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 flower development transcriptome profiling (RNA-seq) of two subspecies Methods: Flower mRNA profiles of wild-type (WT) four developmental stages and the same stages of Vitis vinifera subp vinifera were generated by deep sequencing using Illumina. Initial quality assessment was based on data passing the Illumina Chastity filtering. Subsequently, reads containing adapters and/or PhiX control signal were removed using an in-house filtering protocol. The second quality assessment was based on the remaining reads using the FASTQC quality control tool version 0.10.0. qRT–PCR validation was performed using EvaGreen assays. Results: Using an optimized data analysis workflow, we mapped about 13 to 19 million sequence reads per Vitis sample, 50 bp in length equivalent to 1.5 Gb of total sequence data by each sample. The exception was male stage G (M_G) were only 7 to 8 million sequence reads were obtained. Five genes (VvTFL1, VvLFY, VvAP1, Vv AP3, VvPI), related to flowering development, were used to validate RNA-Seq data and to test for data reproducibility through qRT–PCR. The coefficient of correlation (r) obtained between the log2 of RPKM (RNA-Seq) versus log2 of mRNA average number (RT-qPCR), varied from ≈ 0.97 (VvTLF) to ≈ 0.73 (VvPI) indicating a good correlation between both techniques and thus validating our RNA-Seq results. Conclusions: Our study represents the first detailed transcriptome analysis of four Vitis flower developmental stages, with the same individual, in three genders, 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 NGS offers a comprehensive and accurate quantitative and qualitative evaluation of mRNA contentper developmental stage. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Flowering mRNA profiles of four developmental stages of Vitis wild type (WT) and the domesticated Vitis were generated by deep sequencing using Illumina HiSeq 2500.

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 flower development transcriptome profiling (RNA-seq) of two subspecies Methods: Flower mRNA profiles of wild-type (WT) four developmental stages and the same stages of Vitis vinifera subp vinifera were generated by deep sequencing using Illumina. Initial quality assessment was based on data passing the Illumina Chastity filtering. Subsequently, reads containing adapters and/or PhiX control signal were removed using an in-house filtering protocol. The second quality assessment was based on the remaining reads using the FASTQC quality control tool version 0.10.0. qRT–PCR validation was performed using EvaGreen assays. Results: Using an optimized data analysis workflow, we mapped about 13 to 19 million sequence reads per Vitis sample, 50 bp in length equivalent to 1.5 Gb of total sequence data by each sample. The exception was male stage G (M_G) were only 7 to 8 million sequence reads were obtained. Five genes (VvTFL1, VvLFY, VvAP1, Vv AP3, VvPI), related to flowering development, were used to validate RNA-Seq data and to test for data reproducibility through qRT–PCR. The coefficient of correlation (r) obtained between the log2 of RPKM (RNA-Seq) versus log2 of mRNA average number (RT-qPCR), varied from ≈ 0.97 (VvTLF) to ≈ 0.73 (VvPI) indicating a good correlation between both techniques and thus validating our RNA-Seq results. Conclusions: Our study represents the first detailed transcriptome analysis of four Vitis flower developmental stages, with the same individual, in three genders, 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 NGS offers a comprehensive and accurate quantitative and qualitative evaluation of mRNA contentper developmental stage. 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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