GO4genome: a prokaryotic phylogeny based on genome organization

Conserved genomic neighborhood is a strong but no perfect indicator for a direct interaction of microbial gene products

BACKGROUND

The order of genes in bacterial genomes is not random; for example, the products of genes belonging to an operon work together in the same pathway. The cotranslational assembly of protein complexes is deemed to conserve genomic neighborhoods even stronger than a common function. This is why a conserved genomic neighborhood can be utilized to predict, whether gene products form protein complexes.

RESULTS

We were interested to assess the performance of a neighborhood-based classifier that analyzes a large number of genomes. Thus, we determined for the genes encoding the subunits of 494 experimentally verified hetero-dimers their local genomic context. In order to generate phylogenetically comprehensive genomic neighborhoods, we utilized the tools offered by the Enzyme Function Initiative. For each subunit, a sequence similarity network was generated and the corresponding genome neighborhood network was analyzed to deduce the most frequent gene product. This was predicted as interaction partner, if its abundance exceeded a threshold, which was the frequency giving rise to the maximal Matthews correlation coefficient. For the threshold of 16%, the true positive rate was 45%, the false positive rate 0.06%, and the precision 55%. For approximately 20% of the subunits, the interaction partner was not found in a neighborhood of ± 10 genes.

CONCLUSIONS

Our phylogenetically comprehensive analysis confirmed that complex formation is a strong evolutionary factor that conserves genome neighborhoods. On the other hand, for 55% of the cases analyzed here, classification failed. Either, the interaction partner was not present in a ± 10 gene window or was not the most frequent gene product.

Species-specificity of DNA trimer densities in chromosomes and their use in the classification of closely related organisms

16S rDNA sequences are conventionally used for classification of organisms. However, the use of these sequences is sometimes not successful, especially for closely related species. For better classification of these organisms, several methods that are genome sequence-based have been developed. Sequence alignment-based methods are tedious and time-consuming, as they need conserved coding sequences to be identified and deduced prior to sequence alignment. Likewise, method that relies on gene function needs genes to be assessed for function similarity. Other alignment-free methods, which are based on particular genome sequence properties, so far have been complex and not species-specific enough for classification of organisms below genus level. The present study found that the ratios of DNA trimer frequencies to chromosomal length were species-specific. Density of a trimer in a chromosomal sequence was defined as the average frequency of the trimer per 1 kbp. The species-specificity of trimer densities in chromosomes of many closely related bacteria was compared in parallel with 16S rDNA sequences in these same bacteria. The results of these comparisons indicate that trimer densities in chromosomes can be used to simply and efficiently classify the organisms below genus level.

FunSimMat update: new features for exploring functional similarity

Quantifying the functional similarity of genes and their products based on Gene Ontology annotation is an important tool for diverse applications like the analysis of gene expression data, the prediction and validation of protein functions and interactions, and the prioritization of disease genes. The Functional Similarity Matrix (FunSimMat, http://www.funsimmat.de) is a comprehensive database providing various precomputed functional similarity values for proteins in UniProtKB and for protein families in Pfam and SMART. With this update, we significantly increase the coverage of FunSimMat by adding data from the Gene Ontology Annotation project as well as new functional similarity measures. The applicability of the database is greatly extended by the implementation of a new Gene Ontology-based method for disease gene prioritization. Two new visualization tools allow an interactive analysis of the functional relationships between proteins or protein families. This is enhanced further by the introduction of an automatically derived hierarchy of annotation classes. Additional changes include a revised user front-end and a new RESTlike interface for improving the user-friendliness and online accessibility of FunSimMat.

Horizontal gene transfer in evolution: facts and challenges

The contribution of horizontal gene transfer to evolution has been controversial since it was suggested to be a force driving evolution in the microbial world. In this paper, I review the current standpoint on horizontal gene transfer in evolutionary thinking and discuss how important horizontal gene transfer is in evolution in the broad sense, and particularly in prokaryotic evolution. I review recent literature, asking, first, which processes are involved in the evolutionary success of transferred genes and, secondly, about the extent of horizontal gene transfer towards different evolutionary times. Moreover, I discuss the feasibility of reconstructing ancient phylogenetic relationships in the face of horizontal gene transfer. Finally, I discuss how horizontal gene transfer fits in the current neo-Darwinian evolutionary paradigm and conclude there is a need for a new evolutionary paradigm that includes horizontal gene transfer as well as other mechanisms in the explanation of evolution.