Prolonged inflammation in patients hospitalized for coronavirus disease 2019 (COVID-19) resolves 2 years after infection.

Long-term complications from coronavirus disease 2019 (COVID-19) are concerning, as survivors can develop subclinical multiorgan dysfunction. It is unknown if such complications are due to prolonged inflammation, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination may reduce sequela. We conducted a prospective longitudinal study on hospitalized patients over 24 months. Clinical symptoms were collected by self-reporting during follow-up, along with blood samples for quantification of inflammatory markers and immune cell frequencies. All patients were given one dose of mRNA vaccine at 12-16 months. Their immune profiles at 12 and 24 months were compared. Approximately 37% and 39% of our patients reported post-COVID-19 symptoms at 12 and 24 months, respectively. The proportion of symptomatic patients with more than one symptom decreased from 69% at 12 months to 56% at 24 months. Longitudinal cytokine profiling revealed a cluster of individuals with persistently high inflammatory cytokine levels 12 months after infection. Patients with prolonged inflammation showed elevated terminally differentiated memory T cells in their blood; 54% had symptoms at 12 months. The majority of inflammatory markers and dysregulated immune cells in vaccinated patients recovered to a healthy baseline at 24 months, even though symptoms persisted. Post-COVID-19 symptoms can linger for 2 years after the initial infection and are associated with prolonged inflammation. Prolonged inflammation in hospitalized patients resolves after 2 years. We define a set of analytes associated with persistent inflammation and presence of symptoms, which could be useful biomarkers for identifying and monitoring high-risk survivors.

Genome-wide analysis of CRISPR perturbations indicates that enhancers act multiplicatively and without epistatic-like interactions.

A single gene may be regulated by multiple enhancers, but how they work in concert to regulate transcription is poorly understood. Prior studies have mostly examined enhancers at single loci and have reached inconsistent conclusions about whether epistatic-like interactions exist between them. To analyze enhancer interactions throughout the genome, we developed a statistical framework for CRISPR regulatory screens that utilizes negative binomial generalized linear models that account for variable guide RNA (gRNA) efficiency. We reanalyzed a single-cell CRISPR interference experiment that delivered random combinations of enhancer-targeting gRNAs to each cell and interrogated interactions between 3,808 enhancer pairs. We found that enhancers act multiplicatively with one another to control gene expression, but our analysis provides no evidence for interaction effects between pairs of enhancers regulating the same gene. Our findings illuminate the regulatory behavior of multiple enhancers and our statistical framework provides utility for future analyses studying interactions between enhancers.

Deletion mapping of regulatory elements for GATA3 in T cells reveals a distal enhancer involved in allergic diseases.

GATA3 is essential for T cell differentiation and is surrounded by genome-wide association study (GWAS) hits for immune traits. Interpretation of these GWAS hits is challenging because gene expression quantitative trait locus (eQTL) studies lack power to detect variants with small effects on gene expression in specific cell types and the genome region containing GATA3 contains dozens of potential regulatory sequences. To map regulatory sequences for GATA3, we performed a high-throughput tiling deletion screen of a 2 Mb genome region in Jurkat T cells. This revealed 23 candidate regulatory sequences, all but one of which is within the same topological-associating domain (TAD) as GATA3. We then performed a lower-throughput deletion screen to precisely map regulatory sequences in primary T helper 2 (Th2) cells. We tested 25 sequences with ∼100 bp deletions and validated five of the strongest hits with independent deletion experiments. Additionally, we fine-mapped GWAS hits for allergic diseases in a distal regulatory element, 1 Mb downstream of GATA3, and identified 14 candidate causal variants. Small deletions spanning the candidate variant rs725861 decreased GATA3 levels in Th2 cells, and luciferase reporter assays showed regulatory differences between its two alleles, suggesting a causal mechanism for this variant in allergic diseases. Our study demonstrates the power of integrating GWAS signals with deletion mapping and identifies critical regulatory sequences for GATA3.

Discovering functional sequences with RELICS, an analysis method for CRISPR screens.

