Endogenous games and mechanisms: Side payments among players

We characterize the outcomes of games when players may make binding offers of strategy contingent side payments before the game is played. This does not always lead to efficient outcomes, despite complete information and costless contracting. The characterizations are illustrated in a series of examples, including voluntary contribution public good games, Cournot and Bertrand oligopoly, principal–agent problems, and commons games, among others

Type III Effector Diversification via Both Pathoadaptation and Horizontal Transfer in Response to a Coevolutionary Arms Race

The concept of the coevolutionary arms race holds a central position in our understanding of pathogen–host interactions. Here we identify the molecular mechanisms and follow the stepwise progression of an arms race in a natural system. We show how the evolution and function of the HopZ family of type III secreted effector proteins carried by the plant pathogen Pseudomonas syringae are influenced by a coevolutionary arms race between pathogen and host. We surveyed 96 isolates of P. syringae and identified three homologs (HopZ1, HopZ2, and HopZ3) distributed among ∼45% of the strains. All alleles were sequenced and their expression was confirmed. Evolutionary analyses determined that the diverse HopZ1 homologs are ancestral to P. syringae, and have diverged via pathoadaptive mutational changes into three functional and two degenerate forms, while HopZ2 and HopZ3 have been brought into P. syringae via horizontal transfer from other ecologically similar bacteria. A PAML selection analysis revealed that the C terminus of HopZ1 is under strong positive selection. Despite the extensive genetic variation observed in this family, all three homologs have cysteine–protease activity, although their substrate specificity may vary. The introduction of the ancestral hopZ1 allele into strains harboring alternate alleles results in a resistance protein-mediated defense response in their respective hosts, which is not observed with the endogenous allele. These data indicate that the P. syringae HopZ family has undergone allelic diversification via both pathoadaptive mutational changes and horizontal transfer in response to selection imposed by the host defense system. This genetic diversity permits the pathogen to avoid host defenses while still maintaining a virulence-associated protease, thereby allowing it to thrive on its current host, while simultaneously impacting its host range

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Computational Prediction and Molecular Characterization of an Oomycete Effector and the Cognate Arabidopsis Resistance Gene

Hyaloperonospora arabidopsidis (Hpa) is an obligate biotroph oomycete pathogen of the model plant Arabidopsis thaliana and contains a large set of effector proteins that are translocated to the host to exert virulence functions or trigger immune responses. These effectors are characterized by conserved amino-terminal translocation sequences and highly divergent carboxyl-terminal functional domains. The availability of the Hpa genome sequence allowed the computational prediction of effectors and the development of effector delivery systems enabled validation of the predicted effectors in Arabidopsis. In this study, we identified a novel effector ATR39-1 by computational methods, which was found to trigger a resistance response in the Arabidopsis ecotype Weiningen (Wei-0). The allelic variant of this effector, ATR39-2, is not recognized, and two amino acid residues were identified and shown to be critical for this loss of recognition. The resistance protein responsible for recognition of the ATR39-1 effector in Arabidopsis is RPP39 and was identified by map-based cloning. RPP39 is a member of the CC-NBS-LRR family of resistance proteins and requires the signaling gene NDR1 for full activity. Recognition of ATR39-1 in Wei-0 does not inhibit growth of Hpa strains expressing the effector, suggesting complex mechanisms of pathogen evasion of recognition, and is similar to what has been shown in several other cases of plant-oomycete interactions. Identification of this resistance gene/effector pair adds to our knowledge of plant resistance mechanisms and provides the basis for further functional analyses

Study of Upsilon(3S,2S) -> eta Upsilon(1S) and Upsilon(3S,2S) -> pi+pi- Upsilon(1S) hadronic trasitions

