Spliced synthetic genes as internal controls in RNA sequencing experiments.
Ontology highlight
ABSTRACT:
ORGANISM(S): synthetic construct Homo sapiens
PROVIDER: GSE77072 | GEO | 2016/07/21
SECONDARY ACCESSION(S): PRJNA309391
REPOSITORIES: GEO
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Project description:RNA sequencing (RNAseq) can be used to assemble spliced isoforms, quantify expressed genes and provide a global profile of the transcriptome. However, the size and diversity of the transcriptome, the wide dynamic range in gene expression and inherent technical biases confound RNAseq analysis. We have developed a set of spike-in RNA standards, termed âsequinsâ (sequencing spike-ins), that represent full-length spliced mRNA isoforms. Sequins have an entirely artificial sequence with no homology to natural reference genomes, but align to gene loci encoded on an artificial in silico chromosome. The combination of multiple sequins across a range of concentrations emulates alternative splicing and differential gene expression, and provides scaling factors for normalization between samples. We demonstrate the use of sequins in RNAseq experiments to measure sample-specific biases and determine the limits of reliable transcript assembly and quantification in accompanying human RNA samples. In addition, we have designed a complementary set of sequins that represent fusion genes arising from rearrangements of the in silico chromosome to aid in cancer diagnosis. RNA sequins provide a qualitative and quantitative reference with which to navigate the complexity of the human transcriptome. Detailed transcriptomic analysis of a human cell-type with synthetic RNA spike-ins ('sequins'). Sequins were initially combined at equimolar concentrations (a "flat" mix) and sequenced neat (i.e. without any natural RNA added). We then prepared two staggered mixtures (Mix A & B) and sequenced them neat. Mix A was then spiked into total RNA extracted from the K562 cell-type. Finally, we prepared a staggered mixture of fusion sequins and sequenced it neat.
2016-07-21 | E-GEOD-77072 | biostudies-arrayexpress
Project description:The transcriptional regulator peroxisome proliferator activated receptor gamma coactivator 1A (PGC-1α), encoded by PPARGC1A, has been linked to neurodegenerative diseases. Recently discovered CNS-specific PPARGC1A transcripts are initiated far upstream of the reference promoter, spliced to exon 2 of the reference gene, and are more abundant than reference gene transcripts in post-mortem human brain samples. The proteins translated from the CNS and reference transcripts differ only at their N-terminal regions. To dissect functional differences between CNS-specific isoforms and reference proteins, we used clustered regularly interspaced short palindromic repeats transcriptional activation (CRISPRa) for selective endogenous activation of the CNS or the reference promoters in SH-SY5Y cells. Expression and/or exon usage of the targets was ascertained by RNA sequencing. Compared to controls, more differentially expressed genes were observed after activation of the CNS than the reference gene promoter, while the magnitude of alternative exon usage was comparable between activation of the two promoters. Promoter- selective associations were observed with canonical signaling pathways, mitochondrial and nervous system functions and neurological diseases. The distinct N-terminal as well as the shared downstream regions of PGC-1α isoforms affect the exon usage of numerous genes. Furthermore, associations of risk genes of amyotrophic lateral sclerosis and Parkinson’s disease were noted with differentially expressed genes resulting from the activation of the CNS and reference gene promoter, respectively. Thus, CNS-specific isoforms markedly amplify the biological functions of PPARGC1A and CNS-specific isoforms and reference proteins have common, complementary and selective functions relevant for neurodegenerative diseases.
2021-04-14 | GSE171992 | GEO
Project description:Single-cell RNA-seq (scRNA-seq) is emerging as a powerful tool to dissect cell-specific effects of drug treatment in complex tissues. This application requires high levels of precision, robustness, and quantitative accuracy beyond those achievable with current methods for qualitative single cell characterization. Here, we establish the use of standardized reference cells as spike-in controls for accurate and robust dissection of single-cell drug responses. We find that contamination by cell-free RNA can constitute up to 20% of reads in human primary tissue samples, and show that the ensuing biases can effectively be removed by a novel bioinformatics method. Applying this method to both human and mouse pancreatic islets treated ex vivo, we obtain an accurate and quantitative assessment of cell-specific drug effects on the transcriptome. We observe that FOXO inhibition induces dedifferentiation of both alpha and beta cells, while artemether treatment upregulates insulin and other beta cell marker genes in a subset of alpha cells. In beta cells, dedifferentiation and insulin repression upon artemether treatment occurs predominantly in mouse but not in human samples. This new method for quantitative, error-correcting, scRNA-seq data normalization using spike-in reference cells allows to clarify the complexities of the cell-specific effects of pharmacological perturbations with single-cell resolution and high quantitative accuracy.
