Identification of QTLs associated with agronomic performance under nitrogen-deficient conditions using chromosome segment substitution lines of a wild rice relative, Oryza rufipogon

Improved root system architecture can enhance agronomic performance by increasing water and nitrogen (N) acquisition efficiency. However, little is known about interaction between root system architecture and agronomic performance under field environments. To gain a better understanding about the genetic basis of these relationships, we evaluated a set of chromosome segment substitution lines (CSSLs) derived from crosses between a tropical japonica rice cultivar ‘Curinga’ and a wild species Oryza rufipogon accession IRGC105491. Root system architectural traits were investigated using the CSSLs at 40 days old seedlings using the root basket method under hydroponic conditions, and agronomic performances were also tested under field conditions with different N treatments. Agronomic performances were computed as the ratio of a trait value under low to high N treatments, including grain yield and biomass yield as nitrogen-deficiency tolerance (NDT) traits. Root architecture and NDT trait QTLs were mapped using 238 SNP marker loci. A total of 13 QTLs for root system architectural, NDT and morpho-physiological traits were identified on chromosomes 1, 3, 4, 5, 7, 8, 9, 10 and 12. Interestingly, a QTL for deeper root number was identified the region of SNP markers between id1012330 and id1021697 on chromosome 1 under hydroponic conditions overlapped with a QTL for NDT trait of relative grain yield (qRGY1). These results suggest that deeper root trait is helpful to maintain grain yield under nitrogen-deficient conditions. The QTL associated root architecture could potentially be used in future rice-breeding efforts to increase agronomic performance under nitrogen-deficient conditions

A universal core genetic map for rice

To facilitate the creation of easily comparable, low-resolution genetic maps with evenly distributed markers in rice (Oryza sativa L.), we conceived of and developed a Universal Core Genetic Map (UCGM). With this aim, we derived a set of 165 anchors, representing clusters of three microsatellite or simple sequence repeat (SSR) markers arranged into non-recombining groups. Each anchor consists of at least three, closely linked SSRs, located within a distance below the genetic resolution provided by common, segregating populations (<500 individuals). We chose anchors that were evenly distributed across the rice chromosomes, with spacing between 2 and 3.5 Mbp (except in the telomeric regions, where spacing was 1.5 Mbp). Anchor selection was performed using in silico tools and data: the O. sativa cv. Nipponbare rice genome sequence, the CHARM tool, information from the Gramene database and the OrygenesDB database. Sixteen AA-genome accessions of the Oryza genus were used to evaluate polymorphisms for the selected markers, including accessions from O. sativa, O. glaberrima, O. barthii, O. rufipogon, O. glumaepatula and O. meridionalis. High levels of polymorphism were found for the tested O. sativa × O. glaberrima or O. sativa × wild rice combinations. We developed Paddy Map, a simple database that is helpful in selecting optimal sets of polymorphic SSRs for any cross that involves the previously mentioned species. Validation of the UCGM was done by using it to develop three interspecific genetic maps and by comparing genetic SSR locations with their physical positions on the rice pseudomolecules. In this study, we demonstrate that the UCGM is a useful tool for the rice genetics and breeding community, especially in strategies based on interspecific hybridisation