Relatedness measured by oligonucleotide probe DNA fingerprints and an estimate of the mating system of Sea Lavender (Limonium carolinianum)

Using DNA fingerprint markers within species and populations of wild plants requires information on the relationship between fingerprint similarity and relatedness. We identified a hypervariable marker based on oliog(GATA)₄-hybridization of DpnII-cut genomic DNA from Sea Lavender (Limonium carolinianum). Banding patterns were somatically stable and highly variable among unrelated individuals. Band molecular-weight sizing errors (as a percent of band molecular weight) were estimated at 0.44%±0.003 within gels and 0.76%±0.964 between gels. Band sizing errors defined a 99% confidence bin of ±0.95% (1.90% total) of molecular weight. Band-sharing estimates were based on this bin size and on variance estimates that compensate for non-independent comparisons. Band-sharing among nine unrelated individuals () was 0.198±0.O11. Experimental pollinations designed to produce selfed, fulland half-sib progeny groups led to five selfed progeny groups and no outcrossed progeny (mean band-sharing, ovS=0.468±0.074). A linear regression between band-sharing (S) and relatedness (r) assuming 17% inbreeding was r=0.006+0.914*S (R²=0.973) and established the maximum amount of inbreeding. ovS(0.392±0.022) estimated from wild pollinated seeds from four maternal families was intermediate to unrelated individuals and experimental selfed progeny, giving evidence for mixed mating in wild plants. More extensive plant pedigrees with known levels of inbreeding will be needed to measure variation in the relationship between S and r among populations and families.     

Kin selection under blending inheritance

Why did Darwin fail to develop his insights on kin selection into a proper theory of social adaptation? One suggestion has been that his inadequate understanding of heredity kept the problem out of focus. Here, I determine whether it is possible to develop a quantitative theory of kin selection upon the assumption of blending inheritance. I find that, whilst Hamilton's rule of kin selection can be readily derived under the assumption of blending inheritance, this mechanism complicates the computation of relatedness coefficients, and can even cause them to fluctuate over generations. Nevertheless, I show that the ultimate criterion for selection to favour any social trait - i.e. a time-average of Hamilton's rule - remains the same as under particulate inheritance. By eliminating the gene from the theory of kin selection, I clarify the role that it plays in the theory of social adaptation.     

Cooperation among unrelated individuals: the ant foundress case

Ant foundress associations are an example of cooperation among non-kin. Across a dozen genera, queens able to found a colony alone often join unrelated queens, thereby enhancing worker production and colony survivorship. The benefits of joining other queens vary with group size and ecological conditions. However, after the first workers mature, the queens fight until only one survives. The presence of cofoundresses, and their relative fighting ability, also affects the extent of cooperative investment before worker emergence. This reveals previously overlooked early conflicts among queens, which reduce the mutualistic benefits of cooperation.     

The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years

Background

Marker-assisted selection (MAS) and genomic selection (GS) based on genome-wide marker data provide powerful tools to predict the genotypic value of selection material in plant breeding. However, case-to-case optimization of these approaches is required to achieve maximum accuracy of prediction with reasonable input.

Results

Based on extended field evaluation data for grain yield, plant height, starch content and total pentosan content of elite hybrid rye derived from testcrosses involving two bi-parental populations that were genotyped with 1048 molecular markers, we compared the accuracy of prediction of MAS and GS in a cross-validation approach. MAS delivered generally lower and in addition potentially over-estimated accuracies of prediction than GS by ridge regression best linear unbiased prediction (RR-BLUP). The grade of relatedness of the plant material included in the estimation and test sets clearly affected the accuracy of prediction of GS. Within each of the two bi-parental populations, accuracies differed depending on the relatedness of the respective parental lines. Across populations, accuracy increased when both populations contributed to estimation and test set. In contrast, accuracy of prediction based on an estimation set from one population to a test set from the other population was low despite that the two bi-parental segregating populations under scrutiny shared one parental line. Limiting the number of locations or years in field testing reduced the accuracy of prediction of GS equally, supporting the view that to establish robust GS calibration models a sufficient number of test locations is of similar importance as extended testing for more than one year.

Conclusions

In hybrid rye, genomic selection is superior to marker-assisted selection. However, it achieves high accuracies of prediction only for selection candidates closely related to the plant material evaluated in field trials, resulting in a rather pessimistic prognosis for distantly related material. Both, the numbers of evaluation locations and testing years in trials contribute equally to prediction accuracy.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-556) contains supplementary material, which is available to authorized users.     

Statistical test for detecting overdispersion in offspring number based on kinship information

In this paper, we develop a theory of a new statistic that tests overdispersion in offspring number on the basis of exactly known kinship relationships. The statistic utilizes the sample size and the number of kinship pairs found in a sample, specially the number of mother–offspring (MO) and maternal–half-sibling (MHS) pairs. Given a sufficiently large sample size, the statistic proposed in this paper approximately follows a standard-normal distribution under non-overdispersed conditions (Poisson’s variance). We found that (1) the value of the statistic (\(\ge 2\) or \(<2\)) reasonably indicates whether reproduction is overdispersed at the 5% significance level; (2) the power of the statistic is determined primarily by the balance between the degree of overdispersion and the sample size; (3) in many cases, if the number of kinship pairs can be approximated by a normal distribution, false-positive and false-negative situations can be avoided. The proposed method can detect moderate-weak levels of overdispersion that produce few MHS pairs in a sample because the effect of the population size (which determines the number of detected MHS pairs) is canceled by the detection of the number of MO pairs. Once the kinship determination procedure is established, this indirect measurement will be readily applicable to species even with weak overdispersion, expanding the available opportunities for understanding how overdispersion in offspring number affects ecological processes.     

Natural selection of altruism in inelastic viscous homogeneous populations

Biological explanations are given of three main uninterpreted theoretical results on the selection of altruism in inelastic viscous homogeneous populations, namely that non-overlapping generations hinder the evolution of altruism, fecundity effects are more conducive to altruism than survival effects, and one demographic regime (so-called death-birth) permits altruism whereas another (so-called birth-death) does not. The central idea is ‘circles of compensation’, which measure how far the effects of density dependence extend from a focal individual. Relatednesses can then be calculated that compensate for density dependence. There is very generally a ‘balancing circle of compensation’, at which the viscosity of the population slows up selection of altruism, but does not affect its direction, and this holds for altruism towards any individual, not just immediate neighbours. These explanations are possible because of recent advances in the theory of inclusive fitness on graphs. The assumption of node bitransitivity in that recent theory is relaxed to node transitivity and symmetry of the dispersal matrix, and new formulae show how to calculate relatedness from dispersal and vice versa.     

Informativeness of genetic markers for pairwise relationship and relatedness inference

Measuring the information content of markers in relationship/relatedness inferences is important in selecting highly informative markers to attain a given statistical power with the minimal genotyping effort. Using information-theoretic principles, I introduce the informativeness for relationship (I(R)) and the informativeness for relatedness (I(r)) to measure the amount of information provided by markers in inferring pairwise relationships (R) and relatedness (r), respectively. I also propose a fast and accurate algorithm to calculate the power (PW(R)) of a set of markers in differentiating two candidate relationships, and the reciprocal of the mean squared deviations of relatedness estimates (RMSD) to measure the amount of information of markers actually used by an estimator in estimating relatedness. All of the four measurements (I(R), I(r), PW(R), RMSD) apply to dominant and codominant markers, haploid and diploid individuals, and take into account of mutations and typing errors in data. The statistical properties of the four measurements and their relationships are investigated analytically and are examined by applying these methods to simulated and empirical data.