ABSTRACT
Direct observation of evolution in response to natural environmental change can resolve fundamental questions about adaptation, including its pace, temporal dynamics, and underlying phenotypic and genomic architecture. We tracked the evolution of fitness-associated phenotypes and allele frequencies genome-wide in 10 replicate field populations of Drosophila melanogaster over 10 generations from summer to late fall. Adaptation was evident over each sampling interval (one to four generations), with exceptionally rapid phenotypic adaptation and large allele frequency shifts at many independent loci. The direction and basis of the adaptive response shifted repeatedly over time, consistent with the action of strong and rapidly fluctuating selection. Overall, we found clear phenotypic and genomic evidence of adaptive tracking occurring contemporaneously with environmental change, thus demonstrating the temporally dynamic nature of adaptation.
Subject(s)
Acclimatization , Biological Evolution , Drosophila melanogaster/physiology , Selection, Genetic , Animals , Drosophila melanogaster/genetics , Ecosystem , Environment , Evolution, Molecular , Gene Frequency , Genetic Fitness , Genome, Insect , Phenotype , SeasonsABSTRACT
BACKGROUND: The PathOlogist is a new tool designed to transform large sets of gene expression data into quantitative descriptors of pathway-level behavior. The tool aims to provide a robust alternative to the search for single-gene-to-phenotype associations by accounting for the complexity of molecular interactions. RESULTS: Molecular abundance data is used to calculate two metrics--'activity' and 'consistency'--for each pathway in a set of more than 500 canonical molecular pathways (source: Pathway Interaction Database, http://pid.nci.nih.gov). The tool then allows a detailed exploration of these metrics through integrated visualization of pathway components and structure, hierarchical clustering of pathways and samples, and statistical analyses designed to detect associations between pathway behavior and clinical features. CONCLUSIONS: The PathOlogist provides a straightforward means to identify the functional processes, rather than individual molecules, that are altered in disease. The statistical power and biologic significance of this approach are made easily accessible to laboratory researchers and informatics analysts alike. Here we show as an example, how the PathOlogist can be used to establish pathway signatures that robustly differentiate breast cancer cell lines based on response to treatment.
Subject(s)
Algorithms , Gene Expression Profiling/methods , Gene Expression Regulation, Neoplastic , Metabolic Networks and Pathways , Neoplasms/genetics , Neoplasms/metabolism , Cell Line, Tumor , Cluster Analysis , Databases, Genetic , Glioblastoma/drug therapy , Humans , Neoplasms/drug therapy , Neoplasms/mortalityABSTRACT
UNLABELLED: Primary liver cancer is the third most common cause of cancer-related death worldwide, with a rising incidence in Western countries. Little is known about the genetic etiology of this disease. To identify genetic factors associated with hepatocellular carcinoma (HCC) and liver cirrhosis (LC), we conducted a comprehensive, genome-wide variation analysis in a population of unrelated Asian individuals. Copy number variation (CNV) and single nucleotide polymorphisms (SNPs) were assayed in peripheral blood with the high-density Affymetrix SNP6.0 microarray platform. We used a two-stage discovery and replication design to control for overfitting and to validate observed results. We identified a strong association with CNV at the T-cell receptor gamma and alpha loci (P < 1 × 10(-15)) in HCC cases when contrasted with controls. This variation appears to be somatic in origin, reflecting differences between T-cell receptor processing in lymphocytes from individuals with liver disease and healthy individuals that is not attributable to chronic hepatitis virus infection. Analysis of constitutional variation identified three susceptibility loci including the class II MHC complex, whose protein products present antigen to T-cell receptors and mediate immune surveillance. Statistical analysis of biologic networks identified variation in the "antigen presentation and processing" pathway as being highly significantly associated with HCC (P = 1 × 10(-11)). SNP analysis identified two variants whose allele frequencies differ significantly between HCC and LC. One of these (P = 1.74 × 10(-12)) lies in the PTEN homolog TPTE2. CONCLUSION: Combined analysis of CNV, individual SNPs, and pathways suggest that HCC susceptibility is mediated by germline factors affecting the immune response and differences in T-cell receptor processing.
