Function prediction of transcription start site associated RNAs (TSSaRNAs) in Halobacterium salinarum NRC-1

• Ano de defesa: 2019
• Autor(a) principal: Adam, Yagoub Ali Ibrahim
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Biblioteca Digitais de Teses e Dissertações da USP
• Palavras-chave em Português: Anotação estrutural; Anotação funcional; Docagem de RNA; Estruturas de ncRNAs de ordem superior; Estruturas RNA; Funções de ncRNAs; Functional annotation; Halobacterium salinarum NRC-1; Higher-order ncRNAs structures; Interações de RNA; Interações de TSSaRNAs-LSm; ncRNAs functions; ncRNAs prediction; Non-coding RNA; Predição de ncRNAs; Regulação baseada em RNA; Rfam; RNA based regulation; RNA docking; RNA interactions; RNA não codificante; RNA structures; Structural annotation; TSSaRNAs; TSSaRNAs-LSm interactions
• Link de acesso: http://www.teses.usp.br/teses/disponiveis/95/95131/tde-02042019-201857/

The Transcription Start Site Associated non-coding RNAs (TSSaRNAs) have been predicted across the three domain of life. However, still, there are no reliable annotation efforts to identify their biological functions and their underline molecular machinery. Therefore, this project addresses the question of what are the potential functions of TSSaRNAs regarding their roles in addressing the cellular functions. To answer this question, we aimed to accurately identify TSSaRNAs in the model organism Halobacterium salinarum NRC-1 (an Archean microorganism) that incubated at the standard growth condition. Consequently, we aimed to investigate TSSaRNAs structural stability in the term of the thermodynamic energies. Moreover, we attempted to functionally annotate TSSaRNAs based on Rfam functional classification of non-coding RNAs. Based on the statistical approach we developed an algorithm to predict TSSaRNA using next-generation RNA sequencing data (RNA-Seq). To perform structural annotation of TSSaRNAs, we investigated the structural stability of TSSaRNAs by modeling the secondary structures by minimizing the thermodynamic free energy. We simulated TSSaRNAs tertiary structures based on the secondary structures constrain using the Rosetta-Common RNA tool. The structures of the minimum free energy supposed to be biophysically stable structures. To investigate the higher order structures of TSSaRNAs, we studied the hybridization between TSSaRNAs and their cognate genes as part of RNA based regulation system. Also, based on our hypothesis that TSSaRNAs may bind to protein to trigger their function, we have investigated the interaction between TSSaRNAs and Lsm protein which known as a chaperone protein that mediates RNA function and involved in RNA processing. Our pipeline to perform the functional annotation of TSSaRNAs aimed to classify TSSaRNAs into their corresponding Rfam families based on two steps: either through querying TSSaRNAs sequences against the co-variance models of Rfam families or by querying the Rfam sequences against the co-variance models of the consensus secondary structures in TSSaRNAs. The results showed that the prediction algorithm has succeeded to identify a total of 224 TSSaRNAs that expressed in the same strand of the mRNAs and 58 TSSaRNAs that expressed as antisense of the mRNAs. The identified TSSaRNAs molecules showed a median length of 25 nucleotides. Regarding the structural annotation of TSSaRNAs, the results showed that most of TSSaRNAs possessed thermodynamically stable secondary structures and their tertiary structures were capable of forming more complex structures through binding with other biomolecules. About the formation of higher-order structures, we have observed that most of TSSaRNAs (92.2%) were capable of hybridizing into their cognate genes also 55 TSSaRNAs indicated putative interactions with Lsm protein. Furthermore, the computation docking experiments demonstrated the TSSaRNAs-Lsm complexes associated with favorable binding energy of a median of -542900 kcal mole -¹. Regarding the functional annotation of TSSaRNAs, the results showed that the majority of TSSaRNAs (42.05%) considered as potential cis-acting regulators such as cis-regulatory element and sRNAs, but still, there are potential trans-acting regulators to regulate distant molecules such as CRISPR and antisense RNA. Moreover, the results indicated that TSSaRNAs could trigger more complex function as a catalytic function such as Riboswitch or to play a role in the defense against a virus such as CRISPR. As a conclusion; based on the results of this study we could state that TSSaRNAs have several potential functions opening the experimental validation perspective.