ABSTRACT: Long read reference genome-free reconstruction of a full-length transcriptome from Astragalus membranaceus reveals transcript variants involved in bioactive compound biosynthesis
Project description:To identify biomarkers regulated by traditional Chinese medicine Astragalus membranaceus Fischer Bge. var. mongolicus Bge. Hsiao in colorectal cancer. We have identified several differentially expressed genes including microRNAs using Affymetrix HTA-2.0 array. In this dataset, we include the expression data obtained from colon cancer cell line HCT116 grafted into nude mice. The mice was treated either water or traditional Chinese medicine Astragalus membranaceus for 28 days. These data are used to obtain 1425 genes that are differentially expressed in response to Astragalus membranaceus treatment.
Project description:A traditional Chinese medicine (TCM) formula, containing Astragalus membranaceus (Fisch.) Bunge, Aconitum wilsonii Stapf ex Veitch, Curcuma longa L., and Radix ophiopogonis (AACO), has clinically proven therapeutic value for the treatment of chronic heart failure (CHF). In this study, we explored the potential pharmacological mechanism underlying the activity of the AACO formula against CHF.
Project description:Alternative splicing is widely acknowledged to be a crucial regulator of gene expression and is a key contributor to both normal developmental processes and disease states. While cost-effective and accurate for quantification, short-read RNA-seq lacks the ability to resolve full-length transcript isoforms despite increasingly sophisticated computational methods. Long-read sequencing platforms such as Pacific Biosciences (PacBio) and Oxford Nanopore (ONT) bypass the transcript reconstruction challenges of short-reads. Here we describe TALON, the ENCODE4 pipeline for analyzing PacBio cDNA and ONT direct-RNA transcriptomes. We apply TALON to three human ENCODE Tier 1 cell lines and show that while both technologies perform well at full-transcript discovery and quantification, each one displayed distinct artifacts. We further apply TALON to mouse cortical and hippocampal transcriptomes and find that a substantial proportion of neuronal genes have more reads associated with novel isoforms than with annotated ones. These data show that TALON is a technology-agnostic long-read transcriptome discovery and quantification pipeline capable of tracking both known and novel transcript models, as well as their expression levels, across datasets for both simple studies and in larger projects. These properties will enable TALON users to move beyond the limitations of short-read data to perform isoform discovery and quantification in a uniform manner on existing and future long-read platforms.
Project description:Full length long read transcript sequences were used as guides along with other multi-omics data to build gene model annotation of Cassava.
Project description:Alternative splicing is widely acknowledged to be a crucial regulator of gene expression and is a key contributor to both normal developmental processes and disease states. While cost-effective and accurate for quantification, short-read RNA-seq lacks the ability to resolve full-length transcript isoforms despite increasingly sophisticated computational methods. Long-read sequencing platforms such as Pacific Biosciences (PacBio) and Oxford Nanopore (ONT) bypass the transcript reconstruction challenges of short-reads. Here we describe TALON, the ENCODE4 pipeline for analyzing PacBio cDNA and ONT direct-RNA transcriptomes. We apply TALON to three human ENCODE Tier 1 cell lines and show that while both technologies perform well at full-transcript discovery and quantification, each technology has its distinct artifacts. We further apply TALON to mouse cortical and hippocampal transcriptomes and find that a substantial proportion of neuronal genes have more reads associated with novel isoforms than annotated ones. The TALON pipeline for technology-agnostic, long-read transcriptome discovery and quantification tracks both known and novel transcript models as well as expression levels across datasets for both simple studies and larger projects such as ENCODE that seek to decode transcriptional regulation in the human and mouse genomes to predict more accurate expression levels of genes and transcripts than possible with short-reads alone.
2019-06-15 | GSE132766 | GEO
Project description:Full length transcriptome sequence of Astragalus mongholicus