Back

Comparative analysis of RAN translation from CAG repeats within the Huntingtin coding sequence

Krans, A.; Albertson, R. M.; Maltby, C.; Todd, P.

2025-09-04 neuroscience
10.1101/2025.09.02.673827 bioRxiv
Show abstract

Repeat associated non-AUG (RAN) translation is a non-canonical initiation event that occurs in the absence of a start codon in repeat expansion disorders, generating aggregation-prone proteins which may contribute to pathogenicity. The mechanism by which repeats trigger RAN translation is not completely understood, with most prior work focused on how repeats might elicit initiation when placed within a 5 leader in reporter plasmids. However, RAN translation is also reported to generate out-of-frame proteins in Huntington disease (HD), where a CAG repeat expansion in exon 1 of the Huntingtin gene (HTT) resides within the coding sequence of the gene. To explore this process, we generated a series of RAN translation-specific reporter constructs that include the 5 leader and first exon of HTT and compared their translation to CGG and GGGGCC repeats. CAG repeats support RAN translation in both the alanine (GCA) and glutamine (CAG) frames in both the presence and absence of upstream start codons or near-AUG cognate codons. HTT RAN translation in the alanine frame is comparable in efficiency to polyalanine RAN translation from CGG repeats and exhibits cap-dependence and selective enhancement by activation of the integrated stress response. Importantly, this translation was readily detectable from in vitro transcribed RNAs transfected into neurons or cellular lysates, suggesting that plasmid based aberrant splicing into CAG repeats does not explain the observed phenomena. CAG repeats in the context of HTT exon 1 elicit neuronal toxicity in the absence of any AUG initiation codons. Taken together, these data suggest that RAN translation shares key mechanistic parameters across different repeat sequences and surrounding RNA contexts with implications for therapy development.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.