Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm

Autores
Federico, Maria Laura; Carrere Gómez, Manuela; Chakrabarty, Subhadra; Erazzú, Luis Ernesto; Snowdon, Rod
Año de publicación
2021
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Gene prioritization pipelines are designed to rank positional candidate genes (CG) within quantitative trait loci (QTL) and reduce the list of CG that is selected for further in-depth functional analysis. We have designed an integrated approach to prioritize CG in sorghum (Sorghum bicolor) combining the use of high-resolution QTL mapping, a machine learning algorithm, sequence analysis of the parental genomes and CG expression profiling. First, we re-mapped QTL associated with 20 different bioenergy-related traits in a recombinant inbred line (RIL) population from a cross between grain (M71) and sweet sorghum (SS79), genotyped using an Affymetrix 90K sorghum single nucleotide polymorphism (SNP) array. Thirty-eight QTL for 16 traits were identified using composite interval mapping; reference genome coordinates were determined for each QTL confidence interval and lists of positional CG generated. Positional CG lists were ranked using a machine learning algorithm, QTG-Finder2. Genomes of the RIL parental lines were re-sequenced in an Illumina NovaSeq 6000 (S4 flow cell, 300 cycles, PE150). Sequencing reads were aligned to the sorghum reference genome, BTx623, and SNPs were called for the parental genotypes. SNP effects on parental allele function were assessed using SNPeff. We also evaluated the tissue-specificity of each of the top 20% CG ranked by QTG-Finder2. Lastly, we generated a prioritized list of positional CG for each of the 38 QTL based on QTG-Finder2 rank, SNP presence/effect between parental alleles and expression profile. Taken together, these results bring us a step closer to finding the causal genes behind these set of bioenergy-associated traits.
Fil: Federico, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Carrere Gómez, Manuela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Chakrabarty, Subhadra. Justus Liebig Universitat Giessen; Alemania
Fil: Erazzú, Luis Ernesto. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-Santiago del Estero. Estación Experimental Agropecuaria Famaillá; Argentina
Fil: Snowdon, Rod. Justus Liebig Universitat Giessen; Alemania
XVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human Genetics
Valdivia
Chile
Sociedad Argentina de Genética
Sociedad de Genética de Chile
Sociedad Uruguaya de Genética
Asociación Latinoamericana de Genética
Sociedad Paraguaya de Genética
Red Latinoamericana de Genética Humana
Materia
QTL
SNP
BIOENERGY
CANDIDATE GENES
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/237918
Acceder
id CONICETDig_e7400cd7d07434728bac740472807168
oai_identifier_str oai:ri.conicet.gov.ar:11336/237918
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithmFederico, Maria LauraCarrere Gómez, ManuelaChakrabarty, SubhadraErazzú, Luis ErnestoSnowdon, RodQTLSNPBIOENERGYCANDIDATE GENEShttps://purl.org/becyt/ford/4.4https://purl.org/becyt/ford/4Gene prioritization pipelines are designed to rank positional candidate genes (CG) within quantitative trait loci (QTL) and reduce the list of CG that is selected for further in-depth functional analysis. We have designed an integrated approach to prioritize CG in sorghum (Sorghum bicolor) combining the use of high-resolution QTL mapping, a machine learning algorithm, sequence analysis of the parental genomes and CG expression profiling. First, we re-mapped QTL associated with 20 different bioenergy-related traits in a recombinant inbred line (RIL) population from a cross between grain (M71) and sweet sorghum (SS79), genotyped using an Affymetrix 90K sorghum single nucleotide polymorphism (SNP) array. Thirty-eight QTL for 16 traits were identified using composite interval mapping; reference genome coordinates were determined for each QTL confidence interval and lists of positional CG generated. Positional CG lists were ranked using a machine learning algorithm, QTG-Finder2. Genomes of the RIL parental lines were re-sequenced in an Illumina NovaSeq 6000 (S4 flow cell, 300 cycles, PE150). Sequencing reads were aligned to the sorghum reference genome, BTx623, and SNPs were called for the parental genotypes. SNP effects on parental allele function were assessed using SNPeff. We also evaluated the tissue-specificity of each of the top 20% CG ranked by QTG-Finder2. Lastly, we generated a prioritized list of positional CG for each of the 38 QTL based on QTG-Finder2 rank, SNP presence/effect between parental alleles and expression profile. Taken together, these results bring us a step closer to finding the causal genes behind these set of bioenergy-associated traits.Fil: Federico, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Carrere Gómez, Manuela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; ArgentinaFil: Chakrabarty, Subhadra. Justus Liebig Universitat Giessen; AlemaniaFil: Erazzú, Luis Ernesto. