Biology subjects

Chen, L.-L.

Publications and source records attributed to Chen, L.-L..

3 recordsLinked to original sources

bioRxiv2020

Screening for functional circular RNAs using the CRISPR-Cas13 system

Circular RNAs (circRNAs) produced from back-spliced exons are widely expressed, but individual circRNA functions remain poorly understood due to inadequate methods, such as RNAi and genome engineering, in distinguishing overlapped exons in circRNAs from those in linear cognate mRNAs1,2. Here we report that the programable RNA-guided, RNA-targeting CRISPR-Cas13, RfxCas13d, effectively and specifically discriminates circRNAs from mRNAs, using guide (g)RNAs targeting sequences spanning the back-splicing junction (BSJ) sites featured in RNA circles. Using a lentiviral library that targets sequences across BSJ sites of highly expressed human circRNAs, we show that a group of circRNAs are important for cell growth mostly in a cell-type specific manner and that a common oncogenic circRNA, circFAM120A, promotes cell proliferation in vitro and in vivo by preventing FAM120A mRNA from binding the translation inhibitor IGF2BP2 for efficient translation. Application of RfxCas13d/BSJ-gRNA screening has also uncovered circMan1a2 with regulatory potential in mouse embryo preimplantation development. Together, these results establish CRISPR-RfxCas13d as a useful tool for the discovery and functional study of circRNAs at both individual and large-scale levels.

molecular biology↗

bioRxiv2020

Designing of a next generation multiepitope based vaccine (MEV) against SARS-COV-2: Immunoinformatics and in silico approaches

Coronavirus disease 2019 (COVID-19) associated pneumonia caused by severe acute respiratory coronavirus 2 (SARS-COV-2) was first reported in Wuhan, China in December 2019. Till date, no vaccine or completely effective drug is available to cure COVID-19. Therefore, an effective vaccine against SARS-COV-2 is crucially needed. This study was conducted to design an effective multiepitope based vaccine (MEV) against SARS-COV-2. Seven antigenic proteins were taken as targets and different epitopes (B-cell, T-cell and IFN-{gamma} inducing) were predicted. Highly antigenic and overlapping epitopes were shortlisted. Selected epitopes indicated significant interactions with the HLA-binding alleles and 99.29% coverage of the worlds population. Finally, 505 amino acids long MEV was designed by connecting sixteen MHC class I and eleven MHC class II epitopes with suitable linkers and adjuvant. Linkers and adjuvant were added to enhance the immunogenicity response of the MEV. The antigenicity, allergenicity, physiochemical properties and structural details of MEV were analyzed in order to ensure safety and immunogenicity. MEV construct was non-allergenic, antigenic, stable and flexible. Molecular docking followed by molecular dynamics (MD) simulation analysis, demonstrated a stable and strong binding affinity of MEV with human pathogenic toll-like receptors (TLR), TLR3 and TLR8. Codon optimization and in silico cloning of MEV ensured increased expression in the Escherichia coli K-12 system. Designed MEV in present study could be a potential candidate for further vaccine production process against COVID-19. However, to ensure its safety and immunogenic profile, the proposed MEV needs to be experimentally validated.

immunology↗

bioRxiv2019

A CLEAR pipeline for direct comparison of circular and linear RNA expression

Sequences of circular RNAs (circRNAs) produced from back-splicing of exon(s) completely overlap with sequences from cognate linear RNAs transcribed from the same gene loci with the exception of their back-splicing junction (BSJ) sites. Examination of global circRNA expression from RNA-seq datasets generally relies on the detection of RNA-seq fragments spanning BSJ sites, but a direct comparison of circular and linear RNA expression from the same gene loci in a genome-wide manner has remained challenging. This is because quantification of BSJ fragments differs from that of linear RNA expression that uses normalized RNA-seq fragments mapped to the whole gene bodies. Here, we have developed a computational pipeline for circular and linear RNA expression analysis from ribosomal-RNA depleted RNA-seq (CLEAR, https://github.com/YangLab/CLEAR). A new quantitation parameter, FPB (fragments per billion mapped bases), is applied to evaluate circular and linear RNA expression individually by fragments mapped to circRNA-specific BSJ sites or to linear RNA-specific splicing junction (SJ) sites. Then, circular and linear RNA expression are directly compared by dividing FPBcirc by FPBlinear to generate a CIRCscore, which indicates the relative circRNA expression using linear RNA expression as the background. Highly-expressed circRNAs with low cognate linear RNA expression background can be identified for further investigation.

bioinformatics↗