Mutual information, multiple mutations, and non-random adaptive evolution
Posted on March 16, 2013 by James Kohl.
Re: Non-random adaptive evolution.
Nucl. Acids Res. first published online March 6, 2013 doi:10.1093/nar/gkt147 [Full text is free]
Jianxin Wang, Bo Chen, Yaqun Wang, Ningtao Wang, Marc Garbey, Roger Tran-Son-Tay, Scott A. Berceli, and Rongling Wu
Article excerpt: “The difference of expression for the same gene between different environments is called expression plasticity (7,8). As a new concept, expression plasticity has emerged to be useful for studying the constraints for the evolution of gene expression in fluctuating environments (9–11).”
My comment: The citations to works that support the “new concept” of expression plasticity do not address hormone-organized and hormone-activated behavior associated with the concept of expression plasticity we detailed in our 1996 Hormones and Behavior review article, which was later used in the context of hormone-organized and hormone-activated gene expression and invertebrate behavior.
Article excerpt: Our model for network construction capitalizes on gene expression plasticity, aimed at gleaning a better insight into the regulatory mechanisms for an organism’s adaptation to environmental changes. The model is founded on mutual information, a quantity that measures the mutual dependence of the two random variables, particularly in terms of positive, negative and non-linear correlations (12).
My comment: My model incorporates two variables that do not randomly occur. Although the availability of nutrients is the first variable, it is also linked to the metabolism of the nutrients and the production of pheromones that control reproduction in species from microbes to man. Although the article may indicate that they are addressing “…the mutual dependence of the two random variables, particularly in terms of positive, negative and non-linear correlations…” what they actually are addressing is the epigenetic effects of nutrients and pheromones on the microRNA/messenger RNA balance responsible for de novo gene expression and adaptive evolution in species from microbes to man.
Article excerpt: External stimuli or agents can alter the speed and direction of cellular processes through differential expression of the gene set. There exist specific mechanisms that shepherd the signal into the nucleus, where signal integration occurs by complex transcription factor networks.
My comment: The specific mechanisms are detailed in my model, with information added to our 1996 representation of how the epigenetic landscape becomes the physical landscape of DNA via chromatin remodeling. My model of systems biology represents the conservation of bottom-up organization and top-down activation via: 1) Nutrient stress-induced and social stress-induced intracellular changes in the microRNA (miRNA) / messenger RNA (mRNA) balance; 2) Intermolecular changes in DNA (genes) and alternative splicing; 3) Non-random experience-dependent stochastic variations in de novo gene expression and biosynthesis of odor receptors; 4) The required gene-cell-tissue-organ-organ system pathway that links sensory input directly to gene activation in neurosecretory cells and to miRNA-facilitated learning and memory in the amygdala of the adaptively evolved mammalian brain; and 5) The required reciprocity that links gene expression to behavior that alters gene expression (i.e., reciprocity from genes to behavior and back) in model organisms like the honeybee.”
Wang et al., mathematically confirm the cause and effect in my model. It is unfortunate that some people may be misled by their mention of “…mutual dependence of the two random variables…” when their mutual dependence shows they are not random. Similarly, Adaptive Evolution of Multiple Traits Through Multiple Mutations at a Single Gene does not suggest that adaptive evolution occurs via random mutations.
The “multiple mutations” theory is simply another misrepresentation of nutrient-dependent pheromone-controlled epigenetic effects on gene expression. Note, however, that progress is made by approaching evidence for multiple mutations of a single gene instead of random mutations of multiple genes that slowly accumulate and cause something that random mutations theory cannot explain, which is the thermodynamically controlled thermoregulation of adaptive evolution in my model.
Retired medical laboratory scientist
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