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:We report the application of single-molecule-based sequencing technology for high-throughput profiling of DNA methylations in Burkholderia pseudomallei. SMRTbell™ sequencing
Project description:Iso-Seq (PacBio) sequencing was performed to generate a reference library of H. perforatum. We generated genome-wide transcriptome data from in vitro cell suspensions and shoot cultures of H. perforatum.
Project description:In this study, we compared the transcriptome map of maize and sorghum using PacBio single-molecule long-read sequencing from multiple matched tissues in each species. Maize and sorghum are both important crops with similar overall plant architectures, but they have key differences, especially in regard to their inflorescences. To better understand these two organisms at the molecular level, we compared the transcriptional profiles of both protein-coding and non-coding transcripts in matched tissues using large-scale single-molecule sequencing from 130 RSII cells and 5 Sequel cells, as well as deep short-read RNA sequencing. The use of multiple size-fractionated libraries (<1 kb, 12 kb, 23 kb, 35 kb, and >5 kb) enhanced our capture of non-redundant transcripts in these tissues.
Project description:Large-scale sequencing of RNAs from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states. However, current single-cell RNA-sequencing (scRNA-seq) methods have limited ability to count RNAs at allele- and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells. Here, we introduce Smart-seq3 that combines full-length transcriptome coverage with a 5’ unique molecular identifier (UMI) RNA counting strategy that enabled in silico reconstruction of thousands of RNA molecules per cell. Importantly, a large portion of counted and reconstructed RNA molecules could be directly assigned to specific isoforms and allelic origin, and we identified significant transcript isoform regulation in mouse strains and human cell types. Moreover, Smart-seq3 showed a dramatic increase in sensitivity and typically detected thousands more genes per cell than Smart-seq2. Altogether, we developed a short-read sequencing strategy for single-cell RNA counting at isoform and allele-resolution applicable to large-scale characterization of cell types and states across tissues and organisms.
Project description:2 samples have been prepared for ISO-seq sequencing. CD34+ blast cells from 5 MDS patients before 5-AZA treatment (GEO531A16, GEO531A13, GEO531A5, GEO531A11, GEO531A3) were pooled to generate one sample and 2 AML non-treated and 2 CMML non-treated cells (GEO531A2, GEO531A9, GEO531A6, GEO531A7) were pooled for second sample.
Project description:This study benchmarks bulk and single-cell long-read RNA sequencing technologies in a human neuronal model of Fragile X syndrome. NGN2-induced neurons were generated from patient-derived iPSCs carrying a silenced FMR1 gene (FXS line E3) and an isogenic CRISPR-corrected rescue line (IsoB11) in which FMR1 expression is restored. These conditions provide a defined system to evaluate transcript detection and quantification across sequencing platforms. Bulk and single-cell RNA-seq datasets were generated using Illumina short-read sequencing and long-read sequencing from Pacific Biosciences (PB) and Oxford Nanopore Technologies (ONT). Single-cell libraries were prepared using the 10x Genomics Chromium platform. ERCC and SIRV spike-in controls were added to bulk samples to enable benchmarking of transcript quantification accuracy. Three biological replicates were sequenced for each condition. The dataset enables cross-platform comparisons of transcript detection, quantification methods, transcript length biases, and sequencing depth requirements for long-read transcriptomic analyses.
Project description:This study benchmarks bulk and single-cell long-read RNA sequencing technologies in a human neuronal model of Fragile X syndrome. NGN2-induced neurons were generated from patient-derived iPSCs carrying a silenced FMR1 gene (FXS line E3) and an isogenic CRISPR-corrected rescue line (IsoB11) in which FMR1 expression is restored. These conditions provide a defined system to evaluate transcript detection and quantification across sequencing platforms. Bulk and single-cell RNA-seq datasets were generated using Illumina short-read sequencing and long-read sequencing from Pacific Biosciences (PB) and Oxford Nanopore Technologies (ONT). Single-cell libraries were prepared using the 10x Genomics Chromium platform. ERCC and SIRV spike-in controls were added to bulk samples to enable benchmarking of transcript quantification accuracy. Three biological replicates were sequenced for each condition. The dataset enables cross-platform comparisons of transcript detection, quantification methods, transcript length biases, and sequencing depth requirements for long-read transcriptomic analyses.