Browse
Submit Data
Databases
API
Help

Dataset Information

14 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Replicate sequencing libraries are important for quantification of allelic imbalance.

ABSTRACT: A sensitive approach to quantitative analysis of transcriptional regulation in diploid organisms is analysis of allelic imbalance (AI) in RNA sequencing (RNA-seq) data. A near-universal practice in such studies is to prepare and sequence only one library per RNA sample. We present theoretical and experimental evidence that data from a single RNA-seq library is insufficient for reliable quantification of the contribution of technical noise to the observed AI signal; consequently, reliance on one-replicate experimental design can lead to unaccounted-for variation in error rates in allele-specific analysis. We develop a computational approach, Qllelic, that accurately accounts for technical noise by making use of replicate RNA-seq libraries. Testing on new and existing datasets shows that application of Qllelic greatly decreases false positive rate in allele-specific analysis while conserving appropriate signal, and thus greatly improves reproducibility of AI estimates. We explore sources of technical overdispersion in observed AI signal and conclude by discussing design of RNA-seq studies addressing two biologically important questions: quantification of transcriptome-wide AI in one sample, and differential analysis of allele-specific expression between samples.

SUBMITTER: Mendelevich A

PROVIDER: S-EPMC8184992 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Pacybara: accurate long-read sequencing for barcoded mutagenized allelic libraries.

Project description:MotivationLong-read sequencing technologies, an attractive solution for many applications, often suffer from higher error rates. Alignment of multiple reads can improve base-calling accuracy, but some applications, e.g. sequencing mutagenized libraries where multiple distinct clones differ by one or few variants, require the use of barcodes or unique molecular identifiers. Unfortunately, sequencing errors can interfere with correct barcode identification, and a given barcode sequence may be linked to multiple independent clones within a given library.ResultsHere we focus on the target application of sequencing mutagenized libraries in the context of multiplexed assays of variant effects (MAVEs). MAVEs are increasingly used to create comprehensive genotype-phenotype maps that can aid clinical variant interpretation. Many MAVE methods use long-read sequencing of barcoded mutant libraries for accurate association of barcode with genotype. Existing long-read sequencing pipelines do not account for inaccurate sequencing or nonunique barcodes. Here, we describe Pacybara, which handles these issues by clustering long reads based on the similarities of (error-prone) barcodes while also detecting barcodes that have been associated with multiple genotypes. Pacybara also detects recombinant (chimeric) clones and reduces false positive indel calls. In three example applications, we show that Pacybara identifies and correctly resolves these issues.Availability and implementationPacybara, freely available at https://github.com/rothlab/pacybara, is implemented using R, Python, and bash for Linux. It runs on GNU/Linux HPC clusters via Slurm, PBS, or GridEngine schedulers. A single-machine simplex version is also available.

| S-EPMC11021806 | biostudies-literature

False negatives in GBA1 sequencing due to polymerase dependent allelic imbalance.

Project description:A variant in the GBA1 gene is one of the most common genetic risk factors to develop Parkinson's disease (PD). Here the serendipitous finding is reported of a polymerase dependent allelic imbalance when using next generation sequencing, potentially resulting in false-negative results when the allele frequency falls below the variant calling threshold (by default commonly at 30%). The full GBA1 gene was sequenced using next generation sequencing on saliva derived DNA from PD patients. Four polymerase chain reaction conditions were varied in twelve samples, to investigate the effect on allelic imbalance: (1) the primers (n = 4); (2) the polymerase enzymes (n = 2); (3) the primer annealing temperature (Ta) specified for the used polymerase; and (4) the amount of DNA input. Initially, 1295 samples were sequenced using Q5 High-Fidelity DNA Polymerase. 112 samples (8.6%) had an exonic variant and an additional 104 samples (8.0%) had an exonic variant that did not pass the variant frequency calling threshold of 30%. After changing the polymerase to TaKaRa LA Taq DNA Polymerase Hot-Start Version: RR042B, all samples had an allele frequency passing the calling threshold. Allele frequency was unaffected by a change in primer, annealing temperature or amount of DNA input. Sequencing of the GBA1 gene using next generation sequencing might be susceptible to a polymerase specific allelic imbalance, which can result in a large amount of flase-negative results. This was resolved in our case by changing the polymerase. Regions displaying low variant calling frequencies in GBA1 sequencing output in previous and future studies might warrant additional scrutiny.

