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Title: Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice

In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.
Authors:
 [1] ;  [2] ;  [3] ;  [4] ;  [1] ;  [2] ;  [2] ;  [2] ;  [5] ;  [6] ;  [2] ;  [1] ;  [1]
  1. Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management
  2. International Rice Research Inst. (IRRI), Los Banos (Phillippines)
  3. Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management; Duke Univ., Durham, NC (United States). Dept. of Biology
  4. Univ. of Texas, Austin, TX (United States). Dept. of Integrative Biology
  5. Kansas State Univ., Manhattan, KS (United States). Dept. of Plant Pathology
  6. Colorado State Univ., Fort Collins, CO (United States). Dept. of Biology
Publication Date:
Grant/Contract Number:
FG02-08ER64629
Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 7; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Research Org:
Colorado State Univ., Fort Collins, CO (United States)
Sponsoring Org:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; agriculture genetics; plant breeding
OSTI Identifier:
1366463

Tanger, Paul, Klassen, Stephen, Mojica, Julius P., Lovell, John T., Moyers, Brook T., Baraoidan, Marietta, Naredo, Maria Elizabeth B., McNally, Kenneth L., Poland, Jesse, Bush, Daniel R., Leung, Hei, Leach, Jan E., and McKay, John K.. Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. United States: N. p., Web. doi:10.1038/srep42839.
Tanger, Paul, Klassen, Stephen, Mojica, Julius P., Lovell, John T., Moyers, Brook T., Baraoidan, Marietta, Naredo, Maria Elizabeth B., McNally, Kenneth L., Poland, Jesse, Bush, Daniel R., Leung, Hei, Leach, Jan E., & McKay, John K.. Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice. United States. doi:10.1038/srep42839.
Tanger, Paul, Klassen, Stephen, Mojica, Julius P., Lovell, John T., Moyers, Brook T., Baraoidan, Marietta, Naredo, Maria Elizabeth B., McNally, Kenneth L., Poland, Jesse, Bush, Daniel R., Leung, Hei, Leach, Jan E., and McKay, John K.. 2017. "Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice". United States. doi:10.1038/srep42839. https://www.osti.gov/servlets/purl/1366463.
@article{osti_1366463,
title = {Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice},
author = {Tanger, Paul and Klassen, Stephen and Mojica, Julius P. and Lovell, John T. and Moyers, Brook T. and Baraoidan, Marietta and Naredo, Maria Elizabeth B. and McNally, Kenneth L. and Poland, Jesse and Bush, Daniel R. and Leung, Hei and Leach, Jan E. and McKay, John K.},
abstractNote = {In order to ensure food security in the face of population growth, decreasing water and land for agriculture, and increasing climate variability, crop yields must increase faster than the current rates. Increased yields will require implementing novel approaches in genetic discovery and breeding. We demonstrate the potential of field-based high throughput phenotyping (HTP) on a large recombinant population of rice to identify genetic variation underlying important traits. We find that detecting quantitative trait loci (QTL) with HTP phenotyping is as accurate and effective as traditional labor- intensive measures of flowering time, height, biomass, grain yield, and harvest index. Furthermore, genetic mapping in this population, derived from a cross of an modern cultivar (IR64) with a landrace (Aswina), identified four alleles with negative effect on grain yield that are fixed in IR64, demonstrating the potential for HTP of large populations as a strategy for the second green revolution.},
doi = {10.1038/srep42839},
journal = {Scientific Reports},
number = ,
volume = 7,
place = {United States},
year = {2017},
month = {2}
}