Genome-Wide Association Study of Grain Quality Traits in Rice Detected Genomic Regions of High-Quality Rice for Increasing Rice Consumption

Abstract

This review describes the current status of genome-wide association study (GWAS) of the major cereal crop in rice (Oryza sativa L.) concentrate on the rice quality traits that related to the consumers demand. These rice quality traits that also become major concern in the rice industry and determine the rice consumption value, including grain length, grain width, grain length to width ratio, grain weight, amylose content, protein content, as well as gelatinization temperature. One of the primary objective in the rice breeding program is to increase rice grain quality based on the consumption demands. Rice grain quality preferences influenced by countries and cultures. genome-wide association study has an important role in increasing the rice quality based on the consumers demand because this method identified many crucial genomic regions of important traits. genome-wide association study has many advantages correlated with reducing genotyping cost and research time, increasing mapping resolution and larger allele number. Meanwhile, genome-wide association study has two main limitations related to population size and the number of markers. There are many software packages for data analysis in genome-wide association study. The most commonly software that was used in genome-wide association study especially in these crops is TASSEL because frequently updated. Recently, many research papers concentrated on genome-wide association study in rice quality traits. A total of 121, 138, 81, 60, 18, 6, and 5 QTLs for grain length, grain width, grain length to width ratio, grain weight, amylose content, protein content, and gelatinization temperature; respectively have been identified by genome-wide association study in different rice populations for almost twelve years (2010 until 2022). genome-wide association study analysis accelerated identification of genetic regions, candidate genes within these genomic regions and their metabolomic analysis correlated to the rice quality traits. Developing high-quality rice varieties that meet consumer preferences and increasing global population demands can be accelerated by genome-wide association study.