TY - JOUR
AB - Self-incompatibility (SI) is a genetically based recognition system that functions to prevent self-fertilization and mating among related plants. An enduring puzzle in SI is how the high diversity observed in nature arises and is maintained. Based on the underlying recognition mechanism, SI can be classified into two main groups: self- and non-self recognition. Most work has focused on diversification within self-recognition systems despite expected differences between the two groups in the evolutionary pathways and outcomes of diversification. Here, we use a deterministic population genetic model and stochastic simulations to investigate how novel S-haplotypes evolve in a gametophytic non-self recognition (SRNase/S Locus F-box (SLF)) SI system. For this model the pathways for diversification involve either the maintenance or breakdown of SI and can vary in the order of mutations of the female (SRNase) and male (SLF) components. We show analytically that diversification can occur with high inbreeding depression and self-pollination, but this varies with evolutionary pathway and level of completeness (which determines the number of potential mating partners in the population), and in general is more likely for lower haplotype number. The conditions for diversification are broader in stochastic simulations of finite population size. However, the number of haplotypes observed under high inbreeding and moderate to high self-pollination is less than that commonly observed in nature. Diversification was observed through pathways that maintain SI as well as through self-compatible intermediates. Yet the lifespan of diversified haplotypes was sensitive to their level of completeness. By examining diversification in a non-self recognition SI system, this model extends our understanding of the evolution and maintenance of haplotype diversity observed in a self recognition system common in flowering plants.
AU - Bodova, Katarina
AU - Priklopil, Tadeas
AU - Field, David
AU - Barton, Nicholas H
AU - Pickup, Melinda
ID - 316
IS - 3
JF - Genetics
TI - Evolutionary pathways for the generation of new self-incompatibility haplotypes in a non-self recognition system
VL - 209
ER -
TY - JOUR
AB - Gene regulatory networks evolve through rewiring of individual components—that is, through changes in regulatory connections. However, the mechanistic basis of regulatory rewiring is poorly understood. Using a canonical gene regulatory system, we quantify the properties of transcription factors that determine the evolutionary potential for rewiring of regulatory connections: robustness, tunability and evolvability. In vivo repression measurements of two repressors at mutated operator sites reveal their contrasting evolutionary potential: while robustness and evolvability were positively correlated, both were in trade-off with tunability. Epistatic interactions between adjacent operators alleviated this trade-off. A thermodynamic model explains how the differences in robustness, tunability and evolvability arise from biophysical characteristics of repressor–DNA binding. The model also uncovers that the energy matrix, which describes how mutations affect repressor–DNA binding, encodes crucial information about the evolutionary potential of a repressor. The biophysical determinants of evolutionary potential for regulatory rewiring constitute a mechanistic framework for understanding network evolution.
AU - Igler, Claudia
AU - Lagator, Mato
AU - Tkacik, Gasper
AU - Bollback, Jonathan P
AU - Guet, Calin C
ID - 67
IS - 10
JF - Nature Ecology and Evolution
TI - Evolutionary potential of transcription factors for gene regulatory rewiring
VL - 2
ER -
TY - DATA
AB - Mean repression values and standard error of the mean are given for all operator mutant libraries.
AU - Igler, Claudia
AU - Lagator, Mato
AU - Tkacik, Gasper
AU - Bollback, Jonathan P
AU - Guet, Calin C
ID - 5585
TI - Data for the paper Evolutionary potential of transcription factors for gene regulatory rewiring
ER -
TY - JOUR
AB - The resolution of a linear system with positive integer variables is a basic yet difficult computational problem with many applications. We consider sparse uncorrelated random systems parametrised by the density c and the ratio α=N/M between number of variables N and number of constraints M. By means of ensemble calculations we show that the space of feasible solutions endows a Van-Der-Waals phase diagram in the plane (c, α). We give numerical evidence that the associated computational problems become more difficult across the critical point and in particular in the coexistence region.
AU - Colabrese, Simona
AU - De Martino, Daniele
AU - Leuzzi, Luca
AU - Marinari, Enzo
ID - 823
IS - 9
JF - Journal of Statistical Mechanics: Theory and Experiment
SN - 17425468
TI - Phase transitions in integer linear problems
VL - 2017
ER -
TY - JOUR
AB - The Ising model is one of the simplest and most famous models of interacting systems. It was originally proposed to model ferromagnetic interactions in statistical physics and is now widely used to model spatial processes in many areas such as ecology, sociology, and genetics, usually without testing its goodness-of-fit. Here, we propose an exact goodness-of-fit test for the finite-lattice Ising model. The theory of Markov bases has been developed in algebraic statistics for exact goodness-of-fit testing using a Monte Carlo approach. However, this beautiful theory has fallen short of its promise for applications, because finding a Markov basis is usually computationally intractable. We develop a Monte Carlo method for exact goodness-of-fit testing for the Ising model which avoids computing a Markov basis and also leads to a better connectivity of the Markov chain and hence to a faster convergence. We show how this method can be applied to analyze the spatial organization of receptors on the cell membrane.
AU - Martin Del Campo Sanchez, Abraham
AU - Cepeda Humerez, Sarah A
AU - Uhler, Caroline
ID - 2016
IS - 2
JF - Scandinavian Journal of Statistics
SN - 03036898
TI - Exact goodness-of-fit testing for the Ising model
VL - 44
ER -