Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf

10 pages. -- 8 supplementary figures. Figure S1. Phenotypic distributions of leaf accumulation of Cd and Hg in leaves, and relative root growth (RRG) in response to both metals. Corresponding histograms for each phenotype are displayed opposite to the x and y axes. Linear regression and 95% confiden...

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Detalles Bibliográficos
Autores: Paape, Timothy, Heiniger, Benjamin, Santo Domingo, Miguel, Clear, Michael R., Lucas, M. Mercedes, Pueyo, José Javier
Tipo de recurso: conjunto de datos
Fecha de publicación:2022
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/311730
Acceso en línea:http://hdl.handle.net/10261/311730
Access Level:acceso abierto
Palabra clave:Cadmium
Mercury
Polygenic
Standing variation
Genetic architecture
Medicago truncatula (Medicago)
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network_name_str España
repository_id_str
dc.title.none.fl_str_mv Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
title Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
spellingShingle Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
Paape, Timothy
Cadmium
Mercury
Polygenic
Standing variation
Genetic architecture
Medicago truncatula (Medicago)
title_short Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
title_full Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
title_fullStr Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
title_full_unstemmed Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
title_sort Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdf
dc.creator.none.fl_str_mv Paape, Timothy
Heiniger, Benjamin
Santo Domingo, Miguel
Clear, Michael R.
Lucas, M. Mercedes
Pueyo, José Javier
author Paape, Timothy
author_facet Paape, Timothy
Heiniger, Benjamin
Santo Domingo, Miguel
Clear, Michael R.
Lucas, M. Mercedes
Pueyo, José Javier
author_role author
author2 Heiniger, Benjamin
Santo Domingo, Miguel
Clear, Michael R.
Lucas, M. Mercedes
Pueyo, José Javier
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Cadmium
Mercury
Polygenic
Standing variation
Genetic architecture
Medicago truncatula (Medicago)
topic Cadmium
Mercury
Polygenic
Standing variation
Genetic architecture
Medicago truncatula (Medicago)
description 10 pages. -- 8 supplementary figures. Figure S1. Phenotypic distributions of leaf accumulation of Cd and Hg in leaves, and relative root growth (RRG) in response to both metals. Corresponding histograms for each phenotype are displayed opposite to the x and y axes. Linear regression and 95% confidence intervals are overlayed on the scatter plot. Heritability (H2) is shown next to each histogram, and Pearson correlation coefficients (r) are shown in each panel. -- Figure S2. Average cross validation errors of 10 Admixture runs for each k between 1 and 10. The yaxis represents the cross-validation error value, the x-axis is k, number of population clusters. The distribution of ancestry components in all samples of the HapMap dataset for the best iteration (lowest cross validation error) was k = 5. -- Figure S3. Population structure analysis identified five admixture components. The population structure was determined using the software Admixture. -- Figure S4. Genome wide association analysis of heavy metal accumulation and tolerance traits (Manhattan plots shown for each trait; output from GEMMA). -- Figure S5. Genomic organization of three tandem ABC transporters (Medtr2g436680.1, Medtr2g436710, Medtr2g436730) on chromosome 2 in the Mt4.0 reference genome (www.medicagohapmap.org). The closest Blast hit to these three genes is the Arabidopsis thaliana ABC transporter ABCC14 (AT3G62700.1). -- Figure S6. The Pleiotropic Drug Resistance 3 gene PDR3 (Medtr5g070320) and Cation Exchanger 3 gene CAX3 (Medtr5g070330) are 5878 bp apart in the Mt4.0 reference genome (www.medicagohapmap.org). -- Figure S7. Density plots showing the genome wide distribution of SNP effect sizes (gray) and the top 1000 SNPs with lowest p-values for each trait (red). The most significant SNPs have the largest effect. -- Figure S8. Effect size and minor allele frequency (MAF) from the top 100 most significant SNPs using the GEMMA package for GWAS (left four panels, one for each trait).
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
http://purl.org/coar/resource_type/c_ddb1
format dataset
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/311730
url http://hdl.handle.net/10261/311730
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Paape, Timothy; Heiniger, Benjamin; Santo Domingo, Miguel; Clear, Michael R.; Lucas, M. Mercedes; Pueyo, José J. Genome-wide association study reveals complex genetic architecture of cadmium and mercury accumulation and tolerance traits in Medicago truncatula. https://doi.org/10.3389/fpls.2021.806949. http://hdl.handle.net/10261/286968
https://doi.org/10.3389/fpls.2021.806949.s001
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Figshare
publisher.none.fl_str_mv Figshare
