| Autor: |
Zan eWang, Haiping eQiang, Haiming eZhao, Ruixuan eXu, Zhengli eZhang, Hongwen eGao, Xuemin eWang, Yingjun eZhang, Guibo eLiu |
| Jazyk: |
angličtina |
| Rok vydání: |
2016 |
| Předmět: |
|
| Zdroj: |
Frontiers in Plant Science, Vol 7 (2016) |
| Druh dokumentu: |
article |
| ISSN: |
1664-462X |
| DOI: |
10.3389/fpls.2016.00331 |
| Popis: |
Association mapping is a powerful approach for exploring the molecular genetic basis of complex quantitative traits. An alfalfa (Medicago sativa) association panel comprised of 336 genotypes from 75 alfalfa accessions represented by four to eight genotypes for each accession. Each genotype was genotyped using 85 simple sequence repeat (SSR) markers and phenotyped for five fiber-related traits in four different environments. A model-based structure analysis was used to group all genotypes into two groups. Most of the genotypes have a low relative kinship (less than 0.3), suggesting population stratification not be an issue for association analysis. Generally, the Q + K model exhibited the best performance to eliminate the false associated positives. In total, 124 marker-trait associations were predicted (p < 0.005). Among these, eight associations were predicted in two environments repeatedly and 20 markers were predicted to be associated with multiple traits. These trait-associated markers will greatly help marker-assisted breeding programs to improve fiber-related quality traits in alfalfa. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
|
