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Wilson, R. K.

Publications and source records attributed to Wilson, R. K..

11 recordsLinked to original sources
bioRxiv2025

NR0B1 alters the 9-cis-retinoic acid response in Ewing Sarcoma cells

Pediatric cancers are often characterized by relatively low DNA mutation rates and are frequently driven instead by alterations in gene expression programs. In Ewing Sarcoma (EwS), these changes result from the activity of an oncogenic fusion transcription factor, EWS::FLI1, which alters the enhancer landscape and rewires transcriptional programs to promote oncogenic transformation. Among the targets directly activated by EWS::FLI1, NR0B1 has emerged as a potentially targetable transcription co-regulator and as a manifold for widespread alterations in downstream gene expression programs mediated by members of the ligand-inducible nuclear receptor superfamily of transcription factors. We have dissected the gene regulatory activity of NR0B1 in EwS models, showing its role in altering the basal gene expression programs of nuclear receptors COUP-TFII, EAR2, RXRa, and TR4. Additionally, we show that NR0B1 impacts the EwS response to retinoids, particularly 9-cis-retinoic acid signaling in part through RXRa. Our findings suggest NR0B1 silencing or inhibition offer a means of achieving a more potent response to retinoids, which may activate differentiation programs, decrease EwS gene expression signatures, and limit in vitro transformation phenotypes. Taken together, our study presents evidence of NR0B1 acting canonically as a nuclear receptor co-regulator in EwS, revealing a potential pathway to treatment of this aggressive cancer by combining NR0B1 inhibition with therapeutic nuclear receptor ligands.

cancer biology↗
bioRxiv2021

Genomic and transcriptomic somatic alterations of hepatocellular carcinoma in non-cirrhotic livers

BackgroundLiver cancer is the second leading cause of cancer-related deaths worldwide. Hepatocellular carcinoma (HCC) risk factors include chronic hepatitis, cirrhosis, and alcohol abuse, whereby tumorigenesis is induced through inflammation and subsequent fibrotic response. However, a subset of HCC arises in non-cirrhotic livers. We characterized the genomic and transcriptomic landscape of non-cirrhotic HCC to identify features underlying the diseases development and progression. MethodsWhole genome and transcriptome sequencing was performed on 30 surgically resectable tumors comprised of primarily of non-cirrhotic HCC and adjacent normal tissue. Using somatic variants, capture reagents were created and employed on an additional 87 cases of mixed cirrhotic/non-cirrhotic HCC. Cases were analyzed to identify viral integrations, single nucleotide variants (SNVs), insertions and deletions (INDELS), copy number variants, loss of heterozygosity, gene fusions, structural variants, and differential gene expression. ResultsWe detected 3,750 SNVs/INDELS and extensive CNVs and expression changes. Recurrent TERT promoter mutations occurred in >52% of non-cirrhotic discovery samples. Frequently mutated genes included TP53, CTNNB1, and APOB. Cytochrome P450 mediated metabolism was significantly downregulated. Structural variants were observed at MACROD2, WDPCP and NCKAP5 in >20% of samples. Furthermore, NR1H4 fusions involving gene partners EWSR1, GNPTAB, and FNIP1 were detected and validated in 2 non-cirrhotic samples. ConclusionGenomic analysis can elucidate mechanisms that may contribute to non-cirrhotic HCC tumorigenesis. The comparable mutational landscape between cirrhotic and non-cirrhotic HCC supports previous work suggesting a convergence at the genomic level during disease progression. It is therefore possible genomic-based treatments can be applied to both HCC subtypes with progressed disease. HighlightsO_LINon-cirrhotic HCC genomically resembles cirrhotic HCC C_LIO_LIComprehensive genome- and transcriptome-wide profiling allows detection of novel structural variants, fusions, and undiagnosed viral infections C_LIO_LINR1H4 fusions may represent a novel mechanism for tumorigenesis in HCC C_LIO_LINon-cirrhotic HCC is characterized by genotoxic mutational signatures and dysregulated liver metabolism C_LIO_LIClinical history and comprehensive omic profiling incompletely explain underlying etiologies for non-cirrhotic HCC highlighting the need for further research C_LI Short DescriptionThis study characterizes the genomic landscape of hepatocellular carcinomas (HCCs) in non-cirrhotic livers. Using 117 HCCs tumor/normal pairs, we identified 3,750 SNVs/INDELS with high variant frequency in TERT, TP53, CTNNB1, and APOB. CYP450 was significantly downregulated and many structural variants were observed. This characterization could assist in elucidating non-cirrhotic HCC tumorigenesis.

