Complete sequences of the rRNA genes of Drosophila melanogaster

In this, the first of three papers, we present the sequence of the ribosomal RNA (rRNA) genes of Drosophila melanogaster. The gene regions of D. melanogaster rDNA encode four individual rRNAs: 18S (1,995 nt), 5.8S (123 nt), 2S (30 nt), and 28S (3,945 nt). The ribosomal DNA (rDNA) repeat of D. melanogaster is AT rich (65.9% overall), with the spacers being particularly AT rich. Analysis of DNA simplicity reveals that, in contrast to the intergenic spacer (IGS) and the external transcribed spacer (ETS), most of the rRNA gene regions have been refractory to the action of slippage-like events, with the exception of the 28S rRNA gene expansion segments. It would seem that the 28S rRNA can accommodate the products of slippage-like events without loss of activity. In the following two papers we analyze the effects of sequence divergence on the evolution of (1) the 28S gene "expansion segments" and (2) the 28S and 18S rRNA secondary structures among eukaryotic species, respectively. Our detailed analyses reveal, in addition to unequal crossing-over, (1) the involvement of slippage and biased mutation in the evolution of the rDNA multigene family and (2) the molecular coevolution of both expansion segments and the nucleotides involved with compensatory changes required to maintain secondary structures of RNA.      

An overview of models of stomatal conductance at the leaf level

Stomata play a key role in plant adaptation to changing environmental conditions as they control both water losses and CO₂ uptake. Particularly, in the context of global change, simulations of the consequences of drought on crop plants are needed to design more efficient and water‐saving cropping systems. However, most of the models of stomatal conductance (g_s) developed at the leaf level link g_s to environmental factors or net photosynthesis (A_net), but do not include satisfactorily the effects of drought, impairing our capacity to simulate plant functioning in conditions of limited water supply. The objective of this review was to draw an up‐to‐date picture of the g_s models, from the empirical to the process‐based ones, along with their mechanistic or deterministic bases. It focuses on models capable to account for multiple environmental influences with emphasis on drought conditions. We examine how models that have been proposed for well‐watered conditions can be combined with those specifically designed to deal with drought conditions. Ideas for future improvements of g_s models are discussed: the issue of co‐regulation of g_s and A_net; the roles of CO₂, absissic acid and H₂O₂; and finally, how to better address the new challenges arising from the issue of global change.     

Evolution of xyloglucan-related genes in green plants

Background  

The cell shape and morphology of plant tissues are intimately related to structural modifications in the primary cell wall that are associated with key processes in the regulation of cell growth and differentiation. The primary cell wall is composed mainly of cellulose immersed in a matrix of hemicellulose, pectin, lignin and some structural proteins. Xyloglucan is a hemicellulose polysaccharide present in the cell walls of all land plants (Embryophyta) and is the main hemicellulose in non-graminaceous angiosperms.     

Diversity of bacteria at various depths in the southern part of lake Baikal as detected by 16S rRNA sequencing

Phylogenetic analysis of the bacterial community inhabiting the water of Lake Baikal was performed on the basis of 16S rRNA sequencing. The composition of the bacterial community was shown to vary significantly with depth. Cyanobacteria were dominant species at the surface of the lake. At a moderate depth (400 m), actinomycete relatives were most abundant. At a great depth and near the bottom, the community was composed mainly of proteobacteria and cyanobacteria (the latter are probably brought from the surface layers by vertical near-shore water fluxes). Most of the bacterial 16S rRNA sequences detected exhibited low similarity to those known and formed separate clusters in the phylogenetic tree, which may indicate the endemic nature of the corresponding bacteria.