737 research outputs found
Analysis of GK/Slac specific protein affecting SNVs.
No full text<p>(A) Variants were classified into five groups based on their genotypes in GK/Slac and Wistar/Slac. As shown in the bottom legend, circles stand for the original reference allele whereas stars and triangles represent two different mutant alleles. Taken group 1 as an example, variants is heterozygous in GK/Slac that have one mutant allele and one reference allele, while it is homozygous-reference in Wistar/Slac. Almost all variants are in group1, group2, and group3. (B) Genotype profiling for 1762 GK/Slac specific SNVs in 28 previous sequenced rat strains. GK/Ox and GK/Slac are GK strains which came from different geographical locations. BBDP is a type 1 diabetic model, another 11 Wistar derived rats are labeled by green. (C) T2D related prior genes. (D) Functional effect of nonsynonymous SNVs predicted by SIFT.</p
Five different genotype of GK/Slac specific SNVs and indels.
No full text<p>Five different genotype of GK/Slac specific SNVs and indels.</p
The insulin (mRNA), morphological, and molecular changes along the T2D progression of GK rats.
No full text(A) Enrichment of the angiogenesis pathway in the gene differentiation between GK and WST rats over the five time points. (B) The first principal sample loadings of GK and WST rats as displayed by each time point. (C) Definition of a single-valued morphometric index that measures islet deterioration, as exemplified by the islet micrographs of 6-month-old wild-type (WT) and Akt1+/-Akt2-/- (a type 2 diabetic model) mice. In each islet micrograph (scale bar shown at the bottom is 50 μm), the rim (blue line) of the insulin region (green) is sketched, and the distances of glucagon pixels (red) away from the rim are defined. Pixels inside the rim have positive distances and those outside have negative ones. A kernel density of the distances is shown next to each micrograph. It quantifies the spatial distribution of α- and β-cells via that of glucagon and insulin. The islet irregularity index is defined by the trimmed mean of the kernel density. (D) Islet α/β-cell distribution irregularity over time in GK and WST rats. (E) INS1 mRNA levels of GK and WST rats. At each time point is the average value of 3 individuals. (F) INS2 mRNA levels of GK and WST rats. (G) The second principal sample loadings of GK and WST rats. (H) Heatmap shows pathways enriched at the two poles of the second principal gene-eigenvector of rat. ATP biosynthetic process, oxygen transport, and oxidative stress-related pathways are enriched at the positive pole (red), and angiogenesis-related pathways at the negative pole (blue). The increased insulin levels in GK rats during week 4–8 correspond to up-regulation of ATP synthesis and down-regulation of angiogenesis. ROS, reactive oxygen species; VEGF, vascular endothelial growth factor.</p
Comparative Genome of GK and Wistar Rats Reveals Genetic Basis of Type 2 Diabetes.
No full textThe Goto-Kakizaki (GK) rat, which has been developed by repeated inbreeding of glucose-intolerant Wistar rats, is the most widely studied rat model for Type 2 diabetes (T2D). However, the detailed genetic background of T2D phenotype in GK rats is still largely unknown. We report a survey of T2D susceptible variations based on high-quality whole genome sequencing of GK and Wistar rats, which have generated a list of GK-specific variations (228 structural variations, 2660 CNV amplification and 2834 CNV deletion, 1796 protein affecting SNVs or indels) by comparative genome analysis and identified 192 potential T2D-associated genes. The genes with variants are further refined with prior knowledge and public resource including variant polymorphism of rat strains, protein-protein interactions and differential gene expression. Finally we have identified 15 genetic mutant genes which include seven known T2D related genes (Tnfrsf1b, Scg5, Fgb, Sell, Dpp4, Icam1, and Pkd2l1) and eight high-confidence new candidate genes (Ldlr, Ccl2, Erbb3, Akr1b1, Pik3c2a, Cd5, Eef2k, and Cpd). Our result reveals that the T2D phenotype may be caused by the accumulation of multiple variations in GK rat, and that the mutated genes may affect biological functions including adipocytokine signaling, glycerolipid metabolism, PPAR signaling, T cell receptor signaling and insulin signaling pathways. We present the genomic difference between two closely related rat strains (GK and Wistar) and narrow down the scope of susceptible loci. It also requires further experimental study to understand and validate the relationship between our candidate variants and T2D phenotype. Our findings highlight the importance of sequenced-based comparative genomics for investigating disease susceptibility loci in inbreeding animal models
High-confident T2D candidate genes and their homozygous SNVs in GK rat.
