30 resultados para Genetic Programming, NPR, Evolutionary Art
em University of Queensland eSpace - Australia
Resumo:
An absence of genetic variance in traits under selection is perhaps the oldest explanation for a limit to evolutionary change, but has also been the most easily dismissed. We review a range of theoretical and empirical results covering single traits to more complex multivariate systems, and show that an absence of genetic variance may be more common than is currently appreciated. From a single-trait perspective, we highlight that it is becoming clear that some trait types do not display significant levels of genetic variation, and we raise the possibility that species with restricted ranges may differ qualitatively from more widespread species in levels of genetic variance in ecologically important traits. A common misconception in many life-history studies is that a lack of genetic variance in single traits, and genetic constraints as a consequence of bivariate genetic correlations, are different causes of selection limits. We detail how interpretations of bivariate patterns are unlikely to demonstrate genetic limits to selection in many cases. We advocate a multivariate definition of genetic constraints that emphasizes the presence (or otherwise) of genetic variance in the multivariate direction of selection. For multitrait systems, recent results using longer term studies of organisms, in which more is understood concerning what traits may be under selection, have indicated that selection may exhaust genetic variance, resulting in a limit to the selection response.
Resumo:
We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.
Resumo:
Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (
Resumo:
Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (
Resumo:
There is a wealth of literature documenting a directional change of body size in heavily harvested populations. Most of this work concentrates on aquatic systems, but terrestrial populations are equally at risk. This paper explores the capacity of harvest refuges to counteract potential effects of size-selective harvesting on the allele frequency,of populations. We constructed a stochastic, individual-based model parameterized with data on red kangaroos. Because we do not know which part of individual growth would change in the course of natural selection, we explored the effects of two alternative models of individual growth in which alleles affect either the growth rate or the maximum size. The model results show that size-selective harvesting can result in significantly smaller kangaroos for a given age when the entire population is subject to harvesting. In contrast, in scenarios that include dispersal from harvest refuges, the initial allele frequency remains virtually unchanged.
Resumo:
We examined the genetic basis of clinal adaptation by determining the evolutionary response of life-history traits to laboratory natural selection along a gradient of thermal stress in Drosophila serrata. A gradient of heat stress was created by exposing larvae to a heat stress of 36degrees for 4 hr for 0, 1, 2, 3, 4, or 5 days of larval development, with the remainder of development taking place at 25degrees. Replicated lines were exposed to each level of this stress every second generation for 30 generations. At the end of selection, we conducted a complete reciprocal transfer experiment where all populations were raised in all environments, to estimate the realized additive genetic covariance matrix among clinal environments in three life-history traits. Visualization of the genetic covariance functions of the life-history traits revealed that the genetic correlation between environments generally declined as environments became more different and even became negative between the most different environments in some cases. One exception to this general pattern was a life-history trait representing the classic trade-off between development time and body size, which responded to selection in a similar genetic fashion across all environments. Adaptation to clinal environments may involve a number of distinct genetic effects along the length of the cline, the complexity of which may not be fully revealed by focusing primarily on populations at the ends of the cline.
Resumo:
The houbara bustard, Chlamydotis undulata, is a declining cryptic desert bird whose range extends from North Africa to Central Asia. Three subspecies are currently recognized by geographical distribution and morphology: C.u.fuertaventurae, C.u.undulata and C.u.macqueenii. We have sequenced 854 bp of mitochondrial control region from 73 birds to describe their population genetic structure with a particular sampling focus on the connectivity between C.u.fuertaventurae and C.u.undulata along the Atlantic seaboard of North Africa. Nucleotide and haplotypic diversity varied among the subspecies being highest in C.u.undulata, lowest in C.u.fuertaventurae and intermediate in C.u.macqueenii. C.u.fuertaventurae and C.u.undulata are paraphyletic and an average nucleotide divergence of 2.08% splits the later from C.u.macqueenii. We estimate that C.u.fuertaventurae and C.u.undulata split from C.u.macqueenii approximately 430 000 years ago. C.u.fuertaventurae and C.u.undulata are weakly differentiated (F-ST = 0.27, N-m = 1.3), indicative of a recent shared history. Archaeological evidence indicates that houbara bustards have been present on the Canary Islands for 130-170 000 years. However, our genetic data point to a more recent separation of C.u.fuertaventurae and C.u.undulata at around 20-25 000 years. Concordant archaeological, climatic opportunities for colonization and genetic data point to a scenario of: (i) initial colonization of the Canary Islands about 130 000 years ago; (ii) a period of secondary contact 19-30 000 years ago homogenizing any pre-existing genetic structure followed by; (iii) a period of relative isolation that persists today.
