Exploring genetic architecture of grain yield and quality traits in a 16-way indica by japonica rice MAGIC global population

Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map

Developing high-yielding rice varieties that possess favorable agronomic characteristics and enhanced grain Zn content is crucial in ensuring food security and addressing nutritional needs. This research employed ICIM, IM, and multi-parent population QTL mapping methods to identify important genetic regions associated with traits such as DF, PH, NT, NP, PL, YLD, TGW, GL, GW, Zn, and Fe. Two populations of recombinant inbred lines consisting of 373 lines were phenotyped for agronomic, yield and grain micronutrient traits for three seasons at IRRI, and genotyped by sequencing. Most of the traits demonstrated moderate to high broad-sense heritability. There was a positive relationship between Zn and Fe contents. The principal components and correlation results revealed a significant negative association between YLD and Zn/Fe. ICIM identified 81 QTLs, while IM detected 36 QTLs across populations. The multi-parent population analysis detected 27 QTLs with six of them consistently detected across seasons. We shortlisted eight candidate genes associated with yield QTLs, 19 genes with QTLs for agronomic traits, and 26 genes with Zn and Fe QTLs. Notable candidate genes included CL4 and d35 for YLD, dh1 for DF, OsIRX10, HDT702, sd1 for PH, OsD27 for NP, whereas WFP and OsIPI1 were associated with PL, OsRSR1 and OsMTP1 were associated to TGW. The OsNAS1, OsRZFP34, OsHMP5, OsMTP7, OsC3H33, and OsHMA1 were associated with Fe and Zn QTLs. We identified promising RILs with acceptable yield potential and high grain Zn content from each population. The major effect QTLs, genes and high Zn RILs identified in our study are useful for efficient Zn biofortification of rice.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Agronomic potential of plant-specific Gγ proteins

The vascular plant-specific type III Gγ proteins have emerged as important targets for biotechnological applications. These proteins are exemplified by Arabidopsis AGG3, rice Grain Size 3 (GS3), Dense and Erect Panicle 1 (DEP1), and GGC2 and regulate plant stature, seed size, weight and quality, nitrogen use efficiency, and multiple stress responses. These Gγ proteins are an integral component of the plant heterotrimeric G-protein complex and differ from the canonical Gγ proteins due to the presence of a long, cysteine-rich C-terminal region. Most cereal genomes encode three or more of these proteins, which have similar N-terminal Gγ domains but varying lengths of the C-terminal domain. The C-terminal domain is hypothesized to give specificity to the protein function. Intriguingly, many accessions of cultivated cereals have natural deletion of this region in one or more proteins, but the mechanistic details of protein function remain perplexing. Distinct, sometimes contrasting, effects of deletion of the C-terminal region have been reported in different crops or under varying environmental conditions. This review summarizes the known roles of type III Gγ proteins, the possible action mechanisms, and a perspective on what is needed to comprehend their full agronomic potential.

Moving beyond the arabidopsis-centric view of G-protein signaling in plants

Heterotrimeric G-protein-mediated signaling is a key mechanism to transduce a multitude of endogenous and environmental signals in diverse organisms. The scope and expectations of plant G-protein research were set by pioneering work in metazoans. Given the similarity of the core constituents, G-protein-signaling mechanisms were presumed to be universally conserved. However, because of the enormous diversity of survival strategies and endless forms among eukaryotes, the signal, its interpretation, and responses vary even among different plant groups. Earlier G-protein research in arabidopsis (Arabidopsis thaliana) has emphasized its divergence from Metazoa. Here, we compare recent evidence from diverse plant lineages with the available arabidopsis G-protein model and discuss the conserved and novel protein components, signaling mechanisms, and response regulation.

Genome-wide association study reveals novel genomic regions governing agronomic and grain quality traits and superior allelic combinations for Basmati rice improvement

BACKGROUND

Basmati is a speciality segment in the rice genepool characterised by explicit grain quality. For the want of suitable populations, genome-wide association study (GWAS) in Basmati rice has not been attempted.

