Genomic selection and genomics-assisted breeding delivers superior wheat cultivars

Vikas Belamkar1, P. Stephen Baenziger1, Mary Guttieri2, Ibrahim El-basyoni1,3, Sarah Blecha1,4, Fang Wang1, Diego Jarquin1, and Jesse Poland5

1** Department of Agronomy and Horticulture, University of Nebraska-Lincoln, USA.

2** USDA, Agricultural Research Service, Center for Grain and Animal Health Research, Hard Winter Wheat Genetics Research Unit, USA.

3** Crop Science Department, Faculty of Agriculture, Damanhour University, Egypt.

4** Plant Science Research Unit, USDA, Agricultural Research Service, USA.

5** Wheat Genetics Resource Center, Department of Plant Pathology, Kansas State University, USA.

vikas.belamkar@unl.edu

Abstract

The current era is no different from the pre-omics era in terms of the key questions (e.g., increasing yield gain, developing biotic and abiotic resistant cultivars, etc.), but the plant breeding programs now have access to improved and advanced technologies (phenomics, genomics, among others), better experimental designs, and statistical methods that can aid in developing climate-resilient and superior cultivars. The overall goal of this research is to develop novel quantitative genetics methodologies and integrate emerging technologies, such as genomic selection (GS), genomics-assisted breeding, and advanced statistical analyses in the Nebraska wheat breeding program to develop superior cultivars. Cultivar development requires nearly 10 to 12 years and experimental lines are tested in target environments over the years. In the first five to six years of the breeding cycle, the phenotype data are not accurate because lines are evaluated in one location (not representative of all the target environments) with none or minimal replication (due to the limited seed availability), and this also makes them prone to adverse climatic conditions. This main drawback of early generation testing can be overcome by using emerging technologies including GS. This talk will highlight how GS and genomics-assisted breeding using genotyping-by-sequencing derived SNP markers, and advanced phenotypic analyses incorporating spatial variation have substantially increased the selection accuracy in early generation nurseries, observation (F3:5) and preliminary (F3:6) yield trials, over the last five years. Additionally, practical insights will be presented on lines advanced using these methodologies currently in the final testing nursery as candidates for release as cultivars.

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Keywords:  Genomic selection, genomics-assisted breeding, Triticum spp., spatial variation.