STATISTICAL ISSUES IN THE ANALYSIS OF MICROBIAL COMMUNITIES IN SOIL

Corn and soybean production dominates the agricultural systems of the mid-western United States. Studies have found that when a single crop species is grown continually, without the rotation of other crops, yield decline occurs. At present, this phenomenon, remains poorly understood, but there are possible links to microbial community dynamics in the associated rhizosphere soil. In this study, corn plants were grown in disturbed and undisturbed soils with a 24 year history of growth as a mono culture crop or two crops grown in annual rotation. Characteristic profiles of the microbial communities were obtained by denaturing gradient gel electrophoresis of polymerase chain reaction amplified 16S rDNA from soil extracted DNA. This problem is approached as the statistical analysis of high-dimensional multivariate binary data with an emphasis on modeling and variable selection

Regulation of Gene Expression and Inhibition of Experimental Prostate Cancer Bone Metastasis by Dietary Genistein

AbstractProstate cancer frequently metastasizes to the bone, and the treatment outcome for metastatic prostate cancer has been disappointing so far. Dietary genistein, derived primarily from soy product, has been proposed to be partly responsible for the low rate of prostate cancer in Asians. Our previous studies have shown that genistein elicits pleiotropic effects on prostate cancer cells, but there are no studies documenting comprehensive gene expression profiles and antitumor effects of dietary genistein on human prostate cancer grown in human bone environment. In this study, we investigated the effects of genistein on PC3 prostate cancer cells and experimental PC3 bone tumors created by injecting PC3 cells into human bone fragments previously implanted in severe combined immunodeficient (SCID) mice (SCID human model). We found that genistein significantly inhibited PC3 bone tumor growth using both prevention and intervention strategies. By using microarray and real-time polymerase chain reaction technology, we found that genistein regulated the expression of multiple genes involved in the control of cell growth, apoptosis, and metastasis both in vitro and in vivo. For example, the expression of various metalloproteinases (MMPs) in PC3 bone tumors was inhibited by genistein treatment, whereas osteoprotegerin was upregulated. MMP immunostaining and transfection experiments also demonstrated that MMP-9 expression was inhibited in PC3 cells in vitro and PC3 bone tumors in vivo after genistein treatment. These results, particularly the in vivo results, demonstrate that dietary genistein may inhibit prostate cancer bone metastasis by regulating metastasis-related genes. Genistein may thus be a promising agent for the prevention and/or treatment of prostate cancer

Isolation and fine mapping of Rps6: An intermediate host resistance gene in barley to wheat stripe rust

A plant may be considered a nonhost of a pathogen if all known genotypes of a plant species are resistant to all known isolates of a pathogen species. However, if a small number of genotypes are susceptible to some known isolates of a pathogen species this plant maybe considered an intermediate host. Barley (Hordeum vulgare) is an intermediate host for Puccinia striiformis f. sp. tritici (Pst), the causal agent of wheat stripe rust. We wanted to understand the genetic architecture underlying resistance to Pst and to determine whether any overlap exists with resistance to the host pathogen, Puccinia striiformis f. sp. hordei (Psh). We mapped Pst resistance to chromosome 7H and show that host and intermediate host resistance is genetically uncoupled. Therefore, we designate this resistance locus Rps6. We used phenotypic and genotypic selection on F2:3 families to isolate Rps6 and fine mapped the locus to a 0.1 cM region. Anchoring of the Rps6 locus to the barley physical map placed the region on two adjacent fingerprinted contigs. Efforts are now underway to sequence the minimal tiling path and to delimit the physical region harbouring Rps6. This will facilitate additional marker development and permit identification of candidate genes in the region

Comprehensive DNA methylation profiling in a human cancer genome identifies novel epigenetic targets

Using a unique microarray platform for cytosine methylation profiling, the DNA methylation landscape of the human genome was monitored at more than 21,000 sites, including 79% of the annotated transcriptional start sites (TSS). Analysis of an oligodendroglioma derived cell line LN-18 revealed more than 4000 methylated TSS. The gene-centric analysis indicated a complex pattern of DNA methylation exists along each autosome, with a trend of increasing density approaching the telomeres. Remarkably, 2% of CpG islands (CGI) were densely methylated, and 17% had significant levels of 5 mC, whether or not they corresponded to a TSS. Substantial independent verification, obtained from 95 loci, suggested that this approach is capable of large scale detection of cytosine methylation with an accuracy approaching 90%. In addition, we detected large genomic domains that are also susceptible to DNA methylation reinforced inactivation, such as the HOX cluster on chromosome 7 (CH7). Extrapolation from the data suggests that more than 2000 genomic loci may be susceptible to methylation and associated inactivation, and most have yet to be identified. Finally, we report six new targets of epigenetic inactivation (IRX3, WNT10A, WNT6, RARalpha, BMP7 and ZGPAT). These targets displayed cell line and tumor specific differential methylation when compared with normal brain samples, suggesting they may have utility as biomarkers. Uniquely, hypermethylation of the CGI within an IRX3 exon was correlated with over-expression of IRX3 in tumor tissues and cell lines relative to normal brain samples

Interference of flavonoids with enzymatic assays for the determination of free fatty acid and triglyceride levels

Flavonoids are bioactive food compounds with potential lipid-lowering effects. Commercially available enzymatic assays are widely used to determine free fatty acid (FFA) and triglyceride (TG) levels both in vivo in plasma or serum and in vitro in cell culture medium or cell lysate. However, we have observed that various flavonoids interfere with peroxidases used in these enzymatic assays, resulting in incorrect lower FFA and TG levels than actually present. Furthermore, addition of isorhamnetin or the major metabolite of the flavonoid quercetin in human and rat plasma, quercetin-3-O-glucuronide, to murine serum also resulted in a significant reduction of the detected TG levels, while a trend was seen for FFA levels. It is concluded that when applying these assays, vigilance is needed and alternative analytical methods, directly assessing FFA or TG levels, should be used for studying the biological effects of flavonoids on FFA and TG levels

Onions - mineral soils (eastern Oregon - east of Cascades) [1983]

Revised April 1983.Facts and recommendations in this publication may no longer be valid. Please look for up-to-date information in the OSU Extension Catalog: http://extension.oregonstate.edu/catalo

A semi-nonparametric mixture model for selecting functionally consistent proteins

Background High-throughput technologies have led to a new era of proteomics. Although protein microarray experiments are becoming more common place there are a variety of experimental and statistical issues that have yet to be addressed, and that will carry over to new high-throughput technologies unless they are investigated. One of the largest of these challenges is the selection of functionally consistent proteins. Results We present a novel semi-nonparametric mixture model for classifying proteins as consistent or inconsistent while controlling the false discovery rate and the false non-discovery rate. The performance of the proposed approach is compared to current methods via simulation under a variety of experimental conditions. Conclusions We provide a statistical method for selecting functionally consistent proteins in the context of protein microarray experiments, but the proposed semi-nonparametric mixture model method can certainly be generalized to solve other mixture data problems. The main advantage of this approach is that it provides the posterior probability of consistency for each protein