| Autor: |
Islam ASMF; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA., Mustahsan W; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA.; Department of Agronomy, Kansas State University, Manhattan, KS 66506, USA., Tabien R; Texas A&M AgriLife Beaumont Research Center, Beaumont, TX 77713, USA., Awika JM; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA., Septiningsih EM; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA., Thomson MJ; Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843, USA. |
| Abstrakt: |
Mineral malnutrition is a major problem in many rice-consuming countries. It is essential to know the genetic mechanisms of accumulation of mineral elements in the rice grain to provide future solutions for this issue. This study was conducted to identify the genetic basis of six mineral elements (Cu, Fe, K, Mg, Mn, and Zn) by using three models for single-locus and six models for multi-locus analysis of a genome-wide association study (GWAS) using 174 diverse rice accessions and 6565 SNP markers. To declare a SNP as significant, -log10(P) ≥ 3.0 and 15% FDR significance cut-off values were used for single-locus models, while LOD ≥ 3.0 was used for multi-locus models. Using these criteria, 147 SNPs were detected by one or two GWAS methods at -log10(P) ≥ 3.0, 48 of which met the 15% FDR significance cut-off value. Single-locus models outperformed multi-locus models before applying multi-test correction, but once applied, multi-locus models performed better. While 14 (~29%) of the identified quantitative trait loci (QTLs) after multiple test correction co-located with previously reported genes/QTLs and marker associations, another 34 trait-associated SNPs were novel. After mining genes within 250 kb of the 48 significant SNP loci, in silico and gene enrichment analyses were conducted to predict their potential functions. These shortlisted genes with their functions could guide future experimental validation, helping us to understand the complex molecular mechanisms controlling rice grain mineral elements. |
