Genome editing refers to manipulating the nucleotide sequences of the genome with engineered nucleases. Genome editing by engineered nucleases (GEEN) is a valuable genetic engineering approach that uses artificially or modified engineered endonucleases ((EENs) which induce site-specifically double-stranded DNA break (DSB). These EENs contain DNA-binding domain or RNA sequence, which identify its template and nucleases efficiently and precisely cleave the targeted DNA sequences. The double strand breaks (DSBs) of DNA consequently induce the DNA repair mechanisms, results in gene modification at the target sites. These DNA repair mechanism based on error-prone non-homologous end joining breaks (NHEJ) and homology-directed repair (HDR).
Tolerance response of plants to salinity stress is complex and associated with various biological processes including transcription factor, signal transduction, phytohormone (ethylene and jasmonic acid) biosynthesis, compatible solute synthesis, flavonoid biosynthesis, ROS homeostasis, carbohydrate metabolism, ion transport and defence. Sensing the stress signals and transduction of these signals into appropriate responses is crucial for the adaptation of plants under biotic and abiotic stresses. Transcription factors (TF) play a central role in providing salinity stress tolerance. Wang and co-workers (2016) reported the role of various TFs that confer salt stress tolerance. Overexpression of DREB1A gene improves the tolerance to various abiotic stresses including drought, salt and freezing stress by enhancing accumulation of compatible solute contents in Arabidopsis. Arabidopsis DREB1A gene was reported to improve abiotic stress tolerance in transgenic rice, soybean, peanut and wheat
Transcriptome of an organism provides insights into basic biological processes, detecting variations in gene expression after experimental treatments or infection, discovery of tissue biomarkers, genes and their isoforms among others. Next Generation Sequencing (NGS) platforms generate huge amount of RNA sequence data in a single run. NGS platforms are highly sensitive to detect low-frequency genes. They are cost effective and allow higher throughput with sample multiplexing. In order to assemble such a huge data generated after sequencing, efficient bioinformatics tools are needed. The transcriptome analysis is crucially reliant on the quality of the underlying assembly. Till date various tools have been developed for transcriptome assembly following different algorithms. In the present article, various tools used for transcriptome assembly have discussed in brief.