Project description:The advancement of Third-Generation Sequencing (TGS) techniques managed to increase the sequencing length to several kilobases, which leads to a bright future for completely reserving alternative splicing (AS) events and isoform expressions. In recent years, many computational methods for isoform detection from long-read sequencing data have been developed and published. However, there is no prior comparative study that systemically evaluates the performance of the software implemented with different algorithms. Here we benchmarked nine methods implemented in seven computational tools that can identify isoform structures from TGS RNA sequencing data and analyzed their performances from various aspects using both simulated datasets produced by an in-house simulator and previously published experimental data. Our results comprehensively demonstrate the relative effectiveness of the approaches and provide guidance as well as recommendations for future research on AS analysis and further improvement of the tools for isoform detection using TGS data.
Project description:Alternative cleavage and polyadenylation (APA) is emerging as an important mechanism of gene regulation in eukaryotes and plays important regulatory roles in human development and diseases. Despite the widespread application of Second Generation Sequencing (SGS) technology for polyadenylation site identification, matching each identified polyadenylation site within a gene to its derived isoform remains a major challenge. To achieve the isoform-resolved APA analysis, we developed a tool termed “IDP-APA” that constructs truly expressed isoforms and identifies polyadenylation sites by integrating the respective strengths of Third Generation Sequencing (TGS) long reads and SGS short reads. Compared to existing tools, IDP-APA demonstrated superior performance in both isoform reconstruction and polyadenylation site identification. Applications to human embryonic stem cells, breast cancer cells and brain tissue from a patient with Alzheimer’s disease revealed prevalent APA events and cell-/tissue-specific APA patterns, especially in an isoform-resolved way.
Project description:We applied Single Molecule Real-Time long-read whole-genome sequencing in Dux knockout mouse and confirmed the success of our Dux knockout mouse model.
Project description:The aim of this study is to investigate possible differences in methylated regions between ovarian tissue of third generation PCOS-like (PAMH F3) mice versus control animals (CNTR)
Project description:The aim of this study is to investigate ovarian transcriptomic changes by RNA-seq between 2 experimental groups, control (CNTR) and the third generation of PCOS-like mice (PAMH F3).
Project description:Newly diagnosed chronic phase chronic myeloid leukemia (CML) patients with a major cytogenetic response (MCyR) after 12 months of imatinib therapy have an excellent long-term outcome, while patients without MCyR have a high progression risk. Since patients with primary cytogenetic resistance may benefit from more intensive therapy up-front, we sought to identify biomarkers to predict MCyR. Keywords: Two group comparison to identify trasncriptomic signature that predicts response to therapy
Project description:Cytogenetic abnormalities (CA) are important clinical parameters in various types of cancer, including multiple myeloma (MM). We developed a model to predict CA in patients with MM using gene expression profiling (GEP) and validated it by different cytogenetic techniques. The model was shown to have an accuracy up to 0.89. These results provide proof of concept for the hypothesis that GEP could serve as a one-stop data source for clinical molecular diagnosis and/or prognosis.
