Conservation genetic studies of the endangered Cape Fear Shiner, Notropis mekistocholas (Teleostei: Cyprinidae)

Genetic variation at ten microsatellite lociand one anonymous-nuclear locus was assayed forthree geographic samples of the criticallyendangered North American cyprinidNotropis mekistocholas (Cape Fear shiner). Despite low abundance of this species, therewas little suggestion of small populationeffects; allele diversity and heterozygositywere relatively high, F_IS values withinsamples were non-significant, and genotypeswere distributed in frequencies according toHardy-Weinberg expectations. Geneticdivergence among samples was minimal despitethe presence of dams, constructed in the early1900s, that separate the sample sites. Thissuggests that recent gene flow has beensufficient to inhibit genetic divergence orthat gene flow has been reduced but there hasbeen insufficient time for genetic divergenceto develop. Tests of heterozygosity excesswere non-significant, suggesting that N.mekistocholas in the localities sampledhave not undergone recent reductions ineffective population size. Future studiesemploying larger sample sizes to provide morerobust tests of population structure andtemporally separated samples to estimatecontemporaneous N _e are warranted.     

Tests for Homogeneity of Variances Using Robust Weighted Likelihood Estimates

The classical normal-theory tests for testing the null hypothesis of common variance and the classical estimates of scale have long been known to be quite nonrobust to even mild deviations from normality assumptions for moderate sample sizes. Levene (1960) suggested a one-way ANOVA type statistic as a robust test. Brown and Forsythe (1974) considered a modified version of Levene's test by replacing the sample means with sample medians as estimates of population locations, and their test is computationally the simplest among the three tests recommended by Conover , Johnson , and Johnson (1981) in terms of robustness and power. In this paper a new robust and powerful test for homogeneity of variances is proposed based on a modification of Levene's test using the weighted likelihood estimates (Markatou , Basu , and Lindsay , 1996) of the population means. For two and three populations the proposed test using the Hellinger distance based weighted likelihood estimates is observed to achieve better empirical level and power than Brown-Forsythe's test in symmetric distributions having a thicker tail than the normal, and higher empirical power in skew distributions under the use of F distribution critical values.     

A method for adjusting allele frequencies in the case of microsatellite allele drop‐out

A new method is proposed to adjust allele frequencies when allelic drop‐out is common. This method assumes Hardy–Weinberg equilibrium (HWE), and treats the problematic alleles as a one‐locus two‐allele system with dominance. By assuming that the homozygote frequency of the ‘recessive’ allele is measured correctly, we can back calculate the allele frequency of the ‘dominant’ allele, and adjust the heterozygote frequency accordingly. The drawback is that multilocus genotypes cannot be constructed and tests that use deviations from Hardy–Weinberg such as tests for bottlenecks become impossible. An example is given where a large homozygote excess (F_IS = 0.44) is adjusted to a reasonable level (F_IS = 0.046). The effect of scoring error was set in relation to sampling error and while F_IS values can be seriously biased, F_ST values are not necessarily so, if scoring error and sample size are both low. As sample size increases, the effect of scoring error increases.     

Gene stacking strategies with doubled haploids derived from biparental crosses: theory and simulations assuming a finite number of loci

