Evaluation of Homology-Independent CRISPR-Cas9 Off-Target Assessment Methods.

The ability to alter genomes specifically by CRISPR-Cas gene editing has revolutionized biological research, biotechnology, and medicine. Broad therapeutic application of this technology, however, will require thorough preclinical assessment of off-target editing by homology-based prediction coupled with reliable methods for detecting off-target editing. Several off-target site nomination assays exist, but careful comparison is needed to ascertain their relative strengths and weaknesses. In this study, HEK293T cells were treated with Streptococcus pyogenes Cas9 and eight guide RNAs with varying levels of predicted promiscuity in order to compare the performance of three homology-independent off-target nomination methods: the cell-based assay, GUIDE-seq, and the biochemical assays CIRCLE-seq and SITE-seq. The three methods were benchmarked by sequencing 75,000 homology-nominated sites using hybrid capture followed by high-throughput sequencing, providing the most comprehensive assessment of such methods to date. The three methods performed similarly in nominating sequence-confirmed off-target sites, but with large differences in the total number of sites nominated. When combined with homology-dependent nomination methods and confirmation by sequencing, all three off-target nomination methods provide a comprehensive assessment of off-target activity. GUIDE-seq's low false-positive rate and the high correlation of its signal with observed editing highlight its suitability for nominating off-target sites for ex vivo CRISPR-Cas therapies.

Unbiased Screens Show CD8+ T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein.

Developing effective strategies to prevent or treat coronavirus disease 2019 (COVID-19) requires understanding the natural immune response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). We used an unbiased, genome-wide screening technology to determine the precise peptide sequences in SARS-CoV-2 that are recognized by the memory CD8+ T cells of COVID-19 patients. In total, we identified 3-8 epitopes for each of the 6 most prevalent human leukocyte antigen (HLA) types. These epitopes were broadly shared across patients and located in regions of the virus that are not subject to mutational variation. Notably, only 3 of the 29 shared epitopes were located in the spike protein, whereas most epitopes were located in ORF1ab or the nucleocapsid protein. We also found that CD8+ T cells generally do not cross-react with epitopes in the four seasonal coronaviruses that cause the common cold. Overall, these findings can inform development of next-generation vaccines that better recapitulate natural CD8+ T cell immunity to SARS-CoV-2.

Publisher Correction: Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Enhancer signatures stratify and predict outcomes of non-functional pancreatic neuroendocrine tumors.

Most pancreatic neuroendocrine tumors (PNETs) do not produce excess hormones and are therefore considered 'non-functional'1-3. As clinical behaviors vary widely and distant metastases are eventually lethal2,4, biological classifications might guide treatment. Using enhancer maps to infer gene regulatory programs, we find that non-functional PNETs fall into two major subtypes, with epigenomes and transcriptomes that partially resemble islet α- and ß-cells. Transcription factors ARX and PDX1 specify these normal cells, respectively5,6, and 84% of 142 non-functional PNETs expressed one or the other factor, occasionally both. Among 103 cases, distant relapses occurred almost exclusively in patients with ARX+PDX1- tumors and, within this subtype, in cases with alternative lengthening of telomeres. These markedly different outcomes belied similar clinical presentations and histology and, in one cohort, occurred irrespective of MEN1 mutation. This robust molecular stratification provides insight into cell lineage correlates of non-functional PNETs, accurately predicts disease course and can inform postoperative clinical decisions.

Identification of nuclear hormone receptor pathways causing insulin resistance by transcriptional and epigenomic analysis.

Insulin resistance is a cardinal feature of Type 2 diabetes (T2D) and a frequent complication of multiple clinical conditions, including obesity, ageing and steroid use, among others. How such a panoply of insults can result in a common phenotype is incompletely understood. Furthermore, very little is known about the transcriptional and epigenetic basis of this disorder, despite evidence that such pathways are likely to play a fundamental role. Here, we compare cell autonomous models of insulin resistance induced by the cytokine tumour necrosis factor-α or by the steroid dexamethasone to construct detailed transcriptional and epigenomic maps associated with cellular insulin resistance. These data predict that the glucocorticoid receptor and vitamin D receptor are common mediators of insulin resistance, which we validate using gain- and loss-of-function studies. These studies define a common transcriptional and epigenomic signature in cellular insulin resistance enabling the identification of pathogenic mechanisms.