Widespread Misinterpretable ChIP-seq Bias in Yeast
Ontology highlight
ABSTRACT:
ORGANISM(S): Saccharomyces cerevisiae
PROVIDER: GSE51251 | GEO | 2013/11/15
SECONDARY ACCESSION(S): PRJNA222000
REPOSITORIES: GEO
Similar Datasets
Project description:We report widespread ChIP-seq bias at highly expressed genes in yeast that could lead to misinterpretation ChIP-seq for multiple transcription or chromatin-associated factors and negative controls
2013-11-15 | E-GEOD-51251 | biostudies-arrayexpress
Project description:Usage of synonymous codons represents a characteristic pattern of preference in each organism. It has been inferred that such bias of codon usage has evolved as a result of adaptation for efficient synthesis of proteins. Here we examined synonymous codon usage in genes of the fission yeast Schizosaccharomyces pombe, and compared codon usage bias with expression levels of the gene. In this organism, synonymous codon usage bias was correlated with expression levels of the gene; the bias was most obvious in two-codon amino acids. A similar pattern of the codon usage bias was also observed in Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans, but was not obvious in Oryza sativa, Drosophila melanogaster, Takifugu rubripes and Homo sapiens. As codons of the highly expressed genes have greater influence on translational efficiency than codons of genes expressed at lower levels, it is likely that codon usage in the S. pombe genome has been optimized by translational selection through evolution.
2009-04-01 | GSE13554 | GEO
Project description:MicroRNAs (miRNAs) modulate diverse biological and pathological processes via post-transcriptional gene silencing. High-throughput small RNA sequencing (sRNA-seq) has been widely adopted to investigate the functions and regulatory mechanisms of miRNAs. However, accurate quantification of miRNAs has been limited owing to the severe ligation bias in conventional sRNA-seq methods. Here we quantify miRNAs and their variants (known as isomiRs) by an improved sRNA-seq protocol, termed AQ-seq (accurate quantification by sequencing), that utilizes adapters with terminal degenerate sequences and a high concentration of polyethylene glycol (PEG), which minimize the ligation bias during library preparation. Measurement using AQ-seq allows us to correct the previously misannotated 5′ end usage and strand preference in public databases. Importantly, the analysis of 5′ terminal heterogeneity reveals widespread alternative processing events which have been underestimated. We also identify highly uridylated miRNAs originating from the 3p strands, indicating regulations mediated by terminal uridylyl transferases at the pre-miRNA stage. Taken together, our study reveals the complexity of the miRNA isoform landscape, allowing us to refine miRNA annotation and to advance our understanding of miRNA regulation. Furthermore, AQ-seq can be adopted to improve other ligation-based sequencing methods including crosslinking-immunoprecipitation-sequencing (CLIP-seq) and ribosome profiling (Ribo-seq).
2018-12-12 | GSE123627 | GEO
Project description:Usage of synonymous codons represents a characteristic pattern of preference in each organism. It has been inferred that such bias of codon usage has evolved as a result of adaptation for efficient synthesis of proteins. Here we examined synonymous codon usage in genes of the fission yeast Schizosaccharomyces pombe, and compared codon usage bias with expression levels of the gene. In this organism, synonymous codon usage bias was correlated with expression levels of the gene; the bias was most obvious in two-codon amino acids. A similar pattern of the codon usage bias was also observed in Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans, but was not obvious in Oryza sativa, Drosophila melanogaster, Takifugu rubripes and Homo sapiens. As codons of the highly expressed genes have greater influence on translational efficiency than codons of genes expressed at lower levels, it is likely that codon usage in the S. pombe genome has been optimized by translational selection through evolution. Relative amounts of mRNA for each ORF were measured by DNA microarray using genomic DNA as a reference, and the copy number of mRNA was calculated using an estimate of the total mRNA number in the cell as 100,000 copies.
