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.

High-Dose Methotrexate in Pediatric Acute Lymphoblastic Leukemia: Predictors of Delayed Clearance and the Effect of Increased Hydration Rate on Methotrexate Clearance.

Objectives High-dose methotrexate (HDMTX) is an important chemotherapeutic agent in the treatment of many cancers. Identification of the predictors of poor clearance during HDMTX infusions could advance the introduction of improved supportive care to prevent toxicities and reduce hospital length of stay. The purpose of this study was to identify relationships between patient physical characteristics and HDMTX clearance in the treatment of pediatric acute lymphoblastic leukemia (ALL). At our hospital, patients who have delayed methotrexate (MTX) clearance during a cycle of HDMTX receive an increased rate of hydration with subsequent cycles. This increase in hydration rate was examined for its potential to mitigate predictors of poor clearance and to prevent nephrotoxicity. Methods This study retrospectively examined the treatment records of 87 pediatric patients diagnosed with ALL who were treated on or according to Children's Oncology Group (COG) protocols AALL0232, AALL0434, AALL1131, and AALL1231. Each patient received four cycles of HDMTX (5 g/m2 over 24 hours) at two-week intervals. Patients received either 125 ml/m2/hour (standard) or 200 ml/m2/hour (delayed clearance protocol) hydration before, with, and after each infusion. MTX levels taken at 24-, 42-, and 48-hour time points were used as an indirect measure of drug clearance. Two-tailed inference for ordinary least squares regression and both heteroskedastic and paired two-tailed t-tests were performed to identify physical characteristics associated with delayed MTX clearance and the effects of hydration rate on MTX clearance, respectively. Results Patient age and body surface area (BSA) were found to have statistically significant (p<0.05) positive associations with the serum MTX levels at 24, 42, and 48 hours in cycle 1. Age and BSA were significant only at the 24-hour time point in cycles 2 and 4. Weight alone was not associated with delayed MTX clearance. For patients who had delayed MTX clearance once and thus received the delayed clearance protocol in subsequent cycles, increasing the hydration rate from 125 to 200 ml/m2/hour was associated with a statistically significant decrease in average MTX levels as well as serum creatinine levels at the 24-, 42-, and 48-hour time points. Once patients with delayed clearance received the 200 ml/m2/hour rate of hydration, the history of prior poor clearance lost its predictive value for serum MTX levels and delayed clearance. Conclusions These results suggest that patient age and BSA are significant predictors of MTX clearance if all patients receive the same rate of hydration. Age and BSA affect the distribution phase of MTX kinetics, with downstream effects in the elimination phase. Increased hydration mitigates the effects of these physical characteristics on the elimination phase kinetics by improving renal elimination of MTX, causing a loss of significance of age and BSA as predictors of MTX levels in subsequent cycles at the 42- and 48-hour time points, but with less effect at 24 hours. Thus, hyperhydration regimens prior to cycle 1 of HDMTX could be considered for patients presenting with risk factors of advanced age or high BSA to avoid delayed clearance.