eprintid: 11584
rev_number: 11
eprint_status: archive
userid: 3170
dir: disk0/00/01/15/84
datestamp: 2020-09-04 12:45:07
lastmod: 2020-09-04 12:45:08
status_changed: 2020-09-04 12:45:07
type: article
metadata_visibility: show
creators_name: Jensen, S E
creators_name: Charles, J R
creators_name: Muleta, K
creators_name: Bradbury, P J
creators_name: Casstevens, T
creators_name: Deshpande, S P
creators_name: Gore, M A
creators_name: Gupta, R
creators_name: Ilut, D C
creators_name: Johnson, L
creators_name: Lozano, R
creators_name: Miller, Z
creators_name: Ramu, P
creators_name: Rathore, A
creators_name: Romay, M C
creators_name: Upadhyaya, H D
creators_name: Varshney, R K
creators_name: Morris, G P
creators_name: Pressoir, G
creators_name: Buckler, E S
creators_name: Ramstein, G P
creators_gender: Female
creators_gender: Female
icrisatcreators_name: Deshpande, S P
icrisatcreators_name: Gupta, R
icrisatcreators_name: Rathore, A
icrisatcreators_name: Upadhyaya, H D
icrisatcreators_name: Varshney, R K
affiliation: Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca
affiliation: Chibas and Department of Agriculture and Environmental Sciences, Quisqueya University, Port-au-Prince, Haiti
affiliation: Department of Agronomy, Kansas State University, Manhattan, KS
affiliation: Institute for Genomic Diversity, Cornell University, Ithaca, NY
affiliation: ICRISAT (Patancheru)
affiliation: United States Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY
country: USA
country: Haiti
country: India
title: A sorghum practical haplotype graph facilitates genome‐wide imputation and cost‐effective genomic prediction
ispublished: pub
subjects: PLB1
subjects: s1.4
subjects: s2.13
divisions: CRPS3
full_text_status: public
keywords: Sorghum, Genomics, Breeding
note: 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.
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.
date: 2020-03
date_type: published
publication: The Plant Genome (TSI)
volume: 13
number: 1
publisher: Crop Science Society of America
pagerange: 1-15
id_number: doi:10.1002/tpg2.20009
refereed: TRUE
issn: 1940-3372
official_url: https://doi.org/10.1002/tpg2.20009
related_url_url: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C5&q=10.1002%2Ftpg2.20009&btnG=
related_url_type: pub
citation:   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     
document_url: http://oar.icrisat.org/11584/1/tpg2.20009.pdf