SESC NSU Student Discovers New Genetic Code for Corn

lncRNA are RNA molecules longer than 200 nucleotides that do not translate proteins. MicroRNAs are a class of 20–24 nucleotide noncoding regulatory small RNAs. To date, the involvement of lncRNA and microRNA (miRNA) in plant defense responses under various stress conditions has been proven experimentally. Alexandra Taksanova, an 11th grade student at SESC NSU. She discovered interactions of long non-coding RNAs (lncRNAs) with miRNAs in corn during a special course in bioinformatics at the Institute of Cytology and Genetics SB RAS (ICG). This will be useful when creating new plant varieties through genome editing and conducting new molecular genetic studies for other organisms.

The idea was to identify maize lncRNAs that interact with the plants known miRNAs. The miRNA set was taken from the miRBase database. A set of lncRNAs was obtained from the analysis of 877 maize transcriptome libraries. With the help of special programs, it was possible to detect approx. 34 lncRNAs that interact with known miRNAs. Some of these interactions have been shown to affect drought tolerance in corn.

Artem Pronozin, Project Curator and Junior Researcher ICG, talked about the project,

Our objective was to expand knowledge and at the same time propose a method that scientists can implement in the future to find, for example, the same interactions in other organisms. This method is not only appropriate for corn or plants, it can be used in the study of animals and even humans. In relation to corn, after confirming the data with experiments, the detected interactions can be used to breed more drought-resistant plants.

Taksanova’s project took 2nd place in the «Engineering Design» school competition at the International Student Science Conference. In the future, she would like to continue working with this project and study the resulting lncRNA in more detail.

Taksanova, described her interest in the subject,

Bioinformatics makes it possible for the work of biologists in laboratories to be more efficient, as well as to study what is difficult to touch with our hands. In fact, this is big data in biology because with a huge number in some sequences, you can find those that can be useful with practical applications in the future. This work inspires me.