CRISPR screens are a powerful technology for the identification of genome sequences that affect cellular phenotypes such as gene expression, survival, and proliferation. By targeting non-coding sequences for perturbation, CRISPR screens have the potential to systematically discover novel functional sequences, however, a lack of purpose-built analysis tools limits the effectiveness of this approach. Here we describe RELICS, a Bayesian hierarchical model for the discovery of functional sequences from CRISPR screens. RELICS specifically addresses many of the challenges of non-coding CRISPR screens such as the unknown locations of functional sequences, overdispersion in the observed single guide RNA counts, and the need to combine information across multiple pools in an experiment. RELICS outperforms existing methods with higher precision, higher recall, and finer-resolution predictions on simulated datasets. We apply RELICS to published CRISPR interference and CRISPR activation screens to predict and experimentally validate novel regulatory sequences that are missed by other analysis methods. In summary, RELICS is a powerful new analysis method for CRISPR screens that enables the discovery of functional sequences with unprecedented resolution and accuracy.

R loops regulate promoter-proximal chromatin architecture and cellular differentiation.

Numerous chromatin-remodeling factors are regulated by interactions with RNA, although the contexts and functions of RNA binding are poorly understood. Here we show that R loops, RNA-DNA hybrids consisting of nascent transcripts hybridized to template DNA, modulate the binding of two key chromatin-regulatory complexes, Tip60-p400 and polycomb repressive complex 2 (PRC2) in mouse embryonic stem cells (ESCs). Like PRC2, the Tip60-p400 histone acetyltransferase complex binds to nascent transcripts; however, transcription promotes chromatin binding of Tip60-p400 but not PRC2. Interestingly, we observed higher Tip60-p400 and lower PRC2 levels at genes marked by promoter-proximal R loops. Furthermore, disruption of R loops broadly decreased Tip60-p400 occupancy and increased PRC2 occupancy genome wide. In agreement with these alterations, ESCs partially depleted of R loops exhibited impaired differentiation. These results show that R loops act both positively and negatively in modulating the recruitment of key pluripotency regulators.

High-resolution chromatin dynamics during a yeast stress response.

Covalent histone modifications are highly conserved and play multiple roles in eukaryotic transcription regulation. Here, we mapped 26 histone modifications genome-wide in exponentially growing yeast and during a dramatic transcriptional reprogramming-the response to diamide stress. We extend prior studies showing that steady-state histone modification patterns reflect genomic processes, especially transcription, and display limited combinatorial complexity. Interestingly, during the stress response we document a modest increase in the combinatorial complexity of histone modification space, resulting from roughly 3% of all nucleosomes transiently populating rare histone modification states. Most of these rare histone states result from differences in the kinetics of histone modification that transiently uncouple highly correlated marks, with slow histone methylation changes often lagging behind the more rapid acetylation changes. Explicit analysis of modification dynamics uncovers ordered sequences of events in gene activation and repression. Together, our results provide a comprehensive view of chromatin dynamics during a massive transcriptional upheaval.

Painting by numbers: increasing the parts list for chromatin domains.

In this issue of Molecular Cell, van Bemmel and colleagues (2013) report the genome-wide mapping of 42 novel chromatin factors, systematically identifying new components of the various chromatin domains present in fly cells.

Systematic dissection of roles for chromatin regulators in a yeast stress response.

Packaging of eukaryotic genomes into chromatin has wide-ranging effects on gene transcription. Curiously, it is commonly observed that deletion of a global chromatin regulator affects expression of only a limited subset of genes bound to or modified by the regulator in question. However, in many single-gene studies it has become clear that chromatin regulators often do not affect steady-state transcription, but instead are required for normal transcriptional reprogramming by environmental cues. We therefore have systematically investigated the effects of 83 histone mutants, and 119 gene deletion mutants, on induction/repression dynamics of 170 transcripts in response to diamide stress in yeast. Importantly, we find that chromatin regulators play far more pronounced roles during gene induction/repression than they do in steady-state expression. Furthermore, by jointly analyzing the substrates (histone mutants) and enzymes (chromatin modifier deletions) we identify specific interactions between histone modifications and their regulators. Combining these functional results with genome-wide mapping of several histone marks in the same time course, we systematically investigated the correspondence between histone modification occurrence and function. We followed up on one pathway, finding that Set1-dependent H3K4 methylation primarily acts as a gene repressor during multiple stresses, specifically at genes involved in ribosome biosynthesis. Set1-dependent repression of ribosomal genes occurs via distinct pathways for ribosomal protein genes and ribosomal biogenesis genes, which can be separated based on genetic requirements for repression and based on chromatin changes during gene repression. Together, our dynamic studies provide a rich resource for investigating chromatin regulation, and identify a significant role for the "activating" mark H3K4me3 in gene repression.