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Next Generation Sequencing Facilitates Quantitative Analysis of H1299 Wild Type and TTC28-KO Transcriptomes

ABSTRACT: Currently, research on the TTC family is still in its early stages. We have generated the H1299 TTC28-KO cell line. The purpose of this study is to utilize next-generation sequencing techniques to investigate the effects of TTC28 knockout on the biological behavior of tumor cells.

ORGANISM(S): Homo sapiens

PROVIDER: GSE241497 | GEO | 2024/11/16

REPOSITORIES: GEO

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Project description:PurposeNext-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT-PCR) methods and to evaluate protocols for optimal high-throughput data analysis.MethodsRetinal mRNA profiles of 21-day-old wild-type (WT) and neural retina leucine zipper knockout (Nrl(-/-)) mice were generated by deep sequencing, in triplicate, using Illumina GAIIx. 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. qRT-PCR validation was performed using TaqMan and SYBR Green assays.ResultsUsing an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9) and identified 16,014 transcripts in the retinas of WT and Nrl(-/-) mice with BWA workflow and 34,115 transcripts with TopHat workflow. RNA-seq data confirmed stable expression of 25 known housekeeping genes, and 12 of these were validated with qRT-PCR. RNA-seq data had a linear relationship with qRT-PCR for more than four orders of magnitude and a goodness of fit (R(2)) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and Nrl(-/-) retina, with a fold change ≥1.5 and p value <0.05. Altered expression of 25 genes was confirmed with qRT-PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Hierarchical clustering of differentially expressed genes uncovered several as yet uncharacterized genes that may contribute to retinal function. Data analysis with BWA and TopHat workflows revealed a significant overlap yet provided complementary insights in transcriptome profiling.ConclusionsOur study represents the first detailed analysis of retinal 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 NGS 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.

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.

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Next Generation Sequencing Facilitates Quantitative Analysis of H1299 Wild Type and TTC28-KO Transcriptomes

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