Close relatives in population samples: Evaluation of the consequences for genetic stock identification

Determining the origin of individuals in mixed population samples is key in many ecological, conservation and management contexts. Genetic data can be analyzed using genetic stock identification (GSI), where the origin of single individuals is determined using Individual Assignment (IA) and population proportions are estimated with Mixed Stock Analysis (MSA). In such analyses, allele frequencies in a reference baseline are required. Unknown individuals or mixture proportions are assigned to source populations based on the likelihood that their multilocus genotypes occur in a particular baseline sample. Representative sampling of populations included in a baseline is important when designing and performing GSI. Here, we investigate the effects of family sampling on GSI, using both simulated and empirical genotypes for Atlantic salmon (Salmo salar). We show that nonrepresentative sampling leading to inclusion of close relatives in a reference baseline may introduce bias in estimated proportions of contributing populations in a mixed sample, and increases the amount of incorrectly assigned individual fish. Simulated data further show that the induced bias increases with increasing family structure, but that it can be partly mitigated by increased baseline population sample sizes. Results from standard accuracy tests of GSI (using only a reference baseline and/or self‐assignment) gave a false and elevated indication of the baseline power and accuracy to identify stock proportions and individuals. These findings suggest that family structure in baseline population samples should be quantified and its consequences evaluated, before carrying out GSI.     

Flow-cytometric identification and follow-up of mice exposed to x-irradiation: Evaluation of a model system

An experimental model system is presented that allows the identification and follow-up of mice exposed to ionizing radiation using flow-cytometric measurements of peripheral blood cells. In an experiment, properties of peripheral blood cells were analysed with flow cytometry for a rapid identification of individuals exposed to radiation. Individuals were then followed longitudinally in an attempt to identify those developing neoplasias. Male CBA mice, 25 days old, were subjected to fractionated x-irradiation (4 × 1.31 Gy) to induce haematopoietic malignancies. By repeated blood sampling followed by flow cytometry, frequencies of micronucleated erythrocytes and of proliferating nucleated cells were determined. Neoplasias were diagnosed by histopathology. Five days after the end of radiation exposure, increased frequencies of proliferating cells, polychromatic erythrocytes and micronucleated normochromatic erythrocytes clearly distinguished the exposed group from the control group. Increased cell proliferation in peripheral blood cells could be used to identify animals with manifest tumours, although these animals were at a late stage of tumour development. Animals with thymic lymphoma (not generalized) could not be identified with the flow-cytometric parameters used. We consider that this model system has a potential use when a small number of risk individuals need to be identified and monitored within a large population.     

Characterizing dispersal patterns in a threatened seabird with limited genetic structure

Genetic assignment methods provide an appealing approach for characterizing dispersal patterns on ecological time scales, but require sufficient genetic differentiation to accurately identify migrants and a large enough sample size of migrants to, for example, compare dispersal between sexes or age classes. We demonstrate that assignment methods can be rigorously used to characterize dispersal patterns in a marbled murrelet (Brachyramphus marmoratus) population from central California that numbers approximately 600 individuals and is only moderately differentiated (F_ST～ 0.03) from larger populations to the north. We used coalescent simulations to select a significance level that resulted in a low and approximately equal expected number of type I and II errors and then used this significance level to identify a population of origin for 589 individuals genotyped at 13 microsatellite loci. The proportion of migrants in central California was greatest during winter when 83% of individuals were classified as migrants compared to lower proportions during the breeding (6%) and post‐breeding (8%) seasons. Dispersal was also biased toward young and female individuals, as is typical in birds. Migrants were rarely members of parent‐offspring pairs, suggesting that they contributed few young to the central California population. A greater number of migrants than expected under equilibrium conditions, a lack of individuals with mixed ancestry, and a small number of potential source populations (two), likely allowed us to use assignment methods to rigorously characterize dispersal patterns for a population that was larger and less differentiated than typically thought required for the identification of migrants.     

