BackgroundTrypanosoma cruzi, the etiologic agent of Chagas disease, is currently divided into six discrete typing units (DTUs), named TcI-TcVI. TcII is among the major DTUs enrolled in human infections in South America southern cone, where it is associated with severe cardiac and digestive symptoms. Despite the importance of TcII in Chagas disease epidemiology and pathology, so far, no genome-wide comparisons of the mitochondrial and nuclear genomes of TcII field isolates have been performed to track the variability and evolution of this DTU in endemic regions.ResultsIn the present work, we have sequenced and compared the whole nuclear and mitochondrial genomes of seven TcII strains isolated from chagasic patients from the central and northeastern regions of Minas Gerais, Brazil, revealing an extensive genetic variability within this DTU. A comparison of the phylogeny based on the nuclear or mitochondrial genomes revealed that the majority of branches were shared by both sequences. The subtle divergences in the branches are probably consequence of mitochondrial introgression events between TcII strains. Two T. cruzi strains isolated from patients living in the central region of Minas Gerais, S15 and S162a, were clustered in the nuclear and mitochondrial phylogeny analysis. These two strains were isolated from the other five by the Espinhaço Mountains, a geographic barrier that could have restricted the traffic of insect vectors during T. cruzi evolution in the Minas Gerais state. Finally, the presence of aneuploidies was evaluated, revealing that all seven TcII strains have a different pattern of chromosomal duplication/loss.ConclusionsAnalysis of genomic variability and aneuploidies suggests that there is significant genomic variability within Minas Gerais TcII strains, which could be exploited by the parasite to allow rapid selection of favorable phenotypes. Also, the aneuploidy patterns vary among T. cruzi strains and does not correlate with the nuclear phylogeny, suggesting that chromosomal duplication/loss are recent and frequent events in the parasite evolution.Electronic supplementary materialThe online version of this article (10.1186/s12864-018-5198-4) contains supplementary material, which is available to authorized users.
With the forecasted worldwide increase in travel volumes, it is a priority to improve the capacity of air traffic networks to minimize the economic cost of congestion and improve social welfare. In this paper, we introduce new mixed-integer programming formulations for aircraft conflict resolution with speed and altitude control which are based on a disjunctive linear separation condition. We show that the proposed disjunctive linear separation condition is equivalent to the traditional nonlinear separation condition. Two different objective function are proposed with piecewise linear and quadratic penalties, respectively, resulting in MILP and MIQP formulations. The performance of the proposed Disjunctive model is evaluated using benchmarking conflict resolution instances with up to 100 aircraft and 10 flight levels. Further, the proposed Disjunctive formulations are compared against alternative formulations based on existing and widely used separation constraints. Our results show that the proposed Disjunctive model outperforms existing formulations in the literature and can solve to optimality significantly more instances. Further, instances with up to 50 aircraft can be solved in a less than a second which highlights the potential of this approach as a decision-support tool for tactical conflict resolution.
Minimum flow decomposition (MFD) is an NP-hard problem asking to decompose a network flow into a minimum set of paths (together with associated weights). Variants of it are powerful models in multiassembly problems in Bioinformatics, such as RNA assembly. Owing to its hardness, practical multiassembly tools either use heuristics or solve simpler, polynomial time-solvable versions of the problem, which may yield solutions that are not minimal or do not perfectly decompose the flow. Here, we provide the first fast and exact solver for MFD on acyclic flow networks, based on Integer Linear Programming (ILP). Key to our approach is an encoding of
all
the exponentially many solution paths using only a
quadratic
number of variables. We also extend our ILP formulation to many practical variants, such as incorporating longer or paired-end reads, or minimizing flow errors. On both simulated and real-flow splicing graphs, our approach solves
any
instance in <13 seconds. We hope that our formulations can lie at the core of future practical RNA assembly tools. Our implementations are freely available on Github.
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