We study the Upsilon(3S,2S)->eta Upsilon(1S) and Upsilon(3S,2S)->pi+pi- Upsilon(1S) transitions with 122 million Upsilon(3S) and 100 million Upsilon(2S) mesons collected by the BaBar detector at the PEP-II asymmetric energy e+e- collider. We measure B[Upsilon(2S)->eta Upsilon(1S)]=(2.39+/-0.31(stat.)+/-0.14(syst.))10^-4 and Gamma[Upsilon(2S)->eta Upsilon(1S)]/Gamma[Upsilon(2S)-> pi+pi- Upsilon(1S)]=(1.35+/-0.17(stat.)+/-0.08(syst.))10^-3. We find no evidence for Upsilon(3S)->eta Upsilon(1S) and obtain B[Upsilon(3S)->eta Upsilon(1S)]<1.0 10^-4 and Gamma[Upsilon(3S)->eta Upsilon(1S)]/Gamma[Upsilon(3S)->pi+pi- Upsilon(1S)]<2.3 10^-3 as upper limits at the 90% confidence level. We also provide improved measurements of the Upsilon(2S) - Upsilon(1S) and Upsilon(3S) - Upsilon(1S) mass differences, 562.170+/-0.007(stat.)+/-0.088(syst.) MeV/c^2 and 893.813+/-0.015(stat.)+/-0.107(syst.) MeV/c^2 respectively.Comment: 8 pages, 16 encapsulated postscript figures, submitted to Phys.Rev.

Observation and study of baryonic B decays: B -> D(*) p pbar, D(*) p pbar pi, and D(*) p pbar pi pi

We present a study of ten B-meson decays to a D(*), a proton-antiproton pair, and a system of up to two pions using BaBar's data set of 455x10^6 BBbar pairs. Four of the modes (B0bar -> D0 p anti-p, B0bar -> D*0 p anti-p, B0bar -> D+ p anti-p pi-, B0bar -> D*+ p anti-p pi-) are studied with improved statistics compared to previous measurements; six of the modes (B- -> D0 p anti-p pi-, B- -> D*0 p anti-p pi-, B0bar -> D0 p anti-p pi- pi+, B0bar -> D*0 p anti-p pi- pi+, B- -> D+ p anti-p pi- pi-, B- -> D*+ p anti-p pi- pi-) are first observations. The branching fractions for 3- and 5-body decays are suppressed compared to 4-body decays. Kinematic distributions for 3-body decays show non-overlapping threshold enhancements in m(p anti-p) and m(D(*)0 p) in the Dalitz plots. For 4-body decays, m(p pi-) mass projections show a narrow peak with mass and full width of (1497.4 +- 3.0 +- 0.9) MeV/c2, and (47 +- 12 +- 4) MeV/c2, respectively, where the first (second) errors are statistical (systematic). For 5-body decays, mass projections are similar to phase space expectations. All results are preliminary.Comment: 28 pages, 90 postscript figures, submitted to LP0

Evidence for the h_b(1P) meson in the decay Upsilon(3S) --> pi0 h_b(1P)

Using a sample of 122 million Upsilon(3S) events recorded with the BaBar detector at the PEP-II asymmetric-energy e+e- collider at SLAC, we search for the $h_b(1P)$ spin-singlet partner of the P-wave chi_{bJ}(1P) states in the sequential decay Upsilon(3S) --> pi0 h_b(1P), h_b(1P) --> gamma eta_b(1S). We observe an excess of events above background in the distribution of the recoil mass against the pi0 at mass 9902 +/- 4(stat.) +/- 2(syst.) MeV/c^2. The width of the observed signal is consistent with experimental resolution, and its significance is 3.1sigma, including systematic uncertainties. We obtain the value (4.3 +/- 1.1(stat.) +/- 0.9(syst.)) x 10^{-4} for the product branching fraction BF(Upsilon(3S)-->pi0 h_b) x BF(h_b-->gamma eta_b).Comment: 8 pages, 4 postscript figures, submitted to Phys. Rev. D (Rapid Communications

Bacterial genomic G + C composition-eliciting environmental adaptation

Bacterial genomes reflect their adaptation strategies through nucleotide usage trends found in their chromosome composition. Bacteria, unlike eukaryotes contain a wide range of genomic G + C. This wide variability may be viewed as a response to environmental adaptation. Two overarching trends are observed across bacterial genomes, the first, correlates genomic G + C to environmental niches and lifestyle, while the other utilizees intra-genomic G + C incongruence to delineate horizontally transferred material. In this review, we focus on the influence of several properties including biochemical, genetic flows, selection biases, and the biochemical-energetic properties shaping genome composition. Outcomes indicate a trend toward high G + C and larger genomes in free-living organisms, as a result of more complex and varied environments (higher chance for horizontal gene transfer). Conversely, nutrient limiting and nutrient poor environments dictate smaller genomes of low GC in attempts to conserve replication expense. Varied processes including translesion repair mechanisms, phage insertion and cytosine degradation has been shown to introduce higher AT in genomic sequences. We conclude the review with an analysis of current bioinformatics tools seeking to elicit compositional variances and highlight the practical implications when using such techniques