MATERIALS

To address this gap, we have performed a GWAS on a panel of 172 elite Basmati multiparent population comprising of potential restorers and maintainers. Phenotypic data was generated for various agronomic and grain quality traits across seven different environments during two consecutive crop seasons. Based on the observed phenotypic variation, three agronomic traits namely, days to fifty per cent flowering, plant height and panicle length, and three grain quality traits namely, kernel length before cooking, length breadth ratio and kernel length after cooking were subjected to GWAS. Genotyped with 80K SNP array, the population was subjected to principal component analysis to stratify the underlying substructure and subjected to the association analysis using Bayesian-information and Linkage-disequilibrium Iteratively Nested Keyway (BLINK) model.

RESULTS

We identified 32 unique MTAs including 11 robust MTAs for the agronomic traits and 25 unique MTAs including two robust MTAs for the grain quality traits. Six out of 13 robust MTAs were novel. By genome annotation, six candidate genes associated with the robust MTAs were identified. Further analysis of the allelic combinations of the robust MTAs enabled the identification of superior allelic combinations in the population. This information was utilized in selecting 77 elite Basmati rice genotypes from the panel.

CONCLUSION

This is the first ever GWAS study in Basmati rice which could generate valuable information usable for further breeding through marker assisted selection, including enhancing of heterosis.

Skinny kelp (Saccharina angustissima) provides valuable genetics for the biomass improvement of farmed sugar kelp (Saccharina latissima)

Saccharina latissima (sugar kelp) is one of the most widely cultivated brown marine macroalgae species in the North Atlantic and the eastern North Pacific Oceans. To meet the expanding demands of the sugar kelp mariculture industry, selecting and breeding sugar kelp that is best suited to offshore farm environments is becoming necessary. To that end, a multi-year, multi-institutional breeding program was established by the U.S. Department of Energy's (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program. Hybrid sporophytes were generated using 203 unique gametophyte cultures derived from wild-collected Saccharina spp. for two seasons of farm trials (2019-2020 and 2020-2021). The wild sporophytes were collected from 10 different locations within the Gulf of Maine (USA) region, including both sugar kelp (Saccharina latissima) and the skinny kelp species (Saccharina angustissima). We harvested 232 common farm plots during these two seasons with available data. We found that farmed kelp plots with skinny kelp as parents had an average increased yield over the mean (wet weight 2.48 ± 0.90 kg m^-1 and dry weight 0.32 ± 0.10 kg m^-1) in both growing seasons. We also found that blade length positively correlated with biomass in skinny kelp x sugar kelp crosses or pure sugar kelp crosses. The skinny x sugar progenies had significantly longer and narrower blades than the pure sugar kelp progenies in both seasons. Overall, these findings suggest that sugar x skinny kelp crosses provide improved yield compared to pure sugar kelp crosses.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10811-022-02811-1.

Genetic and molecular factors in determining grain number per panicle of rice

It was suggested that the most effective way to improve rice grain yield is to increase the grain number per panicle (GN) through the breeding practice in recent decades. GN is a representative quantitative trait affected by multiple genetic and environmental factors. Understanding the mechanisms controlling GN has become an important research field in rice biotechnology and breeding. The regulation of rice GN is coordinately controlled by panicle architecture and branch differentiation, and many GN-associated genes showed pleiotropic effect in regulating tillering, grain size, flowering time, and other domestication-related traits. It is also revealed that GN determination is closely related to vascular development and the metabolism of some phytohormones. In this review, we summarize the recent findings in rice GN determination and discuss the genetic and molecular mechanisms of GN regulators.

Comparison between MR and CT imaging used to correct for skull-induced phase aberrations during transcranial focused ultrasound

Transcranial focused ultrasound with the InSightec Exablate system uses thermal ablation for the treatment of movement and mood disorders and blood brain barrier disruption for tumor therapy. The system uses computed tomography (CT) images to calculate phase corrections that account for aberrations caused by the human skull. This work investigates whether magnetic resonance (MR) images can be used as an alternative to CT images to calculate phase corrections. Phase corrections were calculated using the gold standard hydrophone method and the standard of care InSightec ray tracing method. MR binary image mask, MR-simulated-CT (MRsimCT), and CT images of three ex vivo human skulls were supplied as inputs to the InSightec ray tracing method. The degassed ex vivo human skulls were sonicated with a 670 kHz hemispherical phased array transducer (InSightec Exablate 4000). 3D raster scans of the beam profiles were acquired using a hydrophone mounted on a 3-axis positioner system. Focal spots were evaluated using six metrics: pressure at the target, peak pressure, intensity at the target, peak intensity, positioning error, and focal spot volume. Targets at the geometric focus and 5 mm lateral to the geometric focus were investigated. There was no statistical difference between any of the metrics at either target using either MRsimCT or CT for phase aberration correction. As opposed to the MRsimCT, the use of CT images for aberration correction requires registration to the treatment day MR images; CT misregistration within a range of ± 2 degrees of rotation error along three dimensions was shown to reduce focal spot intensity by up to 9.4%. MRsimCT images used for phase aberration correction for the skull produce similar results as CT-based correction, while avoiding both CT to MR registration errors and unnecessary patient exposure to ionizing radiation.

