Sample size requirements for addressing the population genetic issues of forensic use of DNA typing.

DNA typing offers a unique opportunity to identify individuals for medical and forensic purposes. Probabilistic inference regarding the chance occurrence of a match between the DNA type of an evidentiary sample and that of an accused suspect, however, requires reliable estimation of genotype and allele frequencies in the population. Although population-based data on DNA typing at several hypervariable loci are being accumulated at various laboratories, a rigorous treatment of the sample size needed for such purposes has not been made from population genetic considerations. It is shown here that the loci that are potentially most useful for forensic identification of individuals have the intrinsic property that they involve a large number of segregating alleles, and a great majority of these alleles are rare. As a consequence, because of the large number of possible genotypes at the hypervariable loci that offer the maximum potential for individualization, the sample size needed to observe all possible genotypes in a sample is large. In fact, the size is so large that even if such a huge number of individuals could be sampled, it could not be guaranteed that such a sample was drawn from a single homogeneous population. Therefore adequate estimation of genotypic probabilities must be based on allele frequencies, and the sample size needed to represent all possible alleles is far more reasonable. Further economization of sample size is possible if one wants to have representation of only the frequent alleles in the sample, so that the rare allele frequencies can be approximated by an upper bound for forensic applications.     

Estimating population size of endangered brush-tailed rock-wallaby (Petrogale penicillata) colonies using faecal DNA

The brush-tailed rock-wallaby (Petrogale penicillata) is an endangered species in southeastern Australia and many of the remaining populations are declining. The steep rocky habitat and shy nature of the species make it difficult to obtain data on population parameters such as abundance and recruitment. Faecal pellet counts from scat plots are commonly used to monitor population trends but these are imprecise and difficult to relate to absolute population size. We conducted a noninvasive genetic sampling 'mark-recapture' study over a 2-year period to identify individuals from faecal DNA samples and estimate the population size of four brush-tailed rock-wallaby colonies located in Wollemi National Park, New South Wales. Scat plots in rock-wallaby colonies were used as sample collection points for this study. Two separate population estimates were carried out for three of the colonies to determine if we could detect recruitment and changes in population size. We determined that there was one large colony of an estimated 67 individuals (95% confidence interval: 55-91) and three smaller colonies. Monitoring of the smaller colonies also detected possible population size increases in all three. Our results indicate that faecal DNA analysis may be a promising method for estimating and monitoring population trends in this species particularly when used with a traditional field survey method.     

Satellite Telemetry in Avian Research and Management: Sample Size Considerations

Abstract: Satellite tracking is currently used to make inferences to avian populations. Cost of transmitters and logistical challenges of working with some species can limit sample size and strength of inferences. Therefore, careful study design including consideration of sample size is important. We used simulations to examine how sample size, population size, and population variance affected probability of making reliable inferences from a sample and the precision of estimates of population parameters. For populations of >100 individuals, a sample >20 birds was needed to make reliable inferences about questions with simple outcomes (i.e., 2 possible outcomes). Sample size demands increased rapidly for more complex problems. For example, in a problem with 3 outcomes, a sample of >75 individuals will be needed for proper inference to the population. Combining data from satellite telemetry studies with data from surveys or other types of sampling may improve inference strength.     

Coalescent-based DNA barcoding: multilocus analysis and robustness

DNA barcoding is the assignment of individuals to species using standardized mitochondrial sequences. Nuclear data are sometimes added to the mitochondrial data to increase power. A barcoding method for analysing mitochondrial and nuclear data is developed. It is a Bayesian method based on the coalescent model. Then this method is assessed using simulated and real data. It is found that adding nuclear data can reduce the number of ambiguous assignments. Finally, the robustness of coalescent-based barcoding to departures from model assumptions is studied using simulations. This method is found to be robust to past population size variations, to within-species population structures, and to designs that poorly sample populations within species. Supplementary Material is available online at www.liebertonline.com/cmb.     

MULTISITE MARK-RECAPTURE FOR CETACEANS: POPULATION ESTIMATES WITH BAYESIAN MODEL AVERAGING

Mark-recapture techniques are widely used to estimate the size of wildlife populations. However, in cetacean photo-identification studies, it is often impractical to sample across the entire range of the population. Consequently, negatively biased population estimates can result when large portions of a population are unavailable for photographic capture. To overcome this problem, we propose that individuals be sampled from a number of discrete sites located throughout the population's range. The recapture of individuals between sites can then be presented in a simple contingency table, where the cells refer to discrete categories formed by combinations of the study sites. We present a Bayesian framework for fitting a suite of log-linear models to these data, with each model representing a different hypothesis about dependence between sites. Modeling dependence facilitates the analysis of opportunistic photo-identification data from study sites located due to convenience rather than by design. Because inference about population size is sensitive to model choice, we use Bayesian Markov chain Monte Carlo approaches to estimate posterior model probabilities, and base inference on a model-averaged estimate of population size. We demonstrate this method in the analysis of photographic mark-recapture data for bottlenose dolphins from three coastal sites around NE Scotland.     

