Computational prediction and experimental validation identify functionally conserved lncRNAs from zebrafish to human
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ABSTRACT:
PROVIDER: PRJNA1003409 | ENA |
REPOSITORIES: ENA
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Project description:Functional studies of long noncoding RNAs (lncRNAs) have long been hindered by a lack of methods to assess their evolution. Here, we present lncHOME (lncRNA Homology Explorer), a computational pipeline that identifies a unique coPARSE-lncRNA class with conserved genomic locations and patterns of RNA binding protein (RBP) binding sites. Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects that were rescued by predicted zebrafish homologs. Knocking down the coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Moreover, we verified that human, mouse, and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved fuctions relying on specific RBP binding sites. Overall, our study demonstrates a comprehensive approach for studying functional conservation of lncRNAs and implicates numerous lncRNAs in regulating cellular physiology.
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Project description:Functional studies of long noncoding RNAs (lncRNAs) have been hindered by the lack of methods to assess their evolution. Here we present lncRNA Homology Explorer (lncHOME), a computational pipeline that identifies a unique class of long noncoding RNAs (lncRNAs) with conserved genomic locations and patterns of RNA-binding protein (RBP) binding sites (coPARSE-lncRNAs). Remarkably, several hundred human coPARSE-lncRNAs can be evolutionarily traced to zebrafish. Using CRISPR-Cas12a knockout and rescue assays, we found that knocking out many human coPARSE-lncRNAs led to cell proliferation defects, which were subsequently rescued by predicted zebrafish homologs. Knocking down coPARSE-lncRNAs in zebrafish embryos caused severe developmental delays that were rescued by human homologs. Furthermore, we verified that human, mouse and zebrafish coPARSE-lncRNA homologs tend to bind similar RBPs with their conserved functions relying on specific RBP-binding sites. Overall, our study demonstrates a comprehensive approach for studying the functional conservation of lncRNAs and implicates numerous lncRNAs in regulating vertebrate physiology.
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Project description:MicroRNAs (miRNAs) are endogenous, noncoding, short RNAs directly involved in regulating gene expression at the post-transcriptional level. In spite of immense importance, limited information of P. vulgaris miRNAs and their expression patterns prompted us to identify new miRNAs in P. vulgaris by computational methods. Besides conventional approaches, we have used the simple sequence repeat (SSR) signatures as one of the prediction parameter. Moreover, for all other parameters including normalized Shannon entropy, normalized base pairing index and normalized base-pair distance, instead of taking a fixed cut-off value, we have used 99% probability range derived from the available data. We have identified 208 mature miRNAs in P. vulgaris belonging to 118 families, of which 201 are novel. 97 of the predicted miRNAs in P. vulgaris were validated with the sequencing data obtained from the small RNA sequencing of P. vulgaris. Randomly selected predicted miRNAs were also validated using qRT-PCR. A total of 1305 target sequences were identified for 130 predicted miRNAs. Using 80% sequence identity cut-off, proteins coded by 563 targets were identified. The computational method developed in this study was also validated by predicting 229 miRNAs of A. thaliana and 462 miRNAs of G. max, of which 213 for A. thaliana and 397 for G. max are existing in miRBase 20. There is no universal SSR that is conserved among all precursors of Viridiplantae, but conserved SSR exists within a miRNA family and is used as a signature in our prediction method. Prediction of known miRNAs of A. thaliana and G. max validates the accuracy of our method. Our findings will contribute to the present knowledge of miRNAs and their targets in P. vulgaris. This computational method can be applied to any species of Viridiplantae for the successful prediction of miRNAs and their targets.
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Project description:Long non-coding RNAs (lncRNAs) play key roles in cell processes and are good candidates for cancer risk prediction. Few studies have investigated the association between individual genotypes and lncRNA expression. Here we integrate three separate datasets with information on lncRNA expression only, both lncRNA expression and genotype, and genotype information only, to identify circulating lncRNAs associated with the risk of gallbladder cancer (GBC), using robust linear and logistic regression techniques. In the first dataset, we preselect lncRNAs based on expression changes along the sequence “gallstones → dysplasia → GBC”. In the second dataset, we validate associations between genetic variants and serum expression levels of the preselected lncRNAs (cis-lncRNA-eQTLs) and build lncRNA-expression prediction models. In the third dataset, we predict serum lncRNA expression based on individual genotypes, and assess the association between genotype-based expression and GBC risk. AC084082.3 and LINC00662 showed increasing expression levels (p value = 0.009), while C22orf34 expression decreased in the sequence from gallstones to GBC (p value = 0.04). We identified and validated two cis-LINC00662-eQTLs (r2= 0.26) and three cis-C22orf34-eQTLs (r2 = 0.24). Only LINC00662 showed a genotyped-based serum expression associated with GBC risk (OR=1.25 per log2 expression unit, 95%CI 1.04-1.52, p value = 0.02).
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