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Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions

ABSTRACT: We employ a massively parallel reporter assay (MPRA) to measure the ex vivo activities in K562 and HepG2 cells of more than 15,000 human candidate regulatory regions. The regulatory regions were tiled with overlapping constructs enabling high resolution computational inference of activating and repressive nucleotides.

ORGANISM(S): Escherichia coli Homo sapiens

PROVIDER: GSE71279 | GEO | 2016/08/12

SECONDARY ACCESSION(S): PRJNA290789

REPOSITORIES: GEO

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Project description:Subcellular mRNA localization and local translation are essential mechanisms for fine-tuning the spatiotemporal regulation of gene expression in the nervous system. While these processes have been extensively characterized in neurons, the cis-regulatory sequences mediating them in astrocytes remains poorly understood. Here, we developed an in vivo Massively Parallel Reporter Assay (MPRA), termed SN-MPRA, to systematically interrogate the sequence determinants of mRNA localization and local translation in astrocytes. To our knowledge, this represents the first application of an in vivo MPRA to study these processes. Using the SN-MPRA, we comprehensively tiled the 3′ untranslated regions (UTRs) of two locally translated mRNAs in astrocytes, Glt1 and Sparc. This approach enabled us to evaluate multiple models of RNA localization, including increased transcript abundance, “zip-code” elements, and RNA secondary structure. Given that astrocytes do not exhibit the high, unidirectional polarity of neurons, one potential mechanism of driving mRNA localization is that increased transcript abundance leads to increased likelihood of delivery or diffusion to peripheral astrocyte processes (PAPs). Although transcript abundance showed a moderate association with localization, it was insufficient to fully explain differences in localization patterns, suggesting additional sequence-dependent mechanisms. Global 3’ UTR features such as GC content and secondary structure did not correlate with localization. Instead, we identified groups of overlapping tiles with consistent localization, suggesting the presence of cis-regulatory sequence motifs. We validated the sufficiency and necessity of one of these groups[JD1.1] to drive increased local translation and found that this region had similar expression to the full 3’ UTR throughout the entire cell, whereas deletion of this region decreased expression. To further resolve the sequence motifs causing these effects, we designed a single-nucleotide mutagenesis SN-MPRA library targeting 8 element groups with shared localization. This analysis uncovered discrete regions in which nucleotide mutations disrupt localization and local translation. While a subset of these regions overlapped with known RNA-binding protein motifs, including KHDRBS1, many did not correspond to previously annotated binding sites, suggesting that multiple and potentially distinct mechanisms, such as RNA:protein interactions, RNA stability, and other cis-regulatory features, may contribute to mRNA localization in astrocytes. Together, these findings establish a high-throughput in vivo framework for identifying cis-regulatory sequences driving RNA localization and local translation and reveal that astrocytes likely employ diverse mechanisms to regulate subcellular gene expression. More broadly, the SN-MPRA provides a platform for studying RNA localization in vivo, where cellular context and intercellular interactions are preserved.

Project description:Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ~98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 440 variants with allelic regulatory effects (MPRA-positive variants), with 72% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 273 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.

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Genome-scale high-resolution mapping of activating and repressive nucleotides in regulatory regions

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