Predicting demographic group structures based on DNA sequence data

The ability to infer relationships between groups of sequences, either by searching for their evolutionary history or by comparing their sequence similarity, can be a crucial step in hypothesis testing. Interpreting relationships of human immunodeficiency virus type 1 (HIV-1) sequences can be challenging because of their rapidly evolving genomes, but it may also lead to a better understanding of the underlying biology. Several studies have focused on the evolution of HIV-1, but there is little information to link sequence similarities and evolutionary histories of HIV-1 to the epidemiological information of the infected individual. Our goal was to correlate patterns of HIV-1 genetic diversity with epidemiological information, including risk and demographic factors. These correlations were then used to predict epidemiological information through analyzing short stretches of HIV-1 sequence. Using standard phylogenetic and phenetic techniques on 100 HIV-1 subtype B sequences, we were able to show some correlation between the viral sequences and the geographic area of infection and the risk of men who engage in sex with men. To help identify more subtle relationships between the viral sequences, the method of multidimensional scaling (MDS) was performed. That method identified statistically significant correlations between the viral sequences and the risk factors of men who engage in sex with men and individuals who engage in sex with injection drug users or use injection drugs themselves. Using tree construction, MDS, and newly developed likelihood assignment methods on the original 100 samples we sequenced, and also on a set of blinded samples, we were able to predict demographic/risk group membership at a rate statistically better than by chance alone. Such methods may make it possible to identify viral variants belonging to specific demographic groups by examining only a small portion of the HIV-1 genome. Such predictions of demographic epidemiology based on sequence information may become valuable in assigning different treatment regimens to infected individuals.     

Bayes or bootstrap? A simulation study comparing the performance of Bayesian Markov chain Monte Carlo sampling and bootstrapping in assessing phylogenetic confidence

Bayesian Markov chain Monte Carlo sampling has become increasingly popular in phylogenetics as a method for both estimating the maximum likelihood topology and for assessing nodal confidence. Despite the growing use of posterior probabilities, the relationship between the Bayesian measure of confidence and the most commonly used confidence measure in phylogenetics, the nonparametric bootstrap proportion, is poorly understood. We used computer simulation to investigate the behavior of three phylogenetic confidence methods: Bayesian posterior probabilities calculated via Markov chain Monte Carlo sampling (BMCMC-PP), maximum likelihood bootstrap proportion (ML-BP), and maximum parsimony bootstrap proportion (MP-BP). We simulated the evolution of DNA sequence on 17-taxon topologies under 18 evolutionary scenarios and examined the performance of these methods in assigning confidence to correct monophyletic and incorrect monophyletic groups, and we examined the effects of increasing character number on support value. BMCMC-PP and ML-BP were often strongly correlated with one another but could provide substantially different estimates of support on short internodes. In contrast, BMCMC-PP correlated poorly with MP-BP across most of the simulation conditions that we examined. For a given threshold value, more correct monophyletic groups were supported by BMCMC-PP than by either ML-BP or MP-BP. When threshold values were chosen that fixed the rate of accepting incorrect monophyletic relationship as true at 5%, all three methods recovered most of the correct relationships on the simulated topologies, although BMCMC-PP and ML-BP performed better than MP-BP. BMCMC-PP was usually a less biased predictor of phylogenetic accuracy than either bootstrapping method. BMCMC-PP provided high support values for correct topological bipartitions with fewer characters than was needed for nonparametric bootstrap.     

