Dataset Information

Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes.

ABSTRACT: Gene expression is tightly regulated at the post-transcriptional level through splicing, transport, translation, and decay. RNA-binding proteins (RBPs) play key roles in post-transcriptional gene regulation, and genetic variants that alter RBP-RNA interactions can affect gene products and functions. We developed a computational method ASPRIN (Allele-Specific Protein-RNA Interaction) that uses a joint analysis of CLIP-seq (cross-linking and immunoprecipitation followed by high-throughput sequencing) and RNA-seq data to identify genetic variants that alter RBP-RNA interactions by directly observing the allelic preference of RBP from CLIP-seq experiments as compared to RNA-seq. We used ASPRIN to systematically analyze CLIP-seq and RNA-seq data for 166 RBPs in two ENCODE (Encyclopedia of DNA Elements) cell lines. ASPRIN identified genetic variants that alter RBP-RNA interactions by modifying RBP binding motifs within RNA. Moreover, through an integrative ASPRIN analysis with population-scale RNA-seq data, we showed that ASPRIN can help reveal potential causal variants that affect alternative splicing via allele-specific protein-RNA interactions.

SUBMITTER: Bahrami-Samani E

PROVIDER: S-EPMC6407496 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes.

Bahrami-Samani Emad E Xing Yi Y

American journal of human genetics 20190228 3

Gene expression is tightly regulated at the post-transcriptional level through splicing, transport, translation, and decay. RNA-binding proteins (RBPs) play key roles in post-transcriptional gene regulation, and genetic variants that alter RBP-RNA interactions can affect gene products and functions. We developed a computational method ASPRIN (Allele-Specific Protein-RNA Interaction) that uses a joint analysis of CLIP-seq (cross-linking and immunoprecipitation followed by high-throughput sequenci ...[more]

PMID: 30827501

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Project description:BackgroundOrgan-specific gene expression contains rich information about in vivo biological processes. This kind of information, previously gathered through microarray profiling, has been proven fruitful to the understanding of specific mutants, regulatory events, signaling, and development. With the advent of the next-generation sequencing (NGS) of RNAs, more quantitative and detailed information of gene expressions than previously available can now be collected for each organ or organ developmental stages. The combination of an object-oriented experimental design and an efficient treatment of the high volume information generated through a NGS platform may offer a powerful tool for inferring previously intractable developmental processes.ResultsWe collected transcriptomic data over a Solexa/Illumina platform on samples of Ipomoea leaf, sepal, and petals (at three developmental stages), and presented a method for analyzing transcriptomic variations within and between organs. We demonstrated that in vivo signals of transcriptomes can be retrieved de novo through the NGS techniques, proper data handling, bioinformatic tools, and the current understanding of molecular networks. We found that numbers of transcribed genes from both nuclear and chloroplast genomes decreased by the same order of leaf → sepal →petal. Petal resembled leaf in cell division patterns and abundance level of commonly expressed organelle genes. Its chloroplast transcripts constituted a subset of those in leaf. Moreover, reconstructions of multiple metabolic networks for each organ enabled inferences of substance flow, providing transcript evidence for the path of sucrose in leaf to anthocyanin synthesis in petal.ConclusionOur results attest that developmental transcriptomes are highly informative for exploring connections between morphological traits and the associated molecular networks. Significant hypotheses have been developed, including that the petal is a derived organ of leaf and that its color can be modified by fluctuations of substance flow within the associated metabolic networks among organs.

Dataset Information

Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes.

Publications

Discovery of Allele-Specific Protein-RNA Interactions in Human Transcriptomes.

Similar Datasets

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