance), let alone all of it. Further analyses of the explained variance revealed the surprising fact that no single factor accounted for significantly more than its ‘fair share’ of the variance. Taken together, our results demonstrate quantitatively that it is statistically untenable to attribute the errors of probabilistic judgement to any single cause, including base rate neglect. A more nuanced and unifying explanation would be that the actual biases reflect a weighted combination of multiple contributing factors, the exact mix of which depends on the particular problem scenario.

Dataset Information

Towards a more nuanced understanding of the relationship between sex-biased gene expression and rates of protein-coding sequence evolution.

Publications

Towards a more nuanced understanding of the relationship between sex-biased gene expression and rates of protein-coding sequence evolution.

Similar Datasets

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