Estimating the total number of alleles using a sample coverage method.

Previously reported methods for estimating the number of different alleles at a single locus in a population have not described a useful general result. Using the number of alleles observed in a sample gives an underestimate for the true number of alleles. The similar problem of estimating the number of species in a population was first investigated in 1943. In this article we use the sample coverage method proposed by Chao and Lee in 1992 to estimate the number of alleles in a population when there are unequal allele frequencies. Simulation studies under the recurrent mutation model show that, for reasonable sample sizes, a significantly better estimate of the true number can be obtained than that using only the observed alleles. Results under the stepwise mutation model and infinite-allele model are presented. Possible applications include improving the characterization of the prior distribution for the allele frequencies, adjusting the estimates of genetic diversity, and estimating the range of microsatellite alleles.     

Estimating the number of founder lineages from haplotypes of closely linked SNPs

We consider an isolated population founded by a small number of individuals randomly chosen from a source population of known genetic composition at a known time in the past. We develop a Monte-Carlo maximum-likelihood method for estimating the number of founding individuals from the haplotype frequencies at several SNP (single nucleotide polymorphism) loci in a sample. We assume the isolated population was founded recently enough that that mutation can be ignored and that haplotype frequencies in the source population have not changed. We apply the method to simulated data and show that it is unbiased. With a reasonable number of individuals sampled, it is possible to estimate the number of founders within a factor of 2. We show that the performance of the method is not degraded substantially if the frequencies of the rare haplotypes in the source are not known precisely and if there is some recombination. We illustrate the use of our method by applying it to a previously published data set from a recently founded population of wolves (Canis lupus) in Scandinavia.     

Estimating ancestral distributions of lineages with uncertain sister groups： a statistical approach to Dispersal-Vicariance Analysis and a case using Aesculus L. （Sapindaceae） including fossils

We propose a simple statistical approach for using Dispersal-Vicariance Analysis （DIVA） software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as P（rY） = ∑t^n=1 F（rY）t Pt where Y is a node, and F（rY） is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage ＂x＂, where x may vary due to phylogenetic uncertainty （polytomies and nodes with posterior probability 〈 100%）. Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes-DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp＊F（rY） on the Bayesian consensus tree when both variables are 〈 100%, where pp is the posterior probability and F（rY） is the frequency of range r for the node containing the specific crown group. We tested our DIVA-Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and ofAesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA-Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic     

Estimating density of ant nests using distance sampling

The quantification of ant nest densities is a useful but challenging task given the group’s high abundance and diversity of nesting sites. We present a new application of a distance-sampling method which follows standard distance analytical procedures, but introduces a sampling innovation that is particularly useful for ants; instead of having an observer look for ants we let ants find a bait station and measure the distances covered between nest and station. We test this method by estimating the density of epigaeic ant nests in an Amazon tropical forest site near Manaus, Brazil. We distributed 220 baits of canned sardine mixed with cassava flour among 10, 210-m long transects in old-growth upland forest. Forty-five minutes after baiting, we followed the ants’ trails and measured the linear distance between the bait and each nest’s entrance. We then used the freely available program DISTANCE to estimate the number of nests per unit area while accounting for the effect of distance on the probability that a colony will find a bait. There were found 38 species nesting in 287 different colonies, with an estimated 2.66 nests/m². This estimate fell within the 95 % confidence bounds of nest density predicted for a similar number of species based on a literature survey of ant species richness and nest density. Our sampling solution, however, takes less than 30 % of the time used by conventional sampling approaches for a similar area, with the advantage that it produces not only a point estimate but also a quantification of uncertainty about density.     

Estimating the size of closed populations using inverse multiple-recapture sampling

A log-linear model for estimating the size of a closed population is defined for inverse multiple-recapture sampling with dependent samples. Efficient estimators of the log-linear model parameters and the population size are obtained by the method of minimum chi-square. A chi-square test of the general linear hypothesis regarding the log-linear model parameters is defined.     

