Robustness analysis of cellular systems using the genetic tug-of-war method

Robustness is one of the principles of design inherent to biological systems. Cellular robustness can be measured as limits of intracellular parameters such as gene expression levels. We have recently developed an experimental approach coined as genetic Tug-Of-War (gTOW), which we used to perform robustness analysis in yeast. Using gTOW, we were able to measure the upper limit of expression of gene targets. In this review, we first elaborate on how the gTOW method compares to current mathematical simulation models prevalently used in the determination of robustness. We then explain the experimental principles underlying gTOW and its associated tools, and we provide concrete examples of robustness analysis using gTOW, i.e. cell cycle and HOG pathway gene expression analysis. Finally, we list a series of Q&As related to the experimental utilization of gTOW and we describe the potential impact of gTOW and its relevance to the understanding of biological systems.     

Mapping human genetic ancestry

The human genome is a mosaic with respect to its evolutionary history. Based on a phylogenetic analysis of 23,210 DNA sequence alignments from human, chimpanzee, gorilla, orangutan, and rhesus, we present a map of human genetic ancestry. For about 23% of our genome, we share no immediate genetic ancestry with our closest living relative, the chimpanzee. This encompasses genes and exons to the same extent as intergenic regions. We conclude that about 1/3 of our genes started to evolve as human-specific lineages before the differentiation of human, chimps, and gorillas took place. This explains recurrent findings of very old human-specific morphological traits in the fossils record, which predate the recent emergence of the human species about 5-6 MYA. Furthermore, the sorting of such ancestral phenotypic polymorphisms in subsequent speciation events provides a parsimonious explanation why evolutionary derived characteristics are shared among species that are not each other's closest relatives.     

Mapping of porcine genetic markers generated by representational difference analysis

Representational difference analysis (RDA) was performed using pig genomic DNA from a Landrace non-selected control population and a Landrace population selected for increased loin muscle area (LMA) for five generations. Pigs used for the analysis differed phenotypically for various carcass traits and were divergent in genotype at the skeletal muscle ryanodine receptor 1 locus. Two RDA experiments were performed using BamHI and BglII. Fourteen BamHI and 37 BglII difference products were cloned and sequenced. Oligonucleotide primers were designed to amplify RDA difference products and sequence-tagged sites (STS) were developed for 16 RDA fragments (two BamHI and 14 BglII). These 16 STS were mapped using the INRA-Minnesota porcine Radiation Hybrid panel. Polymorphisms identified in nine of the STS were used to place these markers on the PiGMaP genetic linkage map. Sequence-tagged sites were localized to 11 different chromosomes including three markers on chromosome 11 and four markers on chromosome 14. Development of RDA markers increases the resolution of the pig genome maps and markers located within putative quantitative trait locus (QTL) regions can be used to refine QTL positions.     

Mapping of the murine type 1 diabetes locus Idd20 by genetic interaction

In the nonobese diabetes mouse, the murine type 1 diabetes susceptibility locus Idd20 interacts genetically with the diabetes resistance locus Idd19. Both Idds are located on distal mouse Chromosome 6, and previous studies on NOD.C3H congenic strains have shown that C3H alleles at Idd20 can suppress the disease-promoting effects of C3H alleles at Idd19 in both spontaneous and cyclophosphamide-induced diabetes. In this article we present the construction of novel congenic strains which, while maintaining the C3H alleles at Idd19, have allowed the candidate interval of Idd20 to be reduced from 4 to 1.8 cM. The analysis of these strains shows that Idd20 controls the progression of insulitis. Idd20 also increases the suppressive but not the pathogenic activity of splenocytes in diabetes transfer experiments. Our results suggest that the two Chromosome 6 susceptibility loci, Idd6 and Idd20, interact with the resistance locus Idd19 by regulating the activity of suppressor cells in the peripheral immune system.     

Mapping genetic influences on cortical regionalization

In this issue of Neuron, Chen and colleagues combine structural MRI and a twin-study design to investigate the influence of genetics on human cortical regionalization. Their results resonate with findings from animal studies and certain human syndromes of developmental cortical malformation.     

Mapping of signaling networks through synthetic genetic interaction analysis by RNAi

The analysis of synthetic genetic interaction networks can reveal how biological systems achieve a high level of complexity with a limited repertoire of components. Studies in yeast and bacteria have taken advantage of collections of deletion strains to construct matrices of quantitative interaction profiles and infer gene function. Yet comparable approaches in higher organisms have been difficult to implement in a robust manner. Here we report a method to identify genetic interactions in tissue culture cells through RNAi. By performing more than 70,000 pairwise perturbations of signaling factors, we identified >600 interactions affecting different quantitative phenotypes of Drosophila melanogaster cells. Computational analysis of this interaction matrix allowed us to reconstruct signaling pathways and identify a conserved regulator of Ras-MAPK signaling. Large-scale genetic interaction mapping by RNAi is a versatile, scalable approach for revealing gene function and the connectivity of cellular networks.     

A method to estimate the environmental impacts from genetic change in pig production systems

The International Journal of Life Cycle Assessment - The environmental impacts (EIs) of the global pig production sector are expected to increase with increasing global pork demand. Although the...     

