This study characterized Pokkali-derived quantitative trait loci (QTLs) for seedling stage salinity tolerance in preparation for use in marker-assisted breeding. An analysis of 100 SSR markers on 140 IR29/Pokkali recombinant inbred lines (RILs) confirmed the location of the Saltol QTL on chromosome 1 and identified additional QTLs associated with tolerance. Analysis of a series of backcross lines and near-isogenic lines (NILs) developed to better characterize the effect of the Saltol locus revealed that Saltol mainly acted to control shoot Na + /K + homeostasis. Multiple QTLs were required to acquire a high level of tolerance. Unexpectedly, multiple Pokkali alleles at Saltol were detected within the RIL population and between backcross lines, and representative lines were compared with seven Pokkali accessions to better characterize this allelic variation. Thus, while the Saltol locus presents a complex scenario, it provides an opportunity for markerassisted backcrossing to improve salt tolerance of popular varieties followed by targeting multiple loci through QTL pyramiding for areas with higher salt stress.

BackgroundThis article describes the development of Multi-parent Advanced Generation Inter-Cross populations (MAGIC) in rice and discusses potential applications for mapping quantitative trait loci (QTLs) and for rice varietal development. We have developed 4 multi-parent populations: indica MAGIC (8 indica parents); MAGIC plus (8 indica parents with two additional rounds of 8-way F1 inter-crossing); japonica MAGIC (8 japonica parents); and Global MAGIC (16 parents – 8 indica and 8 japonica). The parents used in creating these populations are improved varieties with desirable traits for biotic and abiotic stress tolerance, yield, and grain quality. The purpose is to fine map QTLs for multiple traits and to directly and indirectly use the highly recombined lines in breeding programs. These MAGIC populations provide a useful germplasm resource with diverse allelic combinations to be exploited by the rice community.ResultsThe indica MAGIC population is the most advanced of the MAGIC populations developed thus far and comprises 1328 lines produced by single seed descent (SSD). At the S4 stage of SSD a subset (200 lines) of this population was genotyped using a genotyping-by-sequencing (GBS) approach and was phenotyped for multiple traits, including: blast and bacterial blight resistance, salinity and submergence tolerance, and grain quality. Genome-wide association mapping identified several known major genes and QTLs including Sub1 associated with submergence tolerance and Xa4 and xa5 associated with resistance to bacterial blight. Moreover, the genome-wide association study (GWAS) results also identified potentially novel loci associated with essential traits for rice improvement.ConclusionThe MAGIC populations serve a dual purpose: permanent mapping populations for precise QTL mapping and for direct and indirect use in variety development. Unlike a set of naturally diverse germplasm, this population is tailor-made for breeders with a combination of useful traits derived from multiple elite breeding lines. The MAGIC populations also present opportunities for studying the interactions of genome introgressions and chromosomal recombination.Electronic supplementary materialThe online version of this article (doi:10.1186/1939-8433-6-11) contains supplementary material, which is available to authorized users.

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In 1992 the International Rice Research Institute (IRRI) began to examine the effect of certain soil characteristics on the iron content of rice grains. As part of the Consultative Group for International Agricultural Research (CGIAR) Micronutrients Project, this effort was expanded in 1995 to include analysis of both iron and zinc, in collaboration with the University of Adelaide in Australia. Since then, germplasm screening has shown large genetic variation for iron and zinc concentrations in brown rice. Common cultivars contain about 12 mg of iron and 25 mg of zinc per kilogram. Some traditional varieties have double these amounts. Genetic-byenvironmental interactions are sufficiently moderate that breeding for higher iron and zinc content is considered worthwhile. The next major research step will be to further study the genetics of trace mineral accumulation in the grain to determine the best selection techniques for use in breeding. High iron and zinc traits can be combined with improved agronomic traits. This has already been demonstrated in the serendipitous discovery in the IRRI testing programme of an aromatic variety (IR68144-3B-2-2-3) that has a high concentration of grain iron, about 21 mg/kg in brown rice. This elite line has good tolerance to rice tungro virus and to mineraldeficient soils and has excellent grain qualities. The yields are about 10% below those of IR72, but in partial compensation, maturity is earlier. After 15 minutes of polishing, IR68144-4B-2-2-3 had about 80% more iron than IR64, a widely grown commercial variety. It remains to be shown that this extra iron can improve the iron status of iron-deficient human subjects. A human feeding trial is being planned.

African rice (Oryza glaberrima Steud.) is a cereal crop species closely related to Asian rice (Oryza sativa L.) but was independently domesticated in West Africa ∼3,000 years ago. African rice is rarely grown outside sub-Saharan Africa but is of global interest because of its tolerance to abiotic stresses. Here we describe a map of 2.32 million SNPs of African rice from whole-genome resequencing of 93 landraces. Population genomic analysis shows a population bottleneck in this species that began ∼13,000-15,000 years ago with effective population size reaching its minimum value ∼3,500 years ago, suggesting a protracted period of population size reduction likely commencing with predomestication management and/or cultivation. Genome-wide association studies (GWAS) for six salt tolerance traits identify 11 significant loci, 4 of which are within ∼300 kb of genomic regions that possess signatures of positive selection, suggesting adaptive geographical divergence for salt tolerance in this species.

