Association of molecular markers with physio-biochemical traits related to seed vigour in rice

Association Mapping for Evaluation of Population Structure, Genetic Diversity, and Physiochemical Traits in Drought-Stressed Maize Germplasm Using SSR Markers

Globally, maize is one of the most consumed crops along with rice and wheat. However, maize is sensitive to different abiotic stress factors, such as drought, which have a significant impact on its production. The aims of this study were to investigate (1) genetic variation among 41 maize-inbred lines and the relationships among them and (2) significant marker-trait associations (SMTAs) between 7 selected physiochemical traits and 200 simple sequence repeat (SSR) markers to examine the genetics of these traits. A total of 1023 alleles were identified among the 41 maize-inbred lines using the 200 SSR loci, with a mean of 5.1 alleles per locus. The average major allele frequency, gene diversity, and polymorphism information content were 0.498, 0.627, and 0.579, respectively. The population structure analysis based on the 200 SSR loci divided the maize germplasm into two primary groups with an admixed group. Moreover, this study identified, respectively, 85 SMTAs and 31 SMTAs using a general linear model (Q GLM) and a mixed linear model (Q  + K MLM) with statistically significant (p < 0.05 and <0.01) associations with the seven physiochemical traits (caffeic acid content, chlorogenic acid content, gallic acid content, ferulic acid content, 2,2-diphenyl-1-picrylhydrazyl free radical scavenging activity, leaf relative moisture content, total phenolic content). These SSR markers were highly correlated with one or more of the seven physiochemical traits. This study provides insights into the genetics of the 41 maize-inbred lines and their seven physiochemical traits and will be of assistance to breeders in the marker-assisted selection of maize for breeding programs.

Mapping the Genomic Regions Controlling Germination Rate and Early Seedling Growth Parameters in Rice

Seed vigor is the key performance parameter of good quality seed. A panel was prepared by shortlisting genotypes from all the phenotypic groups representing seedling growth parameters from a total of 278 germplasm lines. A wide variation was observed for the traits in the population. The panel was classified into four genetic structure groups. Fixation indices indicated the existence of linkage disequilibrium in the population. A moderate to high level of diversity parameters was assessed using 143 SSR markers. Principal component, coordinate, neighbor-joining tree and cluster analyses showed subpopulations with a fair degree of correspondence with the growth parameters. Marker-trait association analysis detected eight novel QTLs, namely qAGR4.1, qAGR6.1, qAGR6.2 and qAGR8.1 for absolute growth rate (AGR); qRSG6.1, qRSG7.1 and qRSG8.1 for relative shoot growth (RSG); and qRGR11.1 for relative growth rate (RGR), as analyzed by GLM and MLM. The reported QTL for germination rate (GR), qGR4-1, was validated in this population. Additionally, QTLs present on chromosome 6 controlling RSG and AGR at 221 cM and RSG and AGR on chromosome 8 at 27 cM were detected as genetic hotspots for the parameters. The QTLs identified in the study will be useful for improvement of the seed vigor trait in rice.

Association mapping for protein, total soluble sugars, starch, amylose and chlorophyll content in rice

BACKGROUND

Protein, starch, amylose and total soluble sugars are basic metabolites of seed that influence the eating, cooking and nutritional qualities of rice. Chlorophyll is responsible for the absorption and utilization of the light energy influencing photosynthetic efficiency in rice plant. Mapping of these traits are very important for detection of more number of robust markers for improvement of these traits through molecular breeding approaches.

RESULTS

A representative panel population was developed by including 120 germplasm lines from the initial shortlisted 274 lines for mapping of the six biochemical traits using 136 microsatellite markers through association mapping. A wide genetic variation was detected for the traits, total protein, starch, amylose, total soluble sugars, chlorophyll a, and chlorophyll b content in the population. Specific allele frequency, gene diversity, informative markers and other diversity parameters obtained from the population indicated the effectiveness of utilization of the population and markers for mapping of these traits. The fixation indices values estimated from the population indicated the existence of linkage disequilibrium for the six traits. The population genetic structure at K = 3 showed correspondence with majority of the members in each group for the six traits. The reported QTL, qProt1, qPC6.2, and qPC8.2 for protein content; qTSS8.1 for total soluble sugar; qAC1.2 for amylose content; qCH2 and qSLCHH for chlorophyll a (Chl. a) while qChl5D for chlorophyll b (Chl. b) were validated in this population. The QTL controlling total protein content qPC1.2; qTSS7.1, qTSS8.2 and qTSS12.1 for total soluble sugars; qSC2.1, qSC2.2, qSC6.1 and qSC11.1 for starch content; qAC11.1, qAC11.2 and qAC11.3 for amylose content; qChla8.1 for Chl. a content and qChlb7.1 and qChlb8.1 for Chl. b identified by both Generalized Linear Model and Mixed Linear Model were detected as novel QTL. The chromosomal regions on chromosome 8 at 234 cM for grain protein content and total soluble sugars and at 363 cM for Chl. a and Chl. b along with the position at 48 cM on chromosome 11 for starch and amylose content are genetic hot spots for these traits.

