Considering Antagonistic Pleiotropy
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Antagonistic pleiotropy describes a situation in which a gene provides both benefit and drawback under different circumstances. In evolutionary considerations of aging the usual context for this situation is that a gene is selected because it provides competitive advantages in youth, when reproduction is taking place, and then becomes harmful later in life when evolutionary pressure is much reduced. Here researchers take a measure of the prevalence of this phenomenon in yeast:

The genes responsible for inherited diseases are clearly bad for us, so why hasn't evolution, over time, weeded them out and eliminated them from the human genome altogether? Part of the reason seems to be that genes that can harm us at one stage of our lives are necessary and beneficial to us at other points in our development. [Researchers now] report that antagonistic pleiotropy is very common in yeast, a single-celled organism used by scientists to provide insights about genetics and cell biology.

"In any given environment, yeast expresses hundreds of genes that harm rather than benefit the organism, demonstrating widespread antagonistic pleiotropy. The surprising finding is the sheer number of such genes in the yeast genome that have such properties. From our yeast data we can predict that humans should have even more antagonistic pleiotropy than yeast."

Yeast has about 6,000 genes, about 1,000 of which are essential - eliminate any of them and the organism dies. [Researchers] worked with a set of 5,000 laboratory strains of yeast in which one non-essential gene had been deleted from each strain. [They] grew all 5,000 strains together in a single test tube and compared the growth rates of each strain. This side-by-side comparison allowed them to determine which genes were beneficial (increased growth rate) and which ones were harmful (decreased growth rate) under the six environmental conditions.

The researchers found that for each of the six conditions, on average, the yeasts expressed about 300 genes that slowed their growth and were therefore classified as harmful. Deleting those genes resulted in more rapid growth. But many of the genes that were harmful under one set of environmental conditions proved to be beneficial under another, demonstrating widespread antagonistic pleiotropy.

Link: http://www.ns.umich.edu/new/releases/20928-genetic-tradeoff-harmful-genes-are-widespread-in-yeast-but-hold-hidden-benefits

Comments

The problem with this approach of taking each gene in turn is that it fails to take into account the reality of how the systems that utilise the products of their output (proteins) actually work.

Not only will the genetic profile change depending on age and environmental factors but also at any given time the nature of the interaction of proteins produced by genes are what drive function not the individual proteins. There is rarely a linear relationship between a gene and a particular aspect of the output of that system. Single does not equal specific functional impact if deleted.

The interactions create compensatory pathways, positive and negative synergies and balance between sub-systems. This means for instance that in a knock-out experiment a specific gene can be shown to have little or no impact but this gene may still be synergistically critical to the system as part of a set of genes (or rather the proteins they produce). To establish this you would have to do sets of combinations 2,3,4 etc gene knockouts which takes more money and time than our Universe will allow even on yeast. Then you get into the subtle impacts of type of interaction and conformation rather than straight knockout.

Very quickly the logical conclusion becomes that you must be able to interpret the impact of a gene or rather the related proteins at the all important systems level to have any hope of understanding the reality of how to intervene in the system selectively to get the result you want.

This is where network pharmacology adds vital capability where pathway biology and genetic trends cannot deliver. Yeast is a great model for this but research resources would need to be re-channeled.

Posted by: Network Pharmacology Blog at November 2, 2012 6:18 AM
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