Reduced proportions of natural killer T cells are present in the relatives of lupus patients and are associated with autoimmunity

Introduction

Systemic lupus erythematosus is a genetically complex disease. Currently, the precise allelic polymorphisms associated with this condition remain largely unidentified. In part this reflects the fact that multiple genes, each having a relatively minor effect, act in concert to produce disease. Given this complexity, analysis of subclinical phenotypes may aid in the identification of susceptibility alleles. Here, we used flow cytometry to investigate whether some of the immune abnormalities that are seen in the peripheral blood lymphocyte population of lupus patients are seen in their first-degree relatives.

Methods

Peripheral blood mononuclear cells were isolated from the subjects, stained with fluorochrome-conjugated monoclonal antibodies to identify various cellular subsets, and analyzed by flow cytometry.

Results

We found reduced proportions of natural killer (NK)T cells among 367 first-degree relatives of lupus patients as compared with 102 control individuals. There were also slightly increased proportions of memory B and T cells, suggesting increased chronic low-grade activation of the immune system in first-degree relatives. However, only the deficiency of NKT cells was associated with a positive anti-nuclear antibody test and clinical autoimmune disease in family members. There was a significant association between mean parental, sibling, and proband values for the proportion of NKT cells, suggesting that this is a heritable trait.

Conclusions

The findings suggest that analysis of cellular phenotypes may enhance the ability to detect subclinical lupus and that genetically determined altered immunoregulation by NKT cells predisposes first-degree relatives of lupus patients to the development of autoimmunity.     

Viability assessment of dog spermatozoa using flow cytometry

The percentages of living and dead spermatozoa in fresh dog semen samples were assessed by means of a dual staining technique using carboxifluorescein diacetate (CFDA) and propidium iodide (PI). Two ejaculates were obtained from dogs, each ejaculate was divided into 4 aliquots, and different proportions of freeze-killed cells were added to each aliquot. Data obtained by flow cytometry analysis of each sample were compared with those obtained by the microscopic evaluation under epifluorescence illumination and by phase-contrast microscopy evaluation of the samples stained with eosin-nigrosin. Regression analysis was used to compare the 3 methods for membrane integrity assessment of canine spermatozoa, and high correlation coefficients were found between the flow cytometry procedure and the 2 microscopy techniques. The results from this study validate the use of flow cytometry as a precise method for assessing the viability of dog spermatozoa.     

Rapid identification and detection of parasitized human red cells by automated flow cytometry

Rapid and reliable identification of various human red cells parasites is important in many chemotherapeutic and immunologic studies. Because manual microscopic counting is tedious and imprecise, we have developed a simple diagnostic procedure for the automated flow cytometric detection of in vitro infected red cells, using a nucleic acid-binding fluorescent dye, acridine orange. Human malaria (Plasmodium falciparum)-infected red cells from continuous human erythrocyte culture were incubated at room temperature in acridine orange stain for 5 min after which the samples were analyzed by flow cytometry. Since mature red cells contain no DNA, infected red cells were identified with a distinct fluorescent signal. A total of 200,000 cells per sample were counted and analyzed in less than 2 min. Rings, trophozoites, and schizonts were assessed and identified in synchronized infected red cell cultures by flow cytometry. In addition, various stages of infected red cells were isolated with a cell sorter. This rapid method permits accurate and reliable assessment of data with the exclusion of anomalous data such as damaged cells, extraneous material, and contaminating particles.     

Integrating cytomics and proteomics

Systems biology along with what is now classified as cytomics provides an excellent opportunity for cytometry to become integrated into studies where identification of functional proteins in complex cellular mixtures is desired. The combination of cell sorting with rapid protein-profiling platforms offers an automated and rapid technique for greater clarity, accuracy, and efficiency in identification of protein expression differences in mixed cell populations. The integration of cell sorting to purify cell populations opens up a new area for proteomic analysis. This article outlines an approach in which well defined cell analysis and separation tools are integrated into the proteomic programs within a core laboratory. In addition we introduce the concepts of flow cytometry sorting to demonstrate the importance of being able to use flow cytometry as a cell separation technology to identify and collect purified cell populations. Data demonstrating the speed and versatility of this combination of flow cytometry-based cell separation and protein separation and subsequent analysis, examples of protein maps from purified sorted cells, and an analysis of the overall procedure will be shown. It is clear that the power of cell sorting to separate heterogeneous populations of cells using specific phenotypic characteristics increases the power of rapid automated protein separation technologies.     

