Identifying Cyanobacteria through Next-Generation Sequencing Technology for Modern Agriculture

¹ Bioinformatics and Data Science Research Center, 11480 Bina Nusantara University, Indonesia
² Computer Science Department BINUS Graduate Program, Master of Computer Science, 11480 Bina Nusantara University, Indonesia

^* Corresponding author: joko.trinugroho@binus.edu

Abstract

As the global demand for food continue to increase, it is important to find a way to meet the demand without creating any problems to the environment. Cyanobacteria have a prospective to be utilised for the modern agriculture, as they contribute to the improvement of the soil fertility, the crop yield, and they also do not harm the environment. Therefore, it is crucial to understand the species of cyanobacteria or the characteristics that could be used for modern agriculture. The development of Next-Generation Sequencing (NGS) technologies enables us to study the genome of cyanobacteria. Thus, we can study their characteristics by analysing the NGS data. This paper aims to elaborate a pipeline for genomic analysis on cyanobacteria from NGS data. We used a free Linux-based software tool, namely Breseq to process the NGS sequencing raw data. This tool predicts mutations that occur in the genome of the sample, including single- nucleotide variation, insertions, and deletions which could be beneficial for the identification of a new species or a mutant of cyanobacteria which has the right characteristics for modern agriculture utilisation.