Modeling allelic diversity of multiparent mapping populations affects detection of quantitative trait loci

The search for quantitative trait loci that explain complex traits such as yield and drought tolerance has been ongoing in all crops. Methods such as biparental quantitative trait loci mapping and genome-wide association studies each have their own advantages and limitations. Multiparent advanced generation intercross populations contain more recombination events and genetic diversity than biparental mapping populations and are better able to estimate effect sizes of rare alleles than association mapping populations. Here, we discuss the results of using a multiparent advanced generation intercross population of doubled haploid maize lines created from 16 diverse founders to perform quantitative trait loci mapping. We compare 3 models that assume bi-allelic, founder, and ancestral haplotype allelic states for quantitative trait loci. The 3 methods have differing power to detect quantitative trait loci for a variety of agronomic traits. Although the founder approach finds the most quantitative trait loci, all methods are able to find unique quantitative trait loci, suggesting that each model has advantages for traits with different genetic architectures. A closer look at a well-characterized flowering time quantitative trait loci, qDTA8, which contains vgt1, highlights the strengths and weaknesses of each method and suggests a potential epistatic interaction. Overall, our results reinforce the importance of considering different approaches to analyzing genotypic datasets, and shows the limitations of binary SNP data for identifying multiallelic quantitative trait loci.

Back to the wild: mining maize (Zea mays L.) disease resistance using advanced breeding tools

Cultivated modern maize (Zea mays L.) originated through the continuous process of domestication from its wild progenitors. Today, maize is considered as the most important cereal crop which is extensively cultivated in all parts of the world. Maize shows remarkable genotypic and phenotypic diversity which makes it an ideal model species for crop genetic research. However, intensive breeding and artificial selection of desired agronomic traits greatly narrow down the genetic bases of maize. This reduction in genetic diversity among cultivated maize led to increase the chance of more attack of biotic stress as climate changes hampering the maize grain production globally. Maize germplasm requires to integrate both durable multiple-diseases and multiple insect-pathogen resistance through tapping the unexplored resources of maize landraces. Revisiting the landraces seed banks will provide effective opportunities to transfer the resistant genes into the modern cultivars. Here, we describe the maize domestication process and discuss the unique genes from wild progenitors which potentially can be utilized for disease resistant in maize. We also focus on the genetics and disease resistance mechanism of various genes against maize biotic stresses and then considered the different molecular breeding tools for gene transfer and advanced high resolution mapping for gene pyramiding in maize lines. At last, we provide an insight for targeting identified key genes through CRISPR/Cas9 genome editing system to enhance the maize resilience towards biotic stress.

Goyal A, Chaudhury A. Molecular and Transcriptional Regulation of Seed Development in Cereals: Present Status and Future Prospects

Cereals are a rich source of vitamins, minerals, carbohydrates, fats, oils and protein, making them the world’s most important source of nutrition. The influence of rising global population, as well as the emergence and spread of disease, has the major impact on cereal production. To meet the demand, there is a pressing need to increase cereal production. Optimal seed development is a key agronomical trait that contributes to crop yield. The seed development and maturation is a complex process that includes not only embryo and endosperm development, but also accompanied by huge physiological, biochemical, metabolic, molecular and transcriptional changes. This chapter discusses the growth of cereal seed and highlights the novel biological insights, with a focus on transgenic and new molecular breeding, as well as biotechnological intervention strategies that have improved crop yield in two major cereal crops, primarily wheat and rice, over the last 21 years (2000–2021).