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-Santiago del Estero. Estación Experimental Agropecuaria Famaillá; ArgentinaFil: Snowdon, Rod. Justus Liebig Universitat Giessen; AlemaniaXVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human GeneticsValdiviaChileSociedad Argentina de GenéticaSociedad de Genética de ChileSociedad Uruguaya de GenéticaAsociación Latinoamericana de GenéticaSociedad Paraguaya de GenéticaRed Latinoamericana de Genética HumanaSociedad Argentina de Genética2021info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/conferenceObjectCongresoJournalhttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/237918Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm; XVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human Genetics; Valdivia; Chile; 2021; 231-2311852-6233CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://sag.org.ar/jbag/en/project/vol-xxxii-suppl-1-2/Internacionalinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:05:46Zoai:ri.conicet.gov.ar:11336/237918instacron: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:34982025-10-15 15:05:46.825CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
title Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
spellingShingle Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
Federico, Maria Laura
QTL
SNP
BIOENERGY
CANDIDATE GENES
title_short Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
title_full Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
title_fullStr Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
title_full_unstemmed Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
title_sort Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm
dc.creator.none.fl_str_mv Federico, Maria Laura
Carrere Gómez, Manuela
Chakrabarty, Subhadra
Erazzú, Luis Ernesto
Snowdon, Rod
author Federico, Maria Laura
author_facet Federico, Maria Laura
Carrere Gómez, Manuela
Chakrabarty, Subhadra
Erazzú, Luis Ernesto
Snowdon, Rod
author_role author
author2 Carrere Gómez, Manuela
Chakrabarty, Subhadra
Erazzú, Luis Ernesto
Snowdon, Rod
author2_role author
author
author
author
dc.subject.none.fl_str_mv QTL
SNP
BIOENERGY
CANDIDATE GENES
topic QTL
SNP
BIOENERGY
CANDIDATE GENES
purl_subject.fl_str_mv https://purl.org/becyt/ford/4.4
https://purl.org/becyt/ford/4
dc.description.none.fl_txt_mv Gene prioritization pipelines are designed to rank positional candidate genes (CG) within quantitative trait loci (QTL) and reduce the list of CG that is selected for further in-depth functional analysis. We have designed an integrated approach to prioritize CG in sorghum (Sorghum bicolor) combining the use of high-resolution QTL mapping, a machine learning algorithm, sequence analysis of the parental genomes and CG expression profiling. First, we re-mapped QTL associated with 20 different bioenergy-related traits in a recombinant inbred line (RIL) population from a cross between grain (M71) and sweet sorghum (SS79), genotyped using an Affymetrix 90K sorghum single nucleotide polymorphism (SNP) array. Thirty-eight QTL for 16 traits were identified using composite interval mapping; reference genome coordinates were determined for each QTL confidence interval and lists of positional CG generated. Positional CG lists were ranked using a machine learning algorithm, QTG-Finder2. Genomes of the RIL parental lines were re-sequenced in an Illumina NovaSeq 6000 (S4 flow cell, 300 cycles, PE150). Sequencing reads were aligned to the sorghum reference genome, BTx623, and SNPs were called for the parental genotypes. SNP effects on parental allele function were assessed using SNPeff. We also evaluated the tissue-specificity of each of the top 20% CG ranked by QTG-Finder2. Lastly, we generated a prioritized list of positional CG for each of the 38 QTL based on QTG-Finder2 rank, SNP presence/effect between parental alleles and expression profile. Taken together, these results bring us a step closer to finding the causal genes behind these set of bioenergy-associated traits.