Root distribution of a Mediterranean shrubland in Portugal

The distribution of roots of an Erica (Erica scoparia and Erica lusitanica) dominated Mediterranean maquis was studied using three different approaches: root counts on trench walls (down to 120 cm), estimation of the maximum rooting depth using an allometric relationship and estimation of fine root biomass and fine root length using soil cores (down to 100 cm). Roots were classified according to diameter (fine, 1.0 mm; small, 1.1–5.0 mm; medium, 5.1–10.0 mm; coarse, >10.0 mm) and species (Erica sp., Pteridium aquilinum, Rubus ulmifolius and Ulex jussiaei). The depth corresponding to 50% of all roots (D ₅₀) was determined by fitting a new model to the cumulative root distribution. Fine roots represented 96% of root counts. Root counts of Erica represented 59%, Ulex 34%, Rubus 6% and Pteridium 1%. Overall root counts showed a D ₅₀ of 26 cm. D ₅₀ was higher for Ulex (40 cm) and Erica (22 cm), than for Pteridium (9 cm) and Rubus (3 cm). D ₅₀ for fine roots was 27 cm, for small roots 11 cm, for medium roots 6 cm and for coarse roots 4 cm. The estimated average maximum rooting depth of the 28 deepest Erica roots was 222 cm. The deepest Erica root was estimated to reach 329 cm. A total of 82% of roots growing deeper than 125 cm were not reaching more than 175 cm. The overall fine root length density ranged from 4.6 cm/cm³ at 10 cm to 0.8 cm/cm³ at 80 cm. The overall fine root biomass ranged from 7.7 mg/cm³ at 10 cm to 0.6 mg/cm³ at 40 cm. D ₅₀ for root biomass was 12 cm and D ₅₀ for root length was 14 cm. Fine root biomass was estimated as 1.6 kg/m² and the respective root length as 18.7 km/m².     

A technique for estimating maximum harvesting effort in a stochastic fishery model

Exploitation of biological resources and the harvest of population species are commonly practiced in fisheries, forestry and wild life management. Estimation of maximum harvesting effort has a great impact on the economics of fisheries and other bio-resources. The present paper deals with the problem of a bioeconomic fishery model under environmental variability. A technique for finding the maximum harvesting effort in fluctuating environment has been developed in a two-species competitive system, which shows that under realistic environmental variability the maximum harvesting effort is less than what is estimated in the deterministic model. This method also enables us to find out the safe regions in the parametric space for which the chance of extinction of the species is minimized. A real life fishery problem has been considered to obtain the inaccessible parameters of the system in a systematic way. Such studies may help resource managers to get an idea for controlling the system.     

Optimizing resolution in multidimensional NMR by three-way decomposition

Resolution depends on the number of points sampled in a FID; in indirectly detected dimensions it is an important determinant of the total experiment time. Based on the high redundancy present in NMR data, we propose the following timesaving scheme for three-dimensional spectra. An extensive grid of discrete t1- and t2-values is used, which increases resolution while preserving the spectral width. Total experiment time is reduced by avoiding the recording of t3-FIDs for selected pairs of t1 and t2; typically the recording is omitted for about 75% of the (t1,t2) combinations. These data sets are referred to as sparse, and post-experimental processing making optimal use of spectral redundancy provides the missing, non-recorded data. We have previously shown that three-way decomposition (TWD) within the MUNIN approach provides a practical way to process dense NMR data sets. Here, a novel TWD algorithm [Ibraghimov, (2002) Numer. Linear Algebra Appl. 9, 551–565] is used to complement a sparselyrecorded time-domain data set by providing the missing FIDs for all (t1,t2) combinations omitted in the experiment. A necessary condition is that for each t1-value at least a few FIDs are recorded, and similar for each t2-value. The method is demonstrated on non-uniformly sampled ¹⁵N-NOESY-HSQC data sets recorded for the 14 kD protein azurin. The spectra obtained by TWD, reconstruction and ordinary transform to frequency-domain are, in spite of the large number of signals and the high dynamic range typical for NOESYs, highly similar to a corresponding reference spectrum, for which all (t1,t2) combinations were recorded.     

