139 research outputs found
A set of genes conserved in sequence and expression traces back the establishment of multicellularity in social amoebae
Background: The developmental cycle of Dictyostelid amoebae represents an early form of multicellularity with cell type differentiation. Mutant studies in the model Dictyostelium discoideum revealed that its developmental program integrates the actions of genes involved in signal transduction, adhesion, motility, autophagy and cell wall and matrix biosynthesis. However, due to functional redundancy and fail safe options not required in the laboratory, this single organism approach cannot capture all essential genes. To understand how multicellular organisms evolved, it is essential to recognize both the conserved core features of their developmental programs and the gene modifications that instigated phenotypic innovation. For complex organisms, such as animals, this is not within easy reach, but it is feasible for less complex forms, such as the Dictyostelid social amoebas. Results: We compared global profiles of gene expression during the development of four social amoebae species that represent 600 mya of Dictyostelia evolution, and identified orthologous conserved genes with similar developmental up-regulation of expression using three different methods. For validation, we disrupted five genes of this core set and examined the phenotypic consequences. Conclusion: At least 71 of the developmentally regulated genes that were identified with all methods were likely to be already present in the last ancestor of all Dictyostelia. The lack of phenotypic changes in null mutants indicates that even highly conserved genes either participate in functionally redundant pathways or are necessary for developmental progression under adverse, non-standard laboratory conditions. Both mechanisms provide robustness to the developmental program, but impose a limit on the information that can be obtained from deleting single genes
Data analytics and optimization for assessing a ride sharing system
Ride-sharing schemes attempt to reduce road traffic by matching prospective passengers to drivers with spare seats in their cars. To be successful, such schemes require a critical mass of drivers and passengers. In current deployed implementations, the possible matches are based on heuristics, rather than real route times or distances. In some cases, the heuristics propose infeasible matches; in others, feasible matches are omitted. Poor ride matching is likely to deter participants from using the system. We develop a constraint-based model for acceptable ride matches which incorporates route plans and time windows. Through data analytics on a history of advertised schedules and agreed shared trips, we infer parameters for this model that account for 90% of agreed trips. By applying the inferred model to the advertised schedules, we demonstrate that there is an imbalance between riders and passengers. We assess the potential benefits of persuading existing drivers to switch to becoming passengers if appropriate matches can be found, by solving the inferred model with and without switching. We demonstrate that flexible participation has the potential to reduce the number of unmatched participants by up to 80%
A Multistage Stochastic Programming Approach to the Dynamic and Stochastic VRPTW - Extended version
We consider a dynamic vehicle routing problem with time windows and
stochastic customers (DS-VRPTW), such that customers may request for services
as vehicles have already started their tours. To solve this problem, the goal
is to provide a decision rule for choosing, at each time step, the next action
to perform in light of known requests and probabilistic knowledge on requests
likelihood. We introduce a new decision rule, called Global Stochastic
Assessment (GSA) rule for the DS-VRPTW, and we compare it with existing
decision rules, such as MSA. In particular, we show that GSA fully integrates
nonanticipativity constraints so that it leads to better decisions in our
stochastic context. We describe a new heuristic approach for efficiently
approximating our GSA rule. We introduce a new waiting strategy. Experiments on
dynamic and stochastic benchmarks, which include instances of different degrees
of dynamism, show that not only our approach is competitive with
state-of-the-art methods, but also enables to compute meaningful offline
solutions to fully dynamic problems where absolutely no a priori customer
request is provided.Comment: Extended version of the same-name study submitted for publication in
conference CPAIOR201
Synthesis and crystal structure of 1,4,10,13-tetraoxa-7,16-diazoniumcyclo-octadecane bis(4-chloro-2-methyl-phenoxyacetate)
The title compound was prepared by the reaction of 1,4,10,13-tetraoxa-7,16-diazacyclo-octadecane with 4-chloro-2-methyl-phenoxyacetic acid in a ratio of 1:2. The structure has been proved by the data of elemental analysis, IR spectroscopy, NMR (1H, 13C) technique and by X-ray diffraction analysis. Intermolecular hydrogen bonds between the azonium protons and oxygen atoms of the carboxylate groups were found. Immunoactive properties of the title compound have been screened. The compound has the ability to suppress spontaneous and Con A-stimulated cell proliferation in vitro and therefore can be considered as immunodepressant
Improved annotation with <i>de novo</i> transcriptome assembly in four social amoeba species
Background: Annotation of gene models and transcripts is a fundamental step in genome sequencing projects. Often this is performed with automated prediction pipelines, which can miss complex and atypical genes or transcripts. RNA sequencing (RNA-seq) data can aid the annotation with empirical data. Here we present de novo transcriptome assemblies generated from RNA-seq data in four Dictyostelid species: D. discoideum, P. pallidum, D. fasciculatum and D. lacteum. The assemblies were incorporated with existing gene models to determine corrections and improvement on a whole-genome scale. This is the first time this has been performed in these eukaryotic species. Results: An initial de novo transcriptome assembly was generated by Trinity for each species and then refined with Program to Assemble Spliced Alignments (PASA). The completeness and quality were assessed with the Benchmarking Universal Single-Copy Orthologs (BUSCO) and Transrate tools at each stage of the assemblies. The final datasets of 11,315-12,849 transcripts contained 5,610-7,712 updates and corrections to >50% of existing gene models including changes to hundreds or thousands of protein products. Putative novel genes are also identified and alternative splice isoforms were observed for the first time in P. pallidum, D. lacteum and D. fasciculatum. Conclusions: In taking a whole transcriptome approach to genome annotation with empirical data we have been able to enrich the annotations of four existing genome sequencing projects. In doing so we have identified updates to the majority of the gene annotations across all four species under study and found putative novel genes and transcripts which could be worthy for follow-up. The new transcriptome data we present here will be a valuable resource for genome curators in the Dictyostelia and we propose this effective methodology for use in other genome annotation projects
The multicellularity genes of dictyostelid social amoebas
The evolution of multicellularity enabled specialization of cells, but required novel signalling mechanisms for regulating cell differentiation. Early multicellular organisms are mostly extinct and the origins of these mechanisms are unknown. Here using comparative genome and transcriptome analysis across eight uni- and multicellular amoebozoan genomes, we find that 80% of proteins essential for the development of multicellular Dictyostelia are already present in their unicellular relatives. This set is enriched in cytosolic and nuclear proteins, and protein kinases. The remaining 20%, unique to Dictyostelia, mostly consists of extracellularly exposed and secreted proteins, with roles in sensing and recognition, while several genes for synthesis of signals that induce cell-type specialization were acquired by lateral gene transfer. Across Dictyostelia, changes in gene expression correspond more strongly with phenotypic innovation than changes in protein functional domains. We conclude that the transition to multicellularity required novel signals and sensors rather than novel signal processing mechanisms
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