2010-06-20 | E-GEOD-13554 | biostudies-arrayexpress
Project description:Bias-minimized quantification of microRNA reveals widespread alternative processing and 3′ end modification
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Project description: Not available
| S-EPMC3857294 | biostudies-literature
Project description:Widespread Misinterpretable ChIP-seq Bias in Yeast
| PRJNA222000 | ENA
Project description:71 liver RNA samples from three mouse strains - DBA/2J, C57BL/6J and C3H/HeJ - were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. Keywords: Grouped
2008-03-30 | GSE10736 | GEO
Project description:71 liver RNA samples from three mouse strains - DBA/2J, C57BL/6J and C3H/HeJ - were profiled using a custom-designed microarray monitoring exon and exon-junction expression of 1,020 genes representing 9,406 exons. Gene expression was calculated via two different methods, using the 3'-most exon probe ("3' gene expression profiling") and using all probes associated with the gene ("whole-transcript gene expression profiling"), while exon expression was determined using exon probes and flanking junction probes that spanned across the neighboring exons("exon expression profiling"). Widespread strain and sex influences were detected using a two-way Analysis of Variance (ANOVA) regardless of the profiling method used. However, over 90% of the genes identified in 3' gene expression profiling or whole transcript profiling were identified in exon profiling, along with 75% and 38% more genes, respectively, showing evidence of differential isoform expression. Overall, 55% and 32% of genes, respectively, exhibited strain- and sex-bias differential gene or exon expression. Keywords: Grouped Hybridization material was generated through a random-priming amplification of poly[A]+ purified RNA using primers with a random sequence at the 3' end and a fixed motif at the 5' end that was optimized to generate strand-specific cDNA copies of full-length mRNA transcripts [32]. Since the region used for exon and junction probe selection is constrained to a smaller region, more probes contain sequence with suboptimal characteristics (e.g. high GC content or higher homology to other genes). The hybridization of cDNA, rather than cRNA as commonly done, partially mitigates this issue due to higher specificity and lower background levels [24]. Hybridization conditions were as previously described [33]. All 71 samples were hybridized in a two-channel experiment, where one channel was a common reference, generated by pooling all 71 samples in equal mass. Array hybridizations were done in duplicate with fluor reversal to systematically correct for Cy3/Cy5 dye bias. Array images were processed as described to obtain background noise, single channel intensity and associated measurement error estimates [34]. Expression changes between samples and pool were quantified as mean log10(expression ratio), and associated error.
2010-05-25 | E-GEOD-10736 | biostudies-arrayexpress
Project description:Single-cell RNA-Sequencing (scRNA-Seq) provides high-resolution insights into complex tissues. Cardiac tissue, however, poses a major challenge due to the delicate isolation process and the large size of mature cardiomyocytes. Regardless of the experimental technique, captured cells are often impaired and some capture sites may contain multiple or no cells at all. All this refers to “low quality” potentially leading to data misinterpretation. Common standard quality control parameters involve the number of detected genes and transcripts per cell and the fraction of transcripts from mitochondrial genes (%mtDNA). While cutoffs for transcripts and genes per cell are usually user-defined for each experiment or individually calculated, a fixed threshold of 5% mtDNA is standard and often set as default in scRNA-Seq software. However, this parameter is highly dependent on the tissue type. In the heart, mitochondrial transcripts comprise almost 30% of total mRNA due to high energy demands. Here, we demonstrate that a 5%-threshold not only causes an unacceptable exclusion of cardiomyocytes but also introduces a bias that particularly discriminates pacemaker cells. This effect is apparent for our in vitro generated induced-sinoatrial-bodies (iSABs; highly enriched physiologically functional pacemaker cells), and also evident in a public dataset of cells isolated from embryonal murine sinoatrial node tis-sue [2]. Taken together, we recommend omitting this filtering parameter for scRNA-Seq in cardiovascular applications whenever possible.
2021-05-28 | GSE174233 | GEO