Use of a lectin as an enterocyte-specific cell surface marker for flow cytometric analysis of isolated native small intestinal epithelial cells

Little use has been made of flow cytometry in evaluating small intestinal epithelial cells. Obtaining pure epithelial cell populations devoid of peripheral blood contaminants and intraepithelial lymphocytes contributes to the difficulties encountered in flow cytometry studies. We have investigated the use of lectins as enterocyte specific cell markers using lectin histochemistry, and have identified one lectin, UEA-1, which binds exclusively and specifically to intestinal epithelial cell brush border. Additionally, we have exploited that specificity using flow cytometry and FITC-UEA-1 to identify and separate native intestinal epithelial cells from a mixed cell population isolated by mechanical vibration. This fluorescent-lectin technique is a unique and simple method to identify native small intestinal epithelial cells in a mixed cell population; it may be exploited by flow cytometric sorting of a pure population for biochemical study or as an enterocyte specific label for surface receptor flow cytometric studies in the research or clinical setting.     

Comment on analyzing flow cytometric data for comparison of mean values of the coefficient of variation of the G1 peak.

BACKGROUND: The coefficient of variation (CV) is often used to characterize and summarize the flow cytometry analysis of nuclear DNA of the Go/G1 peak in a cell population within an individual organism. CV values are frequently used in subsequent statistical analysis to compare experimental groups of individuals. METHODS: We explain why the conventional analysis of variance, linear comparisons and regressions that employ the F and t-tests are not appropriate for analyzing CV data sets. The weighted least squares procedure which utilizes the chi-square test is presented as an adequate method. We further explain why this type of data needs to be analyzed by this procedure. RESULTS: To illustrate the application of the weighted least squares procedure, we analyzed a real data set that had been previously analyzed by conventional methods. We found that a non-significant result (p = 1) using the latter was significant when re-analyzed with the weighted least squares procedure (p = 0.032). CONCLUSIONS: Significant differences between treatments established by the weighted least squares often go unidentified by the conventional analysis. Use of the weighted least squares procedure is recommended for analyzing CV data sets.     

Post-thaw evaluation of dog spermatozoa using new triple fluorescent staining and flow cytometry

A new triple fluorescent staining method was developed to evaluate frozen-thawed dog spermatozoa. This method was used to compare functional parameters of canine spermatozoa cryopreserved using 2 different freezing-thawing protocols. One ejaculate from each of 10 dogs was split into 2 aliquots and processed using the Andersen method or the CLONE method. Semen samples were evaluated immediately after thawing and after 3 h of incubation at 37 degrees C. Plasma membrane integrity and acrosomal status of the spermatozoa were evaluated simultaneously by flow cytometry using a combination of 3 fluorescent dyes: Carboxy-SNARF-1 (SNARF), to identify the live spermatozoa; propidium iodide (PI), which only stains dead cells or cells with damaged membranes; and fluorescein isothiocyanate (FITC)-conjugated Pisum sativum agglutinin (PSA), which binds to the acrosomal content of spermatozoa with damaged plasma and outer acrosomal membranes. The accuracy of this new staining method in quantifying the proportions of live and dead spermatozoa by flow cytometry was evaluated by comparing it with the staining technique using carboxyfluorescein diacetate and propidium iodide (CFDA-PI), which yielded high correlation coefficients. The triple-stained sperm samples were also analyzed by epifluorescence microscopy, and both methods proved to be highly correlated. Post-thaw progressive motility and plasma membrane integrity were similar for the 2 freezing procedures, but the proportion of damaged acrosomes after thawing was lower using the Andersen method and the spermatozoa had a higher thermoresistance. This new triple staining method for assessing canine sperm viability and acrosomal integrity provides an efficient procedure for evaluating frozen-thawed dog semen samples either by flow cytometry or fluorescence microscopy.     

