Type V CRISPR-Cas systems are distinguished by a single RNA-guided RuvC domain-containing effector, Cas12. Although effectors of subtypes V-A (Cas12a) and V-B (Cas12b) have been studied in detail, the distinct domain architectures and diverged RuvC sequences of uncharacterized Cas12 proteins suggest unexplored functional diversity. Here, we identify and characterize Cas12c, -g, -h, and -i. Cas12c, -h, and -i demonstrate RNA-guided double-stranded DNA (dsDNA) interference activity. Cas12i exhibits markedly different efficiencies of CRISPR RNA spacer complementary and noncomplementary strand cleavage resulting in predominant dsDNA nicking. Cas12g is an RNA-guided ribonuclease (RNase) with collateral RNase and single-strand DNase activities. Our study reveals the functional diversity emerging along different routes of type V CRISPR-Cas evolution and expands the CRISPR toolbox.

DNA-based human identity testing is conducted by comparison of PCR-amplified polymorphic Short Tandem Repeat (STR) motifs from a known source with the STR profiles obtained from uncertain sources. Samples such as those found at crime scenes often result in signal that is a composite of incomplete STR profiles from an unknown number of unknown contributors, making interpretation an arduous task. To facilitate advancement in STR interpretation challenges we provide over 25,000 multiplex STR profiles produced from one to five known individuals at target levels ranging from one to 160 copies of DNA. The data, generated under 144 laboratory conditions, are classified by total copy number and contributor proportions. For the 70% of samples that were synthetically compromised, we report the level of DNA damage using quantitative and end-point PCR. In addition, we characterize the complexity of the signal by exploring the number of detected alleles in each profile.

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In forensic DNA casework, the interpretation of an evidentiary profile may be dependent upon the assumption on the number of individuals from whom the evidence arose. Three methods of inferring the number of contributors-NOCIt, maximum likelihood estimator, and maximum allele count, were evaluated using 100 test samples consisting of one to five contributors and 0.5-0.016 ng template DNA amplified with Identifiler Plus and PowerPlex 16 HS. Results indicate that NOCIt was the most accurate method of the three, requiring 0.07 ng template DNA from any one contributor to consistently estimate the true number of contributors. Additionally, NOCIt returned repeatable results for 91% of samples analyzed in quintuplicate, while 50 single-source standards proved sufficient to calibrate the software. The data indicate that computational methods that employ a quantitative, probabilistic approach provide improved accuracy and additional pertinent information such as the uncertainty associated with the inferred number of contributors.