Genomic Analysis of Pseudomonas putida Phage tf with Localized Single-Strand DNA Interruptions

The complete sequence of the 46,267 bp genome of the lytic bacteriophage tf specific to Pseudomonas putida PpG1 has been determined. The phage genome has two sets of convergently transcribed genes and 186 bp long direct terminal repeats. The overall genomic architecture of the tf phage is similar to that of the previously described Pseudomonas aeruginosa phages PaP3, LUZ24 and phiMR299-2, and 39 out of the 72 products of predicted tf open reading frames have orthologs in these phages. Accordingly, tf was classified as belonging to the LUZ24-like bacteriophage group. However, taking into account very low homology levels between tf DNA and that of the other phages, tf should be considered as an evolutionary divergent member of the group. Two distinguishing features not reported for other members of the group were found in the tf genome. Firstly, a unique end structure - a blunt right end and a 4-nucleotide 3'-protruding left end - was observed. Secondly, 14 single-chain interruptions (nicks) were found in the top strand of the tf DNA. All nicks were mapped within a consensus sequence 5'-TACT/RTGMC-3'. Two nicks were analyzed in detail and were shown to be present in more than 90% of the phage population. Although localized nicks were previously found only in the DNA of T5-like and phiKMV-like phages, it seems increasingly likely that this enigmatic structural feature is common to various other bacteriophages.

Is everyone Irish on St Patrick's Day? Divergent expectations and experiences of collective self-objectification at a multicultural parade

We examine experiences of collective self-objectification (CSO) (or its failure) among participants in a ‘multicultural’ St Patrick's Day parade. A two-stage interview study was carried out in which 10 parade participants (five each from ethnic majority and minority groups) were interviewed before and after the event. In pre-event interviews, all participants understood the parade as an opportunity to enact social identities, but differed in the category definitions and relations they saw as relevant. Members of the white Irish majority saw the event as being primarily about representing Ireland in a positive, progressive, light, whereas members of minority groups saw it as an opportunity to have their groups' identities and belonging in Ireland recognized by others. Post-event interviews revealed that, for the former group, the event succeeded in giving expression to their relevant category definitions. The latter group, on the other hand, cited features of the event such as inauthentic costume design and a segregated structure as reasons for why the event did not provide the group recognition they sought. The accounts revealed a variety of empowering and disempowering experiences corresponding to the extent of enactment. We consider the implications in terms of CSO, the performative nature of dual identities, as well as the notion of multicultural recognition.

Genome-wide scans of three independent sets of 90 Irish multiplex schizophrenia families and follow-up of selected regions in all families provides evidence for multiple susceptibility genes

From our linkage study of Irish families with a high density of schizophrenia, we have previously reported evidence for susceptibility genes in regions 5q21-31, 6p24-21, 8p22-21, and 10p15-p11. In this report, we describe the cumulative results from independent genome scans of three a priori random subsets of 90 families each, and from multipoint analysis of all 270 families in ten regions. Of these ten regions, three (13q32, 18p11-q11, and 18q22-23) did not generate scores above the empirical baseline pairwise scan results, and one (6q13-26) generated a weak signal. Six other regions produced more positive pairwise and multipoint results. They showed the following maximum multipoint H-LOD (heterogeneity LOD) and NPL scores: 2p14-13: 0.89 (P = 0.06) and 2.08 (P = 0.02), 4q24-32: 1.84 (P = 0.007) and 1.67 (P = 0.03), 5q21-31: 2.88 (P= 0.0007), and 2.65 (P = 0.002), 6p25-24: 2.13 (P = 0.005) and 3.59 (P = 0.0005), 6p23: 2.42 (P = 0.001) and 3.07 (P = 0.001), 8p22-21: 1.57 (P = 0.01) and 2.56 (P = 0.005), 10p15-11: 2.04 (P = 0.005) and 1.78 (P = 0.03). The degree of 'internal replication' across subsets differed, with 5q, 6p, and 8p being most consistent and 2p and 10p being least consistent. On 6p, the data suggested the presence of two susceptibility genes, in 6p25-24 and 6p23-22. Very few families were positive on more than one region, and little correlation between regions was evident, suggesting substantial locus heterogeneity. The levels of statistical significance were modest, as expected from loci contributing to complex traits. However, our internal replications, when considered along with the positive results obtained in multiple other samples, suggests that most of these six regions are likely to contain genes that influence liability to schizophrenia.

