{"title":"In silico analysis, annotation and characterisation of putative ESTs from Sorghum bicolor associated with heat stress","authors":"Gobind Ram, A. Sharma","doi":"10.1504/IJBRA.2015.073240","DOIUrl":null,"url":null,"abstract":"Owing to their sessile nature, plants experience a variety of environmental stresses, but tolerance to these adverse conditions is a very complex phenomenon. Among all stresses, heat stress is the most important constraint that affects plant yield in rain-fed areas. To shed some light on candidate genes involved in heat stress, sequences potentially associated with heat shock resistance were retrieved and identified by in silico analysis using the public sequence database of various plants. A total of 30,000 EST sequences were mined and 24 putative ESTs associated with heat stress were picked up for further studies. In silico analysis revealed that all ESTs were linked with the HSP family. Gene Ontology (GO) analysis revealed that the deduced protein sequences of the heat-linked 24 ESTs were involved in various biological pathways regulating heat stress response. Hydropathy analysis revealed that all protein sequences were hydrophilic in nature. Based on the phylogenetic analysis, all HSP-related protein sequences were divided into seven groups. Analysis of cis-elements provides molecular evidence for the possible involvement of hydrophilic ESTs in the process of abiotic stress tolerance in sorghum. Based on these results, it was suggested that putative ESTs may play an important role in heat stress tolerance.","PeriodicalId":35444,"journal":{"name":"International Journal of Bioinformatics Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJBRA.2015.073240","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Bioinformatics Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBRA.2015.073240","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
引用次数: 0
Abstract
Owing to their sessile nature, plants experience a variety of environmental stresses, but tolerance to these adverse conditions is a very complex phenomenon. Among all stresses, heat stress is the most important constraint that affects plant yield in rain-fed areas. To shed some light on candidate genes involved in heat stress, sequences potentially associated with heat shock resistance were retrieved and identified by in silico analysis using the public sequence database of various plants. A total of 30,000 EST sequences were mined and 24 putative ESTs associated with heat stress were picked up for further studies. In silico analysis revealed that all ESTs were linked with the HSP family. Gene Ontology (GO) analysis revealed that the deduced protein sequences of the heat-linked 24 ESTs were involved in various biological pathways regulating heat stress response. Hydropathy analysis revealed that all protein sequences were hydrophilic in nature. Based on the phylogenetic analysis, all HSP-related protein sequences were divided into seven groups. Analysis of cis-elements provides molecular evidence for the possible involvement of hydrophilic ESTs in the process of abiotic stress tolerance in sorghum. Based on these results, it was suggested that putative ESTs may play an important role in heat stress tolerance.
期刊介绍:
Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.