2 research outputs found

    Comparative Analysis of the Nodule Transcriptomes of Ceanothus thyrsiflorus (Rhamnaceae, Rosales) and Datisca glomerata (Datiscaceae, Cucurbitales)

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    Two types of nitrogen-fixing root nodule symbioses are known, rhizobial and actinorhizal symbioses. The latter involve plants of three orders, Fagales, Rosales, and Cucurbitales. To understand the diversity of plant symbiotic adaptation, we compared the nodule transcriptomes of Datisca glomerata (Datiscaceae, Cucurbitales) and Ceanothus thyrsiflorus (Rhamnaceae, Rosales); both species are nodulated by members of the uncultured Frankia clade, cluster II. The analysis focused on various features. In both species, the expression of orthologs of legume Nod factor receptor genes was elevated in nodules compared to roots. Since arginine has been postulated as export form of fixed nitrogen from symbiotic Frankia in nodules of D. glomerata, the question was whether the nitrogen metabolism was similar in nodules of C. thyrsiflorus. Analysis of the expression levels of key genes encoding enzymes involved in arginine metabolism revealed up-regulation of arginine catabolism, but no up-regulation of arginine biosynthesis, in nodules compared to roots of D. glomerata, while arginine degradation was not upregulated in nodules of C. thyrsiflorus. This new information corroborated an arginine-based metabolic exchange between host and microsymbiont for D. glomerata, but not for C. thyrsiflorus. Oxygen protection systems for nitrogenase differ dramatically between both species. Analysis of the antioxidant system suggested that the system in the nodules of D. glomerata leads to greater oxidative stress than the one in the nodules of C. thyrsiflorus, while no differences were found for the defense against nitrosative stress. However, induction of nitrite reductase in nodules of C. thyrsiflorus indicated that here, nitrite produced from nitric oxide had to be detoxified. Additional shared features were identified: genes encoding enzymes involved in thiamine biosynthesis were found to be upregulated in the nodules of both species. Orthologous nodule-specific subtilisin-like proteases that have been linked to the infection process in actinorhizal Fagales, were also upregulated in the nodules of D. glomerata and C. thyrsiflorus. Nodule-specific defensin genes known from actinorhizal Fagales and Cucurbitales, were also found in C. thyrsiflorus. In summary, the results underline the variability of nodule metabolism in different groups of symbiotic plants while pointing at conserved features involved in the infection process

    Systematic exploration of guide-tree topology effects for small protein alignments

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    Background: Guide-trees are used as part of an essential heuristic to enable the calculation of multiple sequence alignments. They have been the focus of much method development but there has been little effort at determining systematically, which guide-trees, if any, give the best alignments. Some guide-tree construction schemes are based on pair-wise distances amongst unaligned sequences. Others try to emulate an underlying evolutionary tree and involve various iteration methods. Results: We explore all possible guide-trees for a set of protein alignments of up to eight sequences. We find that pairwise distance based default guide-trees sometimes outperform evolutionary guide-trees, as measured by structure derived reference alignments. However, default guide-trees fall way short of the optimum attainable scores. On average chained guide-trees perform better than balanced ones but are not better than default guide-trees for small alignments. Conclusions: Alignment methods that use Consistency or hidden Markov models to make alignments are less susceptible to sub-optimal guide-trees than simpler methods, that basically use conventional sequence alignment between profiles. The latter appear to be affected positively by evolutionary based guide-trees for difficult alignments and negatively for easy alignments. One phylogeny aware alignment program can strongly discriminate between good and bad guide-trees. The results for randomly chained guide-trees improve with the number of sequences.Science Foundation Irelan
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