Genetic diversity and species relationships in the Oryza complex and glufosinate tolerance in rice

The weed red rice is a major problem in rice producing areas world wide. All of the red rice in commercial rice fields in the United States has traditionally been considered to be the same species as commercial rice, Oryza sativa. However, using DNA markers it was found that most of the red rice with black hulls was sufficiently divergent to be considered a separate species. This includes TX4, a red rice ecotype that has been reported to have considerable natural tolerance to the herbicide glufosinate. TX4 is closely related to samples that have been classified as Oryza rufipogon. However, it was shown that both the TX4-like red rice from commercial fields and most of the Oryza rufipogon accessions in the US National Small Grains Collection are more accurately classified as Oryza nivara. This is significant since Oryza rufipogon is regulated under the Federal Noxious Weed Act, while Oryza nivara is not. Oryza nivara closely related to TX4 was found to be widely distributed across the rice production areas of Texas and was also found in Arkansas, Louisiana, and Mississippi. Of 240 samples from across Texas, 23 samples from six different counties were identical with TX4 with all 18 DNA markers tested. The reported glufosinate tolerance of TX4 is a potential problem since this same herbicide would be used in conjunction with genetically modified (GM) that is being developed as a method of red rice control. Thus, field, greenhouse and tissue culture studies were conducted to evaluate the degree of glufosinate tolerance in TX4. TX4 typically was severely damaged by glufosinate, but not efficiently controlled. Even with the maximum number of herbicide applications at the proposed maximum label rate, TX4 often re-sprouted and produced viable seed. Herbicide tolerance was found to be variable, but appears to be sufficient to present a problem with the use of the GM glufosinate resistant varieties currently under development, particularly when combined with variation in the response of ??sensitive?? varieties

Patients' reports or clinicians' assessments: Which are better for prognosticating?

BACKGROUND: The Prognosis in Palliative care Scale (PiPS) predicts survival in advanced cancer patients more accurately than a doctor's or a nurse's estimate. PiPS scores are derived using observer ratings of symptom severity and performance status. The purpose of this study was to determine whether patient-rated data would provide better prognostic estimates than clinician observer ratings. PATIENTS AND METHODS: 1018 subjects with advanced cancer no longer undergoing tumour-directed therapy were recruited to a multi-centre study. Prognostic models were developed using observer ratings, patient ratings or a composite method that used patient ratings when available or else used observer ratings. The performance of the prognostic models was compared by determining the agreement between the models' predictions and the survival of study participants. RESULTS: All three approaches to model development resulted in prognostic scores that were able to differentiate between patients with a survival of 'days', 'weeks' or 'months+'. However, the observer-rated models were significantly (p<0.05) more accurate than the patient-rated models. CONCLUSIONS: A prognostic model derived using observer-rated data was more accurate at predicting survival than a similar model derived using patient self-report measures. This is clinically important because patient-rated data can be burdensome and difficult to obtain in patients with terminal illnesses

Evolution of structural diversity of trichothecenes, a family of toxins produced by plant pathogenic and entomopathogenic fungi

[EN] Trichothecenes are a family of terpenoid toxins produced by multiple genera of fungi, including plant and insect pathogens. Some trichothecenes produced by the fungus Fusarium are among the mycotoxins of greatest concern to food and feed safety because of their toxicity and frequent occurrence in cereal crops, and trichothecene production contributes to pathogenesis of some Fusarium species on plants. Collectively, fungi produce over 150 trichothecene analogs: i.e., molecules that share the same core structure but differ in patterns of substituents attached to the core structure. Here, we carried out genomic, phylogenetic, gene-function, and analytical chemistry studies of strains from nine fungal genera to identify genetic variation responsible for trichothecene structural diversity and to gain insight into evolutionary processes that have contributed to the variation. The results indicate that structural diversity has resulted from gain, loss, and functional changes of trichothecene biosynthetic (TRI) genes. The results also indicate that the presence of some substituents has arisen independently in different fungi by gain of different genes with the same function. Variation in TRI gene duplication and number of TRI loci was also observed among the fungi examined, but there was no evidence that such genetic differences have contributed to trichothecene structural variation. We also inferred ancestral states of the TRI cluster and trichothecene biosynthetic pathway, and proposed scenarios for changes in trichothecene structures during divergence of TRI cluster homologs. Together, our findings provide insight into evolutionary processes responsible for structural diversification of toxins produced by pathogenic fungiSISG received funding from the Spanish Ministry of Economy and Competitiveness (grant number MINECO-AGL2015-70671-C2-2-R). TL received funding from the National Institute of Agricultural Sciences, Rural Development Administration (grant number PJ00843203). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscrip

A unified framework for multi-locus association analysis of both common and rare variants

<p>Abstract</p> <p>Background</p> <p>Common, complex diseases are hypothesized to result from a combination of common and rare genetic variants. We developed a unified framework for the joint association testing of both types of variants. Within the framework, we developed a union-intersection test suitable for genome-wide analysis of single nucleotide polymorphisms (SNPs), candidate gene data, as well as medical sequencing data. The union-intersection test is a composite test of association of genotype frequencies and differential correlation among markers.</p> <p>Results</p> <p>We demonstrated by computer simulation that the false positive error rate was controlled at the expected level. We also demonstrated scenarios in which the multi-locus test was more powerful than traditional single marker analysis. To illustrate use of the union-intersection test with real data, we analyzed a publically available data set of 319,813 autosomal SNPs genotyped for 938 cases of Parkinson disease and 863 neurologically normal controls for which no genome-wide significant results were found by traditional single marker analysis. We also analyzed an independent follow-up sample of 183 cases and 248 controls for replication.</p> <p>Conclusions</p> <p>We identified a single risk haplotype with a directionally consistent effect in both samples in the gene <it>GAK</it>, which is involved in clathrin-mediated membrane trafficking. We also found suggestive evidence that directionally inconsistent marginal effects from single marker analysis appeared to result from risk being driven by different haplotypes in the two samples for the genes <it>SYN3 </it>and <it>NGLY1</it>, which are involved in neurotransmitter release and proteasomal degradation, respectively. These results illustrate the utility of our unified framework for genome-wide association analysis of common, complex diseases.</p

2018 Scholars at Work Conference Program

Program for the 2018 Scholars at Work Conference at Minnesota State University, Mankato on March 30, 2018

Expression Signature of IFN/STAT1 Signaling Genes Predicts Poor Survival Outcome in Glioblastoma Multiforme in a Subtype-Specific Manner

Previous reports have implicated an induction of genes in IFN/STAT1 (Interferon/STAT1) signaling in radiation resistant and prosurvival tumor phenotypes in a number of cancer cell lines, and we have hypothesized that upregulation of these genes may be predictive of poor survival outcome and/or treatment response in Glioblastoma Multiforme (GBM) patients. We have developed a list of 8 genes related to IFN/STAT1 that we hypothesize to be predictive of poor survival in GBM patients. Our working hypothesis that over-expression of this gene signature predicts poor survival outcome in GBM patients was confirmed, and in addition, it was demonstrated that the survival model was highly subtype-dependent, with strong dependence in the Proneural subtype and no detected dependence in the Classical and Mesenchymal subtypes. We developed a specific multi-gene survival model for the Proneural subtype in the TCGA (the Cancer Genome Atlas) discovery set which we have validated in the TCGA validation set. In addition, we have performed network analysis in the form of Bayesian Network discovery and Ingenuity Pathway Analysis to further dissect the underlying biology of this gene signature in the etiology of GBM. We theorize that the strong predictive value of the IFN/STAT1 gene signature in the Proneural subtype may be due to chemotherapy and/or radiation resistance induced through prolonged constitutive signaling of these genes during the course of the illness. The results of this study have implications both for better prediction models for survival outcome in GBM and for improved understanding of the underlying subtype-specific molecular mechanisms for GBM tumor progression and treatment response

The relationship between white matter microstructure and general cognitive ability in patients with schizophrenia and healthy participants in the ENIGMA Consortium

