Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice
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. Here we dem...
| Autores principales: | , , , , , , , , , , , , |
|---|---|
| Formato: | Journal Article |
| Lenguaje: | Inglés |
| Publicado: |
Springer
2017
|
| Acceso en línea: | https://hdl.handle.net/10568/165095 |
| _version_ | 1855542989833633792 |
|---|---|
| author | 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. |
| author_browse | Baraoidan, Marietta Bush, Daniel R. Klassen, Stephen Leach, Jan E. Leung, Hei Lovell, John T. McKay, John K. McNally, Kenneth L. Mojica, Julius P. Moyers, Brook T. Naredo, Maria Elizabeth B. Poland, Jesse Tanger, Paul |
| author_facet | 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. |
| author_sort | Tanger, Paul |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | 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. Here 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. 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. |
| format | Journal Article |
| id | CGSpace165095 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Springer |
| publisherStr | Springer |
| record_format | dspace |
| spelling | CGSpace1650952024-12-19T14:13:49Z Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice 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. 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. Here 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. 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. 2017-02-21 2024-12-19T12:54:42Z 2024-12-19T12:54:42Z Journal Article https://hdl.handle.net/10568/165095 en Open Access Springer 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. Sci Rep, Volume 7, no. 1 |
| spellingShingle | 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 |
| title | Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| title_full | Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| title_fullStr | Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| title_full_unstemmed | Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| title_short | Field-based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| title_sort | field based high throughput phenotyping rapidly identifies genomic regions controlling yield components in rice |
| url | https://hdl.handle.net/10568/165095 |
| work_keys_str_mv | AT tangerpaul fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT klassenstephen fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT mojicajuliusp fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT lovelljohnt fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT moyersbrookt fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT baraoidanmarietta fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT naredomariaelizabethb fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT mcnallykennethl fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT polandjesse fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT bushdanielr fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT leunghei fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT leachjane fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice AT mckayjohnk fieldbasedhighthroughputphenotypingrapidlyidentifiesgenomicregionscontrollingyieldcomponentsinrice |