A CART-based approach to discover emerging patterns in microarray data

MOTIVATION: Cancer diagnosis using gene expression profiles requires supervised learning and gene selection methods. Of the many suggested approaches, the method of emerging patterns (EPs) has the particular advantage of explicitly modeling interactions among genes, which improves classification accuracy. However, finding useful (i.e. short and statistically significant) EP is typically very hard. METHODS: Here we introduce a CART-based approach to discover EPs in microarray data. The method is based on growing decision trees from which the EPs are extracted. This approach combines pattern search with a statistical procedure based on Fisher's exact test to assess the significance of each EP. Subsequently, sample classification based on the inferred EPs is performed using maximum-likelihood linear discriminant analysis. RESULTS: Using simulated data as well as gene expression data from colon and leukemia cancer experiments we assessed the performance of our pattern search algorithm and classification procedure. In the simulations, our method recovers a large proportion of known EPs while for real data it is comparable in classification accuracy with three top-performing alternative classification algorithms. In addition, it assigns statistical significance to the inferred EPs and allows to rank the patterns while simultaneously avoiding overfit of the data. The new approach therefore provides a versatile and computationally fast tool for elucidating local gene interactions as well as for classification. AVAILABILITY: A computer program written in the statistical language R implementing the new approach is freely available from the web page http://www.stat.uni-muenchen.de/~socher/     

A novel exploratory method for visual recombination detection

A versatile visual approach for detecting recombination and identifying recombination breakpoints within a sequence alignment is presented. The method is based on two novel diagrams - the highway plot and the occupancy plot - that graphically portray phylogenetic inhomogeneity along an alignment, and can be viewed as a synthesis of two widely used but unrelated methods: bootscanning and quartet-mapping. To illustrate the method, simulated data and HIV-1 and influenza A datasets are investigated.     

Century-scale Methylome Stability in a Recently Diverged Arabidopsis thaliana Lineage

There has been much excitement about the possibility that exposure to specific environments can induce an ecological memory in the form of whole-sale, genome-wide epigenetic changes that are maintained over many generations. In the model plant Arabidopsis thaliana, numerous heritable DNA methylation differences have been identified in greenhouse-grown isogenic lines, but it remains unknown how natural, highly variable environments affect the rate and spectrum of such changes. Here we present detailed methylome analyses in a geographically dispersed A. thaliana population that constitutes a collection of near-isogenic lines, diverged for at least a century from a common ancestor. Methylome variation largely reflected genetic distance, and was in many aspects similar to that of lines raised in uniform conditions. Thus, even when plants are grown in varying and diverse natural sites, genome-wide epigenetic variation accumulates mostly in a clock-like manner, and epigenetic divergence thus parallels the pattern of genome-wide DNA sequence divergence.     

Mapping-by-Sequencing Identifies HvPHYTOCHROME C as a Candidate Gene for the early maturity 5 Locus Modulating the Circadian Clock and Photoperiodic Flowering in Barley

Phytochromes play an important role in light signaling and photoperiodic control of flowering time in plants. Here we propose that the red/far-red light photoreceptor HvPHYTOCHROME C (HvPHYC), carrying a mutation in a conserved region of the GAF domain, is a candidate underlying the early maturity 5 locus in barley (Hordeum vulgare L.). We fine mapped the gene using a mapping-by-sequencing approach applied on the whole-exome capture data from bulked early flowering segregants derived from a backcross of the Bowman(eam5) introgression line. We demonstrate that eam5 disrupts circadian expression of clock genes. Moreover, it interacts with the major photoperiod response gene Ppd-H1 to accelerate flowering under noninductive short days. Our results suggest that HvPHYC participates in transmission of light signals to the circadian clock and thus modulates light-dependent processes such as photoperiodic regulation of flowering.