Resumo:
Conservation of genetic resources is a recognised necessity for the long term maintenance of evolutionary potential. Effective assessment and implementation Strategies are required to permit rapid evaluation and protection of resources. Here we use information from the chloroplast, total genome and quantitative characters assayed across wide-ranging populations to assess genetic resources in a Neotropical tree, Cedrela odorata. A major differentiation identified for organelle, total genomic and quantitative variation was found to coincide with an environmental gradient across Costa Rica. However, a major evolutionary divergence between the Yucatan region and Honduras/Nicaragua identified within the chloroplast genome was not differentiated using quantitative characters. Based on these and other results, a three-tiered conservation genetic prioritisation process is recommended. In order of importance, and where information is available, conservation units should be defined using quantitative (expressed genes), nuclear (genetic connectivity) and organellar (evolutionary) measures. Where possible, information from range wide and local scale studies should be combined and emphasis should be placed on coincidental disjunctions for two or more measures. However, if only rapid assessments of diversity are possible, then assessment of organelle variation provides the most cautious assessment of genetic resources, at least for C. odorata, and can be used to propose initial conservation units. When considering effective implementation of genetic resource management strategies a final tier should be considered, that of landuse/geopolitical divisions. (C) 2004 Elsevier B.V. All rights reserved.
Resumo:
Sustainable forest restoration and management practices require a thorough understanding of the influence that habitat fragmentation has on the processes shaping genetic variation and its distribution in tree populations. We quantified genetic variation at isozyme markers and chloroplast DNA (cpDNA), analysed by polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) in severely fragmented populations of Sorbus aucuparia (Rosaceae) in a single catchment (Moffat) in southern Scotland. Remnants maintain surprisingly high levels of gene diversity (H-E) for isozymes (H-E = 0.195) and cpDNA markers (H-E = 0.490). Estimates are very similar to those from non-fragmented populations in continental Europe, even though the latter were sampled over a much larger spatial scale. Overall, no genetic bottleneck or departures from random mating were detected in the Moffat fragments. However, genetic differentiation among remnants was detected for both types of marker (isozymes Theta(n) = 0.043, cpDNA Theta(c) = 0.131; G-test, P-value < 0.001). In this self-incompatible, insect-pollinated, bird-dispersed tree species, the estimated ratio of pollen flow to seed flow between fragments is close to 1 (r = 1.36). Reduced pollen-mediated gene flow is a likely consequence of habitat fragmentation, but effective seed dispersal by birds is probably helping to maintain high levels of genetic diversity within remnants and reduce genetic differentiation between them.
Resumo:
Genetic assignment methods use genotype likelihoods to draw inference about where individuals were or were not born, potentially allowing direct, real-time estimates of dispersal. We used simulated data sets to test the power and accuracy of Monte Carlo resampling methods in generating statistical thresholds for identifying F-0 immigrants in populations with ongoing gene flow, and hence for providing direct, real-time estimates of migration rates. The identification of accurate critical values required that resampling methods preserved the linkage disequilibrium deriving from recent generations of immigrants and reflected the sampling variance present in the data set being analysed. A novel Monte Carlo resampling method taking into account these aspects was proposed and its efficiency was evaluated. Power and error were relatively insensitive to the frequency assumed for missing alleles. Power to identify F-0 immigrants was improved by using large sample size (up to about 50 individuals) and by sampling all populations from which migrants may have originated. A combination of plotting genotype likelihoods and calculating mean genotype likelihood ratios (D-LR) appeared to be an effective way to predict whether F-0 immigrants could be identified for a particular pair of populations using a given set of markers.
