Formation of Chimeric Genes by Copy-Number Variation as a Mutational Mechanism in Schizophrenia

Chimeric genes can be caused by structural genomic rearrangements that fuse together portions of two different genes to create a novel gene. We hypothesize that brain-expressed chimeras may contribute to schizophrenia. Individuals with schizophrenia and control individuals were screened genome wide for copy-number variants (CNVs) that disrupted two genes on the same DNA strand. Candidate events were filtered for predicted brain expression and for frequency < 0.001 in an independent series of 20,000 controls. Four of 124 affected individuals and zero of 290 control individuals harbored such events (p = 0.002); a 47 kb duplication disrupted MATK and ZFR2, a 58 kb duplication disrupted PLEKHD1 and SLC39A9, a 121 kb duplication disrupted DNAJA2 and NETO2, and a 150 kb deletion disrupted MAP3K3 and DDX42. Each fusion produced a stable protein when exogenously expressed in cultured cells. We examined whether these chimeras differed from their parent genes in localization, regulation, or function. Subcellular localizations of DNAJA2-NETO2 and MAP3K3-DDX42 differed from their parent genes. On the basis of the expression profile of the MATK promoter, MATK-ZFR2 is likely to be far more highly expressed in the brain during development than the ZFR2 parent gene. MATK-ZFR2 includes a ZFR2-derived isoform that we demonstrate localizes preferentially to neuronal dendritic branch sites. These results suggest that the formation of chimeric genes is a mechanism by which CNVs contribute to schizophrenia and that, by interfering with parent gene function, chimeras may disrupt critical brain processes, including neurogenesis, neuronal differentiation, and dendritic arborization

Efficiently searching for enhancers and their target genes in the human genome

Thesis (Ph.D.)--University of Washington, 2019A single 3 billion letter genome contains the instructions for the 37 trillion diverse cells that make up one human. To accomplish this, the ~21,000 human genes are expressed and perform function in highly specific combinations per cell. Yet, only 2% of the genome codes for genes. The remaining 98% is made up of highly complicated, loosely patterned DNA referred to as “noncoding sequence”. Functional noncoding DNA elements (first termed “enhancers” in 1981) regulate cell-type specific gene expression. Like genes, enhancers disruption is known to cause genetic disease. How can we efficiently search for enhancers within the expansive noncoding genome? The new genome engineering technology CRISPR/Cas9 enables parallelized pooled perturbations to efficiently screen enhancers and the genes they target. In this dissertation, I will cover my development of new pooled methods to screen the noncoding genome. In the first chapter, I introduce the motivation for these methods, the history of enhancers, their current definitions, and emerging technologies for enhancers’ at-scale characterization. In Chapter 2, I describe a method we devised to scan thousands of CRISPR-induced kilobase-sized deletions ("ScanDel") across a desired noncoding region, programming one unique deletion per cell in a pool and phenotyping them in multiplex by pooled functional selection. However, ScanDel and its contemporaries are limited to evaluating enhancers for their effect upon a single gene. In Chapter 3, I describe a second method designed to overcome this limitation, in which large numbers of CRISPR perturbations are introduced to each cell, followed by single-cell transcriptome sequencing to read out their effect upon any transcript. With this method, we effectively evaluated >70,000 potential enhancer-target gene relationships in one experiment. In Chapter 4, I describe a potential path forward to cataloguing all enhancers in the human genome, and how we might do the same for noncoding variants in human disease

A Genome-wide Framework for Mapping Gene Regulation via Cellular Genetic Screens

Over one million candidate regulatory elements have been identified across the human genome, but nearly all are unvalidated and their target genes uncertain. Approaches based on human genetics are limited in scope to common variants and in resolution by linkage disequilibrium. We present a multiplex, expression quantitative trait locus (eQTL)-inspired framework for mapping enhancer-gene pairs by introducing random combinations of CRISPR/Cas9-mediated perturbations to each of many cells, followed by single-cell RNA sequencing (RNA-seq). Across two experiments, we used dCas9-KRAB to perturb 5,920 candidate enhancers with no strong a&nbsp;priori hypothesis as to their target gene(s), measuring effects by profiling 254,974 single-cell&nbsp;transcriptomes. We identified 664 (470 high-confidence) cis enhancer-gene pairs, which were enriched for specific transcription factors, non-housekeeping status, and genomic and 3D conformational proximity to their target genes. This framework will facilitate the large-scale mapping of enhancer-gene regulatory interactions, a critical yet largely uncharted component of the cis-regulatory landscape of the human genome

Swab-Seq: A high-throughput platform for massively scaled up SARS-CoV-2 testing

The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates of transmission by individuals who are asymptomatic at the time of transmission. Frequent, widespread testing of the asymptomatic population for SARS-CoV-2 is essential to suppress viral transmission and is a key element in safely reopening society. Despite increases in testing capacity, multiple challenges remain in deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests at the scale required for population screening of asymptomatic individuals. We have developed SwabSeq, a high-throughput testing platform for SARS-CoV-2 that uses next-generation sequencing as a readout. SwabSeq employs sample-specific molecular barcodes to enable thousands of samples to be combined and simultaneously analyzed for the presence or absence of SARS-CoV-2 in a single run. Importantly, SwabSeq incorporates an in vitro RNA standard that mimics the viral amplicon, but can be distinguished by sequencing. This standard allows for end-point rather than quantitative PCR, improves quantitation, reduces requirements for automation and sample-to-sample normalization, enables purification-free detection, and gives better ability to call true negatives. We show that SwabSeq can test nasal and oral specimens for SARS-CoV-2 with or without RNA extraction while maintaining analytical sensitivity better than or comparable to that of fluorescence-based RT-qPCR tests. SwabSeq is simple, sensitive, flexible, rapidly scalable, inexpensive enough to test widely and frequently, and can provide a turn around time of 12 to 24 hours

Massively scaled-up testing for SARS-CoV-2 RNA via next-generation sequencing of pooled and barcoded nasal and saliva samples.

Frequent and widespread testing of members of the population who are asymptomatic for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for the mitigation of the transmission of the virus. Despite the recent increases in testing capacity, tests based on quantitative polymerase chain reaction (qPCR) assays cannot be easily deployed at the scale required for population-wide screening. Here, we show that next-generation sequencing of pooled samples tagged with sample-specific molecular barcodes enables the testing of thousands of nasal or saliva samples for SARS-CoV-2 RNA in a single run without the need for RNA extraction. The assay, which we named SwabSeq, incorporates a synthetic RNA standard that facilitates end-point quantification and the calling of true negatives, and that reduces the requirements for automation, purification and sample-to-sample normalization. We used SwabSeq to perform 80,000 tests, with an analytical sensitivity and specificity comparable to or better than traditional qPCR tests, in less than two months with turnaround times of less than 24 h. SwabSeq could be rapidly adapted for the detection of other pathogens