Molecular identification of individual North Atlantic right whales (Eubalaena glacialis) using free-floating feces

During the 1990s, North Atlantic right whales had significantly decreased reproduction and showed signs of compromised health, prompting the initiation of noninvasive fecal-based studies to investigate potential causal factors. The interpretation of these studies is enhanced when the defecator is identified, as data can then be linked to individual life history information. Fecal samples (n= 118) were either collected from single photoidentified whales, associated with several individuals by photoidentification of whales in the vicinity upon sample collection, or were collected when no whales were in the vicinity. Genetic profiles from fecal DNA comprising sex, mitochondrial haplotype, and five microsatellite loci helped assign specific samples to individual right whales based on existing genetic profiles. Profiles were informative in assigning 61 fecal samples to known individuals, 24 of which were collected when no whales were in the vicinity. Whales identified genetically were typically photographed in the same habitat area and on the same day of sample collection (n= 35/48). Twelve profiles new to the genetic database were identified, suggesting fecal sampling provides a means to obtain genetic profiles from previously unsampled individuals, which may help refine estimates of population size and habitat use patterns if annual fecal sampling continues.     

Identification of kin structure among Guam rail founders: a comparison of pedigrees and DNA profiles

Kin structure among founders can have a significant effect on subsequent population structure. Here we use the correlation between DNA profile similarity and relatedness calculated from pedigrees to test hypotheses regarding kin structure among founders to the captive Guam rail (Rallus owstoni) population. Five different pedigrees were generated under the following hypotheses: (i) founders are unrelated; (ii) founders are unrelated except for same-nest chicks; (iii) founders from the same major site are siblings; (iv) founders from the same local site are siblings; and (v) founders are related as defined by a UPGMA cluster analysis of DNA similarity data. Relatedness values from pedigrees 1, 2 and 5 had the highest correlation with DNA similarity but the correlation between relatedness and similarity were not significantly different among pedigrees. Pedigree 5 resulted in the highest correlation overall when using only relatedness values that changed as a result of different founder hypotheses. Thus, founders were assigned relatedness based on pedigree 5 because it had the highest correlations with DNA similarity, was the most conservative approach, and incorporated all field data. The analyses indicated that estimating relatedness using DNA profiles remains problematic, therefore we compared mean kinship, a measure of genetic importance, with mean DNA profile similarity to determine if genetic importance among individuals could be determined via use of DNA profiles alone. The significant correlation suggests this method may provide more information about population structure than was previously thought. Thus, DNA profiles can provide a reasonable explanation for founder relatedness and mean DNA profile similarity may be helpful in determining relative genetic importance of individuals when detailed pedigrees are absent.     

Estimation of population profiles of two strains of the fly Megaselia scalaris (Diptera: Phoridae) by bootstrap simulation

Based on experimental population profiles of strains of the fly Megaselia scalaris (Phoridae), the minimal number of sample profiles was determined that should be repeated by bootstrap simulation process in order to obtain a confident estimation of the mean population profile and present estimations of the standard error as a precise measure of the simulations made. The original data are from experimental populations founded with SR and R4 strains, with three replicates, which were kept for 33 weeks by serial transfer technique in a constant temperature room (25 +/- 1.0 degrees C). The variable used was population size and the model adopted for each profile was a stationary stochastic process. By these simulations, the three experimental population profiles were enlarged so as to determine minimum sample size. After sample size was determined, bootstrap simulations were made in order to calculate confidence intervals and to compare the mean population profiles of these two strains. The results show that with a minimum sample size of 50, stabilization of means begins.     

用微卫星指纹识别天鹅洲保护区长江江豚个体

DNA指纹个体识别技术是保护遗传学研究中的一种非常重要的手段。为了准确地识别天鹅洲保护区中的每一头长江江豚以开展保护遗传学及其它相关研究 ,并实施有效的种群管理 ,本研究应用 4个微卫星座位初步构建了该群体的DNA指纹图谱 ,并利用此图谱成功地对不同时期在保护区捕获的江豚进行了个体识别研究。结果显示微卫星指纹技术是一种适用于长江江豚个体识别研究的可靠手段     

Reliable genotyping of the koala (Phascolarctos cinereus) using DNA isolated from a single faecal pellet

