Over the past decade, the data-independent acquisition mode has gained popularity for broad coverage of complex proteomes by LC-MS/MS and quantification of low-abundance proteins. However, there is no consensus in the literature on the best data acquisition parameters and processing tools to use for this specific application. Here, we present the most comprehensive comparison of DIA workflows on Orbitrap instruments published so far in the field of proteomics. Using a standard human 48 proteins mixture (UPS1−Sigma) at 8 different concentrations in an E. coli proteome background, we tested 36 workflows including 4 different DIA window acquisition schemes and 6 different software tools (DIA-NN, DIA-Umpire, OpenSWATH, ScaffoldDIA, Skyline, and Spectronaut) with or without the use of a DDA spectral library. On the basis of the number of proteins identified, quantification linearity and reproducibility, as well as sensitivity and specificity in 28 pairwise comparisons of different UPS1 concentrations, we summarize the major considerations and propose guidelines for choosing the DIA workflow best suited for LC-MS/MS proteomic analyses. Our 96 DIA raw files and software outputs have been deposited on ProteomeXchange for testing or developing new DIA processing tools.

The 3D conformation of the chromatin creates complex networks of noncoding regulatory regions (distal elements) and promoters impacting gene regulation. Despite the importance of the role of noncoding regions in complex diseases, little is known about their interplay within regulatory hubs and implication in multigenic diseases such as schizophrenia. Here we show that cis-regulatory hubs (CRHs) in neurons highlight functional interactions between distal elements and promoters, providing a model to explain epigenetic mechanisms involved in complex diseases. CRHs represent a new 3D model, where distal elements interact to create a complex network of active genes. In a disease context, CRHs highlighted strong enrichments in schizophrenia-associated genes, schizophrenia-associated SNPs, and schizophrenia heritability compared with equivalent structures. Finally, CRHs exhibit larger proportions of genes differentially expressed in schizophrenia compared with promoter-distal element pairs or TADs. CRHs thus capture causal regulatory processes improving the understanding of complex disease etiology such as schizophrenia. These multiple lines of genetic and statistical evidence support CRHs as 3D models to study dysregulation of gene expression in complex diseases more generally.

In the past few years, LC-MS/MS in DIA mode has become a strategy of choice for deep coverage of complex proteomes and accurate quantification of low abundant species. However, there is still no consensus in the literature on the best acquisition parameters and processing tools to use. We present here the largest benchmark of DIA proteomic workflows on Orbitrap instruments ever published. Using a complex proteomic standard, we tested 36 workflows including 4 different acquisition schemes and 6 different software tools (DIA-NN, DIA-Umpire, OpenSWATH, Scaffold-DIA, Skyline and Spectronaut-Pulsar-X) with or without the use of a spectral library. By reporting the protein identifications, linearity, reproducibility, as well as sensitivity and specificity in 28 pairwise comparisons, we propose here a guide book for the users to choose the best DIA strategy for their data. Moreover, our data has been deposited on ProteomeXchange for testing or developing new DIA processing tools.

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