Statistical properties of the ordinary least-squares,generalized least-squares,and minimum-evolution methods of phylogenetic inference

Summary Statistical properties of the ordinary least-squares (OLS), generalized least-squares (GLS), and minimum-evolution (ME) methods of phylogenetic inference were studied by considering the case of four DNA sequences. Analytical study has shown that all three methods are statistically consistent in the sense that as the number of nucleotides examined (m) increases they tend to choose the true tree as long as the evolutionary distances used are unbiased. When evolutionary distances (d_ij's) are large and sequences under study are not very long, however, the OLS criterion is often biased and may choose an incorrect tree more often than expected under random choice. It is also shown that the variance-covariance matrix of d_ij's becomes singular as d_ij's approach zero and thus the GLS may not be applicable when d_ij's are small. The ME method suffers from neither of these problems, and the ME criterion is statistically unbiased. Computer simulation has shown that the ME method is more efficient in obtaining the true tree than the OLS and GLS methods and that the OLS is more efficient than the GLS when d_ij's are small, but otherwise the GLS is more efficient.Offprint requests to: M. Nei     

Assembly of Helicobacter pylori Initiation Complex Is Determined by Sequence-Specific and Topology-Sensitive DnaA–oriC Interactions

In bacteria, chromosome replication is initiated by binding of the DnaA initiator protein to DnaA boxes located in the origin of chromosomal replication (oriC). This leads to DNA helix opening within the DNA-unwinding element. Helicobacter pylori oriC, the first bipartite origin identified in Gram-negative bacteria, contains two subregions, oriC1 and oriC2, flanking the dnaA gene. The DNA-unwinding element region is localized in the oriC2 subregion downstream of dnaA. Surprisingly, oriC2–DnaA interactions were shown to depend on DNA topology, which is unusual in bacteria but is similar to initiator–origin interactions observed in higher organisms. In this work, we identified three DnaA boxes in the oriC2 subregion, two of which were bound only as supercoiled DNA. We found that all three DnaA boxes play important roles in orisome assembly and subsequent DNA unwinding, but different functions can be assigned to individual boxes. This suggests that the H. pylori oriC may be functionally divided, similar to what was described recently for Escherichia coli oriC. On the basis of these results, we propose a model of initiation complex formation in H. pylori.     

Xenopus ElrB, but not ElrA, binds RNA as an oligomer: possible role of the linker

We have shown that ElrA and ElrB, Xenopus ELAV homologues, bind the Vg1 mRNA 3'UTR translation element in Xenopus oocytes and implicated ElrB in mediating translational repression during oogenesis. Here we report that, while ElrA and ElrB are 69% identical and both exhibit RNA binding in the nM range, recombinant ElrB, but not ElrA, is able to oligomerise. This oligomerisation is also seen with the endogenous protein. Both RNA binding and oligomerisation require the linker region flanked with two RNA recognition motifs. Our data demonstrate a novel and unique property of ElrB which may be important for its function as a translational regulator.     

Modeling inspiratory and expiratory steady-state velocity fields in the Sprague-Dawley rat nasal cavity

Distribution patterns of odorant molecules in the rat nasal olfactory region depend in large part on the detailed airflow patterns in the nasal cavity, which in turn depend on the anatomical structure. To investigate these flow patterns, we constructed an anatomically accurate finite element model of the right nasal cavity of the Sprague-Dawley rat based on horizontal (anterior-posterior) nasal cast cross sections. By numerically solving the fluid mechanical momentum and continuity equations using the finite element method, we studied the flow distribution and the complete velocity field for both inspiration and expiration throughout the nasal cavity under physiological flow rates of resting breathing and sniffing. Detailed velocity profiles, volumetric flow distributions, and streamline patterns for quasi-steady airflow are presented. S-shaped streamlines passing through the olfactory region are found to be less prevalent during expiratory than inspiratory flow leading to trapping and an increase in odorant molecule retention in the olfactory region during sniffing. The rat nasal velocity calculations will be used to study the distribution of odorant uptake onto the rat olfactory mucosa and compare it with the known anatomic location of some types of rat olfactory receptors.     

GSTaxClassifier: a genomic signature based taxonomic classifier for metagenomic data analysis

GSTaxClassifier (Genomic Signature based Taxonomic Classifier) is a program for metagenomics analysis of shotgun DNA sequences. The program includes

1. a simple but effective algorithm, a modification of the Bayesian method, to predict the most probable genomic origins of sequences at different taxonomical ranks, on the basis of genome databases;
2. a function to generate genomic profiles of reference sequences with tri-, tetra-, penta-, and hexa-nucleotide motifs for setting a user-defined database;
3. two different formats (tabular- and tree-based summaries) to display taxonomic predictions with improved analytical methods; and
4. effective ways to retrieve, search, and summarize results by integrating the predictions into the NCBI tree-based taxonomic information.

GSTaxClassifier takes input nucleotide sequences and using a modified Bayesian model evaluates the genomic signatures between metagenomic query sequences and reference genome databases. The simulation studies of a numerical data sets showed that GSTaxClassifier could serve as a useful program for metagenomics studies, which is freely available at http://helix2.biotech.ufl.edu:26878/metagenomics/.