Title |
qDTY12.1: a locus with a consistent effect on grain yield under drought in rice
|
---|---|
Published in |
BMC Genomic Data, February 2013
|
DOI | 10.1186/1471-2156-14-12 |
Pubmed ID | |
Authors |
Krishna Kumar Mishra, Prashant Vikram, Ram Baran Yadaw, BP Mallikarjuna Swamy, Shalabh Dixit, Ma Teresa Sta Cruz, Paul Maturan, Shailesh Marker, Arvind Kumar |
Abstract |
Selection for grain yield under drought is an efficient criterion for improving the drought tolerance of rice. Recently, some drought-tolerant rice varieties have been developed using this selection criterion and successfully released for cultivation in drought-prone target environments. The process can be made more efficient and rapid through marker-assisted breeding, a well-known fast-track approach in crop improvement. QTLs have been identified for grain yield under drought with large effects against drought-susceptible varieties. Most of the identified QTLs show large QTL × environment or QTL × genetic background interactions. The development of mapping populations in the background of popular high-yielding varieties, screening across environments, including the target environments, and the identification of QTLs with a consistent effect across environments can be a suitable alternative marker-assisted breeding strategy. An IR74371-46-1-1 × Sabitri backcross inbred line population was screened for reproductive-stage drought stress at the International Rice Research Institute, Philippines, and Regional Agricultural Research Station, Nepalgunj, Nepal, in the dry and wet seasons of 2011, respectively. A bulk segregant analysis approach was used to identify markers associated with high grain yield under drought. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 2 | 1% |
Cuba | 1 | <1% |
Netherlands | 1 | <1% |
Benin | 1 | <1% |
Philippines | 1 | <1% |
Unknown | 142 | 96% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 50 | 34% |
Researcher | 29 | 20% |
Student > Master | 12 | 8% |
Student > Doctoral Student | 7 | 5% |
Student > Bachelor | 7 | 5% |
Other | 24 | 16% |
Unknown | 19 | 13% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 101 | 68% |
Biochemistry, Genetics and Molecular Biology | 10 | 7% |
Engineering | 3 | 2% |
Social Sciences | 2 | 1% |
Economics, Econometrics and Finance | 1 | <1% |
Other | 7 | 5% |
Unknown | 24 | 16% |