Gene Sets Net Correlations Analysis (GSNCA): a multivariate differential coexpression test for gene sets

Motivation: To date, Gene Set Analysis (GSA) approaches primarily focus on identifying differentially expressed gene sets (pathways). Methods for identifying differentially coexpressed pathways also exist but are mostly based on aggregated pairwise correlations, or other pairwise measures of coexpression. Instead, we propose Gene Sets Net Correlations Analysis (GSNCA), a multivariate differential coexpression test that accounts for the complete correlation structure between genes.

Results: In GSNCA, weight factors are assigned to genes in proportion to the genes' cross-correlations (intergene correlations). The problem of finding the weight vectors is formulated as an eigenvector problem with a unique solution. GSNCA tests the null hypothesis that for a gene set there is no difference in the weight vectors of the genes between two conditions. In simulation studies and the analyses of experimental data, we demonstrate that GSNCA, indeed, captures changes in the structure of genes' cross-correlations rather than differences in the averaged pairwise correlations. Thus, GSNCA infers differences in coexpression networks, however, bypassing method-dependent steps of network inference. As an additional result from GSNCA, we define hub genes as genes with the largest weights and show that these genes correspond frequently to major and specific pathway regulators, as well as to genes that are most affected by the biological difference between two conditions. In summary, GSNCA is a new approach for the analysis of differentially coexpressed pathways that also evaluates the importance of the genes in the pathways, thus providing unique information that may result in the generation of novel biological hypotheses.

Sets of multiplicity and closable multipliers on group algebras

We undertake a detailed study of the sets of multiplicity in a second countable locally compact group G and their operator versions. We establish a symbolic calculus for normal completely bounded maps from the space B(L-2(G)) of bounded linear operators on L-2 (G) into the von Neumann algebra VN(G) of G and use it to show that a closed subset E subset of G is a set of multiplicity if and only if the set E* = {(s,t) is an element of G x G : ts(-1) is an element of E} is a set of operator multiplicity. Analogous results are established for M-1-sets and M-0-sets. We show that the property of being a set of multiplicity is preserved under various operations, including taking direct products, and establish an Inverse Image Theorem for such sets. We characterise the sets of finite width that are also sets of operator multiplicity, and show that every compact operator supported on a set of finite width can be approximated by sums of rank one operators supported on the same set. We show that, if G satisfies a mild approximation condition, pointwise multiplication by a given measurable function psi : G -> C defines a closable multiplier on the reduced C*-algebra G(r)*(G) of G if and only if Schur multiplication by the function N(psi): G x G -> C, given by N(psi)(s, t) = psi(ts(-1)), is a closable operator when viewed as a densely defined linear map on the space of compact operators on L-2(G). Similar results are obtained for multipliers on VN(C).

Kuznetsov independence for interval-valued expectations and sets of probability distributions: Properties and algorithms

Kuznetsov independence of variables X and Y means that, for any pair of bounded functions f(X) and g(Y), E[f(X)g(Y)]=E[f(X)] *times* E[g(Y)], where E[.] denotes interval-valued expectation and *times* denotes interval multiplication. We present properties of Kuznetsov independence for several variables, and connect it with other concepts of independence in the literature; in particular we show that strong extensions are always included in sets of probability distributions whose lower and upper expectations satisfy Kuznetsov independence. We introduce an algorithm that computes lower expectations subject to judgments of Kuznetsov independence by mixing column generation techniques with nonlinear programming. Finally, we define a concept of conditional Kuznetsov independence, and study its graphoid properties.