Climatological study of transport to the PICO-NARE site using atmospheric backward trajectories

This study developed a transport climatology to the PICO-NARE station, in the central North Atlantic Ocean, using a 40-year set of atmospheric back trajectories. The trajectory set was subjected to a cluster analysis in order to group trajectories into six flow patterns, or clusters. An air flow probability analysis was conducted in conjunction with the cluster analysis in order to determine the source regions for flow to the site. Seasonal differences in the flow patterns were found, which included enhanced westerly flow in the winter, decreased westerly flow in the summer, and spring and fall having moderate westerly flow. The North Atlantic Oscillation had a significant impact on the winter and fall seasons and less significant impacts during spring and summer. The results of the climatology can be used in conjunction with measurements of ozone, CO, NOx, and NOy, which are currently being measured at the site, to develop a long-term, seasonal climatology of transport of pollutants to the central North Atlantic.

Systemic analysis of microarray data sets towards identifying genes regulating root development

Nitrogen and water are essential for plant growth and development. In this study, we designed experiments to produce gene expression data of poplar roots under nitrogen starvation and water deprivation conditions. We found low concentration of nitrogen led first to increased root elongation followed by lateral root proliferation and eventually increased root biomass. To identify genes regulating root growth and development under nitrogen starvation and water deprivation, we designed a series of data analysis procedures, through which, we have successfully identified biologically important genes. Differentially Expressed Genes (DEGs) analysis identified the genes that are differentially expressed under nitrogen starvation or drought. Protein domain enrichment analysis identified enriched themes (in same domains) that are highly interactive during the treatment. Gene Ontology (GO) enrichment analysis allowed us to identify biological process changed during nitrogen starvation. Based on the above analyses, we examined the local Gene Regulatory Network (GRN) and identified a number of transcription factors. After testing, one of them is a high hierarchically ranked transcription factor that affects root growth under nitrogen starvation. It is very tedious and time-consuming to analyze gene expression data. To avoid doing analysis manually, we attempt to automate a computational pipeline that now can be used for identification of DEGs and protein domain analysis in a single run. It is implemented in scripts of Perl and R.