GWAS to spot candidate genes associated with grain quality traits in diverse rice accessions of North East India

A rice variation map derived from 10 548 rice accessions reveals the importance of rare variants

Detailed knowledge of the genetic variations in diverse crop populations forms the basis for genetic crop improvement and gene functional studies. In the present study, we analyzed a large rice population with a total of 10 548 accessions to construct a rice super-population variation map (RSPVM), consisting of 54 378 986 single nucleotide polymorphisms, 11 119 947 insertion/deletion mutations and 184 736 presence/absence variations. Assessment of variation detection efficiency for different population sizes revealed a sharp increase of all types of variation as the population size increased and a gradual saturation of that after the population size reached 10 000. Variant frequency analysis indicated that ∼90% of the obtained variants were rare, and would therefore likely be difficult to detect in a relatively small population. Among the rare variants, only 2.7% were predicted to be deleterious. Population structure, genetic diversity and gene functional polymorphism of this large population were evaluated based on different subsets of RSPVM, demonstrating the great potential of RSPVM for use in downstream applications. Our study provides both a rich genetic basis for understanding natural rice variations and a powerful tool for exploiting great potential of rare variants in future rice research, including population genetics and functional genomics.

Mapping of QTLs associated with yield and related traits under reproductive stage drought stress in rice using SNP linkage map

BACKGROUND

Drought stress is a major constraint for rice production worldwide. Reproductive stage drought stress (RSDS) leads to heavy yield losses in rice. The prospecting of new donor cultivars for identification and introgression of QTLs of major effect (Quantitative trait locus) for drought tolerance is crucial for the development of drought-resilient rice varieties.

METHODS AND RESULTS

Our study aimed to map QTLs associated with yield and its related traits under RSDS conditions. A saturated linkage map was constructed using 3417 GBS (Genotyping by sequencing) derived SNP (Single nucleotide polymorphism) markers spanning 1924.136 cM map length with an average marker density of 0.56 cM, in the F3 mapping population raised via cross made between the traditional ahu rice cultivar, Koniahu (drought tolerant) and a high-yielding variety, Disang (drought susceptible). Using the Inclusive composite interval mapping approach, 35 genomic regions governing yield and related traits were identified in pooled data from 198 F3 and F4 segregating lines evaluated for two consecutive seasons under both RSDS and irrigated control conditions. Of the 35 QTLs, 23 QTLs were identified under RSDS with LOD (Logarithm of odds) values ranging between 2.50 and 7.83 and PVE (phenotypic variance explained) values of 2.95-12.42%. Two major QTLs were found to be linked to plant height (qPH1.29) and number of filled grains per panicle (qNOG5.12) under RSDS. Five putative QTLs for grain yield namely, qGY2.00, qGY5.05, qGY6.16, qGY9.19, and qGY10.20 were identified within drought conditions. Fourteen QTL regions having ≤ 10 Mb QTL interval size were further analysed for candidate gene identification and a total of 4146 genes were detected out of these 2263 (54.63%) genes were annotated to at least one gene ontology (GO) term.

CONCLUSION

Several QTLs associated with grain yield and yield components and putative candidate genes were identified. The putative QTLs and candidate genes identified could be employed to augment drought resilience in rice after further validation through MAS strategies.

Mining nutri-dense accessions from rice landraces of Assam, India

The Indian subcontinent is the primary center of origin of rice where huge diversity is found in the Indian rice gene pool, including landraces. North Eastern States of India are home to thousands of rice landraces which are highly diverse and good sources of nutritional traits, but most of them remain nutritionally uncharacterized. Hence, nutritional profiling of 395 Assam landraces was done for total starch, amylose content (AC), total dietary fiber (TDF), total protein content (TPC), oil, phenol, and total phytic acid (TPA) using official AOAC and standard methods, where the mean content for the estimated traits were found to be 75.2 g/100g, 22.2 g/100g, 4.67 g/100g, 9.8 g/100g, 5.26%, 0.40 GAE g/100g, and 0.34 g/100g for respectively. The glycaemic index (GI) was estimated in 24 selected accessions, out of which 17 accessions were found to have low GI (<55). Among different traits, significant correlations were found that can facilitate the direct and indirect selection such as estimated glycemic index (EGI) and amylose content (-0.803). Multivariate analyses, including principal component analysis (PCA) and hierarchical clustering analysis (HCA), revealed the similarities/differences in the nutritional attributes. Four principal components (PC) i.e., PC1, PC2, PC3, and PC4 were identified through principal component analysis (PCA) which, contributed 81.6% of the variance, where maximum loadings were from protein, oil, starch, and phytic acid. Sixteen clusters were identified through hierarchical clustering analysis (HCA) from which the trait-specific and biochemically most distant accessions could be identified for use in cultivar development in breeding programs.

Genetic analysis for detection of genes associated to drought tolerance in rice accessions belonging to north east India

INTRODUCTION

The North East (NE) India is rich in biodiversity and also considered as the secondary centre for origin of rice. The NE rice accessions was characterized previously using genetic markers and morphological traits. Simultaneously, genome-wide association studies (GWAS) reveal significant marker-trait associations for the drought tolerance traits.

