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42 results for “Oryza sativa L.”
Determination of traits responding to iron toxicity stress at different stages and genome-wide association analysis for iron toxicity tolerance in rice (Oryza sativa L.)
<p>This vcf file constitute underlying raw data material for the manuscript "Determination of traits responding to iron toxicity stress at different stages and genome-wide association analysis for iron toxicity tolerance in rice (Oryza sativa L.)". <br> The SNP genotype data came from a whole-genome resequencing and were called using the Nipponbare IRGSP 1.0 rice reference genome. SNPs with a miss rate greater than 30% and minor allele frequency (MAF) less than 5% were removed. Heterozygous alleles were also excluded. Finally, 160,498 SNPs were selected and used in the GWAS analysis. </p>
Oryza sativa L. (BR0000025022612)
Belgium Herbarium image of <a href="https://www.plantentuinmeise.be">Meise Botanic Garden</a>.
Vegetative biomass production under different inorganic nitrogen forms of the USDA rice (Oryza sativa L.) diversity panel 1
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Data from: Identification and analysis of novel salt responsive candidate gene based SSRs (cgSSRs) from rice (Oryza sativa L.)
Background: Majority of the Asian people depend on rice for nutritional energy. Rice cultivation and yield are severely affected by soil salinity stress worldwide. Marker assisted breeding is a rapid and efficient way to develop improved variety for salinity stress tolerance. Genomic microsatellite markers are an elite group of markers, but there is possible uncertainty of linkage with the important genes. In contrast, there are better possibilities of linkage detection with important genes if SSRs are developed from candidate genes. To the best of our knowledge, there is no such report on SSR markers development from candidate gene sequences in rice. So the present study was aimed to identify and analyse SSRs from salt responsive candidate genes of rice. Results: In the present study, based on the comprehensive literature survey, we selected 220 different salt responsive genes of rice. Out of them, 106 genes were found to contain 180 microsatellite loci with, tri-nucleotide motifs (56%) being most abundant, followed by di-(41%) and tetra nucleotide (2.8%) motifs. Maximum loci were found in the coding sequences (37.2%), followed by in 5′UTR (26%), intron (21.6%) and 3′UTR (15%). For validation, 19 primer sets were evaluated to detect polymorphism in diversity analysis among the two panels consisting of 17 salt tolerant and 17 susceptible rice genotypes. Except one, all primer sets exhibited polymorphic nature with an average of 21.8 alleles/primer and with a mean PIC value of 0.28. Calculated genetic similarity among genotypes was ranged from 19%-89%. The generated dendrogram showed 3 clusters of which one contained entire 17 susceptible genotypes and another two clusters contained all tolerant genotypes. Conclusion: The present study represents the potential of salt responsive candidate gene based SSR (cgSSR) markers to be utilized as novel and remarkable candidate for diversity analysis among rice genotypes differing in salinity response.
Identification of genetic loci and functional analysis of candidate gene, OsCycB1;5 associated with seed callus induction in rice (Oryza sativa L.)
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Effect of Oryza Sativa l Extract to LPS, ZO-1, and Intestinal Microbiota in Obese Individuals
ClinicalTrials.gov study NCT04827628. IPD Sharing: NO. Countries: 1. Publications: 11.
Data from: Identification, characterization, and transcription analysis of xylogen-like arabinogalactan proteins in rice (Oryza sativa L.)
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Data from: Identification and analysis of novel salt responsive candidate gene based SSRs (cgSSRs) from rice (Oryza sativa L.)
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Figure 2 from: Hartati FK, Nafisah W, Sutanto A, Saati EA, Khairoh M, Sjamsiah (2024) Aqueous black rice (Oryza sativa L. indica) extract enhanced the activation of CD4+ and CD8+ T cells in mouse breast cancer model. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e113442
Figure 2 Aqueous black rice (ABR) extract reduced the relative number of CD4+IL17+, CD4+TNFα+, and CD4+IFNγ+ cytokine production. A, C, E. were flow cytometry diagram; B, D, F. were the graph of flow cytometry results. The bar in the graph shows the calculation results as the mean ± SD of the relative number of cytokine production. *P<0.05, indicate significant different. The group in this study were normal group; Cancer, DMBA 15 mg/kg BW; Cis, DMBA 15 mg/kg BW + Cisplatin 5 mg/kg BW; ABR1, DMBA 15 mg/kg BW + aqueous black rice extract 0.2 g/kg BW; ABR2, DMBA 15 mg/kg BW + aqueous black rice extract 0.3 g/kg BW; ABR3, DMBA 15 mg/kg BW + aqueous black rice extract 0.4 g/kg BW; ABR4, DMBA 15 mg/kg BW + aqueous black rice extract 0.5 g/kg BW.
