Sea urchin Hox genes: insights into the ancestral Hox cluster

We describe the Hox cluster in the radially symmetric sea urchin and compare our findings to what is known from clusters in bilaterally symmetric animals. Several Hox genes from the direct-developing sea urchin Heliocidaris erythrogramma are described. CHEF gel analysis shows that the Hox genes are clustered on a < or = 300 kilobase (kb) fragment of DNA, and only a single cluster is present, as in lower chordates and other nonvertebrate metazoans. Phylogenetic analyses of sea urchin, amphioxus, Drosophila, and selected vertebrate Hox genes confirm that the H. erythrogramma genes, and others previously cloned from other sea urchins, belong to anterior, central, and posterior groups. Despite their radial body plan and lack of cephalization, echinoderms retain at least one of the anterior group Hox genes, an orthologue of Hox3. The structure of the echinoderm Hox cluster suggests that the ancestral deuterostome had a Hox cluster more similar to the current chordate cluster than was expected Sea urchins have at least three Abd-B type genes, suggesting that Abd-B expansion began before the radiation of deuterostomes.      

Pseudomonas aeruginosa diaminopimelate decarboxylase: evolutionary relationship with other amino acid decarboxylases

The lysA gene encodes meso-diaminopimelate (DAP) decarboxylase (E.C.4.1.1.20), the last enzyme of the lysine biosynthetic pathway in bacteria. We have determined the nucleotide sequence of the lysA gene from Pseudomonas aeruginosa. Comparison of the deduced amino acid sequence of the lysA gene product revealed extensive similarity with the sequences of the functionally equivalent enzymes from Escherichia coli and Corynebacterium glutamicum. Even though both P. aeruginosa and E. coli are Gram-negative bacteria, sequence comparisons indicate a greater similarity between enzymes of P. aeruginosa and the Gram- positive bacterium C. glutamicum than between those of P. aeruginosa and E. coli enzymes. Comparison of DAP decarboxylase with protein sequences present in data bases revealed that bacterial DAP decarboxylases are homologous to mouse (Mus musculus) ornithine decarboxylase (E.C.4.1.1.17), the key enzyme in polyamine biosynthesis in mammals. On the other hand, no similarity was detected between DAP decarboxylases and other bacterial amino acid decarboxylases.      

Recognizing the forest for the trees: testing temporal patterns of cladogenesis using a null model of stochastic diversification

Computer simulations are developed and employed to examine the expected temporal distributions of nodes under a null model of stochastic lineage bifurcation and extinction. These Markovian models of phylogenetic process were constructed so as to permit direct comparisons against empirical phylogenetic trees generated from molecular or other information available solely from extant species. For replicate simulated phylads with n extant species, cumulative distribution functions (cdf's) of branching times were calculated, and compared (using the Kolmogorov-Smirnov test statistic D) to those from three published empirical trees. Molecular phylogenies for columbine plants and avian cranes showed statistically significant departures from the null expectations, in directions indicating recent and ancient species' radiations, respectively, whereas a molecular phylogeny for the Drosophila virilis species group showed no apparent historical clustering of branching events. Effects of outgroup choice and phylogenetic frame of reference were investigated for the columbines and found to have a predictable influence on the types of conclusions to be drawn from such analyses. To enable other investigators to statistically test for nonrandomness in temporal cladogenetic pattern in empirical trees generated from data on extant species, we present tables of mean cdf's and associated probabilities under the null model for expected branching times in phylads of varying size. The approaches developed in this report complement and extend those of other recent methods for employing null models to assess the statistical significance of pattern in evolutionary trees.      

Fast Statistical Alignment

We describe a new program for the alignment of multiple biological sequences that is both statistically motivated and fast enough for problem sizes that arise in practice. Our Fast Statistical Alignment program is based on pair hidden Markov models which approximate an insertion/deletion process on a tree and uses a sequence annealing algorithm to combine the posterior probabilities estimated from these models into a multiple alignment. FSA uses its explicit statistical model to produce multiple alignments which are accompanied by estimates of the alignment accuracy and uncertainty for every column and character of the alignment—previously available only with alignment programs which use computationally-expensive Markov Chain Monte Carlo approaches—yet can align thousands of long sequences. Moreover, FSA utilizes an unsupervised query-specific learning procedure for parameter estimation which leads to improved accuracy on benchmark reference alignments in comparison to existing programs. The centroid alignment approach taken by FSA, in combination with its learning procedure, drastically reduces the amount of false-positive alignment on biological data in comparison to that given by other methods. The FSA program and a companion visualization tool for exploring uncertainty in alignments can be used via a web interface at http://orangutan.math.berkeley.edu/fsa/, and the source code is available at http://fsa.sourceforge.net/.