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Turjanski, A. G.

Publications and source records attributed to Turjanski, A. G..

2 recordsLinked to original sources

Yerba mate (Ilex paraguariensis) genome provides new insights into convergent evolution of caffeine biosynthesis

Yerba mate (Ilex paraguariensis) is an economically important crop marketed for the elaboration of mate, the third-most widely consumed caffeine-containing infusion worldwide. Here we report the first genome assembly of this species, which has a total length of 1.06 Gb and contains 53,390 protein-coding genes. Comparative analyses revealed that the large yerba mate genome size is partly due to a whole-genome duplication (Ip-) during the early evolutionary history of Ilex, in addition to the hexaploidization event ({gamma}) shared by core eudicots. Characterization of the genome allowed us to clone the genes encoding methyltransferase enzymes that catalyse multiple reactions required for caffeine production. To our surprise, this species has converged upon a different biochemical pathway compared to that of its relatives, coffee and tea. In order to gain insight into the structural basis for the convergent enzyme activities, we obtained a crystal structure for the terminal enzyme in the pathway that forms caffeine. The structure reveals that convergent solutions have evolved for substrate positioning because different amino acid residues facilitate a different substrate orientation such that efficient methylation occurs in the independently evolved enzymes in yerba mate and coffee. While our results show phylogenomic constraint limits the genes coopted for convergence of caffeine biosynthesis, the x-ray diffraction data suggests structural constraints are minimal for the convergent evolution of individual reactions.

plant biology↗

VarQ: a tool for the structural analysis of Human Protein Variants

Understanding the functional effect of Single Amino acid Substitutions (SAS), derived from the occurrence of single nucleotide variants (SNVs), and their relation to disease development is a major issue in clinical genomics. Even though there are several bioinformatic algorithms and servers that predict if a SAS can be pathogenic or not they give little or non-information on the actual effect on the protein function. Moreover, many of these algorithms are able to predict an effect that no necessarily translates directly into pathogenicity. VarQ Web Server is an online tool that given an UniProt id automatically analyzes known and user provided SAS for their effect on protein activity, folding, aggregation and protein interactions among others. VarQ assessment was performed over a set of previously manually curated variants, showing its ability to correctly predict the phenotypic outcome and its underlying cause. This resource is available online at http://varq.qb.fcen.uba.ar/.\n\nContact: lradusky@qb.fcen.uba.ar\n\nSupporting Information & Tutorials may be found in the webpage of the tool.

bioinformatics↗