The koala, an Australian icon, has been added to the threatened species list. Rationale for the listing includes proposed declines in population size, threats to populations (e.g. disease) and loss and fragmentation of habitat. There is now an urgent need to obtain accurate data to assess the status of koala populations in Australia, to ensure the long‐term viability of this species. Advances in genetic techniques have enabled DNA analysis to study and inform the management of wild populations; however, sampling of individual koalas is difficult in tall, often remote, eucalypt forest. The collection of faecal pellets (scats) from the forest floor presents an opportunistic sampling strategy, where DNA can be collected without capturing or even sighting an individual. Obtaining DNA via noninvasive sampling can be used to rapidly sample a large proportion of a population; however, DNA from noninvasively collected samples is often degraded. Factors influencing DNA quality and quantity include environmental exposure, diet and methods of sample collection, storage and DNA isolation. Reduced DNA quality and quantity can introduce genotyping errors and provide inaccurate DNA profiles, reducing confidence in the ability of such data to inform management/conservation strategies. Here, we present a protocol that produces a reliable individual koala genotype from a single faecal pellet and highlight the importance of optimizing DNA isolation and analysis for the species of interest. This method could readily be adapted for genetic studies of mammals other than koalas, particularly those whose diet contains high proportions of volatile materials that are likely to induce DNA damage.     

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     

Estimating Variable Effective Population Sizes from Multiple Genomes: A Sequentially Markov Conditional Sampling Distribution Approach

Throughout history, the population size of modern humans has varied considerably due to changes in environment, culture, and technology. More accurate estimates of population size changes, and when they occurred, should provide a clearer picture of human colonization history and help remove confounding effects from natural selection inference. Demography influences the pattern of genetic variation in a population, and thus genomic data of multiple individuals sampled from one or more present-day populations contain valuable information about the past demographic history. Recently, Li and Durbin developed a coalescent-based hidden Markov model, called the pairwise sequentially Markovian coalescent (PSMC), for a pair of chromosomes (or one diploid individual) to estimate past population sizes. This is an efficient, useful approach, but its accuracy in the very recent past is hampered by the fact that, because of the small sample size, only few coalescence events occur in that period. Multiple genomes from the same population contain more information about the recent past, but are also more computationally challenging to study jointly in a coalescent framework. Here, we present a new coalescent-based method that can efficiently infer population size changes from multiple genomes, providing access to a new store of information about the recent past. Our work generalizes the recently developed sequentially Markov conditional sampling distribution framework, which provides an accurate approximation of the probability of observing a newly sampled haplotype given a set of previously sampled haplotypes. Simulation results demonstrate that we can accurately reconstruct the true population histories, with a significant improvement over the PSMC in the recent past. We apply our method, called diCal, to the genomes of multiple human individuals of European and African ancestry to obtain a detailed population size change history during recent times.     

Time to the MRCA of a sample in a Wright–Fisher model with variable population size

Determining the expected distribution of the time to the most recent common ancestor of a sample of individuals may deliver important information about the genetic markers and evolution of the population. In this paper, we introduce a new recursive algorithm to calculate the distribution of the time to the most recent common ancestor of the sample from a population evolved by any conditional multinomial sampling model. The most important advantage of our method is that it can be applied to a sample of any size drawn from a population regardless of its size growth pattern. We also present a very efficient method to implement and store the genealogy tree of the population evolved by the Galton–Watson process. In the final section we present results applied to a simulated population with a single bottleneck event and to real populations of known size histories.     

A simulation study of sample size for DNA barcoding

For some groups of organisms, DNA barcoding can provide a useful tool in taxonomy, evolutionary biology, and biodiversity assessment. However, the efficacy of DNA barcoding depends on the degree of sampling per species, because a large enough sample size is needed to provide a reliable estimate of genetic polymorphism and for delimiting species. We used a simulation approach to examine the effects of sample size on four estimators of genetic polymorphism related to DNA barcoding: mismatch distribution, nucleotide diversity, the number of haplotypes, and maximum pairwise distance. Our results showed that mismatch distributions derived from subsamples of ≥20 individuals usually bore a close resemblance to that of the full dataset. Estimates of nucleotide diversity from subsamples of ≥20 individuals tended to be bell‐shaped around that of the full dataset, whereas estimates from smaller subsamples were not. As expected, greater sampling generally led to an increase in the number of haplotypes. We also found that subsamples of ≥20 individuals allowed a good estimate of the maximum pairwise distance of the full dataset, while smaller ones were associated with a high probability of underestimation. Overall, our study confirms the expectation that larger samples are beneficial for the efficacy of DNA barcoding and suggests that a minimum sample size of 20 individuals is needed in practice for each population.     

