Gutenberg Open Science
The Open Science Repository of Johannes Gutenberg University Mainz.
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Recent Submissions
Simulating Bloch points using micromagnetic and Heisenberg models
(2025) Winkler, Thomas Brian; Beg, Marijan; Lang, Martin; Kläui, Mathias; Fangohr, Hans
Homorepeat variability within the human population
(2024) Mier, Pablo; Andrade-Navarro, Miguel A.; Morett, Enrique
Genetic variation within populations plays a crucial role in driving evolution. Unlike the average protein sequence, the evolution of homorepeats can be influenced by DNA replication slippage, when DNA polymerases either add or skip repeats of nucleotides. While there are some diseases known to be caused by abnormal changes in the length of amino acid homorepeats, naturally occurring variations in homorepeat length remain relatively unexplored. In our study, we examined the variation in amino acid homorepeat length of human individuals by analyzing 125 748 exomes, as well as 15 708 whole genomes. Our analyses revealed significant variability in homorepeat length across the human population, indicating that these motifs are prone to mutations at higher rates than non repeat sequences. We focused our study on glutamine homorepeats, also known as polyQ sequences, and found that shorter polyQ sequences tend to exhibit greater length variation, while longer ones primarily undergo deletions. Notably, polyQ sequencesthat are more conserved across primates tend to show less variation within the human population, indicating stronger selective pressure to maintain their length. Overall, our results demonstrate that there is large natural variation in the length of homorepeats within the human population, with no apparent impact on observable traits.
DORQ-seq : high-throughput quantification of femtomol tRNA pools by combination of cDNA hybridization and Deep sequencing
(2024) Kristen, Marco; Lander, Marc; Kilz, Lea-Marie; Gleue, Lukas; Jörg, Marko; Bregeon, Damien; Hamdane, Djemel; Marchand, Virginie; Motorin, Yuri; Friedland, Kristina; Helm, Mark
Due to its high modification content tRNAs are notoriously hard to quantify by reverse transcription and RNAseq. Bypassing numerous biases resulting from concatenation of enzymatic treatments, we here report a hybrid approach that harnesses the advantages of hybridization-based and deep sequencing–based approaches. The method renders obsolete any RNAseq related workarounds and correction factors that affect accuracy, sensitivity, and turnaround time. Rather than by reverse transcription, quantitative information on the isoacceptor composition of a tRNA pool is transferred to a cDNA mixture in a single step procedure, thereby omitting all enzymatic conversations except for the subsequent barcoding PCR. As a result, a detailed tRNA composition matrix can be obtained from femtomolar amounts of total tRNA. The method is fast, low in cost, and its bioinformatic data workup surprisingly simple. These properties make the approach amenable to high-throughput investigations including clinical samples, as we have demonstrated by application to a collection of variegated biological questions, each answered with novel findings. These include tRNA pool quantification of polysome-bound tRNA, of tRNA modification knockout strains under stress conditions, and of Alzheimer patients’ brain tissues.