cancer biology↗
bioRxiv2021

Discovery of Clinically Relevant Fusions in Pediatric Cancer

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPediatric cancers typically have a distinct genomic landscape when compared to adult cancers and frequently carry somatic gene fusion events that alter gene expression and drive tumorigenesis. Sensitive and specific detection of gene fusions through the analysis of next-generation-based RNA sequencing (RNA-Seq) data is computationally challenging and may be confounded by low tumor cellularity or underlying genomic complexity. Furthermore, numerous computational tools are available to identify fusions from supporting RNA-Seq reads, yet each algorithm demonstrates unique variability in sensitivity and precision, and no clearly superior approach currently exists. To overcome these challenges, we have developed an ensemble fusion calling approach to increase the accuracy of identifying fusions. ResultsOur ensemble fusion detection approach utilizes seven fusion calling algorithms: Arriba, CICERO, FusionMap, FusionCatcher, JAFFA, MapSplice, and STAR-Fusion, which are packaged as a fully automated pipeline using Docker and AWS serverless technology. This method uses paired end RNA-Seq sequence reads as input, and the output from each algorithm is examined to identify fusions detected by a consensus of at least three algorithms. These consensus fusion results are filtered by comparison to an internal database to remove likely artifactual fusions occurring at high frequencies in our internal cohort, while a "known fusion list" prevents failure to report known pathogenic events. We have employed the ensemble fusion-calling pipeline on RNA-Seq data from 229 patients with pediatric cancer or blood disorders studied under an IRB-approved protocol. The samples consist of 138 central nervous system tumors, 73 solid tumors, and 18 hematologic malignancies or disorders. The combination of an ensemble fusion-calling pipeline and a knowledge-based filtering strategy identified 67 clinically relevant fusions among our cohort (diagnostic yield of 29.3%), including RBPMS-MET, BCAN-NTRK1, and TRIM22-BRAF fusions. Following clinical confirmation and reporting in the patients medical record, both known and novel fusions provided medically meaningful information. ConclusionsOur ensemble fusion detection pipeline offers a streamlined approach to discover fusions in cancer, at higher levels of sensitivity and accuracy than single algorithm methods. Furthermore, this method accurately identifies driver fusions in pediatric cancer, providing clinical impact by contributing evidence to diagnosis and, when appropriate, indicating targeted therapies.

genomics↗
bioRxiv2020

A novel sialic acid-binding adhesin present in multiple species contributes to the pathogenesis of infective endocarditis