Figure 1 from: Hartati FK, Nafisah W, Sutanto A, Saati EA, Khairoh M, Sjamsiah (2024) Aqueous black rice (Oryza sativa L. indica) extract enhanced the activation of CD4+ and CD8+ T cells in mouse breast cancer model. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e113442
Figure 1 Aqueous black rice (ABR) extract increased the relative number of CD4+CD62L- cells and CD8+CD62L- cells. A, C. Show flow cytometry diagrams, and B, D. Show graphs of the flow cytometry results. The bars in the graphs show the calculated results as the mean ± SD of the relative number of CD4+ and CD8+ cell activations. *P<0.05 indicates a significant difference. The groups in this study included the following groups: Normal; Cancer, DMBA 15 mg/kg BW; Cis, DMBA 15 mg/kg BW + Cisplatin 5 mg/kg BW; ABR1, DMBA 15 mg/kg BW + ABR extract 0.2 g/kg BW; ABR2, DMBA 15 mg/kg BW + ABR extract 0.3 g/kg BW; ABR3, DMBA 15 mg/kg BW + ABR extract 0.4 g/kg BW; and ABR4, DMBA 15 mg/kg BW + ABR extract 0.5 g/kg BW.
Figure 3 from: Hartati FK, Nafisah W, Sutanto A, Saati EA, Khairoh M, Sjamsiah (2024) Aqueous black rice (Oryza sativa L. indica) extract enhanced the activation of CD4+ and CD8+ T cells in mouse breast cancer model. Pharmacia 71: 1-7. https://doi.org/10.3897/pharmacia.71.e113442
Figure 3 Aqueous black rice (ABR) extract effect on mammary mice histology based on Hematoxylin & Eosin staining (M: 400x). D, ductal; AT, adipose tissue; arrow, cancer cell. The group in this study were normal group; Cancer, DMBA 15 mg/kg BW; Cis, DMBA 15 mg/kg BW + Cisplatin 5 mg/kg BW; ABR1, DMBA 15 mg/kg BW + aqueous black rice extract 0.2 g/kg BW; ABR2, DMBA 15 mg/kg BW + aqueous black rice extract 0.3 g/kg BW; ABR3, DMBA 15 mg/kg BW + aqueous black rice extract 0.4 g/kg BW; ABR4, DMBA 15 mg/kg BW + aqueous black rice extract 0.5 g/kg BW.
Effect of planting density on growth characteristics and grain yield increase in successive cultivations of two rice (Oryza sativa L.) cultivars
<p><span>Rice (<i>Oryza sativa</i> L.) re-cultivation plays an important role in increasing land productivity and efficiency in crop rotation. Planting density (PD) is an important agronomic factor to achieving maximum grain yield (GY). The current study aimed to determine the best PD for the first cultivation and re-cultivation of rice. The experiment was conducted as a split plot based on the randomized complete block design with three replications at Ghaemshahr University, Mazandaran (northern Iran) from 2013 to 2014. Treatments consisted of cultivar, i.e. Tarom Hashemi and Koohsar, at two levels as the main factor and PDs at the three levels of 16, 25, and 33.3 hills m<sup>-2</sup> with planting spaces of 25 × 25, 20 × 20, and 30 × 10 cm<sup>2</sup>, respectively, as the sub factor. The results of the current study showed that cultivar for the first cultivation, and year for the re-cultivation had a significant effect on GY. PD had a significant effect on GY in both first cultivation and re-cultivation. The GY of Hashemi in the first cultivation (36.1%) and re-cultivation (18.5%) was higher than that of Koohsar. GY in the first cultivation and re-cultivation had an increasing trend; PD increased up to 33.3 hills m<sup>-2</sup> as 19.9% and 21.4% in the first cultivation and re-cultivation, respectively, due to the increase in number of panicles m<sup>-2</sup> (30.1% and 30.6%, respectively). Hashemi is suitable for the first cultivation. It is noteworthy, also, that a density of 33.3 hills m<sup>-2</sup> is recommended for the first cultivation and re-cultivation.</span></p>
Data from: Hybrid breakdown caused by epistasis-based recessive incompatibility in a cross of rice (Oryza sativa L.)
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Effect of planting density on growth characteristics and grain yield increase in successive cultivations of two rice (Oryza sativa L.) cultivars
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Comparative transcript profiling of alloplasmic male-sterile lines revealed altered gene expression related to pollen development in rice (Oryza sativa L.)
GEO Series GSE79712. Oryza sativa. 8 samples. Type: Expression profiling by array.
Analysis of genome-wide copy number variations in Oryza sativa L.
GEO Series GSE42769. Oryza sativa; Oryza sativa Indica Group; Oryza sativa Japonica Group. 21 samples. Type: Genome variation profiling by genome tiling array.
DNA demethylation activates genes in seed maternal integument development in rice (Oryza sativa L.)
GEO Series GSE95107. Oryza sativa. 6 samples. Type: Methylation profiling by high throughput sequencing.
Identification of Genes and miRNAs Affecting Pre-harvest Sprouting in Rice (Oryza sativa L.) by Transcriptome and Small RNAome Analyses
GEO Series GSE174017. Oryza sativa. 24 samples. Type: Expression profiling by high throughput sequencing.
Genome-wide identification of Drought-responsive Regulatory Coding and Non-coding Transcripts from Oryza sativa L. by deep RNA sequencing
GEO Series GSE74465. Oryza sativa Indica Group. 27 samples. Type: Expression profiling by high throughput sequencing; Non-coding RNA profiling by high throughput sequencing.
Comparative transcriptomics and co-expression networks reveal tissue- and genotype-specific responses to reproductive-stage drought stress in rice (Oryza sativa L.) [panicle]
GEO Series GSE145869. Oryza sativa. 16 samples. Type: Expression profiling by high throughput sequencing.
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