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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/237918
Ver los metadatos del registro completo
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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 Técnicas2025-09-29T10:08:41Zoai: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:34982025-09-29 10:08:41.358CONICET 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 |
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CONICET Digital (CONICET) |
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CONICET Digital (CONICET) |
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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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13.070432 |