METHODS AND RESULTS

The genetic diversity and population structure of 296 NE rice accessions were studied using 96,712 single nucleotide polymorphism (SNP) markers distributed across 12 chromosomes. The accessions were clustered into two major sub-groups (SG). A total of 91 accessions were assembled as SG1 and 114 accessions as SG2, while the remaining 91 were admixture genotypes. A total of 200 genotypes belonging to different groups were phenotyped for yield component traits under drought and control conditions. The GWAS was performed to identify significant marker-trait associations (MTAs). Consequently, 47 MTAs were detected under drought, exhibiting 0.02-9.95% of phenotypic variance (P.V.). Whereas 58 MTAs were discovered under control conditions, showing a 0.01-9.74% contribution to the phenotype. Through in-silico mining of QTLs, 2999 genes were identified. Among these; only 22 genes were directly associated with stress response.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in popular drought susceptible rice varieties.

Genome-wide association analysis of sucrose and alanine contents in edamame beans

The sucrose and Alanine (Ala) content in edamame beans significantly impacts the sweetness flavor of edamame-derived products as an important attribute to consumers' acceptance. Unlike grain-type soybeans, edamame beans are harvested as fresh beans at the R6 to R7 growth stages when beans are filled 80-90% of the pod capacity. The genetic basis of sucrose and Ala contents in fresh edamame beans may differ from those in dry seeds. To date, there is no report on the genetic basis of sucrose and Ala contents in the edamame beans. In this study, a genome-wide association study was conducted to identify single nucleotide polymorphisms (SNPs) related to sucrose and Ala levels in edamame beans using an association mapping panel of 189 edamame accessions genotyped with a SoySNP50K BeadChip. A total of 43 and 25 SNPs was associated with sucrose content and Ala content in the edamame beans, respectively. Four genes (Glyma.10g270800, Glyma.08g137500, Glyma.10g268500, and Glyma.18g193600) with known effects on the process of sucrose biosynthesis and 37 novel sucrose-related genes were characterized. Three genes (Gm17g070500, Glyma.14g201100 and Glyma.18g269600) with likely relevant effects in regulating Ala content and 22 novel Ala-related genes were identified. In addition, by summarizing the phenotypic data of edamame beans from three locations in two years, three PI accessions (PI 532469, PI 243551, and PI 407748) were selected as the high sucrose and high Ala parental lines for the perspective breeding of sweet edamame varieties. Thus, the beneficial alleles, candidate genes, and selected PI accessions identified in this study will be fundamental to develop edamame varieties with improved consumers' acceptance, and eventually promote edamame production as a specialty crop in the United States.

Molecular mapping of drought-responsive QTLs during the reproductive stage of rice using a GBS (genotyping-by-sequencing) based SNP linkage map

BACKGROUND

In rice, drought stress at reproductive stage drastically reduces yield, which in turn hampers farmer's efforts towards crop production. The majority of the rice varieties have resistance genes against several abiotic and biotic stresses. Therefore, the traditional landraces were studied to identify QTLs/candidate genes associated with drought tolerance.

METHODS AND RESULTS

A high-density SNP-based genetic map was constructed using a Genotyping-by-sequencing (GBS) approach. The recombinant inbred lines (RILs) derived from crossing 'Banglami × Ranjit' were used for QTL analysis. A total map length of 1306.424 cM was constructed, which had an average inter-marker distance of 0.281 cM. The phenotypic evaluation of F₆ and F₇ RILs were performed under drought stress and control conditions. A total of 42 QTLs were identified under drought stress and control conditions for yield component traits explaining 1.95-13.36% of the total phenotypic variance (PVE). Among these, 19 QTLs were identified under drought stress conditions, whereas 23 QTLs were located under control conditions. A total of 4 QTLs explained a PVE ≥ 10% which are considered as the major QTLs. Moreover, bioinformatics analysis revealed the presence of 6 candidate genes, which showed differential expression under drought and control conditions.

CONCLUSION

These QTLs/genes may be deployed for marker-assisted pyramiding to improve drought tolerance in the existing rice varieties.

Identification and characterization of genes for drought tolerance in upland rice cultivar 'Banglami' of North East India

INTRODUCTION

Rice is a major crop in Assam, North East (NE) India. The rice accessions belonging to NE India possess unique traits of breeder's interest, i.e., tolerant to biotic and abiotic stresses. In the present research programme, the stress responsive genes were identified within the QTLs associated with drought tolerance. The differential expression profiling of genes were performed under drought stress and control conditions. Thus, the 'candidate genes' associated with drought tolerance were recognised and may be deployed in a breeding programme.

METHODS AND RESULTS

A drought-tolerant traditional rice cultivar, Banglami, was crossed with a high-yielding, drought-susceptible variety, Ranjit. The mapping population (F₄) was raised through the single seed descent (SSD) method and used in QTL analysis. Under drought stress, a total of 4752 genes were identified through in-silico mining of QTLs. Among these, only 21 genes primarily associated with the stress response. The maximum of four stress-responsive genes were located within the QTLs, qNOG12.1 and qGY1.1. However, under control conditions, 2088 genes were identified, out of which, only 15 were categorised as the major stress responsive genes. The functional characterization of genes recognized 24 different types of proteins. Among these, peroxidase and heat shock proteins (Hsp) are the principal proteins encoded during stress. In addition to that, OsbZIP23, inorganic pyrophosphatase, universal stress protein, serine threonine kinase, NADPH oxidoreductase, and proteins belonging to the ABC1 family were also produced during stress condition. The differential expression profiling showed a profound expression pattern of three candidate genes under drought stress condition, i.e., OsI_32199 (Ascorbate peroxidase), OsI_37694 (Universal stress protein) and OsI_32167 (Heat shock protein 81 - 1).

CONCLUSION

The novel candidate genes identified for drought tolerance, may be used in the breeding programme for the development of 'climate smart rice varieties'.