Rice Genotyping
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Project description:In this study, we aim to generate genome-scale DNA methylation profiles at single-base resolution in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. Using high-throughput whole genome bisulfite Sequencing, we generated DNA methylation maps covering the vast majority of cytosines in the rice genome. More than 152 million high quality reads were obtained for each tissue sample using Illumina platform. We discovered extensive DNA methylation in rice cultivars, identified the context and level of methylation at each site.Numerous differentially methylated regions (DMRs) among different cultivars under control and stress conditions were identified and many of them were associated with differential gene expression. The high resolution methylome maps of different rice genotypes and differentially methylated regions will serve as reference for understanding the epigenetic regulation of stress responses in plants. Whole genome bisulfite sequencing of seven control/stressed samples from three rice cultivars (IR64, N22 and Pokkali)
2015-12-31 | E-GEOD-60288 | biostudies-arrayexpress
Project description:Genotyping arrays are tools for high throughput genotyping, which is required in genome-wide association studies (GWAS). Since the first cucumber genome draft was reported, genetic maps were constructed mainly based on simple-sequence repeats (SSRs) or on combinations of SSRs and other sequence-related amplified polymorphism (SRAP). In this study we developed the first cucumber genotyping array which consisted of 32,864 single nucleotide polymorphisms (SNPs). These markers cover the cucumber genome every 2.1Kb and have parents/F1 hybridizations as a training set. The training set was validated with Fludigm technology and had 98% concordance. The application of the genotyping array was illustrated by constructed a genetic map of 600 cM in length based on recombinant inbred lines (RIL) population of a 9930XGy14 cross of which compromise of 11564 SNPs. The markers collinearity between the genetic map and genome references of the two parents estimated as R2=0.97. Moreover, this comparison supports a translocation in the beginning of chromosome 5 that occurred in the lineage of 9930 and Gy14 as well as local variation in the recombination rate. We also used the array to investigate the local allele frequencies along the cucumber genome and found specific region with segregation distortions. We believe that the genotyping array together with the training set would be a powerful tool in applications such as quantitative-trait loci (QTL) analysis and GWAS.
2015-05-01 | GSE57294 | GEO
Project description:The publicly available genome sequence information of two rice strains, japonica cultivar Nipponbare and indica cultivar 93-11, opens a great opportunity for investigation of performances DNA genotyping by high-density oligonucleotide arrays. Here, we compare single feature polymorphism (SFP) detection performances between whole genome hybridization and transcript hybridization using Affymetrix Rice Expression Array and the two rice cultivars.
2010-06-01 | GSE16341 | GEO
Project description:Rice is the most salt sensitive cereal crop and its cultivation is particularly threatened by salt stress. This study reports the development of salt tolerant introgressed lines (ILs) derived from crosses between the salt tolerant indica rice variety FL478, which harbors the Saltol QTL, and the salt-sensitive japonica elite cultivar PL12. Although the introgression of the Saltol QTL has been widely used to improve salinity tolerance, the molecular basis underlying the salinity tolerance conferred by Saltol remains poorly understood. Equally, the impact of introgressions from a Saltol donor parent on the global transcriptome of ILs is largely unknown. Here, genotyping-by-sequencing (GBS) and Kompetitive allele specific PCR (KASP) genotyping, in combination with step-wise phenotypic selection in hydroponic culture, were used for the identification of salt-tolerant ILs. Transcriptome-based genotyping allowed the fine mapping of indica genetic introgressions in the best performing IL line (IL22). A total of 1,595 genes were identified in indica regions in IL22, which mainly located in large introgressions at Chromosomes 1 and 3. In addition to OsHKT1;5, an important number of genes potentially contributing to salt stress tolerance were identified in indica segments of IL22. Comparative transcript profiling also revealed important transcriptional reprograming in IL22 plants both under non-stress and salt-stress conditions, indicating an impact on the transcriptome of the japonica background by the indica introgressed genes and vice versa. Interactions among indica and japonica genes would provide novel regulatory networks contributing to salt stress tolerance in introgression rice lines.
2021-12-20 | GSE167342 | GEO
Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone H3 trimethylation in rice endosperm. By obtaining about four hundred million bases of sequence from rice chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of rice endosperm. We find that the presence of H3K27me3 in either upstream or downstream of a gene is predominately associated with repression of the gene, while its absence is mainly associated with high gene expression. Examination of Histone H3 lysine 27 trimethylation in rice endosperm.
2011-12-06 | E-GEOD-27048 | biostudies-arrayexpress
Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of histone H3 trimethylation in rice endosperm. By obtaining about four hundred million bases of sequence from rice chromatin immunoprecipitated DNA, we generated genome-wide chromatin-state maps of rice endosperm. We find that the presence of H3K27me3 in either upstream or downstream of a gene is predominately associated with repression of the gene, while its absence is mainly associated with high gene expression.
2011-12-06 | GSE27048 | GEO
Project description:<p>Pigmented rice (<em>Oryza sativa L.</em>) is a rich source of nutrients, but pigmented lines typically have long life cycles and limited productivity. Here we generated genome assemblies of 5 pigmented rice varieties and evaluated the genetic variation among 51 pigmented rice varieties by resequencing an additional 46 varieties. Phylogenetic analyses divided the pigmented varieties into four varietal groups: Geng-japonica, Xian-indica, circum-Aus and circum-Basmati. Metabolomics and ionomics profiling revealed that black rice varieties are rich in aromatic secondary metabolites. We established a regeneration and transformation system and used CRISPR-Cas9 to knock out three flowering time repressors (Hd2, Hd4 and Hd5) in the black Indonesian rice Cempo Ireng, resulting in an early maturing variety with shorter stature. Our study thus provides a multi-omics resource for understanding and improving Asian pigmented rice.</p>
2023-03-27 | MTBLS3320 | MetaboLights
Project description:In this study, we aim to generate genome-scale DNA methylation profiles at single-base resolution in different rice cultivars (IR64, Nagina 22 and Pokkali) under control and stress conditions. Using high-throughput whole genome bisulfite Sequencing, we generated DNA methylation maps covering the vast majority of cytosines in the rice genome. More than 152 million high quality reads were obtained for each tissue sample using Illumina platform. We discovered extensive DNA methylation in rice cultivars, identified the context and level of methylation at each site.Numerous differentially methylated regions (DMRs) among different cultivars under control and stress conditions were identified and many of them were associated with differential gene expression. The high resolution methylome maps of different rice genotypes and differentially methylated regions will serve as reference for understanding the epigenetic regulation of stress responses in plants.
2015-12-31 | GSE60288 | GEO
Project description:Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a robust machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.
2022-07-27 | GSE209804 | GEO
Project description:Genomic DNA was extracted from human islets using Dneasy Blood & Tissue Kit (QIAGEN) with RNase A treatment. 200-500ng DNA was genotyped using InfiniumOmni2-5-8v Genotyping BeadChips (Illumina).DNA was isolated from human islet cells from various donors. DNA was genotyped using Illumina Infinium whole-genome genotyping array. Genotypes were called with GenomeStudio (v.2.0.4) using default settings. Genotypes that passed quality filters (missing<0.05, minor allele frequency (MAF>0.01), non-ambiguous alleles defined by AT/GC variants with MAF>40%) were exported.
2023-02-07 | GSE170763 | GEO