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Phylogenies based on gene content rely on statements of primary homology to characterize gene presence or absence. These statements (hypotheses) are usually determined by techniques based on threshold similarity or distance measurements between genes. This fundamental but problematic step can be examined by evaluating each homology hypothesis by the extent to which it is corroborated by the rest of the data. Here we test the effects of varying the stringency for making primary homology statements using a range of similarity (e-value) cutoffs in 166 fully sequenced and annotated genomes spanning the tree of life. By evaluating each resulting data set with tree-based measurements of character consistency and information content, we find a set of homology statements that optimizes overall corroborration. The resulting data set produces well-resolved and well-supported trees of life and greatly ameliorates previously noted inconsistencies such as the misclassification of small genomes. The method presented here, which can be used to test any technique for recognizing primary homology, provides an objective framework for evaluating phylogenetic hypotheses and data sets for the tree of life. It also can serve as a technique for identifying well-corroborated sets of homologous genes for functional genomic applications. [CCM; consistency; corroboration; gene content; homology; ILD; phylogeny; presence absence; tree of life.] [ABSTRACT FROM AUTHOR]

Background: The availability of sequences from whole genomes to reconstruct the tree of life has the potential to enable the development of phylogenomic hypotheses in ways that have not been before possible. A significant bottleneck in the analysis of genomic-scale views of the tree of life is the time required for manual curation of genomic data into multi-gene phylogenetic matrices. Results: To keep pace with the exponentially growing volume of molecular data in the genomic era, we have developed an automated technique, ASAP (Automated Simultaneous Analysis Phylogenetics), to assemble these multigene/multi species matrices and to evaluate the significance of individual genes within the context of a given phylogenetic hypothesis. Conclusion: Applications of ASAP may enable scientists to re-evaluate species relationships and to develop new phylogenomic hypotheses based on genome-scale data. [ABSTRACT FROM AUTHOR]