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Allele-specific protein-RNA binding is an essential aspect that may reveal functional genetic variants (GVs) mediating post-transcriptional regulation. Recently, genome-wide detection of in vivo binding of RNA-binding proteins is greatly facilitated by the enhanced crosslinking and immunoprecipitation (eCLIP) method. We developed a new computational approach, called BEAPR, to identify allele-specific binding (ASB) events in eCLIP-Seq data. BEAPR takes into account crosslinking-induced sequence propensity and variations between replicated experiments. Using simulated and actual data, we show that BEAPR largely outperforms often-used count analysis methods. Importantly, BEAPR overcomes the inherent overdispersion problem of these methods. Complemented by experimental validations, we demonstrate that the application of BEAPR to ENCODE eCLIP-Seq data of 154 proteins helps to predict functional GVs that alter splicing or mRNA abundance. Moreover, many GVs with ASB patterns have known disease relevance. Overall, BEAPR is an effective method that helps to address the outstanding challenge of functional interpretation of GVs.
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http://dx.doi.org/10.1038/s41467-019-09292-w | DOI Listing |
Nat Genet
September 2025
Bioinformatics Interdepartmental Program, University of California, Los Angeles, CA, USA.
Gene expression is modulated jointly by transcriptional regulation and messenger RNA stability, yet the latter is often overlooked in studies on genetic variants. Here, leveraging metabolic labeling data (Bru/BruChase-seq) and a new computational pipeline, RNAtracker, we categorize genes as allele-specific RNA stability (asRS) or allele-specific RNA transcription events. We identify more than 5,000 asRS variants among 665 genes across a panel of 11 human cell lines.
View Article and Find Full Text PDFAdv Sci (Weinh)
September 2025
Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Key Laboratory of Mental Health of the Ministry of Education, Guangdong-Hong Kong-Macao Greater Bay Area Center for Brain Science and Brain-Inspired Intelligence, Guangdong-Hong Kong Joint Laboratory for Psychiatric Diso
Schizophrenia (SCZ) and bipolar disorder (BPD) are highly heritable psychiatric disorders with complex genetic and environmental underpinnings. Allele-specific expression (ASE) has emerged as a critical mechanism linking noncoding genetic variants to disease risk through epigenetic and environmental modulation. Here, whole-genome and transcriptome analyses of monozygotic twin pairs discordant for BPD or SCZ are performed, identifying that noncoding genetic variants drive differential ASE patterns of long noncoding RNAs (lncRNAs) in affected individuals compared to their unaffected co-twins.
View Article and Find Full Text PDFNature
September 2025
Center for Psychiatric Genetics, Endeavor Health Research Institute, Evanston, IL, USA.
Despite genome-wide association studies (GWAS) of late-onset Alzheimer's disease (LOAD) having identified many genetic risk loci, the underlying disease mechanisms remain largely unclear. Determining causal disease variants and their LOAD-relevant cellular phenotypes has been a challenge. Here, using our approach for identifying functional GWAS risk variants showing allele-specific open chromatin, we systematically identified putative causal LOAD-risk variants in human induced pluripotent stem (iPS)-cell-derived neurons, astrocytes and microglia, and linked a PICALM LOAD-risk allele to a microglial-specific role of PICALM in lipid droplet (LD) accumulation.
View Article and Find Full Text PDFComput Biol Med
September 2025
Computational Biology Research Center (CBRC), Department of Mathematics and Computer Science, Amirkabir University of Technology, Tehran, Iran. Electronic address:
Predicting peptide-HLA binding is crucial for advancing immunotherapy; however, current models face several challenges, including peptide length variability, HLA sequence similarity, and a lack of experimentally validated negative data. To address these issues, we present PHLA-SiNet, an efficient pipeline that combines innovative representations with a lightweight architecture. PHLA-SiNet introduces three key components: (1) ESM-Pep, a peptide representation derived from a pre-trained language model (ESM), enabling flexible and training-free embedding of variable-length peptides; (2) IC-HLA, an HLA representation that captures allele-specific discriminative features using information content from binding and non-binding peptides; and (3) SiNet, a Siamese neural network that aligns peptide and HLA embeddings, bringing true binders closer in feature space.
View Article and Find Full Text PDFPLoS Genet
August 2025
University of Pennsylvania Perelman School of Medicine, Epigenetics Institute, Department of Cell and Developmental Biology, Philadelphia, Pennsylvania, United States of America.
Precise, monoallelic expression of imprinted genes is governed by cis regulatory elements called imprinting control regions (ICRs) and enhancer-promoter (E-P) interactions shaped by local chromatin architecture. The Igf2/H19 locus employs allele-specific CTCF binding at the ICR to instruct enhancer accessibility to maternal H19 and paternal Igf2 promoters. Here, we investigate the CTCF-bound centrally conserved domain (CCD), intergenic to H19 and Igf2, and an adjacent widely expressed lncRNA.
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