High Throughput Deep Sequencing Reveals the Important Roles of MicroRNAs During Sweetpotato Storage at Chilling Temperature

Sweetpotato (Impomoea batatas L.) is a globally important economic food crop with a potential of becoming a bioenergy and pharmaceutical crop. Thus, studying the molecular mechanism of tuberous root development and storage is very important. However, not too much progress has been made in this field. In this study, we employed the next generation high-throughput deep sequencing technology to sequence all small RNAs and degradome of sweetpotato for systematically investigating sweetpotato response to chilling stress during storage. A total of 190 known microRNAs (miRNAs) and 191 novel miRNAs were identified, and 428 transcripts were targeted by 184 identified miRNAs. More importantly, we identified 26 miRNAs differentially expressed between chilling stress and control conditions. The expression of these miRNAs and their targets was also confirmed by qRT- PCR. Integrated analysis of small RNAs and degradome sequencing reveals that miRNA-mediated SA signaling, ABA-dependent, and ROS response pathways are involved in sweetpotato root response to chilling stress during storage

Prediction for Pareto distribution based on progressively Type-II censored samples

In this paper, we discuss different predictors of times to failure of units censored in multiple stages in a progressively censored sample from Pareto distribution. The best linear unbiased predictors, maximum likelihood predictors and approximate maximum likelihood predictors are considered. We also present two methods for obtaining prediction intervals for the times to failure of units. A numerical simulation study involving two data sets is presented to illustrate the methods of prediction.Progressive Type-II censoring Pareto distribution Best linear unbiased predictor Maximum likelihood predictor Prediction interval Highest conditional density Monte Carlo simulation