Dataset Information

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses.

ABSTRACT: Artificial 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.

SUBMITTER: Martins FB

PROVIDER: S-EPMC8569613 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses.

Martins Felipe Bitencourt FB Moraes Aline Costa Lima ACL Aono Alexandre Hild AH Ferreira Rebecca Caroline Ulbricht RCU Chiari Lucimara L Simeão Rosangela Maria RM Barrios Sanzio Carvalho Lima SCL Santos Mateus Figueiredo MF Jank Liana L do Valle Cacilda Borges CB Vigna Bianca Baccili Zanotto BBZ de Souza Anete Pereira AP

Frontiers in plant science 20211022

Artificial 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 ...[more]

PMID: 34745171

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Project description:Background and aimsDiploid and polyploid Urochloa (including Brachiaria, Panicum and Megathyrsus species) C4 tropical forage grasses originating from Africa are important for food security and the environment, often being planted in marginal lands worldwide. We aimed to characterize the nature of their genomes, the repetitive DNA and the genome composition of polyploids, leading to a model of the evolutionary pathways within the group including many apomictic species.MethodsSome 362 forage grass accessions from international germplasm collections were studied, and ploidy was determined using an optimized flow cytometry method. Whole-genome survey sequencing and molecular cytogenetic analysis were used to identify chromosomes and genomes in Urochloa accessions belonging to the 'brizantha' and 'humidicola' agamic complexes and U. maxima.Key resultsGenome structures are complex and variable, with multiple ploidies and genome compositions within the species, and no clear geographical patterns. Sequence analysis of nine diploid and polyploid accessions enabled identification of abundant genome-specific repetitive DNA motifs. In situ hybridization with a combination of repetitive DNA and genomic DNA probes identified evolutionary divergence and allowed us to discriminate the different genomes present in polyploids.ConclusionsWe suggest a new coherent nomenclature for the genomes present. We develop a model of evolution at the whole-genome level in diploid and polyploid accessions showing processes of grass evolution. We support the retention of narrow species concepts for Urochloa brizantha, U. decumbens and U. ruziziensis, and do not consider diploids and polyploids of single species as cytotypes. The results and model will be valuable in making rational choices of parents for new hybrids, assist in use of the germplasm for breeding and selection of Urochloa with improved sustainability and agronomic potential, and assist in measuring and conserving biodiversity in grasslands.

Dataset Information

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses.

Publications

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses.

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