Proteome-Level Analysis of Metabolism- and Stress-Related Proteins during Seed Dormancy and Germination in <i>Gnetum parvifolium</i>

Gnetum parvifolium is a rich source of materials for traditional medicines, food, and oil, but little is known about the mechanism underlying its seed dormancy and germination. In this study, we analyzed the proteome-level changes in its seeds during germination using isobaric tags for relative and absolute quantitation. In total, 1,040 differentially expressed proteins were identified, and cluster analysis revealed the distinct time points during which signal transduction and oxidation–reduction activity changed. Gene Ontology analysis showed that “carbohydrate metabolic process” and “response to oxidative stress” were the main enriched terms. Proteins associated with starch degradation and antioxidant enzymes were important for dormancy-release, while proteins associated with energy metabolism and protein synthesis were up-regulated during germination. Moreover, protein-interaction networks were mainly associated with heat-shock proteins. Furthermore, in accord with changes in the energy metabolism- and antioxidant-related proteins, indole-3-acetic acid, Peroxidase, and soluble sugar content increased, and the starch content decreased in almost all six stages of dormancy and germination analyzed (S1–S6). The activity of superoxide dismutase, abscisic acid, and malondialdehyde content increased in the dormancy stages (S1–S3) and then decreased in the germination stages (S4–S6). Our results provide new insights into G. parvifolium seed dormancy and germination at the proteome and physiological levels, with implications for improving seed propagation

Descriptions of candidate genes from <i>Platycladus orientalis</i> for qRT-PCR.

<p>Note: All reference gene sequences from transcriptome data of <i>Platycladus orientalis</i> were searched with BLAST using sequences of <i>Arabidopsis thaliana</i> in GenBank. Sequences of candidate housekeeping genes and NAC domain protein gene are provided in the Supporting Information.</p

Expression profiles of <i>NAC</i> in different-aged tissues and in response to stresses in <i>Platycladus orientalis</i> (as determined by qRT-PCR with UBC and aTUB in combination as reference genes).

<p>Expression profiles of <i>NAC</i> in different-aged tissues and in response to stresses in <i>Platycladus orientalis</i> (as determined by qRT-PCR with UBC and aTUB in combination as reference genes).</p

Modeling SME credit ratings using non-homogenous backward semi-Markovian approach

A Dissertation submitted in partial fulfillment of the requirements for the Master of Science in Mathematical Finance (MSc.MF) at Strathmore UniversityConsidering the growth in SME lending in Kenya and the obvious risks it posses to the banking sector, we establish a credit risk model that is responsive to the jumps in the economy. This is based on simulation of implied values of credit worthiness over a period of 12 months for 1000 SMEs, in which case we establish a case for the discrete time non-homogeneous semi-Markov approach as a proxy for internal rating model for a portfolio of SME loans. While viewing credit risk as a reliability issue, the model provides a credit indicator which gives a prospective measure of credit risk for an SME portfolio. Banks seeking to comply with the new IFRS9 guidelines can espouse this model to adequately measure impairment of financial instruments

It's Christmas Carol (2006)

1. Poster, 2. Photo, 3. Photo, 4. Photo, 5. Photo, 6. Photo, 7. Photo, 8. Photo, 9. Photo, 10. Photo, 11. Photo, 12. Photo, 13. Photo, 14. Photo, 15. Program, 16. Press Release English, 17. Press Release FrenchArchival file for the Glendon College production of It's Christmas Carol, written and directed by Nicole Toogood. The play was performed November 30th - December 9th, 2006

Ranking of candidate reference genes in order of their expression stability as calculated by NormFinder.

<p>Note: Expression stability and ranking of 10 reference genes as calculated by NormFinder in all samples (A), different ages (B), different tissue types (C), cold-treated (D), heat-treated (E), NaCl-treated (F), PEG-treated (G), ABA-treated (H). Lower average expression stability (M value) indicates more stable expression.</p

Gene expression stability and ranking of 10 reference genes as calculated by geNorm.

<p>Gene expression stability and ranking of 10 reference genes as calculated by geNorm.</p

Figure 1

<p> <b>Expression levels of candidate reference genes in different plant samples.</b></p

Determination of the optimal number of reference genes for normalization by pairwise variation (V) using geNorm.

<p>Determination of the optimal number of reference genes for normalization by pairwise variation (V) using geNorm.</p

Ranking of candidate reference genes in order of their expression stability as calculated by BestKeeper.

<p>Note: Expression stability and ranking of 10 reference genes as calculated by Bestkeeper in all samples (A), different ages (B), different tissue types (C), cold-treated (D), heat-treated (E), NaCl-treated (F), PEG-treated (G), ABA-treated (H). Descriptive statistics of 10 candidate genes based on their coefficient of variance (CV) and standard deviation (SD) of Ct values were determined using the whole data set, and all Ct values were analyzed as a total data set. Reference genes are identified as the most stable genes (those with the lowest coefficient of variance and standard deviation; CV±SD).</p