Project description:Full-Length cDNA transcriptome (Iso-Seq) data sequenced on the PacBio Sequel system using 2.1 chemistry. Multiplexed cDNA library of 12 samples (3 tissues x 4 strains). Tissues: root, embryo, endosperm. Strains: B73, Ki11, B73xKi11, Ki11xB73.
Project description:Here we describe CapTrap-Seq, an experimental workflow designed to address the problem of reduced transcript end detection by long-read RNA sequencing methods, especially at the 5' ends. We apply CapTrap-Seq to profile transcriptomes of the human heart and brain and we compared the obtained results with other library preparation approaches. CapTrap-Seq is a platform-agnostic method and here tested the method by using 3 different long-read sequencing platforms: MinION (ONT), Sequel (PacBaio) and Sequel II (PacBio).
Project description:Single-cell RNA sequencing (scRNA-seq) is generally used for profiling transcriptome of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data generated by these two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analyses. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data more. For 10X-based data, we observed higher noise for mRNAs with low expression levels. Approximately 10%-30% of all detected transcripts by both platforms were from non-coding genes, with long non-coding RNAs (lncRNAs) accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected distinct groups of differentially expressed genes between cell clusters, indicating the different characteristics of these technologies. Our study promotes better understanding of these two platforms and offers the basis for an informed choice of these widely used technologies.
Project description:These data correspond to one SMRT cell sequencing run (performed on Sequel II, PacBio) of full length cDNAs from 3 pooled glioma stem cell line libraries. No tag was added to distinguish the 3 different samples
Project description:Macrophage colony-stimulating factor receptor (M-CSFR/CSF1R) signaling is crucial for the differentiation, proliferation, and survival of myeloid cells. Therapeutic targeting of the CSF1R pathway is a promising strategy in many human diseases, including neurological disorders or cancer. Zebrafish are commonly used for human disease modeling and preclinical therapeutic screening. Therefore, it is necessary to understand the proper function of cytokine signaling in zebrafish to reliably model human-related diseases. Here, we investigate the roles of zebrafish csf1ra and csf1rb in adult myelopoiesis using single-cell RNA sequencing. Our analysis of adult whole kidney marrow (WKM) hematopoietic cells suggests that csf1rb is expressed mainly by blood and myeloid progenitors and that the expression of csf1ra and csf1rb is non-overlapping. We point out differentially expressed genes important in hematopoietic cell differentiation and immune response in selected WKM populations. Our findings could improve the understanding of myeloid cell function and lead to the further study of CSF1R pathway deregulation in disease, mostly in cancerogenesis.
Project description:Whole-genome sequencing on PacBio of laboratory mouse strains. See http://www.sanger.ac.uk/resources/mouse/genomes/ for more details. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/