The
mir-35-42 family of microRNAs (miRNAs) acts redundantly to ensure embryonic viability in C. elegans (Alvarez-Saavedra and Horvitz 2010). We are interested in defining the essential targets that must be repressed by the
mir-35-42 family. Our previous work suggested that NHL (ring finger b-box coiled coil) domain containing 2 (
nhl-2) may be one such target because genome editing attempts to delete the
mir-35-42 seed binding region in the
nhl-2 3UTR were unsuccessful (McJunkin and Ambros 2017). The same CRISPR reagents were successful at creating such a deletion in a background containing an NHL-2 CDS deletion (
nhl-2(
ok818)) (McJunkin and Ambros 2017). Together, we took these results to mean that derepression of
nhl-2 induced lethality or sterility, preventing our isolation of the deletion lines in the wild type context. More recently, CRISPR genome editing reagents and protocols have become many-fold more efficient, most notably by injection of recombinant Cas9 RNPs pre-loaded with synthetic guide RNAs (gRNAs) (Paix et al. 2014). Using injection of Cas9/gRNA RNPs, we have succeeded in deleting and mutating the
mir-35-42 seed binding region in the
nhl-2 3UTR in a wild type background (see alleles in Figure 1A). Because such alleles were previously difficult to generate, we quantified their fecundity and embryonic viability (which are two aspects of physiology affected by
mir-35 family mutations) (Alvarez-Saavedra and Horvitz 2010; McJunkin and Ambros 2014) to see if they were impaired, but we found these animals to be wild type (Figure 1B). Therefore, our original interpretation that the difference in CRISPR editing between wild type and
nhl-2(
ok818) backgrounds was due to negative selection of miRNA binding site mutations in the wild type background was incorrect. One possible explanation for the observed difference in editing may be alterations in chromatin structure induced by the 1.5kb
nhl-2(
ok818) deletion. Indeed, nucleosome position and dynamics have been shown to alter efficiency of Cas9 cleavage (Chen et al. 2016; Horlbeck et al. 2016; Isaac et al. 2016; Hinz et al. 2016; Daer et al. 2017; Yarrington et al. 2018; Kim and Kim 2018). Thus, differences in genome editing efficiencies between genetic backgrounds should be interpreted with caution.