Jensen, S E and Charles, J R and Muleta, K and Bradbury, P J and Casstevens, T and Deshpande, S P and Gore, M A and Gupta, R and Ilut, D C and Johnson, L and Lozano, R and Miller, Z and Ramu, P and Rathore, A and Romay, M C and Upadhyaya, H D and Varshney, R K and Morris, G P and Pressoir, G and Buckler, E S and Ramstein, G P (2020) A sorghum practical haplotype graph facilitates genome‐wide imputation and cost‐effective genomic prediction. The Plant Genome (TSI), 13 (1). pp. 1-15. ISSN 1940-3372
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Abstract
Successful management and utilization of increasingly large genomic datasets is essential for breeding programs to accelerate cultivar development. To help with this, we developed a Sorghum bicolor Practical Haplotype Graph (PHG) pangenome database that stores haplotypes and variant information. We developed two PHGs in sorghum that were used to identify genome-wide variants for 24 founders of the Chibas sorghum breeding program from 0.01x sequence coverage. The PHG called single nucleotide polymorphisms (SNPs) with 5.9% error at 0.01x coverage—only 3% higher than PHG error when calling SNPs from 8x coverage sequence. Additionally, 207 progenies from the Chibas genomic selection (GS) training population were sequenced and processed through the PHG. Missing genotypes were imputed from PHG parental haplotypes and used for genomic prediction. Mean prediction accuracies with PHG SNP calls range from .57–.73 and are similar to prediction accuracies obtained with genotyping-by-sequencing or targeted amplicon sequencing (rhAmpSeq) markers. This study demonstrates the use of a sorghum PHG to impute SNPs from low-coverage sequence data and shows that the PHG can unify genotype calls across multiple sequencing platforms. By reducing input sequence requirements, the PHG can decrease the cost of genotyping, make GS more feasible, and facilitate larger breeding populations. Our results demonstrate that the PHG is a useful research and breeding tool that maintains variant information from a diverse group of taxa, stores sequence data in a condensed but readily accessible format, unifies genotypes across genotyping platforms, and provides a cost-effective option for genomic selection.
| Item Type: | Article |
|---|---|
| Divisions: | Research Program : Genetic Gains |
| CRP: | UNSPECIFIED |
| Uncontrolled Keywords: | Sorghum, Genomics, Breeding |
| Subjects: | Others > Plant Breeding Mandate crops > Sorghum Others > Genetics and Genomics |
| Depositing User: | Mr Arun S |
| Date Deposited: | 04 Sep 2020 12:45 |
| Last Modified: | 04 Sep 2020 12:45 |
| URI: | http://oar.icrisat.org/id/eprint/11584 |
| Official URL: | https://doi.org/10.1002/tpg2.20009 |
| Projects: | UNSPECIFIED |
| Funders: | UNSPECIFIED |
| Acknowledgement: | This study is made possible by the support of the American People provided to the Feed the Future Innovation Lab for Collaborative Research on Sorghum and Millet through the United States Agency for International Development (USAID) under Associate Award No. AID-OAA-LA- 16-00003. The information, data, or work presented herein was also funded in part by the Advanced Research Projects Agency-Energy (ARPA-E), U.S. Department of Energy, under Award Number DE-AR0000598. The contents are the responsibility of the authors and do not necessarily state or reflect those of USAID, the United States Government, or any agency thereof. We thank Integrated DNA Technologies for a custom rhAmpSeq panel in sorghum. Additional support comes from the United States Department of Agriculture, Agricultural Research Service and the Bill and Melinda Gates Foundation. |
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