genomics

Reporter Bruce Lieberman profiles geneticist Ajit Varki in this week's Nature. It's a good summary of Varki's work in sialic acid evolution, focusing on one particular change in the N-glycolyl neuraminic acid (Neu5Gc), work that I touched on here around 3 years ago.

On a molecular level, the difference between Neu5Gc and Neu5Ac is tiny -- a single added oxygen atom perched on one arm distinguishes one from the other (see graphic). But on a biological level, the difference could be enormous. "We thought if monkeys and all of our closest relatives have Neu5Gc and humans don't, then there must be a molecular basis for that," Varki says. He subsequently found it in an enzyme that converts Neu5Ac to Neu5Gc, but which is disabled by mutation in humans.

The article also covers the founding of the Center for Academic Research and Training in Anthropogeny, a research effort of the University of California, San Diego and the Salk Institute. Led by Varki, Margaret Schoeninger, and Pascal Gagneux, the center aims to become an important focus of interdisciplinary work in human origins. I was lucky enough to be invited to one of their research seminars two years ago, and I can say it's a wonderful environment for collaboration, if the project can continue and build on these small meetings:

Between 1998 and 2007, the Project for Explaining the Origin of Humans drew in anthropologists, primate biologists, geneticists, immunologists, neuroscientists, linguists and many others. They discussed topics ranging from the evolution of language to the differences between humans, Neanderthals and Homo erectus, the first hominid to leave Africa. Goodman says the interdisciplinary nature of the series made it extremely important to the field. "You really had the chance to explore an issue as it relates to the evolutionary origins of our species," he says.

...

Varki estimates that he has listened to more than 300 talks on various aspects of this discipline. "The idea is the linguist needs to talk to the molecular biologist who needs to talk to the neuroscientist who needs to talk to the psychologist and philosopher about these issues," he says. "Most areas of human knowledge are somewhere relevant."

I think that's exactly the right attitude -- we need more interdisciplinary efforts. I run up against the blind spots of various specialties all the time, and I'm just one person. On the other hand, it is very challenging to get people to invest the time to learn facts outside their narrow field. If this institute helps those efforts, it will be all to the good.

References:

Lieberman B. 2008. Human evolution: details of being human. Nature 454:21-23. doi:10.1038/454021a

The rate of neutral mutations varies across the genome. When studying a single gene, this variation in rates is not especially important -- it is generally possible to obtain an estimate of the neutral rate for a single locus by comparing just that locus among closely related species.

But some comparisons involve looking at the pattern of variation among different loci. For instance, testing hypotheses about the ancestral populations leading to living species (like the common ancestor of humans and chimpanzees) involves comparing the amount of divergence among many independent loci. The variance in divergence times among loci gives an estimate of inbreeding in the ancestral population.

I discussed this particular example two years ago this week, after the paper that proposed extended hybridization between ancestral hominids and chimpanzees. The conclusion of the paper was that the X chromosome displays much less divergence between humans and chimpanzees than the autosomes, and this might reflect a late introgression of the X chromosome into hominids from another population that (mostly) was ancestral to chimpanzees. The autosomes, by contrast, averaged very old genetic divergences, although there was substantial variance. As I concluded then, the data look consistent with a large population size in the human-chimpanzee ancestor species, coupled with greater selection on the X chromosome. The interpretation of large population size (or alternatively, the interpretation of long-term population structure) comes from the low inferred inbreeding in that ancestral population -- which caused the variance in divergence dates among loci.

But there is another reason for a large variance in divergence dates: variance in mutation rates. Whenever mutation rates vary among loci, this variance adds to the variance among loci in their between-species genetic differences -- that is, the substitution rate. And as long as we are excluding selected sites (as we always try to do for these kinds of comparisons) we will overestimate the genetic diversity in ancestral species whenever the mutation rate varies among loci.

A new paper by Svitlana Tyakucheva and colleagues looks at human and macaque genomes to find patterns underlying the variance in mutation rates among regions of the genome. They find that a number of factors may cause such variations, including chemical factors like the CG content of the genome, functional causes such as male versus female rates of recombination, and large-scale structural causes such as telomeric proximity:

While a complete understanding of all biological mechanisms leading to variation in neutral substitution rates across the genome remains elusive, it is plausible that at least some of these mechanisms are conserved over relatively long evolutionary distances. For instance, both mouse-specific and rat-specific substitution rates are positively correlated with rodent-primate substitution rates [14], suggesting shared mechanisms persisting over ca. 90 million years [15]. Additionally, a positive correlation exists in substitution rates of homologous X- and Y-chromosomal introns that diverged from each other ca. 100 million years ago [16] (Tykucheva et al. 2008: R76).

Their finding that male recombination is an important contributor to mutation rate heterogeneity puts the focus on the X chromosome -- which has little recombination in males -- as unusual. X versus autosomal position did not explain a large fraction of the variance in this study (only around 2 percent, controlling for other factors) but the deviation was in the right direction to help account for the low X chromosome divergence between humans and chimpanzees.

Altogether in this study, a large fraction of variation in the human-macaque substitution variability could be explained by phenomena that affect the rate of mutations, including the structural and functional factors listed above as well as the corresponding homologous variability between mice and rats, and dogs and cattle. If these variations were explained by inbreeding in the human-macaque ancestral species, they would be random with respect to the dog-cow or mouse-rat divergences, and with respect to structural causes. So current estimates of the effective sizes of human-chimpanzee and other ancestral populations are almost certainly inflated. The amount of inflation is not clear, but a good estimate will require correcting for a large number of factors -- a complicated analysis.

