Transcriptomes of Wild Type tomato and slstop1 under -Al/+Al treatment
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ABSTRACT: Purpose: Find SlSTOP1 regulated genes Methods: Total RNA was extracted from 20 days old wild-type tomato and slstop1 mutant plants treated with 0 and 60 μM Al solutions (pH 4.7). Three biological replicated samples were collected form each treatment and sequenced. Results:A total of 83.7 GB clean data was obtained by transcriptome sequencing. The clean data of each sample was more than 6.30 GB, and the percentage of q30 base was more than 93.82%. Conclusions: By RNA-seq analysis, we find potential SlSTOP1-regulated genes
Project description:Purpose: Find SlSZP1 regulated genes Methods: Total RNA was extracted from 20 days old wild-type tomato and slszp1 mutant plants treated with 60 μM Al solutions (pH 4.7). Three biological replicated samples were collected form each treatment and sequenced. Results:A total of 40 GB clean data was obtained by transcriptome sequencing. The clean data of each sample was more than 6.11 GB, and the percentage of q30 base was more than 90.98%. Conclusions: By RNA-seq analysis, we find potential SlSZP1-regulated genes
Project description:We explored the gene expression patterns of the pituitary gland and hypothalamus of Angus cows at different growth and developmental stages by deep sequencing the transcriptome and identified genes that affect bovine reproductive performance to provide new ideas for improving bovine fertility in production practice. We selected three 6-month-old (weaning period), three 18-month-old (first mating period) and three 30-month-old (early postpartum) Angus cows. The physiological statuses of the cows in each group were the same, and their body shapes were similar. After quality control of the sequencing, the transcriptome analyses of 18 samples yielded 129.18 GB of clean data. Clean data for each sample reached 6.30 GB. The GC content was >47.61%, and the base percentage of Q30 was at least 94.19%. We detected 13280 and 13318 expressed genes in the pituitary gland and hypothalamus, respectively, and screened 35 and 50 differential genes for each, respectively. Differential genes in both tissues were mainly concentrated in metabolism, lipid synthesis, and immune-related pathways in the 18-month-old cows compared with those in the 6-month-old cows. The 30-month-old cows presented more regulated reproductive behavior, and pituitary CAMK4 was the main factor regulating the reproductive behavior during this period via the pathways for calcium signaling, longevity, oxytocin, and aldosterone synthesis and secretion.
Project description:We compared the transcriptomic differences in rice leaves after being fed by C. medinalis using RNA sequencing. Global transcriptome changes in rice leaves responding to 1, 6, 12 and 24 h of such feeding were quantified by examining mRNAs of 20 libraries (four biological replicates at each of five sampling times) that collectively included 164.04 Gb of clean reads. Each of these samples contained at least 7.36 Gb of data with Q30 quality scores 90.70%. The GC content accounted for 53.16-53.71% of these reads. A total of 44.84-56.19 million reads were mapped uniquely to the rice IRGSP-1.0 reference genome, with unique mapping rates ranging from 89.73% to 91.36%. Using absolute value of log2(fold change) > 0 and FDR adjusted P value (padj) ≤ 0.05 as threshold for recognizing differentially expressed genes between any two treatments, a total of 6,372 DEGs were identified in rice leaves at different time points (1, 6, 12, and 24 h) of C. medinalis infestation.
Project description:The aim of this study was to construct a lncRNA-mRNA co-expression function network and analyze lncRNAs that might contribute to the pathogenesis of cervical cancer. Transcriptome analysis of 3 cervical cancer samples and 3 adjacent tissue samples was completed in this project.LncRNA-mRNA correlation analysis, enrichment of functions, qPCR, K-M survival, clinicopathology analysis, GSEA and immune infiltration analysis were implemented. Total of 67.600 GB of Clean Data (sequencing Data after quality control) was obtained. The average amount of Clean Data of each sample was 11.267 GB, the percentage of Q30 base was above 91.18%, and the GC content was between 45.46% and 47.18%.Reference species: human;Reference genomic version: GRCH38;Reference genome source: http://asia.ensembl.org/Homo_sapiens/Info/Index;The sequencing data of each sample after quality control was compared with the specified reference genome, and the matching rates ranged from 95.957% to 97.270%, and the unique matching rates ranged from 91.363% to 94.258%. Transcriptomic and lncRNA-mRNA correlation analysis revealed PCBP1-AS1 plays a key role as an independent prognostic factor in patients with cervical cancer.
