BackgroundCRISPR-Cas12a (formerly Cpf1) is an RNA-guided endonuclease with distinct features that have expanded genome editing capabilities. Cas12a-mediated genome editing is temperature sensitive in plants, but a lack of a comprehensive understanding on Cas12a temperature sensitivity in plant cells has hampered effective application of Cas12a nucleases in plant genome editing.ResultsWe compared AsCas12a, FnCas12a, and LbCas12a for their editing efficiencies and non-homologous end joining (NHEJ) repair profiles at four different temperatures in rice. We found that AsCas12a is more sensitive to temperature and that it requires a temperature of over 28 °C for high activity. Each Cas12a nuclease exhibited distinct indel mutation profiles which were not affected by temperatures. For the first time, we successfully applied AsCas12a for generating rice mutants with high frequencies up to 93% among T0 lines. We next pursued editing in the dicot model plant Arabidopsis, for which Cas12a-based genome editing has not been previously demonstrated. While LbCas12a barely showed any editing activity at 22 °C, its editing activity was rescued by growing the transgenic plants at 29 °C. With an early high-temperature treatment regime, we successfully achieved germline editing at the two target genes, GL2 and TT4, in Arabidopsis transgenic lines. We then used high-temperature treatment to improve Cas12a-mediated genome editing in maize. By growing LbCas12a T0 maize lines at 28 °C, we obtained Cas12a-edited mutants at frequencies up to 100% in the T1 generation. Finally, we demonstrated DNA binding of Cas12a was not abolished at lower temperatures by using a dCas12a-SRDX-based transcriptional repression system in Arabidopsis.ConclusionOur study demonstrates the use of high-temperature regimes to achieve high editing efficiencies with Cas12a systems in rice, Arabidopsis, and maize and sheds light on the mechanism of temperature sensitivity for Cas12a in plants.Electronic supplementary materialThe online version of this article (10.1186/s12915-019-0629-5) contains supplementary material, which is available to authorized users.

Significant yield increase has been achieved by simultaneous introduction of three trait-related QTLs in three rice varieties with multiplex editing by CRISPR-Cas9. Using traditional breeding approaches to develop new elite rice varieties with high yield and superior quality is challenging. It usually requires introduction of multiple trait-related quantitative trait loci (QTLs) into an elite background through multiple rounds of crossing and selection. CRISPR-Cas9-based multiplex editing of QTLs represents a new breeding strategy that is straightforward and cost effective. To test this approach, we simultaneously targeted three yield-related QTLs for editing in three elite rice varieties, namely J809, L237 and CNXJ. The chosen yield-related QTL genes are OsGS3, OsGW2 and OsGn1a, which have been identified to negatively regulate the grain size, width and weight, and number, respectively. Our approach rapidly generated all seven combinations of single, double and triple mutants for the target genes in elite backgrounds. Detailed analysis of these mutants revealed differential contributions of QTL mutations to yield performance such as grain length, width, number and 1000-grain weight. Overall, the contributions are additive, resulting in 68 and 30% yield per panicle increase in triple mutants of J809 and L237, respectively. Our data hence demonstrates a promising genome editing approach for rapid breeding of QTLs in elite crop varieties.

Polycyclic aromatic hydrocarbons (PAHs) are one of the most important and carcinogenic components in diesel exhaust (DE). Therefore, ambient PAHs concentrations were measured and characterized for work areas in a locomotive engine inspection plant. Pre- and post-shift urine samples and concurrent air samples were collected on 17 workers to measure the concentration of urinary 1-hydroxypyrene (1-OHP), a metabolite of pyrene. Increased urinary 1-OHP concentrations were observed over at least three consecutive sampling days. The biological kinetics of pyrene metabolism was studied with a one-compartment pharmokinetic model. The conversion rate and elimination rate of 1-OHP were estimated using nonlinear mixed-effects model, and validated with multiple nonlinear regression models by assessing the pattern of elimination rates of each worker separately. Urinary 1-OHP was confirmed to be a sensitive marker of PAHs exposure with mean half-life of 29 h in this population of Chinese workers. The study results would be beneficial to future occupational and environmental studies of PAH exposure.

As one of the most popular forms of social e-commerce, group-buying price (GBP) is a widely used pricing mechanism. One typical example is PinDuoDuo, which was listed on the NASDAQ stock exchange in 2018. On the PinDuoDuo app, sellers generally encourage informed buyers to share information about products with uninformed buyers to increase sales volume. However, a growing number of sellers have begun using new methods (e.g., online live streaming) to share information with buyers themselves. In this article, we investigate optimal pricing decisions under various scenarios of product information-sharing between sellers and buyers. We first investigate a scenario in which either the seller or the informed buyer alone shares information with the uninformed buyer. We then consider a scenario in which they share information together. Further, we extend our model to the situation that the unit cost of information-sharing is nonlinear. We find that the seller will choose to share information herself when the cost of information-sharing is small or the cost function is quadratic, whereas the seller will not always choose to act first when both the seller and the informed buyer share information. GBP strategy is preferred by the seller when the information gap between buyers is in a middle range. These results can help guide sellers in choosing efficient information-sharing methods in social e-commerce.

Problem definition: We study a monopolistic robust pricing problem in which the seller does not know the customers’ valuation distribution for a product but knows its mean and variance. Academic/practical relevance: This minimal requirement for information means that the pricing managers only need to be able to answer two questions: How much will your targeted customers pay on average? To measure your confidence in the previous answer, what is the standard deviation of customer valuations? Methodology: We focus on the maximin profit criterion and derive distribution-free upper and lower bounds on the profit function. Results: By maximizing the tight profit lower bound, we obtain the optimal robust price in closed form as well as its distribution-free, worst-case performance bound. We then extend the single-product result to study the robust pure bundle pricing problem where the seller only knows the mean and variance of each product, and we provide easily verifiable, distribution-free, sufficient conditions that guarantee the pure bundle to be more robustly profitable than à la carte (i.e., separate) sales. We further derive a distribution-free, worst-case performance guarantee for a heuristic scheme in which customers choose between buying either a single product or a pure bundle. Moreover, we generalize separate sales and pure bundling to a scheme called clustered bundling that imposes a price for each part (i.e., cluster) of a partition of all products and allows customers to choose one or multiple parts (i.e., clusters), and we provide various algorithms to compute clustered bundling heuristics. In parallel, most of our results hold for the minimax relative regret criterion as well. Managerial implications: The robust price for a single product is in closed form under the maximin profit or minimax relative regret criterion and hence, is easily computable. Its interpretation can be easily explained to pricing managers. We also provide efficient algorithms to compute various mixed bundling heuristics for the multiproduct problem.