CONCLUSION

The validated, co-localized and the novel QTL detected in this study will be useful for improvement of protein, starch, amylose, total soluble sugars and chlorophyll content in rice.

The Use of DArTseq Technology to Identify Markers Linked to Genes Responsible for Seed Germination and Seed Vigor in Maize

Seed vigor and seed germination are very important traits, determined by several factors including genetic and physical purity, mechanical damage, and physiological condition, characterized by maintaining a high seed vigor and stable content after storage. The search for molecular markers related to improvement in seed vigor under adverse condition is an important issue in maize breeding currently. Higher sowing quality of seeds is necessary for the development of the agriculture production and better ability to resist all kinds of adversity in the seeds’ storage. Condition is a very important factor affecting the yield of plants, thanks to the construction of their vitality. Identification of molecular markers associated with seed germination and seed vigor may prove to be very important in the selection of high-yielding maize varieties. The aim of this study was to identify and select new markers for maize (SNP and SilicoDArT) linked to genes influencing the seed germination and seed vigor in inbred lines of maize (Zea mays L.). The plant material used for the research was 152 inbred maize lines. The seed germination and seed vigor were analyzed. For identification of SNP and SilicoDArT markers related to the seed germination and seed vigor, the SilicoDarT technique developed by Diversity Arrays Technology was used. The analysis of variance indicated a statistically significant differentiation between genotypes for both observed traits. Positive (r = 0.41) correlation (p < 0.001) between seed germination and seed vigor was observed. As a result of next-generation sequencing, the molecular markers SilicoDArT (53,031) and SNP (28,571) were obtained. Out of 81,602 identified SilicoDArT and SNP markers, 15,409 (1559 SilicoDArT and 13,850 SNP) were selected as a result of association mapping, which showed them to be significantly related to the analyzed traits. The 890 molecular markers were associated with seed vigor, and 1323 with seed germination. Fifty-six markers (47 SilicoDArT and nine SNP) were significant for both traits. Of these 56 markers, the 20 most significant were selected (five of these markers were significant at the level of 0.001 for seed vigor and at the level of 0.05 for seed germination, another five markers were significant at the level of 0.001 for seed germination and at the level of 0.05 for seed vigor, five markers significant at the level of 0.001 only for seed vigor and five significant at the level of 0.001 only for seed germination also selected). These markers were used for physical mapping to determine their location on the genetic map. Finally, it was found that six of these markers (five silicoDArT—2,435,784, 4,772,587, 4,776,334, 2,507,310, 25,981,291, and one SNP—2,386,217) are located inside genes, the action of which may affect both seed germination and seed vigor. These markers can be used to select genotypes with high vigor and good seed germination.

Detection of Genomic Regions Controlling the Antioxidant Enzymes, Phenolic Content, and Antioxidant Activities in Rice Grain through Association Mapping

Because it is rich in antioxidant compounds, the staple food of rice provides many health benefits. Four antioxidant traits in rice grain, viz., catalase, CUPRAC, DPPH, FRAP and peroxidase, were mapped in a representative panel population containing 117 germplasm lines using 131 SSR markers through association mapping. Donor lines rich in multiple antioxidant properties were identified from the mapping population. The population was classified into three genetic groups and each group showed reasonable correspondence with the antioxidant traits. The presence of linkage disequilibrium in the population was confirmed from the estimated Fst values. A strong positive correlation of DPPH was established with TPC, FRAP and CUPRAC. A moderate to high mean gene diversity was observed in the panel population. Eleven significant marker-trait associations for antioxidant traits were mapped, namely, qACD2.1, qACD11.1 and qACD12.2 for DPPH; qCAT8.1 and qCAT11.1 for catalase; qFRAP11.1, qFRAP12.1 and qFRAP12.2 for FRAP; and qCUPRAC3.1, qCUPRAC11.1 and qCUPRA12.1 regulating CUPRAC. Co-localization of the QTLs for qACD11.1, qFRAP11.1 and qCUPRAC11.1 were detected, which may act as antioxidant hotspots regulating DPPH, FRAP and CUPRAC activities, respectively, while qACD12.2 and qFRAP12.1 remained close on the chromosome 12. These detected QTLs will be useful in antioxidant improvement programs in rice.

