抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.

https://cdr.lib.unc.edu/downloads/v692t8920

A global reference for human genetic variation.

Statistical method for testing the neutral mutation hypothesis by DNA polymorphism.

So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Human biochemical genetics

The 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother-father-child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately 10(-8) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.

http://dash.harvard.edu/bitstream/handle/1/5339502/Durbin_MapHuman.pdf?sequence=1

A Map of Human Genome Variation From Population-Scale Sequencing

The Standard Genetic Code (SGC) is the mapping of nucleic acids into polypeptides that is employed, sometimes with minor variations1, in every organism, organelle and virus. The organization of the SGC is highly non-random2-8. In the four decades since the discovery of the SGC a large spectrum of hypotheses have been conceived to explain how its organization came about. These include a variety of load minimizing hypotheses2,3,5,6,9-15, the frozen accident hypothesis16, the ambiguity reduction hypothesis17,18, the stereochemical hypothesis14,16,19-25, and the metabolic coevolutionary hypothesis26,27. None of these hypotheses has laid down a theory that is fully fledged in the sense that it (i) begins from biological or biochemical considerations, (ii) derives the evolutionary mechanisms that follow from such considerations, and (iii) shows how these mechanisms can reproduce the patterns in the organization of the SGC. Here we present the first fully fledged theory for the evolution of the SGC. The theory derives from two fundamental observations: first, there are patterns in the SGC that strongly suggest that systematic error in replication and translation played a causal role in its evolution2-8; and second, the evolution of a genetic code is mediated through the protein-coding genes, where selection acts upon the proteins which are the product of translating these genes with the genetic code16. We derive the evolutionary mechanisms of code formation that follow from these observations, and show how these mechanisms reproduce two of the salient organizational patterns of the SGC. (Superscript numbers in text denote references cited at the end of the paper.)

The Coevolution of Genes and the Genetic Code

Modeling the effect of changing selective pressures on polymorphism and divergence.

Populations of organisms show prevalent genetic differences called polymorphisms. Understanding the effects of polymorphisms is of central importance in biology and medicine. Here, we ask which polymorphisms occur at high frequency when organisms evolve under tradeoffs between multiple tasks. Multiple tasks present a problem, because it is not possible to be optimal at all tasks simultaneously and hence compromises are necessary. Recent work indicates that tradeoffs lead to a simple geometry of phenotypes in the space of traits: phenotypes fall on the Pareto front, which is shaped as a polytope: a line, triangle, tetrahedron etc. The vertices of these polytopes are the optimal phenotypes for a single task. Up to now, work on this Pareto approach has not considered its genetic underpinnings. Here, we address this by asking how the polymorphism structure of a population is affected by evolution under tradeoffs. We simulate a multi-task selection scenario, in which the population evolves to the Pareto front: the line segment between two archetypes or the triangle between three archetypes. We find that polymorphisms that become prevalent in the population have pleiotropic phenotypic effects that align with the Pareto front. Similarly, epistatic effects between prevalent polymorphisms are parallel to the front. Alignment with the front occurs also for asexual mating. Alignment is reduced when drift or linkage is strong, and is replaced by a more complex structure in which many perpendicular allele effects cancel out. Aligned polymorphism structure allows mating to produce offspring that stand a good chance of being optimal multi-taskers in at least one of the locales available to the species.

https://www.biorxiv.org/content/early/2018/01/06/244210.full.pdf

Evolutionary tradeoffs and the structure of allelic polymorphisms

In human and other hominid (great apes) populations, estimates of the relative levels of neutral polymorphism on the X and autosomes differ from each other and from the naive theoretical expectation of 3/4. These differences have garnered considerable attention over the past decade, with studies highlighting the potential importance of several factors, including historical changes in population size and linked selection near genes. Here, we examine a more realistic neutral model than has been considered to date, which incorporates sex- and age-dependent mortalities, fecundities, reproductive variances and mutation rates, and ask whether such a model can account for diversity levels observed far from genes. To this end, we derive analytical expressions for the X to autosome ratio of polymorphism levels, which incorporate all of these factors and clarify their effects. In particular, our model shows that the genealogical effects of life history can be reduced to ratios of sex-specific generation times and reproductive variances. Applying our results to hominids by relying on estimated life-history parameters and approximate relationships of mutation rates to age and sex, we find that life history effects, and the effects of male and female generation times in particular, may account for much of the observed variation in X to autosome ratios of polymorphism levels across populations and species.

/pdf/life-history-effects-on-neutral-polymorphism-levels-of-3o61honji0.pdf

Life history effects on neutral polymorphism levels of autosomes and sex chromosomes

In human populations, the relative levels of neutral diversity on the X and autosomes differ markedly from each other and from the naive theoretical expectation of 3/4. Here we propose an explanation for these differences based on new theory about the effects of sex-specific life history and given pedigree-based estimates of the dependence of human mutation rates on sex and age. We demonstrate that life history effects, particularly longer generation times in males than in females, are expected to have had multiple effects on human X-to-autosome (X:A) diversity ratios, as a result of male-biased mutation rates, the equilibrium X:A ratio of effective population sizes, and the differential responses to changes in population size. We also show that the standard approach of using divergence between species to correct for male mutation bias results in biased estimates of X:A effective population size ratios. We obtain alternative estimates using pedigree-based estimates of the male mutation bias, which reveal that X:A ratios of effective population sizes are considerably greater than previously appreciated. Finally, we find that the joint effects of historical changes in life history and population size can explain the observed X:A diversity ratios in extant human populations. Our results suggest that ancestral human populations were highly polygynous, that non-African populations experienced a substantial reduction in polygyny and/or increase in the male-to-female ratio of generation times around the Out-of-Africa bottleneck, and that current diversity levels were affected by fairly recent changes in sex-specific life history.

https://www.pnas.org/content/pnas/117/33/20063.full.pdf

Guy Sella

Papers

The Coevolution of Genes and the Genetic Code

Modeling the effect of changing selective pressures on polymorphism and divergence.

Evolutionary tradeoffs and the structure of allelic polymorphisms

Life history effects on neutral polymorphism levels of autosomes and sex chromosomes

Changes in life history and population size can explain the relative neutral diversity levels on X and autosomes in extant human populations.