Dataset Information

A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm.

ABSTRACT: BACKGROUND: The process of horizontal gene transfer (HGT) is believed to be widespread in Bacteria and Archaea, but little comparative data is available addressing its occurrence in complete microbial genomes. Collection of high-quality, automated HGT prediction data based on phylogenetic evidence has previously been impractical for large numbers of genomes at once, due to prohibitive computational demands. DarkHorse, a recently described statistical method for discovering phylogenetically atypical genes on a genome-wide basis, provides a means to solve this problem through lineage probability index (LPI) ranking scores. LPI scores inversely reflect phylogenetic distance between a test amino acid sequence and its closest available database matches. Proteins with low LPI scores are good horizontal gene transfer candidates; those with high scores are not. DESCRIPTION: The DarkHorse algorithm has been applied to 955 microbial genome sequences, and the results organized into a web-searchable relational database, called the DarkHorse HGT Candidate Resource http://darkhorse.ucsd.edu. Users can select individual genomes or groups of genomes to screen by LPI score, search for protein functions by descriptive annotation or amino acid sequence similarity, or select proteins with unusual G+C composition in their underlying coding sequences. The search engine reports LPI scores for match partners as well as query sequences, providing the opportunity to explore whether potential HGT donor sequences are phylogenetically typical or atypical within their own genomes. This information can be used to predict whether or not sufficient information is available to build a well-supported phylogenetic tree using the potential donor sequence. CONCLUSION: The DarkHorse HGT Candidate database provides a powerful, flexible set of tools for identifying phylogenetically atypical proteins, allowing researchers to explore both individual HGT events in single genomes, and large-scale HGT patterns among protein families and genome groups. Although the DarkHorse algorithm cannot, by itself, provide definitive proof of horizontal gene transfer, it is a flexible, powerful tool that can be combined with slower, more rigorous methods in situations where these other methods could not otherwise be applied.

SUBMITTER: Podell S

PROVIDER: S-EPMC2573894 | biostudies-other | 2008

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm.

Podell Sheila S Gaasterland Terry T Allen Eric E EE

BMC bioinformatics 20081007

<h4>Background</h4>The process of horizontal gene transfer (HGT) is believed to be widespread in Bacteria and Archaea, but little comparative data is available addressing its occurrence in complete microbial genomes. Collection of high-quality, automated HGT prediction data based on phylogenetic evidence has previously been impractical for large numbers of genomes at once, due to prohibitive computational demands. DarkHorse, a recently described statistical method for discovering phylogeneticall ...[more]

PMID: 18840280

Similar Datasets

Project description:BackgroundIn Archaea, previous studies have revealed the presence of multiple intron-containing tRNAs and split tRNAs. The full unexpurgated analysis of archaeal tRNA genes remains a challenging task in the field of bioinformatics, because of the presence of various types of hidden tRNA genes in archaea. Here, we suggested a computational method that searched for widely separated genes encoding tRNA halves to generate suppressive variants of missing tRNAs.ObjectivesThe exploration of tRNA genes from a genome with varying hypotheses, among all three domain of life (eukaryotes, bacteria and archaea), has been rapidly identified in different ways in the field of bioinformatics. Like eukaryotic tRNA genes, it has been established that two separated regions of the coding sequence of a tRNA gene are essential and sufficient for promotion of transcription. Our objective is to find out the two essential regions in the genome sequence which comprises two halves of the hidden tRNAs.Material and methodsConsidering the existence of split tRNA genes widely separated throughout the genome, we developed our tRNA search algorithm to predict such separated tRNA genes by searching both a conserved terminal 5'- and 3'-motif of tRNA in agreement with the split hypothesis on the basis of cloverleaf prediction and precise insilico determination of bulge-helix-bulge secondary structure at the splice sites.ResultsBy a comprehensive search for all kinds of missing tRNA genes, we have constructed hybrid tRNA genes containing one essential region from tDNA (XYZ) and the other from tDNA (ABC), both from same species in the archaea. We have also found, this type of hybrid tRNA genes are identified in the different species of the archaea (XYZ ASN, ARG and MET; ABC ASP,SER, ARG and PRO).These hybrid split tRNA share a common structural motif called bulge-helix-bulge (BHB) a more relaxed bulge-helix loop (BHL), at the leader exon boundary and suggested to be evolutionary interrelated.ConclusionsAnalysis of the complete genome sequences of Metallosphaera sedula DSM 5348, Desulfurococcus kamchatkensis 1221n and Ignicoccus hospitalis KIN4/I in archaea by our algorithm revealed that a number of hybrid tRNAs are constructed from different tDNAs . Asymmetric combination of 5' and 3' tRNA halves may have generated the diversity of tRNA molecules. Our study of hybrid tRNA genes will provide a new molecular basis for upcoming tRNA studies.

Project description:Sponge-associated prokaryotic diversity has been studied from a wide range of marine environments across the globe. However, for certain regions, e.g., Vietnam, Thailand, Cambodia, and Singapore, an overview of the sponge-associated prokaryotic communities is still pending. In this study we characterized the prokaryotic communities from 27 specimens, comprising 18 marine sponge species, sampled from the central coastal region of Vietnam. Illumina MiSeq sequencing of 16S ribosomal RNA (rRNA) gene fragments was used to investigate sponge-associated bacterial and archaeal diversity. Overall, 14 bacterial phyla and one archaeal phylum were identified among all 27 samples. The phylum Proteobacteria was present in all sponges and the most prevalent phylum in 15 out of 18 sponge species, albeit with pronounced differences at the class level. In contrast, Chloroflexi was the most abundant phylum in Halichondria sp., whereas Spirastrella sp. and Dactylospongia sp. were dominated by Actinobacteria. Several bacterial phyla such as Acidobacteria, Actinobacteria, Bacteroidetes, Chloroflexi, Deferribacteres, Gemmatimonadetes, and Nitrospirae were found in two-thirds of the sponge species. Moreover, the phylum Thaumarchaeota (Archaea), which is known to comprise nitrifying archaea, was highly abundant among the majority of the 18 investigated sponge species. Altogether, this study demonstrates that the diversity of prokaryotic communities associated with Vietnamese sponges is comparable to sponge-prokaryotic assemblages from well-documented regions. Furthermore, the phylogenetically divergent sponges hosted species-specific prokaryotic communities, thus demonstrating the influence of host identity on the composition and diversity of the associated communities. Therefore, this high-throughput 16S rRNA gene amplicon analysis of Vietnamese sponge-prokaryotic communities provides a foundation for future studies on sponge symbiont function and sponge-derived bioactive compounds from this region.

Dataset Information

A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm.

Publications

A database of phylogenetically atypical genes in archaeal and bacterial genomes, identified using the DarkHorse algorithm.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets