From a single embryo to billions of cells, a whole organism is constructed in a carefully regulated symphony. Every cell in our body shares the same sheet of music in the form of DNA but it is through RNA transcription that rhyme and meter are kept; comprised of a complex regulatory system determining when genes get turned on or off. It is through this regulation that alterations occur, allowing two identical cells to ultimately give rise to completely separate organs and tissue systems. Our current understanding of these processes relies heavily on using short-read sequencing technology to analyze whole transcriptomes. However, this method requires fragmentation of full-length molecules, making it difficult to recapitulate the transcriptome landscape in its entirety. Requiring heavy computational tools to assemble the transcriptome, which only provides an estimation. This loss of contiguity makes it clear we cannot depend on short-read RNA sequencing alone to truly understand the complexities within our transcriptome. Thus, I have established a toolset for creating better, more precise transcriptomes from single cells to bulk RNA studies. This body of work entails how we can elucidate transcript features that tend to be lost in short-read sequencing data. These improvements include developing a 5’ capturing method for single cell data, employing a long-read single cell full-length cDNA sequencing method, increasing throughput and limiting length bias for bulk transcriptomic studies. Together, these improvements create a better snapshot of the transcriptome and will help change how we analyze transcriptomes.

Sequencing technologies are incredibly versatile and have been adapted to measure a wide range of biological phenomena. Using sequencing data, scientists can decipher the genetic makeup of species, and provide understandings into genomics, transcriptomics, and epigenetics. Traditionally, sequencing has been done on Illumina short-read sequencers, but larger Illumina sequencing machines are expensive, and only the best-equipped labs can afford them. As a result, most labs send their libraries out to sequencing cores which could take weeks or months to get their data back. Additionally, traditional sequencing methods face limitations due to their short read lengths. For example, short-read based RNA-seq can’t resolve transcript isoforms and are therefore limited to less detailed gene level analysis. My work addresses both of these issues - expensive hardware and limited read lengths - using Oxford Nanopore Technologies (ONT) affordable long-read sequencers. My first project involved developing a workflow for converting short-read libraries into nanopore libraries while also increasing the low raw accuracy of ONT sequencers. I show that this workflow can be used to replace expensive illumina sequencers and allows labs to sequence their short read libraries at high accuracy on ONT sequencers. For my second project I developed and applied a workflow for using long read sequencing to investigate the isoform landscape of mouse livers over a circadian time course. Together, my projects push the capabilities of ONT sequencers and uncover the nuances of the circadian control of the transcriptional landscape of mouse liver.

All the processes of life are controlled by the complex and carefully regulated usage of the genome. Thus, the understanding of an organism's genomic DNA sequence and regions of the genome that are transcribed into complementary RNA transcripts is critical to the study of life and biomedical research. Our understanding of the DNA and RNA composition of a cell has been heavily based on the high throughput short-read sequencing by synthesis technology. However, DNA and RNA molecules, polymers consisting of long chains of molecular subunits, stretch on for lengths far beyond these methods capabilities such that it requires their fragmentation prior to sequencing followed by computational assembly of the short fragments to estimate their arrangement in the much larger original molecule. Thus, I have developed and optimized methods utilizing nanopore based long-read sequencing to improve the accuracy and completeness of genome assemblies and genomic annotations (transcriptome). These methods include a hybrid genome sequencing and assembly workflow that works with minimal amounts of DNA to generate chromosome-scale assemblies, the conversion of short-read libraries for highly accurate nanopore sequencing that makes DNA sequencing more accessible and, an approach for the deep sequencing of full length transcript isoforms to improve genomic annotations for model organisms. Together, this work improves our ability to understand how living things operate on the molecular level.

Antibodies are created through a unique mechanism whereby different gene segments at the antibody loci are semi-randomly recombined to form functional antibody genes. This process allows that adaptive immune system to generate protection against a near-infinite array of pathogens, however it presents unique challenges from a sequencing prospective. I present three projects addressing problems facing the repertoire sequencing community including a method for full-length antibody transcript sequencing, a method for heavy and light chain pairing in single B cells, and a method for generating repertoires as a byproduct of a general polyA RNA sequencing protocol.

Most transcriptomic analyses are done using Illumina short-read sequencing. While these analyses can be used for highly accurate annotation of individual splice junctions, they are incapable of piecing together combinations of splice junctions to reveal complete RNA transcript isoforms. Exon connectivity information is required for accurate full-length RNA transcript isoform analyses. While long-read sequencing technologies like Pacific Biosciences (PacBio) and Oxford Nanopore Technologies (ONT) can provide exon connectivity information, neither provide a cost effective way to produce high accuracy full-length reads. I present the ONT-based Rolling Circle Amplification to Concatemeric Consensus (R2C2) and Concatemeric Consensus Caller with Partial Order alignments (C3POa) methods, which generate more accurate reads of full-length RNA transcript isoforms than other long-read sequencing methods. I apply these methods to full-length RNA isoform sequencing in single-cells for differential isoform expression across cell types.

Since its inception in the 1970s with Frederick Sanger's pioneering work on Sanger sequencing, DNA sequencing technology has undergone a remarkable evolution. Automated Sanger sequencing in the 1980s and 1990s significantly increased throughput and accuracy, while the 21st century saw the emergence of next-generation sequencing (NGS) technologies like Illumina, revolutionizing genomics research by enabling high-throughput sequencing (van Dijk et al. 2014). However, short-read sequencing techniques, including Illumina, have limitations in accurately resolving repetitive regions and complex structural variations within the genome, hindering comprehensive understanding. In response, third-generation sequencing technologies such as Pacific Biosciences' (PacBio) and Oxford Nanopore Technologies (ONT) have arisen, offering long-read capabilities but facing challenges like DNA polymerase limitations (PacBio) and high error rates (ONT)(Rhoads and Au 2015). Despite these challenges, both PacBio and ONT sequencing technologies continue to advance rapidly, with potential to deepen our understanding of the genome's complexities (Wang et al. 2021). Leveraging the advantages of ONT sequencing, and developing molecular biology methods and bioinformatics tools that overcome the limitations of ONT sequencing to address the unknowns of the adaptive immune system (AIS), is the focus of my graduate work. The diversity of antibody repertoires poses significant challenges for sequencing and annotation. By developing assays that overcome these challenges, my research contributes to a deeper understanding of antibody diversity across vertebrate species, with implications for antibody-based therapy and research applications.

The Rolling Circle Amplification to Concatemeric Consensus (R2C2) protocol was developed to increase the accuracy of Oxford Nanopore Technologies (ONT) long reads for transcriptomic analysis. Originally designed to transform cDNA input into long reads containing multiple copies of individual molecules, this protocol has a wide range of applications using various types of input. I demonstrate the versatility of R2C2 with three general types of input: Illumina libraries, 10X single cell RNA libraries, and plasmids. I developed the PLNK (Processing Live Sequencing experiments) software to monitor ONT MinION runs of Illumina R2C2 libraries to analyze the read quality, library content and coverage over target regions. I used 10X single cell RNA libraries as input for R2C2 and analyzed them with Mandalorion to produce cell type specific transcriptomes. Finally, I shortened the R2C2 protocol to allow for plasmid input and created Chopper, a software pipeline which produces accurate assemblies of full length plasmids.

Summary