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Genomic Tools for Kernza®, Intermediate Wheatgrass Improvement
——Breeder’s toolbox for improving a new perennial grain crop
Xiaofei Zhang1, Traci Kantarski2, Steve Larson3, Kevin Dorn4, Jeremy Schmutz5, Lee DeHaan6,
Jesse Poland4, Donald Wyse1 and James Anderson1
1University of Minnesota, St. Paul, MN; 2Columbia University, New York, NY; 3USDA-ARS Forage and Range
Research, Logan, UT; 4Kansas State University, Manhattan, KS; 5HudsonAlpha Institute for Biotechnology,
Huntsville, AL; 6The Land Institute, Salina, KS
• greatly reduce soil erosion
• sequester more carbon
• reduce green house gas emissions
• reduce nitrogen and phosphorus
contamination of freshwater and
marine ecosystems, and
• reduce weed competition, minimizing
the need of tillage or herbicide
applications.
Kernza, the First Widely Available
Perennial Grain Crop
In 2011, the Forever Green Initiative at the
University of Minnesota initiated the breeding
program with germplasm supplied by The
Land Institute. The goal is to increase the
yield potential of Kernza and improve
Kernza for profitable production in the
Midwest. To increase the efficiency of
selection and accelerate its improvement, we
have developed genomic tools for Kernza
including molecular markers, genetic maps,
genetic mapping, and genomic selection.
Discover Genome-wide Markers
Fig. 1 Discover markers for genetic mapping and genomic
selection using genotyping-by-sequencing[1].
Develop a Consensus Genetic Map
We integrated these maps from seven
populations to produce a consensus map with
21 linkage groups containing 10,029 markers.
Each of the 21 linkage groups contained
between 237 and 683 markers, cumulatively
covering 2,891 cM[2].
Fig. 2 High collinearity and synteny were observed
between barley and Kernza genomes[1].
We performed association mapping in a
breeding population with 1,126 genets and
linkage mapping in two bi-parental
populations with 172 and 265 genets,
respectively.
Map Quantitative Trait Loci
Fig. 3 High genetic correlations (a) were observed among
seed traits and many common QTLs were detected in
the association mapping panel (b) and two linkage
mapping populations (c and d).
Fig. 4 Thirty-three quantitative trait loci for seed weight
and size were identified by association mapping, of
which 23 were verified by linkage mapping.
Sequence Kernza Genome
Establish Genomic Selection
Kernza®, the trade name for intermediate
wheatgrass (Thinopyrum intermedium), is
being developed as a perennial grain crop. By
providing year-round soil coverage and
uniquely large belowground carbon inputs
from roots, farmers growing Kernza will:
Genomic selection models were developed
using 3,883 markers discovered in a breeding
population containing 1,126 representative
genets from 58 half-sib families.
Fig. 5 High predictive ability was observed for seven
agronomic traits using independent validation,
ranging from 0.42 for biomass to 0.66 for seed
weight[1].
Fig. 6 A genomic selection-based recurrent selection
method was established and is being used for
Kernza improvement [1].
Discovery of genome-wide markers, development of
genetic maps, identification of quantitative trait
loci, and establishment of genomic selection will
increase selection efficiency and genetic gain for the
improvement of Kernza. By combining association
mapping, marker-assisted selection for parents, and
genomic selection for progeny, we should be able to
develop Kernza varieties good enough for commercial
production within a few years.
[1] Zhang et al., 2016. The Plant Genome, doi: 10.3835/plantgenome2015.07.0059;
[2] Kantarski et al., 2016. Theoretical and Applied Genetics 10.1007/s00122-016-2799-7.
Assembly of a draft genome of a haploid
plant has been completed using the NRGene
DeNovoMAGIC pipeline and has been
anchored to the consensus map. Efforts to
improve the anchoring/ordering of this
assembly using POPSEQ and HiC are ongoing.