Bacterial binding to platelets is a key step in the development of infective endocarditis (IE). Sialic acid, a common terminal carbohydrate on host glycans, is the major receptor for streptococci on platelets. So far, all defined interactions between streptococci and sialic acid on platelets are mediated by serine rich repeat proteins (SRRPs). However, we identified Streptococcus oralis subsp. oralis IE-isolates that bind sialic acid but lack SRRPs. In addition to binding sialic acid, some SRRP-negative isolates also bind the cryptic receptor {beta}-1,4-linked galactose through a yet unknown mechanism. Using comparative genomics, we identified a novel sialic acid-binding adhesin, here named AsaA (associated with sialic acid adhesion A), present in IE-isolates lacking SRRPs. We demonstrated that S. oralis subsp. oralis AsaA is required for binding to platelets in a sialic acid-dependent manner. AsaA comprises a non-repeat region (NRR), consisting of a FIVAR/CBM and two Siglec-like and Unique domains, followed by 31 DUF1542 domains. When recombinantly expressed, Siglec-like and Unique domains competitively inhibited binding of S. oralis subsp. oralis and directly interacted with sialic acid on platelets. We further demonstrated that AsaA impacts the pathogenesis of S. oralis subsp. oralis in a rabbit model of IE. Additionally, we found AsaA orthologues in other IE-causing species and demonstrated that the NRR of AsaA from Gemella haemolysans blocked binding of S. oralis subsp. oralis, suggesting that AsaA contributes to the pathogenesis of multiple IE-causing species. Finally, our findings provide evidence that sialic acid is a key factor for bacterial-platelets interactions in a broader range of species than previously appreciated, highlighting its potential as a therapeutic target. Authors summaryInfective endocarditis (IE) is typically a bacterial infection of the heart valves that causes high mortality. Infective endocarditis can affect people with preexisting lesions on their heart valves (Subacute-IE). These lesions contain platelets and other host factors to which bacteria can bind. Growth of bacteria and accumulation of host factors results in heart failure. Therefore, the ability of bacteria to bind platelets is key to the development of IE. Here, we identified a novel bacterial protein, AsaA, which helps bacteria bind to platelets and contributes to the development of disease. Although this virulence factor was characterized in Streptococcus oralis, a leading cause of IE, we demonstrated that AsaA is also present in several other IE-causing bacterial species and is likely relevant to their ability to cause disease. We showed that AsaA binds to sialic acid, a terminal sugar present on platelets, thereby demonstrating that sialic acid serves as a receptor for a wider range of IE-causing bacteria than previously appreciated, highlighting its potential as a therapeutic target.

microbiology↗
bioRxiv2019

The burden of deleterious variants in a non-human primate biomedical model

Genome sequencing studies of nonhuman primate (NHP) pedigree and population samples are discovering variants on a large and rapidly growing scale. These studies are increasing the utility of several NHP species as model systems for human disease. In particular, by identifying homozygous protein truncating variants (hPTVs) in genes hypothesized to play a role in causing human diseases, it may be possible to elucidate mechanisms for the phenotypic impact of such variants through investigations that are infeasible in humans. The Caribbean vervet (Chlorocebus aethiops sabaeus) is uniquely valuable for this purpose, as the dramatic expansion of its population following severe bottlenecks has enabled PTVs that passed through the bottleneck to attain a relatively high frequency. Using whole genome sequence (WGS) data from 719 monkeys of the Vervet Research Colony (VRC) extended pedigree, we found 2,802 protein-truncating alleles in 1,747 protein-coding genes present in homozygous state in at least one monkey. Polymorphic sites for 923 SNV hPTVs were also observed in natural Caribbean populations from which the VRC descends. The vervet genome browser (VGB) includes information on these PTVs, together with a catalog of phenotypes and biological samples available for monkeys who carry them. We describe initial explorations of the possible impact of vervet PTVs on early infant mortality.

genetics↗
bioRxiv2019

Functional genomics of the stable fly, Stomoxys calcitrans, reveals mechanisms underlying reproduction, host interactions, and novel targets for pest control

BackgroundThe stable fly, Stomoxys calcitrans, is a major blood-feeding pest of livestock that has near worldwide distribution, causing an annual cost of over $2 billion for control and product loss in the United States alone. Control of these flies has been limited to increased sanitary management practices and insecticide application for suppressing larval stages. Few genetic and molecular resources are available to help in developing novel methods for controlling stable flies.\n\nResultsThis study examines stable fly biology by utilizing a combination of high-quality genome sequencing, microbiome analyses, and RNA-seq analyses targeting multiple developmental stages and tissues. In conjunction, manual curation of over 1600 genes was used to examine gene content related to stable fly reproduction, interactions with their host, host-microbe dynamics, and putative routes for control. Most notable was establishment of reproduction-associated genes and identification of expanded vision, chemosensation, immune repertoire, and metabolic detoxification pathway gene families.\n\nConclusionsThe combined sequencing, assembly, and curation of the male stable fly genome followed by RNA-seq and downstream analyses provide insights necessary to understand the biology of this important pest. These resources and knowledge will provide the groundwork for expanding the tools available to control stable fly infestations. The close relationship of Stomoxys to other blood-feeding (Glossina) and non-blood-feeding flies (medflies, Drosophila, house flies) will allow for understanding the evolution of blood feeding among Cyclorrhapha flies.