Estimating hybridization in the presence of coalescence using phylogenetic intraspecific sampling

Background

Recent research has indicated a positive association between rates of molecular evolution and diversification in a number of taxa. However debate continues concerning the universality and cause of this relationship. Here, we present the first systematic investigation of this relationship within the mammals. We use phylogenetically independent sister-pair comparisons to test for a relationship between substitution rates and clade size at a number of taxonomic levels. Total, non-synonymous and synonymous substitution rates were estimated from mitochondrial and nuclear DNA sequences.

Results

We found no evidence for an association between clade size and substitution rates in mammals, for either the nuclear or the mitochondrial sequences. We found significant associations between body size and substitution rates, as previously reported.

Conclusions

Our results present a contrast to previous research, which has reported significant positive associations between substitution rates and diversification for birds, angiosperms and reptiles. There are three possible reasons for the differences between the observed results in mammals versus other clades. First, there may be no link between substitution rates and diversification in mammals. Second, this link may exist, but may be much weaker in mammals than in other clades. Third, the link between substitution rates and diversification may exist in mammals, but may be confounded by other variables.     

Estimating ancestral distributions of lineages with uncertain sister groups: a statistical approach to Dispersal–Vicariance Analysis and a case using Aesculus L. (Sapindaceae) including fossils

Abstract We propose a simple statistical approach for using Dispersal–Vicariance Analysis (DIVA) software to infer biogeographic histories without fully bifurcating trees. In this approach, ancestral ranges are first optimized for a sample of Bayesian trees. The probability P of an ancestral range r at a node is then calculated as where Y is a node, and F(r_Y ) is the frequency of range r among all the optimal solutions resulting from DIVA optimization at node Y, t is one of n topologies optimized, and Pt is the probability of topology t. Node Y is a hypothesized ancestor shared by a specific crown lineage and the sister of that lineage “x”, where x may vary due to phylogenetic uncertainty (polytomies and nodes with posterior probability <100%). Using this method, the ancestral distribution at Y can be estimated to provide inference of the geographic origins of the specific crown group of interest. This approach takes into account phylogenetic uncertainty as well as uncertainty from DIVA optimization. It is an extension of the previously described method called Bayes‐DIVA, which pairs Bayesian phylogenetic analysis with biogeographic analysis using DIVA. Further, we show that the probability P of an ancestral range at Y calculated using this method does not equate to pp*F(r_Y ) on the Bayesian consensus tree when both variables are <100%, where pp is the posterior probability and F(r_Y ) is the frequency of range r for the node containing the specific crown group. We tested our DIVA‐Bayes approach using Aesculus L., which has major lineages unresolved as a polytomy. We inferred the most probable geographic origins of the five traditional sections of Aesculus and of Aesculus californica Nutt. and examined range subdivisions at parental nodes of these lineages. Additionally, we used the DIVA‐Bayes data from Aesculus to quantify the effects on biogeographic inference of including two wildcard fossil taxa in phylogenetic analysis. Our analysis resolved the geographic ranges of the parental nodes of the lineages of Aesculus with moderate to high probabilities. The probabilities were greater than those estimated using the simple calculation of pp*F(r_y) at a statistically significant level for two of the six lineages. We also found that adding fossil wildcard taxa in phylogenetic analysis generally increased P for ancestral ranges including the fossil's distribution area. The ΔP was more dramatic for ranges that include the area of a wildcard fossil with a distribution area underrepresented among extant taxa. This indicates the importance of including fossils in biogeographic analysis. Exmination of range subdivision at the parental nodes revealed potential range evolution (extinction and dispersal events) along the stems of A. californica and sect. Parryana.     

Estimating genetic correlations based on phenotypic data: a simulation-based method

Knowledge of genetic correlations is essential to understand the joint evolution of traits through correlated responses to selection, a difficult and seldom, very precise task even with easy-to-breed species. Here, a simulation-based method to estimate genetic correlations and genetic covariances that relies only on phenotypic measurements is proposed. The method does not require any degree of relatedness in the sampled individuals. Extensive numerical results suggest that the propose method may provide relatively efficient estimates regardless of sample sizes and contributions from common environmental effects.     

