以高耐热性玉米品种郑单958、低耐热性玉米品种先玉335为试验材料,以正常生长条件为对照(CK),利用半自动伸缩高温棚进行花期高温胁迫(HT)处理,通过circRNA高通量测序筛选高温胁迫下不同玉米品种花粉中差异表达的环状RNA(circRNA),对其...以高耐热性玉米品种郑单958、低耐热性玉米品种先玉335为试验材料,以正常生长条件为对照(CK),利用半自动伸缩高温棚进行花期高温胁迫(HT)处理,通过circRNA高通量测序筛选高温胁迫下不同玉米品种花粉中差异表达的环状RNA(circRNA),对其来源基因进行GO和KEGG富集分析,并筛选具有miRNA结合位点的差异表达circRNA,预测其下游目的基因,分析玉米花粉中响应高温胁迫的潜在circRNA-miRNA-mRNA共表达调控网络,从多层面解析玉米花粉中调控高温胁迫的分子作用机制,为提高玉米品种的耐热性提供理论依据。结果表明,在郑单958、先玉335不同样本中共鉴定出1 843个不同的circRNA,它们在玉米染色体中的分布不同。每个circRNA所包含的外显子数目也不相同,其中,大多数(624个)circRNA只含有1个外显子。在郑单958花粉中共鉴定出1 563个circRNA,其中,CK958-1、CK958-2、CK958-3中分别鉴定出305、213、356个circRNA,HT958-1、HT958-2、HT958-3中分别鉴定出222、242、225个circRNA。在先玉335花粉中共鉴定出1 423个circRNA,其中,CK335-1、CK335-2、CK335-3中分别鉴定出272、188、229个circRNA,HT335-1、HT335-2、HT335-3中分别鉴定出259、237、238个circRNA。不同样本中占比最高的均为外显子circRNA。circRNA与其来源基因不是一一对应的关系,有748个circRNA来源基因通过反向剪接机制只形成1个circRNA,156个circRNA来源基因通过反向剪接机制各自形成2个circRNA。在郑单958高温胁迫花粉与对照花粉对比组(HT958 vs CK958)中共筛选到9个差异表达circRNA,其中2个circRNA呈上调表达,其来源基因显著富集到焦磷酸酶活性、核苷酸磷酸代谢过程、糖基磷脂酰肌醇(GPI)锚定代谢过程等17个GO条目,显著富集到GPI锚定生物合成、代谢途径等KEGG通路。在先玉335高温胁迫花粉与对照花粉对比组(HT335 vs CK335)中共筛选到1个差异表达circRNA,其来源基因没有显著富集到任何GO条目、KEGG通路。在郑单958高温胁迫花粉与先玉335高温胁迫花粉对比组(HT958 vs HT335)中共筛选到17个差异表达circRNA,其中6个circRNA呈上调表达,其来源基因显著富集到内质网系统、高尔基相关囊泡膜、膜蛋白水解等16个GO条目中,没有显著富集到任何KEGG代谢通路。5个circRNA具有miRNA结合位点,可以作为海绵岛吸附miRNA间接调控下游靶标基因的表达,构建了包括5个circRNA、5个不同家族miRNA、2个mRNA在内的circRNA-miRNA-mRNA共表达调控网络。筛选到了54个circRNA包含内部核糖体进入位点(IRES),可以翻译表达多肽或者蛋白质直接作用于靶标基因。展开更多
Circular RNAs(circRNAs) are covalently closed single-stranded RNA molecules, which are widespread in eukaryotic cells. As regulatory molecules, circRNAs have various functions, such as regulating gene expression, bind...Circular RNAs(circRNAs) are covalently closed single-stranded RNA molecules, which are widespread in eukaryotic cells. As regulatory molecules, circRNAs have various functions, such as regulating gene expression, binding mi RNAs or proteins, and being translated into proteins, which are important for cell proliferation and cell differentiation, individual growth and development, as well as many other biological processes. However, compared with that in animal models, studies of circRNAs in plants lags behind and,particularly, the regulatory mechanisms of biogenesis and molecular functions of plant circRNAs remain elusive. Recent studies have shown that circRNAs are wide spread in plants with tissue-or developmentspecific expression patterns and are responsive to a variety of environmental stresses. In this review, we summarize these advances, focusing on the regulatory mechanisms of biogenesis, molecular and biological functions of circRNAs, and the methods for investigating circRNAs. We also discuss the challenges and the prospects of plant circ RNA studies.展开更多
CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs a...CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs and diseases can enhance our understanding of diseases and provide new strategies and tools for early diagnosis,treatment,and disease prevention.However,existing models have limitations in accurately capturing similarities,handling the sparse and noise attributes of association networks,and fully leveraging bioinformatical aspects from multiple viewpoints.To address these issues,this study introduces a new non-negative matrix factorization-based framework called NMFMSN.First,we incorporate circRNA sequence data and disease semantic information to compute circRNA and disease similarity,respectively.Given the sparse known associations between circRNAs and diseases,we reconstruct the network to complete more associations by imputing missing links based on neighboring circRNA and disease interactions.Finally,we integrate these two similarity networks into a non-negative matrix factorization framework to identify potential circRNA-disease associations.Upon conducting 5-fold cross-validation and leave-one-out cross-validation,the AUC values for NMFMSN reach 0.9712 and 0.9768,respectively,outperforming the currently most advanced models.Case studies on lung cancer and hepatocellular carcinoma show that NMFMSN is a good way to predict new associations between circRNAs and diseases.展开更多