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.     

Differences in the flow and absorption cytometric DNA distributions of mouse hepatocytes and tumor cells

We have determined the DNA content, the ploidy levels, and the percentages of different cell types present in small and large mouse mammary tumors as well as in young and old mouse livers by using absorption and flow cytometry. Absorption cytometry data indicated a significant increase in the proportion of transformed G0/G1 cells in the tumors as compared to that of the stromal G0/G1 cells with progressive tumor growth. This increase was not detected by flow cytometry. In both young and old mouse livers, a small number of cells of higher ploidy (8C and 16C) were detected by absorption cytometry but were not apparent in histograms obtained by flow cytometry. Furthermore, changes in the proportions of liver cells of different ploidy with age were apparent in absorption cytometry data but not in flow cytometry data. In one mouse liver experiment, a 6C cell peak appeared in the flow cytometry histogram, but a direct measurement of DNA content by absorption cytometry failed to detect cells with such a peak. We therefore believe that some caution may be warranted in the use of flow cytometry alone for evaluation of DNA distributions and of the proportions of different types of cells in complex solid tissues.     

Genetic tagging: contemporary molecular ecology

Population genetic analyses have been highly successful in deciphering inter- and intra-specific evolutionary relationships, levels of gene flow, genetic divergence and effective population sizes. Parameters estimated by traditional population genetic analyses are evolutionary averages and thus not necessarily relevant for contemporary ecological or conservation issues. Molecular data can, however, also provide insight into contemporary patterns of divergence, population size and gene flow when a sufficient number of variable loci are analysed to focus subsequent data analyses on individuals rather than populations. Genetic tagging of individuals is an example of such individual-based approaches and recent studies have shown it to be a viable alternative to traditional tagging methods. Owing to the ubiquitous presence of hyper-variable DNA sequences in eukaryote genomes it is in principle possible to tag any eukaryote species and the required DNA can be obtained indirectly from substrates such as faeces, sloughed skin and hair. The purpose of this paper is to present the concept of genetic tagging and to further advocate the extension of individual-based genetic analyses beyond the identification of individuals to other kinds of relationships, such as parent-offspring relations, which more fully exploit the genetic nature of the data.     

Backward simulation of ancestors of sampled individuals

If the population is large and the sampling mechanism is random, the coalescent is commonly used to model the haplotypes in the sample. Ordered genotypes can then be formed by random matching of the derived haplotypes. However, this approach is not realistic when (1) there is departure from random mating (e.g., dominant individuals in breeding populations or monogamy in humans), or (2) the population is small and/or the individuals in the sample are ascertained by applying some particular non-random sampling scheme, as is usually the case when considering the statistical modeling and analysis of pedigree data. For such situations, we present here a data generation method where an ancestral graph with non-overlapping generations is first generated backwards in time, using ideas from coalescent theory. Alleles are randomly assigned to the founders, and subsequently the gene flow over the entire genome is simulated forwards in time by dropping alleles down the graph according to recombination model without interference. The parameters controlling the mating behavior of generated individuals in the graph (degree of monogamy) can be tuned in order to match a particular demographic situation, without restriction to simple random mating.The performance of the approach is illustrated with a simulation example. The software (written in C-language) is freely available for research purposes at http://www.rni.helsinki.fi/∼dag/.     

Allele-sharing methods for estimation of population size

Genetic data are becoming increasingly important in ecology and conservation biology. This article presents a novel method for estimating population size from DNA profiles obtained from a random sample of individuals. The underlying idea is that the degree of biological relationship between individuals in the sample reflects the size of the population and that DNA profiles provide information about relatedness. A pseudolikelihood approach is taken, involving pairwise comparison of individuals. The main field of applications is seen to be catch data, and as an example, the method is applied to DNA profiles (10 microsatellite loci) from 334 North Atlantic minke whales. It is concluded that the sample size is too small for the method to give useful results. The question about the required sample size is investigated by simulation.     