Mapping novel QTLs for yield related traits from a popular rice hybrid KRH-2 derived doubled haploid (DH) population

A doubled haploid (DH) population consisting of 125 DHLs derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R) was utilized for Quantitative Trait Loci (QTL) mapping to identify novel genomic regions associated with yield related traits. A genetic map was constructed with 126 polymorphic SSR and EST derived markers, which were distributed across rice genome. QTL analysis using inclusive composite interval mapping (ICIM) method identified a total of 24 major and minor effect QTLs. Among them, twelve major effect QTLs were identified for days to fifty percent flowering (qDFF12-1), total grain yield/plant (qYLD3-1 and qYLD6-1), test (1,000) grain weight (qTGW6-1 and qTGW7-1), panicle weight (qPW9-1), plant height (qPH12-1), flag leaf length (qFLL6-1), flag leaf width (qFLW4-1), panicle length (qPL3-1 and qPL6-1) and biomass (qBM4-1), explaining 29.95-56.75% of the phenotypic variability with LOD scores range of 2.72-16.51. Chromosomal regions with gene clusters were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1) and on chromosome 6 for total grain yield/plant (qYLD6-1), flag leaf length (qFLL6-1) and panicle length (qPL6-1). Majority of the QTLs identified were observed to be co-localized with the previously reported QTL regions. Five novel, major effect QTLs associated with panicle weight (qPW9-1), plant height (qPH12-1), flag leaf width (qFLW4-1), panicle length (qPL3-1) and biomass (qBM4-1) and three novel minor effect QTLs for panicle weight (qPW3-1 and qPW8-1) and fertile grains per panicle (qFGP5-1) were identified. These QTLs can be used in breeding programs aimed to yield improvement after their validation in alternative populations.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-03045-7.

Identification of genomic loci regulating grain iron content in aus rice under two irrigation management systems

Iron (Fe) deficiency is one of the common causes of anaemia in humans. Improving grain Fe in rice, therefore, could have a positive impact for humans worldwide, especially for those people who consume rice as a staple food. In this study, 225–269 accessions of the Bengal and Assam Aus Panel (BAAP) were investigated for their accumulation of grain Fe in two consecutive years in a field experiment under alternative wetting and drying (AWD) and continuous flooded (CF) irrigation. AWD reduced straw Fe by 40% and grain Fe by 5.5–13%. Genotype differences accounted for 35% of the variation in grain Fe, while genotype by irrigation interaction accounted for 12% of the variation in straw and grain Fe in year 1, with no significant interactions detected in year 2. Twelve rice accessions were identified as having high grain Fe for both years regardless of irrigation treatment, half of which were from BAAP aus subgroup 3 which prominently comes from Bangladesh. On average, subgroup 3 had higher grain Fe than the other four subgroups of aus. Genome‐wide association mapping identified 6 genomic loci controlling natural variation of grain Fe concentration in plants grown under AWD. For one QTL, nicotianamine synthase OsNAS3 is proposed as candidate for controlling natural variation of grain Fe in rice. The BAAP contains three haplotypes of OsNAS3 where one haplotype (detected in 31% of the individuals) increased grain Fe up to 11%. Haplotype analysis of this gene in rice suggests that the ability to detect the QTL is enhanced in the BAAP because the high Fe allele is balanced in aus, unlike indica and japonica subgroups.

Genomic Prediction of Grain Yield in a Barley MAGIC Population Modeling Genotype per Environment Interaction

