Several interesting papers found today, including:
Collins et al., 2008: The authors pulled out a new drug out of a small molecule screen that lengthens lifespan in C. elegans. Ethosuximide works by inhibiting chemosensory neurons, which apparently regulate aging. (Genetic mutants in chemosensory neurons also have extended lifespans.) Probably not going to read this paper in much more detail, but I thought the result was interesting. The hypothesis proposed by the authors is that inhibiting chemosensory perception means that the worms are unable to find food and thus reduce their dietary intake.
Breitling et al., 2008: A critical look at the identification of eQTL “hotspots”, which are basically polymorphisms that are responsible for variation in expression in a wide number of genes (usually by trans effects). They argue that many of the “hotspots” identified thus far are due to coregulated genes: a putative “hotspot” is not actually directly affecting the expression of several genes, but rather a few genes that in turn affect the expression of other genes with related function.
There are many nongenetic mechanisms that can create strongly correlated clusters of functionally related genes. On the one hand, such clusters may be a result of a concerted response to some uncontrolled environmental factor. On the other hand, dissected tissue samples can contain slightly varying fractions of individual cell types, leading to cell-type–specific gene clusters, which vary in a correlated manner.
They propose a better method for assessing the statistical significance of a potential eQTL. They also go on to speculate why genuine “hotspots” are so difficult to identify (more so, they claim, than eQTL that affect variation in their own expression, i.e. by cis effects) and often have small effect sizes.
This rarity of convincing hotspots in genetical genomics studies is intriguing. It could be due to the limited power of the initial studies, but it could also have a more profound reason. For example, it might well be that biological systems are so robust against subtle genetic perturbations that the majority of heritable gene expression variation is effectively “buffered” and does not lead to downstream effects on other genes, protein, metabolites, or phenotypes. Experimental evidence for phenotypic buffering of protein coding polymorphisms is well established.
In fact, it has been shown that phenotypic buffering is a general property of complex gene-regulatory networks. Also, if small heritable changes in transcript levels were transmitted unbuffered throughout the system, there would be a grave danger that genetic recombination would lead to unhealthy combinations of alleles and, consequently, to systems failure. Hotspots with large pleiotropic effects are thus more likely to be removed by purifying selection. If, as thus expected, common alleles are predominantly buffered by the robust properties of the system and hence largely inconsequential for the rest of the molecules in the system, this will have profound consequences for the design and interpretation of genetical genomics studies of complex diseases.
Which, if you think about it, is the cis versus trans argument all over again (complete with the discussion of rare disease alleles that was also made in the Lemos et al paper that I discussed in the last post).
Lee et al., 2008: A paper that tries to predict complex phenotypes that will result from a particular combination of SNPs! Isn’t that biology’s Holy Grail: to predict phenotype from genotype alone? Well, okay, I overstate the case: they do go in with a certain set of phenotypes they’re trying to predict, and they know something about the inheritance of that particular phenotype, whether it be the number of causal QTL or the heritability. I can’t assess how impressive their results were, but they do claim to be able to predict unobserved phenotypes for individuals based on just the genotype data alone, and they also seem to map the QTL affecting the trait with fairly good resolution.
Mitrophanov et al., 2008: Really need to come back to this paper, but it talks about the evolution of a feedforward network motif that is mediated at the post-translational level in an antibiotic resistance pathway in bacteria.
Berry & Gasch, 2008: Another stress response paper from the Gasch lab. Labmate referred me to this paper, which addresses the troubling issue brought up by those deletion library competition experiments that found that genes needed to survive stresses were not the same genes that changed expression in response to stress. The authors of this paper argue that the genes involved in the transcriptional response are not essential for initial stress survival but rather protecting the cell against future/chronic stress. Makes me think there’s promise for my pet idea of “cellular memory” in stress responses…a pet idea that has no experimental justification whatsoever.