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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spelling Data_Sheet_1_Genome-Wide Association Study Reveals Complex Genetic Architecture of Cadmium and Mercury Accumulation and Tolerance Traits in Medicago truncatula.pdfPaape, TimothyHeiniger, BenjaminSanto Domingo, MiguelClear, Michael R.Lucas, M. MercedesPueyo, José JavierCadmiumMercuryPolygenicStanding variationGenetic architectureMedicago truncatula (Medicago)10 pages. -- 8 supplementary figures. Figure S1. Phenotypic distributions of leaf accumulation of Cd and Hg in leaves, and relative root growth (RRG) in response to both metals. Corresponding histograms for each phenotype are displayed opposite to the x and y axes. Linear regression and 95% confidence intervals are overlayed on the scatter plot. Heritability (H2) is shown next to each histogram, and Pearson correlation coefficients (r) are shown in each panel. -- Figure S2. Average cross validation errors of 10 Admixture runs for each k between 1 and 10. The yaxis represents the cross-validation error value, the x-axis is k, number of population clusters. The distribution of ancestry components in all samples of the HapMap dataset for the best iteration (lowest cross validation error) was k = 5. -- Figure S3. Population structure analysis identified five admixture components. The population structure was determined using the software Admixture. -- Figure S4. Genome wide association analysis of heavy metal accumulation and tolerance traits (Manhattan plots shown for each trait; output from GEMMA). -- Figure S5. Genomic organization of three tandem ABC transporters (Medtr2g436680.1, Medtr2g436710, Medtr2g436730) on chromosome 2 in the Mt4.0 reference genome (www.medicagohapmap.org). The closest Blast hit to these three genes is the Arabidopsis thaliana ABC transporter ABCC14 (AT3G62700.1). -- Figure S6. The Pleiotropic Drug Resistance 3 gene PDR3 (Medtr5g070320) and Cation Exchanger 3 gene CAX3 (Medtr5g070330) are 5878 bp apart in the Mt4.0 reference genome (www.medicagohapmap.org). -- Figure S7. Density plots showing the genome wide distribution of SNP effect sizes (gray) and the top 1000 SNPs with lowest p-values for each trait (red). The most significant SNPs have the largest effect. -- Figure S8. Effect size and minor allele frequency (MAF) from the top 100 most significant SNPs using the GEMMA package for GWAS (left four panels, one for each trait).Heavy metals are an increasing problem due to contamination from human sources that and can enter the food chain by being taken up by plants. Understanding the genetic basis of accumulation and tolerance in plants is important for reducing the uptake of toxic metals in crops and crop relatives, as well as for removing heavy metals from soils by means of phytoremediation. Following exposure of Medicago truncatula seedlings to cadmium (Cd) and mercury (Hg), we conducted a genome-wide association study using relative root growth (RRG) and leaf accumulation measurements. Cd and Hg accumulation and RRG had heritability ranging 0.44 – 0.72 indicating high genetic diversity for these traits. The Cd and Hg trait associations were broadly distributed throughout the genome, indicated the traits are polygenic and involve several quantitative loci. For all traits, candidate genes included several membrane associated ATP-binding cassette transporters, P-type ATPase transporters, oxidative stress response genes, and stress related UDP-glycosyltransferases. The P-type ATPase transporters and ATP-binding cassette protein-families have roles in vacuole transport of heavy metals, and our findings support their wide use in physiological plant responses to heavy metals and abiotic stresses. We also found associations between Cd RRG with the genes CAX3 and PDR3, two linked adjacent genes, and leaf accumulation of Hg associated with the genes NRAMP6 and CAX9. When plant genotypes with the most extreme phenotypes were compared, we found significant divergence in genomic regions using population genomics methods that contained metal transport and stress response gene ontologies. Several of these genomic regions show high linkage disequilibrium (LD) among candidate genes suggesting they have evolved together. Minor allele frequency (MAF) and effect size of the most significant SNPs was negatively correlated with large effect alleles being most rare. This is consistent with purifying selection against alleles that increase toxicity and abiotic stress. Conversely, the alleles with large affect that had higher frequencies that were associated with the exclusion of Cd and Hg. Overall, macroevolutionary conservation of heavy metal and stress response genes is important for improvement of forage crops by harnessing wild genetic variants in gene banks such as the Medicago HapMap collection.Peer reviewedFigshareConsejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202320232022info:eu-repo/semantics/datasethttp://purl.org/coar/resource_type/c_ddb1application/pdfhttp://hdl.handle.net/10261/311730reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésPaape, Timothy; Heiniger, Benjamin; Santo Domingo, Miguel; Clear, Michael R.; Lucas, M. Mercedes; Pueyo, José J. Genome-wide association study reveals complex genetic architecture of cadmium and mercury accumulation and tolerance traits in Medicago truncatula. https://doi.org/10.3389/fpls.2021.806949. http://hdl.handle.net/10261/286968https://doi.org/10.3389/fpls.2021.806949.s001Síinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3117302026-05-22T06:33:51Z
score 15.812429

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