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Title: Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass

Abstract

AbstractLong-term climate change and periodic environmental extremes threaten food and fuel security1and global crop productivity2–4. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience5, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation6—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass (Panicum virgatum). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for themore » sustainable production of bioenergy.« less

Authors:
ORCiD logo [1];  [2];  [1];  [2]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [1];  [1];  [3]; ORCiD logo [4];  [4];  [5];  [1];  [4];  [4];  [4];  [1];  [2];  [6]; ORCiD logo [7] more »; ORCiD logo [8];  [4]; ORCiD logo [9];  [1];  [9]; ORCiD logo [10]; ORCiD logo [11];  [1];  [12];  [12];  [1]; ORCiD logo [4];  [13];  [14];  [1];  [2];  [1];  [4];  [4];  [4];  [2];  [13];  [2];  [15];  [16]; ORCiD logo [17]; ORCiD logo [18];  [19];  [20];  [18];  [21];  [22]; ORCiD logo [23];  [13];  [24]; ORCiD logo [13]; ORCiD logo [8]; ORCiD logo [25]; ORCiD logo [26];  [27];  [28];  [7]; ORCiD logo [29]; ORCiD logo [1]; ORCiD logo [2]; ORCiD logo [30] « less
+ Show Author Affiliations
  1. HudsonAlpha Inst. for Biotechnology, Huntsville, AL (United States)
  2. Univ. of Texas, Austin, TX (United States)
  3. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
  4. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  5. Rutgers Univ., New Brunswick, NJ (United States)
  6. US Dept. of Agriculture (USDA), Griffin, GA (United States)
  7. Michigan State Univ., East Lansing, MI (United States)
  8. Univ. of Arizona, Tucson, AZ (United States)
  9. Univ. of Georgia, Athens, GA (United States)
  10. Clemson Univ., SC (United States)
  11. Univ. of Texas, Austin, TX (United States); Marshall Univ., Huntington, WV (United States)
  12. Jawaharlal Nehru Univ., New Delhi (India)
  13. Noble Research Inst. LLC, Ardmore, OK (United States)
  14. Univ. of Nebraska, Lincoln, NE (United States)
  15. South Dakota State Univ., Brookings, SD (United States)
  16. US Dept. of Agriculture (USDA), Temple, TX (United States)
  17. Univ. of Missouri, Columbia, MO (United States)
  18. Argonne National Lab. (ANL), Argonne, IL (United States)
  19. US Dept. of Agriculture (USDA), Kingsville, TX (United States)
  20. Antonio Narro Agrarian Autonomous Univ., Saltillo (Mexico)
  21. US Dept. of Agriculture (USDA), Lincoln, NE (United States)
  22. Texas A & M Univ., Overton, TX (United States)
  23. Univ. of California, Davis, CA (United States); Joint BioEnergy Institute (JBEI), Emeryville, CA (United States)
  24. US Dept. of Agriculture (USDA), Albany, CA (United States)
  25. Oklahoma State Univ., Stillwater, OK (United States)
  26. Univ. of Oklahoma, Norman, OK (United States); Washington State Univ., Pullman, WA (United States)
  27. US Dept. of Agriculture (USDA), Madison, WI (United States); Univ. of Wisconsin, Madison, WI (United States)
  28. Univ. of Georgia, Athens, GA (United States); USDOE Center for Bioenergy Innovation, Oak Ridge, TN (United States)
  29. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States); Center for Advanced Bioenergy and Bioproducts Innovation (CABBI), Berkeley, CA (United States); Chan-Zuckerberg Biohub, San Francisco, CA (United States)
  30. HudsonAlpha Inst. for Biotechnology, Huntsville, AL (United States); Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Publication Date:
Research Org.:
Great Lakes Bioenergy Research Center (GLBRC), Madison, WI (United States); Univ. of Texas, Austin, TX (United States); Michigan State Univ., East Lansing, MI (United States); Univ. of Georgia, Athens, GA (United States); Argonne National Laboratory (ANL), Argonne, IL (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER). Biological Systems Science Division; National Science Foundation (NSF)
OSTI Identifier:
1773844
Alternate Identifier(s):
OSTI ID: 1776871; OSTI ID: 1787614; OSTI ID: 1826700
Grant/Contract Number:  
SC0014156; SC0017883; SC0010743; SC0018409; AC02-06CH11357; FC02-07ER64494; AC05-000R22725; AC02-05CH11231; IOS0922457; IOS1444533; IOS1402393
Resource Type:
Accepted Manuscript
Journal Name:
Nature (London)
Additional Journal Information:
Journal Name: Nature (London); Journal Volume: 590; Journal Issue: 7846; Journal ID: ISSN 0028-0836
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
09 BIOMASS FUELS; switchgrass; Panicum virgatum; climate adaptation

