Mailund on the Internet

I am currently involved in a study where we have a gene showing both disease association and high differentiation between Africans and Europeans/Asians (as far as we can see from HapMap data). Sorry, I cannot give more details right now.

Anyway, because of this study I finally got around to reading this paper:

A Map of Recent Positive Selection in the Human Genome

Voight BF, Kudaravalli S, Wen X, Pritchard JK.
PLoS Biology 2007 4(3): e72 doi:10.1371/journal.pbio.0040072

Abstract

The identification of signals of very recent positive selection provides information about the adaptation of modern humans to local conditions. We report here on a genome-wide scan for signals of very recent positive selection in favor of variants that have not yet reached fixation. We describe a new analytical method for scanning single nucleotide polymorphism (SNP) data for signals of recent selection, and apply this to data from the International HapMap Project. In all three continental groups we find widespread signals of recent positive selection. Most signals are region-specific, though a significant excess are shared across groups. Contrary to some earlier low resolution studies that suggested a paucity of recent selection in sub-Saharan Africans, we find that by some measures our strongest signals of selection are from the Yoruba population. Finally, since these signals indicate the existence of genetic variants that have substantially different fitnesses, they must indicate loci that are the source of significant phenotypic variation. Though the relevant phenotypes are generally not known, such loci should be of particular interest in mapping studies of complex traits. For this purpose we have developed a set of SNPs that can be used to tag the strongest ~250 signals of recent selection in each population.

I knew of the results already from a talk by Jonathan Pritchard that I attended this summer, but I hadn't read the paper until now.

The idea is pretty neat: by looking at the haplotypes around a SNP, and how they break down with distance from the SNP, you can spot which SNPs have changed rapidly from low frequency to higher frequency and these SNPs are candidates for being under selection.

This is illustrated nicely in Figure 1 from the paper:

 

A) Decay of haplotypes in a single region in which a new selected allele (red, center column) is sweeping to fixation, replacing the ancestral allele (blue). Horizontal lines are haplotypes; SNP positions are marked below the haplotype plot using blue for SNPs with intermediate allele frequencies (minor allele >0.2), and red otherwise. For a given SNP, adjacent haplotypes with the same color carry identical genotypes everywhere between that SNP and the central (selected) site. The left- and right-hand sides are sorted separately. Haplotypes are no longer plotted beyond the points at which they become unique.

B) Decay of haplotype homozygosity for ten replicate simulations. When the core SNP is neutral (σ = 0; left side) the haplotype homozygosity decays at similar rates for both ancestral and derived alleles. When the derived alleles are favored (σ = 2Ns = 250; right side), the haplotype homozygosity decays much slower for the derived alleles than for the ancestral alleles. The discrepancy in the overall areas spanned by these two curves forms the basis of our text for selection (iHS).

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The citation was (for the benefit of Research Blogging):
Voight, B., Kudaravalli, S., Wen, X., Pritchard, J. (2006). A Map of Recent Positive Selection in the Human Genome. PLoS Biology, 4(3).

I just saw this deCODEme add on Eye on DNA:

It was a bit funny seeing the place I've visited so often on YouTube, and to see people I've met up there describe deCODEme. (I've had some discussions with Agnar and talked to Hakon a few times, but my work when I'm visiting DeCODE is not involving them so I do not know them that well, but still).

My work there has nothing to do with deCODEme, though, but with genome wide association mapping. You can read about it on the PolyGene homepage.

Now there's a study that shows that identical (monozygotic) twins do not have identical genomes (I spotted it here at DNA Direct talk -- I'm getting a lot of science news now that I follow the DNA network).

The genomes are pretty close, but not identical. There seem to be a lot of structural variation between them.

I guess it doesn't surprise me all that much, even if it looks like a major discovery. Considering that the cells within an individual have almost but not quite identical genomes, I would be very surprised if twins' genomes were identical.

For reading about the somatic cell differences, this is an excellent paper:

Genomic Variability within an Organism Exposes Its Cell Lineage Tree

Frumkin D, Wasserstrom A, Kaplan S, Feige U, Shapiro E

Genomic Variability within an Organism Exposes Its Cell Lineage Tree. PLoS Comput Biol 1(5): e50 doi:10.1371/journal.pcbi.0010050

Abstract

What is the lineage relation among the cells of an organism? The answer is sought by developmental biology, immunology, stem cell research, brain research, and cancer research, yet complete cell lineage trees have been reconstructed only for simple organisms such as Caenorhabditis elegans. We discovered that somatic mutations accumulated during normal development of a higher organism implicitly encode its entire cell lineage tree with very high precision. Our mathematical analysis of known mutation rates in microsatellites (MSs) shows that the entire cell lineage tree of a human embryo, or a mouse, in which no cell is a descendent of more than 40 divisions, can be reconstructed from information on somatic MS mutations alone with no errors, with probability greater than 99.95%. Analyzing all ~1.5 million MSs of each cell of an organism may not be practical at present, but we also show that in a genetically unstable organism, analyzing only a few hundred MSs may suffice to reconstruct portions of its cell lineage tree. We demonstrate the utility of the approach by reconstructing cell lineage trees from DNA samples of a human cell line displaying MS instability. Our discovery and its associated procedure, which we have automated, may point the way to a future “Human Cell Lineage Project” that would aim to resolve fundamental open questions in biology and medicine by reconstructing ever larger portions of the human cell lineage tree.

The applications for analysing genetic diseases that the researchers mention still makes this an interesting result, if only you can find sufficent twins with one affected and one unaffected twin...