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Department of Agronomy and Horticulture: Faculty Publications

Series

2020

Genomic selection

Articles 1 - 2 of 2

Full-Text Articles in Life Sciences

Soybean Barcsoysnp6k: An Assay For Soybean Genetics And Breeding Research, Qijian Song, Long Yan, Charles Quigley, Edward Fickus, He Wei, Linfeng Chen, Faming Dong, Susan Araya, Jinlong Liu, David Hyten, Vincent R. Pantalone, Randall L. Nelson Aug 2020

Soybean Barcsoysnp6k: An Assay For Soybean Genetics And Breeding Research, Qijian Song, Long Yan, Charles Quigley, Edward Fickus, He Wei, Linfeng Chen, Faming Dong, Susan Araya, Jinlong Liu, David Hyten, Vincent R. Pantalone, Randall L. Nelson

Department of Agronomy and Horticulture: Faculty Publications

The limited number of recombinant events in recombinant inbred lines suggests that for a biparental population with a limited number of recombinant inbred lines, it is unnecessary to genotype the lines with many markers. For genomic prediction and selection, previous studies have demonstrated that only 1000–2000 genome-wide common markers across all lines/accessions are needed to reach maximum efficiency of genomic prediction in populations. Evaluation of too many markers will not only increase the cost but also generate redundant information. We developed a soybean (Glycine max) assay, BARCSoySNP6K, containing 6000 markers, which were carefully chosen from the SoySNP50K assay based …


Enhancing Hybrid Prediction In Pearl Millet Using Genomic And/Or Multi- Environment Phenotypic Information Of Inbreds, Diego Jarquin, Reka Howard, Zhikai Liang, Shashi K. Gupta, James C. Schnable, Jose Crossa Jan 2020

Enhancing Hybrid Prediction In Pearl Millet Using Genomic And/Or Multi- Environment Phenotypic Information Of Inbreds, Diego Jarquin, Reka Howard, Zhikai Liang, Shashi K. Gupta, James C. Schnable, Jose Crossa

Department of Agronomy and Horticulture: Faculty Publications

Genomic selection (GS) is an emerging methodology that helps select superior lines among experimental cultivars in plant breeding programs. It offers the opportunity to increase the productivity of cultivars by delivering increased genetic gains and reducing the breeding cycles. This methodology requires inexpensive and sufficiently dense marker information to be successful, and with whole genome sequencing, it has become an important tool in many crops. The recent assembly of the pearl millet genome has made it possible to employ GS models to improve the selection procedure in pearl millet breeding programs. Here, three GS models were implemented and compared using …