Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and FGR Transcriptomes
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE137660 | GEO | 2019/09/19
REPOSITORIES: GEO
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Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. Methods: spleen mRNA profiles of 8-weeks-old WT and lncRNA-ISIR, used to be called lnRNA-IRF3, knockout mice were generated by deep sequencing, using BGISEQ-500 system. The sequence reads that passed quality filters were analyzed at the transcriptional level with RSEM (RNA-seq by Expectation Maximization). Conclusions: Our study represents the first detailed analysis of retinal transcriptomes, 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.
2021-11-09 | GSE138700 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare transcriptome profiling (RNA-seq) between treatment and control model samples. Results: Using the RNA-seq analysis workflow, we mapped about an average of 80 million sequence reads per sample to the rat genome (Rnor_6.0) and identified 34,194 transcripts. Conclusions: Our 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.
2022-01-30 | GSE126796 | GEO
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 WT and dKO round spermatids transcriptome profiling (RNA-seq) Methods: Adult WT and dKO round spermatids mRNA profiles mice were generated by deep sequencing, in dulplicate. 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 Results: Using 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 (R2) of 0.8798. Approximately 10% of the transcripts showed differential expression between the WT and dKO round spermatids, 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. Conclusions: Our 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. Adult wild type (WT) and dKO mouse round spermatids were generated by deep sequencing, in dulplicate, using Illumina GAIIx.
2014-07-03 | E-GEOD-59017 | biostudies-arrayexpress
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 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. Methods: Retinal 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. Results: Using 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 (R2) 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. Conclusions: Our 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. Retinal mRNA profiles of 21-day old wild type (WT) and Nrl-/- mice were generated by deep sequencing, in triplicate, using Illumina GAIIx.
2011-10-25 | E-GEOD-33141 | biostudies-arrayexpress
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.
2015-01-26 | E-GEOD-56844 | biostudies-arrayexpress
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 liver 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 Methods: Liver mRNA profiles of 48 hours fasted wild-type (WT) and Acyl-CoA Synthetase Short Chain Family Member 2 knockout (Acss2−/−) 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 SYBR Green assays Results: Using an optimized data analysis workflow, we mapped about 30 million sequence reads per sample to the mouse genome (build mm9). Conclusions: Our study represents the first detailed analysis of liver transcriptomes of Acss2-/- mice, 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.
2018-09-25 | GSE118552 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in CON and PMB treatment cells by using RNA-seq Methods: CON and PMB treatment cells mRNA profiles were generated by deep sequencing, using Illumina Novaseq. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 , IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, EdgeR software was used for differential gene expression analysis and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents detailed analysis of CON and PMB cells 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.
2023-08-11 | GSE185840 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analyse the differential genes and pathways in CTRL and PMB treatment cells by using RNA-seq. Methods: CTRL and PMB treatment cells mRNA profiles were generated by deep sequencing, using Illumina Novaseq. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2, IGV was used to view the mapping result by the Heatmap, histogram, scatter plot or other style, FPKM was then calculated to estimate the expression level of genes in each sample, EdgeR software was used for differential gene expression analysis and Function Enrichment Analysis including GO enrichment analysis and KEGG. Conclusions: Our study represents detailed analysis of CTRL and PMB cells 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.
2023-08-11 | GSE207670 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare TP53-WT and TP53-KO HCT116 cells transcriptome profiling (RNA-seq) under 5-FU treatment condition and to evaluate the correlation between transcriptome profileing and chromatin accessibility under 5-FU treatment. Methods: HCT116 cell profiles of TP53-WT and TP53- KO were generated by deep sequencing, in duplicates, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform levels: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA). Conclusions: Our study represents the detailed analysis of TP53-WT and TP53-KO HCT116 cell transcriptomes under 5-FU treatment with different timepoint, 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 RNA-seq offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a TP53-WT and TP53-KO cells with and without 5-FU treatment in different timepoint. We conclude that NGS based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
2021-02-10 | GSE157951 | GEO
Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of plants. The goals of this study are to compare omparatively evaluated both sequence variation and gene expression at the transcriptomic level between two species. Methods: Pooled total RNA of P. floridana flower buds and young fruits, in triplicate, using Illumina HiSeqTM 2000. The sequence reads remove reads with adaptors or unknown nucleotides larger than 5% and low-quality reads using . qRT–PCR validation was performed using TaqMan and SYBR Green assays Results: Sequencing the Physalis transcriptome revealed 147,118 unigenes. When aligned to the tomato genome, we estimated that around 30,121 genes were expressed in the Physalis floral-fruit transcriptome, and 10,498 orthologous gene pairs were identified between P. floridana and S. pimpinellifolium.with a fold change ≥1.5 and FER value <0.001, 0.68% of the unigenes in the Physalis floral-fruit transcriptome were developmentally regulated at the floral-fruit transition, and Altered expression of 15 genes was confirmed with qRT–PCR, demonstrating the high degree of sensitivity of the RNA-seq method. Conclusions: Our study represents the first detailed analysis of floral-fruit 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 organ or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.
2018-12-29 | GSE92998 | GEO