2020-03-19 | GSE142465 | GEO
Project description:Transcriptomic profiling of metastatic NSCLC cancer patients from tumor tissue and organ-matched normal tissue as reference which were taken as part of the WINTHER clinical trial. The organ-matched normal tissues were used in order to eliminate host gene expression variability while discarding most genetic variability between individuals. The goal was to trial was to navigate patients to therapy on the basis of fresh biopsy-derived DNA sequencing or RNA expression
2021-04-09 | GSE171702 | GEO
Project description:The short length of miRNAs results in a high dynamic range of melting temperatures and therefore impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here we developed a new method based not only to the hybridization process that presents the limits before described, but integrating the hybridization to an enzymatic reaction. Moreover we introduced spike-in in the hybridization-enzymatic reaction allowing the quantification of miRNAs respect to them, canceling biases related to sequence, labeling, or hybridization. An alternative method for the absolute miRNA quantization was recently proposed by Bissels (Absolute quantification of microRNAs by using a universal reference. RNA). It was based on the Absolute quantification of microRNAs by using a universal reference consisting of 954 synthetic human, mouse, rat, and viral miRNAs, with each individual oligoribonucleotide present in equimolar concentrations with tested miRNAs. Thereby, any single miRNA detected on a microarray can be quantified by directly comparing its signal intensity with the one obtained by the same miRNA sequence present in the universal reference adjusting for biases related to sequence, labeling, hybridization, or signal detection. Our method allowed the detection of a comparable concentration of miRNA (10^-18 moles to 10^-14 moles in a linear range), but allows controlling the hybridization quality and reproducibility basing on the results of the interpolation of the spike-in dependent curve. Moreover, our method does not influenced by phenomena imputable to different labeling process due to different sequences because labeling was due only to the incorporation of biotin-d(A) if the hybridized miRNA acted as primer for the klenow enzyme. This method allowed the discussion of miRNA genes expression in 9 different tissues relating them with tissue functionality in the cardiocirculatory system.
2014-04-30 | E-MTAB-1938 | biostudies-arrayexpress
Project description:The short length of miRNAs results in a high dynamic range of melting temperatures and therefore impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here we developed a new method based not only to the hybridization process that presents the limits before described, but integrating the hybridization to an enzymatic reaction. Moreover we introduced spike-in in the hybridization-enzymatic reaction allowing the quantification of miRNAs respect to them, canceling biases related to sequence, labeling, or hybridization. An alternative method for the absolute miRNA quantization was recently proposed by Bissels (Absolute quantification of microRNAs by using a universal reference. RNA). It was based on the Absolute quantification of microRNAs by using a universal reference consisting of 954 synthetic human, mouse, rat, and viral miRNAs, with each individual oligoribonucleotide present in equimolar concentrations with tested miRNAs. Thereby, any single miRNA detected on a microarray can be quantified by directly comparing its signal intensity with the one obtained by the same miRNA sequence present in the universal reference adjusting for biases related to sequence, labeling, hybridization, or signal detection. Our method allowed the detection of a comparable concentration of miRNA (10-18 moles to 10-14 moles in a linear range) (see Figure), but allows controlling the hybridization quality and reproducibility basing on the results of the interpolation of the spike-in dependent curve. Moreover, our method does not influenced by phenomena imputable to different labeling process due to different sequences because labeling was due only to the incorporation of biotin-d(A) if the hybridized miRNA acted as primer for the klenow enzyme. This method allowed the discussion of miRNA genes expression in 14 different tissues relating it with tissue anatomical proximity and functional similarity.
2014-03-31 | GSE28140 | GEO
Project description:Alternative splicing of mRNA diversifies the function of human proteins, with tissue- and cell-specific protein isoforms being the most difficult to validate. While transcriptomic experiments enable the detection of many alternatively spliced transcripts, it is not known if these transcripts have protein-coding potential. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and exon-exon junctions of spliced transcripts by integrating transcriptomics and proteomics data. Using the PG Nexus, we analyzed undifferentiated human mesenchymal stem cells and compared the number of protein isoforms validated using different protein sequence database, including public online databases and RNA-seq derived databases. With significant overlaps with other databases, we identified 8,011 exons and 3,824 splice junctions with the Ensembl database. Both exonic and junction peptides were important for protein isoform validation. The Ensembl database consistently outperformed the other data sources, but predicted open reading frames from RNA-seq derived transcripts were comparable, with only 6 less splice junctions validated. Using proteotypic and isoform-specific peptides, we validated 462 protein isoforms. This number increases to 1,083 if multiple proteotypic peptides per protein are included. Multiplexing proteotypic peptides in SRM assays or similar experiments will increase the confidence and coverage of protein isoform validation experiments.
