인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Sonchus yellow net virus (SYNV), a negative-sense single-stranded RNA (-ssRNA) virus belonging to the Rhabdoviridae family, encodes six known proteins, including five canonic structural proteins and the nonstructural movement protein Sc4. Using the ORF prediction software ViralORFfinder, we found that SYNV genomic RNA (gRNA) might contain small putative open reading frames (sORFs). However, the functions of these additional sORFs remain largely unexplored. In this study, we identified three conserved sORFs, termed A, B, and C on the gRNA of SYNV. The proteins encoded by these sORFs were found to localize to both the nucleus and cytoplasm. Subcellular localization combined with western blotting revealed a time-dependent decrease in the accumulation of these proteins. Bimolecular fluorescence complementation and co-immunoprecipitation assays confirmed the interactions between A and matrix protein (M), A and phosphoprotein (P), and B and P of SYNV. Mutation of the start codon of B (from AUG to AUA) to block its translation delayed the onset of viral infection, resulting in reduced pathogenicity with milder symptoms and less accumulation of viral RNAs in the late infection stage than the wild-type virus. Ectopic overexpression of A and B via the potato virus X (PVX)-based recombinant vector demonstrated that A and B enhanced PVX-CP accumulation and aggravated mosaic symptoms. These findings reveal the potential coding ability of the gRNA of SYNV and suggest that the identified sORFs may play a significant role in modulating viral pathogenicity. This study also highlights the importance of identifying additional coding capacity in viral genomes, which could provide new insights into the biology of -ssRNA viruses and lead to more opportunities for developing targeted antiviral strategies.
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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