Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice
Abstract
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:
-
- Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management
- International Rice Research Inst. (IRRI), Los Banos (Phillippines)
- Colorado State Univ., Fort Collins, CO (United States). Bioagricultural Sciences and Pest Management; Duke Univ., Durham, NC (United States). Dept. of Biology
- Univ. of Texas, Austin, TX (United States). Dept. of Integrative Biology
- Kansas State Univ., Manhattan, KS (United States). Dept. of Plant Pathology
- Colorado State Univ., Fort Collins, CO (United States). Dept. of Biology
- Publication Date:
- Research Org.:
- Colorado State Univ., Fort Collins, CO (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC), Biological and Environmental Research (BER)
- OSTI Identifier:
- 1366463
- Grant/Contract Number:
- FG02-08ER64629
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Scientific Reports
- Additional Journal Information:
- Journal Volume: 7; Journal ID: ISSN 2045-2322
- Publisher:
- Nature Publishing Group
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; agriculture genetics; plant breeding
Citation Formats
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., 2017.
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. https://doi.org/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. Tue .
"Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice". United States. https://doi.org/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 = {Tue Feb 21 00:00:00 EST 2017},
month = {Tue Feb 21 00:00:00 EST 2017}
}
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Figures / Tables:
Figure 1: (A) Tractor based HTP platform with eight sets of canopy sensors mounted on a 24 m boom. (B) Experimental design: each horizontal bar represents a repeated planting cohort from sowing to harvest, with the range of plot heading dates (80% of plants flowered) represented by thicker bars. Verticalmore »
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Editorial: Plant Phenotyping and Phenomics for Plant Breeding
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- Lobos, Gustavo A.; Camargo, Anyela V.; del Pozo, Alejandro
- Frontiers in Plant Science, Vol. 8
Intercomparison of Unmanned Aerial Vehicle and Ground-Based Narrow Band Spectrometers Applied to Crop Trait Monitoring in Organic Potato Production
journal, June 2017
- Domingues Franceschini, Marston; Bartholomeus, Harm; van Apeldoorn, Dirk
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Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.