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Abstract. Whole genome duplication (WGD) is a rare evolutionary event that has played a dramatic role in the diversification of most eucaryotic lineages. Given a set of species known to have evolved from a common ancestor through one or many rounds of WGD together with a set of genome rearrangements, and a phylogenetic tree for these species, the goal is to infer the pre-duplicated ancestral genomes. We use a two step approach: (1) Compute a score for each possible ancestral adjacency at each internal node of the phylogeny; (2) Combine adjacencies to form ancestral chromosomes. The main contribution of our method is the computation of a rigorous score for each potential ancestral adjacency (a, b), reflecting the maximum number of times a and b can be adjacent in the whole phylogeny, for any setting of ancestral genomes. We first apply our method on simulated datasets and show a high accuracy for adjacency prediction. We then infer the pre-duplicated ancestor of a set of 11 yeast species and compare it to a manually assembled ancestral genome obtained by Gordon et al. (2009).

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Abstract:The objective of this work was to assess the accuracy of various coupled mesoscale-microscale wind flow modeling methodologies for wind energy applications. This is achieved by examining and comparing mean wind speeds from several wind flow modeling methodologies with observational measurements from several 50 m met towers distributed across the study area. At the mesoscale level, with a 5 km resolution, two scenarios are examined based on the Mesoscale Compressible Community Model (MC2) model: the Canadian Wind Energy Atlas (CWEA) scenario, which is based on standard input data, and the CWEA High Definition (CWEAHD) scenario where high resolution land cover input data is used. A downscaling of the obtained mesoscale wind climate to the microscale level is then performed, where two linear microscale models, i.e., MsMicro and the Wind Atlas Analysis and Application Program (WAsP), are evaluated following three downscaling scenarios: CWEA-WAsP, CWEA-MsMicro and CWEAHD-MsMicro. Results show that, for the territory studied, with a modeling approach based on the MC2 and MsMicro models, also known as Wind Energy Simulation Toolkit (WEST), the use of high resolution land cover and topography data at the mesoscale level helps reduce modeling errors for both the mesoscale and microscale models, albeit only marginally. At the microscale level, results show that the MC2-WAsP modeling approach gave substantially better results than both MC2 and MsMicro modeling approaches due to tweaked meso-micro coupling. OPEN ACCESSEnergies 2012, 5 4289