No abstract

Nutrient supplies from indigenous sources (IS) can be estimated by measuring plant nutrient uptake in nutrient omission plots. On‐farm experiments were conducted in irrigated rice (Oryza sativa L.) domains of Asia to evaluate relationships of plant N, P, and K uptake with soil tests or grain yield measured in N, P, and K omission (0‐N, 0‐P, and 0‐K, respectively) plots and to develop guidelines for the use of omission plots in site‐specific management. Relationships between grain yield or nutrient accumulation and soil tests were scattered. Only 17% of the variation in plant N uptake in 0‐N plots was explained by total soil organic C. Extractable Olsen P explained 34% of plant P uptake in 0‐P plots, whereas 1 M ammonium acetate K showed no common relationship with plant K uptake in 0‐K plots. With good calibration, indigenous supply of N (INS), P (IPS), and K (IKS) can be estimated from grain yields in omission plots with a precision of about ±5 to 10 kg N ha−1, ±2 to 3 kg P ha−1, and ±10 to 20 kg K ha−1, respectively. Sampling requirements for estimating domain‐specific IS values depend on the homogeneity of the domain of interest. For irrigated rice domains of about 100 to 200 km2, grain yield in omission plots should be measured in at least one high‐yielding season in about 10 farms to estimate the domain mean INS, IPS, and IKS. Future research should focus on developing geospatial techniques for delineating fertilizer recommendation domains based on biophysical and socioeconomic characteristics that determine yield potential, IS, and response to fertilizer.

The rapid progress in rice genotyping must be matched by advances in phenotyping. A better understanding of genetic variation in rice for drought response, root traits, and practical methods for studying them are needed. In this study, the OryzaSNP set (20 diverse genotypes that have been genotyped for SNP markers) was phenotyped in a range of field and container studies to study the diversity of rice root growth and response to drought. Of the root traits measured across more than 20 root experiments, root dry weight showed the most stable genotypic performance across studies. The environment (E) component had the strongest effect on yield and root traits. We identified genomic regions correlated with root dry weight, percent deep roots, maximum root depth, and grain yield based on a correlation analysis with the phenotypes and aus, indica, or japonica introgression regions using the SNP data. Two genomic regions were identified as hot spots in which root traits and grain yield were co-located; on chromosome 1 (39.7–40.7 Mb) and on chromosome 8 (20.3–21.9 Mb). Across experiments, the soil type/ growth medium showed more correlations with plant growth than the container dimensions. Although the correlations among studies and genetic co-location of root traits from a range of study systems points to their potential utility to represent responses in field studies, the best correlations were observed when the two setups had some similar properties. Due to the co-location of the identified genomic regions (from introgression block analysis) with QTL for a number of previously reported root and drought traits, these regions are good candidates for detailed characterization to contribute to understanding rice improvement for response to drought. This study also highlights the utility of characterizing a small set of 20 genotypes for root growth, drought response, and related genomic regions.

We produced 3000 doubled haploid (DH) lines through anther culture of 28 crosses involving indica and japónica rice {Oryza sativa L.) cultivars. Indica cultivars showed low anther culturability (1.2% callus induction) whereas yapon/ca cultivars had 20-fold higher (28.1%) anther culturability. A set of 121 and 124 DH lines was used for phenotypic and molecular analysis, respectively, generated from the japónica cultivar (IR69428) X indica variety (IR64). Significant variation was observed among DH lines for agronomic traits including Zn content. However, the phenotypic variance within each DH line was comparable with the mean phenotypic variance of the parents, suggesting no variation within DH line(s). A set of 209 simple sequence repeat (SSR) markers was selected to construct a linkage map with a total genetic distance of 2148.8 cM. Simple sequence repeat analysis showed 1:1 ratio of indica and japónica alíeles. Of the 209 markers, 21 showed distorted segregation and these markers are randomly located over 12 chromosomes. Homozygosity was detected for all the marker loci in 124 DH lines and 28 were hétérozygote. Results show that indica cultivars are recalcitrant and genes for anther culturability are partially dominant. Molecular and phenotypic trait analysis of the DH lines showed that the origin of DHs Is from pollen and these 121 DH lines are thus a valuable genetic resource in mapping quantitative trait loci (QTL) for grain Zn content and other agronomic traits. Interestingly, some of the DH lines had indica traits and high (28.3 mg kg^^) grain Zn content in polished rice.

A blast-resistance rice mutant, GR978, generated by gamma-irradiation of indica cultivar IR64 was used to characterize the disease resistance transcriptome of rice to gain a better understanding of genes or chromosomal regions contributing to broad-spectrum disease resistance. GR978 was selected from the IR64 mutant collection at IRRI. To facilitate phenotypic characterization of the collection, a set of controlled vocabularies (CV) documenting mutant phenotypes in ~3,700 entries was developed. In collaboration with the Tos17 rice mutant group at National Institute of Agrobiological Sciences, Japan, a merged CV set with 91 descriptions that map onto public ontology databases (PO, TO, OBO) is implemented in the IR64 mutant database. To better characterize the disease resistance transcriptome of rice, gene expression data from a blast resistant cultivar, SHZ-2, was incorporated in the analysis. Disease resistance transcriptome parameters, including differentially expressed genes (DEGs), regions of correlated gene expression (RCEs), and associations between DEGs and RCEs were determined statistically within and between genotypes using MAANOVA, correlation, and fixed ratio analysis. Twelve DEGs were found within the inferred physical location of the recessive gene locus on a ~3.8MB region of chromosome 12 defined by genetic analysis of GR978. Highly expressed DEGs (≥ 2fold difference) in GR978 or SHZ-2 and in common between the two, are mostly defense-response related, suggesting that most of the DEGs participate in causing the resistance phenotype. Comparing RCEs between SHZ-2 and GR978 showed that most RCEs between genotypes did not overlap. However, an 8-gene RCE in chromosome 11 was in common between SHZ2 and GR978. Gene annotations and GO enrichment analysis showed a high association with resistance response. This region has no DEGs nor is it associated with known blast resistance QTLs. Association analyses between RCEs and DEGs show that there was no enrichment of DEGs in the RCEs within a genotype and across genotypes as well. Association analysis of blast-resistance QTL (Bl-QTLs) regions (assembled from published literature; data courtesy of R. Wisser, pers comm., Cornell University) with DEGs and RCEs showed that while Bl- QTLs are not significantly associated with DEGs, they are associated with genotype-specific RCEs; GR978-RCEs are enriched within Bl-QTLs. The analysis suggested that examining patterns of correlated gene expression patterns in a chromosomal context (rather than the expression levels of individual genes) can yield additional insights into the causal relationship between gene expression and phenotype. Based on these results, we put forward a hypothesis that QTLs with small or moderate effects are represented by genomic regions in which the genes show correlated expression. It implies that gene expression within such a region is regulated by a common mechanism, and that coordinated expression of the region contributes to phenotypic effects. This hypothesis is testable by co segregation analysis of the expression patterns in well-characterized backcross and recombinant inbred lines.