Project description:To better understand the molecular mechanisms of the response of arbuscular mycorrhizal S. cannabina to salt stress, the transcriptional profile in both mycorrhizal and non-mycorrhizal Sesbania cannabina subjected to 3 and 27 hours NaCl treatment respectively were performed using the Illumina HiSeq™ 2000 sequencing platform (Illumina Inc., San Diego, CA, USA). Bioinformatic analysis of transcriptome data was performed to allow identification and functional annotation of differentially expressed genes (DEGs). By comparing the different genes appeared in control and treatment groups, we can learn more about the species-specific responses employed by S. cannabina and find novel associated genes or strategies in mycorrhizal plant under salt stress.
Project description:To better understand the molecular mechanisms of the response of S. cannabina to soil waterlogging, the transcriptional profile in both short and long term of waterlogged S. cannabina roots were performed using the Illumina HiSeq™ 2000 sequencing platform (Illumina Inc., San Diego, CA, USA). Bioinformatic analysis of transcriptome data was performed to allow identification and functional annotation of differentially expressed genes (DEGs). By comparing the different genes appeared in control and treatment groups, we can learn more about the species-specific responses employed by S. cannabina and find novel associated genes or strategies in waterlogging resistant species.
Project description:Sesbania grandiflora, a fast-growing shrub from the Fabaceae family, is extensively researched for its therapeutic properties. However, the seeds of Sesbania grandiflora have been largely overlooked in scientific studies. Despite its highly valued medicinal properties, there has been no proteomic investigation and structural characterization of the seed proteins of this plant. Our study aims to address this gap by exploring the proteomic profile of Sesbania grandiflora seeds through bottom-up proteomic analysis. The extracted seed proteins, fractionated by ammonium sulfate into three different saturations viz. 30%, 60%, and 90% were separated on an SDS-PAGE gel. Protein containing bands were carbamidomethylated and trypsin digested followed by high resolution mass spectrometric data collection in a data-dependent mode. Proteins were then identified by searching the mass spectrometry data against Fabaceae database through Mascot search engine. To augment the reliability and accuracy of the identifications, Scaffold software was employed for validation by setting the minimum protein and peptide probability filter at 99% and 95%, respectively. Our comprehensive proteomic analysis identified 731 proteins from Sesbania grandiflora seeds, including seed storage proteins, proteases, protease inhibitors, ribonucleoproteins, transferases, isomerases, and hydrolases. This study provides a fundamental understanding of the seed proteome of Sesbania grandiflora, offering insights that could facilitate further research into the plant's therapeutic properties and potential applications.