湖北海棠的等位酶变异和遗传多样性研究

采用超薄平板微型聚丙烯酰胺等电聚焦电泳方法对湖北海棠（Malus hupehensis)的9个野生居群和2个人工栽培居群的等位酶变异和遗传多样性进行了初步研究。通过对12个酶系统29个酶位点的检测,结果表明湖北海棠有25个酶位点的等位基因频率分布差异,,有10个居群发现稀有等位基因,并有11个（37．9％）重复位点;湖北海棠的遗传多样性水平很高,等位基因平均数A＝2．127,多态位点百分率P＝74．927,平均预期杂合度He=0.376;居群间的基因分化系数GST＝0．224。与其他苹果属植物相比,湖北海棠具有中等丰富的遗传变异水平。居群间的基因流仅为Nm=0.866,表明遗传漂变是影响居群遗传变异和遗传结构的一个重要因素。     

居群遗传学原理及其在珍稀濒危植物保护中的应用

居群遗传学在珍稀濒危植物保护研究中有着重要的应用价值。本文首先介绍了居群遗传学中的几个重要概念——有效居群大小、近交繁殖、遗传漂变和基因流,然后详细叙述了居群遗传学原理在珍稀濒危植物保护中的应用途径和前景。     

INBREEDING AND VARIANCE EFFECTIVE SIZES FOR NONRANDOM MATING POPULATIONS

Following an inbreeding approach and assuming discrete generations and autosomal inheritance involving genes that do not affect viability or reproductive ability, I have derived expressions for the inbreeding effective size, N_eI, for a finite diploid population with variable census sizes for three cases: monoecious populations with partial selfing; dioecious populations of equal numbers of males and females with partial sib mating; and unequal numbers of males and females with random mating. For the first two cases, recurrence equations for the inbreeding coefficient are also obtained, which allow inbreeding coefficients to be predicted exactly in both early and late generations. Following the variance of change in gene frequency approach, a general expression for variance effective size, N_eV, is obtained for a population with unequal numbers of male and female individuals, arbitrary family size distribution, and nonrandom mating. All the parameters involved are allowed to change over generations. For some special cases, the equation reduces to the simple expressions approximately as derived by previous authors. Comparisons are made between equations derived by the present study and those obtained by previous authors. Some of the published equations for N_eI and N_eV are shown to be incomplete or incorrect. Stochastic simulations are run to check the results where disagreements with others are involved.     

A comparison of four methods for detecting weak genetic structure from marker data

Genetic structure is ubiquitous in wild populations and is the result of the processes of natural selection, genetic drift, mutation, and gene flow. Genetic drift and divergent selection promotes the generation of genetic structure, while gene flow homogenizes the subpopulations. The ability to detect genetic structure from marker data diminishes rapidly with a decreasing level of differentiation among subpopulations. Weak genetic structure may be unimportant over evolutionary time scales but could have important implications in ecology and conservation biology. In this paper we examine methods for detecting and quantifying weak genetic structures using simulated data. We simulated populations consisting of two putative subpopulations evolving for up to 50 generations with varying degrees of gene flow (migration), and varying amounts of information (allelic diversity). There are a number of techniques available to detect and quantify genetic structure but here we concentrate on four methods: F(ST), population assignment, relatedness, and sibship assignment. Under the simple mating system simulated here, the four methods produce qualitatively similar results. However, the assignment method performed relatively poorly when genetic structure was weak and we therefore caution against using this method when the analytical aim is to detect fine-scale patterns. Further work should examine situations with different mating systems, for example where a few individuals dominate reproductive output of the population. This study will help workers to design their experiments (e.g., sample sizes of markers and individuals), and to decide which methods are likely to be most appropriate for their particular data.     

Disentangling the impact of demographic factors on population differentiation of an endangered freshwater crayfish (Austropotamobius pallipes) using population density and microsatellite data

1. Habitat fragmentation of stream ecosystems often results in decreased connectivity between populations and lower population sizes. Hence, understanding how habitat fragmentation affects genetic erosion is important for the preservation of freshwater biodiversity, in particular, as small populations suffer from loss of genetic diversity through genetic drift and loss of fitness because of inbreeding, increasing the risk of extinction. 2. Here, we assess the impact of demographic factors on population differentiation in the endangered freshwater crayfish Austropotamobius pallipes by analysing population genetic structure, estimating effective population sizes and comparing levels of polymorphism at five microsatellite loci with density estimates of 10 populations within a small French catchment that has become progressively confined to headwaters over the last six decades. 3. Levels of expected heterozygosity and allelic richness per population were relatively low (0.214–0.396 and 1.6–2.6, respectively). We found strong genetic differentiation between these geographically close populations (F_ST = 0.283), with weak statistical evidence for a pattern of isolation by distance. Estimates of effective population size were low (<150) in most populations, but potentially reached several thousands in three populations. 4. Population density and allelic richness were strongly positively correlated. A robust relationship between population density and heterozygosity values was also noted, but only after discarding two populations for which significant genetic signatures of a recent bottleneck were found; these two populations displayed high expected heterozygosity compared with a very low density. Populations with the highest densities of individuals had the highest effective population size estimates and vice versa. 5. Our results clearly show the importance of demographic factors and genetic drift on A. pallipes populations. Furthermore, analysis of genetic and population density data is a pragmatic and efficient approach to corroborate inferences from genetic data and can be particularly useful in the identification of populations experiencing a bottleneck and therefore in conservation genetics studies aiming at identifying priority populations for conservation.     

