Biology subjects

Edwards, J. S.

Publications and source records attributed to Edwards, J. S..

13 recordsLinked to original sources

bioRxiv2026

Multi-Omic and Spatial Profiling Defines Outcome-Associated Tumor States in Head and Neck Adenoid Cystic Carcinoma

Abstract Head and neck adenoid cystic carcinoma (HNACC) shows highly variable clinical behavior that histopathological features only partly predict, and prognostic biomarkers for aggressive disease at diagnosis remain limited. Here, we show by integrating bulk, single-cell, and spatial transcriptomes from 25 HNACC tumors that poor survival is marked by profound loss of myoepithelial tumor cells and expansion of luminal tumor states. Both outcome groups share a myoepithelial-like origin, but aggressive tumors converge on an actively dividing, MYC/E2F-driven luminal state concentrated in discrete spatial niches. Aggressiveness therefore reflects where tumors end along a shared developmental path rather than a distinct lineage or altered immune infiltration. A four-gene classifier capturing this state predicted survival in an independent cohort, outperforming larger signatures and flagging aggressive subgroups in two others. These findings define a lineage proliferation axis linked to HNACC outcome, providing a basis for prospective risk stratification and proliferative-directed therapy.

cancer biology↗

bioRxiv2025

Gene-Expression Programs in Salivary Gland Adenoid Cystic Carcinoma Analyzed Using Single-Cell and Spatial Transcriptomics

Adenoid cystic carcinoma of the salivary gland (SGACC) is a highly aggressive malignancy characterized by poor patient survival outcomes. While several studies have analyzed the transcriptome of the salivary gland at the bulk and single-cell level, no spatial transcriptomic analyses of this tissue have been published. Most of the existing publications on SGACC have predominantly relied on bulk and single cell RNA sequencing approaches, which do not resolve the spatially localized transcriptional heterogeneity nor have the resolution for defining molecular markers within tumor subpopulations. SGACC is clinically notable for the presence of multiple tumor clones, distinct spatial phenotypes, and its indolent yet invasive nature coupled with a high propensity for distant metastasis. These features may reflect co-expression of tumor-associated markers across diverse cellular niches, and a resultant biological complexity which causes standard treatment such as surgical resection, radiation therapy, and chemotherapy to be largely ineffective in significantly improving long-term survival, and highlights the need for more precise, targeted therapeutic strategies. Herein, we analyzed single cell (n = 4) and high-resolution spatial transcriptomics samples (n = 5) to characterize cancer cell populations in MYB- and non-MYB-expressing cell states, delineated gene expression signatures, and identified critical molecular interactions specific to SGACC. We used Visum HD to obtain spatial transcriptomics data at 2{micro}m squared high resolution. This allowed a multi-omics approach comprising single cell and spatial transcriptomic methods to enable the discovery of novel transcriptional signatures and microenvironmental features not captured by conventional methods. Spatial mapping revealed marked cellular heterogeneity and demonstrated how tissue environments influence cellular transcriptomics. To tumor heterogeneity, we focused on tumorigenic cell populations, profiled plasma and T cell enrichment within the tumor microenvironment and identified key pathways and transcriptional drivers including the MYB-NFIB fusion underlying the tumor cluster formation. Our findings indicate an upregulation of genes involved in extracellular matrix remodeling, autophagy, and reactive stromal cell populations. We further found evidence of partial epithelial-mesenchymal transition (P-EMT) programming within MYB-expressing tumor clusters. Pathway analysis revealed that mutations in the spatial query sample prominently affect the PI3K-AKT and IL-17 signaling pathways, together with a downregulation of canonical Wnt signaling in some regions of the tissue architecture adjacent to immune cells. Collectively, these results underscore the complex regulatory landscape of SGACC and offer insights into its cellular dynamics and possible therapeutic vulnerabilities.

