Data-independent Acquisition Proteomics And Its Applications In Rice

Proteins are the direct performers of life activities,and the study of proteomics is an integral part of the multidisciplinary integration study.Mass spectrometry technology with high-throughput,high sensitivity,high-resolution features,is the current mainstream detection and analysis methods in the proteomics.Conventional data-dependent mass spectrometry patterns can accurately detect high abundance target peptides but do not cover all of the proteins in the sample.Data independent acquisition mode can detect all peptides without discrimination,accordingly obtain all the peptide information of the sample,but its bottleneck is that the detection data are complex and difficult to analyze.Therefore,this study optimized the data independent acquisition model,hoping to reduce the difficulty of data analysis,get higher quality proteomics information.In this study,I modified and optimized the classical protein extraction method for rice root tissue,established the experimental protocol of phenol extraction,and improved the extraction efficiency.Now 24,535 peptides in the single mass spectrometry and 3,334 proteins can be obtained.Secondly,I collected the data-dependent mass spectrometry data,scored the spectrum by Spectra ST software,and selected the high-quality spectrum,reduce the noise to established a spectrum database which can be directly used for the identification of subsequent mass spectrometry,and the identification results show that more peptides can be identified using the actual spectrogram than the theory spectrogram based on protein sequence.Thirdly,we used Coovar to translate the variation nucleotide sequence of different rice varieties into peptide sequence,and integrated them into the protein sequence database.The database was validated by variability information of Minghui 63,and we identified 1321 variation peptide.Based on the data-independent acquisition mode,a new acquisition window was designed and analyzed by mass spectrometry.We obtained 13109 peptides and 6329 proteins in 25 rice varieties.Among them,we quantify 9528 peptides and 4185 proteins which repeated at least 5 times in 15 varieties.And the difference between the experimental group and the control group was investigated.We found the protein expression of each sample was similar,but the difference between the experimental group and the control group was not significant.Short sampling time or stability of proteomic expression regulation maybe the reason.Finally,we compared the relationship between protein and transcriptome data in rice root under nitrogen stress,and found some genes related to nitrogen metabolism process by GO analysis.This study deepens our understanding of proteomics and mass spectrometry techniques,helps us get more comprehensive protein identification and quantitative information,and the combination of transcriptome and proteomic demonstrated the advantages of integration research and necessity.At the same time,based on the difficulty of the development of the algorithm,this study provides a better idea for the balanced progress of bioinformatics and mass spectrometry.It is expected that this data-independent acquisition model will contribute to the development of proteomics.