Recent progress in genotyping and doubled haploid (DH) techniques has created new opportunities for development of improved selection methods in numerous crops. Assuming a finite number of unlinked loci (ℓ) and a given total number (n) of individuals to be genotyped, we compared, by theory and simulations, three methods of marker-assisted selection (MAS) for gene stacking in DH lines derived from biparental crosses: (1) MAS for high values of the marker score (T, corresponding to the total number of target alleles) in the F₂ generation and subsequently among DH lines derived from the selected F₂ individual (Method 1), (2) MAS for augmented F₂ enrichment and subsequently for T among DH lines from the best carrier F₂ individual (Method 2), and (3) MAS for T among DH lines derived from the F₁ generation (Method 3). Our objectives were to (a) determine the optimum allocation of resources to the F₂ ( n₁^* \, n_{1}^{*} ) and DH generations (n - n₁^* ) (n - n_{1}^{*} ) for Methods 1 and 2 by simulations, (b) compare the efficiency of all three methods for gene stacking by simulations, and (c) develop theory to explain the general effect of selection on the segregation variance and interpret our simulation results. By theory, we proved that for smaller values of ℓ, the segregation variance of T among DH lines derived from F₂ individuals, selected for high values of T, can be much smaller than expected in the absence of selection. This explained our simulation results, showing that for Method 1, it is best to genotype more F₂ individuals than DH lines ($ n_{1}^{*} :n > 0.5 $ n_{1}^{*} :n > 0.5 ), whereas under Method 2, the optimal ratio n₁^* :n n_{1}^{*} :n was close to 0.5. However, for ratios deviating moderately from the optimum, the mean [`(X)] \overline{X} of T in the finally selected DH line ( T<sub>\textDH</sub><sup>*</sup> T_{\text{DH}}^{*} ) was hardly reduced. Method 3 had always the lowest mean [`(X)] \overline{X} of T_\textDH^* T_{\text{DH}}^{*} except for small numbers of loci (ℓ = 4) and is favorable only if a small number of loci are to be stacked in one genotype and/or saving one generation is of crucial importance in cultivar development. Method 2 is under most circumstances the superior method, because it generally showed the highest mean [`(X)] \overline{X} and lowest SD of T_\textDH^* T_{\text{DH}}^{*} for the finally selected DH.     

Identifying outlier loci in admixed and in continuous populations using ancestral population differentiation statistics

Finding genetic signatures of local adaptation is of great interest for many population genetic studies. Common approaches to sorting selective loci from their genomic background focus on the extreme values of the fixation index, F_ST, across loci. However, the computation of the fixation index becomes challenging when the population is genetically continuous, when predefining subpopulations is a difficult task, and in the presence of admixed individuals in the sample. In this study, we present a new method to identify loci under selection based on an extension of the F_ST statistic to samples with admixed individuals. In our approach, F_ST values are computed from the ancestry coefficients obtained with ancestry estimation programs. More specifically, we used factor models to estimate F_ST, and we compared our neutrality tests with those derived from a principal component analysis approach. The performances of the tests were illustrated using simulated data and by re‐analysing genomic data from European lines of the plant species Arabidopsis thaliana and human genomic data from the population reference sample, POPRES.     

Estimating sib percentages from small samples of F1 hybrid populations

Plant breeders raising F_x hybrid populations cannot usually grow more than about 300 plants from one seed lot. If not more than k sibs are observed in a random sample of size N, they then need to estimate the probability that the proportion of sibs in the population is at most p. For sample sizes of not more than 300 this note describes the required statistical procedure which, though not new, may be unfamiliar to plant breeders.     

Estimates of Genetic Differentiation Measured by F(ST) Do Not Necessarily Require Large Sample Sizes When Using Many SNP Markers

Population genetic studies provide insights into the evolutionary processes that influence the distribution of sequence variants within and among wild populations. F_ST is among the most widely used measures for genetic differentiation and plays a central role in ecological and evolutionary genetic studies. It is commonly thought that large sample sizes are required in order to precisely infer F_ST and that small sample sizes lead to overestimation of genetic differentiation. Until recently, studies in ecological model organisms incorporated a limited number of genetic markers, but since the emergence of next generation sequencing, the panel size of genetic markers available even in non-reference organisms has rapidly increased. In this study we examine whether a large number of genetic markers can substitute for small sample sizes when estimating F_ST. We tested the behavior of three different estimators that infer F_ST and that are commonly used in population genetic studies. By simulating populations, we assessed the effects of sample size and the number of markers on the various estimates of genetic differentiation. Furthermore, we tested the effect of ascertainment bias on these estimates. We show that the population sample size can be significantly reduced (as small as n = 4–6) when using an appropriate estimator and a large number of bi-allelic genetic markers (k>1,000). Therefore, conservation genetic studies can now obtain almost the same statistical power as studies performed on model organisms using markers developed with next-generation sequencing.     

