An improved algorithm for statistical alignment of sequences related by a star tree

The insertion-deletion model developed by Thorne, Kishino and Felsenstein (1991, J. Mol. Evol., 33, 114–124; the TKF91 model) provides a statistical framework of two sequences. The statistical alignment of a set of sequences related by a star tree is a generalization of this model. The known algorithm computes the probability of a set of such sequences in O(l ^2k ) time, where l is the geometric mean of the sequence lengths and k is the number of sequences. An improved algorithm is presented whose running time is only O(2^2k l ^k).     

The MinMax Squeeze: guaranteeing a minimal tree for population data

We report that for population data, where sequences are very similar to one another, it is often possible to use a two-pronged (MinMax Squeeze) approach to prove that a tree is the shortest possible under the parsimony criterion. Such population data can be in a range where parsimony is a maximum likelihood estimator. This is in sharp contrast to the case with species data, where sequences are much further apart and the problem of guaranteeing an optimal phylogenetic tree is known to be computationally prohibitive for realistic numbers of species, irrespective of whether likelihood or parsimony is the optimality criterion. The Squeeze uses both an upper bound (the length of the shortest tree known) and a lower bound derived from partitions of the columns (the length of the shortest tree possible). If the two bounds meet, the shortest known tree is thus proven to be a shortest possible tree. The implementation is first tested on simulated data sets and then applied to 53 complete human mitochondrial genomes. The shortest possible trees for those data have several significant improvements from the published tree. Namely, a pair of Australian lineages comes deeper in the tree (in agreement with archaeological data), and the non-African part of the tree shows greater agreement with the geographical distribution of lineages.     

Clique-based data mining for related genes in a biomedical database

Background  

Progress in the life sciences cannot be made without integrating biomedical knowledge on numerous genes in order to help formulate hypotheses on the genetic mechanisms behind various biological phenomena, including diseases. There is thus a strong need for a way to automatically and comprehensively search from biomedical databases for related genes, such as genes in the same families and genes encoding components of the same pathways. Here we address the extraction of related genes by searching for densely-connected subgraphs, which are modeled as cliques, in a biomedical relational graph.     

New method for global alignment of 2 DNA sequences by the tree data structure

We introduce a new approach to investigate problem of DNA sequence alignment. The method consists of three parts: (i) simple alignment algorithm, (ii) extension algorithm for largest common substring, (iii) graphical simple alignment tree (GSA tree). The approach firstly obtains a graphical representation of scores of DNA sequences by the scoring equation R₀*R−S₀*S−T₀*(a+bk). Then a GSA tree is constructed to facilitate solving the problem for global alignment of 2 DNA sequences. Finally we give several practical examples to illustrate the utility and practicality of the approach.     

Cambial activity related to tree size in a mature silver-fir plantation

Background and Aims

Our knowledge about the influences of environmental factors on tree growth is principally based on the study of dominant trees. However, tree social status may influence intra-annual dynamics of growth, leading to differential responses to environmental conditions. The aim was to determine whether within-stand differences in stem diameters of trees belonging to different crown classes resulted from variations in the length of the growing period or in the rate of cell production.

Methods

Cambial activity was monitored weekly in 2006 for three crown classes in a 40-year-old silver-fir (Abies alba) plantation near Nancy (France). Timings, duration and rate of tracheid production were assessed from anatomical observations of the developing xylem.

Key Results

Cambial activity started earlier, stopped later and lasted longer in dominant trees than in intermediate and suppressed ones. The onset of cambial activity was estimated to have taken 3 weeks to spread to 90 % of the trees in the stand, while the cessation needed 6 weeks. Cambial activity was more intense in dominant trees than in intermediate and suppressed ones. It was estimated that about 75 % of tree-ring width variability was attributable to the rate of cell production and only 25 % to its duration. Moreover, growth duration was correlated to tree height, while growth rate was better correlated to crown area.

Conclusions

These results show that, in a closed conifer forest, stem diameter variations resulted principally from differences in the rate of xylem cell production rather than in its duration. Tree size interacts with environmental factors to control the timings, duration and rate of cambial activity through functional processes involving source–sink relationships principally, but also hormonal controls.     