We would like to thank the Minnesota Supercomputing Institute for their
resources in genomic data analysis. This work was supported by the Initiative of
Renewable Energy & The Environment, University of Minnesota, the Forever
Green Initiative at the University of Minnesota, the Malone Family Foundation,
and the DOE Joint Genome Institute Community Science Program
Perspectives in Kernza Breeding

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PAG 2017 poster

  • 1. Genomic Tools for Kernza®, Intermediate Wheatgrass Improvement ——Breeder’s toolbox for improving a new perennial grain crop Xiaofei Zhang1, Traci Kantarski2, Steve Larson3, Kevin Dorn4, Jeremy Schmutz5, Lee DeHaan6, Jesse Poland4, Donald Wyse1 and James Anderson1 1University of Minnesota, St. Paul, MN; 2Columbia University, New York, NY; 3USDA-ARS Forage and Range Research, Logan, UT; 4Kansas State University, Manhattan, KS; 5HudsonAlpha Institute for Biotechnology, Huntsville, AL; 6The Land Institute, Salina, KS • greatly reduce soil erosion • sequester more carbon • reduce green house gas emissions • reduce nitrogen and phosphorus contamination of freshwater and marine ecosystems, and • reduce weed competition, minimizing the need of tillage or herbicide applications. Kernza, the First Widely Available Perennial Grain Crop In 2011, the Forever Green Initiative at the University of Minnesota initiated the breeding program with germplasm supplied by The Land Institute. The goal is to increase the yield potential of Kernza and improve Kernza for profitable production in the Midwest. To increase the efficiency of selection and accelerate its improvement, we have developed genomic tools for Kernza including molecular markers, genetic maps, genetic mapping, and genomic selection. Discover Genome-wide Markers Fig. 1 Discover markers for genetic mapping and genomic selection using genotyping-by-sequencing[1]. Develop a Consensus Genetic Map We integrated these maps from seven populations to produce a consensus map with 21 linkage groups containing 10,029 markers. Each of the 21 linkage groups contained between 237 and 683 markers, cumulatively covering 2,891 cM[2]. Fig. 2 High collinearity and synteny were observed between barley and Kernza genomes[1]. We performed association mapping in a breeding population with 1,126 genets and linkage mapping in two bi-parental populations with 172 and 265 genets, respectively. Map Quantitative Trait Loci Fig. 3 High genetic correlations (a) were observed among seed traits and many common QTLs were detected in the association mapping panel (b) and two linkage mapping populations (c and d). Fig. 4 Thirty-three quantitative trait loci for seed weight and size were identified by association mapping, of which 23 were verified by linkage mapping. Sequence Kernza Genome Establish Genomic Selection Kernza®, the trade name for intermediate wheatgrass (Thinopyrum intermedium), is being developed as a perennial grain crop. By providing year-round soil coverage and uniquely large belowground carbon inputs from roots, farmers growing Kernza will: Genomic selection models were developed using 3,883 markers discovered in a breeding population containing 1,126 representative genets from 58 half-sib families. Fig. 5 High predictive ability was observed for seven agronomic traits using independent validation, ranging from 0.42 for biomass to 0.66 for seed weight[1]. Fig. 6 A genomic selection-based recurrent selection method was established and is being used for Kernza improvement [1]. Discovery of genome-wide markers, development of genetic maps, identification of quantitative trait loci, and establishment of genomic selection will increase selection efficiency and genetic gain for the improvement of Kernza. By combining association mapping, marker-assisted selection for parents, and genomic selection for progeny, we should be able to develop Kernza varieties good enough for commercial production within a few years. [1] Zhang et al., 2016. The Plant Genome, doi: 10.3835/plantgenome2015.07.0059; [2] Kantarski et al., 2016. Theoretical and Applied Genetics 10.1007/s00122-016-2799-7. Assembly of a draft genome of a haploid plant has been completed using the NRGene DeNovoMAGIC pipeline and has been anchored to the consensus map. Efforts to improve the anchoring/ordering of this assembly using POPSEQ and HiC are ongoing. We would like to thank the Minnesota Supercomputing Institute for their resources in genomic data analysis. This work was supported by the Initiative of Renewable Energy & The Environment, University of Minnesota, the Forever Green Initiative at the University of Minnesota, the Malone Family Foundation, and the DOE Joint Genome Institute Community Science Program Perspectives in Kernza Breeding