Examining emergence of functional gene clustering in a simulated evolution

A Boolean gene regulatory model of heterosis and speciation

BACKGROUND

Modelling genetic phenomena affecting biological traits is important for the development of agriculture as it allows breeders to predict the potential of breeding for certain traits. One such phenomenon is heterosis or hybrid vigor: crossing individuals from genetically distinct populations often results in improvements in quantitative traits, such as growth rate, biomass production and stress resistance. Heterosis has become a very useful tool in global agriculture, but its genetic basis remains controversial and its effects hard to predict. We have taken a computational approach to studying heterosis, developing a simulation of evolution, independent reassortment of alleles and hybridization of Gene Regulatory Networks (GRNs) in a Boolean framework. These artificial regulatory networks exhibit topological properties that reflect those observed in biology, and fitness is measured as the ability of a network to respond to external inputs in a pre-defined way.

RESULTS

Our model reproduced common experimental observations on heterosis using only biologically justified parameters, such as mutation rates. Hybrid vigor was observed and its extent was seen to increase as parental populations diverged, up until a point of sudden collapse of hybrid fitness. Thus, the model also describes a process akin to speciation due to genetic incompatibility of the separated populations. We also reproduce, for the first time in a model, the fact that hybrid vigor cannot easily be fixed by within a breeding line, currently an important limitation of the use of hybrid crops. The simulation allowed us to study the effects of three standard models for the genetic basis of heterosis: dominance, over-dominance, and epistasis.

CONCLUSION

This study describes the most detailed simulation of heterosis using gene regulatory networks to date and reproduces several phenomena associated with heterosis for the first time in a model. The level of detail in our model allows us to suggest possible warning signs of the impending collapse of hybrid vigor in breeding. In addition, the simulation provides a framework that can be extended to study other aspects of heterosis and alternative evolutionary scenarios.

Linking dopamine neurotransmission and neurogenesis: The evolutionary history of the NTAD (NCAM1-TTC12-ANKK1-DRD2) gene cluster

Genetic studies have long suggested the important role of the DRD2 gene in psychiatric disorders and behavior. Further research has shown a conjoined effect of genes in the Chr11q22–23 region, which includes the NCAM1, TTC12, ANKK1 and DRD2 genes, or NTAD cluster. Despite a growing need to unravel the role of this cluster, few studies have taken into account interspecies and evolutionary approaches. This study shows that behaviorally relevant SNPs from the NTAD cluster, such as rs1800497 (Taq1A) and rs6277, are ancient polymorphisms that date back to the common ancestor between modern humans and Neanderthals/Denisovans. Conserved synteny and neighborhood indicate the NTAD cluster seems to have been established at least 400 million years ago, when the first Sarcopterygians emerged. The NTAD genes are apparently co-regulated and this could be attributed to adaptive functional properties, including those that emerged when the central nervous system became more complex. Finally, our findings indicate that NTAD genes, which are related to neurogenesis and dopaminergic neurotransmission, should be approached as a unit in behavioral and psychiatric genetic studies.

Impact of chromosomal inversions on the yeast DAL cluster

Chromosomal rearrangements occur readily in nature and are a major reshaping force during genome evolution. Such large scale modifications are usually deleterious causing several fitness defects, but sometimes can confer an advantage and become adaptive. For example the DAL metabolic cluster in yeast was assembled in recent evolutionary times in the Hemiascomycetes lineage, through a set of rearrangements that brought together the genes involved in the allantoin degradation pathway. In eukaryotes, the existence of physical clustering of genes with related functions supports the notion that neighbouring ORFs tend to be co-expressed and that the order of genes along the chromosomes may have biological significance, rather than being random as previously believed. In this study, we investigate the phenotypic effect that inversions have on the DAL gene cluster, expressed during nitrogen starvation. In all Saccharomyces "sensu stricto" species the order of the DAL cluster is conserved, while in the "sensu lato" species Naumovia castellii, which grows significantly worse than S. cerevisiae on allantoin, the cluster includes two nested inversions encompassing three DAL genes. We constructed several inverted and non-inverted S. cerevisiae strains possessing different inversions including those to mimic the configuration of the N. castellii DAL cluster. We showed that the inversion of DAL2 lower its own expression and reduces yeast fitness during nitrogen starvation. This rearrangement also altered the expression of the neighbouring genes DAL1 and DAL4. Moreover, we showed that the expression of the DAL4 anti-sense transcript (SUT614) does not change upon inversions of DAL2 and therefore is unlikely to be involved in its regulation. These results show that the order of the DAL cluster has an impact on the phenotype and gene expression, suggesting that these rearrangements may have been adaptive in the "sensu stricto" group in relation to the low availability of nitrogen in the environment.

Evolving synaptic plasticity with an evolutionary cellular development model

Since synaptic plasticity is regarded as a potential mechanism for memory formation and learning, there is growing interest in the study of its underlying mechanisms. Recently several evolutionary models of cellular development have been presented, but none have been shown to be able to evolve a range of biological synaptic plasticity regimes. In this paper we present a biologically plausible evolutionary cellular development model and test its ability to evolve different biological synaptic plasticity regimes. The core of the model is a genomic and proteomic regulation network which controls cells and their neurites in a 2D environment. The model has previously been shown to successfully evolve behaving organisms, enable gene related phenomena, and produce biological neural mechanisms such as temporal representations. Several experiments are described in which the model evolves different synaptic plasticity regimes using a direct fitness function. Other experiments examine the ability of the model to evolve simple plasticity regimes in a task -based fitness function environment. These results suggest that such evolutionary cellular development models have the potential to be used as a research tool for investigating the evolutionary aspects of synaptic plasticity and at the same time can serve as the basis for novel artificial computational systems.

Inevitable evolutionary temporal elements in neural processing: a study based on evolutionary simulations

Recent studies have suggested that some neural computational mechanisms are based on the fine temporal structure of spiking activity. However, less effort has been devoted to investigating the evolutionary aspects of such mechanisms. In this paper we explore the issue of temporal neural computation from an evolutionary point of view, using a genetic simulation of the evolutionary development of neural systems. We evolve neural systems in an environment with selective pressure based on mate finding, and examine the temporal aspects of the evolved systems. In repeating evolutionary sessions, there was a significant increase during evolution in the mutual information between the evolved agent's temporal neural representation and the external environment. In ten different simulated evolutionary sessions, there was an increased effect of time -related neural ablations on the agents' fitness. These results suggest that in some fitness landscapes the emergence of temporal elements in neural computation is almost inevitable. Future research using similar evolutionary simulations may shed new light on various biological mechanisms.