Discovering New QTNs and Candidate Genes Associated with Rice-Grain-Related Traits within a Collection of Northeast Core Set and Rice Landraces

Grain-related traits are pivotal in rice cultivation, influencing yield and consumer preference. The complex inheritance of these traits, involving multiple alleles contributing to their expression, poses challenges in breeding. To address these challenges, a multi-locus genome-wide association study (ML-GWAS) utilizing 35,286 high-quality single-nucleotide polymorphisms (SNPs) was conducted. Our study utilized an association panel comprising 483 rice genotypes sourced from a northeast core set and a landraces set collected from various regions in India. Forty quantitative trait nucleotides (QTNs) were identified, associated with four grain-related traits: grain length (GL), grain width (GW), grain aroma (Aro), and length–width ratio (LWR). Notably, 16 QTNs were simultaneously identified using two ML-GWAS methods, distributed across multiple chromosomes. Nearly 258 genes were found near the 16 significant QTNs. Gene annotation study revealed that sixty of these genes exhibited elevated expression levels in specific tissues and were implicated in pathways influencing grain quality. Gene ontology (GO), trait ontology (TO), and enrichment analysis pinpointed 60 candidate genes (CGs) enriched in relevant GO terms. Among them, LOC_Os05g06470, LOC_Os06g06080, LOC_Os08g43470, and LOC_Os03g53110 were confirmed as key contributors to GL, GW, Aro, and LWR. Insights from QTNs and CGs illuminate rice trait regulation and genetic connections, offering potential targets for future studies

Development of Diagnostic Markers and Applied for Genetic Diversity Study and Population Structure of Bipolaris sorokiniana Associated with Leaf Blight Complex of Wheat

Bipolaris sorokiniana, a key pathogenic fungus in the wheat leaf blight complex, was the subject of research that resulted in the development of fifty-five polymorphic microsatellite markers. These markers were then used to examine genetic diversity and population structure in Indian geographical regions. The simple sequence repeat (SSR) like trinucleotides, dinucleotides, and tetranucleotides accounted for 43.37% (1256), 23.86% (691), and 16.54% (479) of the 2896 microsatellite repeats, respectively. There were 109 alleles produced by these loci overall, averaging 2.36 alleles per microsatellite marker. The average polymorphism information content value was 0.3451, with values ranging from 0.1319 to 0.5932. The loci’s Shannon diversity varied from 0.2712 to 1.2415. These 36 isolates were divided into two main groups using population structure analysis and unweighted neighbour joining. The groupings were not based on where the isolates came from geographically. Only 7% of the overall variation was found to be between populations, according to an analysis of molecular variance. The high amount of gene flow estimate (NM = 3.261 per generation) among populations demonstrated low genetic differentiation in the entire populations (FST = 0.071). The findings indicate that genetic diversity is often minimal. In order to examine the genetic diversity and population structure of the B. sorokiniana populations, the recently produced microsatellite markers will be helpful. This study’s findings may serve as a foundation for developing improved management plans for the leaf blight complex and spot blotch of wheat diseases in India

New insights into QTNs and potential candidate genes governing rice yield via a multi-model genome-wide association study

Abstract Background Rice (Oryza sativa L.) is one of the globally important staple food crops, and yield-related traits are prerequisites for improved breeding efficiency in rice. Here, we used six different genome-wide association study (GWAS) models for 198 accessions, with 553,229 single nucleotide markers (SNPs) to identify the quantitative trait nucleotides (QTNs) and candidate genes (CGs) governing rice yield. Results Amongst the 73 different QTNs in total, 24 were co-localized with already reported QTLs or loci in previous mapping studies. We obtained fifteen significant QTNs, pathway analysis revealed 10 potential candidates within 100kb of these QTNs that are predicted to govern plant height, days to flowering, and plot yield in rice. Based on their superior allelic information in 20 elite and 6 inferior genotypes, we found a higher percentage of superior alleles in the elite genotypes in comparison to inferior genotypes. Further, we implemented expression analysis and enrichment analysis enabling the identification of 73 candidate genes and 25 homologues of Arabidopsis, 19 of which might regulate rice yield traits. Of these candidate genes, 40 CGs were found to be enriched in 60 GO terms of the studied traits for instance, positive regulator metabolic process (GO:0010929), intracellular part (GO:0031090), and nucleic acid binding (GO:0090079). Haplotype and phenotypic variation analysis confirmed that LOC_OS09G15770, LOC_OS02G36710 and LOC_OS02G17520 are key candidates associated with rice yield. Conclusions Overall, we foresee that the QTNs, putative candidates elucidated in the study could summarize the polygenic regulatory networks controlling rice yield and be useful for breeding high-yielding varieties