Estimating number of clusters based on a general similarity matrix with application to microarray data

Many clustering methods require that the number of clusters believed present in a given data set be specified a priori, and a number of methods for estimating the number of clusters have been developed. However, the selection of the number of clusters is well recognized as a difficult and open problem and there is a need for methods which can shed light on specific aspects of the data. This paper adopts a model for clustering based on a specific structure for a similarity matrix. Publicly available gene expression data sets are analyzed to illustrate the method and the performance of our method is assessed by simulation.     

Estimating the number of motor units using random sums with independently thinned terms

The problem of estimating the numbers of motor units N in a muscle is embedded in a general stochastic model using the notion of thinning from point process theory. In the paper a new moment type estimator for the numbers of motor units in a muscle is denned, which is derived using random sums with independently thinned terms. Asymptotic normality of the estimator is shown and its practical value is demonstrated with bootstrap and approximative confidence intervals for a data set from a 31-year-old healthy right-handed, female volunteer. Moreover simulation results are presented and Monte-Carlo based quantiles, means, and variances are calculated for N in{300,600,1000}.     

Estimating the number of viable animal cells in multi-well cultures based on their lactate dehydrogenase activities

A method is described for estimating the numbers ofanimal cells in multi-well culture by simultaneouslymeasuring the lactate dehydrogenase activity of thetotal culture and the medium. The difference betweenthe two reflects the dehydrogenase content of thecells and correlates with cell number. This LDH/INTmethod was tested using several lines of normal andtransformed suspension and adherent cells. Thelactate dehydrogenase activities of duplicate cultureswere determined colourimetrically using reactioncocktails containing lactate, NAD⁺, diaphorase,and p-iodonitrotetrazolium violet, with and withoutTriton X-100. The difference in absorbance at 490 nm(A₄₉₀ = A_{490, test} – A_{490, control}) was used to calculate the lactatedehydrogenase activity of the total culture (+ Triton)and the medium (– Triton). The cellular lactatedehydrogenase activity (difference between totaland medium dehydrogenaseactivities) was proportional to viable cell number. The effects on cell growth of four metabolicinhibitors, sodium azide, actinomycin D,cycloheximide, and taxol, were determined using theLDH/INT assay and direct cell counting. The inhibitorconcentrations that caused decreases in the LDHactivity and cell number by 50% were similar. TheLDH/INT assay is quick and sensitive, works equallywell for adherent and suspension cells, and providesinformation about LDH activities of both the mediumand cells. It is particularly useful for screeningpotential cell-growth inhibitors.     

Estimating divergence time and ancestral effective population size of Bornean and Sumatran orangutan subspecies using a coalescent hidden Markov model

Due to genetic variation in the ancestor of two populations or two species, the divergence time for DNA sequences from two populations is variable along the genome. Within genomic segments all bases will share the same divergence-because they share a most recent common ancestor-when no recombination event has occurred to split them apart. The size of these segments of constant divergence depends on the recombination rate, but also on the speciation time, the effective population size of the ancestral population, as well as demographic effects and selection. Thus, inference of these parameters may be possible if we can decode the divergence times along a genomic alignment. Here, we present a new hidden Markov model that infers the changing divergence (coalescence) times along the genome alignment using a coalescent framework, in order to estimate the speciation time, the recombination rate, and the ancestral effective population size. The model is efficient enough to allow inference on whole-genome data sets. We first investigate the power and consistency of the model with coalescent simulations and then apply it to the whole-genome sequences of the two orangutan sub-species, Bornean (P. p. pygmaeus) and Sumatran (P. p. abelii) orangutans from the Orangutan Genome Project. We estimate the speciation time between the two sub-species to be thousand years ago and the effective population size of the ancestral orangutan species to be , consistent with recent results based on smaller data sets. We also report a negative correlation between chromosome size and ancestral effective population size, which we interpret as a signature of recombination increasing the efficacy of selection.     

