To perform its function as a tumor suppressor, breast cancer 1 (BRCA1) must dimerize with BRCA1-associated RING domain protein 1 (BARD1). Due to this critical interaction, pathogenic BARD1 variants are also associated with increased breast and ovarian cancer risk. Genetic testing has identified many rare single-nucleotide variants (SNVs) that cause missense amino acid substitutions in BARD1. Currently, 93% (1,692 of 1,819) of BARD1 missense SNVs are classified as a variant of uncertain significance (VUS) in ClinVar. A VUS classification prevents clinicians from using genetic test results to guide patient care. Consequently, there is a strong need to functionally assess BARD1 SNVs to help resolve VUS. We applied a multiplex assay for variant effect called saturation genome editing (SGE) to functionally assess all possible 12,000 SNVs and 2,300 3-base deletions in BARD1. In SGE, we use CRISPR-Cas9 to edit all possible SNVs into a region of BARD1 in haploid HAP1 cells. BARD1 is essential for cell growth, therefore cells edited with loss-of-function variants become depleted from the population. We track which SNVs become depleted from the population by sequencing. We then generate functional scores for each variant by calculating the change in the abundance of a variant in the original SNV library versus its abundance in the cell population after 13 days in culture. Thus far, I have generated reagents for all 14,300 variants and 2,400 have completed the full experimental pipeline. Functional scores for the functionally critical BRCA1 interaction domain show depletion of 94% stop-gain, 48% splice-site, and 21% missense variants relative to 5% synonymous and 6% intronic variants. This ultimately demonstrates SGE’s ability to accurately identify functionally normal and loss-of-function BARD1 variants. Generating functional scores for all possible BARD1 variants will provide the functional evidence needed for reclassifying BARD1 VUS and definitive test results for providers treating patients with BARD1 variants.

The human genome is associated with numerous variations, some of which can be pathogenic. Any variations larger than 50 base pairs (bp) are considered structural variants (SVs), and SVs impacting copy number of the genome are termed copy number variants (CNVs). By studying CNVs, we can understand the underlying mechanisms of damage and repair within DNA, which can help work towards prevention and cure in other fields, such as cancer genomics. My project investigates a CNV on chromosome 2 of a pediatric patient, who presents with tetralogy of Fallot, global development delay, and multiple other congenital anomalies. Using array comparative genomics hybridization (aCGH), we identified a 3.2 megabase (Mb) complex genomic rearrangement (CGR) spanning the 2q31 region of the proband’s chromosome 2. Detailed analysis of the short-read whole genome sequencing (WGS) allowed us to locate the exact coordinates of each junction, or the beginning and end points of each extra copy. PacBio long-read genome sequencing and optical genome mapping detected the same junctions and facilitated confirmation of the overall structure. The CGR can be characterized as a duplication-triplication-duplication-triplication-duplication (DUP-TRP-DUP-TRP-DUP), meaning this segment of the genome contains a segment of alternating 1 and 2 extra copies of this region. The CGR is de novo, or not inherited from the proband’s parents. Due to the nature of this variant, it is likely to be impacting the phenotype of our patient. To establish a genotype-phenotype correlation, I did a literature review of patients with overlapping CGRs, comparing their phenotypes to our proband, as well as reviewing any known disease-associated genes in the region using the online catalog of human genes and genetic disorders (OMIM). Patient and disease comparison revealed the extreme rarity of our patient’s CGR, leading us to believe the phenotype of the proband results from impact of multiple genes in the affected region.

High-grade serous carcinoma (HGSC), the most common subtype of ovarian cancer, originates in the fallopian tube epithelium from precursor lesions carrying somatic TP53 mutations. Individuals with germline mutations in DNA repair genes are at high risk of HGSC but the reason is unknown. We hypothesize that individuals at high risk of HGSC carry an excess of pathogenic TP53 mutations in fallopian tube epithelium, which predisposes them to cancer. Preliminary data suggests that individuals with germline mutations in BRCA1 and BRCA2 (lifetime risk of HGSC 45% and 21%, respectively) have more TP53 mutations in fallopian tube than individuals without germline mutations, supporting our hypothesis. However, TP53 mutations have not yet been characterized in individuals with germline mutations in RAD51C/RAD51D, BRIP1 and PALB (lifetime risks of HGSC 10%, 6% and 5%, respectively). We aimed to conduct an ultra-sensitive characterization of TP53 mutations in patients with germline mutations in RAD51C/RAD51D, BRIP1, and PALB2, and compare their mutational profile with those of individuals without germline mutations in HGSC risk genes and those with BRCA1 or BRCA2 germline mutations. Right and left fallopian tube biopsies were collected, frozen, and macrodissected using a 1mm biopsy punch. DNA was extracted and sequenced for TP53 using ultra-deep (15,000x) duplex sequencing. Data from 6 patients revealed varying degrees of pathogenic mutations in individuals with germline mutations. BRIP1 and PALB2 patients showed low and moderate levels of TP53 pathogenic mutations (11% and 41%, respectively), while RAD51C patients showed the highest percentage of pathogenic mutations (67%), matching their higher HGSC risk. We plan to sequence 6 additional patients to get more comprehensive data. By showing the differences in TP53 mutation patterns among these distinct populations, our research seeks to enhance our understanding of the underlying mechanisms of ovarian cancer predisposition and design better tools for early cancer detection, prediction, and risk assessment.