Mapping the genetic landscape of DNA double-strand break repair

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A computational method for the investigation of multistable systems and its application to genetic switches

Background

Genetic switches exhibit multistability, form the basis of epigenetic memory, and are found in natural decision making systems, such as cell fate determination in developmental pathways. Synthetic genetic switches can be used for recording the presence of different environmental signals, for changing phenotype using synthetic inputs and as building blocks for higher-level sequential logic circuits. Understanding how multistable switches can be constructed and how they function within larger biological systems is therefore key to synthetic biology.

Results

Here we present a new computational tool, called StabilityFinder, that takes advantage of sequential Monte Carlo methods to identify regions of parameter space capable of producing multistable behaviour, while handling uncertainty in biochemical rate constants and initial conditions. The algorithm works by clustering trajectories in phase space, and iteratively minimizing a distance metric. Here we examine a collection of models of genetic switches, ranging from the deterministic Gardner toggle switch to stochastic models containing different positive feedback connections. We uncover the design principles behind making bistable, tristable and quadristable switches, and find that rate of gene expression is a key parameter. We demonstrate the ability of the framework to examine more complex systems and examine the design principles of a three gene switch. Our framework allows us to relax the assumptions that are often used in genetic switch models and we show that more complex abstractions are still capable of multistable behaviour.

Conclusions

Our results suggest many ways in which genetic switches can be enhanced and offer designs for the construction of novel switches. Our analysis also highlights subtle changes in correlation of experimentally tunable parameters that can lead to bifurcations in deterministic and stochastic systems. Overall we demonstrate that StabilityFinder will be a valuable tool in the future design and construction of novel gene networks.

     

Uncovering the features of population genetic structures by the descriptive method of "genetic landscape"]

It was found that using surnames as genetical markers in rural Russian populations gives adequate results under conditions of working on the area not extending over the territory of 2 or 3 adjacent regions. Schematic drawings of genetic landscapes in 4 regions of the Kirov district and in 2 regions of the Adyg district are presented. Analysis of anomalous features of equidistant lines has been performed.     

Mapping the genetic architecture of complex traits in experimental populations

SUMMARY: Understanding how interactions among set of genes affect diverse phenotypes is having a greater impact on biomedical research, agriculture and evolutionary biology. Mapping and characterizing the isolated effects of single quantitative trait locus (QTL) is a first step, but we also need to assemble networks of QTLs and define non-additive interactions (epistasis) together with a host of potential environmental modulators. In this article, we present a full-QTL model with which to explore the genetic architecture of complex trait in multiple environments. Our model includes the effects of multiple QTLs, epistasis, QTL-by-environment interactions and epistasis-by-environment interactions. A new mapping strategy, including marker interval selection, detection of marker interval interactions and genome scans, is used to evaluate putative locations of multiple QTLs and their interactions. All the mapping procedures are performed in the framework of mixed linear model that are flexible to model environmental factors regardless of fix or random effects being assumed. An F-statistic based on Henderson method III is used for hypothesis tests. This method is less computationally greedy than corresponding likelihood ratio test. In each of the mapping procedures, permutation testing is exploited to control for genome-wide false positive rate, and model selection is used to reduce ghost peaks in F-statistic profile. Parameters of the full-QTL model are estimated using a Bayesian method via Gibbs sampling. Monte Carlo simulations help define the reliability and efficiency of the method. Two real-world phenotypes (BXD mouse olfactory bulb weight data and rice yield data) are used as exemplars to demonstrate our methods. AVAILABILITY: A software package is freely available at http://ibi.zju.edu.cn/software/qtlnetwork     

Simulation of genetic systems

Summary The effects of intense normalizing selection have been studied, using computer simulation, for models of 3, 4, 5, 6, 8, 12 and 24 loci. The effectiveness of such selection in reducing heterozygosity decreases with increase of the number of loci to a limit that is only slightly greater than that consequent from random genetic dispersion, if the loci are freely recombining. Tight linkage markedly reduces the rate of loss of heterozygosity for small numbers of loci, but this effect of tight linkage decreases with increase of the number of loci.

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Zusammenfassung Es wird die Wirkung normalisierender Selektion für 3, 4, 5, 6, 8, 12 und 24 Loci unter Verwendung von Computer-Simulationen untersucht. Die Wirksamkeit derartiger Selektion hinsichtlich der Reduzierung der Heterozygotie nimmt mit zunehmender Zahl der Loci bis zu einem Grenzwert ab, der nur größer ist als der aus zufällinger genetischer Dispersion folgende, wenn die Loci frei miteinander Rekombinieren. Enge Koppelung reduziert die Rate des Heterozygotenverlustes bei kleiner Zahl von Loci beträchtlich, jedoch nimmt dieser Effekt der engen Koppelung mit steigender Zahl der Loci ab.

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This research was supported by NIH Grant GM-11778.     

Epistatic selection opposed by immigration in multiple locus genetic systems

A model of “complete” epistatis is considered in which all “plus” alleles must be present in an individual before the adaptive phenotype is expressed. The conditions under which the plus alleles and hence the adaptive phenotype can increase and reach a stable equilibrium in the presence of immigration of gametes carrying minus alleles are found. In haploids and diploids in which the plus alleles are recessive, frequencies of the plus alleles are the same at all loci, regardless of the linkage relationships. Tight linkage favors the existence of a locally stable polymorphic equilibrium, but the equilibrium with only minus alleles is locally stable unless there is very tight linkage or very strong selection. Thus, this kind of epistasis, which provides a simple model for a character that requires several components to be present at the same time, is very sensitive to even a small amount of immigration. Hence, the evolution of such characters is likely only in completely rather than partially isolated populations.