Histones are frequently decorated with covalent modifications. These histone modifications are thought to be involved in various chromatin-dependent processes including transcription. To elucidate the relationship between histone modifications and transcription, we derived quantitative models to predict the expression level of genes from histone modification levels. We found that histone modification levels and gene expression are very well correlated. Moreover, we show that only a small number of histone modifications are necessary to accurately predict gene expression. We show that different sets of histone modifications are necessary to predict gene expression driven by high CpG content promoters (HCPs) or low CpG content promoters (LCPs). Quantitative models involving H3K4me3 and H3K79me1 are the most predictive of the expression levels in LCPs, whereas HCPs require H3K27ac and H4K20me1. Finally, we show that the connections between histone modifications and gene expression seem to be general, as we were able to predict gene expression levels of one cell type using a model trained on another one.high CpG content promoter | low CpG content promoter | regression analysis | transcription T he DNA of eukaryotic organisms is packaged into chromatin, whose basic repeating unit is the nucleosome. A nucleosome is formed by wrapping 147 base pairs of DNA around an octamer of four core histones, H2A, H2B, H3, and H4 (1-5) which are subject to a number of posttranslational covalent modifications [(6); for review, see ref. 7]. These modifications can alter the chromatin structure and function by changing the charge of the nucleosome particle, and/or by recruiting protein complexes either individually or in combination (8). Hence, histone modifications are thought to constitute a "Histone Code," which is read out by proteins to bring about specific downstream effects (9, 10).Histone modifications have been linked to a number of chromatin-dependent processes, including replication, DNA-repair, and transcription. The link between histone modifications and transcription has been particularly intensively studied. It has been found that individual modifications can be associated with transcriptional activation or repression. Acetylation and phosphorylation generally accompany transcription; sumoylation, deimination, and proline isomerization are usually found in transcriptionally silent regions; methylation and ubiquitination are implicated in both activation and repression of transcription (8). Furthermore, the establishment of some modifications is dependent on the presence of other modifications, e.g., the catalysis of H3K4me3 requires the presence of H2BK120ub1 (the so-called trans-tail pathway) and the phosphorylation on serine 5 on the C-terminal domain of RNA polymerase II (pol II) (for review, see ref. 11, which also reviews other examples for the combinatorial action of histone modifications).Transcription proceeds in a series of steps, also referred to as transcription cycle, starting with preinitiation complex form...

COVID-19 is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. Here we develop three protein arrays to measure IgG autoantibodies associated with connective tissue diseases, anti-cytokine antibodies, and anti-viral antibody responses in serum from 147 hospitalized COVID-19 patients. Autoantibodies are identified in approximately 50% of patients but in less than 15% of healthy controls. When present, autoantibodies largely target autoantigens associated with rare disorders such as myositis, systemic sclerosis and overlap syndromes. A subset of autoantibodies targeting traditional autoantigens or cytokines develop de novo following SARS-CoV-2 infection. Autoantibodies track with longitudinal development of IgG antibodies recognizing SARS-CoV-2 structural proteins and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

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The classical DNA recognition sequence of the glucocorticoid receptor (GR) appears to be present at only a fraction of bound genomic regions. To identify sequences responsible for recruitment of this transcription factor (TF) to individual loci, we turned to the high-resolution ChIP-exo approach. We exploited this signal by determining footprint profiles of TF binding at single-base-pair resolution using ExoProfiler, a computational pipeline based on DNA binding motifs. When applied to our GR and the few available public ChIP-exo data sets, we find that ChIP-exo footprints are proteinand recognition sequence-specific signatures of genomic TF association. Furthermore, we show that ChIP-exo captures information about TFs other than the one directly targeted by the antibody in the ChIP procedure. Consequently, the shape of the ChIP-exo footprint can be used to discriminate between direct and indirect (tethering to other DNA-bound proteins) DNA association of GR. Together, our findings indicate that the absence of classical recognition sequences can be explained by direct GR binding to a broader spectrum of sequences than previously known, either as a homodimer or as a heterodimer binding together with a member of the ETS or TEAD families of TFs, or alternatively by indirect recruitment via FOX or STAT proteins. ChIP-exo footprints also bring structural insights and locate DNA:protein crosslink points that are compatible with crystal structures of the studied TFs. Overall, our generically applicable footprintbased approach uncovers new structural and functional insights into the diverse ways of genomic cooperation and association of TFs.