Project description:Soil metagenomics has been touted as the "grand challenge" for metagenomics, as the high microbial diversity and spatial heterogeneity of soils make them unamenable to current assembly platforms. Here, we aimed to improve soil metagenomic sequence assembly by applying the Moleculo synthetic long-read sequencing technology. In total, we obtained 267 Gbp of raw sequence data from a native prairie soil; these data included 109.7 Gbp of short-read data (~100 bp) from the Joint Genome Institute (JGI), an additional 87.7 Gbp of rapid-mode read data (~250 bp), plus 69.6 Gbp (>1.5 kbp) from Moleculo sequencing. The Moleculo data alone yielded over 5,600 reads of >10 kbp in length, and over 95% of the unassembled reads mapped to contigs of >1.5 kbp. Hybrid assembly of all data resulted in more than 10,000 contigs over 10 kbp in length. We mapped three replicate metatranscriptomes derived from the same parent soil to the Moleculo subassembly and found that 95% of the predicted genes, based on their assignments to Enzyme Commission (EC) numbers, were expressed. The Moleculo subassembly also enabled binning of >100 microbial genome bins. We obtained via direct binning the first complete genome, that of "Candidatus Pseudomonas sp. strain JKJ-1" from a native soil metagenome. By mapping metatranscriptome sequence reads back to the bins, we found that several bins corresponding to low-relative-abundance Acidobacteria were highly transcriptionally active, whereas bins corresponding to high-relative-abundance Verrucomicrobia were not. These results demonstrate that Moleculo sequencing provides a significant advance for resolving complex soil microbial communities. IMPORTANCE Soil microorganisms carry out key processes for life on our planet, including cycling of carbon and other nutrients and supporting growth of plants. However, there is poor molecular-level understanding of their functional roles in ecosystem stability and responses to environmental perturbations. This knowledge gap is largely due to the difficulty in culturing the majority of soil microbes. Thus, use of culture-independent approaches, such as metagenomics, promises the direct assessment of the functional potential of soil microbiomes. Soil is, however, a challenge for metagenomic assembly due to its high microbial diversity and variable evenness, resulting in low coverage and uneven sampling of microbial genomes. Despite increasingly large soil metagenome data volumes (>200 Gbp), the majority of the data do not assemble. Here, we used the cutting-edge approach of synthetic long-read sequencing technology (Moleculo) to assemble soil metagenome sequence data into long contigs and used the assemblies for binning of genomes. Author Video: An author video summary of this article is available.
Project description:Purpose: To generate a reference long-read transcriptomic data set for use in developing new analysis pipelines and comparing their performance with existing methods. Synthetic “sequin” RNA standards (Hardwick et al. 2016) were sequenced using the Oxford Nanopore Technologies (ONT) GridION platform.
Project description:Osteosarcoma is the most common primary bone cancer in children, adolescents and young adults. It is a rare cancer type. To comprehensively reveal the transcriptomic characteristics of osteosarcoma, we performed Oxford Nanopore Technologies (ONT) long-read RNA-Seq of tumor and adjacent normal tissues from 23 patients with osteosarcoma.
Project description:Purpose: The aim of this study is to identify genes that are under the transcriptional control of the epigenetic modifier Smchd1 in mouse neural stem cells. We profiled the transcriptomes of mouse neural stem cells from samples that were either wild-type or contained a null mutation in the epigenetic regulator Smchd1 using Oxford Nanopore Technologies (ONT) direct cDNA sequencing protocol and a PromethION sequencer.
Project description:OnT dRNA of K562 For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODE_Data_Use_Policy_for_External_Users_03-07-14.pdf
Project description:ONT dRNA of HepG2 For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODE_Data_Use_Policy_for_External_Users_03-07-14.pdf
Project description:Clear cell renal cell carcinoma (ccRCC) is the most common form of kidney cancer. To date, long-read RNA sequencing has not been applied to kidney cancer. Here, we used ONT long-read Direct RNA sequencing to profile the transcriptomes of ccRCC cell line RCC4, with and without exposure to pro-inflammatory cytokines. Our results revealed differentially expressed genes induced by the pro-inflammatory cytokines. Moreover, results here revealed potential tumour origin of novel isoforms and genes that were discovered in the archival tumour samples by long-read sequencing.