genomics↗
bioRxiv2019

Samovar: Single-sample mosaic SNV calling with linked reads

We present Samovar, a mosaic single-nucleotide variant (SNV) caller for linked-read whole-genome shotgun sequencing data. Samovar scores candidate sites using a random forest model trained using the input dataset that considers read quality, phasing, and linked-read characteristics. We show Samovar calls mosaic SNVs within a single sample with accuracy comparable to what previously required trios or matched tumor/normal pairs and outperform single-sample mosaic variant callers at MAF 5%-50% with at least 30x coverage. Furthermore, we use Samovar to find somatic variants in whole genome sequencing of both tumor and normal from 13 pediatric cancer cases that can be corroborated with high recall with whole exome sequencing. Samovar is available open-source at https://github.com/cdarby/samovar under the MIT license.

genomics↗
bioRxiv2018

Exome sequencing identifies high impact trait-associated alleles enriched in Finns

As yet undiscovered rare variants are hypothesized to substantially influence an individuals risk for common diseases and traits, but sequencing studies aiming to identify such variants have generally been underpowered. In isolated populations that have expanded rapidly after a population bottleneck, deleterious alleles that passed through the bottleneck may be maintained at much higher frequencies than in other populations. In an exome sequencing study of nearly 20,000 cohort participants from northern and eastern Finnish populations that exemplify this phenomenon, most novel trait-associated deleterious variants displayed frequencies 10-173 times higher than in other European populations. These enriched alleles underlie 30 novel associations with 20 disease-related quantitative traits and demonstrate a geographical clustering equivalent to that of Mendelian disease mutations characteristic of the Finnish population. Sequencing studies in populations without this unique history would require hundreds of thousands to millions of participants for comparable power.

genomics↗
bioRxiv2017

The prognostic effects of somatic mutations in ER-positive breast cancer

More than 50 genes are recurrently affected by somatic mutation in estrogen receptor positive (ER+) breast cancer but prognostic effects have not been definitively established. Primary tumor DNA was therefore subjected to targeted sequencing from 625 postmenopausal (UBC-TAM series) and 328 premenopausal (MA12 trial) hormone receptor-positive (HR+) patients. Independent validation of prognostic interactions was achieved using independent data from the METABRIC study. Associations between MAP3K1 and PIK3CA with luminal A status and TP53 mutations with Luminal B/non-luminal tumors were observed, validating the methodological approach. In UBC-TAM, NF1 frame-shift nonsense (FS/NS) mutation was validated as a poor outcome driver. For MA12, poor outcome associated with PIK3R1 mutation was similarly validated. DDR1 mutations were strongly associated with poor prognosis in UBC-TAM despite stringent false-discovery correction (q=0.0003). In conclusion, uncommon recurrent somatic mutations should be further explored to create a more complete explanation of the highly variable outcomes that typify ER+ breast cancer.

genomics↗
bioRxiv2016

Genetic variation and gene expression across multiple tissues and developmental stages in a non-human primate

By analyzing multi-tissue gene expression and genome-wide genetic variation data in samples from a vervet monkey pedigree, we generated a transcriptome resource and produced the first catalogue of expression quantitative trait loci (eQTLs) in a non-human primate model. This catalogue contains more genome-wide significant eQTLs, per sample, than comparable human resources, and reveals sex and age-related expression patterns. Findings include a master regulatory locus that likely plays a role in immune function, and a locus regulating hippocampal long non-coding RNAs (lncRNAs), whose expression correlates with hippocampal volume. This resource will facilitate genetic investigation of quantitative traits, including brain and behavioral phenotypes relevant to neuropsychiatric disorders.

genetics↗