Genetic assignment methods for the direct, real-time estimation of migration rate: a simulation-based exploration of accuracy and power

Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (DLR) appeared to be an effective way to predict whether F0 immigrants could be identified for a particular pair of populations using a given set of markers.     

Flow cytometric analysis of micronucleated reticulocytes in mouse bone marrow

This laboratory has previously reported a flow cytometric procedure for quantitatively analyzing mouse peripheral blood reticulocytes for micronucleus content. The current study extends this line of investigation by evaluating whether these same flow cytometric scoring procedures can be applied to the analysis of mouse bone marrow samples. To validate the method, three groups of male BALB/c mice were treated with 100 mg/kg b.wt. methyl methanesulfonate. Bone marrow samples were collected 20, 40 or 60 h after administration. A set of 5 untreated animals was included to provide an indication of spontaneous micronucleus frequencies. The cells were fixed with ultracold methanol, treated with ribonuclease, and labeled with anti-CD71 antibody (FITC conjugate) and propidium iodide. This fixing and labeling procedure resulted in the resolution of the micronucleated reticulocyte population and facilitated high-speed acquisition and enumeration via flow cytometry. The number of micronucleated reticulocytes was determined flow cytometrically by the analysis of 10?000 total reticulocytes per bone marrow sample. In addition to these automated measurements, slides stained with acridine orange were prepared and the number of micronuclei per 1000 reticulocytes was determined microscopically for each sample. The resulting data demonstrate that flow cytometry can effectively enumerate micronucleated reticulocytes in mouse bone marrow. The advantages associated with an objective, high throughput scoring methodology are also clearly indicated.     

Individual organisms as units of analysis: Bayesian-clustering alternatives in population genetics

Population genetic analyses traditionally focus on the frequencies of alleles or genotypes in 'populations' that are delimited a priori. However, there are potential drawbacks of amalgamating genetic data into such composite attributes of assemblages of specimens: genetic information on individual specimens is lost or submerged as an inherent part of the analysis. A potential also exists for circular reasoning when a population's initial identification and subsequent genetic characterization are coupled. In principle, these problems are circumvented by some newer methods of population identification and individual assignment based on statistical clustering of specimen genotypes. Here we evaluate a recent method in this genre--Bayesian clustering--using four genotypic data sets involving different types of molecular markers in non-model organisms from nature. As expected, measures of population genetic structure (F(ST) and phiST) tended to be significantly greater in Bayesian a posteriori data treatments than in analyses where populations were delimited a priori. In the four biological contexts examined, which involved both geographic population structures and hybrid zones, Bayesian clustering was able to recover differentiated populations, and Bayesian assignments were able to identify likely population sources of specific individuals.     

Cellometer image cytometry as a complementary tool to flow cytometry for verifying gated cell populations

Traditionally, many cell-based assays that analyze cell populations and functionalities have been performed using flow cytometry. However, flow cytometers remain relatively expensive and require highly trained operators for routine maintenance and data analysis. Recently, an image cytometry system has been developed by Nexcelom Bioscience (Lawrence, MA, USA) for automated cell concentration and viability measurement using bright-field and fluorescent imaging methods. Image cytometry is analogous to flow cytometry in that gating operations can be performed on the cell population based on size and fluorescent intensity. In addition, the image cytometer is capable of capturing bright-field and fluorescent images, allowing for the measurement of cellular size and fluorescence intensity data. In this study, we labeled a population of cells with an enzymatic vitality stain (calcein-AM) and a cell viability dye (propidium iodide) and compared the data generated by flow and image cytometry. We report that measuring vitality and viability using the image cytometer is as effective as flow cytometric assays and allows for visual confirmation of the sample to exclude cellular debris. Image cytometry offers a direct method for performing fluorescent cell-based assays but also may be used as a complementary tool to flow cytometers for aiding the analysis of more complex samples.