Fil: Federico, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Carrere Gómez, Manuela. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Noroeste de la Provincia de Buenos Aires; Argentina. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Buenos Aires Norte. Estación Experimental Agropecuaria Pergamino; Argentina
Fil: Chakrabarty, Subhadra. Justus Liebig Universitat Giessen; Alemania
Fil: Erazzú, Luis Ernesto. Instituto Nacional de Tecnología Agropecuaria. Centro Regional Tucuman-Santiago del Estero. Estación Experimental Agropecuaria Famaillá; Argentina
Fil: Snowdon, Rod. Justus Liebig Universitat Giessen; Alemania
XVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human Genetics
Valdivia
Chile
Sociedad Argentina de Genética
Sociedad de Genética de Chile
Sociedad Uruguaya de Genética
Asociación Latinoamericana de Genética
Sociedad Paraguaya de Genética
Red Latinoamericana de Genética Humana
description Gene prioritization pipelines are designed to rank positional candidate genes (CG) within quantitative trait loci (QTL) and reduce the list of CG that is selected for further in-depth functional analysis. We have designed an integrated approach to prioritize CG in sorghum (Sorghum bicolor) combining the use of high-resolution QTL mapping, a machine learning algorithm, sequence analysis of the parental genomes and CG expression profiling. First, we re-mapped QTL associated with 20 different bioenergy-related traits in a recombinant inbred line (RIL) population from a cross between grain (M71) and sweet sorghum (SS79), genotyped using an Affymetrix 90K sorghum single nucleotide polymorphism (SNP) array. Thirty-eight QTL for 16 traits were identified using composite interval mapping; reference genome coordinates were determined for each QTL confidence interval and lists of positional CG generated. Positional CG lists were ranked using a machine learning algorithm, QTG-Finder2. Genomes of the RIL parental lines were re-sequenced in an Illumina NovaSeq 6000 (S4 flow cell, 300 cycles, PE150). Sequencing reads were aligned to the sorghum reference genome, BTx623, and SNPs were called for the parental genotypes. SNP effects on parental allele function were assessed using SNPeff. We also evaluated the tissue-specificity of each of the top 20% CG ranked by QTG-Finder2. Lastly, we generated a prioritized list of positional CG for each of the 38 QTL based on QTG-Finder2 rank, SNP presence/effect between parental alleles and expression profile. Taken together, these results bring us a step closer to finding the causal genes behind these set of bioenergy-associated traits.
publishDate 2021
dc.date.none.fl_str_mv 2021
dc.type.none.fl_str_mv info:eu-repo/semantics/publishedVersion
info:eu-repo/semantics/conferenceObject
Congreso
Journal
http://purl.org/coar/resource_type/c_5794
info:ar-repo/semantics/documentoDeConferencia
status_str publishedVersion
format conferenceObject
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/237918
Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm; XVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human Genetics; Valdivia; Chile; 2021; 231-231
1852-6233
CONICET Digital
CONICET
url http://hdl.handle.net/11336/237918
identifier_str_mv Prioritization of candidate genes in QTL regions associated with bioenergy-related traits in sorghum (Sorghum bicolor) using a machine learning algorithm; XVIII Latin American Congress of Genetics; LIV Annual Meeting of the Chilean Society of Genetics; XLIX Argentine Congress of Genetics; VIII Congress of the Uruguayan Society of Genetics; I Paraguayan Congress of Genetics; V Latin American Congress of Human Genetics; Valdivia; Chile; 2021; 231-231
1852-6233
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://sag.org.ar/jbag/en/project/vol-xxxii-suppl-1-2/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.coverage.none.fl_str_mv Internacional
dc.publisher.none.fl_str_mv Sociedad Argentina de Genética
publisher.none.fl_str_mv Sociedad Argentina de Genética
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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