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Heitsch, C.

Publications and source records attributed to Heitsch, C..

3 recordsLinked to original sources

Nuclear-encoded tRNA genes harbor substantial allelic diversity in three nematode species

Cytosolic transfer RNAs, which are encoded as hundreds of genes in nuclear genomes, experience exceptionally high mutation rates and have been hypothesized to confer substantial mutational load in natural populations. Although this phenomenon appears universal across multicellular eukaryotes, a comprehensive characterization of standing variation in tRNA repertoires is still lacking in any system. Here, we resolve within-species allelic variation in nuclear-encoded tRNAs in three nematode species: Caenorhabditis elegans, C. briggsae, and C. tropicalis. We show that these genes carry signatures of high rates of historical transcription-associated mutagenesis and of purifying selection, resulting in allelic variation that includes pervasive instances of within-gene mismatches between the amino acid recognized by the tRNA backbone and that indicated by the anticodon. Furthermore, patterns of tRNA genomic organization and variation differ markedly from those of protein-coding regions. Individual genomes harbor distinct complements of tRNA genes with predicted functional differences, an observation that coincides with recent evidence that variation in tRNA expression and regulation contributes to human disease. Our findings offer an entry point for identifying the micro-evolutionary processes that act on tRNA repertoires, and in turn connecting those processes to the macro-evolutionary patterns that have more frequently been the focus of study. Significance statementTransfer RNAs (tRNAs) are ancient and essential molecules that deliver amino acids to the growing polypeptide chain during protein synthesis. Despite their importance, little is known about how the genes encoding tRNAs vary among individuals, even though they accumulate large numbers of mutations due to their high rates of expression. Here, we report that three nematode species, including the model organism C. elegans, show within-species variation in their tRNA gene repertoires, which may cause differences in protein synthesis across individuals. Our findings may represent patterns common across multicellular species and they set the stage for future investigation into how this diversity influences cellular function and organismal fitness.

genetics↗

Improving RNA branching predictions: advances and limitations

Minimum free energy prediction of RNA secondary structures is based on the Nearest Neighbor Thermodynamics Model. While such predictions are typically good, the accuracy can vary widely even for short sequences, and the branching thermodynamics are an important factor in this variance. Recently, the simplest model for multiloop energetics -- a linear function of the number of branches and unpaired nucleotides -- was found to be the best. Subsequently, a parametric analysis demonstrated that per family accuracy can be improved by changing the weightings in this linear function. However, the extent of improvement was not known due to the ad hoc method used to find the new parameters. Here we develop a branch-and-bound algorithm that finds the set of optimal parameters with the highest average accuracy for a given set of sequences. Our analysis shows that the previous ad hoc parameters are nearly optimal for tRNA and 5S rRNA sequences on both training and testing sets. Moreover, cross-family improvement is possible but more difficult because competing parameter regions favor different families. The results also indicate that restricting the unpaired nucleotide penalty to small values is warranted. This reduction makes analyzing longer sequences using the present techniques more feasible.

bioinformatics↗

The challenge of RNA branching prediction: a parametric analysis of multiloop initiation under thermodynamic optimization

Prediction of RNA base pairings yields insight into molecular structure, and therefore function. The most common methods predict an optimal structure under the standard thermodynamic model. One component of this model is the equation which governs the cost of branching, where three or more helical "arms" radiate out from a multiloop (also known as a junction). The multiloop initiation equation has three parameters; changing those values can significantly alter the predicted structure. We give a complete analysis of the prediction accuracy, stability, and robustness for all possible parameter combinations for a diverse set of tRNA sequences, and also for 5S rRNA. We find that the accuracy can often be substantially improved on a per sequence basis. However, simultaneous improvement within families, and most especially between families, remains a challenge.

bioinformatics↗