Nutritional improvement of cereal crops to combat hidden hunger during COVID-19 pandemic: Progress and prospects

COVID-19 has posed a severe challenge on food security by limiting access to food for the marginally placed population. While access to food is a challenge, access to nutritional food is a greater challenge to the population. The present-day foods are not sufficient to meet the nutritional requirements of the human body. In a pandemic condition, providing nutritious food to the population is imperative to ensure the health and well-being of humankind. Exploiting the existing biodiversity of crop species and deploying classical and modern tools to improve the nutritional potential of these species holds the key to addressing the above challenge. Breeding has been a classical tool of crop improvement that relied predominantly on genetic diversity. Collecting and conserving diverse germplasms and characterizing their diversity using molecular markers is essential to preserve diversity and use them in genetic improvement programs. These markers are also valuable for association mapping analyses to identify the genetic determinants of traits-of-interest in crop species. Association mapping identifies the quantitative trait loci (QTL) underlying the trait-of-interest by exploring marker-trait associations, and these QTLs can further be exploited for the genetic improvement of cultivated species through genomics-assisted breeding. Conventional breeding and genomics approaches are also being applied to develop biofortified cereal crops to reduce nutritional deficiencies in consumers. In this context, chapter explains the prerequisites for association mapping, population structure, genetic diversity, different approaches of performing association mapping to dissect nutritional traits, use the information for genomics-assisted breeding for nutrient-rich cereal crops, and application of genomics strategies in crop biofortification. These approaches will ensure food and nutrition security for all amidst the current COVID-19 crisis.

The Potential of High-Anthocyanin Purple Rice as a Functional Ingredient in Human Health

Purple rice is recognized as a source of natural anthocyanin compounds among health-conscious consumers who employ rice as their staple food. Anthocyanin is one of the major antioxidant compounds that protect against the reactive oxygen species (ROS) that cause cellular damage in plants and animals, including humans. The physiological role of anthocyanin in plants is not fully understood, but the benefits to human health are apparent against both chronic and non-chronic diseases. This review focuses on anthocyanin synthesis and accumulation in the whole plant of purple rice, from cultivation to the processed end products. The anthocyanin content in purple rice varies due to many factors, including genotype, cultivation, and management as well as post-harvest processing. The cultivation method strongly influences anthocyanin content in rice plants; water conditions, light quantity and quality, and available nutrients in the soil are important factors, while the low stability of anthocyanins means that they can be dramatically degraded under high-temperature conditions. The application of purple rice anthocyanins has been developed in both functional food and other purposes. To maximize the benefits of purple rice to human health, understanding the factors influencing anthocyanin synthesis and accumulation during the entire process from cultivation to product development can be a path for success.

Population genetic structure and association mapping for iron toxicity tolerance in rice

Iron (Fe) toxicity is a major abiotic stress which severely reduces rice yield in many countries of the world. Genetic variation for this stress tolerance exists in rice germplasms. Mapping of gene(s)/QTL controlling the stress tolerance and transfer of the traits into high yielding rice varieties are essential for improvement against the stress. A panel population of 119 genotypes from 352 germplasm lines was constituted for detecting the candidate gene(s)/QTL through association mapping. STRUCTURE, GenAlEx and Darwin softwares were used to classify the population. The marker-trait association was detected by considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) analyses. Wide genetic variation was observed among the genotypes present in the panel population for the stress tolerance. Linkage disequilibrium was detected in the population for iron toxicity tolerance. The population was categorized into three genetic structure groups. Marker-trait association study considering both the Generalized Linear Model (GLM) and Mixed Linear Model (MLM) showed significant association of leaf browning index (LBI) with markers RM471, RM3, RM590 and RM243. Three novel QTL controlling Fe-toxicity tolerance were detected and designated as qFeTox4.3, qFeTox6.1 and qFeTox10.1. A QTL reported earlier in the marker interval of C955-C885 on chromosome 1 is validated using this panel population. The present study showed that QTL controlling Fe-toxicity tolerance to be co-localized with the QTL for Fe-biofortification of rice grain indicating involvement of common pathway for Fe toxicity tolerance and Fe content in rice grain. Fe-toxicity tolerance QTL qFeTox6.1 was co-localized with grain Fe-biofortification QTLs qFe6.1 and qFe6.2 on chromosome 6, whereas qFeTox10.1 was co-localized with qFe10.1 on chromosome 10. The Fe-toxicity tolerance QTL detected from this mapping study will be useful in marker-assisted breeding programs.