Methods in molecular biology
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Whole-genome bisulfite sequencing (WGBS) has become a powerful tool to dissect genome-wide methylation profiles at single-base resolution. In this chapter we describe in detail the bioinformatics pipeline used for the analysis of ARGONAUTE-dependent DNA methylation in Arabidopsis thaliana. We provide tools and command lines used for mapping bisulfite sequencing reads, for estimating methylation levels at individual cytosine sites, for identifying differentially methylated regions (DMRs), and for calculating methylation levels of DMRs.
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High-throughput proteomics studies generate large amounts of data. Biological interpretation of these large scale datasets is often challenging. ⋯ In this chapter, we describe various analyses that can be performed and bioinformatics tools and resources that enable users to do the analyses. Many Web-based and stand-alone tools are relatively user-friendly and can be used by most biologists without significant assistance.
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Traditional bottom-up mass spectrometry-based proteomics relies on the use of an enzyme, often trypsin, to generate small peptides (typically < 25 amino acids long). In top-down proteomics, proteins remain intact and are directly measured within the mass spectrometer. ⋯ In this chapter, we will show the analysis of intact protein spectra through deconvolution, deisotoping, and searching with ProSight Lite, a free, vendor-agnostic tool for the analysis of top-down mass spectrometry data. We will illustrate with two examples of intact protein fragmentation spectra and discuss the iterative use of the software to characterize proteoforms and discover the sites of post-translational modifications.
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The bottom-up proteomic analysis of cell line and tissue samples to a depth > 10,000 proteins still represents a considerable challenge because of the sheer number of peptides generated by proteolytic digestions and the high dynamic range of protein expression. As a result, comprehensive protein coverage requires multidimensional peptide separation. ⋯ The protocol includes optimized sample preparation steps (lysis with the aid of mechanical disruption, one-step disulfide bridge reduction and alkylation), setup and operation of hSAX columns and gradients, desalting of hSAX fractions prior to LC-MS/MS analysis, and suggestions for the choice of data acquisition parameters and data analysis using MaxQuant. Application of the protocol to the fractionation of 300 μg human brain tissue digest led to the identification of more than 100,000 unique peptide sequences representing over 10,195 proteins and 9,500 genes in 3 days of measurement time on a Q Exactive Plus mass spectrometer.
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Recent advancements in high-throughput technologies such as mass spectrometry have led to an increase in the rate at which data is generated and accumulated. As a result, standard statistical methods no longer suffice as a way of analyzing such gigantic amounts of data. Network analysis, the evaluation of how nodes relate to one another, has over the years become an integral tool for analyzing high throughput proteomic data as they provide a structure that helps reduce the complexity of the underlying data. ⋯ These tools enable the visualization of proteins as networks of signaling, regulatory, and biochemical interactions. In this chapter, we provide an overview of networks and network theory fundamentals for the analysis of proteomics data. We further provide an overview of interaction databases and network tools which are frequently used for analyzing proteomics data.