A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs

Autores
Vanagas, Laura; Cristaldi, Constanza; La Bella, Gino; Ganuza, Agustina; Angel, Sergio Oscar; Alonso, Andrés Mariano
Año de publicación
2024
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Long non-coding RNAs (lncRNAs) have emerged as significant players in diverse cellular processes, including cell differentiation. Advancements in computational methodologies have facilitated the prediction of lncRNA functions, enabling insights even in non-model organisms like pathogenic parasites, in roles such as parasite development, antigenic variation, and epigenetics. In this work, we focus on the apicomplexan Toxoplasma gondii differentiation process, where the infective stage, tachyzoite, can develop into the cysted stage, bradyzoite, under stress conditions. Using a publicly available transcriptome dataset, we predicted putative lncRNA sequences associated with this differentiation process. Notably, a substantial proportion of these putative lncRNAs exhibited stage-specific expression, particularly at the bradyzoite stage. Furthermore, co-expression patterns between coding transcripts and putative TglncRNAs suggest their involvement in shared processes, such as bradyzoite development. Putative TglncRNA loci analysis revealed their potential influence on the expression of nearby coding genes, including subtelomeric genes unique to the T. gondii genome. Finally we propose a k-mer analysis approach to predict putative functional relationships between characterized lncRNAs from model organisms like Homo sapiens and the putative T. gondii lncRNAs. Our perspective led to predict putative T. gondii lncRNA that potentially could act mediating DNA damage repair pathways, opening a new study field to validate this kind of adaptive mechanisms of T. gondii in response to stress conditions.
Fil: Vanagas, Laura. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Cristaldi, Constanza. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: La Bella, Gino. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Ganuza, Agustina. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Angel, Sergio Oscar. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Alonso, Andrés Mariano. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Materia
TOXOPLASMA GONDII
NON-CODING RNAS
STRESS RESPONSE
DIFFERENTIATION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/248680
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/248680
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAsVanagas, LauraCristaldi, ConstanzaLa Bella, GinoGanuza, AgustinaAngel, Sergio OscarAlonso, Andrés MarianoTOXOPLASMA GONDIINON-CODING RNASSTRESS RESPONSEDIFFERENTIATIONhttps://purl.org/becyt/ford/1.7https://purl.org/becyt/ford/1Long non-coding RNAs (lncRNAs) have emerged as significant players in diverse cellular processes, including cell differentiation. Advancements in computational methodologies have facilitated the prediction of lncRNA functions, enabling insights even in non-model organisms like pathogenic parasites, in roles such as parasite development, antigenic variation, and epigenetics. In this work, we focus on the apicomplexan Toxoplasma gondii differentiation process, where the infective stage, tachyzoite, can develop into the cysted stage, bradyzoite, under stress conditions. Using a publicly available transcriptome dataset, we predicted putative lncRNA sequences associated with this differentiation process. Notably, a substantial proportion of these putative lncRNAs exhibited stage-specific expression, particularly at the bradyzoite stage. Furthermore, co-expression patterns between coding transcripts and putative TglncRNAs suggest their involvement in shared processes, such as bradyzoite development. Putative TglncRNA loci analysis revealed their potential influence on the expression of nearby coding genes, including subtelomeric genes unique to the T. gondii genome. Finally we propose a k-mer analysis approach to predict putative functional relationships between characterized lncRNAs from model organisms like Homo sapiens and the putative T. gondii lncRNAs. Our perspective led to predict putative T. gondii lncRNA that potentially could act mediating DNA damage repair pathways, opening a new study field to validate this kind of adaptive mechanisms of T. gondii in response to stress conditions.Fil: Vanagas, Laura. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Cristaldi, Constanza. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: La Bella, Gino. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Ganuza, Agustina. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Angel, Sergio Oscar. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaFil: Alonso, Andrés Mariano. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; ArgentinaNature2024-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/248680Vanagas, Laura; Cristaldi, Constanza; La Bella, Gino; Ganuza, Agustina; Angel, Sergio Oscar; et al.; A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs; Nature; Scientific Reports; 14; 1; 11-2024; 1-142045-2322CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-024-79204-6info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-024-79204-6info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-03T09:45:27Zoai:ri.conicet.gov.ar:11336/248680instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-03 09:45:27.789CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
title A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
spellingShingle A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
Vanagas, Laura
TOXOPLASMA GONDII
NON-CODING RNAS
STRESS RESPONSE
DIFFERENTIATION
title_short A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
title_full A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
