Evolutionary relationships of eukaryotic kingdoms

The evolutionary relationships of four eukaryotic kingdoms—Animalia, Plantae, Fungi, and Protista—remain unclear. In particular, statistical support for the closeness of animals to fungi rather than to plants is lacking, and a preferred branching order of these and other eukaryotic lineages is still controversial even though molecular sequences from diverse eukaryotic taxa have been analyzed. We report a statistical analysis of 214 sequences of nuclear small-subunit ribosomal RNA (srRNA) gene undertaken to clarify these evolutionary relationships. We have considered the variability of substitution rates and the nonindependence of nucleotide substitution across sites in the srRNA gene in testing alternative hypotheses regarding the branching patterns of eukaryote phylogeny. We find that the rates of evolution among sites in the srRNA sequences vary substantially and are approximately gamma distributed with size and shape parameter equal to 0.76. Our results suggest that (1) the animals and true fungi are indeed closer to each other than to any other crown group in the eukaryote tree, (2) red algae are the closest relatives of animals, true fungi, and green plants, and (3) the heterokonts and alveolates probably evolved prior to the divergence of red algae and animal-fungus-green-plant lineages. Furthermore, our analyses indicate that the branching order of the eukaryotic lineages that diverged prior to the evolution of alveolates may be generally difficult to resolve with the srRNA sequence data.     

Integrated Genetic Map of Anopheles Gambiae: Use of Rapd Polymorphisms for Genetic, Cytogenetic and Sts Landmarks

Randomly amplified polymorphic DNA (RAPD) markers have been integrated in the genetic and cytogenetic maps of the malaria vector mosquito, Anopheles gambiae. Fifteen of these markers were mapped by recombination, relative to microsatellite markers that had been mapped previously. Thirty-four gel-purified RAPD bands were cloned and sequenced, generating sequence tagged sites (STSs) that can be used as entry points to the A. gambiae genome. Thirty one of these STSs were localized on nurse cell polytene chromosomes through their unique hybridization signal in in situ hybridization experiments. Five STSs map close to the breakpoints of polymorphic inversions, which are notable features of the Anopheles genome. The usefulness and limitations of this integrated mosquito map are discussed.     

A model for cell type-specific differential gene expression during heterocyst development and the constitution of aerobic nitrogen fixation ability inAnabaena sp. strain PCC 7120

When deprived of combined nitrogen, aerobically-grown filaments ofAnabaena sp. strain PCC7120 differentiate specialized cells called the heterocysts. The differentiation process is an elaborate and well orchestrated programme involving sensing of environmental and developmental signals, commitment of cells to development, gene rearrangements, intricate DNA-protein interactions, and differential expression of several genes. It culminates in a physiological division of labour between heterocysts, which become the sole sites of aerobic nitrogen fixation, and vegetative cells, that provide photosynthate to the heterocysts in return for nitrogen supplies. We propose a model, to describe the chronology of the important events and to explain how cell type-specific differential gene expression is facilitated by DNA-protein interactions leading to the development of heterocysts and constitution of nitrogen-fixing apparatus inAnabaena.     

Modeling of nitrogen transformations and translocations

Different submodels within complex model packages on N regimes-for plant N-uptake, net N-mineralization, nitrate leaching and microbial N immobilization-are critically reviewed mainly with regard to their prediction ability on the basis of three comparative papers. Only for some of the processes adequate statistical evaluation of the models was possible. Compared to the other statistically evaluable process, nitrate leaching, modeling of plant N-uptake yields the better results. Most models for mineralization use arbitrary approaches rather than empirical ones. Although only approximate estimates of N mineralisation were at hand, the models generally behave expectedly poor. Only one model-DAISY-out of 16 involved in the comparison uses an explicit microbial biomass sub-model including microbial growth, decline and maintenance terms. So DAISY is the only model coupling C and N cycles. But what is true for an individual model describing the C and N transformation of a lab incubation experiment seems to be valid for most of the complex simulation work on the C and N regimes: this model was said to be overparameterized with respect to the available data.     

A 43 kDa DNA binding protein from the pea chloroplast interacts with and stimulates the cognate DNA polymerase.