Multi-parent Advanced Generation Inter-crosses (MAGIC) lines have mosaic genomes that are generated shuffling the genetic material of the founder parents following pre-defined crossing schemes. In cereal crops, these experimental populations have been extensively used to investigate the genetic bases of several traits and dissect the genetic bases of epistasis. In plants, genomic prediction models are usually fitted using either diverse panels of mostly unrelated accessions or individuals of biparental families and several empirical analyses have been conducted to evaluate the predictive ability of models fitted to these populations using different traits. In this paper, we constructed, genotyped and evaluated a barley MAGIC population of 352 individuals developed with a diverse set of eight founder parents showing contrasting phenotypes for grain yield. We combined phenotypic and genotypic information of this MAGIC population to fit several genomic prediction models which were cross-validated to conduct empirical analyses aimed at examining the predictive ability of these models varying the sizes of training populations. Moreover, several methods to optimize the composition of the training population were also applied to this MAGIC population and cross-validated to estimate the resulting predictive ability. Finally, extensive phenotypic data generated in field trials organized across an ample range of water regimes and climatic conditions in the Mediterranean were used to fit and cross-validate multi-environment genomic prediction models including G×E interaction, using both genomic best linear unbiased prediction and reproducing kernel Hilbert space along with a non-linear Gaussian Kernel. Overall, our empirical analyses showed that genomic prediction models trained with a limited number of MAGIC lines can be used to predict grain yield with values of predictive ability that vary from 0.25 to 0.60 and that beyond QTL mapping and analysis of epistatic effects, MAGIC population might be used to successfully fit genomic prediction models. We concluded that for grain yield, the single-environment genomic prediction models examined in this study are equivalent in terms of predictive ability while, in general, multi-environment models that explicitly split marker effects in main and environmental-specific effects outperform simpler multi-environment models.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.

Bin-based genome-wide association studies reveal superior alleles for improvement of appearance quality using a 4-way MAGIC population in rice

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4-way Multiparental population covered the limitations of the biparental structure.

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The combination of SNP and bin-GWAS showed a powerful tool for QTL mapping.

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qPGWC8.2 harbored a novel predicted gene for rice chalkiness quality.

Introduction

The multiparental population provides us the chance to identify superior alleles controlling a trait for genetic improvement. Genome wide association studies at bin level (bin-GWAS) are expected to be more power in QTL mapping than GWAS at SNP level (SNP-GWAS).

Objectives

This study is to estimate genetic effects of QTL conferring grain appearance quality in rice by SNP-GWAS and bin-GWAS, compare their power in QTL mapping and identify the superior alleles of all detected QTL from 4 parents for genetic improvement.

Methods

A 4-way MAGIC population and its four founders were cultivated in two environments to dissect the genetic basis of rice grain appearance quality. Both SNP-GWAS and bin-GWAS were conducted for QTL mapping. Multiple comparison among 4 parental bin/alleles was used to identify the superior alleles.

Results

A total of 16 and 20 QTL associated with grain appearance quality were identified by SNP- and bin-GWAS, respectively. A minor chalkiness QTL qPGWC8.2/qDEC8 was assigned to a 30-kb genomic region, in which OsMH_08T0121900 is the potential candidate gene because its encoded protein, glucan endo-1,3-beta-glucosidase precursor is involved in the starch and sucrose metabolism pathway. The superior parental alleles for GS3, GL3.1, GW5, GW7, and Chalk5 and two QTLs were almost carried by the high-quality parents Cypress and Yuejingsimiao (YJSM), while the poor-quality parent Guichao-2 (GC2) always carried the inferior alleles. The top five recombinant inbred lines with the highest quality of grain shape and chalkiness traits all carried gene combinations of superior alleles.

Conclusions

Both SNP- and bin-GWAS methods are encouraged for joint QTL mapping with MAGIC population. qPGWC8.2/qDEC8 is a novel candidate gene strongly associated with chalkiness. The superior alleles of GS3, GW5, GL3.1, GW7, Chalk5 and qPGWC8.2 were identified, and the pyramiding of these superior alleles is helpful to improve rice appearance quality.

A, Chakraborty A, Thirunavukkarasu N. Multiple Genome Wide Association Mapping Models Identify Quantitative Trait Nucleotides for Brown Planthopper (Nilaparvata lugens) Resistance in MAGIC Indica Population of Rice

Brown planthopper (BPH), one of the most important pests of the rice (Oryza sativa) crop, becomes catastrophic under severe infestations and causes up to 60% yield loss. The highly disastrous BPH biotype in the Indian sub-continent is Biotype 4, which also known as the South Asian Biotype. Though many resistance genes were mapped until now, the utility of the resistance genes in the breeding programs is limited due to the breakdown of resistance and emergence of new biotypes. Hence, to identify the resistance genes for this economically important pest, we have used a multi-parent advanced generation intercross (MAGIC) panel consisting of 391 lines developed from eight indica founder parents. The panel was phenotyped at the controlled conditions for two consecutive years. A set of 27,041 cured polymorphic single nucleotide polymorphism (SNPs) and across-year phenotypic data were used for the identification of marker–trait associations. Genome-wide association analysis was performed to find out consistent associations by employing four single and two multi-locus models. Sixty-one SNPs were consistently detected by all six models. A set of 190 significant marker-associations identified by fixed and random model circulating probability unification (FarmCPU) were considered for searching resistance candidate genes. The highest number of annotated genes were found in chromosome 6 followed by 5 and 1. Ninety-two annotated genes identified across chromosomes of which 13 genes are associated BPH resistance including NB-ARC (nucleotide binding in APAF-1, R gene products, and CED-4) domain-containing protein, NHL repeat-containing protein, LRR containing protein, and WRKY70. The significant SNPs and resistant lines identified from our study could be used for an accelerated breeding program to develop new BPH resistant cultivars.