Isolation and Identification of Fructo-oligosaccharides in Roots of Asparagus (Asparagus officinalis L.)

Eight fructo-oligosaccharides were isolated from purified oligosaccharide fractions of the roots of Asparagus officinalis L. (Liliaceae). By examination of constituent sugars, gas-liquid-chromatographic analysis of methyl derivatives, and investigation of partial acid hydrolyzates and products of β-fructofuranosidase action, they were confirmed to be 1^F(1-β -fructofuranosyl)_n sucrose [n = 1 (1-kestose), 2 (nystose), and 3], 6^G (1-β-fructofuranosyl)_n sucrose [n = 1 (neokestose), 2, and 3], 1^F,6^G-di-β-fructofuranosyl sucrose, and a new pentasaccharide 1^F (1-β-fructofuranosyl)₂-6^G-β-fructofuranosyl sucrose.     

An Approximate Solution to the Behrens-Fisher Problem

An approximate and practical solution is proposed for the Behrens-Fisher problem. This solution is compared to the solutions considered by Mehta and Srinivasan (1970) and Welch's (1937) approximate t-test in terms of the stability of the size and magnitude of the power. It is shown that the stability of the size of the new test is better than that of Welch's t when at least one of the sample sizes is small. When the sample sizes are moderately large or large the sizes and powers of all the recommended tests are almost the same.     

Power of tests for QTL detection using replicated progenies derived from a diallel cross

In crop species, most QTL (quantitative trait loci) mapping strategies use segregating populations derived from an initial cross between two lines. However, schemes including more than two parents could also be used. We propose an approach using a high-density restriction fragment length polymorphism (RFLP) map established on six F ₂ populations derived from diallel crosses among four inbred lines and the phenotypic performances of two types of replicated progenies (F ₃ and topcross). The QTL is supposed to be on the marker locus considered. Three linear model tests for the detection of QTL effects (T ₁, T ₂ and T ₃) are described and their power studied for the two types of progeny. T ₁ tests the global genetic effects of the QTL (additivity and dominance) and T ₂ tests only additive effects assuming dominance is absent when it could exist. The models of these two tests assume that the main effects of QTL alleles are constant in different genetic backgrounds. The additive model of test T ₃ considers the six F ₂ populations independently, and T ₃ is the equivalent of the classical mean comparison test if we neglect dominance; it uses only contrasts between the homozygote marker classes. The results show that T ₂ is much more powerful than T ₃. The power of T ₁ and T ₂ depends on the relative sizes of the additive and dominance effects, and their comparison is not easy to establish. Nevertheless, T ₂ seems to be the more powerful in most situations, indicating that it is often more interesting to ignore dominance when testing for a QTL effect. For a given size of genetic effects, the power is affected by the total number of individuals genotyped in F ₂ and the recombination rate between the marker locus and the putative QTL. The approach presented in this paper has some drawbacks but could be easily generalized to other sizes of diallels and different progeny types.     

Is local selection so widespread in river organisms? Fractal geometry of river networks leads to high bias in outlier detection

Identifying local adaptation is crucial in conservation biology to define ecotypes and establish management guidelines. Local adaptation is often inferred from the detection of loci showing a high differentiation between populations, the so‐called F_ST outliers. Methods of detection of loci under selection are reputed to be robust in most spatial population models. However, using simulations we showed that F_ST outlier tests provided a high rate of false‐positives (up to 60%) in fractal environments such as river networks. Surprisingly, the number of sampled demes was correlated with parameters of population genetic structure, such as the variance of F_STs, and hence strongly influenced the rate of outliers. This unappreciated property of river networks therefore needs to be accounted for in genetic studies on adaptation and conservation of river organisms.     

