Genetic Relationships of Crown Rust Resistance, Grain Yield, Test Weight, and Seed Weight in Oat

Integrating selection for agronomic performance and quantitative resistance to crown rust, caused by Puccinia coronata Corda var. avenae W.P. Fraser & Ledingham, in oat (Avena sativa L.) requires an understanding of their genetic relationships. This study was conducted to investigate the genetic relationships of crown rust resistance, grain yield, test weight, and seed weight under both inoculated and fungicide-treated conditions. A Design II mating was performed between 10 oat lines with putative partial resistance to crown rust and nine lines with superior grain yield and grain quality potential. Progenies from this mating were evaluated in both crown rust-inoculated and fungicide-treated plots in four Iowa environments to estimate genetic effects and phenotypic correlations between crown rust resistance and grain yield, seed weight, and test weight under either infection or fungicide-treated conditions. Lines from a random-mated population derived from the same parents were evaluated in three Iowa environments to estimate heritabilities of, and genetic correlations between, these traits. Resistance to crown rust, as measured by area under the disease progress curve (AUDPC), was highly heritable (H = 0.89 on an entry-mean basis), and was favorably correlated with grain yield, seed weight, and test weight measured in crown rust-inoculated plots. AUDPC was unfavorably correlated or uncorrelated with grain yield, test weight, and seed weight measured in fungicide-treated plots. To improve simultaneously crown rust resistance, grain yield, and seed weight under both lower and higher levels of crown rust infection, an optimum selection index can be developed with the genetic parameters estimated in this stud

Leptonic and Semileptonic Decays of Charm and Bottom Hadrons

We review the experimental measurements and theoretical descriptions of leptonic and semileptonic decays of particles containing a single heavy quark, either charm or bottom. Measurements of bottom semileptonic decays are used to determine the magnitudes of two fundamental parameters of the standard model, the Cabibbo-Kobayashi-Maskawa matrix elements $V_{cb}$ and $V_{ub}$. These parameters are connected with the physics of quark flavor and mass, and they have important implications for the breakdown of CP symmetry. To extract precise values of $|V_{cb}|$ and $|V_{ub}|$ from measurements, however, requires a good understanding of the decay dynamics. Measurements of both charm and bottom decay distributions provide information on the interactions governing these processes. The underlying weak transition in each case is relatively simple, but the strong interactions that bind the quarks into hadrons introduce complications. We also discuss new theoretical approaches, especially heavy-quark effective theory and lattice QCD, which are providing insights and predictions now being tested by experiment. An international effort at many laboratories will rapidly advance knowledge of this physics during the next decade.Comment: This review article will be published in Reviews of Modern Physics in the fall, 1995. This file contains only the abstract and the table of contents. The full 168-page document including 47 figures is available at http://charm.physics.ucsb.edu/papers/slrevtex.p

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Semileptonic Meson Decays in the Quark Model: An Update

We present the predictions of ISGW2, an update of the ISGW quark model for semileptonic meson decays. The updated model incorporates a number of features which should make it more reliable, including the constraints imposed by Heavy Quark Symmetry, hyperfine distortions of wavefunctions, and form factors with more realistic high recoil behaviors.Comment: All text and tables contained in the ".latex" file and all figures (14) contained in the ".uu" file

Driver Fusions and Their Implications in the Development and Treatment of Human Cancers.

Gene fusions represent an important class of somatic alterations in cancer. We systematically investigated fusions in 9,624 tumors across 33 cancer types using multiple fusion calling tools. We identified a total of 25,664 fusions, with a 63% validation rate. Integration of gene expression, copy number, and fusion annotation data revealed that fusions involving oncogenes tend to exhibit increased expression, whereas fusions involving tumor suppressors have the opposite effect. For fusions involving kinases, we found 1,275 with an intact kinase domain, the proportion of which varied significantly across cancer types. Our study suggests that fusions drive the development of 16.5% of cancer cases and function as the sole driver in more than 1% of them. Finally, we identified druggable fusions involving genes such as TMPRSS2, RET, FGFR3, ALK, and ESR1 in 6.0% of cases, and we predicted immunogenic peptides, suggesting that fusions may provide leads for targeted drug and immune therapy

Cell-of-Origin Patterns Dominate the Molecular Classification of 10,000 Tumors from 33 Types of Cancer

We conducted comprehensive integrative molecular analyses of the complete set of tumors in The Cancer Genome Atlas (TCGA), consisting of approximately 10,000 specimens and representing 33 types of cancer. We performed molecular clustering using data on chromosome-arm-level aneuploidy, DNA hypermethylation, mRNA, and miRNA expression levels and reverse-phase protein arrays, of which all, except for aneuploidy, revealed clustering primarily organized by histology, tissue type, or anatomic origin. The influence of cell type was evident in DNA-methylation-based clustering, even after excluding sites with known preexisting tissue-type-specific methylation. Integrative clustering further emphasized the dominant role of cell-of-origin patterns. Molecular similarities among histologically or anatomically related cancer types provide a basis for focused pan-cancer analyses, such as pan-gastrointestinal, pan-gynecological, pan-kidney, and pan-squamous cancers, and those related by stemness features, which in turn may inform strategies for future therapeutic development. Comprehensive, integrated molecular analysis identifies molecular relationships across a large diverse set of human cancers, suggesting future directions for exploring clinical actionability in cancer treatment