Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and L3mbtl2 cKO Testicular Transcriptomes
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ABSTRACT:
ORGANISM(S): Mus musculus
PROVIDER: GSE109921 | GEO | 2018/08/01
REPOSITORIES: GEO
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Project description:Purpose: 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 Conclusions: Our study represents the detailed analysis of panicles 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.
2021-08-12 | GSE181713 | 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 femoral diaphysis and metaphysis transcriptome profiling (RNA-seq) to determine pathways and networks dependent on Dlx3 during bone development and homeostasis. Methods: mRNA profiles of diaphysis and metaphysis isolated from the femur of 5-week-old wild-type (WT) and Dlx3Oc-cKO (OC-cre;Dlx3f/-) conditional knockout mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level by ANOVA (ANOVA) and TopHat. qRT-PCR validation was performed using SYBR Green assay. Results: RNA-Seq data were generated with Illumina's HiSeq 2000 system. Raw sequencing data were processed with CASAVA 1.8.2 to generate fastq files. Reads of 50 bases were mapped to the mouse transcriptome and genome mm9 using TopHat 1.3.2. Gene expression values (RPKM) were calculated with Partek Genomics Suite 6.6, which was also used for the ANOVA analysis to determine significantly differentially expressed genes. Conclusions: Our study represents the first detailed analysis of Dlx3Oc-cKO diaphysis and metaphysis from femurs, with biologic triplicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Diaphysis and metaphysis mRNA profiles of metaphysis and diaphysis from femurs of 5-wk-old (WT) and Dlx3Oc-cKO male mice were generated by deep sequencing, in triplicate, using Illumina HiSeq 2000.
2014-11-04 | E-GEOD-53105 | 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 8-week-old wild-type (WT) and liver specific conditional CTCF KO (CTCF cKO) mice were generated by deep sequencing, in quadruplet, 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.
2021-07-27 | GSE151501 | 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 small non-coding RNA profiling (snRNA-seq) in WT oocyte, sperm and 2PN stage embryos to those sperm and 2PN stage embryos derived from WT, Dicer cKO and Drosha cKO. We further study the roles of sperm-borne small RNA on fertilization and pre-implantation embryonic development. Methods: Small RNA profiles of adult wild-type (WT) oocytes, adult WT sperm, 2PN stage embryos, adult Dicer cKO/Drosha cKO sperm, 2PN stage embryos were generated by deep sequencing in duplicate, using Ion Torrent Proton. The sequence reads that passed quality filters were analyzed at the small RNA level with two methods: Burrows–Wheeler Aligner (BWA) followed by ANOVA (ANOVA) and TopHat followed by Cufflinks. 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 small RNA (miRNA and endo-siRNA) in the oocyte, sperm and 2PN stage of WT and Dicer cKO/Drosha cKO mice with BWA workflow and 34,115 transcripts with TopHat workflow. Approximately 47% of the miRNAs showed differential expression between the WT and Dicer cKO sperm, ~52% of miRNAs were shown dysregulated in Drosha cKO sperm compared to those in WT sperm with a fold change ≥2.0 and p value <0.05. 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 small non-coding RNAs (miRNAs) in sperm and demonstrated that sperm-borne small RNAs are important for fertilization and early embrynic develoment, with biologic duplicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of small RNAs profiles in mouse sperm, oocytes and 2PN stage of embryos. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of small RNA contents within sperm or oocytes/embryos. We conclude that RNA-seq based small RNAs characterization in gametes would expedite genetic network analyses and permit the dissection of complex biologic functions during fertilization and embryonic development.
2015-10-08 | GSE73824 | 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 IL4/IL13 treated BMDMs transcriptome profiling (RNA-seq) to quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods. Methods: BMDMs mRNA profiles of 8 weeks old wild-type (WT) mice were generated, stimulated with IL4/IL13, IL4/IL13+ TNF or TNF, deep sequenced, in triplicate, using Illumina NovaSeq 6000 platform. 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 IL4/IL13 or IL4/IL13+TNF stimulated BMDMs, 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.
2021-05-04 | GSE169348 | 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 skin transcriptome profiling (RNA-seq) to determine pathways and networks dependent on retinoic acid during skin development. Methods: Skin mRNA profiles of embryonic day E16.5 wild-type (WT) and Cyp26b1 knockout (Cyp26b1?/?), and of control and of dermal and epidermal skin fractions of Engrailed1cre;Cyp26b1f/- (En1cre;Cyp26b1f/-) conditional knockout mice were generated by deep sequencing, in duplicate, using Illumina HiSeq2000. The sequence reads that passed quality filters were analyzed at the transcript isoform level by ANOVA (ANOVA) and TopHat. qRT–PCR validation was performed using TaqMan and SYBR Green assay. Results: RNA-Seq data were generated with Illumina’s HiSeq 2000 system. Raw sequencing data were processed with CASAVA 1.8.2 to generate fastq files. Reads of 50 bases were mapped to the mouse transcriptome and genome mm9 using TopHat 1.3.2. Gene expression values (RPKM) were calculated with Partek Genomics Suite 6.6, which was also used for the ANOVA analysis to determine significantly differentially expressed genes. Conclusions: Our study represents the first detailed analysis of Cyp26b1-/- skin and En1cre;Cyp26b1f/- dermis/epidermic 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. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions. Skin mRNA profiles of embryonic-day 16.5 wild type (WT) and Cyp26b1-/- mice and of dermis and epidermis of embryonic day 18.5 control and En1cre;Cyp26b1f/- were generated by deep sequencing, in duplicate, using Illumina HiSeq2000.
2012-12-07 | E-GEOD-40436 | biostudies-arrayexpress
Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and L3mbtl2 cKO Testicular Transcriptomes
| PRJNA432346 | ENA