Acclimation of tropical tree seedlings to excessive light in simulated tree-fall gaps

Acclimation to periodic high‐light stress was studied in tree seedlings from a neotropical forest. Seedlings of several pioneer and late‐succession species were cultivated under simulated tree‐fall gap conditions; they were placed under frames covered with shade cloth with apertures of different widths that permitted defined periods of daily leaf exposure to direct sunlight. During direct sun exposure, all plants exhibited a marked reversible decline in potential photosystem II (PSII) efficiency, determined by means of the ratio of variable to maximum Chl a fluorescence (F_v/F_m). The decline in F_v/F_m under full sunlight was much stronger in late‐succession than in pioneer species. For each gap size, all species exhibited a similar degree of de‐epoxidation of violaxanthin in direct sunlight and similar pool sizes of xanthophyll cycle pigments. Pool sizes increased with increasing gap size. Pioneer plants possessed high levels of β‐carotene that also increased with gap size, whereas α‐carotene decreased. In contrast to late‐succession plants, pioneer plants were capable of adjusting their Chl a/b ratio to a high value in wide gaps. The content of extractable UV‐B‐absorbing compounds was highest in the plants acclimated to large gaps and did not depend on the successional status of the plants. The results demonstrate a better performance of pioneer species under high‐light conditions as compared with late‐succession plants, manifested by reduced photoinhibition of PSII in pioneer species. This was not related to increased pool size and turnover of xanthophyll cycle pigments, nor to higher contents of UV‐B‐absorbing substances. High β‐carotene levels and increased Chl a/b ratios, i.e. reduced size of the Chl a and b binding antennae, may contribute to photoprotection in pioneer species.     

The use of Artemia biomass sampling to predict cyst yields in culture ponds

The possibility of using biomass volume (= mean biomass present in the pond.week ^–1) to predict the total amount of harvestable cysts (= kg wet weight collected. week ^–1) produced in a culture pond by an Artemia franciscana population using a mixed model regression was evaluated for two different sampling methods; horizontal transects and vertical point samples. For transects, the following equation was found: `log (0.01 + cyst yields) = –2.05 + 0.025<sup>*</sup>(biomass volume)' with F <sub>(1, 4.87)</sub> = 8.83 and p = 0.032. For the point samples, the regression was also significant with F <sub>(1, 55.2)</sub> = 13.62 and p = 0.0005 for following equation: `log (0.01 + cyst yield) = –3.613 + 0.021^*(biomass volume). As pond effect and interaction terms did not significantly explain a significant portion of the variance for either of the sampling methods (Transects: pond: F _{(3, 14.3)} = 2.48; p = 0.103; pond^*biomass volume: F _{(3, 3.61)} = 4.63; p = 0.0976; Point samples: pond: F _{(3, 44.5)} = 0.00; p = 0.999; pond^*biomass volume: F _{(3, 44.2)} = 0.11; p = 0.954 ), the variable pond (repeated measurement factor) was not included in the final calculations for the regression equations. Although a combination of factors influences the equation, the high significance levels of the regression indicate biomass volume can be safely used to predict production trends. The low investment requirements of this method make it especially attractive for on farm use, where correctly determining the point of cyst decline will help farmers to allocate resources where needed.     

