近年来，研究表明人类以及其它模式生物的“非编码区”上存在小开放阅读框，能够编码产生长度在150个氨基酸以下的肽段(SEPs)，而且部分肽段已被证实在代谢、发育以及细胞凋亡等生物学过程中扮演重要角色。目前基于“bottom-up”以及数据库检索的策略在人类肿瘤细胞中鉴定到348个SEPs，不及预测数量的20%，而且较低的序列覆盖率不利于深入挖掘SEPs的表达特征。因此，急需建立大规模、准确鉴定完整SEPs的分析方法。根据SEPs序列短、分子量小的特点，本项目拟在前人工作基础上，通过多维液相色谱分离与质谱联用进一步开发SEPs的“top-down”分析方法，实现全序列覆盖率检测。此外，在数据处理上辅以从头测序，发挥其不依赖数据库检索的优势，鉴定全新的SEPs。通过上述不同分析策略的整合，从而探索出大规模提高SEPs鉴定数量和覆盖率的新方法，为深入开展SEPs功能研究提供技术和数据支持。

In recent years, it has been widely reported that the short/small open reading frames (smORFs) exist in the ‘non-coding regions’ of human and other model organisms, which can encode polypeptides (SEPs) with a length less than 150 amino acids residues. A small number of well-studied SEPs have indicated that these polypeptides may act as important regulators in many fundamental biological processes such as metabolism, development and cell apoptosis. Nowadays, only 348 SEPs have been detected in human tumour cells based on bottom-up proteomics and database search, which accounts for 20% less of computational prediction. In addition, the lower sequence coverage impedes profound excavation on the SEPs expression features. Therefore, it is calling for analytical method for large scale detection of complete SEPs. According to the short sequence and lower molecular mass characteristics of SEPs, we tend to exploit a top-down approach to detect SEPs based on multidimensional liquid chromatography separation and mass spectrometric analysis, which will obtain the complete sequence coverage of SEPs. Furthermore, peptide de novo sequencing that is independent from database is also considered in the data processing to discover more novel SEPs. The integration of above mentioned analytic strategy will create a new method to improve the number and coverage rate of SEPs in large scale, and provides new means and data support for the further functional study of SPEs.