Budding yeast cultures grown in limited sulfate conditions are overtaken by cells with an inverted triplication of the gene SUL1, which encodes for a sulfate transporter. The extra copies of the sulfate transporter provide a selective advantage because these cells outcompete other yeast cells for the limiting resource. To explain the mechanism behind this type of amplification the Brewer and Dunham Labs proposed a model (Origin Dependent Inverted Repeat Amplification or ODIRA), which requires both a DNA replication origin and inverted repeats flanking SUL1. ODIRA starts with a DNA replication error involving replication fork regression that leads to an extrachromosomal DNA intermediate. This intermediate then replicates and recombines into the genome, producing the observed amplification. Because similar triplications are observed in the human genome, including in human disorders, the mechanism of ODIRA offers insights into human genome evolution and disease. While the yeast research is consistent with ODIRA, we still do not know which proteins are responsible for the process. I am testing whether the genes RAD5 and RAD54 — involved in fork regression and strand switching, respectively — are involved in ODIRA. To do so, I am measuring the ODIRA frequency in strains with each gene deleted compared to a wild-type control. If either gene deletion leads to a statistically significant change in ODIRA frequency compared to the wild-type strain, I can conclude this gene is involved in ODIRA. To measure ODIRA frequency, I grow the deletion strains under selection for DNA recombination events and use whole chromosome gel electrophoresis and Southern blotting to detect ODIRA events. Preliminary data analysis suggests that there is a reduction in ODIRA events when either RAD5 or RAD54 is deleted, indicating that these genes are likely needed for ODIRA. These results may provide insight into how inverted triplications may arise.

In order to design effective countermeasures against HIV, we must first understand the forces that drive it to evolve resistance within hosts. While linkage patterns in genetic data are potentially a powerful tool to quantify the relative contributions of multiple evolutionary forces (mutation, recombination, selection) acting during an HIV infection, the severe viral population bottlenecks accompanying drug therapy complicate these patterns. To interpret genetic linkage in the context of such major changes in population structure (which are themselves driven by specific mutations), we develop a simulation framework for viral evolution in which genetics and population structure influence each other. This framework overcomes limitations from both dynamical modeling, in which patterns of linked variation are ignored, and from population genetic modeling, in which population structure is predetermined. Using few parameters, we are able to reproduce linkage patterns and population bottlenecks that broadly conform to those observed in vivo. As a case study to demonstrate this model’s utility, we consider a recent hypothesis that viral recombination is suppressed during population bottlenecks due to diminished opportunities for coinfection. In simulating populations with and without recombination suppression during population contraction, we show that this effect measurably changes genetic diversity in rebounding populations, but is less visible when examining simulated viral loads or resistance mutations alone. Then, using this model as a null expectation for linkage patterns, we assess if the linkage structure in HIV populations treated with bNAbs is consistent with density-dependent recombination in vivo. Collectively, our work demonstrates that, by generating realistic null expectations of linkage under complex changes in population structure, we can employ linkage patterns as a powerful source of information for evaluating viral evolutionary hypotheses.

Understanding genetic risk factors for osteoporosis, a common chronic bone disease that increases fracture risk, is essential for developing new therapies. Genetic variants near SLC8A1, a member of the SLC8 gene family of sodium/calcium exchangers, have been associated with bone mineral density and fracture risk. More recently, I have shown that zebrafish slc8a4b, an ortholog of human SLC8A1, is highly expressed in osteoblasts through scRNA sequencing analysis. However, animal studies examining the expression pattern and necessity of slc8a4b in developing bone have yet to be conducted. Here, I tested the hypothesis that slc8a4b is highly expressed in osteoblasts and required for early bone formation in zebrafish. To evaluate the expression of slc8a4b, we performed whole-mount in situ hybridization chain reaction (HCR) RNA FISH of zebrafish embryos at 3dpf and 5dpf. To assess the function of slc8a4b, I utilized slc8a4b mutant allele sa34209, generated through large-scale zebrafish mutagenesis efforts. Structural modeling revealed that sa34209 results in severe protein truncation. To determine whether slc8a4b is necessary for skeletal development, I will incross adult slc8a4b^+/sa34209 heterozygous mutants to generate slc8a4b^{sa34209/sa34209} homozygous mutants and perform calcein staining at 5dpf and 13dpf to assess craniofacial and vertebral morphology in zebrafish. My preliminary data shows that slc8a4b is highly expressed in early craniofacial structures such as the opercle. This study will be the first to examine the necessity of slc8a4b in vivo and thus could uncover the role of solute carrier family 8 genes in skeletal development, which could lead to new therapies for osteoporosis.