Objective: Schizophrenia has recently been associated with widespread white matter microstructural abnormalities, but the functional effects of these abnormalities remain unclear. Widespread heterogeneity of results from studies published to date preclude any definitive characterization of the relationship between white matter and cognitive performance in schizophrenia. Given the relevance of deficits in cognitive function to predicting social and functional outcomes in schizophrenia, the authors carried out a meta-analysis of available data through the ENIGMA Consortium, using a common analysis pipeline, to elucidate the relationship between white matter microstructure and a measure of general cognitive performance, IQ, in patients with schizophrenia and healthy participants. Methods: The meta-analysis included 760 patients with schizophrenia and 957 healthy participants from 11 participating ENIGMA Consortium sites. For each site, principal component analysis was used to calculate both a global fractional anisotropy component (gFA) and a fractional anisotropy component for six long association tracts (LA-gFA) previously associated with cognition. Results: Meta-analyses of regression results indicated that gFA accounted for a significant amount of variation in cognition in the full sample (effect size [Hedges’ g]=0.27, CI=0.17–0.36), with similar effects sizes observed for both the patient (effect size=0.20, CI=0.05–0.35) and healthy participant groups (effect size=0.32, CI=0.18–0.45). Comparable patterns of association were also observed between LA-gFA and cognition for the full sample (effect size=0.28, CI=0.18–0.37), the patient group (effect size=0.23, CI=0.09–0.38), and the healthy participant group (effect size=0.31, CI=0.18–0.44). Conclusions: This study provides robust evidence that cognitive ability is associated with global structural connectivity, with higher fractional anisotropy associated with higher IQ. This association was independent of diagnosis; while schizophrenia patients tended to have lower fractional anisotropy and lower IQ than healthy participants, the comparable size of effect in each group suggested a more general, rather than disease-specific, pattern of association

The HLA–DRB1 shared epitope is associated with susceptibility to rheumatoid arthritis in African Americans through European genetic admixture

To determine whether shared epitope (SE)–containing HLA–DRB1 alleles are associated with rheumatoid arthritis (RA) in African Americans and whether their presence is associated with higher degrees of global (genome-wide) genetic admixture from the European population

Polymorphisms near TBX5 and GDF7 are associated with increased risk for Barrett's esophagus.

BACKGROUND & AIMS: Barrett's esophagus (BE) increases the risk of esophageal adenocarcinoma (EAC). We found the risk to be BE has been associated with single nucleotide polymorphisms (SNPs) on chromosome 6p21 (within the HLA region) and on 16q23, where the closest protein-coding gene is FOXF1. Subsequently, the Barrett's and Esophageal Adenocarcinoma Consortium (BEACON) identified risk loci for BE and esophageal adenocarcinoma near CRTC1 and BARX1, and within 100 kb of FOXP1. We aimed to identify further SNPs that increased BE risk and to validate previously reported associations. METHODS: We performed a genome-wide association study (GWAS) to identify variants associated with BE and further analyzed promising variants identified by BEACON by genotyping 10,158 patients with BE and 21,062 controls. RESULTS: We identified 2 SNPs not previously associated with BE: rs3072 (2p24.1; odds ratio [OR] = 1.14; 95% CI: 1.09-1.18; P = 1.8 × 10(-11)) and rs2701108 (12q24.21; OR = 0.90; 95% CI: 0.86-0.93; P = 7.5 × 10(-9)). The closest protein-coding genes were respectively GDF7 (rs3072), which encodes a ligand in the bone morphogenetic protein pathway, and TBX5 (rs2701108), which encodes a transcription factor that regulates esophageal and cardiac development. Our data also supported in BE cases 3 risk SNPs identified by BEACON (rs2687201, rs11789015, and rs10423674). Meta-analysis of all data identified another SNP associated with BE and esophageal adenocarcinoma: rs3784262, within ALDH1A2 (OR = 0.90; 95% CI: 0.87-0.93; P = 3.72 × 10(-9)). CONCLUSIONS: We identified 2 loci associated with risk of BE and provided data to support a further locus. The genes we found to be associated with risk for BE encode transcription factors involved in thoracic, diaphragmatic, and esophageal development or proteins involved in the inflammatory response

Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.55 years (95% CI: 2.91, 4.19; I2 = 57.53%) compared to controls, after adjusting for age, sex and site (Cohen's d = 0.48). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions