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Next Generation Sequencing Facilitates Quantitative Analysis of Runx2fl/fl and Gli1-CreERT2 Runx2fl/fl Incisor Transcriptomes

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of Runx2fl/fl and Gli1-CreERT2 Runx2fl/fl Incisor Transcriptomes

PROVIDER: PRJNA610172 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR11234892.fastq.gz	Fastqsanger.gz
	SRR11234893.fastq.gz	Fastqsanger.gz
	SRR11234894.fastq.gz	Fastqsanger.gz
	SRR11234895.fastq.gz	Fastqsanger.gz
	SRR11234896.fastq.gz	Fastqsanger.gz

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Next Generation Sequencing Facilitates Quantitative Analysis of Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl Incisor Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived incisor transcriptome profiling (RNA-seq) between Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl mice to identify the potential target of Runx2. Methods: Incisor mRNA profiles from one week after induction of one-month-old Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl mice were generated by deep sequencing, in triplicate, using Illumina NextSeq500. Results: Using an optimized data analysis workflow, we mapped about 68 million sequence reads per sample to the mouse genome ( mm10) and identified 80,214 transcripts in th incisors of Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl mice with Partek E/M workflow. Five hundred and eleven differentially regulated genes were identified (＞2-fold, p＜0.05), of which 299 were upregulated and 212 were downregulated.

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Project description:Purpose: To study the function of Runx2 on mouse tooth root development. The goals of this study are to compare NGS-derived molar transcriptome profiling (RNA-seq) bwtween Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl mice to identify the potential downstream target of Runx2. Methods: molar mRNA profiles from PN7.5 Runx2fl/fl and Gli1-CreERT2;Runx2fl/fl mice (induction at PN3.5) were generated by deep sequencing, using Novaseq. Results: Using an optimized data analysis workflow, we mapped about 68 million sequence reads per sample to the mouse genome ( mm10) and identified 80,214 transcripts with Partek E/M workflow. 427 differentially regulated genes were identified (＞1.8-fold, p＜0.05), of which 219 were upregulated and 208 were downregulated.

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