A semi-automated SNP-based approach for contaminant identification in biparental Polyploid Populations of tropical forage grasses.

Vista sencilla de ítem
dc.contributorFELIPE BITENCOURT MARTINS, Center for Molecular Biology and Genetic Engineering
dc.contributorALINE COSTA LIMA MORAES, Center for Molecular Biology and Genetic Engineering
dc.contributorALEXANDRE HILD AONO, Center for Molecular Biology and Genetic Engineering
dc.contributorREBECCA CAROLINE ULBRICHT FERREIRA, Center for Molecular Biology and Genetic Engineering
dc.contributorLUCIMARA CHIARI, CNPGC
dc.contributorROSANGELA MARIA SIMEAO, CNPGC
dc.contributorSANZIO CARVALHO LIMA BARRIOS, CNPGC
dc.contributorMATEUS FIGUEIREDO SANTOS, CNPGC
dc.contributorLIANA JANK, CNPGC
dc.contributorCACILDA BORGES DO VALLE, CNPGC
dc.contributorBIANCA BACCILI ZANOTTO VIGNA, CPPSE
dc.contributorANETE PEREIRA DE SOUZA, Center for Molecular Biology and Genetic Engineering
dc.contributorUNICAMP.
dc.creatorMARTINS, F. B.
dc.creatorMORAES, A. C. L.
dc.creatorAONO, A. H.
dc.creatorFERREIRA, R. C. U.
dc.creatorCHIARI, L.
dc.creatorSIMEÃO, R. M.
dc.creatorBARRIOS, S. C. L.
dc.creatorSANTOS, M. F.
dc.creatorJANK, L.
dc.creatorVALLE, C. B. do
dc.creatorVIGNA, B. B. Z.
dc.creatorSOUZA, A. P. DE
dc.date2021-12-07T14:00:42Z
dc.date2021-12-07T14:00:42Z
dc.date2021-12-07
dc.date2021
dc.date.accessioned2026-07-07T05:29:24Z
dc.descriptionArtificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation, and clustering analysis (CA). The combination of these methods allowed for the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.
dc.format19 p.
dc.identifierFrontiers in Plant Science, v.12, article 737919, 2021.
dc.identifierhttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1137227
dc.identifierhttps://doi.org/10.3389/fpls.2021.737919
dc.identifier.urihttp://hdl.handle.net/123456789/492767
dc.languageeng
dc.rightsopenAccess
dc.subjectGBS
dc.subjectApomictic clones
dc.subjectSelf fertilization
dc.subjectHalf sibling
dc.subjectAllele dosage
dc.subjectClustering analysis
dc.subjectShiny
dc.subjectPrincipal component analysis
dc.titleA semi-automated SNP-based approach for contaminant identification in biparental Polyploid Populations of tropical forage grasses.
dc.typeArtigo de periódico

Archivos

Colecciones

Embrapa Pecuaria Sudeste (CPPSE)