42 research outputs found

    Evaluating rice germplasm for iron and zinc concentration in brown rice and seed dimensions

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    The lack of micronutrients such as Fe and Zn in staple food crops is a widespread nutrition and health problem in developing countries. Biofortification is one of the sustainable approaches, for improving the Fe and Zn content and their bioavailability in rice grain. Screening germplasm for Fe and Zn content is the initial step of biofortification. We analyzed brown rice of 126 accessions of rice genotypes for Fe and Zn concentration. Iron concentration ranged from 6.2 ppm to 71.6 ppm and zinc from 26.2 ppm to 67.3 ppm. Zn concentration and grain elongation (-0.25) was significantly correlated. The wild accessions had the highest Fe and Zn. Thus, wild species are a good source for biofortification of popular rice cultivars using conventional, acceptable, non transgenic methods. Â

    Genome-Wide Association Mapping in a Rice MAGIC Plus Population Detects QTLs and Genes Useful for Biofortification

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    The development of rice genotypes with micronutrient-dense grains and disease resistance is one of the major priorities in rice improvement programs. We conducted Genome-wide association studies (GWAS) using a Multi-parent Advanced Generation Inter-Cross (MAGIC) Plus population to identify QTLs and SNP markers that could potentially be integrated in biofortification and disease resistance breeding. We evaluated 144 MAGIC Plus lines for agronomic and biofortification traits over two locations for two seasons, while disease resistance was screened for one season in the screen house. X-ray fluorescence technology was used to measure grain Fe and Zn concentrations. Genotyping was carried out by genotype by sequencing and a total of 14,242 SNP markers were used in the association analysis. We used Mixed linear model (MLM) with kinship and detected 57 significant genomic regions with a -log10 (P-value) ≥ 3.0. The PH1.1 and Zn7.1 were consistently identified in all the four environments, ten QTLs qDF3.1, qDF6.2qDF9.1qPH5.1qGL3.1, qGW3.1, qGW11.1, and qZn6.2 were detected in two environments, while two major loci qBLB11.1 and qBLB5.1 were identified for Bacterial Leaf Blight (BLB) resistance. The associated SNP markers were found to co-locate with known major genes and QTLs such as OsMADS50 for days to flowering, osGA20ox2 for plant height, and GS3 for grain length. Similarly, Xa4 and xa5 genes were identified for BLB resistance and Pi5(t), Pi28(t), and Pi30(t) genes were identified for Blast resistance. A number of metal homeostasis genes OsMTP6, OsNAS3, OsMT2D, OsVIT1, and OsNRAMP7 were co-located with QTLs for Fe and Zn. The marker-trait relationships from Bayesian network analysis showed consistency with the results of GWAS. A number of promising candidate genes reported in our study can be further validated. We identified several QTLs/genes pyramided lines with high grain Zn and acceptable yield potential, which are a good resource for further evaluation to release as varieties as well as for use in breeding programs

    Molecular dissection of connected rice populations revealed important genomic regions for agronomic and biofortification traits

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    Breeding staple crops with increased micronutrient concentration is a sustainable approach to address micronutrient malnutrition. We carried out Multi-Cross QTL analysis and Inclusive Composite Interval Mapping for 11 agronomic, yield and biofortification traits using four connected RILs populations of rice. Overall, MC-156 QTLs were detected for agronomic (115) and biofortification (41) traits, which were higher in number but smaller in effects compared to single population analysis. The MC-QTL analysis was able to detect important QTLs viz: qZn5.2, qFe7.1, qGY10.1, qDF7.1, qPH1.1, qNT4.1, qPT4.1, qPL1.2, qTGW5.1, qGL3.1, and qGW6.1, which can be used in rice genomics assisted breeding. A major QTL (qZn5.2) for grain Zn concentration has been detected on chromosome 5 that accounted for 13% of R2. In all, 26 QTL clusters were identified on different chromosomes. qPH6.1 epistatically interacted with qZn5.1 and qGY6.2. Most of QTLs were co-located with functionally related candidate genes indicating the accuracy of QTL mapping. The genomic region of qZn5.2 was co-located with putative genes such as OsZIP5, OsZIP9, and LOC_OS05G40490 that are involved in Zn uptake. These genes included polymorphic functional SNPs, and their promoter regions were enriched with cis-regulatory elements involved in plant growth and development, and biotic and abiotic stress tolerance. Major effect QTL identified for biofortification and agronomic traits can be utilized in breeding for Zn biofortified rice varieties

    Variation in grain Zn concentration, and the grain ionome, in field-grown Indian wheat