Iron deficiency is endemic in much of the world, and food system-based approaches to eradication may be viable with new plant breeding approaches to increase the micronutrient content in staple crops. It is thought that conventional plant breeding approaches provide varieties of rice that have 400-500% higher iron contents than varieties commonly consumed in much of Asia. The efficacy of consuming high-iron rice was tested during a 9-mo feeding trial with a double-blind dietary intervention in 192 religious sisters living in 10 convents around metro Manila, the Philippines. Subjects were randomly assigned to consume either high-iron rice (3.21 mg/kg Fe) or a local variety of control rice (0.57 mg/kg Fe), and daily food consumption was monitored. The high-iron rice contributed 1.79 mg Fe/d to the diet in contrast to 0.37 mg Fe/d from the control rice. The 17% difference in total dietary iron consumption compared with controls (10.16 +/- 1.06 vs. 8.44 +/- 1.82 mg/d) resulted in a modest increase in serum ferritin (P = 0.10) and total body iron (P = 0.06) and no increase in hemoglobin (P = 0.59). However, the response was greater in nonanemic subjects for ferritin (P = 0.02) and body iron (P = 0.05), representing a 20% increase after controlling for baseline values and daily rice consumption. The greatest improvements in iron status were seen in those nonanemic women who had the lowest baseline iron status and in those who consumed the most iron from rice. Consumption of biofortified rice, without any other changes in diet, is efficacious in improving iron stores of women with iron-poor diets in the developing world.

BackgroundFe toxicity occurs in lowland rice production due to excess ferrous iron (Fe2+) formation in reduced soils. To contribute to the breeding for tolerance to Fe toxicity in rice, we determined quantitative trait loci (QTL) by screening two different bi-parental mapping populations under iron pulse stresses (1,000 mg L−1 = 17.9 mM Fe2+ for 5 days) in hydroponic solution, followed by experiments with selected lines to determine whether QTLs were associated with iron exclusion (i.e. root based mechanisms), or iron inclusion (i.e. shoot-based mechanisms).ResultsIn an IR29/Pokkali F8 recombinant inbred population, 7 QTLs were detected for leaf bronzing score on chromosome 1, 2, 4, 7 and 12, respectively, individually explaining 9.2-18.7% of the phenotypic variation. Two tolerant recombinant inbred lines carrying putative QTLs were selected for further experiments. Based on Fe uptake into the shoot, the dominant tolerance mechanism of the tolerant line FL510 was determined to be exclusion with its root architecture being conducive to air transport and thus the ability to oxidize Fe2+ in rhizosphere. In line FL483, the iron tolerance was related mainly to shoot-based mechanisms (tolerant inclusion mechanism). In a Nipponbare/Kasalath/Nipponbare backcross inbred population, 3 QTLs were mapped on chromosomes 1, 3 and 8, respectively. These QTLs explained 11.6-18.6% of the total phenotypic variation. The effect of QTLs on chromosome 1 and 3 were confirmed by using chromosome segment substitution lines (SL), carrying Kasalath introgressions in the genetic background on Nipponbare. The Fe uptake in shoots of substitution lines suggests that the effect of the QTL on chromosome 1 was associated with shoot tolerance while the QTL on chromosome 3 was associated with iron exclusion.ConclusionTolerance of certain genotypes were classified into shoot- and root- based mechanisms. Comparing our findings with previously reported QTLs for iron toxicity tolerance, we identified co-localization for some QTLs in both pluse and chronic stresses, especially on chromosome 1.

Environmental gene regulatory influence networks (EGRINs) coordinate the timing and rate of gene expression in response to environmental signals. EGRINs encompass many layers of regulation, which culminate in changes in accumulated transcript levels. Here, we inferred EGRINs for the response of five tropical Asian rice (Oryza sativa) cultivars to high temperatures, water deficit, and agricultural field conditions by systematically integrating time-series transcriptome data, patterns of nucleosome-free chromatin, and the occurrence of known cis-regulatory elements. First, we identified 5447 putative target genes for 445 transcription factors (TFs) by connecting TFs with genes harboring known cis-regulatory motifs in nucleosomefree regions proximal to their transcriptional start sites. We then used network component analysis to estimate the regulatory activity for each TF based on the expression of its putative target genes. Finally, we inferred an EGRIN using the estimated transcription factor activity (TFA) as the regulator. The EGRINs include regulatory interactions between 4052 target genes regulated by 113 TFs. We resolved distinct regulatory roles for members of the heat shock factor family, including a putative regulatory connection between abiotic stress and the circadian clock. TFA estimation using network component analysis is an effective way of incorporating multiple genome-scale measurements into network inference.