Multi-Gene Phylogenetic Approach for Identification and Diversity Analysis of <i>Bipolaris maydis</i> and <i>Curvularia lunata</i> Isolates Causing Foliar Blight of <i>Zea mays</i>

Bipolaris species are known to be important plant pathogens that commonly cause leaf spot, root rot, and seedling blight in a wide range of hosts worldwide. In 2017, complex symptomatic cases of maydis leaf blight (caused by Bipolaris maydis) and maize leaf spot (caused by Curvularia lunata) have become increasingly significant in the main maize-growing regions of India. A total of 186 samples of maydis leaf blight and 129 maize leaf spot samples were collected, in 2017, from 20 sampling sites in the main maize-growing regions of India to explore the diversity and identity of this pathogenic causal agent. A total of 77 Bipolaris maydis isolates and 74 Curvularia lunata isolates were screened based on morphological and molecular characterization and phylogenetic analysis based on ribosomal markers—nuclear ribosomal DNA (rDNA) internal transcribed spacer (ITS) region, 28S nuclear ribosomal large subunit rRNA gene (LSU), D1/D2 domain of large-subunit (LSU) ribosomal DNA (rDNA), and protein-coding gene-glyceraldehyde-3-phosphate dehydrogenase (GAPDH). Due to a dearth of molecular data from ex-type cultures, the use of few gene regions for species resolution, and overlapping morphological features, species recognition in Bipolaris has proven difficult. The present study used the multi-gene phylogenetic approach for proper identification and diversity of geographically distributed B. maydis and C. lunata isolates in Indian settings and provides useful insight into and explanation of its quantitative findings

SSR and SNP Marker-Based Investigation of Indian Rice Landraces in Relation to Their Genetic Diversity, Population Structure, and Geographical Isolation

India is blessed with an abundance of diverse rice landraces in its traditional cultivated areas. Two marker systems (simple sequence repeats (SSR) and single nucleotide polymorphism (SNP)) were used to study a set of 298 rice landrace accessions collected from six different regions of India (Andaman and Nicobar Islands, Chhattisgarh, Jharkhand, Uttar Pradesh, Uttarakhand, and West Bengal). Thirty hyper-variable simple sequence repeats (HvSSRs) and 32,782 single nucleotide polymorphisms (SNPs) were used in inferring genetic structure and geographical isolation. Rice landraces from Uttar Pradesh were the most diverse, with a gene diversity value of 0.42 and 0.49 with SSR and SNP markers, respectively. Neighbor-joining trees classified the rice landraces into two major groups with SSR and SNP markers, and complete geographical isolation was observed with SSR markers. Fast STRUCTURE analysis revealed four populations for SSR markers and three populations for SNP markers. The population structure with SSR markers showed that few individuals from Uttarakhand and Andaman and Nicobar Islands were grouped in small clusters. Population structure analysis with SNP markers showed not very distinct region-wise clustering among the rice landraces. Discriminant analysis of principal components (DAPC) and minimum spanning network (MSN) using SSR markers showed region-wise grouping of landraces with some intermixing, but DAPC and MSN with SNP markers showed very clear region-wise clustering. Genetic differentiation of rice landraces between the regions was significant with both SSR (Fst 0.094–0.487) and SNP markers (Fst 0.047–0.285). A Mantel test revealed a positive correlation between the genetic and geographic distance of rice landraces. The present study concludes that rice landraces investigated in this study were very diverse, and unlinked SSR markers show better geographical isolation than a large set of SNP markers