| S-EPMC7794395 | biostudies-literature

Allelic imbalance sequencing reveals that single-nucleotide polymorphisms frequently alter microRNA-directed repression.

Project description:Genetic changes that help explain the differences between two individuals might create or disrupt sites complementary to microRNAs (miRNAs), but the extent to which such polymorphic sites influence miRNA-mediated repression is unknown. Here, we describe a method to measure mRNA allelic imbalances associated with a regulatory site found in mRNA transcribed from one allele but not found in that transcribed from the other. Applying this method, called allelic imbalance sequencing, to sites for three miRNAs (miR-1, miR-133 and miR-122) provided quantitative measurements of repression in vivo without altering either the miRNAs or their targets. A substantial fraction of polymorphic sites mediated repression in tissues that expressed the cognate miRNA, and downregulation was correlated with site type and site context. Extrapolating these results to the other broadly conserved miRNAs suggests that when comparing two mouse strains (or two human individuals), polymorphic miRNA sites cause expression of many genes (often hundreds) to differ.

| S-EPMC2828817 | biostudies-literature

ExomeAI: detection of recurrent allelic imbalance in tumors using whole-exome sequencing data.

Project description:SummaryWhole-exome sequencing (WES) has extensively been used in cancer genome studies; however, the use of WES data in the study of loss of heterozygosity or more generally allelic imbalance (AI) has so far been very limited, which highlights the need for user-friendly and flexible software that can handle low-quality datasets. We have developed a statistical approach, ExomeAI, for the detection of recurrent AI events using WES datasets, specifically where matched normal samples are not available.AvailabilityExomeAI is a web-based application, publicly available at: http://genomequebec.mcgill.ca/exomeai.ContactJavadNadaf@gmail.com or somayyeh.fahiminiya@mcgill.caSupplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC4308664 | biostudies-literature

Unexpected variability of allelic imbalance estimates from RNA sequencing

Project description:RNA sequencing and other experimental methods producing large amounts of data are increasingly dominant in molecular biology. However, the noise properties of these techniques are not fully appreciated. We assessed how reproducible are the measurements of allele-specific expression between replicate RNA-seq experiments from the same RNA sample. Surprisingly, estimates of allelic imbalance (AI) varied between technical replicates up to 8-fold higher than expected from commonly applied noise models. We show that AI overdispersion substantially varies between replicates and experimental series, appears to arise during the construction of sequencing libraries, and can be measured by comparing technical replicates. We demonstrate that compensation for AI overdispersion greatly reduces technical variation and enables reliable differential analysis of allele-specific expression across samples and across experiments. Conversely, not taking AI overdispersion into account can lead to a substantial number of false positives in analysis of allele-specific gene expression.

2021-03-26 | GSE143310 | GEO

Quantification of massively parallel sequencing libraries - a comparative study of eight methods.

Project description:Quantification of massively parallel sequencing libraries is important for acquisition of monoclonal beads or clusters prior to clonal amplification and to avoid large variations in library coverage when multiple samples are included in one sequencing analysis. No gold standard for quantification of libraries exists. We assessed eight methods of quantification of libraries by quantifying 54 amplicon, six capture, and six shotgun fragment libraries. Chemically synthesized double-stranded DNA was also quantified. Light spectrophotometry, i.e. NanoDrop, was found to give the highest concentration estimates followed by Qubit and electrophoresis-based instruments (Bioanalyzer, TapeStation, GX Touch, and Fragment Analyzer), while SYBR Green and TaqMan based qPCR assays gave the lowest estimates. qPCR gave more accurate predictions of sequencing coverage than Qubit and TapeStation did. Costs, time-consumption, workflow simplicity, and ability to quantify multiple samples are discussed. Technical specifications, advantages, and disadvantages of the various methods are pointed out.

| S-EPMC5773690 | biostudies-other

Rapid and powerful detection of subtle allelic imbalance from exome sequencing data with hapLOHseq.

Project description:MotivationThe detection of subtle genomic allelic imbalance events has many potential applications. For example, identifying cancer-associated allelic imbalanced regions in low tumor-cellularity samples or in low-proportion tumor subclones can be used for early cancer detection, prognostic assessment and therapeutic selection in cancer patients. We developed hapLOHseq for the detection of subtle allelic imbalance events from next-generation sequencing data.ResultsOur method identified events of 10 megabases or greater occurring in as little as 16% of the sample in exome sequencing data (at 80×) and 4% in whole genome sequencing data (at 30×), far exceeding the capabilities of existing software. We also found hapLOHseq to be superior at detecting large chromosomal changes across a series of pancreatic samples from TCGA.Availability and implementationhapLOHseq is available at scheet.org/software, distributed under an open source MIT license.Contactpscheet@alum.wustl.eduSupplementary informationSupplementary data are available at Bioinformatics online.

| S-EPMC5039922 | biostudies-literature

Allelic imbalance in CALR somatic mutagenesis.

Project description: Not available

| S-EPMC4430307 | biostudies-literature

RNA-sequencing reveals allelic expression imbalance in the diploid pathogen Candida albicans

Project description:The diploid fungal pathogen Candida albicans is a highly heterozygous organism, with numerous non-synonymous substitutions often seen within two alleles. RNA-sequencing of the wild-type strain SC5314 has revealed 233 genes with significant levels of allelic expression imbalance. Overall percentage protein identity comparisons were significantly lower in these differentially expressed alleles. This suggests that two different, perhaps functionally divergent, proteins are being expressed at significantly different quantities by the two alleles of a single gene. Previously, gene expression levels have been correlated with structural factors such as GC content, ORF length and codon usage. Here, these factors were first correlated with overall gene expression data to decipher the relationship they have with gene expression in Candida albicans. These relationships were then used to assess the contribution of these factors to allelic expression imbalance. GC content and codon usage did not differ significantly in differentially expressed alleles whereas ORF length was found to be significantly lower in the allele with lowest expression. This surprising result goes against the overall trend observed between length and gene expression. Differences in GC content and ORF length between alleles correlated strongly with percentage protein identity, suggesting an indirect link between these factors and allelic expression imbalance. One sample (SC5314: wild-type strain) assessed in triplicate and compared to the reference diploid genome

2014-06-30 | E-GEOD-35233 | biostudies-arrayexpress

Contribution of allelic imbalance to colorectal cancer.

Project description:Point mutations in cancer have been extensively studied but chromosomal gains and losses have been more challenging to interpret due to their unspecific nature. Here we examine high-resolution allelic imbalance (AI) landscape in 1699 colorectal cancers, 256 of which have been whole-genome sequenced (WGSed). The imbalances pinpoint 38 genes as plausible AI targets based on previous knowledge. Unbiased CRISPR-Cas9 knockout and activation screens identified in total 79 genes within AI peaks regulating cell growth. Genetic and functional data implicate loss of TP53 as a sufficient driver of AI. The WGS highlights an influence of copy number aberrations on the rate of detected somatic point mutations. Importantly, the data reveal several associations between AI target genes, suggesting a role for a network of lineage-determining transcription factors in colorectal tumorigenesis. Overall, the results unravel the contribution of AI in colorectal cancer and provide a plausible explanation why so few genes are commonly affected by point mutations in cancers.

| S-EPMC6131244 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data