Project description:Dendrobaena schmidti (Michaelsen, 1907) is a polymorphic earthworm species from the Caucasus and adjacent regions. Adult D. schmidti individuals have highly variable body size (from 1.5 to well over 10 cm) and color (from dark purple to total lack of pigmentation), so a lot of subspecies of D. schmidti have been described; however, the existence of most of them is currently under dispute. We studied the genetic diversity of D. schmidti from seven locations from the Western Caucasus using mitochondrial (a fragment of the cytochrome oxidase I gene) and nuclear (internal ribosomal transcribed spacer 2) DNA. For both genes studied, we found that our sample was split into two groups. The first group included somewhat bigger (3-7.5 cm) individuals that were only slightly pigmented or totally unpigmented (when fixed by ethanol). The second group contained small (1.7-3.5 cm) specimens with dark purple pigmentation. In one of the studied locations these two groups were found in sympatry. However, there were no absolute differences either in general appearance (pigmented/unpigmented, small/big) or among diagnostic characters. Although the two groups differed in size (the majority of individuals from the first group were 5-6 cm long, and of the second one, 2-3 cm), the studied samples overlapped to a certain degree. Pigmentation, despite apparent differences, was also unreliable, since it was heavily affected by fixation of the specimens. Thus, based on the obtained data we can conclude that D. schmidti consists of at least two species that have identical states of diagnostic characters, but differ in general appearance.
Project description:Co-expression networks and gene regulatory networks (GRNs) are emerging as important tools for predicting the functional roles of individual genes at a system-wide scale. To enable network reconstructions we built a large-scale gene expression atlas comprised of 62,547 mRNAs, 17,862 non-modified proteins, and 6,227 phosphoproteins harboring 31,595 phosphorylation sites quantified across maize development. There was little edge conservation in co-expression and GRNs reconstructed using transcriptome versus proteome data yet networks from either data type were enriched in ontological categories and effective in predicting known regulatory relationships. This integrated gene expression atlas provides a valuable community resource. The networks should facilitate plant biology research and they provide a conceptual framework for future systems biology studies highlighting the importance of studying gene regulation at several levels.