Soil properties predict plant community development of mitigation wetlands created in the Virginia Piedmont, USA.

The study investigated vegetative and soil properties in four created mitigation wetlands, ranging in age from three to ten years, all created in the Virginia Piedmont. Vegetation attributes included percent cover, richness (S), diversity (H'), floristic quality assessment index (FQAI), prevalence index (PI), and productivity [i.e., peak above-ground biomass (AGB) and below-ground biomass]. Soil attributes included soil organic matter (SOM), gravimetric soil moisture (GSM), pH, and bulk density (D(b)) for the top 10 cm. Species dominance (e.g., Juncus effusus, Scirpus cyperinus, Arthraxon hispidus) led to a lack of differences in vegetative attributes between sites. However, site-based differences were found for GSM, pH, and SOM (P < 0.001). Soil attributes were analyzed using Euclidean cluster analysis, resulting in four soil condition (SC) categories where plots were grouped based on common attribute levels (i.e., SC1 > SC2 > SC3 > SC4, trended more to less developed). When vegetation attributes were compared between SC groups, greater SOM, lower D(b), more circumneutral pH, and higher GSM, all indicative of maturation, were associated with higher H' (P < 0.05), FQAI (P < 0.05), and total and volunteer percent cover (P < 0.05), and lower AGB (P < 0.001), PI (P < 0.05), and seeded percent cover (P < 0.05). The outcome of the study shows that site age does not necessarily equate with site development with soil and vegetation developmental rates varying both within and among sites. The inclusion of soil attributes in post-construction monitoring should be required to enhance our understanding and prediction of developmental trajectory of created mitigation wetlands.

Alternative splicing and differential gene expression in colon cancer detected by a whole genome exon array.

BACKGROUND: Alternative splicing is a mechanism for increasing protein diversity by excluding or including exons during post-transcriptional processing. Alternatively spliced proteins are particularly relevant in oncology since they may contribute to the etiology of cancer, provide selective drug targets, or serve as a marker set for cancer diagnosis. While conventional identification of splice variants generally targets individual genes, we present here a new exon-centric array (GeneChip Human Exon 1.0 ST) that allows genome-wide identification of differential splice variation, and concurrently provides a flexible and inclusive analysis of gene expression. RESULTS: We analyzed 20 paired tumor-normal colon cancer samples using a microarray designed to detect over one million putative exons that can be virtually assembled into potential gene-level transcripts according to various levels of prior supporting evidence. Analysis of high confidence (empirically supported) transcripts identified 160 differentially expressed genes, with 42 genes occupying a network impacting cell proliferation and another twenty nine genes with unknown functions. A more speculative analysis, including transcripts based solely on computational prediction, produced another 160 differentially expressed genes, three-fourths of which have no previous annotation. We also present a comparison of gene signal estimations from the Exon 1.0 ST and the U133 Plus 2.0 arrays. Novel splicing events were predicted by experimental algorithms that compare the relative contribution of each exon to the cognate transcript intensity in each tissue. The resulting candidate splice variants were validated with RT-PCR. We found nine genes that were differentially spliced between colon tumors and normal colon tissues, several of which have not been previously implicated in cancer. Top scoring candidates from our analysis were also found to substantially overlap with EST-based bioinformatic predictions of alternative splicing in cancer. CONCLUSION: Differential expression of high confidence transcripts correlated extremely well with known cancer genes and pathways, suggesting that the more speculative transcripts, largely based solely on computational prediction and mostly with no previous annotation, might be novel targets in colon cancer. Five of the identified splicing events affect mediators of cytoskeletal organization (ACTN1, VCL, CALD1, CTTN, TPM1), two affect extracellular matrix proteins (FN1, COL6A3) and another participates in integrin signaling (SLC3A2). Altogether they form a pattern of colon-cancer specific alterations that may particularly impact cell motility.

MicroRNA expression analysis using the Affymetrix Platform.

Microarrays have been used extensively for messenger RNA expression monitoring. Recently, microarrays have been designed to interrogate expression levels of noncoding RNAs. Here, we describe methods for RNA labeling and the use of a miRNA array to identify and measure microRNA present in RNA samples.