Since the date of the human-chimpanzee divergence depends on our assessment of the diversity within the human-chimpanzee ancestral population, it may be a while before we can settle the issue of human-chimpanzee divergence time. That may or may not provide hope for Sahelanthropus, Orrorin, and Ardipithecus kadabba -- all supposed hominids that would predate 5 million years ago, the current best genetic estimate of the human-chimpanzee divergence time. To be sure, if the date is simply in error, that error might encompass older dates consistent with a 7-million-year divergence. But I'm not sure we should believe that the error is biased toward an older divergence -- "error" might lean in either direction, and a younger species divergence remains possible.

References:

Tyakucheva S, Makova KD, Karro JE, Hardison RC, Miller W, Chiaromonte F. 2008. Human-macaque comparisons illuminate variation in neutral substitution rates. Genome Biol 9:R76. doi:10.1186/gb-2008-9-4-r76

Laura MacConaill and Matthew Meyerson present a cool short review in Nature Genetics of metagenomics applications in pathogen discovery.

The basic principle is to extract DNA from a tumor or sore, do intensive sequencing of all the DNA in it, and use the computers to subtract out everything human. What's left after you subtract out the human DNA is any pathogen that might be in the sample:

The two recent studies combined computational subtraction with microreactor-based pyrosequencing to identify viral signatures associated with human disease. Feng et al. used high-throughput pyrosequencing15 and comparison to the human transcriptome to identify a viral sequence in a library of cDNAs generated from individuals with Merkel cell carcinoma, a rare but aggressive human skin cancer. The authors sequenced over 395,000 reads of 150-200 bp in length. After digital transcriptome subtraction, 2,395 sequences remained. Among these, conceptual translation of one sequence showed similarity to a polyomavirus. By cloning the complete viral genome and carrying out further analyses, the authors found that the Merkel cell polyomavirus sequence was present in eight of ten Merkel cell carcinomas.

A second group used the same high-throughput DNA sequencing technology to identify a previously undiscovered arenavirus that likely caused the deaths of three transplant recipients who all received organs from a single donor.

I don't know if sequencing will ever get so cheap that this will become practical diagnostic method, but it really doesn't need to be. As soon as you suspect a pathogen, you can probe directly for that pathogen's DNA in a sample -- and there's no barrier to testing for hundreds of pathogens at once. Heck, there ought to be a SNP chip for it.

But this is a potentially important way of identifying new pathogens in unknown samples from scratch. The article mentions that the current cost of this kind of sequencing is around $10,000 per sample, and that is rapidly falling. For that cost, you get the sequence on your computer, even if you can't identify it yet, and who knows -- it might pop up two years later when somebody else finds it in some unexpected place.

References:

MacConaill L, Meyerson M. 2008. Adding pathogens by genomic subtraction. Nat Genet 40:380-382. doi:10.1038/ng0408-380

A complicated story is tangled through this paper by Augustine Kong and colleagues, and I don't see where it may end. But here's the abstract:

The genome-wide recombination rate varies between individuals, but the mechanism controlling this variation in humans has remained elusive. A genome-wide search identified sequence variants in the 4p16.3 region correlated with recombination rate in both males and females. These variants are located in the RNF212 gene, a putative ortholog of the ZHP-3 gene that is essential for recombinations and chiasma formation in Caenorhabditis elegans. It is noteworthy that the haplotype formed by two single-nucleotide polymorphisms (SNPs) associated with the highest recombination rate in males is associated with a low recombination rate in females. Consequently, if the frequency of the haplotype changes, the average recombination rate will increase for one sex and decrease for the other, but the sex-averaged recombination rate of the population can stay relatively constant.

Perhaps it's not so curious that alleles of this gene have opposite effects on recombination in males and females. The mechanisms of gamete production are obviously different in the two sexes, and we might expect some kind of frequency-dependent mechanism to regulate recombination. At least, it's a hypothesis.

What I find mysterious is this:

A phylogenetic analysis of a 55-kb region containing rs3796619 and rs1670533 in the HapMap data (24) revealed three well-differentiated clusters of haplotypes showing notable differences in frequency between the Yoruban Nigerians (YRI) and CEU and East Asians (CHB and JPT) (fig. S6). The [C,T] and [T,C] haplotypes that associate most strongly with recombination rate have a combined frequency of only 17% in the YRI sample, but reach a frequency of 91% and 98% in the CEU and East Asian samples, respectively. Several SNPs in this region show an unusual degree of divergence among the HapMap groups, on the basis of the rank percentile of their FST values (Wright's coefficient, a measure of variance in allele frequencies among populations) among all autosomal SNPs with the same overall frequency in the HapMap. Specifically, we identified eight SNPs whose FST values are in the top 0.5% for differences between the YRI and East Asian HapMap samples and also in the top 5% of differences between the YRI and CEU samples. Each of these SNPs differentiated a subset of [T,T] haplotypes from the rest, perhaps indicating an episode of positive selection (or a severe founder effect) that increased the frequency of [C,T] and [T,C] haplotypes in the ancestors of European and East Asian populations.

The [C,T] and [T,C] haplotypes are the ones associated with increased recombination rate in males and females, respectively. The markers are in strong disequilibrium (no [C,C] haplotypes were observed), and seem to have been selected outside of Africa.

I have no idea why.

The recombination rates were all inferred from a large Icelandic sample, so maybe the rates don't really characterize the haplotypes in other populations. Maybe recombination rate is incidental to the real reason for the selection. Or maybe in populations roaring with positive selection on many genes at once, it is a good thing to break them apart more often.

References:

Kong A and 16 others. 2008. Sequence variants in the RNF212 gene associate with genome-wide recombination rate. Science 319:1398-1401. doi:10.1126/science.1152422