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Rice whole transcriptome differences at two temperature levels surveyed by RNA-Seq

ABSTRACT: We report that TOG1 coordinates global changes of gene expression upon high temperature to support rice thermotolerant growth. We performed gene ontology (GO) enrichment analysis of the differentially expressed genes in rice seedlings grown at 25 ℃ and 30 ℃ and found that when temperature increases, wild-type dramatically adjusts the expression level of hundreds of genes in GO terms polysaccharide metabolic process, carbohydrate metabolic process, glucan metabolic process, carbon fixation, response to stimulus and organic substance metabolic process required for growth. However, in a tog1 mutant, the differentially expressed genes in response to the temperature increase significantly enriched in GO terms response to stimulus, response to oxidative stress and response to stress, whereas the coordination of primary metabolic processes and carbon fixation were largely impaired or undetectable. Differentially expressed mRNA profiles of 22-day-old wild type (WT) and tog1 rice upon a temperature difference were generated by deep sequencing

ORGANISM(S): Oryza sativa Indica Group

SUBMITTER: Dong Wang

PROVIDER: E-GEOD-42096 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Rice whole transcriptome differences at two temperature levels surveyed by RNA-Seq

Project description:We report that TOG1 coordinates global changes of gene expression upon high temperature to support rice thermotolerant growth. We performed gene ontology (GO) enrichment analysis of the differentially expressed genes in rice seedlings grown at 25 ℃ and 30 ℃ and found that when temperature increases, wild-type dramatically adjusts the expression level of hundreds of genes in GO terms polysaccharide metabolic process, carbohydrate metabolic process, glucan metabolic process, carbon fixation, response to stimulus and organic substance metabolic process required for growth. However, in a tog1 mutant, the differentially expressed genes in response to the temperature increase significantly enriched in GO terms response to stimulus, response to oxidative stress and response to stress, whereas the coordination of primary metabolic processes and carbon fixation were largely impaired or undetectable.

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Next-generation sequencing analyses of the differently expressed genes of wild type and atcep1 mutant Arabidopsis thaliana

Project description:Purpose: The goal of this study is to compare the differently expressed genes in the wild type and the KDEL-tailed cysteine protease AtCEP1 knockout (atcep1) Arabidopsis using RNA-sequencing (RNA-seq). Methods: Arabidopsis buds mRNA profiles of anther development stages 5-6, 7-9, and 10-11 of the wild type (WT) and atcep1 mutant were generated by deep sequencing via Illumina HiSeqTM 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with the following steps: Remove reads with adaptor sequences; Remove reads in which the percentage of unknown bases (N) is greater than 10%; Remove low quality reads, in which the percentage of the low quality base (base with quality value â¤ 5) is greater than 50%. The clean reads were mapped to the Arabidopsis reference genome and reference genes using SOAP aligner/SOAP2. No more than 2 mismatches were allowed in the alignment. The gene expression level was calculated using RPKM (Reads Per Kb per Million reads). Differential expression analysis between the wild type and the atcep1 mutant was performed using the DEGseq R package (1.12.0) based on normalized read counts. A corrected P value of < 0.005 and |log2Ratio| > 1 were set as the threshold for significantly differential expression. Results: We identified 872 genes showing significant differential expression, and in the atcep1 mutant, the upregulated genes significantly outnumbered the downregulated genes at the three time points. The GO analysis of the differently expressed genes showed that the expression of genes participating in anther tapetal secretory structure formation, pollen wall development, and tapetal cell wall generation, clearly changed. Arabidopsis buds mRNA profiles of development stages 5-6, 7-9, and 10-11 of the wild type (WT) and atcep1 muant were generated by deep sequencing via Illumina HiSeqTM 2000.

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A global profiling of gene expression in chilling stress in rice

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Project description:Soybean is one of the most economically important crops in the world. The cotyledon is the nutrient storage area in seeds, and it is critical for seed quality and yield. Cotyledon mutants are important for the genetic dissection of embryo patterning and seed development.Here, we characterised a soybean curled-cotyledon (cco) mutant. Compared with wild-type (WT), the entire embryos of cco mutant resembled the “tail of swallow”. To explore the molecular mechanisms underlying soybean cotyledon development, we executed RNA-Seq using the Illumina HiSeq2000 system. Pods at 7DAF collected from WT and cco were analyzed by RNA-seq.

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2016-04-01 | E-GEOD-78893 | biostudies-arrayexpress

RNA-seq of pericarp of purple-grain wheat Luozhen No.1 of 15 days (D15) and 20 days (D20) shading treatment after pollination, against 15 DAP, 20 DAP untreated controls. The purple-grain wheat were grown under natural field conditions at Shandong Agricultural University Experimental Station (36169 N, 117169 E), Taian, China during Octubor, 2015 to June, 2016.

Project description:Purple-grain wheat are caused by anthocyanin accumulation in the seed coat. But little is known about molecular mechanism of anthocyanin biosynthesis. The anthocyanin biosynthesis and accumulation were affected by light in purple-grain wheat. The spikes of purple-grain wheat Luozhen No.1 were bagged with four-layer Kraft paper bags after pollination. To identify genes involved in the anthocyanin biosynthesis, we sequenced four pericarp cDNA libraries, D15 (15 DAP), D20 (20 DAP) of shading treatment, and L15 (15 DAP), L20 (20 DAP) of untreated control using an Illumina HiSeqTM 2000. After quality control, raw reads are filtered into clean reads which will be aligned to the reference sequences. The alignment data is utilized to calculate distribution of reads on reference genes and mapping ratio, and proceed with downstream analysis including gene and isoform expression, deep analysis based on gene expression (PCA/correlation/screening differentially expressed genes and so on),exon expression, gene structure refinement, alternative splicing, novel transcript prediction and annotation, SNP detection, Indel detection. Further, we also perform deep analysis based on different expression genes, including Gene Ontology (GO) enrichment analysis, Pathway enrichment analysis, cluster analysis, and finding transcriptor factor.

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