Background

Genome engineering is essential to the study of biology, which attracted several new technological breakthroughs (Doudna and Charpentier, 2014). CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated protein 9) technology has proven to have great efficiency and generalizability both in gene editing and gene regulation (Qi et al., 2013; La Russa and Qi, 2015). CRISPR-Cas9 system consists of Cas9 endonuclease and a target-identifying CRISPR RNA duplex (crRNA and trans-activating crRNA (tracrRNA)) that can be simplified into a single guide RNA (sgRNA). sgRNA sequence can match and target with an 18- to 25-bp DNA sequence, with a required DNA motif termed the protospacer-adjacent motif (PAM) adjacent to the binding site. The most commonly used type of Cas9 is derived from Streptococcus pyogenes, and the PAM sequence is NGG (N represents any nucleotide), while NAG works sporadically with lower efficiency.

In CRISPR-Cas9 system, sgRNA with a general 20 bp custom designed sequence determines target specificity and efficiency. Designing sgRNA is an indispensible part of CRISPR related projects. Of the published tools that enable automated sgRNA design, CRISPR-ERA can provide sgRNA searching approaches for both gene editing and gene regulation applications, and provide additional genome-wide sgRNA library building protocol (Liu et al., 2015). Currently, CRISPR-ERA supports sgRNA design for nine organisms with different kinds of manipulations. It provides a user-friendly webserver to enable sgRNA searching in preassembled databases. The preassembled genome-wide sgRNA databases are built by seeking all targetable sites with patterns of N₂₀NGG. To evaluate the efficiency and specificity of each sgRNA, CRISPR-ERA utilizes criteria summarized from published data, and then computes an efficacy score (E-score) and a specificity score (S-score). Criteria will have a slight change within different kinds of manipulation and organisms.