Multi-trait association study identifies loci associated with tolerance of low phosphorus in Oryza sativa and its wild relatives.

We studied variation in adaptive traits and genetic association to understand the low P responses, including the symbiotic association of arbuscular mycorrhizal (AM) fungal colonization in Oryza species (O. sativa, O. nivara, and O. rufipogon). In the present experiment, we performed the phenotypic variability of the morphometric and geometric traits for P deficiency tolerance and conducted the association studies in GLM and MLM methods. A positive association between the geometric trait of the top-view area and root traits suggested the possibility of exploring a non-destructive approach in screening genotypes under low P. The AMOVA revealed a higher proportion of variation among the individuals as they belonged to different species of Oryza and the NM value was 2.0, indicating possible gene flow between populations. A sub-cluster with superior-performing accessions had a higher proportion of landraces (42.85%), and O. rufipogon (33.3%) was differentiated by four Pup1-specific markers. Association mapping identified seven notable markers (RM259, RM297, RM30, RM6966, RM242, RM184, and PAP1) and six potential genotypes (IC459373, Chakhao Aumbi, AC100219, AC100062, Sekri, and Kumbhi Phou), which will be helpful in the marker-assisted breeding to improve rice for P-deprived condition. In addition, total root surface area becomes a single major trait that helps in P uptake under deficit P up to 33% than mycorrhizal colonization. Further, the phenotypic analysis of the morphometric and geometric trait variations and their interactions provides excellent potential for selecting donors for improving P-use efficiency. The identified potential candidate genes and markers offered new insights into our understanding of the molecular and physiological mechanisms driving PUE and improving grain yield under low-P conditions.

Characterization and exploring genetic potential of landraces from Odisha with special emphasis on grain micronutrient content for benefaction of biofortification in rice.

Assessing genetic variability of micronutrient content in association with qualitative and quantitative traits in germplasm is prerequisite for effective biofortification programme. Odisha, a state of eastern India is considered as one of the most potential hot spot of diversity of cultivated rice for grain yield and nutritional traits. Significant variability for most of the qualitative and quantitative traits including Fe and Zn content was observed in a set of 293 germplasm with varying kernel colour encompassing 14 districts of Odisha. Mostly these landraces were low yielding with some exception (Haldigundi: AC 36454, 50.08 g/plant). These landraces were mostly represented by medium Fe (10-20 ppm)-medium Zn group (20-30 ppm). Fe and Zn content had positive association with each other and also with grain size. Landraces with red kernel colour were observed to have slightly higher average Zn content (26.30 ppm) as compared to white (25.87 ppm) grains. Diversity analysis of 14 districts revealed that Nayagarh, a south-eastern district was rich in Fe content while Deogarh, Keonjhar and Mayurbhanj, all north-western districts were rich in Zn content. This study identified 10 superior micronutrient dense genotypes with medium to high Fe and Zn content. This set of donors for micronutrient content was validated in another year. Champeisiali (AC 43368) and Gedemalati (AC 34306) with highest Fe (44.1 ppm) and Zn (40.48 ppm) content, respectively were detected over the environments. Identified donors and associated traits could be utilized in biofortificaion programme using appropriate breeding methodologies for enhancing micronutrients in high yielding background. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s12298-021-01119-7.

Non-destructive phenotyping for early seedling vigor in direct-seeded rice.

BACKGROUND: Early seedling vigor is an essential trait of direct-seeded rice. It helps the seedlings to compete with weeds for water and nutrient availability, and contributes to better seedling establishment during the initial phase of crop growth. Seedling vigor is a complex trait, and phenotyping by a destructive method limits the improvement of this trait through traditional breeding. Hence, a non-invasive, rapid, and precise image-based phenotyping technique is developed to increase the possibility to improve early seedling vigor through breeding in rice and other field crops. RESULTS: To establish and assess the methodology using free-source software, early seedling vigor was estimated from images captured with a digital SLR camera in a non-destructive way. Here, the legitimacy and strength of the method have been proved through screening seven diverse rice cultivars varying for early seedling vigor. In the regression analysis, whole-plant area (WPA) estimated by destructive-flatbed scanner (WPAs) and non-destructive imaging (WPAi) approaches was strongly related (R2 > 83%) and suggested that WPAi can be adapted in place of destructive methods to estimate seedling vigor. In addition, this study has identified a set of new geometric traits (convex hull and top view area) for screening breeding lines for early seedling vigor in rice, which decreased the time by 80% and halved the cost of labor in data observation. CONCLUSIONS: The method demonstrated here is affordable and easy to establish as a phenotypic platform. It is suitable for most glasshouses/net houses for characterizing genotypes to understand the plasticity of shoots under a given environment at the seedling stage. The methodology explained in this experiment has been proven to be practical and suggested as a technique for researchers involved in direct-seeded rice. Consequently, it will help in the simultaneous screening of genotypes in large numbers, the identification of donors, and in gaining information on the genetic basis of the trait to design a breeding program for direct-seeded rice.

Detection of stable QTLs for grain protein content in rice (Oryza sativa L.) employing high throughput phenotyping and genotyping platforms.

Lack of appropriate donors, non-utilization of high throughput phenotyping and genotyping platforms with high genotype × environment interaction restrained identification of robust QTLs for grain protein content (GPC) in rice. In the present investigation a  BC3F4 mapping population was developed using grain protein donor, ARC10075 and high-yielding cultivar Naveen and 190 lines were genotyped using 40 K Affimetrix custom SNP array with the objective to identify stable QTLs for protein content. Three of the identified QTLs, one for GPC (qGPC1.1) and the other two for single grain protein content (qSGPC2.1, qSGPC7.1) were stable over the environments explaining  13%, 14% and 7.8% of the phenotypic variances, respectively. Stability and repeatability of these additive QTLs were supported by the synergistic additive effects of multi-environmental-QTLs. One epistatic-QTL, independent of  the  main effect QTL was detected over the environment for SGPC. A few functional genes governing seed storage protein were hypothesised inside these identified QTLs. The qGPC1.1 was validated by NIR Spectroscopy-based high throughput phenotyping in BC3F5 population. Higher glutelin content was estimated in high-protein lines with the introgression of qGPC1.1 in telomeric region of short arm of chromosome 1. This was supported by the postulation of probable candidate gene inside this QTL region encoding glutelin family proteins.