Resumo:
There is concern that the commercial harvest of kangaroos (Macropus spp.) is affecting species fitness and evolutionary potential because the harvest selects for larger individuals, particularly males. This paper reviews the likely effect of selective harvesting on specific traits associated with fitness, including size, and on adaptive genotypes through generalised loss of gene diversity. Heritability for traits associated with fitness is low generally. The intensity of selection imposed by harvesting is low for several reasons: the geographic size of genetic populations is much larger than the harvest localities, which are therefore not closed but open with immigration acting to correct any change in allele frequencies through harvesting; the harvest targets kangaroos above a threshold weight that includes all adult males, not the largest males specifically; larger, older males may not confer significant fitness benefits on offspring; fitness traits are inherited through both sexes while males are targeted predominantly; populations are not at a selective equilibrium because food availability fluctuates, and the fittest is unlikely to be the largest. Comparisons of harvested and unharvested populations do not show any loss of gene diversity as a result of harvesting. The likelihood of a long-term genetic impact of kangaroo harvesting as currently practiced is negligible.
Resumo:
Genetic diversity and population structure were investigated across the core range of Tasmanian devils (Sarcophilus laniarius; Dasyuridae), a wide-ranging marsupial carnivore restricted to the island of Tasmania. Heterozygosity (0.386-0.467) and allelic diversity (2.7-3.3) were low in all subpopulations and allelic size ranges were small and almost continuous, consistent with a founder effect. Island effects and repeated periods of low population density may also have contributed to the low variation. Within continuous habitat, gene flow appears extensive up to 50 km (high assignment rates to source or close neighbour populations; nonsignificant values of pairwise F-ST), in agreement with movement data. At larger scales (150-250 km), gene flow is reduced (significant pairwise F-ST) but there is no evidence for isolation by distance. The most substantial genetic structuring was observed for comparisons spanning unsuitable habitat, implying limited dispersal of devils between the well-connected, eastern populations and a smaller northwestern population. The genetic distinctiveness of the northwestern population was reflected in all analyses: unique alleles; multivariate analyses of gene frequency (multidimensional scaling, minimum spanning tree, nearest neighbour); high self-assignment (95%); two distinct populations for Tasmania were detected in isolation by distance and in Bayesian model-based clustering analyses. Marsupial carnivores appear to have stronger population subdivisions than their placental counterparts.
Resumo:
Inferring the spatial expansion dynamics of invading species from molecular data is notoriously difficult due to the complexity of the processes involved. For these demographic scenarios, genetic data obtained from highly variable markers may be profitably combined with specific sampling schemes and information from other sources using a Bayesian approach. The geographic range of the introduced toad Bufo marinus is still expanding in eastern and northern Australia, in each case from isolates established around 1960. A large amount of demographic and historical information is available on both expansion areas. In each area, samples were collected along a transect representing populations of different ages and genotyped at 10 microsatellite loci. Five demographic models of expansion, differing in the dispersal pattern for migrants and founders and in the number of founders, were considered. Because the demographic history is complex, we used an approximate Bayesian method, based on a rejection-regression algorithm. to formally test the relative likelihoods of the five models of expansion and to infer demographic parameters. A stepwise migration-foundation model with founder events was statistically better supported than other four models in both expansion areas. Posterior distributions supported different dynamics of expansion in the studied areas. Populations in the eastern expansion area have a lower stable effective population size and have been founded by a smaller number of individuals than those in the northern expansion area. Once demographically stabilized, populations exchange a substantial number of effective migrants per generation in both expansion areas, and such exchanges are larger in northern than in eastern Australia. The effective number of migrants appears to be considerably lower than that of founders in both expansion areas. We found our inferences to be relatively robust to various assumptions on marker. demographic, and historical features. The method presented here is the only robust, model-based method available so far, which allows inferring complex population dynamics over a short time scale. It also provides the basis for investigating the interplay between population dynamics, drift, and selection in invasive species.