Dataset Information

Simultaneous Bayesian gene tree reconstruction and reconciliation analysis.

ABSTRACT: We present GSR, a probabilistic model integrating gene duplication, sequence evolution, and a relaxed molecular clock for substitution rates, that enables genomewide analysis of gene families. The gene duplication and loss process is a major cause for incongruence between gene and species tree, and deterministic methods have been developed to explain such differences through tree reconciliations. Although probabilistic methods for phylogenetic inference have been around for decades, probabilistic reconciliation methods are far less established. Based on our model, we have implemented a Bayesian analysis tool, PrIME-GSR, for gene tree inference that takes a known species tree into account. Our implementation is sound and we demonstrate its utility for genomewide gene-family analysis by applying it to recently presented yeast data. We validate PrIME-GSR by comparing with previous analyses of these data that take advantage of gene order information. In a case study we apply our method to the ADH gene family and are able to draw biologically relevant conclusions concerning gene duplications creating key yeast phenotypes. On a higher level this shows the biological relevance of our method. The obtained results demonstrate the value of a relaxed molecular clock. Our good performance will extend to species where gene order conservation is insufficient.

SUBMITTER: Akerborg O

PROVIDER: S-EPMC2667006 | biostudies-literature | 2009 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Simultaneous Bayesian gene tree reconstruction and reconciliation analysis.

Akerborg Orjan O Sennblad Bengt B Arvestad Lars L Lagergren Jens J

Proceedings of the National Academy of Sciences of the United States of America 20090319 14

We present GSR, a probabilistic model integrating gene duplication, sequence evolution, and a relaxed molecular clock for substitution rates, that enables genomewide analysis of gene families. The gene duplication and loss process is a major cause for incongruence between gene and species tree, and deterministic methods have been developed to explain such differences through tree reconciliations. Although probabilistic methods for phylogenetic inference have been around for decades, probabilisti ...[more]

PMID: 19299507

Similar Datasets

Project description:We introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of Bacillus subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs, and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, we reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches, and small regulatory RNAs. Overall, regulatory information is included in the model for ?2500 of the ?4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same "ON" and "OFF" gene expression profiles across multiple samples of experimental data. We show how ARs for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how ARs can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology.

Project description:The rooting of phylogenetic trees permits important inferences about ancestral states and the polarity of evolutionary events. Recently, methods that reconcile discordance between gene-trees and species-trees-tree reconciliation methods-are becoming increasingly popular for rooting species trees. Rooting via reconciliation requires values for a particular parameter, the gene transfer to gene duplication ratio (T:D), which in current practice is estimated on the fly from discordances observed in the trees. To date, the accuracy of T:D estimates obtained by reconciliation analyses has not been compared to T:D estimates obtained by independent means, hence the effect of T:D upon inferences of species tree roots is altogether unexplored. Here we investigated the issue in detail by performing tree reconciliations of more than 10,000 gene trees under a variety of T:D ratios for two phylogenetic cases: a bacterial (prokaryotic) tree with 265 species and a fungal-metazoan (eukaryotic) tree with 31 species. We show that the T:D ratios automatically estimated by a current tree reconciliation method, ALE, generate virtually identical T:D ratios across bacterial genes and fungal-metazoan genes. The T:D ratios estimated by ALE differ 10- to 100-fold from robust, ALE-independent estimates from real data. More important is our finding that the root inferences using ALE in both datasets are strongly dependent upon T:D. Using more realistic T:D ratios, the number of roots inferred by ALE consistently increases and, in some cases, clearly incorrect roots are inferred. Furthermore, our analyses reveal that gene duplications have a far greater impact on ALE's preferences for phylogenetic root placement than gene transfers or gene losses do. Overall, we show that obtaining reliable species tree roots with ALE is only possible when gene duplications are abundant in the data and the number of falsely inferred gene duplications is low. Finding a sufficient sample of true gene duplications for rooting species trees critically depends on the T:D ratios used in the analyses. T:D ratios, while being important parameters of genome evolution in their own right, affect the root inferences with tree reconciliations to an unanticipated degree.

Dataset Information

Simultaneous Bayesian gene tree reconstruction and reconciliation analysis.

Publications

Simultaneous Bayesian gene tree reconstruction and reconciliation analysis.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure