R01HG011868

High-throughput Detection of Transcriptomic and Epitranscriptomic Variation and Kinetics using MarathonRT - Project Summary

The discovery and characterization of an efficient, ultraprocessive reverse transcriptase (MarathonRT) now makes it possible to develop high-throughput methods for accurate end-to-end sequencing of long RNA transcripts. This preserves information content on alternative splicing, editing, and modification isoforms while conserving positional linkage information. Consequently, it enables one to distinguish RNA isoforms in complex mixtures without mapping to a reference genome. This type of technology is essential for deciphering the role of post-transcriptional RNA processing events during the control of developmental stage, cell and tissue specificity, and regulation of gene expression in higher organisms. It must be sufficiently efficient and accurate to power the long-read sequencing approaches used in single-cell RNAseq, particularly when transcript diversification is monitored as a function of time.

The first two aims of the proposal are focused on high-throughput detection of RNA modifications (such as 2-O-methyl groups and N7-methyl guanosines). In the first aim, a unique MarathonRT primer extension protocol will be combined with a trained mutational profiling algorithm to recognize the positions and chemical identities of specific RNA modifications. This will report a modification signature that can be recognized at high throughput during long-read sequencing (MRT-MODSEQ). In the second aim, MRT-MODSEQ will be tested on unknown RNAs to predict sites of modifications on challenging long transcripts. The robustness of the predictions will be directly evaluated using mass spectrometry.

The second half of the proposal is focused on the identification of linked alternative splicing and editing sites on long transcripts within complex cellular mixtures. In aim 3, MarathonRT will be incorporated into a workflow for accurately profiling the relative abundance and processing diversity of the highly complex paralytic (Para) gene. This gene encodes more than 1 million possible processing variants, a subset of which are essential for the voltage-gating of a sodium channel. This sets the stage for aim 4, in which the sensitivity of the workflow must be further optimized and merged with data analysis strategies suitable for time-resolved single-cell applications. The resulting method will be tested by monitoring full-length transcriptomic signatures induced by cell stress.

Yale Univ

NOT APPLICABLE

93.172 - Human Genome Research

National Human Genome Research Institute (NHGRI) [HHS - NIH]

New Haven, Connecticut 065111984 United States

Single Zip Code

Novel Genomic Technology Development (R01 Clinical Trial Not Allowed) (PAR-18-777)

Amendment Since initial award the total obligations have increased 286% from $1,005,089 to $3,879,651.