Project description:Sampada and Sujata are two contrasting genotypes of Papaver somniferum that are contrasting in terms of their latex and alkaloid profiles. The major objective of the present study was to use a small-scale (750 target genes) microarray of P. somniferum for identification of genes that are differentially expressed in the capsule walls of the two contrasting genotypes, Sampada and Sujata. Nidarshana Chaturvedi and Mridula Singh made equal contribution as first authors to this data.
Project description:Since short reads from Illumina RNA-seq data are challenging to map to repetitive elements , we wanted to confirm the bulk RNA-seq findings using an orthogonal method, namely, using the long read technology of Pacific Biosciences (PacBio) full-length transcriptome sequencing. This dataset provided around 1.1 (WT) and 1.3 (RBM4 KO) million sequence reads of 2.6 kb average length mapping to the human genome.
Project description:Single-cell RNA sequencing analysis has recently provided snapshots of gene expression of specific cell types and enabled cell types classification within an heterogenous population. As well as transcriptional changes, alternative splicing events and modifications of components of splicing machinery actively contributes in shaping cellular phenotype as well as ageing process and diseases occurence. Current high-throughput single-cell RNA sequencing methods may lack information on cell-specific isoform expression, missing key aspects of cell biology. In the present work we introduce a novel approach using the 10X Genomics Chromium to generate short-read (Illumina) and long-read (Pacific Biosciences Sequel II) RNA-sequencing libraries from the same single cells. This approach produced single cell parallel transcriptional and splicing profiling that demonstrates for the first time cell-type specific isoform expression and alterations at transcriptional levels associated with ageing in haematopoietic stem and progenitor cells
Project description:Sampada and Sujata are two contrasting genotypes of Papaver somniferum that are contrasting in terms of their latex and alkaloid profiles. The major objective of the present study was to use a small-scale (750 target genes) microarray of P. somniferum for identification of genes that are differentially expressed in the capsule walls of the two contrasting genotypes, Sampada and Sujata. Nidarshana Chaturvedi and Mridula Singh made equal contribution as first authors to this data. The experiment aimed at studying the expression levels of target genes in P. somniferum. A dual channel procedure with dye-swap arrangement was adopted in the study on two samples - Sampada and Sujata. The interest was to compare the expression levels of target genes in Sujata against Sampada. The expression data was generated on 1,569 probes, which includes controls and target probes.
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.