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Transcriptome Analysis of Pediatric Acute Myeloid Leukemia

ABSTRACT: Purpose: This study aimed to generate a whole transcriptome dataset for children with acute myeloid leukemia Methods: RNA-seq data were generated by deep sequencing using Illumina. The sequence reads that passed quality filters were analyzed. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the human genome (buildhg38) and annotated with ensemble release 100.

ORGANISM(S): Homo sapiens

PROVIDER: GSE192638 | GEO | 2022/08/16

REPOSITORIES: GEO

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RNA-seq analysis of the chromosome-associated RNAs

Project description:The goals of this study are to discover the RNAs associated with the condensed chromosomes during mitosis. RNA from the soluble and pellet fraction of the lysed mitotic HCT116 cells were extracted, RNA profiles of soluble and pellet RNA were generated by deep sequencing, using MGISEQ2000. The sequence reads that passed quality filters were analyzed by STAR (v2.7.8a). Using an optimized data analysis workflow, we found that the pre-rRNAs were significantly enriched in the pellet fraction of the mitotic HCT116 cells.

2022-03-01 | GSE182987 | GEO

Quantitative Analysis of Wild Type and miR-203 KO transcriptomes in the rat endometrial adenocarcinoma cell line RUCA-I

Project description:Purpose: identification of mRNAs that are potential targets of miR-203 in the endometrium and endometrial carcinoma Methods: mRNA profiles of three batches of wild-type (WT) and three independently generated miR-203 knockout (miR-203 KO) RUCA-I cells were produced by deep sequencing, using Illumina HiSeq 2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped between 30 and 50 million sequence reads per sample to the rat genome (build rn6) and identified 26751 transcripts of which 1591 are differentially expressed in WT and miR-203 KO cells (p<0.05).

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Cardiac Sex Differences in the Transcriptome of C57 Male and Female Adult Hearts

Project description:Purpose: The goals of this study are to compare adult male and female C57 mouse hearts transcriptome profiling (RNA-seq) to conclude cardiac sex differences at the mRNA level. Methods: mRNA profiles of adult male and female C57 mouse hearts were generated by deep sequencing, n=4 for each sex, using Illumina HiSeq2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 50 million sequence reads per sample to the mouse genome (build mm10) and identified 16,160 transcripts in the mouse hearts.

2021-08-25 | GSE182691 | GEO

Cardiac Sex Differences in the Transcriptome of C57 Male and Female E9.5 Hearts

Project description:Purpose: The goals of this study are to compare E9.5 male and female C57 mouse embryonic hearts transcriptome profiling (RNA-seq) to conclude cardiac sex differences at the mRNA level. Methods: mRNA profiles of E9.5 male and female C57 mouse embryonic hearts were generated by deep sequencing, n=4 for each sex, using Illumina HiSeq2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm10) and identified 16,460 transcripts in the mouse hearts.

2021-08-25 | GSE182690 | GEO

Genome-wide profiling of gene expression under electro-acupuncture treatment on MI heart in rats

Project description:Purpose: Acupuncture exerts cardioprotective effects on several types of cardiac injuries, especially myocardial ischemia (MI). In order to elucidate the potential mechanisms, RNA-seq by next generation sequencing was used to identify the rat genome-wide alterations after MI and EA treatment in this study Methods: Adult male Sprague Dawley rats (250-300g) were divided into three groups: Control, MI and electro-acupuncture (EA) groups, myocardium mRNA profiles of rats in each group were generated by deep sequencing,using Illumina Hiseq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: BurrowsâWheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 25 million sequence reads per sample to the mouse genome (UCSC RN4) and identified 121,233, 178,242, 161,880 transcripts in the Control, MI and EA rats with TopHat and Cufflinks workflow respectively. Approximately 32% and 22% of the transcripts showed differential expression between the Control and MI, MI and EA respectively with a fold change â¥2.0. Conclusions: Our results for the first time generated genome-wide gene expression profiles both in the rat MI model and in acupuncture treatment by high throughput sequencing. The optimized data analysis workflows reported here should provide a framework for acupuncture investigations of expression profiles. Myocardium mRNA profiles of Control, MI and EA rats were generated by Hiseq 2000, Control and MI+EA group there were three samples, MI group there were two samples.

