Genomic Selection in Wheat Breeding using Genotyping‐by‐Sequencing

By Jesse Poland, Jeffrey B. Endelman, J. Dawson, J. Rutkoski, Shuangye Wu, Y. Manes, Susanne Dreisigacker, Jose Crossa, Hector Sanchez-Villeda, M. Sorrells and 1 more. 2012

678 citations recorded by the source corpus.

Genomic selection (GS) uses genomewide molecular markers to predict breeding values and make selections of individuals or breeding lines prior to phenotyping. Here we show that genotyping‐by‐sequencing (GBS) can be used for de novo genotyping of breeding panels and to develop accurate GS models, even for the large, complex, and polyploid wheat (Triticum aestivum L.) genome. With GBS we discovered 41,371 single nucleotide polymorphisms (SNPs) in a set of 254 advanced breeding lines from CIMMYT's semiarid wheat breeding program. Four different methods were evaluated for imputing missing marker scores in this set of unmapped markers, including random forest regression and a newly developed multivariate‐normal expectation‐maximization algorithm, which gave more accurate imputation than heterozygous or mean imputation at the marker level, although no significant differences were observed in the accuracy of genomic‐estimated breeding values (GEBVs) among imputation methods. Genomic‐estimated breeding value prediction accuracies with GBS were 0.28 to 0.45 for grain yield, an improvement of 0.1 to 0.2 over an established marker platform for wheat. Genotyping‐by‐sequencing combines marker discovery and genotyping of large populations, making it an excellent marker platform for breeding applications even in the absence of a reference genome sequence or previous polymorphism discovery. In addition, the flexibility and low cost of GBS make this an ideal approach for genomics‐assisted breeding.

Subfields: Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/c4108f0d610346d775f46ba82cb0867b7f914135

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Citations in the corpus

Genome Wide Association Mapping of Sclerotinia sclerotiorum Resistance in Soybean with a Genotyping‐by‐Sequencing Approach (2014, positive): “However, the simultaneous handling of many small-efect QTLs for several characters within a breeding program via phenotypic selection could prove challenging. he development of genomic selection schemes could provide an alternative way to achieve this goal (Poland et al., 2012).”
Genetic Gains in Grain Yield Through Genomic Selection in Eight Bi-parental Maize Populations under Drought Stress (2015, background): “Most studies have used different cross-validation designs and schemes that attempt to predict performance of untested individuals and environments (VanRaden, 2008; Hayes et al., 2009; Crossa et al., 2010, 2013, 2014; Pérez-Rodríguez et al., 2012; Poland et al., 2012; Dawson et al., 2013; Heslot et a”
LinkImpute: Fast and Accurate Genotype Imputation for Nonmodel Organisms (2015, background): “For example, genotyping-by-sequencing (GBS) (Elshire et al. 2011) produces genotype data useful for GS in wheat (Poland et al. 2012) and drastically reduces the cost of linkage mapping in apple compared with arrays (Gardner et al. 2014).”
Relatedness and Genotype × Environment Interaction Affect Prediction Accuracies in Genomic Selection: A Study in Cassava (2013, positive): “The missing genotypic data were imputed using a classification method called random forest (Breiman, 2001; Poland et al., 2012).”
High-Throughput SNP Genotyping to Accelerate Crop Improvement (2014, methodology): “…and high-density genotyping on a training population to calculate genome estimated breeding values (GEBVs), which are then used on breeding populations for rapid cycles of selection with the genotype data alone (Heffner et al. 2009; Bernardo 2010; Jannink et al. 2010; Poland et al. 2012b).”
Genotyping‐by‐Sequencing for Plant Breeding and Genetics (2012, methodology): “…be robust across a range of species and capable of producing tens of thousands to hundreds of thousands of molecular markers (Elshire et al., 2011; Poland et al., 2012a). h e l exibility of GBS in regards to species, populations, and research objectives makes this an ideal tool for plant genetics…”
Breeding wheat for drought tolerance: Progress and technologies (2016, background): “Advances in sequence based gene expression analysis through the use of NGS techniques could shade more light on the regulatory mechanisms and networks of this polygenic trait (Poland et al. 2012; Edwards et al. 2013).”