Nitrogen assimilation by a Citrus tree

Primary assimilation of ¹⁵N-ammonium or ¹⁵N-nitrate by excised leaves of satsuma mandarin (Citrus unshiu Markovitch) was examined under light and dark conditions. Under both conditions both types of nitrogen were most markedly incorporated into glutamine-amide nitrogen in the primary step of the assimilation, and into proline in the later steps. Incorporation of ammonium or nitrate into amino acids was more active in the light than in the dark, although the stimulating effect of light on the incorporation was relatively small in both cases.     

Inferring tree models for oncogenesis from comparative genome hybridization data.

Comparative genome hybridization (CGH) is a laboratory method to measure gains and losses of chromosomal regions in tumor cells. It is believed that DNA gains and losses in tumor cells do not occur entirely at random, but partly through some flow of causality. Models that relate tumor progression to the occurrence of DNA gains and losses could be very useful in hunting cancer genes and in cancer diagnosis. We lay some mathematical foundations for inferring a model of tumor progression from a CGH data set. We consider a class of tree models that are more general than a path model that has been developed for colorectal cancer. We derive a tree model inference algorithm based on the idea of a maximum-weight branching in a graph, and we show that under plausible assumptions our algorithm infers the correct tree. We have implemented our methods in software, and we illustrate with a CGH data set for renal cancer.     

Estimating hypermutation rates from clonal tree data

To understand the mechanisms underlying the varying patterns of mutations that occur during immune and autoimmune responses, estimates of the somatic hypermutation rate are critical. However, despite its significance, precise estimates of the mutation rate do not currently exist. Microdissection studies of mutating B cell clones provide an opportunity to measure this rate more accurately than previously possible. Each microdissection provides a number of clonally related sequences that, through the analysis of shared mutations, can be genealogically related to each other. The shape of these clonal trees is influenced by many processes, including the hypermutation rate. We have developed two different methods to estimate the mutation rate based on these data. These methods are applied to two sets of experimental data, one from an autoimmune response and one from the antihapten response to (4-hydroxy-3-nitrophenyl)acetyl (NP). Comparable mutation rates are estimated for both responses, 0.7-0.9 x 10(-3) and 0.9-1.1 x 10(-3) bp(-1) division(-1) for the autoimmune and NP responses, respectively. In addition to comparing the results of the two procedures, we investigate the effect on our estimate of assumptions, such as the fraction of lethal mutations.     

A model for the conquest of a tree by bark beetles

A model for the interaction between attacking bark beetles and a tree is developed and discussed. It is shown that in addition to the more intuitive outcomes where the tree wins or the beetles win, it is also deduced that under certain conditions there may exist a stable coexistence (at least for some period of time) between the beetles and a living tree. Finally, it is demonstrated that the outcome of the tree-beetle interaction often depends on initial conditions such as the number of colonizing beetles.
These results are discussed with reference to empirical findings, as well as to the development of proper population dynamics models for bark beetles in a forest stand, and models developed for assisting forest managers in avoiding bark beetle outbreaks and for minimizing the damage caused by a bark beetle outbreak.     

Classification tree method for bacterial source tracking with antibiotic resistance analysis data

Various statistical classification methods, including discriminant analysis, logistic regression, and cluster analysis, have been used with antibiotic resistance analysis (ARA) data to construct models for bacterial source tracking (BST). We applied the statistical method known as classification trees to build a model for BST for the Anacostia Watershed in Maryland. Classification trees have more flexibility than other statistical classification approaches based on standard statistical methods to accommodate complex interactions among ARA variables. This article describes the use of classification trees for BST and includes discussion of its principal parameters and features. Anacostia Watershed ARA data are used to illustrate the application of classification trees, and we report the BST results for the watershed.     

Stomatal regulation by microclimate and tree water relations: interpreting ecophysiological field data with a hydraulic plant model

