Mixed model approaches for the identification of QTLs within a maize hybrid breeding program

Two outlines for mixed model based approaches to quantitative trait locus (QTL) mapping in existing maize hybrid selection programs are presented: a restricted maximum likelihood (REML) and a Bayesian Markov Chain Monte Carlo (MCMC) approach. The methods use the in-silico-mapping procedure developed by Parisseaux and Bernardo (2004) as a starting point. The original single-point approach is extended to a multi-point approach that facilitates interval mapping procedures. For computational and conceptual reasons, we partition the full set of relationships from founders to parents of hybrids into two types of relations by defining so-called intermediate founders. QTL effects are defined in terms of those intermediate founders. Marker based identity by descent relationships between intermediate founders define structuring matrices for the QTL effects that change along the genome. The dimension of the vector of QTL effects is reduced by the fact that there are fewer intermediate founders than parents. Furthermore, additional reduction in the number of QTL effects follows from the identification of founder groups by various algorithms. As a result, we obtain a powerful mixed model based statistical framework to identify QTLs in genetic backgrounds relevant to the elite germplasm of a commercial breeding program. The identification of such QTLs will provide the foundation for effective marker assisted and genome wide selection strategies. Analyses of an example data set show that QTLs are primarily identified in different heterotic groups and point to complementation of additive QTL effects as an important factor in hybrid performance

Influence of Contact Definitions in Assessment of the Relative Importance of Social Settings in Disease Transmission Risk

BACKGROUND: Realistic models of disease transmission incorporating complex population heterogeneities require input from quantitative population mixing studies. We use contact diaries to assess the relative importance of social settings in respiratory pathogen spread using three measures of person contact hours (PCH) as proxies for transmission risk with an aim to inform bipartite network models of respiratory pathogen transmission. METHODS AND FINDINGS: Our survey examines the contact behaviour for a convenience sample of 65 adults, with each encounter classified as occurring in a work, retail, home, social, travel or "other" setting. The diary design allows for extraction of PCH-interaction (cumulative time in face-face conversational or touch interaction with contacts)--analogous to the contact measure used in several existing surveys--as well as PCH-setting (product of time spent in setting and number of people present) and PCH-reach (product of time spent in setting and number of people in close proximity). Heterogeneities in day-dependent distribution of risk across settings are analysed using partitioning and cluster analyses and compared between days and contact measures. Although home is typically the highest-risk setting when PCH measures isolate two-way interactions, its relative importance compared to social and work settings may reduce when adopting a more inclusive contact measure that considers the number and duration of potential exposure events. CONCLUSIONS: Heterogeneities in location-dependent contact behaviour as measured by contact diary studies depend on the adopted contact definition. We find that contact measures isolating face-face conversational or touch interactions suggest that contact in the home dominates, whereas more inclusive contact measures indicate that home and work settings may be of higher importance. In the absence of definitive knowledge of the contact required to facilitate transmission of various respiratory pathogens, it is important for surveys to consider alternative contact measures

Cancer cell sensitivity to bortezomib is associated with survivin expression and p53 status but not cancer cell types

<p>Abstract</p> <p>Background</p> <p>Survivin is known playing a role in drug resistance. However, its role in bortezomib-mediated inhibition of growth and induction of apoptosis is unclear. There are conflicting reports for the effect of bortezomib on survivin expression, which lacks of a plausible explanation. Methods: In this study, we tested cancer cells with both p53 wild type and mutant/null background for the relationship of bortezomib resistance with survivin expression and p53 status using MTT assay, flow cytometry, DNA fragmentation, caspase activation, western blots and RNAi technology.</p> <p>Results</p> <p>We found that cancer cells with wild type p53 show a low level expression of survivin and are sensitive to treatment with bortezomib, while cancer cells with a mutant or null p53 show a high level expression of survivin and are resistant to bortezomib-mediated apoptosis induction. However, silencing of survivin expression utilizing survivin mRNA-specific siRNA/shRNA in p53 mutant or null cells sensitized cancer cells to bortezomib mediated apoptosis induction, suggesting a role for survivin in bortezomib resistance. We further noted that modulation of survivin expression by bortezomib is dependent on p53 status but independent of cancer cell types. In cancer cells with mutated p53 or p53 null, bortezomib appears to induce survivin expression, while in cancer cells with wild type p53, bortezomib downregulates or shows no significant effect on survivin expression, which is dependent on the drug concentration, cell line and exposure time.</p> <p>Conclusions</p> <p>Our findings, for the first time, unify the current inconsistent findings for bortezomib treatment and survivin expression, and linked the effect of bortezomib on survivin expression, apoptosis induction and bortezomib resistance in the relationship with p53 status, which is independent of cancer cell types. Further mechanistic studies along with this line may impact the optimal clinical application of bortezomib in solid cancer therapeutics.</p

Population Genetic Analysis Infers Migration Pathways of Phytophthora ramorum in US Nurseries