Physiological optimization underlies growth rate-independent chlorophyll-specific gross and net primary production

Characterization of physiological variability in phytoplankton photosynthetic efficiencies is one of the greatest challenges in assessing ocean net primary production (NPP) from remote sensing of surface chlorophyll (Chl). Nutrient limitation strongly influences phytoplankton intracellular pigmentation, but its impact on Chl-specific NPP (NPP ^*) is debated. We monitored six indices of photosynthetic activity in steady-state Dunaliella tertiolecta cultures over a range of nitrate-limited growth rates (μ), including photosynthetic efficiency of PSII (F _v/F _m), O₂-based gross and net production, 20 min and 24 h carbon assimilation, and carbon- and μ-based NPP. Across all growth rates, O₂-based Chl-specific gross primary production ( GPP_\textO2 ^* GPP_{{{\text{O}}_{2} }}^{*} ), NPP ^*, and F _v/F _m were constant. GPP_\textO2 ^* GPP_{{{\text{O}}_{2} }}^{*} was 3.3 times greater than NPP ^*. In stark contrast, Chl-specific short-term C fixation showed clear linear dependence on μ, reflecting differential allocation of photosynthate between short-lived C products and longer-term storage products. Indeed, ¹⁴C incorporation into carbohydrates was five times greater in cells growing at 1.2 day⁻¹ than 0.12 day⁻¹. These storage products are catabolized for ATP and reductant generation within the period of a cell cycle. The relationship between Chl-specific gross and net O₂ production, short-term ¹⁴C-uptake, NPP ^*, and growth rate reflects cellular-level regulation of fundamental metabolic pathways in response to nutrient limitation. We conclude that growth rate-dependent photosynthate metabolism bridges the gap between gross and net production and resolves a controversial question regarding nutrient limitation effects on primary production measures.     

Performance index in assessing the physiological state of trees in urban ecosystems

Based on PAM and PEA measurements of fluorescence of bark chloroplasts, we have compared the information capacity of the methods for assessing the physiological state of Tilia cordata Mill. by the maximal quantum efficiency of PS II photochemistry (F _v/F _m) and by the performance index (PI). The measurements were made on annual shoots of linden trees growing in different environs. It was shown that the chlorophyll content in the bark of shoots growing near a busy urban street was twice less than in controls growing out of town. For the trees in the unfavorable environment, a small decrease in (F _v/F _m) was registered, and there was a significant statistical scatter in these values as compared with controls. The PI and its constituent parameters calculated from fluorescence induction curves (PEA method) are more informative and allow recognizing changes in the primary energy conversion processes in PS II when they are still small. Thus, PI can be used as a sensitive, robust, and rapid test to evaluate the physiological state of trees and other plant objects even under minor environmental changes.     

The calculation and significance testing of genetic correlations across environments

Genetic correlations within a trait across environments (r_g) are important in the analysis of phenotypic plasticity. Not all methods are, however, equally reliable. An overview of all different methods for estimation of r_g with one generation data sets is given. Formulae for the relationship between causal variance components and family means are derived. When these formulae are used covariances derived from family means, thought to be incorrect, are exactly the same as those derived with the ANOVA method. The bias, precision and power of the different methods are compared with Monte Carlo simulations. For all methods bias is small and precision is high for the large balanced data sets analyzed here, except when the variance in one or both of the environments is close to 0. Significance testing causes more problems. Confidence intervals with or without z-transformation are not suitable for testing, nor is testing for g*e interaction in an ANOVA suitable for testing whether the r_g is different from 1. The F-test in a mixed model ANOVA and a likelihood ratio test in a REML-analysis can be used for testing a difference from 0 but not from 1 or other values. Jackknife and Bootstrap, however, are suitable tests both for differences with 0,1 and other values, though negative variances can make these tests difficult to apply.     

Dynamic micro-geographic and temporal genetic diversity in vertebrates: the case of lake-spawning populations of brown trout (Salmo trutta)

