Transcriptomic network of Tulipa gesneriana during petal senescence
Ontology highlight
ABSTRACT:
ORGANISM(S): Tulipa gesneriana
PROVIDER: GSE136183 | GEO | 2022/11/02
REPOSITORIES: GEO
Similar Datasets
Project description:Purpose: We aimed to dissect heat response of bermudagrass and identify heat stress responsive genes. Methods: A total amount of 3 µg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, six samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified genes modulated by short term heat (2h) and long term heat (12h) treatments.
2021-12-21 | GSE136182 | GEO
Project description:Purpose: We aimed to compare transcriptomic changes after high concentration melatonin treatment in Arabidopsis Methods: A total amount of 3 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, eight samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis revealed different networks which were modulated by melatonin and IAA in Arabidopsis seedlings
2021-12-21 | GSE139595 | GEO
Project description:Purpose: We aimed to dissect function of Medicago truncutula homeodomain finger protein, MtPHD6 in Arabidopsis Methods: A total amount of 3 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, four samples with three biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis revealed different networks which were modulated by drought stress and MtPHD6 transgene in Arabidopsis seedlings
2020-01-08 | GSE134945 | GEO
Project description:Purpose: We aimed to dissect heat response of tall fescue and possible roles of melatonin and 24-epibrassinolide during thermotolerance. Methods: A total amount of 3 µg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, six samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified genes modulated by short term heat (2h) and long term heat (12h) treatments.
2018-03-02 | GSE101699 | GEO
Project description:Purpose: We aimed to identify ZAT18 target genes and characterize functions of ZAT18 during plant drought tolerance Methods: A total amount of 3 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, eight samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis revealed that 1777 genes were transcriptionally affected by AtZAT18 trasngene or drought treatment. The results showed that overexpression of AtZAT18 modulated expression level changes of 423 and 561genes under control and drought stress conditions, respectively. Drought stress treatment changed expression of 971 genes with 768 up-regulated and 203 down-regulated.
2017-06-13 | GSE93979 | GEO
Project description:Purpose: We aimed to compare transcriptomic changes after melatonin (MT) and IAA treatments in Arabidopsis and dissected cross-talk between MT and IAA Methods: A total amount of 1 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq2000 platform and paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, six samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified coregulated genes by melatonin and IAA in Arabidopsis seedlings
2021-12-21 | GSE152813 | GEO
Project description:Purpose: We aimed to compare transcriptomic changes after melatonin (MT) and IAA treatments in Arabidopsis and dissected cross-talk between MT and IAA Methods: A total amount of 1 μg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq2000 platform and paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. Index of the Arabidopsis genome was built using Bowtie v2.2.3 and paired-end clean reads were aligned to the reference genome using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then FPKM (Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced) of each gene was calculated based on the length of the gene and reads count mapped to this gene. Differential expression analysis of drought stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, six samples with two biological replicates per genotype/treatment combination were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified coregulated genes by melatonin and IAA in Arabidopsis seedlings
2021-08-11 | GSE167524 | GEO
Project description:Purpose: We aimed to dissect response of bermudagrass to drought, salt, submergence and heat stresses and identify stress responsive genes inbermudagrass. Methods: A total amount of 3 µg RNA was used for generation of sequencing libraries using NEBNext® Ultra™ RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Clean reads were obtained by removing low quality reads, reads containing adapter and ploy-N from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated.Paired-end clean reads were aligned to the reference genome of TAIR10 and rice protein sequence from MSU (version_7.0) using TopHat v2.0.12. HTSeq v0.6.1 was used to count the reads numbers mapped to each gene. And then RPKM of each gene was calculated . Differential expression analysis of abiotic stress versus control condition was performed using the DESeq R package (1.18.0). Results:In total, 12 samples with two biological replicates per treatment were used for RNA sequencing analysis. At least 2 G clean bases were generated for each sample. Comparative analysis identified genes modulated by different abiotic stress treatments.
2022-11-01 | GSE140362 | GEO
Project description:Purpose: RNA-Seq uses next-generation sequencing to analyze expression across the transcriptome, enabling to detect known or novel features and quantify RNA. The goal of this study is to compare transcriptome profiles between control and GLUT1-HK2-PFKFB3 overexpressed mouse skeletal muscle. Methods: Total RNA was isolated from the gastrocnemius muscle of chow diet-fed M;G and control mice at the age of 3-month-old using RNAiso Plus (Takara Bio). Three independent pooled samples per group were analyzed. Sequencing libraries were generated using NEBNext® UltraTM RNA Library Prep Kit for Illumina® (NEB, USA) following manufacturer’s recommendations and index codes were added to attribute sequences to each sample. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions. After cluster generation, the library preparations were sequenced on an Illumina Hiseq platform and 125 bp/150 bp paired-end reads were generated. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. Fragments Per Kb of exon per Million mapped reads (FPKM) were calculated using featureCounts v1.5.0-p3. Results: We mapped about 6 million sequence reads per sample to the mouse genome and identified 54533 transcripts in the gastrocnemius muscle of control and GLUT1-HK2-PFKFB3-overexpressed mice. RNA-seq data confirmed stable expression of 10 known housekeeping genes, and 7 of these were validated with qRT–PCR. A total 664 transtripts were differentially expressed in wildtype and GLUT1-HK2-PFKFB3 overexpressed skeletal muscle with a cutoff of 2.0-fold and p < 0.05 from RNA sequencing analysis. Altered expression of 15 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method.
2022-09-01 | GSE157257 | GEO
Project description:Purpose: To obtain an overview of the metabolic changes associated to the absence of KpsM in Synechocystis, in particular on carbon-related metabolic pathways Methods: The trancriptomes of Synechocystis wild type and kpsM mutant were analyzed by RNA sequencing, using three biological replicates. Cultures were grown until reaching an OD730nm of 1.5. Sequencing libraries were generated using NEBNext® Ultra TM RNA Library Prep Kit for Illumina®. PCR products were purified (AMPure XP system) and library quality was assessed on the Agilent Bioanalyzer 2100 system. The clustering of the index-coded samples was performed on a cBot Cluster Generation System using PE Cluster Kit cBot-HS (Illumina). Raw data (raw reads) of FASTQ format were firstly processed through in-house scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter and poly-N sequences and reads with low quality from raw data. Paired-end clean reads were mapped to the reference genome using HISAT2 software.HTSeq was used to count the read numbers mapped of each gene, including known and novel genes. And then RPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. RPKM, Reads Per Kilobase of exon model per Million mapped reads, considers the effect of sequencing depth and gene length for the reads count at the same time, and is currently the most commonly used method for estimating gene expression levels. Differential expression analysis between two conditions/groups (three biological replicates per condition) was performed using DESeq2 R package. DESeq2 provides statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P values were adjusted using the Benjamini and Hochberg’s approach for controlling the False Discovery Rate (FDR). Genes with an adjusted P value < 0.05 found by DESeq2 were assigned as differentially expressed. Results: Approximately 700 genes (out of the 3636 identified and 215 quantified, representing a coverage of 85,12%) were significantly differentially expressed (P 216 value < 0.05) in the kpsM mutant compared to the wild type. Of those, 406 were down217 regulated, while 297 were up-regulated. Conclusions: Overall, our transcriptomic data indicates alterations in the mechanisms of energy production and conversion in the kpsM mutant compared to the wild type. The approach resulted in the identification of altered levels of transcripts belonging to a variety of functional categories and highlighting a number of key metabolic processes affected by the disruption of kpsM, namely photosynthesis, oxidative phosphorylation and carbon metabolism.
2021-01-20 | GSE165073 | GEO