Statistical methods for detecting molecular adaptation

The past few years have seen the development of powerful statistical methods for detecting adaptive molecular evolution. These methods compare synonymous and nonsynonymous substitution rates in protein-coding genes, and regard a nonsynonymous rate elevated above the synonymous rate as evidence for darwinian selection. Numerous cases of molecular adaptation are being identified in various systems from viruses to humans. Although previous analyses averaging rates over sites and time have little power, recent methods designed to detect positive selection at individual sites and lineages have been successful. Here, we summarize recent statistical methods for detecting molecular adaptation, and discuss their limitations and possible improvements.     

A retrospective assessment of the accuracy of the paternity inference program CERVUS

CERVUS is a Windows-based software package written to infer paternity in natural populations. It offers advantages over exclusionary-based methods of paternity inference in that multiple nonexcluded males can be statistically distinguished, laboratory typing error is considered and statistical confidence is determined for assigned paternities through simulation. In this study we use a panel of 84 microsatellite markers to retrospectively determine the accuracy of statistical confidence when CERVUS was used to infer paternity in a population of red deer (Cervus elaphus). The actual confidence of CERVUS-assigned paternities was not significantly different from that predicted by simulation.     

Phylogenetic analyses of mode of larval development

Phylogenies based on morphological or molecular characters have been used to provide an evolutionary context for analysis of larval evolution. Studies of gastropods, bivalves, tunicates, sea stars, sea urchins, and polychaetes have revealed massive parallel evolution of similar larval forms. Some of these studies were designed to test, and have rejected, the species selection hypothesis for evolutionary trends in the frequency of derived larvae or life history traits. However, the lack of well supported models of larval character evolution leave some doubt about the quality of inferences of larval evolution from phylogenies of living taxa. Better models based on maximum likelihood methods and known prior probabilities of larval character state changes will improve our understanding of the history of larval evolution.     

The Biology of the Nurse Shark,Ginglymostoma cirratum,Off the Florida East Coast and the Bahama Islands

The nurse shark is an extremely abundant shallow water species in Florida and the Caribbean, yet its biology is poorly known. Moreover, there is a great deal of misinformation about it in the literature. The maximum size and weight attained by the nurse shark have often been exaggerated. None of the specimens measured in this study exceeded 265cm TL and 114.5kg, and none of the specimens actually measured by other researchers exceeded 280cm. Females reach maturity at a length of 223–231cm, or at 86% of their maximum size. Males reach maturity between 214 and 214.6cm in length or at about 83% of their maximum size. Mating primarily occurs from mid-June to early July. The embryos are enclosed in sturdy egg capsules for the first 12–14 weeks of gestation. In a gravid female, the embryos are at different stages of development during the first four months of gestation. Embryos are lecithotrophic and there is no evidence of any supplemental mode of embryonic nourishment. Embryos measure 28–30.5cm at birth. The gestation period is estimated at about five to six months. Brood sizes are large, ranging from 21 to 50 young, with a median of 34 young. The reproductive cycle of the nurse shark consists of a five to six-month gestation period and a two-year ovarian cycle. Thus, the reproductive cycle is biennial and a female produces a brood every two years. The nurse shark is an opportunistic predator that consumes a wide range of small fishes, primarily grunts (Haemulidae).     

Likelihood analysis of ongoing gene flow and historical association

Abstract.— We develop a Monte Carlo-based likelihood method for estimating migration rates and population divergence times from data at unlinked loci at which mutation rates are sufficiently low that, in the recent past, the effects of mutation can be ignored. The method is applicable to restriction fragment length polymorphisms (RFLPs) and single nucleotide polymorphisms (SNPs) sampled from a subdivided population. The method produces joint maximum-likelihood estimates of the migration rate and the time of population divergence, both scaled by population size, and provides a framework in which to test either for no ongoing gene flow or for population divergence in the distant past. We show the method performs well and provides reasonably accurate estimates of parameters even when the assumptions under which those estimates are obtained are not completely satisfied. Furthermore, we show that, provided that the number of polymorphic loci is sufficiently large, there is some power to distinguish between ongoing gene flow and historical association as causes of genetic similarity between pairs of populations.