Conservation of species should be based on knowledge of effective population sizes and understanding of how breeding tactics and selection of recruitment habitats lead to genetic structuring. In the stream‐spawning and genetically diverse brown trout, spawning and rearing areas may be restricted source habitats. Spatio–temporal genetic variability patterns were studied in brown trout occupying three lakes characterized by restricted stream habitat but high recruitment levels. This suggested non‐typical lake‐spawning, potentially representing additional spatio–temporal genetic variation in continuous habitats. Three years of sampling documented presence of young‐of‐the‐year cohorts in littoral lake areas with groundwater inflow, confirming lake‐spawning trout in all three lakes. Nine microsatellite markers assayed across 901 young‐of‐the‐year individuals indicated overall substantial genetic differentiation in space and time. Nested gene diversity analyses revealed highly significant (≤P = 0.002) differentiation on all hierarchical levels, represented by regional lakes (F_LT = 0.281), stream vs. lake habitat within regional lakes (F_HL = 0.045), sample site within habitats (F_SH = 0.010), and cohorts within sample sites (F_CS = 0.016). Genetic structuring was, however, different among lakes. It was more pronounced in a natural lake, which exhibited temporally stable structuring both between two lake‐spawning populations and between lake‐ and stream spawners. Hence, it is demonstrated that lake‐spawning brown trout form genetically distinct populations and may significantly contribute to genetic diversity. In another lake, differentiation was substantial between stream‐ and lake‐spawning populations but not within habitat. In the third lake, there was less apparent spatial or temporal genetic structuring. Calculation of effective population sizes suggested small spawning populations in general, both within streams and lakes, and indicates that the presence of lake‐spawning populations tended to reduce genetic drift in the total (meta‐) population of the lake.     

When can noninvasive samples provide sufficient information in conservation genetics studies?

Noninvasive sampling, of faeces and hair for example, has enabled many genetic studies of wildlife populations. However, two prevailing problems common to these studies are small sample sizes and high genotyping errors. The first problem stems from the difficulty in collecting noninvasive samples, particularly from populations of rare or elusive species, and the second is caused by the low quantity and quality of DNA extracted from a noninvasive sample. A common question is therefore whether noninvasive sampling provides sufficient information for the analyses commonly conducted in conservation genetics studies. Here, we conducted a simulation study to investigate the effect of small sample sizes and genotyping errors on the precision and accuracy of the most commonly estimated genetic parameters. Our results indicate that small sample sizes cause little bias in measures of expected heterozygosity, pairwise F_ST and population structure, but a large downward bias in estimates of allelic diversity. Allelic dropouts and false alleles had a much smaller effect than missing data, which effectively reduces sample size further. Overall, reasonable estimates of genetic variation and population subdivision are obtainable from noninvasive samples as long as error rates are kept below a frequency of 0.2. Similarly, unbiased estimates of population clustering can be made with genotyping error rates below 0.5 when the populations are highly differentiated. These results provide a useful guide for researchers faced with studying the conservation genetics of small, endangered populations from noninvasive samples.     

Robustness of statistical tests for multiplicative terms in the additive main effects and multiplicative interaction model for cultivar trials

The additive main effects multiplicative interaction model is frequently used in the analysis of multilocation trials. In the analysis of such data it is of interest to decide how many of the multiplicative interaction terms are significant. Several tests for this task are available, all of which assume that errors are normally distributed with a common variance. This paper investigates the robustness of several tests (Gollob, F _GH1, F_GH2, F_R)to departures from these assumptions. It is concluded that, because of its better robustness, the F _Rtest is preferable. If the other tests are to be used, preliminary tests for the validity of assumptions should be performed.     

Genetics of complement C4. Two homoduplication haplotypes C4S C4S and C4F C4F in a family

Summary A family in which two homoduplicated C4 haplotypes (or supergenes) segregate is described. One haplotype C4F ^* 3 C4F ^*2.2 is composed of two C4F alleles and the other C4S ^* 5.1 C4S ^*1 of two C4S alleles. The C4F duplication haplotype is a partial inhibitor of the Rodgers antigen, and judged from our family and population material, it seems to be rather frequent and associated with HLAB ^*35, Bf ^* F, and HLAD/DR ^*1. The C4S duplication haplotype is Rg(a-) and is not identified in individuals without another S, Ch(a+) variant.This work was supported by grant No 12-1727 from the Danish Medical Research Council