共 39 条
Proteomics-driven identification of short open reading frame-encoded peptides
被引:9
作者:
Zhang, Zheng
Li, Yujie
Yuan, Wenqian
Wang, Zhiwei
Wan, Cuihong
[1
,2
]
机构:
[1] Cent China Normal Univ, Sch Life Sci, Wuhan, Hubei, Peoples R China
[2] Cent China Normal Univ, Hubei Key Lab Genet Regulat & Integrat Biol, Wuhan, Hubei, Peoples R China
关键词:
LC;
MS;
method development;
peptidomics;
sample preparation;
short open reading frame;
sORF-encode peptides;
HIDDEN MARKOV MODEL;
PROTEIN INTERACTIONS;
SAMPLE PREPARATION;
LIVING CELLS;
SMALL ORFS;
BOTTOM-UP;
TRANSLATION;
RNA;
DISCOVERY;
REVEALS;
D O I:
10.1002/pmic.202100312
中图分类号:
Q5 [生物化学];
学科分类号:
071010 ;
081704 ;
摘要:
Accumulating evidence has shown that a large number of short open reading frames (sORFs) also have the ability to encode proteins. The discovery of sORFs opens up a new research area, leading to the identification and functional study of sORF encoded peptides (SEPs) at the omics level. Besides bioinformatics prediction and ribosomal profiling, mass spectrometry (MS) has become a significant tool as it directly detects the sequence of SEPs. Though MS-based proteomics methods have proved to be effective for qualitative and quantitative analysis of SEPs, the detection of SEPs is still a great challenge due to their low abundance and short sequence. To illustrate the progress in method development, we described and discussed the main steps of large-scale proteomics identification of SEPs, including SEP extraction and enrichment, MS detection, data processing and quality control, quantification, and function prediction and validation methods.
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页数:17
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