cancer biology↗

bioRxiv2024

Deep Learning enabled discovery of kinase drug targets in Pharos

AO_SCPLOWBSTRACTC_SCPLOWWe use machine learning with standardized molecular structure and gene ontology data to predict ligand interactions for a set of human kinases. We realize this by leveraging information from the TCRD / Pharos database, developed and maintained within the Illuminating the Druggable Genome (IDG) project. Pharos collects relevant biochemical and clinically relevant information of a large set of biologically important (human) proteins from publicly available sources, including scientific publications as well as specialized databases. The 635 kinases listed in Pharos are classified into levels reflecting the relative amount and type of accumulated information. Importantly, molecular structure and Gene Ontology annotations are available for the entire set, but only 455 of the kinases have recorded ligand affinity data. We developed a deep neural network-based framework to predict the ligand affinity profile for kinases using generally available information (molecular structure and Gene Ontology annotations) as input. The input data is organized into a 2,770 - dimensional vector with binary entries. The output data are predicted affinity values for interactions between the respective kinase and possible ligands. To address the very large number of possible ligands (58,800) and the sparsity of available binding data, we organized the ligands into 5,275 clusters based on structural similarity measures. Our model framework is trained to predict likely interactions between kinases and these ligand clusters. We aim to identify sets of likely ligand partners associated with high predicted relative affinities for a given kinase. We measure performance by evaluating the efficiency in identifying known ligand partners for documented kinases that were not included in the training data. Our results indicate that our model framework can identify sets of ligands that will contain a significant fraction of the correct (known) ligand partners.

bioinformatics↗

bioRxiv2024

Bioinformatic analysis of human ZPR1 gene pathogenic exome mutation

Advanced sequencing technologies enable rapid detection of sequence variants, aiming to uncover the molecular foundations of human genetic disorders. The challenge lies in interpreting the influence of new exome variants that lead to diverse phenotypes. Our study introduces a detailed, multi-tiered method for assessing the impact of novel variants, particularly focusing on the zinc finger protein 1 (ZPR1) gene. Herein, we employed a combination of variant effect predictors, protein stability analyses, and the American College of Medical Genetics and Association of Molecular Pathology (ACMG/AMP) guidelines. Our structural analysis pinpoints specific amino acid residues in the ZPR1 zinc finger domains that are sensitive to changes, distinguishing between benign and disease-causing coding variants using rigorous in silico tools. We examined 223 germline ZPR1 exome variants, uncovering significant ethnic disparities in the frequency of heterozygous harmful ZPR1 variants, ranging from 0.04% in the Ashkenazi Jewish population to 0.34% in African/African Americans. Additionally, the discovery of three homozygous carriers in European and South Asian groups suggests a higher occurrence of ZPR1 variants in these demographics, meriting further exploration. This research provides insights into the prevalence and implications of amino acid substitutions in the ZPR1 protein.

bioinformatics↗

bioRxiv2021

SARS-CoV-2 Variant Identification Using a Genome Tiling Array and Genotyping Probes

With over three million deaths worldwide attributed to the respiratory disease COVID-19 caused by the novel coronavirus SARS-CoV-2, it is essential that continued efforts be made to track the evolution and spread of the virus globally. We previously presented a rapid and cost-effective method to sequence the entire SARS-CoV-2 genome with 95% coverage and 99.9% accuracy. This method is advantageous for identifying and tracking variants in the SARS-CoV-2 genome when compared to traditional short read sequencing methods which can be time consuming and costly. Herein we present the addition of genotyping probes to our DNA chip which target known SARS-CoV-2 variants. The incorporation of the genotyping probe sets along with the advent of a moving average filter have improved our sequencing coverage and accuracy of the SARS-CoV-2 genome.

bioinformatics↗

bioRxiv2021

The Lithuanian reference genome LT1 - a human de novo genome assembly with short and long read sequence and Hi-C data

We present LT1, the first high-quality human reference genome from the Baltic States. LT1 is a female de novo human reference genome assembly constructed using 57x of ultra-long nanopore reads and 47x of short paired-end reads. We also utilized 72 Gb of Hi-C chromosomal mapping data to maximize the assemblys contiguity and accuracy. LT1s contig assembly was 2.73 Gbp in length comprising of 4,490 contigs with an N50 value of 13.4 Mbp. After scaffolding with Hi-C data and extensive manual curation, we produced a chromosome-scale assembly with an N50 value of 138 Mbp and 4,699 scaffolds. Our gene prediction quality assessment using BUSCO identify 89.3% of the single-copy orthologous genes included in the benchmarking set. Detailed characterization of LT1 suggested it has 73,744 predicted transcripts, 4.2 million autosomal SNPs, 974,000 short indels, and 12,330 large structural variants. These data are shared as a public resource without any restrictions and can be used as a benchmark for further in-depth genomic analyses of the Baltic populations.

