Nanopore Long-Read Single Cell RNAseq Reveals Widespread Transcriptional Variation Across Individual B cells
Ashley Byrne1,2, Anna E. Beaudin1,3, Hugh E. Olsen1,2, Miten Jain1,2, Charles Cole1,2,Theron Palmer1, Rebecca M. DuBois1, E. Camilla Forsberg1,3, Mark Akeson1,2, Christopher Vollmers1,2,
1Department of Biomolecular Engineering, University of California–Santa Cruz, Santa Cruz, CA, USA; 2UC Santa Cruz Genomics Institute, Santa Cruz, California, USA; 3Institute for the Biology of Stem Cells, Department of Biomolecular Engineering, University of California–Santa Cruz, Santa Cruz, CA, USA
To fully understand gene regulation and function, we require an in-depth knowledge of the transcriptome landscape. Acquiring this knowledge, in its entirety would entail a genome-wide method capable of capturing both gene expression levels and isoform diversity. Illumina Short-read RNAseq, the current gold standard, cannot accurately resolve complex isoforms due to its inability to capture full-length RNA molecules. To overcome this limitation, we investigated whether using the long-read single-molecule Oxford Nanopore (ONT) sequencing technology would be able to identify complex isoforms without sacrificing accurate gene expression quantification. The Oxford Nanopore Technologies (ONT) MinION sequencer is a highly portable device that is based on a single molecule sequencing technique that provides reads of unprecedented length by performing voltage driven molecule translocations through small nanosensors.
As a benchmark, we applied our experimental and computational approaches on a highly complex synthetic mixture of known transcripts varying in length and structure. We further adapted our approach to interrogate transcriptomes at the single-cell level using a cellular indexing strategy for multiplexing. By applying our multiplexed ONT RNAseq method to seven murine B1a cells, we identified ~ 5,000 un-annotated transcription start and end sites as well as ~150 alternative splicing events. As a result, we found many genes that were expressed, including B cell specific cell surface receptors demonstrating widespread intra-cellular and inter-cellular variation based on their isoform usage. Indicating possible significant biological variation across B1a cells. Using ONT RNAseq has not only the potential to define gene-level correlations but also unprecedented isoform-level changes at the single cell level.
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