Abstract
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.
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