Vestige: maximum likelihood phylogenetic footprinting

Oncogenic BRCA1,2 Mutations in the Human Lineage-A By-Product of Sexual Selection?

In this review, we discuss the long-known problem of tissue-specific carcinogenesis in BRCA1 and BRCA2 mutation carriers: while the genes are expressed ubiquitously, increased cancer risk is observed mostly in the breast and ovaries, and to a much lesser extent, in some other tissues such as the prostate or pancreas. We reevaluate hypotheses on the evolutionary origin of these mutations in humans. Also, we align together the reports that at least some great apes have much lower risks of epithelial cancers in general and breast cancer in particular with the fact that humans have more voluminous breast tissue as compared to their closest extant relatives, particularly chimpanzees and bonobos. We conjecture that this disparity may be a consequence of sexual selection, augmented via selection for enhanced lactation. Further, we argue that there is an organ-specific enigma similar to the Peto paradox: breast cancer risk in humans is only minimally correlated with breast size. These considerations lead to the hypothesis that, along with the evolutionary development of larger breasts in humans, additional changes have played a balancing role in suppressing breast cancer. These yet-to-be-discovered mechanisms, while purely speculative, may be valuable to understanding human breast cancer, though they may not be exclusive to the mammary gland epithelial cells. Combining these themes, we review some anti-carcinogenesis preventive strategies and prospects of new interventions against breast cancer.

Selection and the cell cycle: positive Darwinian selection in a well-known DNA damage response pathway

Cancer is a common occurrence in multi-cellular organisms and is not strictly limited to the elderly in a population. It is therefore possible that individuals with genotypes that protect against early onset cancers have a selective advantage. In this study the patterns of mutation in the proteins of a well-studied DNA damage response pathway have been examined for evidence of adaptive evolutionary change. Using a maximum likelihood framework and the mammalian species phylogeny, together with codon models of evolution, selective pressure variation across the interacting network of proteins has been detected. The presence of signatures of adaptive evolution in BRCA1 and BRCA2 has already been documented but the effect on the entire network of interacting proteins in this damage response pathway has, until now, been unknown. Positive selection is evident throughout the network with a total of 11 proteins out of 15 examined displaying patterns of substitution characteristic of positive selection. It is also shown here that modern human populations display evidence of an ongoing selective sweep in 9 of these DNA damage repair proteins. The results presented here provide the community with new residues that may be relevant to cancer susceptibility while also highlighting those proteins where human and mouse have undergone lineage-specific functional shift. An understanding of this damage response pathway from an evolutionary perspective will undoubtedly contribute to future cancer treatment approaches.

Evidence that localized variation in primate sequence divergence arises from an influence of nucleosome placement on DNA repair

Understanding the origins of localized substitution rate heterogeneity has important implications for identifying functional genomic sequences. Outside of gene regions, the origins of rate heterogeneity remain unclear. Experimental studies establish that chromatin compaction affects rates of both DNA lesion formation and repair. A functional association between chromatin status and 5-methyl-cytosine also exists. These suggest that both the total rate and the type of substitution will be affected by chromatin status. Regular positioning of nucleosomes, the building block of chromatin, further predicts that substitution rate and type should vary spatially in an oscillating manner. We addressed chromatin's influence on substitution rate and type in primates. Matched numbers of sites were sampled from Dnase I hypersensitive (DHS) and closed chromatin control flank (Flank). Likelihood ratio tests revealed significant excesses of total and of transition substitutions in Flank compared with matched DHS for both intergenic and intronic samples. An additional excess of CpG transitions was evident for the intergenic, but not intronic, regions. Fluctuation in substitution rate along approximately 1,800 primate promoters was measured using phylogenetic footprinting. Significant positive correlations were evident between the substitution rate and a nucleosome score from resting human T-cells, with up to approximately 50% of the variance in substitution rate accounted for. Using signal processing techniques, a dominant oscillation at approximately 200 bp was evident in both the substitution rate and the nucleosome score. Our results support a role for differential DNA repair rates between open and closed chromatin in the spatial distribution of rate heterogeneity.

Evolutionary genomics of human intellectual disability

Previous studies have postulated that X-linked and autosomal genes underlying human intellectual disability may have also mediated the evolution of human cognition. We have conducted the first comprehensive assessment of the extent and patterns of positive Darwinian selection on intellectual disability genes in humans. We report three main findings. First, as noted in some previous reports, intellectual disability genes with primary functions in the central nervous system exhibit a significant concentration to the X chromosome. Second, there was no evidence for a higher incidence of recent positive selection on X-linked than autosomal intellectual disability genes, nor was there a higher incidence of selection on such genes overall, compared to sets of control genes. However, the X-linked intellectual disability genes inferred to be subject to recent positive selection were concentrated in the Rho GTP-ase pathway, a key signaling pathway in neural development and function. Third, among all intellectual disability genes, there was evidence for a higher incidence of recent positive selection on genes involved in DNA repair, but not for genes involved in other functions. These results provide evidence that alterations to genes in the Rho GTP-ase and DNA-repair pathways may play especially-important roles in the evolution of human cognition and vulnerability to genetically-based intellectual disability.

Initial implementation of a comparative data analysis ontology

Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species) are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: “Operational Taxonomic Units” (OTUs), representing the entities to be compared; “character-state data” representing the observations compared among OTUs; “phylogenetic tree”, representing the historical path of evolution among the entities; and “transitions”, the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL), we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO). CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc.) that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

PyCogent: a toolkit for making sense from sequence

The COmparative GENomic Toolkit, a framework for probabilistic analyses of biological sequences, devising workflows and generating publication quality graphics, has been implemented in Python.

We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from .

Distinguishing HIV-1 drug resistance, accessory, and viral fitness mutations using conditional selection pressure analysis of treated versus untreated patient samples

BACKGROUND

HIV can evolve drug resistance rapidly in response to new drug treatments, often through a combination of multiple mutations 123. It would be useful to develop automated analyses of HIV sequence polymorphism that are able to predict drug resistance mutations, and to distinguish different types of functional roles among such mutations, for example, those that directly cause drug resistance, versus those that play an accessory role. Detecting functional interactions between mutations is essential for this classification. We have adapted a well-known measure of evolutionary selection pressure (Ka/Ks) and developed a conditional Ka/Ks approach to detect important interactions.

RESULTS

We have applied this analysis to four independent HIV protease sequencing datasets: 50,000 clinical samples sequenced by Specialty Laboratories, Inc.; 1800 samples from patients treated with protease inhibitors; 2600 samples from untreated patients; 400 samples from untreated African patients. We have identified 428 mutation interactions in Specialty dataset with statistical significance and we were able to distinguish primary vs. accessory mutations for many well-studied examples. Amino acid interactions identified by conditional Ka/Ks matched 80 of 92 pair wise interactions found by a completely independent study of HIV protease (p-value for this match is significant: 10-70). Furthermore, Ka/Ks selection pressure results were highly reproducible among these independent datasets, both qualitatively and quantitatively, suggesting that they are detecting real drug-resistance and viral fitness mutations in the wild HIV-1 population.

CONCLUSION

Conditional Ka/Ks analysis can detect mutation interactions and distinguish primary vs. accessory mutations in HIV-1. Ka/Ks analysis of treated vs. untreated patient data can distinguish drug-resistance vs. viral fitness mutations. Verification of these results would require longitudinal studies. The result provides a valuable resource for AIDS research and will be available for open access upon publication at http://www.bioinformatics.ucla.edu/HIV.