Interpreting selection when individuals interact

A useful interpretation of quantitative genetic models of evolutionary change is that they (i) define a set of phenotypes that have a causal effect on fitness and on which selection acts, and (ii) define a set of breeding values that change as a correlated response to that selection because they covary with the phenotypes. When the expression of one trait causes variation in other traits then there are multiple paths by which a trait can cause fitness variation. Because of this, there are multiple ways in which selection can be defined, and still be consistent with a causal effect of traits on fitness. We use this result to show that genetical theories of natural/kin selection ignore causation and because of this we suggest they shed little light on the nature of selection. When traits expressed by an individual are affected by traits of their social partners (indirect genetic effects), we suggest a causal partitioning that allows selection to be cast in terms of Hamilton's costs and benefits. We show that previous attempts to understand Hamilton's rule in the context of indirect genetic effects either lack generality, or do not adequately describe all the ways in which an individual's actions constitute a cost to the individual or a benefit to its social partner(s). Our results allow us to explore Hamilton's rule in a multitrait setting. We show that evolution always increases inclusive fitness, and when the traits are measured in units of generalised genetic distance evolutionary change in the traits is in the direction in which inclusive fitness increases the fastest. However, we show that Hamilton's rule only holds in a multitrait context when the suite of traits are at equilibrium. When they are out of equilibrium, the conditions for altruism to evolve may be more or less stringent depending on genetic architecture and how costs and benefits are defined.</p

Genomic, Marker-Assisted, and Pedigree-BLUP Selection Methods for β-Glucan Concentration in Elite Oat

β-glucan, a soluble fiber found in oat (Avena sativa L.) grain, is good for human health, and selection for higher levels of this compound is regarded as an important breeding objective. Recent advances in oat DNA markers present an opportunity to investigate new selection methods for polygenic traits such as β-glucan concentration. Our objectives in this study were to compare genomic, marker-assisted, and best linear unbiased prediction (BLUP)–based phenotypic selection for short-term response to selection and ability to maintain genetic variance for β-glucan concentration. Starting with a collection of 446 elite oat lines from North America, each method was conducted for two cycles. The average β-glucan concentration increased from 4.57 g/100 g in Cycle 0 to between 6.66 and 6.88 g/100 g over the two cycles. The averages of marker-based selection methods in Cycle 2 were greater than those of phenotypic selection (P \u3c 0.08). Progenies with the highest β-glucan came from the marker-based selection methods. Marker-assisted selection (MAS) for higher β-glucan concentration resulted in a later heading date. We also found that marker-based selection methods maintained greater genetic variance than did BLUP phenotypic selection, potentially enabling greater future selection gains. Overall, the results of these experiments suggest that genomic selection is a superior method for selecting a polygenic complex trait like β-glucan concentration

Inter-individual genetic variation in the temperature response of Leptosphaeria species pathogenic on oilseed rape

It is important to understand the likely response of plant pathogens to increased temperatures due to anthropogenic climate change. This includes evolutionary change due to selection on genetically based variation in growth rate with temperature. We attempted to quantify this in two ways. First, radial mycelial growth rates in agar culture were determined for a collection of 44 English isolates of Leptosphaeria maculans and 17 isolates of L. biglobosa, at 14 temperatures. For L. maculans the genetic variances in four parameters were measured: minimum temperature allowing growth, optimum temperature, growth rate at the optimum temperature and growth rate at the highest usable temperature, 31.8°C. The standard deviations were 0.068 °C , 1.28°C, 0.21 mm day-1 and 0.31 mm day 1 °C-1 respectively. For L. biglobosa, these figures were, respectively: immeasurably small, 1.31 °C, 0.053 mm day-1 and 0.53 mm day- °C-1. In addition, the incidence and severity of phoma stem canker in planta over a natural growing cycle at four temperatures (16°C, 20°C, 24°C and 28°C) around the average culture optimum were determined. There was no correlation between in vitro and in planta growth, and the decrease in pathogen measures either side of the optimum temperature was much less for in planta growth than for in vitro growth. We conclude that both pathogens have the capacity to evolve to adapt to changes in environmental conditions, but that predictions of the effect of this adaptation, or estimates of heritability in natural conditions, cannot be made from measurements in vitro