Citation Formats

Lovell, John T., MacQueen, Alice H., Mamidi, Sujan, Bonnette, Jason, Jenkins, Jerry, Napier, Joseph D., Sreedasyam, Avinash, Healey, Adam, Session, Adam, Shu, Shengqiang, Barry, Kerrie, Bonos, Stacy, Boston, LoriBeth, Daum, Christopher, Deshpande, Shweta, Ewing, Aren, Grabowski, Paul P., Haque, Taslima, Harrison, Melanie, Jiang, Jiming, Kudrna, Dave, Lipzen, Anna, Pendergast, Thomas H., Plott, Chris, Qi, Peng, Saski, Christopher A., Shakirov, Eugene V., Sims, David, Sharma, Manoj, Sharma, Rita, Stewart, Ada, Singan, Vasanth R., Tang, Yuhong, Thibivillier, Sandra, Webber, Jenell, Weng, Xiaoyu, Williams, Melissa, Wu, Guohong Albert, Yoshinaga, Yuko, Zane, Matthew, Zhang, Li, Zhang, Jiyi, Behrman, Kathrine D., Boe, Arvid R., Fay, Philip A., Fritschi, Felix B., Jastrow, Julie D., Lloyd-Reilley, John, Martínez-Reyna, Juan Manuel, Matamala, Roser, Mitchell, Robert B., Rouquette, Francis M., Ronald, Pamela, Saha, Malay, Tobias, Christian M., Udvardi, Michael, Wing, Rod A., Wu, Yanqi, Bartley, Laura E., Casler, Michael, Devos, Katrien M., Lowry, David B., Rokhsar, Daniel S., Grimwood, Jane, Juenger, Thomas E., and Schmutz, Jeremy. Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass. United States: N. p., 2021. Web. doi:10.1038/s41586-020-03127-1.
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Lovell, John T., MacQueen, Alice H., Mamidi, Sujan, Bonnette, Jason, Jenkins, Jerry, Napier, Joseph D., Sreedasyam, Avinash, Healey, Adam, Session, Adam, Shu, Shengqiang, Barry, Kerrie, Bonos, Stacy, Boston, LoriBeth, Daum, Christopher, Deshpande, Shweta, Ewing, Aren, Grabowski, Paul P., Haque, Taslima, Harrison, Melanie, Jiang, Jiming, Kudrna, Dave, Lipzen, Anna, Pendergast, Thomas H., Plott, Chris, Qi, Peng, Saski, Christopher A., Shakirov, Eugene V., Sims, David, Sharma, Manoj, Sharma, Rita, Stewart, Ada, Singan, Vasanth R., Tang, Yuhong, Thibivillier, Sandra, Webber, Jenell, Weng, Xiaoyu, Williams, Melissa, Wu, Guohong Albert, Yoshinaga, Yuko, Zane, Matthew, Zhang, Li, Zhang, Jiyi, Behrman, Kathrine D., Boe, Arvid R., Fay, Philip A., Fritschi, Felix B., Jastrow, Julie D., Lloyd-Reilley, John, Martínez-Reyna, Juan Manuel, Matamala, Roser, Mitchell, Robert B., Rouquette, Francis M., Ronald, Pamela, Saha, Malay, Tobias, Christian M., Udvardi, Michael, Wing, Rod A., Wu, Yanqi, Bartley, Laura E., Casler, Michael, Devos, Katrien M., Lowry, David B., Rokhsar, Daniel S., Grimwood, Jane, Juenger, Thomas E., & Schmutz, Jeremy. Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass. United States. https://doi.org/10.1038/s41586-020-03127-1
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Lovell, John T., MacQueen, Alice H., Mamidi, Sujan, Bonnette, Jason, Jenkins, Jerry, Napier, Joseph D., Sreedasyam, Avinash, Healey, Adam, Session, Adam, Shu, Shengqiang, Barry, Kerrie, Bonos, Stacy, Boston, LoriBeth, Daum, Christopher, Deshpande, Shweta, Ewing, Aren, Grabowski, Paul P., Haque, Taslima, Harrison, Melanie, Jiang, Jiming, Kudrna, Dave, Lipzen, Anna, Pendergast, Thomas H., Plott, Chris, Qi, Peng, Saski, Christopher A., Shakirov, Eugene V., Sims, David, Sharma, Manoj, Sharma, Rita, Stewart, Ada, Singan, Vasanth R., Tang, Yuhong, Thibivillier, Sandra, Webber, Jenell, Weng, Xiaoyu, Williams, Melissa, Wu, Guohong Albert, Yoshinaga, Yuko, Zane, Matthew, Zhang, Li, Zhang, Jiyi, Behrman, Kathrine D., Boe, Arvid R., Fay, Philip A., Fritschi, Felix B., Jastrow, Julie D., Lloyd-Reilley, John, Martínez-Reyna, Juan Manuel, Matamala, Roser, Mitchell, Robert B., Rouquette, Francis M., Ronald, Pamela, Saha, Malay, Tobias, Christian M., Udvardi, Michael, Wing, Rod A., Wu, Yanqi, Bartley, Laura E., Casler, Michael, Devos, Katrien M., Lowry, David B., Rokhsar, Daniel S., Grimwood, Jane, Juenger, Thomas E., and Schmutz, Jeremy. Wed . "Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass". United States. https://doi.org/10.1038/s41586-020-03127-1. https://www.osti.gov/servlets/purl/1773844.
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@article{osti_1773844,
title = {Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass},