2016-03-21 | E-GEOD-54132 | biostudies-arrayexpress

Next Generation Sequencing Quantitative Analysis of the transcriptomes of Wild Type and Mki67-/- 4T1 tumors in mice

Project description:Purpose: The goals of this study were to compare gene expression profiles of mouse xenografted 4T1 tumors with intact or disrupted Mki67 gene. Methods: mRNA profiles of wild-type (WT) and Ki-67 knockout (Mki67−/−) mouse xenografted 4T1 tumors, in triplicate, were generated by deep sequencing using Illumina Hiseq2500 in paired-end read mode, 50bp. The sequence reads that passed quality filters were aligned to the mouse genome, quantified, and differential gene expression (DGE) analysis was performed using DEseq2. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCm38.p6) and identified differentially expressed genes. This revealed widespread changes in gene expression Conclusions: Ki-67 knockout causes genome-scale transcriptome alterations

2021-02-18 | GSE162885 | GEO

Next Generation Sequencing Quantitative Analysis of the transcriptomes of Wild Type and Mki67-/- MDA-mb231 (human breast adenocarcinoma) cell line

Project description:Purpose: The goals of this study were to compare gene expression profiles of MDA-mb231 cell lines with intact or disrupted Mki67 gene. Methods: mRNA profiles of wild-type (WT) and three Ki-67 knockout (Mki67−/−) clones in the MDA-mb231 cell line, were generated by deep sequencing using DNBSEQ-G50 in paired-end read mode, 100bp. The sequence reads that passed quality filters were aligned to the mouse genome, quantified, and differential gene expression (DGE) analysis was performed using DEseq2. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (GRCh38) and identified differentially expressed genes. This revealed widespread changes in gene expression Conclusions: Ki-67 knockout causes genome-scale transcriptome alterations

2021-02-18 | GSE162879 | GEO

Transcriptome analyses of Arabidopsis ldl1ldl2 (lysine-specific demethylase1 [LSD1]-like1 [ldl1]) double mutants as well as wild-type Columbia-0 plants via next-generation sequencing (NGS)

Project description:Purpose: The goals of this study are to compare transcriptome of ldl1ldl2 double mutants with that of wild-type Columbia-0 plants and to identify genes whose expression are tightly regualted by LDL1/LDL2 prtoeins in Arabidopsis. Methods: mRNA profiles of 3-week-old wild-type Col-0 and ldl1ldl2 mutant plants were generated by deep sequencing, in duplicate, using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with a method : TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 27~31 million sequence reads per sample to the Arabidopsis genome (TAIR10). Conclusions: Our results show that LDL1 and LDL2 protein had significant effects on transcription of genes important for plant immune reponses against Pseudomonas infection.

2021-04-04 | GSE171433 | GEO

Genome-wide transcriptome analysis of NIPBL hematopoeitic progenitors and megakaryocytes

Project description:The purpose of this study was to compare the transcriptome of NIPBL patient derived Hematopoietic progenitors and patient-derived megakaryocytes to healthy unaffected individuals Methods: HPC transcriptome profiles of three CdLS patient iPSCs harboring mutations in the NIPBL gene and megakaryocytes generated from patient-iPSCS were generated by deep sequencing, in triplicate, using Illumina HiSeq 2500. The sequence reads that passed quality filters were analyzed at the transcript isoform level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 15 million sequence reads per sample to the human genome and identified transcripts in CdLS-HPCs and transcripts in CdLS-MEGs. Conclusion: Our data supports dysregulation of megakaroyctye maturation and growth arrest in response to multiple conserved developmental pathways.

2019-11-01 | GSE119828 | GEO

RNA Sequencing Quantitative Analysis of cell lines derived from tumours from two mouse models of human osteosarcoma that recapitulate clinically distinct human osteosarcoma subtypes.

Project description:Purpose: Osteosarcoma (OS) is the most common primary bone malignancy. OS consists of several subtypes including fibroblastic, osteoblastic and chondroblastic OS. We have developed genetically engineered mouse models of human OS that recapitulate two distinct subtypes, fibroblastic (Osx-CreLox p53-/- Rb-/-) and osteoblastic (Osx-Cre shRNA p53-/-) OS. The goal of this study was to identify transcriptional differences that distinguish the two subtypes. Methods: mRNA profiles of cell lines derived from tumours from Osx-Cre p53fl/fl Rbfl/fl (fibroblastic OS) and Osx-Cre shRNA TRE-p53.1224 pRbfl/fl (osteoblastic OS) mouse models were generated by RNA sequencing, in triplicate, using Illumina HiSeq2000. The sequence reads that passed quality filters were analyzed at the transcript level with TopHat followed by Cufflinks. Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 12,436 transcripts in the tumours of Osx-Cre p53fl/fl Rbfl/fl and 12,074 Osx-Cre shRNA TRE-p53.1224 pRbfl/fl with the TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes. Conclusions: Our study represents a detailed analysis of OS subtype transcriptomes generated by RNA-seq technology. mRNA profiles of cell lines derived from tumours from two genetically engineered mouse models of human osteosarcoma (Osx-Cre p53fl/fl Rbfl/fl and Osx-Cre shRNA TRE-p53.1224 pRbfl/fl) were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000.

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