No full text<p>a. Additional evidence of association with T2D. 1) T2D prior genes curated from literatures. 2) Protein-protein interaction partners are enriched with T2D prior genes. 3) Differential expression or differential co-expression in GSE13271 dataset.</p><p>b. P-value for enrichment of T2D prior genes in the interaction partners. P-value was calculated by fisher test, and was adjusted by <i>p</i>.<i>adjust</i> in <i>R</i>.</p><p>c. Differential expression between GK and Wistar rats.</p><p>d. Differential co-expression between GK and Wistar rats.</p><p>High-confident T2D candidate genes and their homozygous SNVs in GK rat.</p
The plasma insulin levels of GK and WKY rats over time.
No full textThe plasma insulin levels of GK and WKY rats over time.</p
Pipeline for whole-genome sequencing and comparative analysis between GK and Wistar rats.
No full text<p>Pipeline for whole-genome sequencing and comparative analysis between GK and Wistar rats.</p
The onset of large-scale turbulence in the interstellar medium of spiral galaxies
No full textDFG thanks the European Research Council (ADG-2011 ECOGAL), and Brazilian agencies CAPES (3400-13-1) and FAPESP (no.2011/12909-8) for financial support. IB acknowledges the European Research Council (ADG-2011 ECOGAL) for financial support. GK acknowledges support from FAPESP (grants no. 2013/04073-2 and 2013/18815-0).Turbulence is ubiquitous in the interstellar medium (ISM) of the Milky Way and other spiral galaxies. The energy source for this turbulence has been much debated with many possible origins proposed. The universality of turbulence, its reported large-scale driving, and that it occurs also in starless molecular clouds, challenges models invoking any stellar source. A more general process is needed to explain the observations. In this work, we study the role of galactic spiral arms. This is accomplished by means of three-dimensional hydrodynamical simulations which follow the dynamical evolution of interstellar diffuse clouds (similar to 100 cm-3) interacting with the gravitational potential field of the spiral pattern. We find that the tidal effects of the arm's potential on the cloud result in internal vorticity, fragmentation and hydrodynamical instabilities. The triggered turbulence results in large-scale driving, on sizes of the ISM inhomogeneities, i.e. as large as similar to 100 pc, and efficiencies in converting potential energy into turbulence in the range similar to 10-25 per cent per arm crossing. This efficiency is much higher than those found in previous models. The statistics of the turbulence in our simulations are strikingly similar to the observed power spectrum and Larson scaling relations of molecular clouds and the general ISM. The dependence found from different models indicate that the ISM turbulence is mainly related to local spiral arm properties, such as its mass density and width. This correlation seems in agreement with recent high angular resolution observations of spiral galaxies, e.g. M51 and M33.Peer reviewe
Protein-protein interaction (PPI) network for T2D candidate genes identified in GK rats.
No full text<p>(A) PPI network for six T2D prior genes that have GK/Slac specific PAVs. Edges indicate PPI got from STRING database (only considering interaction with other T2D prior genes). Genes involved in important KEGG pathways were shown by colored boxes. (B) Relationship network among fifteen T2D candidate genes. Seven genes were T2D prior genes and have GK/Slac specific PAVs; another eight genes were enriched with T2D prior genes as PPI partners. Widths of edges were proportional to the number of shared PPI patterns.</p
Consistency between the time-course expression of GK and WST islets by RNA-seq and RT-PCR data.
No full textConsistency between the time-course expression of GK and WST islets by RNA-seq and RT-PCR data.</p
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