TY - DATA AB - Data and scripts are provided in support of the manuscript "Efficient inference of paternity and sibship inference given known maternity via hierarchical clustering", and the associated Python package FAPS, available from www.github.com/ellisztamas/faps. Simulation scripts cover: 1. Performance under different mating scenarios. 2. Comparison with Colony2. 3. Effect of changing the number of Monte Carlo draws The final script covers the analysis of half-sib arrays from wild-pollinated seed in an Antirrhinum majus hybrid zone. AU - Ellis, Thomas ID - 5583 TI - Data and Python scripts supporting Python package FAPS ER - TY - DATA AB - Nela Nikolic, Tobias Bergmiller, Alexandra Vandervelde, Tanino G. Albanese, Lendert Gelens, and Isabella Moll (2018) “Autoregulation of mazEF expression underlies growth heterogeneity in bacterial populations” Nucleic Acids Research, doi: 10.15479/AT:ISTA:74; microscopy experiments by Tobias Bergmiller; image and data analysis by Nela Nikolic. AU - Bergmiller, Tobias AU - Nikolic, Nela ID - 5569 KW - microscopy KW - microfluidics TI - Time-lapse microscopy data ER - TY - JOUR AB - Which properties of metabolic networks can be derived solely from stoichiometry? Predictive results have been obtained by flux balance analysis (FBA), by postulating that cells set metabolic fluxes to maximize growth rate. Here we consider a generalization of FBA to single-cell level using maximum entropy modeling, which we extend and test experimentally. Specifically, we define for Escherichia coli metabolism a flux distribution that yields the experimental growth rate: the model, containing FBA as a limit, provides a better match to measured fluxes and it makes a wide range of predictions: on flux variability, regulation, and correlations; on the relative importance of stoichiometry vs. optimization; on scaling relations for growth rate distributions. We validate the latter here with single-cell data at different sub-inhibitory antibiotic concentrations. The model quantifies growth optimization as emerging from the interplay of competitive dynamics in the population and regulation of metabolism at the level of single cells. AU - De Martino, Daniele AU - Mc, Andersson Anna AU - Bergmiller, Tobias AU - Guet, Calin C AU - Tkacik, Gasper ID - 161 IS - 1 JF - Nature Communications TI - Statistical mechanics for metabolic networks during steady state growth VL - 9 ER - TY - DATA AB - Supporting material to the article STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH boundscoli.dat Flux Bounds of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium. polcoli.dat Matrix enconding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium, obtained from the soichiometric matrix by standard linear algebra (reduced row echelon form). ellis.dat Approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium obtained with the Lovasz method. point0.dat Center of the approximate Lowner-John ellipsoid rounding the polytope of the E. coli catabolic core model iAF1260 in a glucose limited minimal medium obtained with the Lovasz method. lovasz.cpp This c++ code file receives in input the polytope of the feasible steady states of a metabolic network, (matrix and bounds), and it gives in output an approximate Lowner-John ellipsoid rounding the polytope with the Lovasz method NB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. For further details we refer to PLoS ONE 10.4 e0122670 (2015). sampleHRnew.cpp This c++ code file receives in input the polytope of the feasible steady states of a metabolic network, (matrix and bounds), the ellipsoid rounding the polytope, a point inside and it gives in output a max entropy sampling at fixed average growth rate of the steady states by performing an Hit-and-Run Monte Carlo Markov chain. NB inputs are referred by defaults to the catabolic core of the E.Coli network iAF1260. For further details we refer to PLoS ONE 10.4 e0122670 (2015). AU - De Martino, Daniele AU - Tkacik, Gasper ID - 5587 KW - metabolic networks KW - e.coli core KW - maximum entropy KW - monte carlo markov chain sampling KW - ellipsoidal rounding TI - Supporting materials "STATISTICAL MECHANICS FOR METABOLIC NETWORKS IN STEADY-STATE GROWTH" ER - TY - JOUR AB - The t-haplotype, a mouse meiotic driver found on chromosome 17, has been a model for autosomal segregation distortion for close to a century, but several questions remain regarding its biology and evolutionary history. A recently published set of population genomics resources for wild mice includes several individuals heterozygous for the t-haplotype, which we use to characterize this selfish element at the genomic and transcriptomic level. Our results show that large sections of the t-haplotype have been replaced by standard homologous sequences, possibly due to occasional events of recombination, and that this complicates the inference of its history. As expected for a long genomic segment of very low recombination, the t-haplotype carries an excess of fixed nonsynonymous mutations compared to the standard chromosome. This excess is stronger for regions that have not undergone recent recombination, suggesting that occasional gene flow between the t and the standard chromosome may provide a mechanism to regenerate coding sequences that have accumulated deleterious mutations. Finally, we find that t-complex genes with altered expression largely overlap with deleted or amplified regions, and that carrying a t-haplotype alters the testis expression of genes outside of the t-complex, providing new leads into the pathways involved in the biology of this segregation distorter. AU - Kelemen, Réka K AU - Vicoso, Beatriz ID - 542 IS - 1 JF - Genetics TI - Complex history and differentiation patterns of the t-haplotype, a mouse meiotic driver VL - 208 ER -