2015-05-20 | PXD001449 | Pride
Project description:Background.The cell-free methylated DNA immunoprecipitation-sequencing (cfMeDIP-seq) method, is adapted to work with low input DNA and with circulating cell-free DNA (cfDNA). This method allowsfor epigenetic profiling from liquid biopsy samples, providing potential information about tissue of origin. Similar to classical immunoprecipitation based enrichment protocols, interpretation requires a referenceor control to draw inference against a composite experimental baseline and against designed standards allowing for cross-experiment comparisons. Methods.To meet the need for a reference control in cfMeDIP-seqexperiments, we designed spike-in controlsand integrated the use of unique molecular index (UMI) to adjust for polymerase chain reaction (PCR)bias, and immunoprecipitation bias caused by the fragment length, G+C content, and CpG density ofthe DNA fragments. This enables for absolute quantification of methylated DNA in picomoles, while retaining epigenomic information that allows for sensitive, tissue-specific detection as well as comparableresults between different experiments. We designed 54 DNA fragments with combinations of methylationstatus (methylated and unmethylated), fragment length in base pair (bp) (80 bp,160 bp,320 bp), G+C content (35%,50%,65%), and fraction of CpGs within a fragment (1/80 bp,1/40 bp,1/20 bp). We checked spike-in control DNA sequence to ensure they had no cross alignment to the human genome and minimized formation of secondary structures to avoid issues with amplification. We carried outcfMeDIP-seq on either solely spike-in DNA fragments, spike-in DNA added to sheared HCT116 genomic DNA or spike-inDNA added tocfDNAfrom acute myeloid leukemia (AML) samples to assess technical and biological biases, determine optimal amount of spike-in DNA required for an experiment and to assess batch effects,respectively. Results. We show thatcfMeDIP-seqenriches for highly methylated regions, with less than 0.01%non-specific binding and preference to high G+C content and CpG fraction DNA fragments. The use of 0.01 ngof spike-in control DNA results in sufficient sequencing reads to adjust for variance due to fragment length,G+C content and CpG fraction without negatively impacting the number of sequencing reads generatedfor each sample. With known amount of each spike-in control, we generated a generalized linear modelthat can absolutely quantify molar amount from read counts while adjusting for fragment length, G+C content, and CpG fraction. Using our spike-in controls, we show that we can greatly mitigate batch effects,reducing batch associated variance in the data to ≤5%of the total variance. Conclusions.The incorporation of spike-in controls allows for easier interpretation of data generated from cfMeDIP-seq and MeDIP-seq experiments when compared to relative read count. Through the use of a generalized linear model tailored to each experiment, molar amount for each genomic region can becalculated, greatly mitigating both biological and technical biases in the data. We have created an Rpackage, spiky, to convert read counts to DNA picomoles while adjusting for fragment length, G+C contentand CpG fraction.
2021-02-16 | GSE166259 | GEO
Project description:Normalization of RNA sequencing (RNA-seq) data for gene expression comparison is essential to ensure accurate gene expression quantification. It has been argued that samples with large differences in global expression level cannot be properly normalized without spike-in control RNAs, however, spike-in controls are expensive and not yet widely used. Here, we presented a spike-in independent quantitative RNA sequencing (siqRNA-seq) method, which uses reads from genome DNA as an internal reference to quantify gene expression level. We showed that siqRNA-seq profiles gene expression as traditional RNA-seq, but allows to identify different expression genes between samples with distinct mRNA content. We also showed siqRNA-seq enable us to assess the copy number of mRNA per cell without counting cells and adding spike-ins. Thus, siqRNA-seq provides a convenient and versatile means to quantitatively profile the mRNA landscape in cells.
2024-04-08 | GSE223145 | GEO
Project description:The short length of miRNAs results in a high dynamic range of melting temperatures and therefore impedes a proper selection of detection probes or optimized PCR primers. While miRNA microarrays allow for massive parallel and accurate relative measurement of all known miRNAs, they have so far been less useful as an assay for absolute quantification. Here we developed a new method based not only to the hybridization process that presents the limits before described, but integrating the hybridization to an enzymatic reaction. Moreover we introduced spike-in in the hybridization-enzymatic reaction allowing the quantification of miRNAs respect to them, canceling biases related to sequence, labeling, or hybridization. An alternative method for the absolute miRNA quantization was recently proposed by Bissels (Absolute quantification of microRNAs by using a universal reference. RNA). It was based on the Absolute quantification of microRNAs by using a universal reference consisting of 954 synthetic human, mouse, rat, and viral miRNAs, with each individual oligoribonucleotide present in equimolar concentrations with tested miRNAs. Thereby, any single miRNA detected on a microarray can be quantified by directly comparing its signal intensity with the one obtained by the same miRNA sequence present in the universal reference adjusting for biases related to sequence, labeling, hybridization, or signal detection. Our method allowed the detection of a comparable concentration of miRNA (10-18 moles to 10-14 moles in a linear range) (see Figure), but allows controlling the hybridization quality and reproducibility basing on the results of the interpolation of the spike-in dependent curve. Moreover, our method does not influenced by phenomena imputable to different labeling process due to different sequences because labeling was due only to the incorporation of biotin-d(A) if the hybridized miRNA acted as primer for the klenow enzyme. This method allowed the discussion of miRNA genes expression in 14 different tissues relating it with tissue anatomical proximity and functional similarity. 2K microarray was hybridized with small RNAs from 14 different tissues (Atrium Sinister; Skin; Liver; W_B_A: White Blood Cells from Arteriosum blood; W_B_V: White Blood Cells from Venosum blood; Lymph Node; Tongue; Spleen; Skeletal Muscle; Lung; Kidney; Stomach; Adipose Tissue; Ventricle Sinister). Each experiment was replicated to have 28 experiments and miRNA gene expression was correlated with mRNA gene expression in the same samples.
2014-03-31 | E-GEOD-28140 | biostudies-arrayexpress