author = {Lovell, John T. and MacQueen, Alice H. and Mamidi, Sujan and Bonnette, Jason and Jenkins, Jerry and Napier, Joseph D. and Sreedasyam, Avinash and Healey, Adam and Session, Adam and Shu, Shengqiang and Barry, Kerrie and Bonos, Stacy and Boston, LoriBeth and Daum, Christopher and Deshpande, Shweta and Ewing, Aren and Grabowski, Paul P. and Haque, Taslima and Harrison, Melanie and Jiang, Jiming and Kudrna, Dave and Lipzen, Anna and Pendergast, Thomas H. and Plott, Chris and Qi, Peng and Saski, Christopher A. and Shakirov, Eugene V. and Sims, David and Sharma, Manoj and Sharma, Rita and Stewart, Ada and Singan, Vasanth R. and Tang, Yuhong and Thibivillier, Sandra and Webber, Jenell and Weng, Xiaoyu and Williams, Melissa and Wu, Guohong Albert and Yoshinaga, Yuko and Zane, Matthew and Zhang, Li and Zhang, Jiyi and Behrman, Kathrine D. and Boe, Arvid R. and Fay, Philip A. and Fritschi, Felix B. and Jastrow, Julie D. and Lloyd-Reilley, John and Martínez-Reyna, Juan Manuel and Matamala, Roser and Mitchell, Robert B. and Rouquette, Francis M. and Ronald, Pamela and Saha, Malay and Tobias, Christian M. and Udvardi, Michael and Wing, Rod A. and Wu, Yanqi and Bartley, Laura E. and Casler, Michael and Devos, Katrien M. and Lowry, David B. and Rokhsar, Daniel S. and Grimwood, Jane and Juenger, Thomas E. and Schmutz, Jeremy},
abstractNote = {AbstractLong-term climate change and periodic environmental extremes threaten food and fuel security1and global crop productivity2–4. Although molecular and adaptive breeding strategies can buffer the effects of climatic stress and improve crop resilience5, these approaches require sufficient knowledge of the genes that underlie productivity and adaptation6—knowledge that has been limited to a small number of well-studied model systems. Here we present the assembly and annotation of the large and complex genome of the polyploid bioenergy crop switchgrass (Panicum virgatum). Analysis of biomass and survival among 732 resequenced genotypes, which were grown across 10 common gardens that span 1,800 km of latitude, jointly revealed extensive genomic evidence of climate adaptation. Climate–gene–biomass associations were abundant but varied considerably among deeply diverged gene pools. Furthermore, we found that gene flow accelerated climate adaptation during the postglacial colonization of northern habitats through introgression of alleles from a pre-adapted northern gene pool. The polyploid nature of switchgrass also enhanced adaptive potential through the fractionation of gene function, as there was an increased level of heritable genetic diversity on the nondominant subgenome. In addition to investigating patterns of climate adaptation, the genome resources and gene–trait associations developed here provide breeders with the necessary tools to increase switchgrass yield for the sustainable production of bioenergy.},
doi = {10.1038/s41586-020-03127-1},
journal = {Nature (London)},
number = 7846,
volume = 590,
place = {United States},
year = {Wed Jan 27 00:00:00 EST 2021},
month = {Wed Jan 27 00:00:00 EST 2021}
}
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Net energy of cellulosic ethanol from switchgrass
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Accelerating the Switchgrass (Panicum virgatum L.) Breeding Cycle Using Genomic Selection Approaches
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Durum wheat genome highlights past domestication signatures and future improvement targets
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Post-glacial evolution of Panicum virgatum: centers of diversity and gene pools revealed by SSR markers and cpDNA sequences
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VarScan 2: Somatic mutation and copy number alteration discovery in cancer by exome sequencing
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Five Nuclear Loci Resolve the Polyploid History of Switchgrass (Panicum virgatum L.) and Relatives
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Massive haplotypes underlie ecotypic differentiation in sunflowers
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The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools
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A Low Resolution Epistasis Mapping Approach To Identify Chromosome Arm Interactions in Allohexaploid Wheat
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  • Santantonio, Nicholas; Jannink, Jean-Luc; Sorrells, Mark
  • G3 Genes|Genomes|Genetics, Vol. 9, Issue 3
  • DOI: 10.1534/g3.118.200646

