非編碼RNA是指不能翻譯成蛋白的功能性RNA分子,佔人類基因組的98%,之前被認為是沒有功能的,稱為「垃圾RNA」,或是叫「暗物質」。隨著高通量測序技術,基因晶片以及生物信息學的快速發展,這些大量的非編碼RNA在人類生物學和疾病中發揮的作用被逐步揭示出來。
近年來大量研究表明非編碼RNA在人類疾病的調控中扮演了越來越重要的角色。包括腫瘤、神經系統疾病、心血管的發生以及參與免疫與代謝疾病調控、胚胎發育調控等,為開發疾病診斷標誌物以及篩選新藥靶標帶來了諸多新的方向。
為此,生物谷主辦2018(第六屆)非編碼RNA與疾病研討會。目前嘉賓確認過半,下面就一起搶先預覽下部分嘉賓摘要。
中南大學腫瘤研究所
Long non-coding RNAs (lncRNA) have been associated with various types of cancer, however, the precise role of many lncRNAs in tumorigenesis remains elusive. Here we demonstrate that the cytosolic lncRNA P53RRA is downregulated in cancers and functions as a tumor suppressor by inhibiting cancer progression. Chromatin remodeling proteins LSH and Cfp1 silenced or increased P53RRAexpression respectively. P53RRA bound Ras GTPase-activating protein-binding protein 1 (G3BP1) using nucleotides 1 and 871 of P53RRA and the RRM interaction domain of G3BP1 (aa 177-466). The cytosolic P53RRA-G3BP1 interaction displaced p53 from a G3BP1 complex resulting in greater p53 retention in the nucleus which led to cell cycle arrest, apoptosis, and ferroptosis. P53RRApromoted ferroptosis and apoptosis by affecting transcription of several metabolic genes. Low P53RRA expression significantly correlated with poor survival in patients with breast and lung cancers harboring wild-type p53. These data show that lncRNAs can directly interact with the functional domain of signaling proteins in the cytoplasm, thus regulating p53 modulators to suppress cancer progression.
天津醫科大學總醫院
小鼠創傷性腦損傷後腦細胞外間隙外泌體中環狀RNA表達的變化
通過分離小鼠腦細胞外間隙外泌體,應用高通量測序技術分析小鼠創傷性腦損傷(traumatic brain injury,TBI)後腦細胞外間隙外泌體中circRNA(circRNA)表達的變化。對差異性表達的circRNA進行相關的生物信息學分析,闡明外泌體及circRNA的調控功能,為TBI的分子生物學機制研究提供新思路,為TBI的臨床診斷提供新的分子標記物,為TBI的治療提供新策略。
中山大學生命科學學院
Interactions and Regulatory Networks of Non-coding RNAs and RNA-binding Proteins
Non-coding RNAs (ncRNAs, e.g. miRNAs, lncRNAs, circRNAs) play important roles in deciding cellular function and fate that have been implicated in regulating tumorigenesis through interaction with RNA-binding proteins (RBPs). However, for the majority of ncRNAs, the mechanism underlying their interaction with RBPs remains unknown. In our previous studies, we have developed several software to discover novel ncRNAs and decode their targetome and interactome. In the present study, by integrating large-scale CLIP-seq and degradome-seq datasets, we developed novel algorithms and platforms to systematically identify the regulatory networks between ncRNAs and RBPs, and predict potential functions of novel ncRNAs.Through combining cancer genomics data, our algorithms and platforms can identify novel tumor-specific ncRNA-RBP interaction networks, and promote our understanding of their roles in carcinogenesis and progression.