Solar Magnetic Feature Detection and Tracking for Space Weather Monitoring

We present an automated system for detecting, tracking, and cataloging emerging active regions throughout their evolution and decay using SOHO Michelson Doppler Interferometer (MDI) magnetograms. The SolarMonitor Active Region Tracking (SMART) algorithm relies on consecutive image differencing to remove both quiet-Sun and transient magnetic features, and region-growing techniques to group flux concentrations into classifiable features. We determine magnetic properties such as region size, total flux, flux imbalance, flux emergence rate, Schrijver's R-value, R* (a modified version of R), and Falconer's measurement of non-potentiality. A persistence algorithm is used to associate developed active regions with emerging flux regions in previous measurements, and to track regions beyond the limb through multiple solar rotations. We find that the total number and area of magnetic regions on disk vary with the sunspot cycle. While sunspot numbers are a proxy to the solar magnetic field, SMART offers a direct diagnostic of the surface magnetic field and its variation over timescale of hours to years. SMART will form the basis of the active region extraction and tracking algorithm for the Heliophysics Integrated Observatory (HELIO)

Measuring Selection when Parents and Offspring Interact

Non-social and social selection gradients are key evolutionary parameters in systems where individuals interact. They are most easily obtained by regressing an individual's fitness on the trait values of the individual and its social partner. In the context of parental care it is more common to regress the trait value of the parents (i.e. the social partner) on a ‘mixed’ fitness measure that is a function of the parent's and offspring's fitness (for example, the number of recruits, which equals parental fecundity multiplied by offspring survival). For such an approach to yield correct estimates of net-selection, the trait must be sex-limited and not affect the parents’ own survival. When a trait is not sex-limited, the non-social selection should be weighted by one (because all individuals express the trait) and social selection should be weighted by a half (because the relatedness between parents and the offspring they care for is a half, usually). The ‘mixed’ fitness approach does not give estimates of both components of selection and so they cannot be weighted appropriately. We show that mixed fitness components are frequently used in place of direct fitness measures in the literature (37% of fecundity selection estimates use a mixed fitness approach), but that the frequency is much higher in some taxa, such as birds and mammals. We suggest alternative methods that could be used to estimate both social and non-social selection gradients, while at the same time assessing the importance of unmeasured traits

Genome-wide Association Study for Beta-glucan Concentration in Elite North American Oat

Genome-wide association studies (GWAS) can be a useful approach to detect quantitative trait loci (QTL) controlling complex traits in crop plants. Oat (Avena sativa L.) β-glucan is a soluble dietary fiber and has been shown to have positive health benefits. We report a GWAS involving 446 elite oat breeding lines from North America genotyped with 1005 diversity arrays technology (DArT) markers and with phenotypic data from both historical and balanced 2-yr data. Association analyses accounting for pair-wise relationships and population structure were conducted using single-marker tests and least absolute shrinkage and selection operator (LASSO). Single-marker tests yielded six and 15 significant markers for the historical and balanced data sets, respectively. The LASSO method selected 24 and 37 markers as the most important in explaining β-glucan concentration for the historical and balanced data sets, respectively. Comparisons of genetic location showed that 15 of the markers in our study were found on the same linkage groups as QTL identified in previous studies. Four of the markers colocalized to within 4 cM of three previously detected QTL, suggesting concordance between QTL detected in our study and previous studies. Two of the significant markers were also adjacent to a β-glucan candidate gene in the rice (Oryza sativa L.) genome. Our findings suggest that GWAS can be used for QTL detection for the purpose of gene discovery and for marker-assisted selection to improve β-glucan concentration in elite oat

Genetic and environmental influences on Anxious/Depression during childhood: a study from the Netherlands Twin Register

For a large sample of twin pairs from the Netherlands Twins Register who were recruited at birth and followed through childhood, we obtained parental ratings of Anxious/Depression (A/D). Maternal ratings were obtained at ages 3 years (for 9025 twin pairs), 5 years (9222 pairs), 7 years (7331 pairs), 10 years (4430 pairs) and 12 years (2363 pairs). For 60-90% of the pairs, father ratings were also available. Multivariate genetic models were used to test for rater-independent and rater-specific assessments of A/D and to determine the genetic and environmental influences on individual differences in A/D at different ages. At all ages, monozygotic twins resembled each other more closely for A/D than dizygotic twins, implying genetic influences on variation in A/D. Opposite sex twin pairs resembled each other to same extent as same-sex dizygotic twins, suggesting that the same genes are expressed in boys and girls. Heritability estimates for rater-independent A/D were high in 3-year olds (76%) and decreased in size as children grew up [60% at age 5, 67% at age 7, 53% at age 10 (60% in boys) and 48% at age 12 years]. The decrease in genetic influences was accompanied by an increase in the influence of the shared family environment [absent at ages 3 and 7, 16% at age 5, 20% at age 10 (5% in boys) and 18% at age 12 years]. The agreement between parental A/D ratings was between 0.5 and 0.7, with somewhat higher correlations for the youngest group. Disagreement in ratings between the parents was not merely the result of unreliability or rater bias. Both the parents provided unique information from their own perspective on the behavior of their children. Significant influences of genetic and shared environmental factors were found for the unique parental views. At all ages, the contribution of shared environmental factors to variation in rater-specific views was higher for father ratings. Also, at all ages except age 12, the heritability estimates for the rater-specific phenotype were higher for mother ratings (59% at age 3 and decreasing to 27% at age 12 years) than for father ratings (between 14 and 29%). Differences between children, even as young as 3 years, in A/D are to a large extent due to genetic differences. As children grow up, the variation in A/D is due in equal parts to genetic and environmental influences. Anxious/Depression, unlike many other common childhood psychopathologies, is influenced by the shared family environment. These findings may provide support for why certain family therapeutic approaches are effective in the A/D spectrum of illnesses. Copyright © Blackwell Munksgaard 2005

Statistics and geometry of cosmic voids

We introduce new statistical methods for the study of cosmic voids, focusing on the statistics of largest size voids. We distinguish three different types of distributions of voids, namely, Poisson-like, lognormal-like and Pareto-like distributions. The last two distributions are connected with two types of fractal geometry of the matter distribution. Scaling voids with Pareto distribution appear in fractal distributions with box-counting dimension smaller than three (its maximum value), whereas the lognormal void distribution corresponds to multifractals with box-counting dimension equal to three. Moreover, voids of the former type persist in the continuum limit, namely, as the number density of observable objects grows, giving rise to lacunar fractals, whereas voids of the latter type disappear in the continuum limit, giving rise to non-lacunar (multi)fractals. We propose both lacunar and non-lacunar multifractal models of the cosmic web structure of the Universe. A non-lacunar multifractal model is supported by current galaxy surveys as well as cosmological $N$-body simulations. This model suggests, in particular, that small dark matter halos and, arguably, faint galaxies are present in cosmic voids.Comment: 39 pages, 8 EPS figures, supersedes arXiv:0802.038

Familial influences on sustained attention and inhibition in preschoolers

Background: In this study several aspects of attention were studied in 237 nearly 6-year-old twin pairs. Specifically, the ability to sustain attention and inhibition were investigated using a computerized test battery (Amsterdam Neuropsychological Tasks). Furthermore, the Teacher's Report Form (TRF) was filled out by the teacher of the child and the attention subscale of this questionnaire was analyzed. Methods: The variance in performance on the different tasks of the test battery and the score on the attention scale of the TRF were decomposed into a contribution of the additive effects of many genes (A), environmental effects that are shared by twins (C) and unique environmental influences not shared by twins (E) by using data from MZ and DZ twins. Results: The genetic model fitting results showed an effect of A and E for the attention scale of the TRF, and for some of the inhibition and sustained attention measures. For most of the attention variables, however, it was not possible to decide between a model with A and E or a model with C and E. Time-on-task effects on reaction time or number of errors and the delay after making an error did not show familial resemblances. A remarkable finding was that the heritability of the attention scale of the TRF was found to be higher than the heritability of indices that can be considered to be more direct measures of attention, such as mean tempo in the sustained attention task and response speed in the Go-NoGo task. Conclusion: In preschoolers, familial resemblances on sustained attention and inhibition were observed. © Association for Child Psychology and Psychiatry, 2004