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Title: Genome-wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America

Abstract

To improve the efficiency of breeding of Miscanthus for biomass yield, there exists a need to develop genomics-assisted selection for this long-lived perennial crop by relating genotype to phenotype and breeding value across a broad range of environments. We present the first genome-wide association (GWA) and genomic prediction study of Miscanthus that utilizes multi-location phenotypic data. A panel of 568 M. sinensis accessions was genotyped with 46,177 SNPs and evaluated at one subtropical and five temperate locations over three years for biomass yield and 14 yield-component traits. GWA and genomic prediction were performed separately for different years of data in order to assess reproducibility. The analyses were also performed for individual field trial locations, as well as combined phenotypic data across groups of locations. GWA analyses identified 27 significant SNPs for yield, and a total of 504 associations across 298 unique SNPs over all traits, sites, and years. For yield, the greatest number of significant SNPs was identified by combining phenotypic data across all six locations. For some of the other yield-component traits, greater numbers of significant SNPs were obtained from single site data, although the number of significant SNPs varied greatly from site to site. Candidate genes were identified.more » Accounting for population structure, genomic prediction accuracies for biomass yield ranged from 0.32-0.36 over five northern sites and 0.15-0.20 for the subtropical location, relying on estimation method. Genomic prediction accuracies of all traits were similar for single-location and multi-location data, suggesting that genomic selection will be useful for breeding broadly-adapted M. sinensis as well as M. sinensis optimized for specific climates. All of our data, including DNA sequences flanking each SNP, are publicly available. By facilitating genomic selection in M. sinensis and M. ×giganteus, our results will accelerate the breeding of these species for biomass in diverse environments.« less

Authors:
ORCiD logo [1];  [2];  [2];  [3];  [4];  [5];  [6];  [7];  [8];  [1];  [9]; ORCiD logo [2];  [7];  [7];  [10]; ORCiD logo [1];  [1]
  1. Univ. of Illinois, Urbana-Champaign, IL (United States)
  2. Hokkaido Univ., Sapporo (Japan)
  3. Colorado State Univ., Fort Collins, CO (United States)
  4. Konkuk Univ., Seoul (South Korea)
  5. Univ. of Nebraska‐Lincoln, Lincoln, NE (United States)
  6. Bio Architecture Lab .Berkeley, CA (United States)
  7. Kangwon National Univ., Gangwon (South Korea)
  8. Zhejiang Univ., Hangzhou (China)
  9. HuaZhi Biotechnology Inst., Hunan (China)
  10. Huazhong Agricultural Univ., Hubei (China)
Publication Date:
Research Org.:
Univ. of Illinois, Urbana-Champaign, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1512519
Alternate Identifier(s):
OSTI ID: 1510514; OSTI ID: 1512520
Grant/Contract Number:  
SC0018420; SC0006634 DE-SC0018420
Resource Type:
Published Article
Journal Name:
Global Change Biology. Bioenergy
Additional Journal Information:
Journal Name: Global Change Biology. Bioenergy; Journal ID: ISSN 1757-1693
Publisher:
Wiley
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; Miscanthus sinensis; Miscanthus ×giganteus; genomic selection; genome‐wide association studies; RAD‐seq; biomass yield; field trials

Citation Formats

Clark, Lindsay V., Dwiyanti, Maria S., Anzoua, Kossonou G., Brummer, Joe E., Ghimire, Bimal Kumar, Głowacka, Katarzyna, Hall, Megan, Heo, Kweon, Jin, Xiaoli, Lipka, Alexander E., Peng, Junhua, Yamada, Toshihiko, Yoo, Ji Hye, Yu, Chang Yeon, Zhao, Hua, Long, Stephen P., and Sacks, Erik J.. Genome-wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America. United States: N. p., 2019. Web. doi:10.1111/gcbb.12620.
Clark, Lindsay V., Dwiyanti, Maria S., Anzoua, Kossonou G., Brummer, Joe E., Ghimire, Bimal Kumar, Głowacka, Katarzyna, Hall, Megan, Heo, Kweon, Jin, Xiaoli, Lipka, Alexander E., Peng, Junhua, Yamada, Toshihiko, Yoo, Ji Hye, Yu, Chang Yeon, Zhao, Hua, Long, Stephen P., & Sacks, Erik J.. Genome-wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America. United States. doi:10.1111/gcbb.12620.
Clark, Lindsay V., Dwiyanti, Maria S., Anzoua, Kossonou G., Brummer, Joe E., Ghimire, Bimal Kumar, Głowacka, Katarzyna, Hall, Megan, Heo, Kweon, Jin, Xiaoli, Lipka, Alexander E., Peng, Junhua, Yamada, Toshihiko, Yoo, Ji Hye, Yu, Chang Yeon, Zhao, Hua, Long, Stephen P., and Sacks, Erik J.. Wed . "Genome-wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America". United States. doi:10.1111/gcbb.12620.
@article{osti_1512519,
title = {Genome-wide association and genomic prediction for biomass yield in a genetically diverse Miscanthus sinensis germplasm panel phenotyped at five locations in Asia and North America},
author = {Clark, Lindsay V. and Dwiyanti, Maria S. and Anzoua, Kossonou G. and Brummer, Joe E. and Ghimire, Bimal Kumar and Głowacka, Katarzyna and Hall, Megan and Heo, Kweon and Jin, Xiaoli and Lipka, Alexander E. and Peng, Junhua and Yamada, Toshihiko and Yoo, Ji Hye and Yu, Chang Yeon and Zhao, Hua and Long, Stephen P. and Sacks, Erik J.},
abstractNote = {To improve the efficiency of breeding of Miscanthus for biomass yield, there exists a need to develop genomics-assisted selection for this long-lived perennial crop by relating genotype to phenotype and breeding value across a broad range of environments. We present the first genome-wide association (GWA) and genomic prediction study of Miscanthus that utilizes multi-location phenotypic data. A panel of 568 M. sinensis accessions was genotyped with 46,177 SNPs and evaluated at one subtropical and five temperate locations over three years for biomass yield and 14 yield-component traits. GWA and genomic prediction were performed separately for different years of data in order to assess reproducibility. The analyses were also performed for individual field trial locations, as well as combined phenotypic data across groups of locations. GWA analyses identified 27 significant SNPs for yield, and a total of 504 associations across 298 unique SNPs over all traits, sites, and years. For yield, the greatest number of significant SNPs was identified by combining phenotypic data across all six locations. For some of the other yield-component traits, greater numbers of significant SNPs were obtained from single site data, although the number of significant SNPs varied greatly from site to site. Candidate genes were identified. Accounting for population structure, genomic prediction accuracies for biomass yield ranged from 0.32-0.36 over five northern sites and 0.15-0.20 for the subtropical location, relying on estimation method. Genomic prediction accuracies of all traits were similar for single-location and multi-location data, suggesting that genomic selection will be useful for breeding broadly-adapted M. sinensis as well as M. sinensis optimized for specific climates. All of our data, including DNA sequences flanking each SNP, are publicly available. By facilitating genomic selection in M. sinensis and M. ×giganteus, our results will accelerate the breeding of these species for biomass in diverse environments.},
doi = {10.1111/gcbb.12620},
journal = {Global Change Biology. Bioenergy},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {4}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
DOI: 10.1111/gcbb.12620

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