A DNA binding protein with DNA polymerase 'accessory activity' has been identified and purified to apparent homogeneity from pea chloroplasts. This protein consists of a single subunit of 43 kDa and binds to DNA regardless of its base sequence and topology. It increases cognate DNA polymerase-primase activity in a dose dependent manner. Using solid phase protein-protein interaction trapping and co-immunoprecipitation techniques, the purified protein was found to associate with the chloroplast DNA polymerase. The chloroplast DNA polymerase also binds directly to the radioiodinated 43 kDa protein. The specific interaction between 43 kDa protein and chloroplast DNA polymerase results in the synthesis of longer DNA chains. The 43 kDa protein, present abundantly in the pea chloroplast, appears to increase processivity of the chloroplast DNA polymerase and may play an important role in the replication of pea chloroplast DNA.     

Patterns of Nucleotide Substitution in Mitochondrial Protein Coding Genes of Vertebrates

Maximum likelihood methods were used to study the differences in substitution rates among the four nucleotides and among different nucleotide sites in mitochondrial protein-coding genes of vertebrates. In the 1st+2nd codon position data, the frequency of nucleotide G is negatively correlated with evolutionary rates of genes, substitution rates vary substantially among sites, and the transition/transversion rate bias (R) is two to five times larger than that expected at random. Generally, largest transition biases and greatest differences in substitution rates among sites are found in the highly conserved genes. The 3rd positions in placental mammal genes exhibit strong nucleotide composition biases and the transitional rates exceed transversional rates by one to two orders of magnitude. Tamura-Nei and Hasegawa-Kishino-Yano models with gamma distributed variable rates among sites (gamma parameter, α) adequately describe the nucleotide substitution process in 1st+2nd position data. In these data, ignoring differences in substitution rates among sites leads to largest biases while estimating substitution rates. Kimura's two-parameter model with variable-rates among sites performs satisfactorily in likelihood estimation of R, α, and overall amount of evolution for 1st+2nd position data. It can also be used to estimate pairwise distances with appropriate values of α for a majority of genes.     

A stepwise algorithm for finding minimum evolution trees

A stepwise algorithm for reconstructing minimum evolution (ME) trees from evolutionary distance data is proposed. In each step, a taxon that potentially has a neighbor (another taxon connected to it with a single interior node) is first chosen and then its true neighbor searched iteratively. For m taxa, at most (m-1)!/2 trees are examined and the tree with the minimum sum of branch lengths (S) is chosen as the final tree. This algorithm provides simple strategies for restricting the tree space searched and allows us to implement efficient ways of dynamically computing the ordinary least squares estimates of S for the topologies examined. Using computer simulation, we found that the efficiency of the ME method in recovering the correct tree is similar to that of the neighbor-joining method (Saitou and Nei 1987). A more exhaustive search is unlikely to improve the efficiency of the ME method in finding the correct tree because the correct tree is almost always included in the tree space searched with this stepwise algorithm. The new algorithm finds trees for which S values may not be significantly different from that of the ME tree if the correct tree contains very small interior branches or if the pairwise distance estimates have large sampling errors. These topologies form a set of plausible alternatives to the ME tree and can be compared with each other using statistical tests based on the minimum evolution principle. The new algorithm makes it possible to use the ME method for large data sets.      

Approximate methods for estimating the pattern of nucleotide substitution and the variation of substitution rates among sites

We propose two approximate methods (one based on parsimony and one on pairwise sequence comparison) for estimating the pattern of nucleotide substitution and a parsimony-based method for estimating the gamma parameter for variable substitution rates among sites. The matrix of substitution rates that represents the substitution pattern can be recovered through its relationship with the observable matrix of site pattern frequences in pairwise sequence comparisons. In the parsimony approach, the ancestral sequences reconstructed by the parsimony algorithm were used, and the two sequences compared are those at the ends of a branch in the phylogenetic tree. The method for estimating the gamma parameter was based on a reinterpretation of the numbers of changes at sites inferred by parsimony. Three data sets were analyzed to examine the utility of the approximate methods compared with the more reliable likelihood methods. The new methods for estimating the substitution pattern were found to produce estimates quite similar to those obtained from the likelihood analyses. The new method for estimating the gamma parameter was effective in reducing the bias in conventional parsimony estimates, although it also overestimated the parameter. The approximate methods are computationally very fast and appear useful for analyzing large data sets, for which use of the likelihood method requires excessive computation.