Adaptations between Ecotypes and along Environmental Gradients in Panicum virgatum
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  • Lowry, David B.; Behrman, Kathrine D.; Grabowski, Paul
  • The American Naturalist, Vol. 183, Issue 5
  • DOI: 10.1086/675760

adegenet 1.3-1: new tools for the analysis of genome-wide SNP data
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Haplotype estimation for biobank-scale data sets
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  • O'Connell, Jared; Sharp, Kevin; Shrine, Nick
  • Nature Genetics, Vol. 48, Issue 7
  • DOI: 10.1038/ng.3583

HTSeq--a Python framework to work with high-throughput sequencing data
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A genome resource for green millet Setaria viridis enables discovery of agronomically valuable loci
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UniProt: a worldwide hub of protein knowledge
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A high-performance computing toolset for relatedness and principal component analysis of SNP data
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phangorn: phylogenetic analysis in R
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Extending multivariate distance matrix regression with an effect size measure and the asymptotic null distribution of the test statistic
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A genome assembly and the somatic genetic and epigenetic mutation rate in a wild long-lived perennial Populus trichocarpa
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  • Hofmeister, Brigitte T.; Denkena, Johanna; Colomé-Tatché, Maria
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  • DOI: 10.1186/s13059-020-02162-5

Quantitative trait locus mapping identifies candidate alleles involved in adaptive introgression and range expansion in a wild sunflower
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  • Whitney, Kenneth D.; Broman, Karl W.; Kane, Nolan C.
  • Molecular Ecology, Vol. 24, Issue 9
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The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data
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The genomic landscape of molecular responses to natural drought stress in Panicum hallii
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False discovery rates: a new deal
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A fast, lock-free approach for efficient parallel counting of occurrences of k-mers
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Range Shifts and Adaptive Responses to Quaternary Climate Change
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Accurate detection of complex structural variations using single-molecule sequencing
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Navigating complexity to breed disease-resistant crops
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  • Nelson, Rebecca; Wiesner-Hanks, Tyr; Wisser, Randall
  • Nature Reviews Genetics, Vol. 19, Issue 1
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Flexible statistical methods for estimating and testing effects in genomic studies with multiple conditions
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Genome-wide associations with flowering time in switchgrass using exome-capture sequencing data
journal, July 2016

  • Grabowski, Paul P.; Evans, Joseph; Daum, Chris
  • New Phytologist, Vol. 213, Issue 1
  • DOI: 10.1111/nph.14101

The Sequence Alignment/Map format and SAMtools
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