genomics↗

bioRxiv2019

Raptor genomes reveal evolutionary signatures of predatory and nocturnal lifestyles

BackgroundBirds of prey (raptors) are dominant apex predators in terrestrial communities, with hawks (Accipitriformes) and falcons (Falconiformes) hunting by day, and owls (Strigiformes) hunting by night.\n\nResultsHere, we report new genomes and transcriptomes for 20 species of birds, including 16 species of birds of prey, and high-quality reference genomes for the Eurasian eagle-owl (Bubo bubo), oriental scops-owl (Otus sunia), eastern buzzard (Buteo japonicus), and common kestrel (Falco tinnunculus). Our extensive genomic analysis and comparisons with non-raptor genomes identified common molecular signatures that underpin anatomical structure and sensory, muscle, circulatory, and respiratory systems related to a predatory lifestyle. Compared with diurnal birds, owls exhibit striking adaptations to the nocturnal environment, including functional trade-offs in the sensory systems (e.g., loss of color vision genes and selection for enhancement of nocturnal vision and other sensory systems) that are probably convergent with other nocturnal avian orders. Additionally, we found that a suite of genes associated with vision and circadian rhythm were differentially expressed between nocturnal and diurnal raptors, indicating adaptive expression change during the transition to nocturnality.\n\nConclusionsOverall, raptor genomes showed genomic signatures associated with the origin and maintenance of several specialized physiological and morphological features essential to be apex predators.

genomics↗

bioRxiv2018

Genomic perspectives on adaptation and conservation in the endangered long-tailed goral (Naemorhedus caudatus).

Native to the mountains of East Asia, the long-tailed goral (Naemorhedus caudatus) is a vulnerable wild ungulate in the tribe Caprini. To understand key conservation issues related to fragmentation and subsequent endangerment of this montane species, we sequenced and analyzed the genome of a long-tailed goral to explore historical demography, contemporary levels of genetic diversity, and potential immune response. When compared to ten additional mammalian reference genomes, we identified 357 positively selected genes (PSGs) in the long-tailed goral and 364 PSGs in the Caprini lineage. Gene Ontology analyses showed statistical enrichment in biological processes related to immune function and in genes and pathways related to blood coagulation. We also identified low levels of heterozygosity (0.00114) in the long-tailed goral along with decreases in population size relative to other species of Caprini. Finally, we provide evidence for positive selection on the muscle development gene myostatin (MSTN) in the Caprini lineage, which may have increased the muscle development and climbing ability in the caprine common ancestor. Low effective population size and decreased heterozygosity of the long-tailed goral raise conservation concern about the effects of habitat fragmentation, over harvest, and inbreeding on this vulnerable species.

bioinformatics↗

bioRxiv2018

The jellyfish genome sheds light on the early evolution of active predation

BackgroundUnique among cnidarians, jellyfish have remarkable morphological and biochemical innovations that allow them to actively hunt in the water column. One of the first animals to become free-swimming, jellyfish employ pulsed jet propulsion and venomous tentacles to capture prey.\n\nResultsTo understand these key innovations, we sequenced the genome of the giant Nomuras jellyfish (Nemopilema nomurai), the transcriptomes of its bell and tentacles, and transcriptomes across tissues and developmental stages of the Sanderia malayensis jellyfish. Analyses of Nemopilema and other cnidarian genomes revealed adaptations associated with swimming, marked by codon bias in muscle contraction and expansion of neurotransmitter genes, along with expanded Myosin type II family and venom domains; possibly contributing to jellyfish mobility and active predation. We also identified gene family expansions of Wnt and posterior Hox genes, and discovered the important role of retinoic acid signaling in this ancient lineage of metazoans, which together may be related to the unique jellyfish body plan (medusa formation).\n\nConclusionsTaken together, the jellyfish genome and transcriptomes genetically confirm their unique morphological and physiological traits that have combined to make these animals one of the worlds earliest and most successful multi-cellular predators.

genomics↗

bioRxiv2018

The whale shark genome reveals how genomic and physiological properties scale with body size

