Structural Variation in the Human Genome

Back in mid December I attended a talk by Evan Eichler entitled, “Structural Variation in the Human Genome”. Evan gave an excellent talk focusing on his lab’s recent work on identifying the regions of the genome which change in structure and content very quickly. In short, identify length variations within the human genome. His talk broke down into two major components:

1. Identify duplicated regions associated with phenotypes
2. Catalog normal structural variation in the genome

I’ll go into more details on both below the fold …

Buffering Mechanisms for genetic information

Over the holidays I read a Review article entitled “From genotype to phenotype: buffering mechanisms and the storage of genetic information” by S.L. Rutherford.

Most models of evolution focus on DNA variation, either between individuals or between populations. However, reality is a bit more complicated, as most natural selection acts on variation among phenotypes rather than genotypes. The mapping from phenotype to genotype is complicated by the fact that genetic buffering allows for the buildup and storage of genetic variation in phenotypically normal populations.

“A more realistic picture of genetic networks will emerge from combining the perspectives of molecular and developmental genetics with those of population and evolutionary genetics. Understanding how specific genes are modulated relative to genetic and environmental variation is essential to understanding the course of evolution.”

“Natural History” of Ascomycota fungi

Nature recently published a paper by Wapinski et. al. entitled “Natural history and evolutionary principles of gene duplication in fungi.”. This was a follow up paper to their ISMB paper “Automatic genome-wide reconstruction of phylogenetic gene trees.” Bioinformatics, 23(13), i549-i558 (2007). DOI: 10.1093/bioinformatics/btm193. In these papers the authors seek to answer the following questions:

1. How does one clearly identify orthologs?
2. What genes share a common ancestor?
3. What happened to them along the way?

Orthologous TFs have different functions and regulate different genes.

A recent PLoS Comp. Bio paper by Price, Dehal and Arkin (2007) looked at the evolution of transcription factors — focusing on the ability of bi-directional blast hits (BBH) to predict orthology. Their findings (in brief):

1. BBHs of TFs from distantly related bacteria are usually not evolutionary orthologs.
2. False orthologs typically respond to different signals and regulate different genes.
3. True evolutionary orthologs typically have (nearly) conserved function.
4. Regulatory networks evolve more rapidly than previously thought, as even closely in closely related species specific predictions are incorrect.

Anyone who has followed the literature on gene duplication evolution, the orthology inference problem, or TF binding/motif evolution should not be surprised by their findings. Predicting the associations of a particular TF with targets might not even be inferrable in detail (even in closely related sequences) if the “neutral binding” / “neutral turnover” model is true.

M. Eisen’s work in the twelve Drosophilia species emphasizes this point as well — since the two points he raised at the recent RECOMB meeting on Regulatory Genomics were that (1) most binding may be neutral and (2) distant enhancers with very different patterns of binding events can still drive correct patterning in Drosophilia. I am reminded of G. Wray who stated (in his Jan 2005 Symposium on Complex Life Histories in Marine Bathic Invertebrates) that the “picture of cis-regulatory sequence evolution that is emerging is one of dynamic change at the level of sequence comparison, coupled with long-term conservation of expression profiles.”

Price, M.N., Dehal, P.S., Arkin, A.P. (2007). Orthologous Transcription Factors in Bacteria Have Different Functions and Regulate Different Genes. PLoS Computational Biology, 3(9), e175. DOI: 10.1371/journal.pcbi.0030175

Evolutionary Dynamics of Language

A pair of letters appeared in this week’s Nature which are quite interesting. Pagel et. al. have a piece on how the frequency of word-use predicts the rate of lexical change in Indo-European history [Nature 449:717-721]. This is complemented by the Lieberman et. al. piece on quantifying the evolutionary dynamics of language [Nature 449:713-716], which focuses in on the use of conjugation. There is also a corresponding News and Views written by W. Tecumseh Fitch which puts these two papers into the context of the larger field of linguistics.