选择性剪接的理论预测

Methods and Tools of Computational Prediction of Alternative Splicing

可变剪接作为真核生物转录后加工机制普遍存在于不同组织、不同发育时期或不同病理状态下的基因表达调控过程中。对同一基因不同剪接变体的研究可使我们更深入的了解发育、进化、疾病发生机理等基本的生物学问题。讨论了一些基于序列比对而建立的可变剪接的理论预测方法,尚存不足之处,有待于进一步完善。

Alternative splicing （AS） is more frequent than previously thought and some genes may produce tens of thousands of different transcripts. A list of AS variants for such genes would be difficult to build and hard to analyze. Moreover, such a list does not show the relationships between different transcripts and does not show the overall structure of all transcripts. A better approach would be to represent all splicing variants for a given gene in a way that captures the relationships between different splicing variants. Here, we provide an overview of current methods for the computational prediction of alternative splicing based on the alignment of genome and transcript sequences. Specific features and limitations of different approaches and software are discussed, particularly those affecting prediction accuracy and assembly of alternative transcripts.