Genomic regions and candidate genes affect root anatomical traits in diverse rice accessions

Root anatomical traits show significant variation among rice, Oryza sativa L., genotypes and are of interest for improving adaptation to a variety of edaphic, hydrological and nutritional environments in which rice is grown. However, they are difficult to measure and the genetic controls of these traits are not well understood in rice. We conducted genome-wide association (GWA) analyses using moderate- and high-density SNP panels on a diverse rice population to identify genomic regions and candidate genes that control root anatomical traits. We identified 28 genomic regions for metaxylem vessel area and number, root cross-sectional area, stele area, and aerenchyma area. One genomic region associated with metaxylem vessel number and two regions associated with three root thickness-related traits, stele area, root cross-sectional area and metaxylem vessel area, were supported by chromosome-specific GWA using a high-density SNP panel and are regarded as highly significant regions controlling trait variation. Candidate genes in these regions were related to cell differentiation, elongation and division, and secondary cell wall formation. For genomic regions identified in the indica subpopulation, haplotype variation and root anatomical phenotypes were associated with geographic distributions of the accessions, notably the presence of alternate alleles conferring larger diameter roots, stele, and metaxylem vessels in accessions from the indica 2 and indica 3 subgroups originating largely in south and southeast Asia. The identification of genomic regions and candidate genes related to root anatomical traits in a diverse panel of rice varieties deepens our understanding of trait variation and genetic architecture and facilitates the incorporation of favorable alleles into breeding populations. Key message Genomic regions and candidate genes associated with root anatomical traits were identified in Oryza sativa using genome-wide association analyses.