Genome-wide association study (GWAS) was performed for 16 agronomic traits including nitrogen use efficiency (NUE) and yield-related components using a panel of 190 mainly japonica rice varieties and a set of 38 390 single nucleotide polymorphism (SNP) markers. This panel was evaluated under rainfed upland conditions in Madagascar in two consecutive cropping seasons with two contrasted nitrogen input levels. Using another set of five grain traits, we identified previously known genes (GW5, GS3, Awn1 and Glabrous1), thus validating the pertinence and accuracy of our datasets for GWAS. A total of 369 significant associations were detected between SNPs and agronomic traits, gathered into 46 distinct haplotype groups and 28 isolated markers. Few association signals were identified for the complex quantitative trait NUE, however, larger number of quantitative trait loci (QTLs) were detected for its component traits, with 10 and 2 association signals for nitrogen utilization efficiency and nitrogen uptake efficiency, respectively. Several detected association signals co-localized with genes involved in nitrogen transport or nitrogen remobilization within 100 kb. The present study thus confirmed the potential of GWAS to identify candidate genes and new loci associated with agronomic traits. However, because of the quantitative and complex nature of NUE-related traits, GWAS might have not captured a large number of QTLs with limited effects.

使用一组 190 个主要粳稻品种和一组 38 390 个单核苷酸多态性 (SNP) 标记对 16 个农艺性状进行全基因组关联研究 (GWAS)，包括氮利用效率 (NUE) 和产量相关成分。该小组在马达加斯加的雨养高地条件下在两个连续的作物季节进行了评估，其中有两种对比的氮输入水平。使用另一套粒形性状，我们确定了先前已知基因（GW5，GS3，Awn1和Glabrous1)，从而验证了我们的 GWAS 数据集的相关性和准确性。在 SNP 和农艺性状之间总共检测到 369 个显着关联，这些关联被收集到 46 个不同的单倍型组和 28 个分离的标记中。复杂数量性状NUE的关联信号很少，但其组成性状检测到大量数量性状基因座（QTL），氮利用效率和氮吸收效率分别有10个和2个关联信号。几个检测到的关联信号与 100 年内参与氮转运或氮再动员的基因共定位 KB。因此，本研究证实了 GWAS 在识别与农艺性状相关的候选基因和新位点方面的潜力。然而，由于 NUE 相关性状的数量性和复杂性，GWAS 可能没有捕获大量效果有限的 QTL。