Dynamics in microclimate and physiological plant traits were studied for Pubescent oak and Scots pine in a dry inner-alpine valley in Switzerland, at a 10 min resolution for three consecutive years (2001-2003). As expected, stomata tended to close with increasing drought in air and soil. However, stomatal aperture in oak was smaller than in pine under relatively wet conditions, but larger under dry conditions. To explore underlying mechanisms, a model was applied that (i) quantifies water relations within trees from physical principles (mechanistic part) and (ii) assumes that signals from light, stomatal aperture, crown water potential, and tree water deficit in storage pools control stomata (systemic part). The stomata of pine showed a more sensitive response to increasing drought because both factors, the slowly changing tree water deficit and the rapidly changing crown water potential, closed the stomata. By contrast, the stomata of oak became less drought-sensitive as the closing signal of crown water potential was opposed by the opening signal of tree water deficit. Moreover, parameter optimization suggests that oak withdrew more water from the storage pools and reduced leaf water potentials to lower levels, without risking serious damage by cavitation. The new model thus suggests how the hydraulic water flow and storage system determines the responses in stomatal aperture and transpiration to drought at time scales ranging from hours to multiple years, and why pine and oak might differ in such responses. These differences explain why oaks are more efficient competitors during drought periods, although this was not the case in the extremely dry year 2003, which provoked massive leaf loss and, from July onwards, physiological activity almost ceased.     

Peak tree: a new tool for multiscale hierarchical representation and peak detection of mass spectrometry data

Peak detection is one of the most important steps in mass spectrometry (MS) analysis. However, the detection result is greatly affected by severe spectrum variations. Unfortunately, most current peak detection methods are neither flexible enough to revise false detection results nor robust enough to resist spectrum variations. To improve flexibility, we introduce peak tree to represent the peak information in MS spectra. Each tree node is a peak judgment on a range of scales, and each tree decomposition, as a set of nodes, is a candidate peak detection result. To improve robustness, we combine peak detection and common peak alignment into a closed-loop framework, which finds the optimal decomposition via both peak intensity and common peak information. The common peak information is derived and loopily refined from the density clustering of the latest peak detection result. Finally, we present an improved ant colony optimization biomarker selection method to build a whole MS analysis system. Experiment shows that our peak detection method can better resist spectrum variations and provide higher sensitivity and lower false detection rates than conventional methods. The benefits from our peak-tree-based system for MS disease analysis are also proved on real SELDI data.     

Comparative performance of species-richness estimators using data from a subtropical forest tree community

We used survey data collected from a large plot (20 ha) of sub-tropical forest in the Dinghushan Nature Reserve, Guangdong Province, southern China, in 2005 to test the comparative performance of nine species-richness estimators (number of observed species, three species-individual curve models, five nonparametric estimators). As the true species richness, we used the 210 free-standing shrub and tree species of >1 cm diameter at breast height recorded during the survey. This true species richness was then used to calculate performance measures of bias, accuracy, and precision for each estimator, whereby we distinguished performance for low, medium, and high sampling intensity. Unsurprisingly, all estimators performed better than the number of observed species in terms of bias and accuracy. Surprisingly, however, two curve models (logistic and logarithm) outperformed all other estimators in terms of bias, accuracy, and precision, which is in contrast to most other previous studies, in which nonparametric methods usually outperform curve models. Intriguingly, relative estimator performance changed between low, medium, and high sampling intensity, sometimes dramatically, reinforcing the assertion that the influence of sampling intensity on estimator performance is an important aspect to investigate and to consider when choosing estimators for ecological surveys. Because these results are based on only one dataset, the results should be treated with caution, both because (1) the generality of these results needs to be confirmed with simulated datasets and (2) more work is needed to establish what “true” species richness is extrapolated by each of the tested estimators in both the statistical and the practical sense. Nevertheless, the two curve estimators, namely Logistic and Logarithm, should be considered in future studies of comparative performance of species-richness estimators because of their outstanding performance in this study.     

Analysis of qPCR data by converting exponentially related Ct values into linearly related X0 values

A common method for calculating results from qPCR experiments is the comparative Ct method, also called the 2(-ΔΔCt) method. However, several assumptions are included in the 2(-ΔΔCt) method and standard statistical analyses are not directly applicable. Here, we describe a different method, the X(0) method, for result calculations and statistical analysis from qPCR experiments. The X(0) method differs from the 2(-ΔΔCt) method by introducing a conversion of the exponentially related Ct values into linearly related X(0) values, which represent the amount of starting material in a qPCR experiment. Results calculated by the X(0) method are illustrated for qPCR experiments with technical and biological replicates, including procedures to calculate standard deviations. Incorporation of primer efficiencies in calculations by the X(0) method is also described. Altogether, the X(0) method constitutes a very simple and accurate alternative to the 2(-ΔΔCt) method for result calculations from qPCR data.