We have developed a workflow that robustly identifies intact glycopeptides at a proteome scale using stepped-energy mass-spectrometry.This workflow has decoded as a computational strategy called as pGlyco+,a dedicated search engine for glycopeptide analysis.Our high-throughput method has enable us to interpret a total of 5,564 distinct site-specific N-glycoforms,on 1,478 glycosylation sites of relative 809 glycoproteins from five mouse tissues,and in 20 hours of mass-spectrometry analysis.Strict quality control(1%false discovery rate)was performed not only for the peptide matches but novel for glycan ones as well.We have also compared our search engine with a routinely used glycoproteomic software and believed that our method is a rather robust tool for site-specific glycosylation study likely.To demonstrate the importance of comprehensive quality control for both the glycan and peptide matches,we have conducted a fair performance comparison between pGlyco+ and Byonic,a routinely used glycoproteomic software: exactly same MS/MS data,and parameters such as tolerance,databases of protein and glycan were used.Under 1%FDR,pGlyco+ identified 23,086 glycopeptide spectra,while Byonic only identified 8,866 glycopeptide spectra.The corresponding number of identified distinct glycopeptides were 5,430 for pGlyco+ and 2,206 for Byoinc.To reach the same sensitivity of pGlyco+(23,086 identified spectra under 1%FDR),Byonic would have unacceptably 30%FDR using the same criteria.