| Title |
Association Mapping of Yield and Yield-related Traits Under Reproductive Stage Drought Stress in Rice (Oryza sativa L.)
|
|---|---|
| Published in |
Rice, May 2017
|
| DOI | 10.1186/s12284-017-0161-6 |
| Pubmed ID | |
| Authors |
B. P. Mallikarjuna Swamy, Noraziyah Abd Aziz Shamsudin, Site Noorzuraini Abd Rahman, Ramil Mauleon, Wickneswari Ratnam, Ma. Teressa Sta. Cruz, Arvind Kumar |
| Abstract |
The identification and introgression of major-effect QTLs for grain yield under drought are some of the best and well-proven approaches for improving the drought tolerance of rice varieties. In the present study, we characterized Malaysian rice germplasm for yield and yield-related traits and identified significant trait marker associations by structured association mapping. The drought screening was successful in screening germplasm with a yield reduction of up to 60% and heritability for grain yield under drought was up to 78%. There was a wider phenotypic and molecular diversity within the panel, indicating the suitability of the population for quantitative trait loci (QTL) mapping. Structure analyses clearly grouped the accessions into three subgroups with admixtures. Linkage disequilibrium (LD) analysis revealed that LD decreased with an increase in distance between marker pairs and the LD decay varied from 5-20 cM. The Mixed Linear model-based structured association mapping identified 80 marker trait associations (MTA) for grain yield (GY), plant height (PH) and days to flowering (DTF). Seven MTA were identified for GY under drought stress, four of these MTA were consistently identified in at least two of the three analyses. Most of these MTA identified were on chromosomes 2, 5, 10, 11 and 12, and their phenotypic variance (PV) varied from 5% to 19%. The in silico analysis of drought QTL regions revealed the association of several drought-responsive genes conferring drought tolerance. The major-effect QTLs are useful in marker-assisted QTL pyramiding to improve drought tolerance. The results have clearly shown that structured association mapping is one of the feasible options to identify major-effect QTLs for drought tolerance-related traits in rice. |
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 134 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 23 | 17% |
| Researcher | 18 | 13% |
| Student > Master | 12 | 9% |
| Student > Bachelor | 10 | 7% |
| Lecturer | 8 | 6% |
| Other | 20 | 15% |
| Unknown | 43 | 32% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 67 | 50% |
| Biochemistry, Genetics and Molecular Biology | 10 | 7% |
| Psychology | 2 | 1% |
| Unspecified | 1 | <1% |
| Nursing and Health Professions | 1 | <1% |
| Other | 6 | 4% |
| Unknown | 47 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 May 2017.
All research outputs
#20,421,487
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Outputs from Rice
#306
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Outputs of similar age
#273,097
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Outputs of similar age from Rice
#12
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