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    Wheat is an important dietary source of zinc (Zn) and other mineral elements in many countries. Dietary Zn deficiency is widespread, especially in developing countries, and breeding (genetic biofortification) through the HarvestPlus programme has recently started to deliver new wheat varieties to help alleviate this problem in South Asia. To better understand the potential of wheat to alleviate dietary Zn deficiency, this study aimed to characterise the baseline effects of genotype (G), site (E), and genotype by site interactions (GxE) on grain Zn concentration under a wide range of soil conditions in India. Field experiments were conducted on a diverse panel of 36 Indian-adapted wheat genotypes, grown on a range of soil types (pH range 4.5–9.5), in 2013–14 (five sites) and 2014–15 (six sites). Grain samples were analysed using inductively coupled plasma-mass spectrometry (ICP-MS). The mean grain Zn concentration of the genotypes ranged from 24.9–34.8 mg kg-1, averaged across site and year. Genotype and site effects were associated with 10% and 6% of the overall variation in grain Zn concentration, respectively. Whilst G x E interaction effects were evident across the panel, some genotypes had consistent rankings between sites and years. Grain Zn concentration correlated positively with grain concentrations of iron (Fe), sulphur (S), and eight other elements, but did not correlate negatively with grain yield, i.e. no yield dilution was observed. Despite a relatively small contribution of genotype to the overall variation in grain Zn concentration, due to experiments being conducted across many contrasting sites and two years, our data are consistent with reports that biofortifying wheat through breeding is likely to be effective at scale given that some genotypes performed consistently across diverse soil types. Notably, all soils in this study were probably Zn deficient and interactions between wheat genotypes and soil Zn availability/management (e.g. the use of Zn-containing fertilisers) need to be better-understood to improve Zn supply in food systems

    Tolerance of Iron-Deficient and -Toxic Soil Conditions in Rice

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    Iron (Fe) deficiency and toxicity are the most widely prevalent soil-related micronutrient disorders in rice (Oryza sativa L.). Progress in rice cultivars with improved tolerance has been hampered by a poor understanding of Fe availability in the soil, the transportation mechanism, and associated genetic factors for the tolerance of Fe toxicity soil (FTS) or Fe deficiency soil (FDS) conditions. In the past, through conventional breeding approaches, rice varieties were developed especially suitable for low- and high-pH soils, which indirectly helped the varieties to tolerate FTS and FDS conditions. Rice-Fe interactions in the external environment of soil, internal homeostasis, and transportation have been studied extensively in the past few decades. However, the molecular and physiological mechanisms of Fe uptake and transport need to be characterized in response to the tolerance of morpho-physiological traits under Fe-toxic and -deficient soil conditions, and these traits need to be well integrated into breeding programs. A deeper understanding of the several factors that influence Fe absorption, uptake, and transport from soil to root and above-ground organs under FDS and FTS is needed to develop tolerant rice cultivars with improved grain yield. Therefore, the objective of this review paper is to congregate the different phenotypic screening methodologies for prospecting tolerant rice varieties and their responsible genetic traits, and Fe homeostasis related to all the known quantitative trait loci (QTLs), genes, and transporters, which could offer enormous information to rice breeders and biotechnologists to develop rice cultivars tolerant of Fe toxicity or deficiency. The mechanism of Fe regulation and transport from soil to grain needs to be understood in a systematic manner along with the cascade of metabolomics steps that are involved in the development of rice varieties tolerant of FTS and FDS. Therefore, the integration of breeding with advanced genome sequencing and omics technologies allows for the fine-tuning of tolerant genotypes on the basis of molecular genetics, and the further identification of novel genes and transporters that are related to Fe regulation from FTS and FDS conditions is incredibly important to achieve further success in this aspect

    Alteration in pre-operative and post-operative lipid profile – in carcinoma breast

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    Background: There is no single etiological factor or risk factor for carcinoma breast, it has been shown to have multiple risk factors. One such risk factor that is being widely accepted is that poor living conditions is associated with carcinoma cervix while carcinoma breast is seen more commonly in societies with better living conditions. In our study we wish to study the correlation between lipid profile and carcinoma breast. Methods: This was an observational prospective correlational study. Fasting lipid profile, after 12 hours of (fasting 9pm to 9am) was done on the day after admission and on the 7th postoperative day. Result:The change in the pre and post operative lipid profile was not statistically significant for any of the lipid profile parameters. Conclusion: In our study we did not find any statistically significant Change in the lipid parameters pre and post operatively, thus showing that the removal of the primary tumor does have any effect on the lipid profile
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