Mitochondrial markers differentiate two distinct phylogenetic groups in indigenous rice landraces of northeast India: an evolutionary insight.

The inheritance of the mitochondria genome and its diversity is unique for genetic and evolutionary studies relative to nuclear genomes. Northeast India and Himalayan regions are considered as one of the centres of indica rice origin. Also, rice diversity in northeast India is very distinct and highly suited for evolutionary studies. Although reports are available on the genetic diversity of indigenous northeast rice landraces, its relationship with the wild relatives is not yet properly explored and understood. In an attempt, mitochondrial markers were used to study the evolutionary relationship between the 68 landraces of northeast India and wild relatives (O. rufipogon and O. nivara) along with IR64 (indica) and Nipponbare (japonica) were taken as reference cultivars. Phylogenetically, the findings include two distinct clusters in the indigenous northeast India landraces representing indica and japonica groups. Further, the wild relatives and ~60% of northeast India landraces were identified to be closely related to the Nipponbare cluster. Besides, landraces of northeast India grouping with the indica group (IR64) are characterized by the absence of wild relatives. This indicates that there are two distinct evolutionary paths in the origin of northeast Indian rice landraces based on mitochondrial markers diversity and it is proposed that the inheritance of mitochondria, mitonuclear genome interactions, and bottleneck events could have genetically separated these two phylogenetically unique groups of northeast rice landraces.

Gene based markers improve precision of genome-wide association studies and accuracy of genomic predictions in rice breeding.

It is hypothesized that the genome-wide genic markers may increase the prediction accuracy of genomic selection for quantitative traits. To test this hypothesis, a set of candidate gene-based markers for yield and grain traits-related genes cloned across the rice genome were custom-designed. A multi-model, multi-locus genome-wide association study (GWAS) was performed using new genic markers developed to test their effectiveness for gene discovery. Two multi-locus models, FarmCPU and mrMLM, along with a single-locus mixed linear model (MLM), identified 28 significant marker-trait associations. These associations revealed novel causative alleles for grain weight and pleiotropic associations with other traits. For instance, the marker YD91 derived from the gene OsAAP3 on chromosome 1 was consistently associated with grain weight, while the gene has a significant effect on grain yield. Furthermore, nine genomic selection methods, including regression-based and machine learning-based models, were used to predict grain weight using a leave-one-out five-fold cross-validation approach to optimize the genomic selection model with genic markers. Among nine prediction models, Kernel Hilbert Space Regression (RKHS) is the best among regression-based models, and Random Forest Regression (RFR) is the best among machine learning-based models. Genomic prediction accuracies with and without GWAS significant markers were compared to assess the effectiveness of markers. The rapid decreases in prediction accuracy upon dropping GWAS significant markers indicate the effectiveness of new genic markers in genomic selection. Apart from that, the candidate gene-based markers were found to be more effective in genomic selection programs for better accuracy.

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.

Improvement of Phosphorus Use Efficiency in Rice by Adopting Image-Based Phenotyping and Tolerant Indices.

Phosphorus is one of the second most important nutrients for plant growth and development, and its importance has been realised from its role in various chains of reactions leading to better crop dynamics accompanied by optimum yield. However, the injudicious use of phosphorus (P) and non-renewability across the globe severely limit the agricultural production of crops, such as rice. The development of P-efficient cultivar can be achieved by screening genotypes either by destructive or non-destructive approaches. Exploring image-based phenotyping (shoot and root) and tolerant indices in conjunction under low P conditions was the first report, the epicentre of this study. Eighteen genotypes were selected for hydroponic study from the soil-based screening of 68 genotypes to identify the traits through non-destructive (geometric traits by imaging) and destructive (morphology and physiology) techniques. Geometric traits such as minimum enclosing circle, convex hull, and calliper length show promising responses, in addition to morphological and physiological traits. In 28-day-old seedlings, leaves positioned from third to fifth played a crucial role in P mobilisation to different plant parts and maintained plant architecture under P deficient conditions. Besides, a reduction in leaf angle adjustment due to a decline in leaf biomass was observed. Concomitantly, these geometric traits facilitate the evaluation of low P-tolerant rice cultivars at an earlier stage, accompanying several stress indices. Out of which, Mean Productivity Index, Mean Relative Performance, and Relative Efficiency index utilising image-based traits displayed better responses in identifying tolerant genotypes under low P conditions. This study signifies the importance of image-based phenotyping techniques to identify potential donors and improve P use efficiency in modern rice breeding programs.

Genetic diversity analysis of specialty glutinous and low-amylose rice (Oryza sativa L.) landraces of Assam based on Wx locus and microsatellite diversity.

The sticky rice of Assam is traditionally classified as bora (glutinous) and chokuwa (semi-glutinous) based on their stickiness after cooking. The Waxy (Wx) gene encodes for granule-bound starch synthase (GBSS) that controls the synthesis of amylose, which is a key determinant of rice end-use quality attributes. In this report, we analysed the level of variation in grain quality traits in a collection of bora and chokuwa cultivars, and examined the nucleotide diversity at the Wx locus of selected rice accessions to identify the possible cause of low-amylose in these rice cultivar groups. The Wx gene sequencing from 24 bora and chokuwa cultivars revealed several nucleotide variations that can explain the variation in the amylose phenotypes. The nucleotide polymorphisms in the downstream intron regions were similar to those reported in Bangladeshi Beruin cultivars. Among the Wx polymorphisms, the CTn microsatellite in exon 1 and G/T SNP in intron 1 (G/T-Int1) should be considered for marker assisted breeding involving bora cultivars. The Wx gene tree, classified the bora accessions possessing the G/T-Int1 SNP as japonicas. However, cluster analysis using microsatellite markers classified the bora and chokuwa cultivars as indica, and intermediate of indica-aus. The findings of this study supplemented our understanding on the evolution of the Wx gene under human selection. The results will assist plant breeders to effectively improve the bora and chokuwa landraces.

Morphological and molecular dissection of wild rices from eastern India suggests distinct speciation between O. rufipogon and O. nivara populations.

The inter relationships between the two progenitors is interesting as both wild relatives are known to be the great untapped gene reservoirs. The debate continues on granting a separate species status to Oryza nivara. The present study was conducted on populations of Oryza rufipogon and Oryza nivara from Eastern India employing morphological and molecular characteristics. The cluster analysis of the data on morphological traits could clearly classify the two wild forms into two separate discrete groups without any overlaps i.e. lack of intermediate forms, suggesting the non-sympatric existence of the wild forms. Amplification of hyper variable regions of the genome could reveal 144 alleles suggesting high genetic diversity values (average He = 0.566). Moreover, with 42.37% of uncommon alleles between the two wild relatives, the molecular variance analysis (AMOVA) could detect only 21% of total variation (p < 0.001) among them and rest 59% was within them. The population structure analysis clearly classified these two wild populations into two distinct sub-populations (K = 2) without any overlaps i.e. lack of intermediate forms, suggesting the non-sympatric existence of the wild forms. Clear differentiation into two distinct groups indicates that O. rufipogon and O. nivara could be treated as two different species.