Search

ZSF1 rats exhibit spontaneous nephropathy secondary to obesity, hypertension, and diabetes, and have gained interest as a model system with potentially high translational value to progressive human disease. To thoroughly characterize this model, and to better understand how closely it recapitulates human disease, we performed a high resolution longitudinal analysis of renal disease progression in ZSF1 rats spanning from early disease to end stage renal disease. Analyses included metabolic endpoints, renal histology and ultrastructure, evaluation of a urinary biomarker of fibrosis, and transcriptome analysis of glomerular-enriched tissue over the course of disease. Our findings support the translational value of the ZSF1 rat model, and are provided here to assist researchers in the determination of the model’s suitability for testing a particular mechanism of interest, the design of therapeutic intervention studies, and the identification of new targets and biomarkers for type 2 diabetic nephropathy. [ABSTRACT FROM AUTHOR]

Although yield trials for switchgrass (Panicum virgatum L.), a potentially high value biofuel feedstock crop, are currently underway throughout North America, the genetic tools for crop improvement in this species are still in the early stages of development. Identification of high-density molecular markers, such as single nucleotide polymorphisms (SNPs), that are amenable to high-throughput genotyping approaches, is the first step in a quantitative genetics study of this model biofuel crop species. We generated and sequenced expressed sequence tag (EST) libraries from thirteen diverse switchgrass cultivars representing both upland and lowland ecotypes, as well as tetraploid and octoploid genomes. We followed this with reduced genomic library preparation and massively parallel sequencing of the same samples using the Illumina Genome Analyzer technology platform. EST libraries were used to generate unigene clusters and establish a gene-space reference sequence, thus providing a framework for assembly of the short sequence reads. SNPs were identified utilizing these scaffolds. We used a custom software program for alignment and SNP detection and identified over 149,000 SNPs across the 13 short-read sequencing libraries (SRSLs). Approximately 25,000 additional SNPs were identified from the entire EST collection available for the species. This sequencing effort generated data that are suitable for marker development and for estimation of population genetic parameters, such as nucleotide diversity and linkage disequilibrium. Based on these data, we assessed the feasibility of genome wide association mapping and genomic selection applications in switchgrass. Overall, the SNP markers discovered in this study will help facilitate quantitative genetics experiments and greatly enhance breeding efforts that target improvement of key biofuel traits and development of new switchgrass cultivars. [ABSTRACT FROM AUTHOR]

Despite rapid development and application of a wide range of manufactured metal oxide nanoparticles (NPs), the understanding of potential risks of using NPs is less completed, especially at the molecular level. The nematode Caenorhabditis elegans (C.elegans) has been emerging as an environmental model to study the molecular mechanism of environmental contaminations, using standard genetic tools such as the real-time quantitative PCR (RT-qPCR). The most important factor that may affect the accuracy of RT-qPCR is to choose appropriate genes for normalization. In this study, we selected 13 reference gene candidates (act-1, cdc-42, pmp-3, eif-3.C, actin, act-2, csq-1, Y45F10D.4, tba-1, mdh-1, ama-1, F35G12.2, and rbd-1) to test their expression stability under different doses of nano-copper oxide (CuO 0, 1, 10, and 50 mg/ mL) using RT-qPCR. Four algorithms, geNorm, NormFinder, BestKeeper, and the comparative ΔCt method, were employed to evaluate these 13 candidates expressions. As a result, tba-1, Y45F10D.4 and pmp-3 were the most reliable, which may be used as reference genes in future study of nanoparticle-induced genetic response using C.elegans. [ABSTRACT FROM AUTHOR]