Association mapping (AM) is an approach that accounts for thousands of polymorphisms to evaluate the effects of quantitative trait loci (QTL). It is an important instrument for identification of alleles and new genes as well as dissection of complex characters. AM is more advantageous than linkage analysis due to the comparatively high-resolution provided, which is based on the structure of linkage disequilibrium (LD). Marker density, population, sample sizes and population structure are among the critical factors that should be considered when AM is used. It is necessary to note that, the choice of germplasm, genotypic and phenotypic data quality, the use of appropriate statistical analysis for marker-phenotype association detections and verifications are key to association analysis. Great potentials to enhance crop genetic improvement are offered by AM. However, to understand its application, extensive research is needed, such as improvements in computational and statistical methods and its integration with gene annotation data or functional analysis. Statistical apparatuses that are user-friendly and genetic resources are also needed and must be enhanced. Rare allele/variant analysis is an important area to be considered to enhance AM studies. Joint linkage association mapping has now been proposed to improve linkage-based QTL mapping and AM limitations. In the future, new candidate genes and QTL can be easily identified if genome-wide association studies (GWAS) are combined with functional genomics. As such, this review describes association mapping, its utilization in plant breeding, limitations as well as advantages over linkage mapping.

中文翻译：

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植物育种中关联图谱的原理和方法

关联映射（AM）是一种解决数千种多态性以评估定量性状基因座（QTL）效果的方法。它是鉴定等位基因和新基因以及解剖复杂特征的重要工具。由于基于链接不平衡（LD）的结构提供了相对较高的分辨率，因此AM比链接分析更具优势。标记密度，种群，样本量和种群结构是使用AM时应考虑的关键因素。需要注意的是，种质，基因型和表型数据质量的选择，对标记-表型关联检测和验证使用适当的统计分析是关联分析的关键。AM提供了增强作物遗传改良的巨大潜力。但是，要了解其应用，需要进行广泛的研究，例如在计算和统计方法上的改进以及与基因注释数据或功能分析的集成。还需要用户友好和遗传资源的统计设备，并且必须加以加强。罕见的等位基因/变异分析是增强AM研究的重要领域。现在已经提出了联合链接关联映射以改善基于链接的QTL映射和AM限制。如果将来将全基因组关联研究（GWAS）与功能基因组学结合起来，则可以轻松地识别出新的候选基因和QTL。因此，本评论介绍了关联映射，其在植物育种中的利用，