群体遗传结构中的基因流

群体遗传结构上的差异是遗传多样性的一种重要体现,对群体遗传结构的研究已有较久的历史,而其中的基因流研究近些年来越来越受到重视。它对群体遗传学、进化生物学、保护生物学、生态学有着极其重要的作用。虽然传统的群体遗传学能估测基因流大小,但它的精确性还有很大局限性。随着生物技术的进步,对基因流的研究逐渐向分子水平过渡,应用蛋白质电泳技术、分子标记技术(RAPD、RFLP、VNTR、ISSR、DNA测序等)方法对群体间基因流的流动水平进行了深入细致的研究。通过综述群体遗传结构的几种模式:陆岛模式、海岛模式、阶石模式、距离隔离模式、层次模式,以及在群体遗传结构的几种模式基础上的基因流的研究方法、作用、地位和近些年来研究者的研究成果,并指出了这些方法的局限性。     

Methodologies for estimating the sample size required for genetic conservation of outbreeding crops

Summary The main purpose of germplasm banks is to preserve the genetic variability existing in crop species. The effectiveness of the regeneration of collections stored in gene banks is affected by factors such as sample size, random genetic drift, and seed viability. The objective of this paper is to review probability models and population genetics theory to determine the choice of sample size used for seed regeneration. A number of conclusions can be drawn from the results. First, the size of the sample depends largely on the frequency of the least common allele or genotype. Genotypes or alleles occurring at frequencies of more than 10% can be preserved with a sample size of 40 individuals. A sample size of 100 individuals will preserve genotypes (alleles) that occur at frequencies of 5%. If the frequency of rare genotypes (alleles) drops below 5%, larger sample sizes are required. A second conclusion is that for two, three, and four alleles per locus the sample size required to include a copy of each allele depends more on the frequency of the rare allele or alleles than on the number. Samples of 300 to 400 are required to preserve alleles that are present at a frequency of 1%. Third, if seed is bulked, the expected number of parents involved in any sample drawn from the bulk will be less than the number of parents included in the bulk. Fourth, to maintain a rate of breeding (F) of 1 %, the effective population size (N_e) should be at least 150 for three alleles, and 300 for four alleles. Fifth, equalizing the reproductive output of each family to two progeny doubles the effective size of the population. Based on the results presented here, a practical option is considered for regenerating maize seed in a program constrained by limited funds.Part of this paper was presented at the Global Maize Germplasm Workshop, CIMMYT, El Batan, Mexico, March 6–12, 1988     

Effective population size associated with self-fertilization: lessons from temporal changes in allele frequencies in the selfing annual Medicago truncatula

Despite its significance in evolutionary and conservation biology, few estimates of effective population size (N(e)) are available in plant species. Self-fertilization is expected to affect N(e), through both its effect on homozygosity and population dynamics. Here, we estimated N(e) using temporal variation in allele frequencies for two contrasted populations of the selfing annual Medicago truncatula: a large and continuous population and a subdivided population. Estimated N(e) values were around 5-10% of the population census size suggesting that other factors than selfing must contribute to variation in allele frequencies. Further comparisons between monolocus allelic variation and changes in the multilocus genotypic composition of the populations show that the local dynamics of inbred lines can play an important role in the fluctuations of allele frequencies. Finally, comparing N(e) estimates and levels of genetic variation suggest that H(e) is a poor estimator of the contemporaneous variance effective population size.     

Coalescent process with fluctuating population size and its effective size

We consider a Wright-Fisher model whose population size is a finite Markov chain. We introduce a sequence of two-dimensional discrete time Markov chains whose components describe the coalescent process and the fluctuation of population size. For the limiting process of the sequence of Markov chains, the relationship of the expectation of coalescence time to the harmonic and the arithmetic means of population sizes is shown, and the Laplace transform of the distribution of coalescence time is calculated. We define the coalescence effective population size (cEPS) by the expectation of coalescence time. We show that cEPS is strictly larger (resp. smaller) than the harmonic (resp. arithmetic) mean. As the population size fluctuates more quickly (resp. slowly), cEPS is closer to the harmonic (resp. arithmetic) mean. For the case of a two-valued Markov chain, we show the explicit expression of cEPS and its dependency on the sample size.