Familial identification: population structure and relationship distinguishability

With the expansion of offender/arrestee DNA profile databases, genetic forensic identification has become commonplace in the United States criminal justice system. Implementation of familial searching has been proposed to extend forensic identification to family members of individuals with profiles in offender/arrestee DNA databases. In familial searching, a partial genetic profile match between a database entrant and a crime scene sample is used to implicate genetic relatives of the database entrant as potential sources of the crime scene sample. In addition to concerns regarding civil liberties, familial searching poses unanswered statistical questions. In this study, we define confidence intervals on estimated likelihood ratios for familial identification. Using these confidence intervals, we consider familial searching in a structured population. We show that relatives and unrelated individuals from population samples with lower gene diversity over the loci considered are less distinguishable. We also consider cases where the most appropriate population sample for individuals considered is unknown. We find that as a less appropriate population sample, and thus allele frequency distribution, is assumed, relatives and unrelated individuals become more difficult to distinguish. In addition, we show that relationship distinguishability increases with the number of markers considered, but decreases for more distant genetic familial relationships. All of these results indicate that caution is warranted in the application of familial searching in structured populations, such as in the United States.     

Statistical analysis of the individual variability of 1D protein profiles as a tool in ecology: an application to parasitoid venom

Understanding the forces that shape eco‐evolutionary patterns often requires linking phenotypes to genotypes, allowing characterization of these patterns at the molecular level. DNA‐based markers are less informative in this aim compared to markers associated with gene expression and, more specifically, with protein quantities. The characterization of eco‐evolutionary patterns also usually requires the analysis of large sample sizes to accurately estimate interindividual variability. However, the methods used to characterize and compare protein samples are generally expensive and time‐consuming, which constrains the size of the produced data sets to few individuals. We present here a method that estimates the interindividual variability of protein quantities based on a global, semi‐automatic analysis of 1D electrophoretic profiles, opening the way to rapid analysis and comparison of hundreds of individuals. The main original features of the method are the in silico normalization of sample protein quantities using pictures of electrophoresis gels at different staining levels, as well as a new method of analysis of electrophoretic profiles based on a median profile. We demonstrate that this method can accurately discriminate between species and between geographically distant or close populations, based on interindividual variation in venom protein profiles from three endoparasitoid wasps of two different genera (Psyttalia concolor, Psyttalia lounsburyi and Leptopilina boulardi). Finally, we discuss the experimental designs that would benefit from the use of this method.     

Time to the MRCA of a sample in a Wright-Fisher model with variable population size

Determining the expected distribution of the time to the most recent common ancestor of a sample of individuals may deliver important information about the genetic markers and evolution of the population. In this paper, we introduce a new recursive algorithm to calculate the distribution of the time to the most recent common ancestor of the sample from a population evolved by any conditional multinomial sampling model. The most important advantage of our method is that it can be applied to a sample of any size drawn from a population regardless of its size growth pattern. We also present a very efficient method to implement and store the genealogy tree of the population evolved by the Galton–Watson process. In the final section we present results applied to a simulated population with a single bottleneck event and to real populations of known size histories.     

Statistical Method for Testing the Neutral Mutation Hypothesis by DNA Polymorphism

The relationship between the two estimates of genetic variation at the DNA level, namely the number of segregating sites and the average number of nucleotide differences estimated from pairwise comparison, is investigated. It is found that the correlation between these two estimates is large when the sample size is small, and decreases slowly as the sample size increases. Using the relationship obtained, a statistical method for testing the neutral mutation hypothesis is developed. This method needs only the data of DNA polymorphism, namely the genetic variation within population at the DNA level. A simple method of computer simulation, that was used in order to obtain the distribution of a new statistic developed, is also presented. Applying this statistical method to the five regions of DNA sequences in Drosophila melanogaster, it is found that large insertion/deletion (greater than 100 bp) is deleterious. It is suggested that the natural selection against large insertion/deletion is so weak that a large amount of variation is maintained in a population.     

北方冬季有蹄类动物4种数量调查方法的比较

科学的种群数量调查方法的探索一直是困扰北方有蹄类动物种群资源有效管理工作的重要问题。目前,北方野生有蹄类调查所采用的方法主要有样线法、样带法、大样方法和非损伤性CMR法4种。然而,不同的调查方法基于的统计学假设和生态学原理不同,调查结果往往会出现很大差异,迫切需要对北方冬季有蹄类动物的这4 种调查方法的有效性进行评估。以驼鹿种群数量调查为例,采用样线法、样带法、大样方法和非损伤性CMR调查法,于2012年3月和2012年12月对内蒙古汗马国家级自然保护区约120 km²的区域驼鹿种群数量进行了调查和评估。 结果显示,以上4 种方法得到的驼鹿种群数量分别为:样线法168(109-227) 只,样带法237(165-309) 只,大样方法37(23-50) 只,非损伤性CMR法55(43-68) 只,表明样线法和样带法的调查结果远大于大样方法和非损伤性CMR法,并探讨了不同调查方法应用的科学性、限制性和适用性,为北方冬季有蹄类动物种群资源调查方法的选择和应用提供了科学参考。