Identification of genomic regions associated with agronomic and biofortification traits in DH populations of rice

Abstract

Rice provides energy and nutrition to more than half of the world’s population. Breeding rice varieties with the increased levels of bioavailable micronutrients is one of the most sustainable approaches to tackle micronutrient malnutrition. So, high zinc and iron content in the grain are primary targets in rice biofortification breeding. In this study, we conducted QTL mapping using doubled haploid (DH) populations, PSBRc82 x Joryeongbyeo and PSBRc82 x IR69428, phenotyped for agronomic traits and micronutrients during two growing seasons and using genotypic information from analysis with the 6K SNP chip. A number of DH lines were identified as having high grain Zn and Fe content in polished rice. Importantly, we identified 20 QTLs for agronomic traits and 59 QTLs for a number of biofortification traits. Of the 79 QTLs, 12 were large-effect QTLs (>25% PVE), nine QTLs were consistent across seasons in either population, and one QTL was identified in both populations. Moreover, at least two QTLs were clustered in defined regions of chromosomes 1, 2, 3, 4, 5, 7 and 9. Eight epistatic interactions were detected for Cu, Mg, Na, and Zn in population 1. Furthermore, we identified several candidate genes near QTLs for grain Zn (OsNRAMP, OsNAS, OsZIP, OsYSL, OsFER, and OsZIFL family) and grain yield (OsSPL14 and OsSPL16). These new QTLs and candidate genes help to further elucidate the genetic basis for grain micronutrient concentration, and may prove useful for marker assisted breeding for this important trait.

Genetic Analysis of Agronomic Traits and Grain Iron and Zinc Concentrations in a Doubled Haploid Population of Rice (Oryza sativa L.)

“…Identification of new donors for agronomic, yield and mineral nutrient traits, dissecting their genetic basis and using them to diversify the breeding population is a continuous process in developing high-yielding and nutritious rice varieties [15][16][17] . Several QTLs and genes have been identified and successfully used in rice improvement.…”

Analysis of QTL responsible for grain iron and zinc content in doubled haploid lines of rice (Oryza sativa) derived from an intra‐japonica cross

“…Grain iron and zinc contents are positively correlated (Anandan, Rajiv, Eswaran, & Prakash, ; Descalsota et al, ; Descalsota‐Empleo, Amparado, et al, ; Dixit et al, ; Inabangan‐Asilo et al, ; Stangoulis et al, ; Swamy, Descalsota, et al, ; Xu et al, ). Similarly, in this work, grain iron and zinc contents were positively correlated and presented similar correlations with other traits.…”

“…Zhang et al () identified QTL for milled grain iron and zinc contents on chromosomes 1 and 7 in 698 germplasm comprising indica and japonica subsets. Swamy, Descalsota, et al () identified one QTL for iron on chromosome 4 and QTL for zinc on chromosomes 2 and 11 in DH populations from crosses between PSBRc82 and Joryeongbyeo and between PSBRc82 and IR69428. Furthermore, Swamy, Kaladhar, et al () reported that QTL for iron and zinc contents are closely colocated in two BC 2 F 3 mapping populations developed by crossing the indica cultivar 'Swarna' with two different accessions of O. nivara .…”

“…QTL for rice grain iron and zinc contents have been mapped by using different biparental mapping populations originating from crosses between indica and japonica varieties and crosses involving wild rice relatives. Mapping populations include F 2 progeny (Kumar, Jain, & Jain, ), recombinant inbred lines (RILs, Anuradha et al, ; Zhang et al, ), doubled haploid (DH) lines (Stangoulis, Huynh, Welch, Choi, & Graham, ; Swamy, Descalsota, et al, , Descolta‐Empleo et al ), backcross inbred lines (BILs, Garcia‐Oliveira, Tan, Fu, & Sun, ) and introgression lines (Xu, Li, Yang, & Xu, ). DH lines are favoured as QTL mapping populations because their true breeding nature and convenient production enable accurate phenotyping with replications.…”

“…DH lines are favoured as QTL mapping populations because their true breeding nature and convenient production enable accurate phenotyping with replications. Moreover, they are faster to develop than other mapping populations, can be easily evaluated across years and locations, and feature limited genetic background noise (Murovec & Bohanec, ; Swamy, Descalsota, et al, ). However, studies that detected iron‐ and zinc‐related QTL in populations derived from intra‐ japonica crosses are rare, and the QTL that are involved in the control of differences among the grain iron and zinc contents of closely related japonica cultivars remain unclear.…”