Antagonism between Prdm16 and Smad4 specifies the trajectory and progression of pancreatic cancer.

The transcription factor Prdm16 functions as a potent suppressor of transforming growth factor-beta (TGF-ß) signaling, whose inactivation is deemed essential to the progression of pancreatic ductal adenocarcinoma (PDAC). Using the KrasG12D-based mouse model of human PDAC, we surprisingly found that ablating Prdm16 did not block but instead accelerated PDAC formation and progression, suggesting that Prdm16 might function as a tumor suppressor in this malignancy. Subsequent genetic experiments showed that ablating Prdm16 along with Smad4 resulted in a shift from a well-differentiated and confined neoplasm to a highly aggressive and metastatic disease, which was associated with a striking deviation in the trajectory of the premalignant lesions. Mechanistically, we found that Smad4 interacted with and recruited Prdm16 to repress its own expression, therefore pinpointing a model in which Prdm16 functions downstream of Smad4 to constrain the PDAC malignant phenotype. Collectively, these findings unveil an unprecedented antagonistic interaction between the tumor suppressors Smad4 and Prdm16 that functions to restrict PDAC progression and metastasis.

TGIF1 functions as a tumor suppressor in pancreatic ductal adenocarcinoma.

A prominent function of TGIF1 is suppression of transforming growth factor beta (TGF-ß) signaling, whose inactivation is deemed instrumental to the progression of pancreatic ductal adenocarcinoma (PDAC), as exemplified by the frequent loss of the tumor suppressor gene SMAD4 in this malignancy. Surprisingly, we found that genetic inactivation of Tgif1 in the context of oncogenic Kras, KrasG12D , culminated in the development of highly aggressive and metastatic PDAC despite de-repressing TGF-ß signaling. Mechanistic experiments show that TGIF1 associates with Twist1 and inhibits Twist1 expression and activity, and this function is suppressed in the vast majority of human PDACs by KrasG12D /MAPK-mediated TGIF1 phosphorylation. Ablating Twist1 in KrasG12D ;Tgif1KO mice completely blunted PDAC formation, providing the proof-of-principle that TGIF1 restrains KrasG12D -driven PDAC through its ability to antagonize Twist1. Collectively, these findings pinpoint TGIF1 as a potential tumor suppressor in PDAC and further suggest that sustained activation of TGF-ß signaling might act to accelerate PDAC progression rather than to suppress its initiation.

Twist1 Activation in Muscle Progenitor Cells Causes Muscle Loss Akin to Cancer Cachexia.

Cancer cachexia is characterized by extreme skeletal muscle loss that results in high morbidity and mortality. The incidence of cachexia varies among tumor types, being lowest in sarcomas, whereas 90% of pancreatic ductal adenocarcinoma (PDAC) patients experience severe weight loss. How these tumors trigger muscle depletion is still unfolding. Serendipitously, we found that overexpression of Twist1 in mouse muscle progenitor cells, either constitutively during development or inducibly in adult animals, caused severe muscle atrophy with features reminiscent of cachexia. Using several genetic mouse models of PDAC, we detected a marked increase in Twist1 expression in muscle undergoing cachexia. In cancer patients, elevated levels of Twist1 are associated with greater degrees of muscle wasting. Finally, both genetic and pharmacological inactivation of Twist1 in muscle progenitor cells afforded substantial protection against cancer-mediated cachexia, which translated into meaningful survival benefits, implicating Twist1 as a possible target for attenuating muscle cachexia in cancer patients.

Identification and Quantification of a Toxigenic and Non-Toxigenic Aspergillus flavus Strain in Contaminated Maize Using Quantitative Real-Time PCR.

Aflatoxins, which are produced by Aspergillus flavus, are toxic to humans, livestock, and pets. The value of maize (Zea mays) grain is markedly reduced when contaminated with aflatoxin. Plant resistance and biological control using non-toxin producing strains are considered effective strategies for reducing aflatoxin accumulation in maize grain. Distinguishing between the toxin and non-toxin producing strains is important in determining the effectiveness of bio-control strategies and understanding inter-strain interactions. Using polymorphisms found in the fungal rRNA intergenic spacer region (IGS) between a toxigenic strain of A. flavus (NRRL 3357) and the non-toxigenic strain used in the biological control agent Afla-Guard(®) (NRRL 21882), we developed a set of primers that allows for the identification and quantification of the two strains using quantitative PCR. This primer set has been used to screen maize grain that was inoculated with the two strains individually and co-inoculated with both strains, and it has been shown to be effective in both the identification and quantification of both strains. Screening of co-inoculated ears from multiple resistant and susceptible genotypic crosses revealed no significant differences in fungal biomass accumulation of either strain in the field tests from 2010 and 2011 when compared across the means of all genotypes. Only one genotype/year combination showed significant differences in strain accumulation. Aflatoxin accumulation analysis showed that, as expected, genotypes inoculated with the toxigenic strain accumulated more aflatoxin than when co-inoculated with both strains or inoculated with only the non-toxigenic strain. Furthermore, accumulation of toxigenic fungal mass was significantly correlated with aflatoxin accumulation while non-toxigenic fungal accumulation was not. This primer set will allow researchers to better determine how the two fungal strains compete on the maize ear and investigate the interaction between different maize lines and these A. flavus strains.