文摘以高耐热性玉米品种郑单958、低耐热性玉米品种先玉335为试验材料,以正常生长条件为对照(CK),利用半自动伸缩高温棚进行花期高温胁迫(HT)处理,通过circRNA高通量测序筛选高温胁迫下不同玉米品种花粉中差异表达的环状RNA(circRNA),对其来源基因进行GO和KEGG富集分析,并筛选具有miRNA结合位点的差异表达circRNA,预测其下游目的基因,分析玉米花粉中响应高温胁迫的潜在circRNA-miRNA-mRNA共表达调控网络,从多层面解析玉米花粉中调控高温胁迫的分子作用机制,为提高玉米品种的耐热性提供理论依据。结果表明,在郑单958、先玉335不同样本中共鉴定出1 843个不同的circRNA,它们在玉米染色体中的分布不同。每个circRNA所包含的外显子数目也不相同,其中,大多数(624个)circRNA只含有1个外显子。在郑单958花粉中共鉴定出1 563个circRNA,其中,CK958-1、CK958-2、CK958-3中分别鉴定出305、213、356个circRNA,HT958-1、HT958-2、HT958-3中分别鉴定出222、242、225个circRNA。在先玉335花粉中共鉴定出1 423个circRNA,其中,CK335-1、CK335-2、CK335-3中分别鉴定出272、188、229个circRNA,HT335-1、HT335-2、HT335-3中分别鉴定出259、237、238个circRNA。不同样本中占比最高的均为外显子circRNA。circRNA与其来源基因不是一一对应的关系,有748个circRNA来源基因通过反向剪接机制只形成1个circRNA,156个circRNA来源基因通过反向剪接机制各自形成2个circRNA。在郑单958高温胁迫花粉与对照花粉对比组(HT958 vs CK958)中共筛选到9个差异表达circRNA,其中2个circRNA呈上调表达,其来源基因显著富集到焦磷酸酶活性、核苷酸磷酸代谢过程、糖基磷脂酰肌醇(GPI)锚定代谢过程等17个GO条目,显著富集到GPI锚定生物合成、代谢途径等KEGG通路。在先玉335高温胁迫花粉与对照花粉对比组(HT335 vs CK335)中共筛选到1个差异表达circRNA,其来源基因没有显著富集到任何GO条目、KEGG通路。在郑单958高温胁迫花粉与先玉335高温胁迫花粉对比组(HT958 vs HT335)中共筛选到17个差异表达circRNA,其中6个circRNA呈上调表达,其来源基因显著富集到内质网系统、高尔基相关囊泡膜、膜蛋白水解等16个GO条目中,没有显著富集到任何KEGG代谢通路。5个circRNA具有miRNA结合位点,可以作为海绵岛吸附miRNA间接调控下游靶标基因的表达,构建了包括5个circRNA、5个不同家族miRNA、2个mRNA在内的circRNA-miRNA-mRNA共表达调控网络。筛选到了54个circRNA包含内部核糖体进入位点(IRES),可以翻译表达多肽或者蛋白质直接作用于靶标基因。
基金supported by grants of Key project of intergovernmental International Science and Technology Innovation Cooperation, MOST of China (2022YFE0100500)the National Key Laboratory of Crop Genetic Improvement Self-research Program (ZW18B0102)。
文摘Circular RNAs(circRNAs) are covalently closed single-stranded RNA molecules, which are widespread in eukaryotic cells. As regulatory molecules, circRNAs have various functions, such as regulating gene expression, binding mi RNAs or proteins, and being translated into proteins, which are important for cell proliferation and cell differentiation, individual growth and development, as well as many other biological processes. However, compared with that in animal models, studies of circRNAs in plants lags behind and,particularly, the regulatory mechanisms of biogenesis and molecular functions of plant circRNAs remain elusive. Recent studies have shown that circRNAs are wide spread in plants with tissue-or developmentspecific expression patterns and are responsive to a variety of environmental stresses. In this review, we summarize these advances, focusing on the regulatory mechanisms of biogenesis, molecular and biological functions of circRNAs, and the methods for investigating circRNAs. We also discuss the challenges and the prospects of plant circ RNA studies.
基金the Gansu Province Industrial Support Plan(No.2023CYZC-25)Natural Science Foundation of Gansu Province(No.23JRRA770)the National Natural Science Foundation of China(No.62162040)。
文摘CircRNAs,widely found throughout the human bodies,play a crucial role in regulating various biological processes and are closely linked to complex human diseases.Investigating potential associations between circRNAs and diseases can enhance our understanding of diseases and provide new strategies and tools for early diagnosis,treatment,and disease prevention.However,existing models have limitations in accurately capturing similarities,handling the sparse and noise attributes of association networks,and fully leveraging bioinformatical aspects from multiple viewpoints.To address these issues,this study introduces a new non-negative matrix factorization-based framework called NMFMSN.First,we incorporate circRNA sequence data and disease semantic information to compute circRNA and disease similarity,respectively.Given the sparse known associations between circRNAs and diseases,we reconstruct the network to complete more associations by imputing missing links based on neighboring circRNA and disease interactions.Finally,we integrate these two similarity networks into a non-negative matrix factorization framework to identify potential circRNA-disease associations.Upon conducting 5-fold cross-validation and leave-one-out cross-validation,the AUC values for NMFMSN reach 0.9712 and 0.9768,respectively,outperforming the currently most advanced models.Case studies on lung cancer and hepatocellular carcinoma show that NMFMSN is a good way to predict new associations between circRNAs and diseases.