The Dawn of the Age of Multi-Parent MAGIC Populations in Plant Breeding: Novel Powerful Next-Generation Resources for Genetic Analysis and Selection of Recombinant Elite Material

The compelling need to increase global agricultural production requires new breeding approaches that facilitate exploiting the diversity available in the plant genetic resources. Multi-parent advanced generation inter-cross (MAGIC) populations are large sets of recombinant inbred lines (RILs) that are a genetic mosaic of multiple founder parents. MAGIC populations display emerging features over experimental bi-parental and germplasm populations in combining significant levels of genetic recombination, a lack of genetic structure, and high genetic and phenotypic diversity. The development of MAGIC populations can be performed using “funnel” or “diallel” cross-designs, which are of great relevance choosing appropriate parents and defining optimal population sizes. Significant advances in specific software development are facilitating the genetic analysis of the complex genetic constitutions of MAGIC populations. Despite the complexity and the resources required in their development, due to their potential and interest for breeding, the number of MAGIC populations available and under development is continuously growing, with 45 MAGIC populations in different crops being reported here. Though cereals are by far the crop group where more MAGIC populations have been developed, MAGIC populations have also started to become available in other crop groups. The results obtained so far demonstrate that MAGIC populations are a very powerful tool for the dissection of complex traits, as well as a resource for the selection of recombinant elite breeding material and cultivars. In addition, some new MAGIC approaches that can make significant contributions to breeding, such as the development of inter-specific MAGIC populations, the development of MAGIC-like populations in crops where pure lines are not available, and the establishment of strategies for the straightforward incorporation of MAGIC materials in breeding pipelines, have barely been explored. The evidence that is already available indicates that MAGIC populations will play a major role in the coming years in allowing for impressive gains in plant breeding for developing new generations of dramatically improved cultivars.

Molecular mapping of QTLs for yield related traits in recombinant inbred line (RIL) population derived from the popular rice hybrid KRH-2 and their validation through SNP genotyping

The study was undertaken to identify the quantitative trait loci (QTLs) governing yield and its related traits using a recombinant inbred line (RIL) population derived from the popular rice hybrid, KRH-2 (IR58025A/KMR3R). A genetic map spanning 294.2 cM was constructed with 126 simple sequence repeats (SSR) loci uniformly distributed across the rice genome. QTL analysis using phenotyping and genotyping information identified a total of 22 QTLs. Of these, five major effect QTLs were identified for the following traits: total grain yield/plant (qYLD3-1), panicle weight (qPW3-1), plant height (qPH12-1), flag leaf width (qFLW4-1) and panicle length (qPL3-1), explaining 20.23–22.76% of the phenotypic variance with LOD scores range of 6.5–10.59. Few genomic regions controlling several traits (QTL hotspot) were identified on chromosome 3 for total grain yield/plant (qYLD3-1) and panicle length (qPL3-1). Significant epistatic interactions were also observed for total grain yield per plant (YLD) and panicle length (PL). While most of these QTLs were observed to be co-localized with the previously reported QTL regions, a novel, major QTL associated with panicle length (qPL3-1) was also identified. SNP genotyping of selected high and low yielding RILs and their QTL mapping with 1,082 SNPs validated most of the QTLs identified through SSR genotyping. This facilitated the identification of novel major effect QTLs with much better resolution and precision. In-silico analysis of novel QTLs revealed the biological functions of the putative candidate gene (s) associated with selected traits. Most of the high-yielding RILs possessing the major yield related QTLs were identified to be complete restorers, indicating their possible utilization in development of superior rice hybrids.