The RAS/RAF signaling pathway is an important mediator of tumor cell proliferation and angiogenesis. The novel bi-aryl urea BAY 43-9006 is a potent inhibitor of Raf-1, a member of the RAF/MEK/ERK signaling pathway. Additional characterization showed that BAY 43-9006 suppresses both wild-type and V599E mutant BRAF activity in vitro.

Angiogenesis and signaling through the RAF/mitogen-activated protein/extracellular signal-regulated kinase (ERK) kinase (MEK)/ERK cascade have been reported to play important roles in the development of hepatocellular carcinomas (HCC). Sorafenib (BAY 43-9006, Nexavar) is a multikinase inhibitor with activity against Raf kinase and several receptor tyrosine kinases, including vascular endothelial growth factor receptor 2 (VEGFR2), platelet-derived growth factor receptor (PDGFR), FLT3, Ret, and c-Kit. In this study, we investigated the in vitro effects of sorafenib on PLC/PRF/5 and HepG2 HCC cells and the in vivo antitumor efficacy and mechanism of action on PLC/ PRF/5 human tumor xenografts in severe combined immunodeficient mice. Sorafenib inhibited the phosphorylation of MEK and ERK and down-regulated cyclin D1 levels in these two cell lines. Sorafenib also reduced the phosphorylation level of eIF4E and down-regulated the antiapoptotic protein Mcl-1 in a MEK/ ERK-independent manner. Consistent with the effects on both MEK/ERK-dependent and MEK/ERK-independent signaling pathways, sorafenib inhibited proliferation and induced apoptosis in both HCC cell lines. In the PLC/PRF/5 xenograft model, sorafenib tosylate dosed at 10 mg/kg inhibited tumor growth by 49%. At 30 mg/kg, sorafenib tosylate produced complete tumor growth inhibition. A dose of 100 mg/kg produced partial tumor regressions in 50% of the mice. In mechanism of action studies, sorafenib inhibited the phosphorylation of both ERK and eIF4E, reduced the microvessel area (assessed by CD34 immunohistochemistry), and induced tumor cell apoptosis (assessed by terminal deoxynucleotidyl transferase-mediated nick end labeling) in PLC/PRF/5 tumor xenografts. These results suggest that the antitumor activity of sorafenib in HCC models may be attributed to inhibition of tumor angiogenesis (VEGFR and PDGFR) and direct effects on tumor cell proliferation/survival (Raf kinase signalingdependent and signaling-independent mechanisms).

Teosinte, the progenitor of maize, is restricted to tropical environments in Mexico and Central America. The pre-Columbian spread of maize from its center of origin in tropical Southern Mexico to the higher latitudes of the Americas required postdomestication selection for adaptation to longer day lengths. Flowering time of teosinte and tropical maize is delayed under long day lengths, whereas temperate maize evolved a reduced sensitivity to photoperiod. We measured flowering time of the maize nested association and diverse association mapping panels in the field under both short and long day lengths, and of a maize-teosinte mapping population under long day lengths. Flowering time in maize is a complex trait affected by many genes and the environment. Photoperiod response is one component of flowering time involving a subset of flowering time genes whose effects are strongly influenced by day length. Genome-wide association and targeted high-resolution linkage mapping identified ZmCCT, a homologue of the rice photoperiod response regulator Ghd7, as the most important gene affecting photoperiod response in maize. Under long day lengths ZmCCT alleles from diverse teosintes are consistently expressed at higher levels and confer later flowering than temperate maize alleles. Many maize inbred lines, including some adapted to tropical regions, carry ZmCCT alleles with no sensitivity to day length. Indigenous farmers of the Americas were remarkably successful at selecting on genetic variation at key genes affecting the photoperiod response to create maize varieties adapted to vastly diverse environments despite the hindrance of the geographic axis of the Americas and the complex genetic control of flowering time.genetic diversity | quantitative trait locus T he rapid spread of agriculture from the Fertile Crescent was enabled in part by the East-West axis of Eurasia, permitting crop cultivation to spread across large geographic regions at a common latitude (1). The relatively simple genetic control of flowering time of the key crops domesticated in the Fertile Crescent, wheat and barley (2), coupled with a predominantly selffertilizing mating system, also facilitated colonization of new environments by rare mutants with large effects on flowering time responses to day length and temperature.In contrast, the spread of maize from its origin in Southern Mexico 6 to 10,000 y ago was relatively slow (1), hindered by the North-South axis of the Americas. Maize (Zea mays L. subsp. mays) was domesticated from the Mexican native teosinte Zea mays L. subsp. parviglumis (3), a species adapted to day lengths less than 13 h. Under the longer day lengths of higher latitudes, teosinte flowers very late or not at all (4). From its Meso-American origin, maize was spread by early humans to geographically and ecologically diverse environments from Canada to Chile well before the arrival of Columbus to the Americas (5, 6), requiring its adaptation to long day lengths. Thus, although the spread of maize occurred later than that of wheat, ...

Our results show the ability of sorafenib to potently inhibit the growth of both ectopically- and orthotopically-implanted Renca and 786-O tumors. The observed tumor growth inhibition and tumor stasis or stabilization correlated strongly with decreased tumor angiogenesis, which was due, at least in part, to inhibition of VEGF and PDGF-mediated endothelial cell and pericyte survival. Finally, sorafenib-mediated inhibition of tumor growth and angiogenesis occurred at concentrations equivalent to those achieved in patients in the clinic.