Recently introduced, exotic plant pathogens may exhibit low genetic diversity and be limited to clonal reproduction. However, rapidly mutating molecular markers such as microsatellites can reveal genetic variation within these populations and be used to model putative migration patterns. Phytophthora ramorum is the exotic pathogen, discovered in the late 1990s, that is responsible for sudden oak death in California forests and ramorum blight of common ornamentals. The nursery trade has moved this pathogen from source populations on the West Coast to locations across the United States, thus risking introduction to other native forests. We examined the genetic diversity of P. ramorum in United States nurseries by microsatellite genotyping 279 isolates collected from 19 states between 2004 and 2007. Of the three known P. ramorum clonal lineages, the most common and genetically diverse lineage in the sample was NA1. Two eastward migration pathways were revealed in the clustering of NA1 isolates into two groups, one containing isolates from Connecticut, Oregon, and Washington and the other isolates from California and the remaining states. This finding is consistent with trace forward analyses conducted by the US Department of Agriculture's Animal and Plant Health Inspection Service. At the same time, genetic diversities in several states equaled those observed in California, Oregon, and Washington and two-thirds of multilocus genotypes exhibited limited geographic distributions, indicating that mutation was common during or subsequent to migration. Together, these data suggest that migration, rapid mutation, and genetic drift all play a role in structuring the genetic diversity of P. ramorum in US nurseries. This work demonstrates that fast-evolving genetic markers can be used to examine the evolutionary processes acting on recently introduced pathogens and to infer their putative migration patterns, thus showing promise for the application of forensics to plant pathogens

Diversity in the Reproductive Modes of European Daphnia pulicaria Deviates from the Geographical Parthenogenesis

10 páginas, 5 figuras, 3 tablas.Background: Multiple transitions to obligate parthenogenesis have occurred in the Daphnia pulex complex in North America. These newly formed asexual lineages are differentially distributed being found predominantly at high latitudes. This conforms to the rule of geographical parthenogenesis postulating prevalence of asexuals at high latitudes and altitudes. While the reproductive mode of high-latitude populations is relatively well studied, little is known about the reproduction mode in high altitudes. This study aimed to assess the reproductive mode of Daphnia pulicaria, a species of the D. pulex complex, from high altitude lakes in Europe. Methodology/Principal Findings: Variation at eight microsatellite loci revealed that D. pulicaria from the High Tatra Mountains (HTM) had low genotype richness and showed excess of heterozygotes and significant deviations from Hardy- Weinberg expectations, and was thus congruent with reproduction by obligate parthenogenesis. By contrast, populations from the Pyrenees (Pyr) were generally in Hardy-Weinberg equilibrium and had higher genotypic richness, suggesting that they are cyclic parthenogens. Four lakes from lowland areas (LLaP) had populations with an uncertain or mixed breeding mode. All D. pulicaria had mtDNA ND5 haplotypes of the European D. pulicaria lineage. Pyr were distinct from LLaP and HTM at the ND5 gene. By contrast, HTM shared two haplotypes with LLaP and one with Pyr. Principal Coordinate Analysis of the microsatellite data revealed clear genetic differentiation into three groups. HTM isolates were intermediate to Pyr and LLaP, congruent with a hybrid origin. Conclusion/Significance: Inferred transitions to obligate parthenogenesis have occurred only in HTM, most likely as a result of hybridizations. In contrast to North American populations, these transitions do not appear to involve meiosis suppressor genes and have not been accompanied by polyploidy. The absence of obligate parthenogenesis in Pyr, an environment highly similar to the HTM, may be due to the lack of opportunities for hybridization.Peer reviewe

Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support

<p>Abstract</p> <p>Background</p> <p>Decision support in health systems is a highly difficult task, due to the inherent complexity of the process and structures involved.</p> <p>Method</p> <p>This paper introduces a new hybrid methodology <it>Expert-based Cooperative Analysis </it>(EbCA), which incorporates explicit prior expert knowledge in data analysis methods, and elicits implicit or tacit expert knowledge (IK) to improve decision support in healthcare systems. EbCA has been applied to two different case studies, showing its usability and versatility: 1) Bench-marking of small mental health areas based on technical efficiency estimated by <it>EbCA-Data Envelopment Analysis (EbCA-DEA)</it>, and 2) Case-mix of schizophrenia based on functional dependency using <it>Clustering Based on Rules (ClBR)</it>. In both cases comparisons towards classical procedures using qualitative explicit prior knowledge were made. Bayesian predictive validity measures were used for comparison with expert panels results. Overall agreement was tested by Intraclass Correlation Coefficient in case "1" and kappa in both cases.</p> <p>Results</p> <p>EbCA is a new methodology composed by 6 steps:. 1) Data collection and data preparation; 2) acquisition of "Prior Expert Knowledge" (PEK) and design of the "Prior Knowledge Base" (PKB); 3) PKB-guided analysis; 4) support-interpretation tools to evaluate results and detect inconsistencies (here <it>Implicit Knowledg </it>-IK- might be elicited); 5) incorporation of elicited IK in PKB and repeat till a satisfactory solution; 6) post-processing results for decision support. EbCA has been useful for incorporating PEK in two different analysis methods (DEA and Clustering), applied respectively to assess technical efficiency of small mental health areas and for case-mix of schizophrenia based on functional dependency. Differences in results obtained with classical approaches were mainly related to the IK which could be elicited by using EbCA and had major implications for the decision making in both cases.</p> <p>Discussion</p> <p>This paper presents EbCA and shows the convenience of completing classical data analysis with PEK as a mean to extract relevant knowledge in complex health domains. One of the major benefits of EbCA is iterative elicitation of IK.. Both explicit and tacit or implicit expert knowledge are critical to guide the scientific analysis of very complex decisional problems as those found in health system research.</p

DNA methylation subgroups and the CpG island methylator phenotype in gastric cancer: A comprehensive profiling approach

10.1186/1471-230X-14-55BMC Gastroenterology141-BGMA