The investigation was carried out to estimate the components of genetic variability and associated statistical parameters for grain quality traits of 215 indigenous rice landraces of Chhattisgarh, India. Substantial genetic variability among the all genotypes was observed for the characteristics under study. All the genotypes were showed highly significant differences for all the studied grain quality traits. Coefficient of variation ranges from 8.61% for hulling percentage to 45.01% for alkali spreading value. Negligible difference between genotypic coefficient of variation and phenotypic coefficient of variation was observed for all the traits. High heritability with high genetic advance as percent mean was observed for all the grain quality traits except for hulling percent and milling percent. These results indicated that direct selection based on phenotypic performance could be rewarding for all quality traits because they are less influenced by environment and mostly governed by additive gene action. It has been observed that sixty nine genotypes had short slender type grain characteristics whereas; forty seven genotypes have short bold type grains. Thirty genotypes showed more than 80% hulling percent, fifty six genotypes showed more than 70% milling percent and fourteen genotypes showed more than 65%

The recent advancements in forward genetics have expanded the applications of mutation techniques in advanced genetics and genomics, ahead of direct use in breeding programs. The advent of next-generation sequencing (NGS) has enabled easy identification and mapping of causal mutations within a short period and at relatively low cost. Identifying the genetic mutations and genes that underlie phenotypic changes is essential for understanding a wide variety of biological functions. To accelerate the mutation mapping for crop improvement, several high-throughput and novel NGS based forward genetic approaches have been developed and applied in various crops. These techniques are highly efficient in crop plants, as it is relatively easy to grow and screen thousands of individuals. These approaches have improved the resolution in quantitative trait loci (QTL) position/point mutations and assisted in determining the functional causative variations in genes. To be successful in the interpretation of NGS data, bioinformatics computational methods are critical elements in delivering accurate assembly, alignment, and variant detection. Numerous bioinformatics tools/pipelines have been developed for such analysis. This article intends to review the recent advances in NGS based forward genetic approaches to identify and map the causal mutations in the crop genomes. The article also highlights the available bioinformatics tools/pipelines for reducing the complexity of NGS data and delivering the concluding outcomes.

Rice has been cultivating and utilizing by humans for thousands of years under diverse environmental conditions. Therefore, tremendous genetic differentiation and diversity has occurred at various agro-ecosystems. The significant indica–japonica differentiation in rice provides great opportunities for its genetic improvement. In the present investigation, a total of 42 polymorphic InDel markers were used for differentiating 188 rice landraces and two local varieties of Chhattisgarh, India into indica and japonica related genotypes based on ‘InDel molecular index’. Frequency of japonica alleles varied from 0.11 to 0.89 among landraces. Results revealed that 104 rice landraces have indica type genetic architecture along with three tested indica cultivars Swarna, Mahamaya and Rajeshwari. Another 60 landraces were placed under ‘close to indica’ type. It was found that three rice landraces i.e. Kalajeera, Kapri, Tulsimala were ‘close to japonica’ type and 21 landraces were ‘intermediate’ type. The result from the calculation of ‘InDel molecular index’ was further verified with STRUCTURE, AMOVA, PCA and cluster analysis. Population structure analysis revealed two genetically distinct populations within the 190 rice landraces/genotypes. Based on AMOVA, ‘intermediate’ type, ‘close to japonica’ type and Dongjinbyeo (a japonica cultivar from Republic of Korea) displayed significant genetic differentiation (ɸPT = 0.642, P = 0.000) from ‘indica’ and ‘close to indica’ groups. The PCA scatter plot and dendrogram demonstrated a clear pattern of two major group differentiations. ‘Close to japonica’ type and ‘intermediate’ type landraces/genotypes were grouped with Dongjinbyeo and formed a separate cluster at 30% Jaccard’s similarity level from rest of the landraces/genotypes which were ‘close to indica’ or ‘indica’ type. Such a significant genetic differentiation among the locally adapted landraces could be exploited for the development of rice varieties introgressing higher yield potential and better plant types of japonica type as per the need of consumers and rice traders.

Rice production needs to be sustained in the coming decades, as the changeable climatic conditions are becoming more conducive to disease outbreaks. The majority of rice diseases cause enormous economic damage and yield instability. Among them, rice blast caused by Magnaportheoryzae is a serious fungal disease and is considered one of the major threats to world rice production. This pathogen can infect the above-ground tissues of rice plants at any growth stage and causes complete crop failure under favorable conditions. Therefore, management of blast disease is essentially required to sustain global food production. When looking at the drawback of chemical management strategy, the development of durable, resistant varieties is one of the most sustainable, economic, and environment-friendly approaches to counter the outbreaks of rice blasts. Interestingly, several blast-resistant rice cultivars have been developed with the help of breeding and biotechnological methods. In addition, 146 R genes have been identified, and 37 among them have been molecularly characterized to date. Further, more than 500 loci have been identified for blast resistance which enhances the resources for developing blast resistance through marker-assisted selection (MAS), marker-assisted backcross breeding (MABB), and genome editing tools. Apart from these, a better understanding of rice blast pathogens, the infection process of the pathogen, and the genetics of the immune response of the host plant are very important for the effective management of the blast disease. Further, high throughput phenotyping and disease screening protocols have played significant roles in easy comprehension of the mechanism of disease spread. The present review critically emphasizes the pathogenesis, pathogenomics, screening techniques, traditional and molecular breeding approaches, and transgenic and genome editing tools to develop a broad spectrum and durable resistance against blast disease in rice. The updated and comprehensive information presented in this review would be definitely helpful for the researchers, breeders, and students in the planning and execution of a resistance breeding program in rice against this pathogen.

A core set of 190 rice landraces were used to decipher the genetic structure and to discover the chromosomal regions containing QTLs, affecting the grain micro-nutrients, fatty acids, and yield-related traits by using 148 molecular markers in this study. Landraces were categorized into three sub-groups based on population stratification study and followed by neighborjoining tree and principal component analysis. Analysis of variance revealed abundant variations among the landraces for studied traits with less influence of environmental factors. Genome Wide Association Studies (GWAS) revealed 22 significant and consistent QTLs through marker trait association (MTAs) for 12 traits based on 2 years and pooled analysis. Out of 22 QTLs, three have been reported earlier while 19 QTLs are novel. Interestingly, 13 QTLs out of 22 were explained more than 10% phenotypic variance. Association of RM1148 and RM205 with Days to 50% flowering was comparable with flowering control genes Ghd8/qDTH8 and qDTH9, respectively. Similarly, Zn content was associated with RM44, which is situated within the QTL qZn8-1. Moreover, significant association of RM25 with oleic acid content was closely positioned with QTL qOle8. Association of RM7434 with grain yield/plant; RM184 with spikelet fertility %; R3M10, R9M42 with hundred seed weight; RM536, RM17467, RM484, RM26063 with Fe content; RM44, RM6839 with Zn content are the major outcomes of this study. In addition, association of R11M23 with days to 50% flowering, panicle length and total spikelets per panicle are explained the possible occurrence of pleiotropism among these traits. Prominent rice landraces viz., Anjani (early maturity); Sihar (extra dwarf); Gangabaru (highest grain yield/plant); Karhani (highest iron content); Byalo-2 (highest zinc content) and Kadamphool (highest oleic acid) were identified through this study. The present study will open many avenues towards utilization of these QTLs and superior landraces in rice breeding for developing nutrition-rich high yielding varieties.