Characterization of the Maize Chitinase Genes and Their Effect on Aspergillus flavus and Aflatoxin Accumulation Resistance.

Maize (Zea mays L.) is a crop of global importance, but prone to contamination by aflatoxins produced by fungi in the genus Aspergillus. The development of resistant germplasm and the identification of genes contributing to resistance would aid in the reduction of the problem with a minimal need for intervention by farmers. Chitinolytic enzymes respond to attack by potential pathogens and have been demonstrated to increase insect and fungal resistance in plants. Here, all chitinase genes in the maize genome were characterized via sequence diversity and expression patterns. Recent evolution within this gene family was noted. Markers from within each gene were developed and used to map the phenotypic effect on resistance of each gene in up to four QTL mapping populations and one association panel. Seven chitinase genes were identified that had alleles associated with increased resistance to aflatoxin accumulation and A. flavus infection in field grown maize. The chitinase in bin 1.05 identified a new and highly significant QTL, while chitinase genes in bins 2.04 and 5.03 fell directly beneath the peaks of previously published QTL. The expression patterns of these genes corroborate possible grain resistance mechanisms. Markers from within the gene sequences or very closely linked to them are presented to aid in the use of marker assisted selection to improve this trait.

Maize toxin degrades peritrophic matrix proteins and stimulates compensatory transcriptome responses in fall armyworm midgut.

Understanding the molecular mechanisms underlying insect compensatory responses to plant defenses could lead to improved plant resistance to herbivores. The Mp708 inbred line of maize produces the maize insect resistant 1-cysteine protease (Mir1-CP) toxin. Reduced feeding and growth of fall armyworm larvae fed on Mp708 was previously linked to impairment of nutrient utilization and degradation of the midgut (MG) peritrophic matrix (PM) by Mir1-CP. Here we examine the biochemical and transcriptional responses of fall armyworm larvae to Mir1-CP. Insect Intestinal Mucin (IIM) was severely depleted from pure PMs treated in vitro with recombinant Mir1-CP. Larvae fed on Mp708 midwhorls excrete frass largely depleted of IIM. Cracks, fissures and increased porosity previously observed in the PM of larvae fed on Mp708 midwhorls could ensue when Mir1-CP degrades the IIM that cross-links chitin fibrils in the PM. Both targeted and global transcriptome analyses were performed to determine how complete dissolution of the structure and function of the PM is prevented, enabling larvae to continue growing in the presence of Mir1-CP. The MGs from fall armyworm fed on Mp708 upregulate expression of genes encoding proteins involved in PM production as an apparent compensation to replace the disrupted PM structure and restore appropriate counter-current MG gradients. Also, several families of digestive enzymes (endopeptidases, aminopeptidases, lipases, amylase) were more highly expressed in MGs from larvae fed on Mp708 than MGs from larvae fed on diets lacking Mir1-CP (artificial diet, midwhorls from Tx601 or B73 maize). Impaired growth of larvae fed on Mp708 probably results from metabolic costs associated with higher production of PM constituents and digestive enzymes in a compensatory attempt to maintain MG function.

Cross-Ontology multi-level association rule mining in the Gene Ontology.

The Gene Ontology (GO) has become the internationally accepted standard for representing function, process, and location aspects of gene products. The wealth of GO annotation data provides a valuable source of implicit knowledge of relationships among these aspects. We describe a new method for association rule mining to discover implicit co-occurrence relationships across the GO sub-ontologies at multiple levels of abstraction. Prior work on association rule mining in the GO has concentrated on mining knowledge at a single level of abstraction and/or between terms from the same sub-ontology. We have developed a bottom-up generalization procedure called Cross-Ontology Data Mining-Level by Level (COLL) that takes into account the structure and semantics of the GO, generates generalized transactions from annotation data and mines interesting multi-level cross-ontology association rules. We applied our method on publicly available chicken and mouse GO annotation datasets and mined 5368 and 3959 multi-level cross ontology rules from the two datasets respectively. We show that our approach discovers more and higher quality association rules from the GO as evaluated by biologists in comparison to previously published methods. Biologically interesting rules discovered by our method reveal unknown and surprising knowledge about co-occurring GO terms.

