Introns control stochastic allele expression bias
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ABSTRACT:
SUBMITTER: Sands B
PROVIDER: S-EPMC8585970 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Stochastic and deterministic allele specific gene expression (ASE) might influence single cell phenotype, but the extent and nature of the phenomenon at the onset of early mouse development is unknown. Here we performed single cell RNA-Seq analysis of single blastomeres of mouse embryos, which revealed significant changes in the transcriptome. Importantly, over half of the transcripts with detectable genetic polymorphisms exhibit ASE, most notably, individual blastomeres from the same two-cell embryo show similar pattern of ASE. However, about 6% of them exhibit stochastic expression, indicated by altered expression ratio between the two alleles. Thus, we demonstrate that ASE is both deterministic and stochastic in early blastomeres. Furthermore, we also found that 1,718 genes express two isoforms with different lengths of 3'UTRs, with the shorter one on average 5-6 times more abundant in early blastomeres compared to the transcripts in epiblast cells, suggesting that microRNA mediated regulation of gene expression acquires increasing importance as development progresses.
| S-EPMC3121735 | biostudies-literature
Project description:Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.
| S-EPMC4274012 | biostudies-literature
Project description:Pervasive allelic variation at both gene and single nucleotide level (SNV) between individuals is commonly associated with complex traits in humans and animals. Allele-specific expression (ASE) analysis, using RNA-Seq, can provide a detailed annotation of allelic imbalance and infer the existence of cis-acting transcriptional regulation. However, variant detection in RNA-Seq data is compromised by biased mapping of reads to the reference DNA sequence. In this manuscript, we describe an unbiased standardized computational pipeline for allele-specific expression analysis using RNA-Seq data, which we have adapted and developed using tools available under open license. The analysis pipeline we present is designed to minimize reference bias while providing accurate profiling of allele-specific expression across tissues and cell types. Using this methodology, we were able to profile pervasive allelic imbalance across tissues and cell types, at both the gene and SNV level, in Texel×Scottish Blackface sheep, using the sheep gene expression atlas data set. ASE profiles were pervasive in each sheep and across all tissue types investigated. However, ASE profiles shared across tissues were limited, and instead, they tended to be highly tissue-specific. These tissue-specific ASE profiles may underlie the expression of economically important traits and could be utilized as weighted SNVs, for example, to improve the accuracy of genomic selection in breeding programs for sheep. An additional benefit of the pipeline is that it does not require parental genotypes and can therefore be applied to other RNA-Seq data sets for livestock, including those available on the Functional Annotation of Animal Genomes (FAANG) data portal. This study is the first global characterization of moderate to extreme ASE in tissues and cell types from sheep. We have applied a robust methodology for ASE profiling to provide both a novel analysis of the multi-dimensional sheep gene expression atlas data set and a foundation for identifying the regulatory and expressed elements of the genome that are driving complex traits in livestock.
| S-EPMC6761296 | biostudies-literature
Project description:The HIV promoter within the viral long terminal repeat (LTR) orchestrates many aspects of the viral life cycle, from the dynamics of viral gene expression and replication to the establishment of a latent state. In particular, after viral integration into the host genome, stochastic fluctuations in viral gene expression amplified by the Tat positive feedback loop can contribute to the formation of either a productive, transactivated state or an inactive state. In a significant fraction of cells harboring an integrated copy of the HIV-1 model provirus (LTR-GFP-IRES-Tat), this bimodal gene expression profile is dynamic, as cells spontaneously and continuously flip between active (Bright) and inactive (Off) expression modes. Furthermore, these switching dynamics may contribute to the establishment and maintenance of proviral latency, because after viral integration long delays in gene expression can occur before viral transactivation. The HIV-1 promoter contains cis-acting Sp1 and NF-kappaB elements that regulate gene expression via the recruitment of both activating and repressing complexes. We hypothesized that interplay in the recruitment of such positive and negative factors could modulate the stability of the Bright and Off modes and thereby alter the sensitivity of viral gene expression to stochastic fluctuations in the Tat feedback loop. Using model lentivirus variants with mutations introduced in the Sp1 and NF-kappaB elements, we employed flow cytometry, mRNA quantification, pharmacological perturbations, and chromatin immunoprecipitation to reveal significant functional differences in contributions of each site to viral gene regulation. Specifically, the Sp1 sites apparently stabilize both the Bright and the Off states, such that their mutation promotes noisy gene expression and reduction in the regulation of histone acetylation and deacetylation. Furthermore, the NF-kappaB sites exhibit distinct properties, with kappaB site I serving a stronger activating role than kappaB site II. Moreover, Sp1 site III plays a particularly important role in the recruitment of both p300 and RelA to the promoter. Finally, analysis of 362 clonal cell populations infected with the viral variants revealed that mutations in any of the Sp1 sites yield a 6-fold higher frequency of clonal bifurcation compared to that of the wild-type promoter. Thus, each Sp1 and NF-kappaB site differentially contributes to the regulation of viral gene expression, and Sp1 sites functionally "dampen" transcriptional noise and thereby modulate the frequency and maintenance of this model of viral latency. These results may have biomedical implications for the treatment of HIV latency.
| S-EPMC2607019 | biostudies-literature
Project description:The use of RNA-seq as the preferred method for the discovery and validation of small RNA biomarkers is hindered by high variability and biased sequence counts. In this paper we develop a statistical model for sequence counts that accounts for ligase bias and stochastic variation in library amplification steps and sequencing depth variation. Our analytical contributions are the description of the Linear Quadratic (LQ) relation between the mean and variance of the sequence counts in an RNA-seq experiment and the derivation of the Poisson truncated mixture as the underlying probability distribution for RNA-seq data. Using a large number of sequencing datasets, we demonstrate here how one can use this modeling framework to calculate empirical correction factors for ligase bias, while accounting for random variation in sequence counts. Bias correction may remove the majority of bias in the absence of differential expression and more than 40% of the bias in the presence of variable expression of miRNAs. Empirical bias correction factors appear to be nearly constant over at least one and up to four orders of magnitude of total RNA input and independent of sample composition.
2017-03-15 | GSE93399 | GEO
Project description:We consider the problem of estimating common community structures in multi-layer stochastic block models, where each single layer may not have sufficient signal strength to recover the full community structure. In order to efficiently aggregate signal across different layers, we argue that the sum-of-squared adjacency matrices contain sufficient signal even when individual layers are very sparse. Our method uses a bias-removal step that is necessary when the squared noise matrices may overwhelm the signal in the very sparse regime. The analysis of our method relies on several novel tail probability bounds for matrix linear combinations with matrix-valued coefficients and matrix-valued quadratic forms, which may be of independent interest. The performance of our method and the necessity of bias removal is demonstrated in synthetic data and in microarray analysis about gene co-expression networks.
| S-EPMC10963943 | biostudies-literature
Project description:BackgroundArbuscular mycorrhizal (AM) fungi are arguably the most important symbionts of plants, offering a range of benefits to their hosts. However, the provisioning of these benefits does not appear to be uniform among AM fungal individuals, with genetic variation between fungal symbionts having a substantial impact on plant performance. Interestingly, genetic variation has also been reported within fungal individuals, which contain millions of haploid nuclei sharing a common cytoplasm. In the model AM fungus, Rhizophagus irregularis, several isolates have been reported to be dikaryotes, containing two genetically distinct types of nuclei recognized based on their mating-type (MAT) locus identity. However, their extremely coenocytic nature and lack of a known single nucleus stage has raised questions on the origin, distribution and dynamics of this genetic variation.ResultsHere we performed DNA and RNA sequencing at the mycelial individual, single spore and single nucleus levels to gain insight into the dynamic genetic make-up of the dikaryote-like R. irregularis C3 isolate and the effect of different host plants on its genetic variation. Our analyses reveal that parallel spore and root culture batches can have widely variable ratios of two main genotypes in C3. Additionally, numerous polymorphisms were found with frequencies that deviated significantly from the general genotype ratio, indicating a diverse population of slightly different nucleotypes. Changing host plants did not show consistent host effects on nucleotype ratio's after multiple rounds of subculturing. Instead, we found a major effect of host plant-identity on allele-specific expression in C3.ConclusionOur analyses indicate a highly dynamic/variable genetic organization in different isolates of R. irregularis. Seemingly random fluctuations in nucleotype ratio's upon spore formation, recombination events, high variability of non-tandemly repeated rDNA sequences and host-dependent allele expression all add levels of variation that may contribute to the evolutionary success of these widespread symbionts.
| S-EPMC9883914 | biostudies-literature
Project description:This SuperSeries is composed of the SubSeries listed below.
2008-09-24 | GSE12751 | GEO
Project description:Highly specific amplification of complex DNA pools without bias or template-independent products (TIPs) remains a challenge. We have developed a procedure using phi29 DNA polymerase and trehalose and optimized control of amplification to create micrograms of specific amplicons without TIPs from down to sub-femtograms of DNA. The amplicons from 5 ng and 0.5 ng DNA, which were from originally good quality of gDNA (05-050), or partially degraded gDNA (04-018), were validate with Illumina HumanHap550-Duo Genotyping Beadchip. As seen in (Suppl. Table 5a), the call rates (97.30% to 99.07%) and accuracy or concordance ( > 99.85% for the SNPs called in both amplicon and natural reference) for 5 ng derived amplicons with both Wpa and Gv2 were close to each other and close to native gDNA (call rate: 98.3% to 99.75%). These call rates were better than a recent report (amplicon 95.9% vs. un-amplified 98.5%), in which the early kit Repli-g 625S was applied, and re-genotyping was performed when the performance was low and duplicate samples were filtered for the highest call rate. The genotyping accuracy of Wpa was actually in the same range as the variation in technical replicates with similar SNP typing arrays (99.87% and 99.88%, replicated Affymetrix array, or between Affymetrix and Illumina arrays). Importantly, the genotyping concordance for amplicons generated from 0.5 ng with Wpa (99.88% and 99.69%) were also close to the technical replicates. In this case, the call rates of Wpa were slightlyreduced compared to that with 5 ng input, but the call rate for the partially degraded sample 04-018, was modestly improved over Gv2 (92.06 % vs. 90.53%). Wpa data also showed some amplification non-uniformity among different locations, resulting in some “artificial CNVs” similar to Gv2 (exampled as in Suppl. Fig. 5 and Suppl. Table 6), with the outputs obtained by taking unamplified gDNAs as their reference. This imbalance however was consistent and reproducible for each method but different between Wpa and Gv2. These artificial CNVs can be efficiently cancelled if pair-wise amplified test and reference are compared, as observed in CGH result (Fig. 4 and Suppl. Fig. 4), also supported by others {Pugh 2008}. It is interesting to note that the representation of chromosomal terminal sequences was greatly improved with Wpa compared with Gv2 (Fig. 5), and that some of these regions were significantly under-amplified or even lost with Gv2 (Suppl. Fig. 5 and Suppl. Table 6, 7), as also independently reported recently {Pugh 2008}. This occurred especially in the terminal 3 to 5 Mb and sometimes extended to 10 Mb in many chromosome termini, and was particularly serious when low levels or degraded DNA was as input. An analysis for 5 Mb termini is shown (Suppl. Table 5b calculated all involved SNPs as a cohort. Fig. 5 and Suppl. Tables 6 and 7 were the result for each chromosome terminus). Importantly, the SNP typing was also greatly improved, outstandingly exemplified by the amplicons of 0.5 ng input for the partially degraded 04-018, with Wpa versus Gv2 call rate of 91.9% vs. 84.45% and accuracy of 99.57% vs. 98.62%. The result also showed that these terminal regions underrepresentation in Gv2 was not absolutely associated with the distance-to-end, but possibly was a sequence related issue. Keywords: Whole-pool amplification, whole genome SNP typing
2008-09-24 | GSE12732 | GEO
Project description:To assess the impact of genetic variation in regulatory loci on human health, we constructed a high-resolution map of allelic imbalances in DNA methylation, histone marks, and gene transcription in 71 epigenomes from 36 distinct cell and tissue types from 13 donors. Deep whole-genome bisulfite sequencing of 49 methylomes revealed sequence-dependent CpG methylation imbalances at thousands of heterozygous regulatory loci. Such loci are enriched for stochastic switching, which is defined as random transitions between fully methylated and unmethylated states of DNA. The methylation imbalances at thousands of loci are explainable by different relative frequencies of the methylated and unmethylated states for the two alleles. Further analyses provided a unifying model that links sequence-dependent allelic imbalances of the epigenome, stochastic switching at gene regulatory loci, and disease-associated genetic variation.
| S-EPMC6198826 | biostudies-literature