种群微卫星DNA分析中样本量对各种遗传多样性度量指标的影响

我们以中国飞蝗种群的微卫星遗传分析数据为例 ,评估了取样对种群遗传多样性指标的影响 ,结果显示 :样本大小与所观测到的每位点等位基因数、平均等位基因数及基因丰富度指数均呈显著正相关 ,而与期望杂合度无显著相关 ;微卫星位点多态性的高低直接影响所观测到的种群基因丰富度及其检测所需的样本量 ;对大多数种群遗传和分子生态学研究而言 ,30 - 5 0个个体是微卫星DNA分析所需要的最小样本量。基因丰富度经过稀疏法或多次随机抽样法校正后 ,可适用于瓶颈效应等种群历史数量变动的检测。另外 ,在研究中 ,还应避免采集时间的不同及样本的性比构成所可能造成的对种群遗传结构的影响

Effects of sample size on various genetic diversity measures in population genetic study with microsatellite DNA markers

Sample collection and sampling strategy is of primary importance in population genetic studies, and can greatly influence the analysis and interpretation of the data obtained. Microsatellite DNA sequences are the most revealing DNA markers available so far for inferring population structure and dynamics, and have been widely employed in genetic studies of populations. Nevertheless, few studies have specifically examined the effects of sample size and other sampling factors on various genetic diversity measures in population genetic work using these markers. When such issues were discussed in the literature, it was often very brief or not based on experimental data. Here, we examined these issues more closely using empirical genotype data from an analysis of 26 populations of the migratory locusts Locusta migratoria ( 1 381 individuals) at 8 microsatellite loci. The following genetic diversity measures were studied: number of alleles per locus (NA), mean number of allele over loci (MNA), observed heterozygosity (Ho) and expected heterozygosity (He). We also tried to infer the theoretic minimum sample size needed for population genetic studies with microsatellite loci. Our main results and conclusions are as follows. (1)NA and MNA, i.e. the estimated allelic richness of populations, are significantly affected by sample size (see Figs.1-4, Table 2), while no significant correlation between sample size and heterozygosities (He and Ho) was observed (Figs.6-7). (2)Both the rarefaction method and random resampling method can remove effects of sample size on the allelic richness measures (NA and MNA) discussed above (Fig.5, Figs.8,9). Therefore, although the uncorrected NA and MNA are sensitive to sample size variation and should not be reliable parameters for assessing demographic processes such as bottleneck events, these measures after correction can be used to infer historical population size reduction. Measures of heterogygosity (Ho and He) appears to be fairly stable and suitable for studying genic variation of populations. (3)The extent to which NA and MNA were affected by sample size varies among microsatellite loci. Sample size variation has much greater impact on highly polymorphic loci (e.g. LmIOZc19 locus of the migratory locust) than on less polymorphic loci (e.g. LmIOZc76 locus; see Figs.1 and 3). (4)The minimum sample size needed in a study depends much on the objective of the research project, and is determined by the population frequency of the least represented allele (s). In order to detect an allele of the frequency 0.01 in population with 95% probability, 149 or more samples are required (Table 3). Given that most microsatellite DNA loci have 20 to 30 alleles, at least 30-50 individuals should be analyzed in most cases to detect all these alleles. This theoretical value, calculated from the formula P 0 = (1-q) 2n (where n is the sample size, q is the frequency of the allele in question, P 0 is the probability of the allele being not represented in the sample), agrees well with simulation results (see Fig.3). (5)Finally, we strongly advise that homogeneity tests should be carried out between samples collected at different times from the same location or between sexes before pooling such samples, to check potential heterogeneity due to temporal variation in population structure or sex-bias dispersal. Although with the migratory locusts we studied, no significant difference exists among such samples, this may not be the case for other study systems .