A public platform for the verification of the phenotypic effect of candidate genes for resistance to aflatoxin accumulation and Aspergillus flavus infection in maize.

A public candidate gene testing pipeline for resistance to aflatoxin accumulation or Aspergillus flavus infection in maize is presented here. The pipeline consists of steps for identifying, testing, and verifying the association of selected maize gene sequences with resistance under field conditions. Resources include a database of genetic and protein sequences associated with the reduction in aflatoxin contamination from previous studies; eight diverse inbred maize lines for polymorphism identification within any maize gene sequence; four Quantitative Trait Loci (QTL) mapping populations and one association mapping panel, all phenotyped for aflatoxin accumulation resistance and associated phenotypes; and capacity for Insertion/Deletion (InDel) and SNP genotyping in the population(s) for mapping. To date, ten genes have been identified as possible candidate genes and put through the candidate gene testing pipeline, and results are presented here to demonstrate the utility of the pipeline.

Adventures in the enormous: a 1.8 million clone BAC library for the 21.7 Gb genome of loblolly pine.

Loblolly pine (LP; Pinus taeda L.) is the most economically important tree in the U.S. and a cornerstone species in southeastern forests. However, genomics research on LP and other conifers has lagged behind studies on flowering plants due, in part, to the large size of conifer genomes. As a means to accelerate conifer genome research, we constructed a BAC library for the LP genotype 7-56. The LP BAC library consists of 1,824,768 individually-archived clones making it the largest single BAC library constructed to date, has a mean insert size of 96 kb, and affords 7.6X coverage of the 21.7 Gb LP genome. To demonstrate the efficacy of the library in gene isolation, we screened macroarrays with overgos designed from a pine EST anchored on LP chromosome 10. A positive BAC was sequenced and found to contain the expected full-length target gene, several gene-like regions, and both known and novel repeats. Macroarray analysis using the retrotransposon IFG-7 (the most abundant repeat in the sequenced BAC) as a probe indicates that IFG-7 is found in roughly 210,557 copies and constitutes about 5.8% or 1.26 Gb of LP nuclear DNA; this DNA quantity is eight times the Arabidopsis genome. In addition to its use in genome characterization and gene isolation as demonstrated herein, the BAC library should hasten whole genome sequencing of LP via next-generation sequencing strategies/technologies and facilitate improvement of trees through molecular breeding and genetic engineering. The library and associated products are distributed by the Clemson University Genomics Institute (www.genome.clemson.edu).

AgBase: supporting functional modeling in agricultural organisms.

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website.

Integrated database for identifying candidate genes for Aspergillus flavus resistance in maize.

BACKGROUND: Aspergillus flavus Link:Fr, an opportunistic fungus that produces aflatoxin, is pathogenic to maize and other oilseed crops. Aflatoxin is a potent carcinogen, and its presence markedly reduces the value of grain. Understanding and enhancing host resistance to A. flavus infection and/or subsequent aflatoxin accumulation is generally considered an efficient means of reducing grain losses to aflatoxin. Different proteomic, genomic and genetic studies of maize (Zea mays L.) have generated large data sets with the goal of identifying genes responsible for conferring resistance to A. flavus, or aflatoxin. RESULTS: In order to maximize the usage of different data sets in new studies, including association mapping, we have constructed a relational database with web interface integrating the results of gene expression, proteomic (both gel-based and shotgun), Quantitative Trait Loci (QTL) genetic mapping studies, and sequence data from the literature to facilitate selection of candidate genes for continued investigation. The Corn Fungal Resistance Associated Sequences Database (CFRAS-DB) (http://agbase.msstate.edu/) was created with the main goal of identifying genes important to aflatoxin resistance. CFRAS-DB is implemented using MySQL as the relational database management system running on a Linux server, using an Apache web server, and Perl CGI scripts as the web interface. The database and the associated web-based interface allow researchers to examine many lines of evidence (e.g. microarray, proteomics, QTL studies, SNP data) to assess the potential role of a gene or group of genes in the response of different maize lines to A. flavus infection and subsequent production of aflatoxin by the fungus. CONCLUSIONS: CFRAS-DB provides the first opportunity to integrate data pertaining to the problem of A. flavus and aflatoxin resistance in maize in one resource and to support queries across different datasets. The web-based interface gives researchers different query options for mining the database across different types of experiments. The database is publically available at http://agbase.msstate.edu.

Proteome profile of the developing maize (Zea mays L.) rachis.

In this study, we performed the first high-throughput proteomic analysis of developing rachis (cob) from maize genotype Mp313E. Using two proteomic approaches, 2-DE and 2-D LC, we identified 967 proteins. A 2-D proteome reference map was established. Functional classification of identified proteins revealed that proteins involved in various cellular metabolisms, response to stimulus and transport, were the most abundant.