The endangered whale shark (Rhincodon typus) is the largest fish on Earth and is a long-lived member of the ancient Elasmobranchii clade. To characterize the relationship between genome features and biological traits, we sequenced and assembled the genome of the whale shark and compared its genomic and physiological features to those of 81 animals and yeast. We examined scaling relationships between body size, temperature, metabolic rates, and genomic features and found both general correlations across the animal kingdom and features specific to the whale shark genome. Among animals, increased lifespan is positively correlated to body size and metabolic rate. Several genomic features also significantly correlated with body size, including intron and gene length. Our large-scale comparative genomic analysis uncovered general features of metazoan genome architecture: GC content and codon adaptation index are negatively correlated, and neural connectivity genes are longer than average genes in most genomes. Focusing on the whale shark genome, we identified multiple features that significantly correlate with lifespan. Among these were very long gene length, due to large introns highly enriched in repetitive elements such as CR1-like LINEs, and considerably longer neural genes of several types, including connectivity, activity, and neurodegeneration genes. The whale sharks genome had an expansion of gene families related to fatty acid metabolism and neurogenesis, with the slowest evolutionary rate observed in vertebrates to date. Our comparative genomics approach uncovered multiple genetic features associated with body size, metabolic rate, and lifespan, and showed that the whale shark is a promising model for studies of neural architecture and lifespan.

genomics↗

bioRxiv2017

Sequential Super-Resolution Imaging using DNA Strand Displacement

Sequential labeling and imaging in fluorescence microscopy allows the imaging of multiple structures in the same cell using a single fluorophore species. In super-resolution applications, the optimal dye suited to the method can be chosen, the optical setup can be simpler and there are no chromatic aberrations between images of different structures. We describe a method based on DNA strand displacement that can be used to quickly and easily perform the labeling and removal of the fluorophores during each sequence. Site-specific tags are conjugated with unique and orthogonal single stranded DNA. Labeling for a particular structure is achieved by hybridization of antibody-bound DNA with a complimentary dye-labeled strand. After imaging, the dye is removed using toehold-mediated strand displacement, in which an invader strand competes off the dye-labeled strand than can be subsequently washed away. Labeling and removal of each DNA-species requires only a few minutes. We demonstrate the concept using sequential dSTORM super-resolution for multiplex imaging of subcellular structures.

bioengineering↗

bioRxiv2017

A whole genome analysis of the red-crowned crane provides insight into avian longevity

The red-crowned crane (Grus japonensis) is an endangered and large-bodied crane native to East Asia. It is a traditional symbol of longevity and its long lifespan has been confirmed both in captivity and in the wild. Lifespan in birds is positively correlated with body size and negatively correlated with metabolic rate; although the genetic mechanisms for the red-crowned cranes long lifespan have not previously been investigated. Using whole genome sequencing and comparative evolutionary analyses against the grey-crowned crane and other avian genomes, we identified candidate genes that are correlated with longevity. Included among these are positively selected genes with known associations with longevity in metabolism and immunity pathways (NDUFA5, NDUFA8, NUDT12 IL9R, SOD3, NUDT12, PNLIP, CTH, and RPA1). Our analyses provide genetic evidence for low metabolic rate and longevity, accompanied by possible convergent adaptation signatures among distantly related large and long-lived birds. Finally, we identified low genetic diversity in the red-crowned crane, consistent with its listing as an endangered species, and we hope this genome will provide a useful genetic resource for future conservation studies of this rare and iconic species.

bioinformatics↗

bioRxiv2017

The Sentieon Genomics Tools - A fast and accurate solution to variant calling from next-generation sequence data

In the past six years worldwide capacity for human genome sequencing has grown by more than five orders of magnitude, with costs falling by nearly two orders of magnitude over the same period [1], [2]. The rapid expansion in the production of next-generation sequence data and the use of these data in a wide range of new applications has created a need for improved computational tools for data processing. The Sentieon Genomics tools provide an optimized reimplementation of the most accurate pipelines for calling variants from next-generation sequence data, resulting in more than a 10-fold increase in processing speed while providing identical results to best practices pipelines. Here we demonstrate the consistency and improved performance of Sentieons tools relative to BWA, GATK, MuTect, and MuTect2 through analysis of publicly available human exome, low-coverage genome, and high-depth genome sequence data.

bioinformatics↗