Motif identification method based on Gibbs sampling and genetic algorithm

The regulation of gene expression is the key of organism genetic mechanism. Motif identification is an important step in constructing expression regulatory network. Based on Gibbs sampling method, this work constructed position weight matrix, thereby proposing motif recognition method based on genetic algorithm. Scoring function is defined to update the population and obtain the convergence matrix of position weight, achieving the identification of motifs with different length. Simulation and experimental data sets were utilized to verify the accuracy and execution time of the algorithm.     

Photographic sampling: a photographic sampling method for mites on plants

A photographic sampling method for mites on plants was evaluated using Tetranychus urticae and Phytoseiulus persimilis on pepper plants. It was found to be 92% accurate for T. urticae eggs and 98% accurate for P. persimilis eggs at densities up to 45 eggs per cm² for T. urticae, and up to 3 eggs per cm² for P. persimilis. The motiles of the two species were not confused, nor were they confused with exuviae or other matter.     

An easy-to-use maximum-likelihood method of estimating the ascertainment probability.

An easy-to-compute statistic for estimating the ascertainment probability is proposed. This statistic is determined through the use of the maximum-likelihood principle and, therefore, in addition to being easy to compute, has the desirable properties of a maximum-likelihood statistic. Variance tables are given to facilitate computation of the estimate and its variance.     

Estimating handling times for herbivore diets: a statistical method using the gamma distribution

1. We present a statistical model for the prediction of handling times for different diet items of herbivores foraging in heterogeneous environments, based on the distribution of time intervals between bites.
2. We propose the gamma distribution as a convenient and appropriate model for foraging data and illustrate its use with field observations of foraging Nubian ibex ( Capra ibex nubiana Linnaeus 1758) in the Negev Desert of Israel.
3. Specifically, we demonstrate how to estimate handling times from skewed frequency data of intervals between bites within patches.
4. We compared two mathematically equivalent gamma models and found a pronounced difference in the numerical results in fitting empirical data.
5. Estimated handling times varied with bite size, but not with plant category or sex of the foraging animal.
6. Fitting a gamma model to foraging data allows the efficient estimation of minimum handling constraints, mean handling times and within-patch cropping rates, which should be useful for models of the herbivore foraging process.     

Allelic lineages of the ficolin genes (FCNs) are passed from ancestral to descendant primates

The ficolins recognize carbohydrates and acetylated compounds on microorganisms and dying host cells and are able to activate the lectin pathway of the complement system. In humans, three ficolin genes have been identified: FCN1, FCN2 and FCN3, which encode ficolin-1, ficolin-2 and ficolin-3, respectively. Rodents have only two ficolins designated ficolin-A and ficolin-B that are closely related to human ficolin-1, while the rodent FCN3 orthologue is a pseudogene. Ficolin-2 and ficolin-3 have so far only been observed in humans. Thus, we performed a systematic investigation of the FCN genes in non-human primates. The exons and intron-exon boundaries of the FCN1-3 genes were sequenced in the following primate species: chimpanzee, gorilla, orangutan, rhesus macaque, cynomolgus macaque, baboon and common marmoset. We found that the exon organisation of the FCN genes was very similar between all the non-human primates and the human FCN genes. Several variations in the FCN genes were found in more than one primate specie suggesting that they were carried from one species to another including humans. The amino acid diversity of the ficolins among human and non-human primate species was estimated by calculating the Shannon entropy revealing that all three proteins are generally highly conserved. Ficolin-1 and ficolin-2 showed the highest diversity, whereas ficolin-3 was more conserved. Ficolin-2 and ficolin-3 were present in non-human primate sera with the same characteristic oligomeric structures as seen in human serum. Taken together all the FCN genes show the same characteristics in lower and higher primates. The existence of trans-species polymorphisms suggests that different FCN allelic lineages may be passed from ancestral to descendant species.