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

Arlequin ver 3.0 is a software package integrating several basic and advanced methods for population genetics data analysis, like the computation of standard genetic diversity indices, the estimation of allele and haplotype frequencies, tests of departure from linkage equilibrium, departure from selective neutrality and demographic equilibrium, estimation or parameters from past population expansions, and thorough analyses of population subdivision under the AMOVA framework. Arlequin 3 introduces a completely new graphical interface written in C++, a more robust semantic analysis of input files, and two new methods: a Bayesian estimation of gametic phase from multi-locus genotypes, and an estimation of the parameters of an instantaneous spatial expansion from DNA sequence polymorphism. Arlequin can handle several data types like DNA sequences, microsatellite data, or standard multi-locus genotypes. A Windows version of the software is freely available on http://cmpg.unibe.ch/software/arlequin3.

/pdf/arlequin-version-3-0-an-integrated-software-package-for-4cs6nd3y2p.pdf

Arlequin (version 3.0): An integrated software package for population genetics data analysis

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

Summary: GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G′ST, G′′ST, Jost’s Dest and F′ST through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised.

Availability and implementation: GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx.

Contact: rod.peakall@anu.edu.au

GenAlEx 6.5

Interpretation of genetic differentiation values is often problematic because of their dependence on the level of genetic variation. For example, the maximum level of GST is less than the average within population homozygosity so that for highly variable loci, even when no alleles are shared between subpopulations, GST may be low. To remedy this difficulty, a standardized measure of genetic differentiation is introduced here, one which has the same range, 0–1, for all levels of genetic variation. With this measure, the magnitude is the proportion of the maximum differentiation possible for the level of subpopulation homozygosity observed. This is particularly important for situations in which the mutation rate is of the same magnitude or higher than the rate of gene flow. The standardized measure allows comparison between loci with different levels of genetic variation, such as allozymes and microsatellite loci, or mtDNA and Y-chromosome genes, and for genetic differentiation for organisms with d...

A standardized genetic differentiation measure

Although highly variable loci, such as microsatellite loci, are revolutionizing both evolutionary and conservation biology, data from these loci need to be carefully evaluated. First, because these loci often have very high within-population heterozygosity, the magnitude of differentiation measures may be quite small. For example, maximum GST values for populations with no common alleles at highly variable loci may be small and are at maximum less than the average within-population homozygosity. As a result, measures that are variation independent are recommended for highly variable loci. Second, bottlenecks or a reduction in population size can generate large genetic distances in a short time for these loci. In this case, the genetic distance may be corrected for low variation in a population and tests to detect bottlenecks are advised. Third, statistically significant differences may not reflect biologically meaningful differences both because the patterns of adaptive loci may not be correlated with highly variable loci and statistical power with these markers is so high. As an example of this latter effect, the statistical power to detect a one-generation bottleneck of different sizes for different numbers of highly variable loci is discussed. All of these concerns need to be incorporated in the utilization and interpretation of patterns of highly variable loci for both evolutionary and conservation biology.

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1558-5646.1999.tb03767.x

Perspective: highly variable loci and their interpretation in evolution and conservation.

Although F(ST) is widely used as a measure of population structure, it has been criticized recently because of its dependency on within-population diversity. This dependency can lead to difficulties in interpretation and in the comparison of estimates among species or among loci and has led to the development of two replacement statistics, F'(ST) and D. F'(ST) is the normal F(ST) standardized by the maximum value it can obtain, given the observed within-population diversity. D uses a multiplicative partitioning of diversity, based on the effective number of alleles rather than on the expected heterozygosity. In this study, we review the relationships between the three classes of statistics (F(ST), F'(ST) and D), their estimation and their properties. We illustrate the relationships between the statistics using a data set of estimates from 84 species taken from the last 4 years of Molecular Ecology. As with F(ST), unbiased estimators are available for the two new statistics D and F'(ST). Here, we develop a new unbiased F'(ST) estimator based on G(ST), which we call G''(ST). However, F'(ST) can be calculated using any F(ST) estimator for which the maximum value can be obtained. As all three statistics have their advantages and their drawbacks, we recommend continued use of F(ST) in combination with either F'(ST) or D. In most cases, F'(ST) would be the best choice among the latter two as it is most suited for inferences of the influence of demographic processes such as genetic drift and migration on genetic population structure.

Assessing population structure: FST and related measures

Five different measures of gametic disequilibrium in current use and a new one based on R. C. Lewontin's D', are examined and compared. All of them, except the measure based on Lewontin's D', are highly dependent upon allelic frequencies, including four measures that are normalized in some manner. In addition, the measures suggested by A. H. D. Brown, M. F. Feldman and E. Nevo, and T. Ohta can have negative values when there is maximum disequilibrium and have rates of decay in infinite populations that are a function of the initial gametic array. The variances were large for all the measures in samples taken from populations at equilibrium under neutrality, with the measure based on D' having the lowest variance. In these samples, three of the measures were highly correlated, D2, D (equal to the correlation coefficient when there are two alleles at each locus) and the measure X(2) of Brown et al. Using frequency-dependent measures may result in mistaken conclusions, a fact illustrated by discussion of studies inferring recombinational hot spots and the effects of population bottlenecks from disequilibrium values.

https://www.genetics.org/content/genetics/117/2/331.full.pdf

Gametic disequilibrium measures: proceed with caution

▪ Abstract Inbreeding depression is of major concern in the management and conservation of endangered species. Inbreeding appears universally to reduce fitness, but its magnitude and specific effects are highly variable because they depend on the genetic constitution of the species or populations and on how these genotypes interact with the environment. Recent natural experiments are consistent with greater inbreeding depression in more stressful environments. In small populations of randomly mating individuals, such as are characteristic of many endangered species, all individuals may suffer from inbreeding depression because of the cumulative effects of genetic drift that decrease the fitness of all individuals in the population. In three recent cases, introductions into populations with low fitness appeared to restore fitness to levels similar to those before the effects of genetic drift. Inbreeding depression may potentially be reduced, or purged, by breeding related individuals. However, the Speke's ...

Philip W. Hedrick

Papers

A standardized genetic differentiation measure

Perspective: highly variable loci and their interpretation in evolution and conservation.

Assessing population structure: FST and related measures

Gametic disequilibrium measures: proceed with caution

Inbreeding depression in conservation biology