m+Medelevator.RU
← Поиск публикаций
Biomolecules · 2026

Comparative Analysis of Reported Gene Targets and Binding Regions of Glu-CTC tRNA Fragments Across Human Diseases.

СтатьяСравнительное исследованиеНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Gulati Nikita, Grigoriev Andrey

Аннотация

Recurrent detection of overlapping tRNA-derived fragments (tRFs) across diverse disease conditions supports the emerging view that tRFs may act as regulatory molecules rather than random degradation products. While cases of identical tRFs have been described, their comparative analyses are lacking. tRF-Glu-CTC is one such fragment, repeatedly detected in various pathological conditions. We performed a comparative analysis of tRF-Glu-CTC isoforms, their targets and binding regions reported in 18 disease-associated studies. An 18-nucleotide sequence, TCCCTGGTGGTCTAGTGG, was identified in most (14 out of 18) of these studies despite differences in tRF naming, length and disease context. Several reported tRF targets showed consistent binding regions, with reverse complementarity to the tRF sequence. Comparison with databases of tRF targets, tatDB and tRFTar, identified matching target entries and sequence overlaps, often involving common regions rather than full-length matches. Exploratory analysis of target homologs further illustrated that related genes might share candidate target sites. Our findings indicate that tRF-Glu-CTC represents a recurrent candidate regulatory fragment potentially relevant in a broad range of human diseases. Its structural stability, extracellular vesicle association, detection in multiple species and a core sequence shared between related isoforms support further investigation of its biological and translational relevance. Our work illustrates how tRF target databases can be leveraged to advance smaller-scale tRF studies.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты