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Genome-wide strand asymmetry in massively parallel reporter activity favors genic strands.

ABSTRACT: Massively parallel reporter assays (MPRAs) are useful tools to characterize regulatory elements in human genomes. An aspect of MPRAs that is not typically the focus of analysis is their intrinsic ability to differentiate activity levels for a given sequence element when placed in both of its possible orientations relative to the reporter construct. Here, we describe pervasive strand asymmetry of MPRA signals in data sets from multiple reporter configurations in both published and newly reported data. These effects are reproducible across different cell types and in different treatments within a cell type and are observed both within and outside of annotated regulatory elements. From elements in gene bodies, MPRA strand asymmetry favors the sense strand, suggesting that function related to endogenous transcription is driving the phenomenon. Similarly, we find that within Alu mobile element insertions, strand asymmetry favors the transcribed strand of the ancestral retrotransposon. The effect is consistent across the multiplicity of Alu elements in human genomes and is more pronounced in less diverged Alu elements. We find sequence features driving MPRA strand asymmetry and show its prediction from sequence alone. We see some evidence for RNA stabilization and transcriptional activation mechanisms and hypothesize that the effect is driven by natural selection favoring efficient transcription. Our results indicate that strand asymmetry is a pervasive and reproducible feature in MPRA data. More importantly, the fact that MPRA asymmetry favors naturally transcribed strands suggests that it stems from preserved biological functions that have a substantial, global impact on gene and genome evolution.

SUBMITTER: Roberts BS

PROVIDER: S-EPMC8092006 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Motivation:The majority of the human genome is composed of non-coding regions containing regulatory elements such as enhancers, which are crucial for controlling gene expression. Many variants associated with complex traits are in these regions, and may disrupt gene regulatory sequences. Consequently, it is important to not only identify true enhancers but also to test if a variant within an enhancer affects gene regulation. Recently, allele-specific analysis in high-throughput reporter assays, such as massively parallel reporter assays (MPRAs), have been used to functionally validate non-coding variants. However, we are still missing high-quality and robust data analysis tools for these datasets. Results:We have further developed our method for allele-specific analysis QuASAR (quantitative allele-specific analysis of reads) to analyze allele-specific signals in barcoded read counts data from MPRA. Using this approach, we can take into account the uncertainty on the original plasmid proportions, over-dispersion, and sequencing errors. The provided allelic skew estimate and its standard error also simplifies meta-analysis of replicate experiments. Additionally, we show that a beta-binomial distribution better models the variability present in the allelic imbalance of these synthetic reporters and results in a test that is statistically well calibrated under the null. Applying this approach to the MPRA data, we found 602 SNPs with significant (false discovery rate 10%) allele-specific regulatory function in LCLs. We also show that we can combine MPRA with QuASAR estimates to validate existing experimental and computational annotations of regulatory variants. Our study shows that with appropriate data analysis tools, we can improve the power to detect allelic effects in high-throughput reporter assays. Availability and implementation:http://github.com/piquelab/QuASAR/tree/master/mpra. Contact:fluca@wayne.edu or rpique@wayne.edu. Supplementary information:Supplementary data are available online at Bioinformatics.

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Genome-wide strand asymmetry in massively parallel reporter activity favors genic strands.

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