Project description:We developed VODKA (Viral Opensource DVG Key Algorithm) to identify cbDVGs from RNA-Seq data from infected samples and used these DVG sequences to identify signals that regulate cbDVG generation. We applied VODKA to datasets from RSV-positive patients. VODKA identified common cbDVGs across multiple samples in both patients, and predicted specific genomic loci that mediate cbDVG formation.
Project description:We successfully developed a two-in-one approach to generate non-viral genome specific targeted CAR T cells through CRISPR/Cas9. In the adoptive therapy for relapsed/refractory aggressive B-cell non-Hodgkin lymphoma, we observed durable responses without serious adverse events and complete remission in patients treated with PD1 knockin CAR T cells. Here we applied single-cell sequencing to analyze the characteristcis of infusion products and T cells after administration.
Project description:Coronavirus RNA-dependent RNA polymerases produce subgenomic RNAs (sgRNAs) that encode viral structural and accessory proteins. The kinetics and efficiency of sgRNAs production during viral replication in different cell types or sgRNA transcription by individual viral strains or variants are yet to be studied to shed light on fundamental mechanisms necessary for viral replication. User-friendly bioinformatic tools to detect and quantify sgRNA production are urgently needed to study a growing number of next-generation sequencing (NGS) data of SARS-CoV-2. Starting from DI-tector, a bioinformatic tool for the detection of viral defective interfering genomes, here we introduced sgDI-tector to identify and quantify sgRNA in SARS-CoV-2 NGS data. This new tool allowed detection of sgRNA without initial knowledge of the transcription-regulatory sequences. As a proof of principle, we analyzed new data sets and successfully detected the nested set of sgRNAs produced with the ranking M>ORF3a>N>ORF6>ORF7a>ORF8>S>E>ORF7b. Our study also compared, for the first time for SARS-CoV-2, the level of sgRNA production with other types of viral RNA products such as defective interfering viral genomes.
Project description:As the most widely used mammalian model organism, mice play a critical role in biomedical research for mechanistic study of human development and diseases. Today, functional sequences in the mouse genome are still poorly annotated a decade after its initial sequencing. We report here a map of nearly 300,000 cis-regulatory sequences in the mouse genome, representing active promoters, enhancers and CTCF binding sites in a diverse set of 19 tissues and cell types. This map provides functional annotation to nearly 11% of the genome, and over 70% of conserved, non-coding sequences. We define tissue-specific enhancers and identify potential transcription factors regulating gene expression in each tissue or cell type. Finally, we demonstrate that cis-regulatory sequences are organized into domains of coordinately regulated enhancers and promoters. Our results provide a valuable resource for the annotation of functional elements in the mammalian genome, and study of regulatory mechanisms for tissue-specific gene expression. Cortex Hi-C experiment were conducted in biological replicates