title_fullStr A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
title_full_unstemmed A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
title_sort A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs
dc.creator.none.fl_str_mv Vanagas, Laura
Cristaldi, Constanza
La Bella, Gino
Ganuza, Agustina
Angel, Sergio Oscar
Alonso, Andrés Mariano
author Vanagas, Laura
author_facet Vanagas, Laura
Cristaldi, Constanza
La Bella, Gino
Ganuza, Agustina
Angel, Sergio Oscar
Alonso, Andrés Mariano
author_role author
author2 Cristaldi, Constanza
La Bella, Gino
Ganuza, Agustina
Angel, Sergio Oscar
Alonso, Andrés Mariano
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv TOXOPLASMA GONDII
NON-CODING RNAS
STRESS RESPONSE
DIFFERENTIATION
topic TOXOPLASMA GONDII
NON-CODING RNAS
STRESS RESPONSE
DIFFERENTIATION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.7
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Long non-coding RNAs (lncRNAs) have emerged as significant players in diverse cellular processes, including cell differentiation. Advancements in computational methodologies have facilitated the prediction of lncRNA functions, enabling insights even in non-model organisms like pathogenic parasites, in roles such as parasite development, antigenic variation, and epigenetics. In this work, we focus on the apicomplexan Toxoplasma gondii differentiation process, where the infective stage, tachyzoite, can develop into the cysted stage, bradyzoite, under stress conditions. Using a publicly available transcriptome dataset, we predicted putative lncRNA sequences associated with this differentiation process. Notably, a substantial proportion of these putative lncRNAs exhibited stage-specific expression, particularly at the bradyzoite stage. Furthermore, co-expression patterns between coding transcripts and putative TglncRNAs suggest their involvement in shared processes, such as bradyzoite development. Putative TglncRNA loci analysis revealed their potential influence on the expression of nearby coding genes, including subtelomeric genes unique to the T. gondii genome. Finally we propose a k-mer analysis approach to predict putative functional relationships between characterized lncRNAs from model organisms like Homo sapiens and the putative T. gondii lncRNAs. Our perspective led to predict putative T. gondii lncRNA that potentially could act mediating DNA damage repair pathways, opening a new study field to validate this kind of adaptive mechanisms of T. gondii in response to stress conditions.
Fil: Vanagas, Laura. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Cristaldi, Constanza. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: La Bella, Gino. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Ganuza, Agustina. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Angel, Sergio Oscar. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
Fil: Alonso, Andrés Mariano. Universidad Nacional de San Martin. Instituto Tecnologico de Chascomus. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - la Plata. Instituto Tecnologico de Chascomus.; Argentina
description Long non-coding RNAs (lncRNAs) have emerged as significant players in diverse cellular processes, including cell differentiation. Advancements in computational methodologies have facilitated the prediction of lncRNA functions, enabling insights even in non-model organisms like pathogenic parasites, in roles such as parasite development, antigenic variation, and epigenetics. In this work, we focus on the apicomplexan Toxoplasma gondii differentiation process, where the infective stage, tachyzoite, can develop into the cysted stage, bradyzoite, under stress conditions. Using a publicly available transcriptome dataset, we predicted putative lncRNA sequences associated with this differentiation process. Notably, a substantial proportion of these putative lncRNAs exhibited stage-specific expression, particularly at the bradyzoite stage. Furthermore, co-expression patterns between coding transcripts and putative TglncRNAs suggest their involvement in shared processes, such as bradyzoite development. Putative TglncRNA loci analysis revealed their potential influence on the expression of nearby coding genes, including subtelomeric genes unique to the T. gondii genome. Finally we propose a k-mer analysis approach to predict putative functional relationships between characterized lncRNAs from model organisms like Homo sapiens and the putative T. gondii lncRNAs. Our perspective led to predict putative T. gondii lncRNA that potentially could act mediating DNA damage repair pathways, opening a new study field to validate this kind of adaptive mechanisms of T. gondii in response to stress conditions.
publishDate 2024
dc.date.none.fl_str_mv 2024-11
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/248680
Vanagas, Laura; Cristaldi, Constanza; La Bella, Gino; Ganuza, Agustina; Angel, Sergio Oscar; et al.; A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs; Nature; Scientific Reports; 14; 1; 11-2024; 1-14
2045-2322
CONICET Digital
CONICET
url http://hdl.handle.net/11336/248680
identifier_str_mv Vanagas, Laura; Cristaldi, Constanza; La Bella, Gino; Ganuza, Agustina; Angel, Sergio Oscar; et al.; A bioinformatic approach for the prediction and functional classification of Toxoplasma gondii long non-coding RNAs; Nature; Scientific Reports; 14; 1; 11-2024; 1-14
2045-2322
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.nature.com/articles/s41598-024-79204-6
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41598-024-79204-6
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Nature
publisher.none.fl_str_mv Nature
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.13397

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