On the species of origin: diagnosing the source of symbiotic transcripts.

BACKGROUND: Most organisms have developed ways to recognize and interact with other species. Symbiotic interactions range from pathogenic to mutualistic. Some molecular mechanisms of interspecific interaction are well understood, but many remain to be discovered. Expressed sequence tags (ESTs) from cultures of interacting symbionts can help identify transcripts that regulate symbiosis, but present a unique challenge for functional analysis. Given a sequence expressed in an interaction between two symbionts, the challenge is to determine from which organism the transcript originated. For high-throughput sequencing from interaction cultures, a reliable computational approach is needed. Previous investigations into GC nucleotide content and comparative similarity searching provide provisional solutions, but a comparative lexical analysis, which uses a likelihood-ratio test of hexamer counts, is more powerful. RESULTS: Validation with genes whose origin and function are known yielded 94% accuracy. Microbial (non-plant) transcripts comprised 75% of a Phytophthora sojae-infected soybean (Glycine max cv Harasoy) library, contrasted with 15% or less in root tissue libraries of Medicago truncatula from axenic, Phytophthora medicaginis-infected, mycorrhizal, and rhizobacterial treatments. Mycorrhizal libraries contained about 23% microbial transcripts; an axenic plant library contained a similar proportion of putative microbial transcripts. CONCLUSIONS: Comparative lexical analysis offers numerous advantages over alternative approaches. Many of the transcripts isolated from mixed cultures were of unknown function, suggesting specificity to symbiotic metabolism and therefore candidates likely to be interesting for further functional investigation. Future investigations will determine whether the abundance of non-plant transcripts in a pure plant library indicates procedural artifacts, horizontally transferred genes, or other phenomena.

Comparative analysis of expressed sequences in Phytophthora sojae.

Phytophthora sojae (Kaufmann and Gerdemann) is an oomycete that causes stem and root rot on soybean (Glycine max L. Merr) plants. We have constructed three cDNA libraries using mRNA isolated from axenically grown mycelium and zoospores and from tissue isolated from plant hypocotyls 48 h after inoculation with zoospores. A total of 3,035 expressed sequence tags (ESTs) were generated from the three cDNA libraries, representing an estimated 2,189 cDNA transcripts. The ESTs were classified according to putative function based on similarity to known proteins, and were analyzed for redundancy within and among the three source libraries. Distinct expression patterns were observed for each library. By analysis of the percentage G+C content of the ESTs, we estimate that two-thirds of the ESTs from the infected plant library are derived from P. sojae cDNA transcripts. The ESTs originating from this study were also compared with a collection of Phytophthora infestans ESTs and with all other non-human ESTs to assess the similarity of the P. sojae sequences to existing EST data. This collection of cDNA libraries, ESTs, and accompanying annotation will provide a new resource for studies on oomycetes and on soybean responses to pathogen challenge.

Estimating the contributions of selection and self-organization in RNA secondary structure.

In addition to characteristic structural properties imposed by evolutionary modification, evolved, single-stranded RNAs also display characteristic structural properties imposed by intrinsic physical constraints on RNA polymer folding. The balance of intrinsic and functionally selected characters in the folded conformation of evolved secondary structures was determined by comparing the predicted secondary structures of evolved and unevolved (random) RNA sequences. Though evolved conformations are significantly more ordered than conformations of random-sequence RNA, this analysis demonstrates that the majority of conformational order within evolved structures results not from evolutionary optimization but from constraints imposed by rules intrinsic to RNA polymer folding.

Global similarities in nucleotide base composition among disparate functional classes of single-stranded RNA imply adaptive evolutionary convergence.

The number of distinct functional classes of single-stranded RNAs (ssRNAs) and the number of sequences representing them are substantial and continue to increase. Organizing this data in an evolutionary context is essential, yet traditional comparative sequence analyses require that homologous sites can be identified. This prevents comparative analysis between sequences of different functional classes that share no site-to-site sequence similarity. Analysis within a single evolutionary lineage also limits evolutionary inference because shared ancestry confounds properties of molecular structure and function that are historically contingent with those that are imposed for biophysical reasons. Here, we apply a method of comparative analysis to ssRNAs that is not restricted to homologous sequences, and therefore enables comparison between distantly related or unrelated sequences, minimizing the effects of shared ancestry. This method is based on statistical similarities in nucleotide base composition among different functional classes of ssRNAs. In order to denote base composition unambiguously, we have calculated the fraction G+A and G+U content, in addition to the more commonly used fraction G+C content. These three parameters define RNA composition space, which we have visualized using interactive graphics software. We have examined the distribution of nucleotide composition from 15 distinct functional classes of ssRNAs from organisms spanning the universal phylogenetic tree and artificial ribozymes evolved in vitro. Surprisingly, these distributions are biased consistently in G+A and G+U content, both within and between functional classes, regardless of the more variable G+C content. Additionally, an analysis of the base composition of secondary structural elements indicates that paired and unpaired nucleotides, known to have different evolutionary rates, also have significantly different compositional biases. These universal compositional biases observed among ssRNAs sharing little or no sequence similarity suggest, contrary to current understanding, that base composition biases constitute a convergent adaptation among a wide variety of molecular functions.

The ecology of echo.

Echo is a generic ecosystem model in which evolving agents are situated in a resource-limited environment. The Echo model is described, and the behavior of Echo is evaluated on two well-studied measures of ecological diversity: relative species abundance and the species-area scaling relation. In simulation experiments, these measures are used to compare the behavior of Echo with that of a neutral model, in which selection on agent genotypes is random. These simulations show that the evolutionary component of Echo makes a significant contribution to its behavior and that Echo shows good qualitative agreement with naturally occurring species abundance distributions and species-area scaling relations.