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CRISPR-Cas systems inherently multiplex through CRISPR arrays—whether to defend against different invaders or mediate multi-target editing, regulation, imaging, or sensing. However, arrays remain difficult to generate due to their reoccurring repeat sequences. Here, we report a modular, one-pot scheme called CRATES to construct CRISPR arrays and array libraries. CRATES allows assembly of repeat-spacer subunits using defined assembly junctions within the trimmed portion of spacers. Using CRATES, we construct arrays for the single-effector nucleases Cas9, Cas12a, and Cas13a that mediated multiplexed DNA/RNA cleavage and gene regulation in cell-free systems, bacteria, and yeast. CRATES further allows the one-pot construction of array libraries and composite arrays utilized by multiple Cas nucleases. Finally, array characterization reveals processing of extraneous CRISPR RNAs from Cas12a terminal repeats and sequence- and context-dependent loss of RNA-directed nuclease activity via global RNA structure formation. CRATES thus can facilitate diverse multiplexing applications and help identify factors impacting crRNA biogenesis.
Family studies suggest a genetic component to the etiology of chronic kidney disease (CKD) and end stage renal disease (ESRD). Previously, we identified 16 loci for eGFR in genome-wide association studies, but the associations of these single nucleotide polymorphisms (SNPs) for incident CKD or ESRD are unknown. We thus investigated the association of these loci with incident CKD in 26,308 individuals of European ancestry free of CKD at baseline drawn from eight population-based cohorts followed for a median of 7.2 years (including 2,122 incident CKD cases defined as eGFR < 60ml/min/1.73m(2) at follow-up) and with ESRD in four case-control studies in subjects of European ancestry (3,775 cases, 4,577 controls). SNPs at 11 of the 16 loci (UMOD, PRKAG2, ANXA9, DAB2, SHROOM3, DACH1, STC1, SLC34A1, ALMS1/NAT8, UBE2Q2, and GCKR) were associated with incident CKD; p-values ranged from p = 4.1e-9 in UMOD to p = 0.03 in GCKR. After adjusting for baseline eGFR, six of these loci remained significantly associated with incident CKD (UMOD, PRKAG2, ANXA9, DAB2, DACH1, and STC1). SNPs in UMOD (OR = 0.92, p = 0.04) and GCKR (OR = 0.93, p = 0.03) were nominally associated with ESRD. In summary, the majority of eGFR-related loci are either associated or show a strong trend towards association with incident CKD, but have modest associations with ESRD in individuals of European descent. Additional work is required to characterize the association of genetic determinants of CKD and ESRD at different stages of disease progression.