Project description:This project completed the transcriptome analysis of 6 samples and obtained 79.158 Gb Clean Data (after quality control sequencing data). The average clean data volume of each sample was 13.193 Gb, the Q30 base percentage was over 93.02%, and the GC content was 39.35. % To 46.16%. through lncRNA sequencing, bioinformatics analysis and cell function studies, we found that MIR100HG is a new bladder cancer promoter that regulates the expression of CALD1 gene by targeting miR-142-5p and promotes the proliferation, migration and invasion of bladder cancer cells. These findings provide a new perspective for the study of the pathogenesis and development of bladder cancer, and have the potential as a new target for the diagnosis, prognosis and targeted therapy of bladder cancer.
Project description:Sepsis is a common systemic inflammatory response syndrome caused by infection. It has high mortality and great harm. Long non-coding RNA (lncRNA) has been reported to play a regulatory role in a variety of diseases and is a potential prognostic marker and therapeutic target. However, there are few data on the regulatory effect of lncRNA on sepsis. Therefore, we used transcriptome sequencing and series methods to screen and analyze lncRNAs with potential for prognostic markers in sepsis.we collected 4 sepsis patients whole blood samples and 4 healthy controls whole blood samples for transcriptome sequencing. After quality filtering of the raw sequencing data, we obtained a total of 125.581 Gb Clean Data, the average data amount of each sample was 15.698 Gb, the percentage of Q30 bases was over 93.89%, and the GC content was between 47.53% and 57.54%. Subsequently, we used HISAT2 to align the Clean Data of each sample with the human GRCH38 genome, and the alignment rate was between 96.355% and 97.986%. Through statistics, we found that the obtained lncRNAs were divided into 10 types (figure 1A), among which antisense (36.05%) and lincRNA (33.76%) were the main types.
Project description:The aim of this study was to screen abnormal lncRNAs in the progression of hepatocellular carcinoma through high-throughput sequencing, and to screen the biomarkers for prognosis and diagnosis of hepatocellular carcinoma. Transcriptome analysis of 6 samples was completed in this project. A total of 93.581 Gb Clean Data (sequencing Data after quality control) was obtained. The average amount of Clean Data of each sample was 15.597 Gb. The Q30 base percentage was above 93.69 % and GC content was between 44.95% and 50.05%. In conclusion, sequencing analysis provided a landscape for abnormal regulation of lncRNAs, and screened out a significantly different lncRNAs ZFAS1. ZFAS1were found to be overexpressed in hepatocellular carcinoma tissues and correlated with malignant status and prognosis of hepatocellular carcinoma patients, and ZFAS1 silencing inhibited proliferation, migration and invasion of SK-Hep1 cells. The overexpression of miR-582-3p can eliminate the inhibitory effect of ZFAS1 silencing on SK-Hep1 cells, which may be valuable for the diagnosis and treatment of hepatocellular carcinoma. ZFAS1 may be a new potential biomarker for liver cancer. Further studies on the regulatory process of ZFAS1/miR-582-3p will help us to understand the mechanism of the occurrence and development of liver cancer
Project description:A total of 18 RNA samples over 6 time points under heat stress treatment and 21 RNA samples at 7 time points under drought condition were sequenced on Illumina HiSeq2500. After quality assessment and data clearance, a total of 288 Gb of data with average Q30 values 95.85% were obtained.
Project description:Purpose: we used transcriptional profiling to identify differentially expressed genes in Col-0 and OE-SAUR41 seedlings Methods: Total RNA of 5-day-old Arabidopsis roots and the shoot parts were send to Vazyme BIotech Co., Ltd (Nanjing, China) to carry out library construction, Illumina HiSeq sequencing, and bioinformatical analysis. Each sample generated 4 Gb of clean data and contained three biological replicates.
Project description:Purpose: we used transcriptional profiling to identify differentially expressed genes in Col-0 and saur41/4071/72 seedlings Methods: Total RNA of 5-day-old Arabidopsis roots and the shoot parts were send to Vazyme BIotech Co., Ltd (Nanjing, China) to carry out library construction, Illumina HiSeq sequencing, and bioinformatical analysis. Each sample generated 4 Gb of clean data and contained three biological replicates.