Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform "N-of-1" analyses on individual patients. The increasing sizes of ultra-rare, "N-of-1" disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development.1,2 The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale N-of-1 analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We apply existing and introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We make our gene-level findings and variant-level information across the cohort available in a public-facing browser (https://dbmi-bgm.github.io/udn-browser/). These results show that N-of-1 efforts should be supplemented by a joint genomic analysis across cohorts.

Peptide fusion improves prime editing efficiency.

Prime editing enables search-and-replace genome editing but is limited by low editing efficiency. We present a high-throughput approach, the Peptide Self-Editing sequencing assay (PepSEq), to measure how fusion of 12,000 85-amino acid peptides influences prime editing efficiency. We show that peptide fusion can enhance prime editing, prime-enhancing peptides combine productively, and a top dual peptide-prime editor increases prime editing significantly in multiple cell lines across dozens of target sites. Top prime-enhancing peptides function by increasing translation efficiency and serve as broadly useful tools to improve prime editing efficiency.

Ribosome impairment regulates intestinal stem cell identity via ZAKɑ activation.

The small intestine is a rapidly proliferating organ that is maintained by a small population of Lgr5-expressing intestinal stem cells (ISCs). However, several Lgr5-negative ISC populations have been identified, and this remarkable plasticity allows the intestine to rapidly respond to both the local environment and to damage. However, the mediators of such plasticity are still largely unknown. Using intestinal organoids and mouse models, we show that upon ribosome impairment (driven by Rptor deletion, amino acid starvation, or low dose cyclohexamide treatment) ISCs gain an Lgr5-negative, fetal-like identity. This is accompanied by a rewiring of metabolism. Our findings suggest that the ribosome can act as a sensor of nutrient availability, allowing ISCs to respond to the local nutrient environment. Mechanistically, we show that this phenotype requires the activation of ZAKɑ, which in turn activates YAP, via SRC. Together, our data reveals a central role for ribosome dynamics in intestinal stem cells, and identify the activation of ZAKɑ as a critical mediator of stem cell identity.