Recent and Ancient Signature of Balancing Selection around the S-Locus in Arabidopsis halleri and A. lyrata

Balancing selection can maintain different alleles over long evolutionary times. Beyond this direct effect on the molecular targets of selection, balancing selection is also expected to increase neutral polymorphism in linked genome regions, in inverse proportion to their genetic map distances from the selected sites. The genes controlling plant self-incompatibility are subject to one of the strongest forms of balancing selection, and they show clear signatures of balancing selection. The genome region containing those genes (the S-locus) is generally described as nonrecombining, and the physical size of the region with low recombination has recently been established in a few species. However, the size of the region showing the indirect footprints of selection due to linkage to the S-locus is only roughly known. Here, we improved estimates of this region by surveying synonymous polymorphism and estimating recombination rates at 12 flanking region loci at known physical distances from the S-locus region boundary, in two closely related self-incompatible plants Arabidopsis halleri and A. lyrata. In addition to studying more loci than previous studies and using known physical distances, we simulated an explicit demographic scenario for the divergence between the two species, to evaluate the extent of the genomic region whose diversity departs significantly from neutral expectations. At the closest flanking loci, we detected signatures of both recent and ancient indirect effects of selection on the S-locus flanking genes, finding ancestral polymorphisms shared by both species, as well as an excess of derived mutations private to either species. However, these effects are detected only in a physically small region, suggesting that recombination in the flanking regions is sufficient to quickly break up linkage disequilibrium with the S-locus. Our approach may be useful for distinguishing cases of ancient versus recently evolved balancing selection in other systems

ZRT1 harbors an excess of nonsynonymous polymorphism and shows evidence of balancing selection in Saccharomyces cerevisiae

Estimates of the fraction of nucleotide substitutions driven by positive selection vary widely across different species. Accounting for different estimates of positive selection has been difficult, in part because selection on polymorphism within a species is known to obscure a signal of positive selection between species. While methods have been developed to control for the confounding effects of negative selection against deleterious polymorphism, the impact of balancing selection on estimates of positive selection has not been assessed. In Saccharomyces cerevisiae, there is no signal of positive selection within protein coding sequences as the ratio of nonsynonymous to synonymous polymorphism is higher than that of divergence. To investigate the impact of balancing selection on estimates of positive selection we examined five genes with high rates of nonsynonymous polymorphism in S. cerevisiae relative to divergence from S. paradoxus. One of the genes, a high affinity zinc transporter ZRT1, shows an elevated rate of synonymous polymorphism indicative of balancing selection. The high rate of synonymous polymorphism coincides with nonsynonymous divergence between three haplotype groups, which we find to be functionally indistinguishable. We conclude that balancing selection is not likely to be a common cause of genes harboring a large excess of nonsynonymous polymorphism in yeast

Criteria for the Optimal Design of a Social Security Retirement System

This paper discusses a series of selection points in the design and financing of social security retirement systems. For each criterion, the paper lists and discusses advantages and disadvantages of the options available. The selection points include (1) Funded versus PAYGO; (2) Minimum benefits, Demogrant or Welfare; (3) Progressive versus Regressive; (4) Voluntary versus Mandatory; (5) Individual Accounts versus Commingling of Risk (6) Public versus Private sourcing; (7) Automatic Balancing Mechanisms; (8) System Risk Diversification. It is the sincere hope of the author that this discussion will create even more debate of the issues surrounding these important selection criteria which, in turn, will result in better social security retirement systems for all.Social Security design and financing, Funded pay-as-you-go, Individual Accounts, Automatic Balancing Mechanisms

Detecting signatures of balancing selection to identify targets of anti-parasite immunity.

Parasite antigen genes might evolve under frequency-dependent immune selection. The distinctive patterns of polymorphism that result can be detected using population genetic methods that test for signatures of balancing selection, allowing genes encoding important targets of immunity to be identified. Analyses can be complicated by population structures, histories and features of a parasite's genome. However, new sequencing technologies facilitate scans of polymorphism throughout parasite genomes to identify the most exceptional gene specific signatures. We focus on malaria parasites to illustrate challenges and opportunities for detecting targets of frequency-dependent immune selection to discover new potential vaccine candidates

Balancing Conflict and Cost in the Selection of Negotiation Opponents

Within the context of agent-to-agent purchase negotiations, a problem that has received little attention is that of identifying negotiation opponents in situations where the consequences of conflict and the ability to access resources dynamically vary. Such dynamism poses a number of problems that make it difficult to automate the identification of appropriate opponents. To that end, this paper describes a motivation-based opponent selection mechanism used by a buyer-agent to evaluate and select between an already identified set of seller-agents. Sellers are evaluated in terms of the amount of conflict they are expected to bring to a negotiation and the expected amount of cost a negotiation with them will entail. The mechanism allows trade-offs to be made between conflict and cost minimisation, and experimental results show the effectiveness of the approach

Lepskii Principle in Supervised Learning

In the setting of supervised learning using reproducing kernel methods, we propose a data-dependent regularization parameter selection rule that is adaptive to the unknown regularity of the target function and is optimal both for the least-square (prediction) error and for the reproducing kernel Hilbert space (reconstruction) norm error. It is based on a modified Lepskii balancing principle using a varying family of norms