Knockout of Cia5 gene using CRISPR/Cas9 technique in Chlamydomonas reinhardtii and evaluating CO2 sequestration in control and mutant isolates.

CRISPR/Cas9 technology is one of the common methods of genome editing and targeted gene mutation, which has recently been used for manipulating microalgae such as Chlamydomonas reinhardtii. Besides, this technology can play a role in the fight against greenhouse gases (e.g., carbon dioxide) production by studying genetic pathways to improve algal strains. Among several genes in algae that respond to CO2 and regulators control the expression of each; Cia5 is one of the most critical transcriptional regulators. In this research, we knocked out the Cia5 gene using the CRISPR/Cas9 technique and analysed the ability of C. reinhardtii to perform CO2 sequestration. Our results showed that C. reinhardtii has better performance (i.e., response to CO2 treatment) in both control and mutant species at 0.5% CO2 concentration than other concentrations. However, the difference between the control microalgae species and the mutant species was in the CO2 removal efficiency. Additionally, our findings revealed that the control type isolate in CO2 concentrations of 0.04%, 0.5% and 1% had removal efficiencies of 27%, 37% and 21%, respectively. Nevertheless, for mutant species in the same concentrations, the observed removal efficiencies were 16%, 23% and 9%.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review.

BACKGROUND: Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs. OBJECTIVE: The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA's roles in cellular processes and drugs design, briefly. METHOD: In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases. RESULTS: The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs. CONCLUSION: ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.