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Next generation sequencing facilitates quantitative analysis of wild type and overexpression of LbDREB6 transgenic line transcriptomes

ABSTRACT: Next generation sequencing facilitates quantitative analysis of wild type and overexpression of LbDREB6 transgenic line transcriptomes

PROVIDER: PRJNA491689 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR7869670_1.fastq.gz	Fastqsanger.gz
	SRR7869670_2.fastq.gz	Fastqsanger.gz
	SRR7869671_1.fastq.gz	Fastqsanger.gz
	SRR7869671_2.fastq.gz	Fastqsanger.gz
	SRR7869672_1.fastq.gz	Fastqsanger.gz

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Next generation sequencing facilitates quantitative analysis of wild type and overexpression of LbDREB6 transgenic line transcriptomes

Project description:Purpose: we performed comparative RNA-seq analyses to identify differentially expressed genes between overexpression of LbDREB6 transgenic lines and Wild Type expose to pathogen stress Methods:After 2 days of inoculation with the pathogen, leaves of WT, OE14 and OE18 plants were harvested and frozen in liquid nitrogen immediately for RNA extraction. For each sample, ~20 μg total RNA of stem tip with 2 pieces of leaves was sent to Annoroad Gene Technology Co., Ltd, Beijing, China for high throughout Illumina HiSeq 4000 sequencing (Illumina, San Diego, CA, USA). Results: To determine the possible pathways of LbDREB6 in pathogen defense, we conduct the transcriptomotic sequencing. After sequence, we achieved 53.20 Gb clean reads (18.2–24.7 million per library, Q30 ≥95.02%). About 68.3%-70.42% clean reads per library could be mapped to the Populus trichocarpa genome (see Table S2). The quality of the assembled transcriptome is good enough for functional annotation and further analysis compared with WT. Conclusions: Our study represents the detailed analysis of pathogen response transcriptomes , with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that next generation sequencing offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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Next generation sequencing facilitates quantitative analysis of transcriptomes of wild type and overexpression of PuHSFA4a transgenic lines

Project description:Purpose: we performed comparative RNA-seq analyses to identify differentially expressed genes between overexpression of PuHSFA4a transgenic lines and Wild Type with or without excess Zn stress Methods: Illumina HiSeq technology was used to generate mRNA profiles from PuHSFA4a transgenic roots compared to wild type roots.overexpression of PuHSFA4a and wild type material was obtained from root of Populus ussuriensis grown for 7 days in 1/2 MS medium only then exposed to 1/2 MS medium supplemented with 1.2mM ZnSO4 for two weeks. The control was plant grown for three weeks in 1/2 MS medium. Reads of 150bp were generated and aligned to the Populus trichocarpa reference genome (https://phytozome.jgi.doe.gov/pz/portal.html). qRT–PCR validation was performed using TransStart 1 Top Green qPCR SuperMix Results: By pairwise comparisons of the RNA-seq data, 33 genes were showed significant expression differences between PuHSFA4a-OE and WT (FDR adjusted P value < 0.01 including 17 genes under normal condition, 19 genes under excess Zn treatment. Altered expression of 17 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Conclusions: Our study represents the detailed analysis of excess Zn response transcriptomes , with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that next generation sequencing offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

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