Tocopherols and tocotrienols, collectively known as tocochromanols, are the major lipid-soluble antioxidants in maize (Zea mays L.) grain. Given that individual tocochromanols differ in their degree of vitamin E activity, variation for tocochromanol composition and content in grain from among diverse maize inbred lines has important nutritional and health implications for enhancing the vitamin E and antioxidant contents of maize-derived foods through plant breeding. Toward this end, we conducted a genome-wide association study of six tocochromanol compounds and 14 of their sums, ratios, and proportions with a 281 maize inbred association panel that was genotyped for 591,822 SNP markers. In addition to providing further insight into the association between ZmVTE4 (γ-tocopherol methyltransferase) haplotypes and α-tocopherol content, we also detected a novel association between ZmVTE1 (tocopherol cyclase) and tocotrienol composition. In a pathway-level analysis, we assessed the genetic contribution of 60 a priori candidate genes encoding the core tocochromanol pathway (VTE genes) and reactions for pathways supplying the isoprenoid tail and aromatic head group of tocochromanols. This analysis identified two additional genes, ZmHGGT1 (homogentisate geranylgeranyltransferase) and one prephenate dehydratase parolog (of four in the genome) that also modestly contribute to tocotrienol variation in the panel. Collectively, our results provide the most favorable ZmVTE4 haplotype and suggest three new gene targets for increasing vitamin E and antioxidant levels through marker-assisted selection.

Genotyping-by-sequencing (GBS) technologies have proven capacity for delivering large numbers of marker genotypes with potentially less ascertainment bias than standard single nucleotide polymorphism (SNP) arrays. Therefore, GBS has become an attractive alternative technology for genomic selection. However, the use of GBS data poses important challenges, and the accuracy of genomic prediction using GBS is currently undergoing investigation in several crops, including maize, wheat, and cassava. The main objective of this study was to evaluate various methods for incorporating GBS information and compare them with pedigree models for predicting genetic values of lines from two maize populations evaluated for different traits measured in different environments (experiments 1 and 2). Given that GBS data come with a large percentage of uncalled genotypes, we evaluated methods using nonimputed, imputed, and GBS-inferred haplotypes of different lengths (short or long). GBS and pedigree data were incorporated into statistical models using either the genomic best linear unbiased predictors (GBLUP) or the reproducing kernel Hilbert spaces (RKHS) regressions, and prediction accuracy was quantified using cross-validation methods. The following results were found: relative to pedigree or marker-only models, there were consistent gains in prediction accuracy by combining pedigree and GBS data; there was increased predictive ability when using imputed or nonimputed GBS data over inferred haplotype in experiment 1, or nonimputed GBS and information-based imputed short and long haplotypes, as compared to the other methods in experiment 2; the level of prediction accuracy achieved using GBS data in experiment 2 is comparable to those reported by previous authors who analyzed this data set using SNP arrays; and GBLUP and RKHS models with pedigree with nonimputed and imputed GBS data provided the best prediction correlations for the three traits in experiment 1, whereas for experiment 2 RKHS provided slightly better prediction than GBLUP for drought-stressed environments, and both models provided similar predictions in well-watered environments.

Genotyping by sequencing (GBS) is the latest application of next-generation sequencing protocols for the purposes of discovering and genotyping SNPs in a variety of crop species and populations. Unlike other high-density genotyping technologies which have mainly been applied to general interest "reference" genomes, the low cost of GBS makes it an attractive means of saturating mapping and breeding populations with a high density of SNP markers. One barrier to the widespread use of GBS has been the difficulty of the bioinformatics analysis as the approach is accompanied by a high number of erroneous SNP calls which are not easily diagnosed or corrected. In this study, we use a 384-plex GBS protocol to add 30,984 markers to an indica (IR64) x japonica (Azucena) mapping population consisting of 176 recombinant inbred lines of rice (Oryza sativa) and we release our imputation and error correction pipeline to address initial GBS data sparcity and error, and streamline the process of adding SNPs to RIL populations. Using the final imputed and corrected dataset of 30,984 markers, we were able to map recombination hot and cold spots and regions of segregation distortion across the genome with a high degree of accuracy, thus identifying regions of the genome containing putative sterility loci. We mapped QTL for leaf width and aluminum tolerance, and were able to identify additional QTL for both phenotypes when using the full set of 30,984 SNPs that were not identified using a subset of only 1,464 SNPs, including a previously unreported QTL for aluminum tolerance located directly within a recombination hotspot on chromosome 1. These results suggest that adding a high density of SNP markers to a mapping or breeding population through GBS has great value for numerous applications in rice breeding and genetics research.

A combination of two approaches, namely QTL analysis and gene enrichment analysis were used to identify candidate genes in the “QTL-hotspot” region for drought tolerance present on the Ca4 pseudomolecule in chickpea. In the first approach, a high-density bin map was developed using 53,223 single nucleotide polymorphisms (SNPs) identified in the recombinant inbred line (RIL) population of ICC 4958 (drought tolerant) and ICC 1882 (drought sensitive) cross. QTL analysis using recombination bins as markers along with the phenotyping data for 17 drought tolerance related traits obtained over 1–5 seasons and 1–5 locations split the “QTL-hotspot” region into two subregions namely “QTL-hotspot_a” (15 genes) and “QTL-hotspot_b” (11 genes). In the second approach, gene enrichment analysis using significant marker trait associations based on SNPs from the Ca4 pseudomolecule with the above mentioned phenotyping data, and the candidate genes from the refined “QTL-hotspot” region showed enrichment for 23 genes. Twelve genes were found common in both approaches. Functional validation using quantitative real-time PCR (qRT-PCR) indicated four promising candidate genes having functional implications on the effect of “QTL-hotspot” for drought tolerance in chickpea.