Biology subjects

Turner, S. D.

Publications and source records attributed to Turner, S. D..

At least 19 recordsLinked to original sources

bioRxiv2026

nf-core/genomeqc: a best-practice pipeline for comparing genome and assembly quality

The rapid growth in publicly available genome assemblies has made selecting genomes suitable for downstream analyses increasingly challenging. Differences in assembly and annotation quality can influence gene completeness, duplication rates, contiguity, repeat representation, and other characteristics. Assessing genome quality therefore requires integrating multiple complementary quality metrics that are often generated by independent tools. Here, we present nf-core/genomeqc, a workflow for assessing and comparing genome assemblies. The pipeline accepts RefSeq/GenBank accessions for automatic genome and annotation retrieval, or local genome (FASTA) and annotation (GFF3/GTF) files. It integrates complementary analyses of assembly contiguity, gene completeness, annotation quality, repeat content and other quality metrics using tools such as BUSCO, QUAST, Merqury, and AGAT, before combining the results on a phylogenetic tree for visualisation and comparison across species. GenomeQC is implemented in Nextflow within the nf-core framework, providing an accessible, reproducible, scalable and community-driven workflow for genome quality assessment.

bioinformatics↗

bioRxiv2026

Survey and Evaluation of Applied Containerization Practices in Bioinformatics

Containerization enables portable, reproducible, and scalable scientific computing. However, container development, documentation, and deployment practices can vary widely, even within a single domain. Understanding patterns of how containers are implemented in real-world settings can inform community guidelines, quality scoring rubrics, and systems to automate software review. Focusing on bioinformatics as an exemplar domain, we surveyed published software tools to find applied containerization examples. After identifying >250 tools to review, we annotated metadata regarding version control, asset provenance, and general container image health and tested the ability to build and pull the container images in a purpose-built evaluation platform (https://github.com/vpnagraj/socr8s). The majority of images tested did not build successfully in our environment. Of the tool characteristics we tracked, the strongest predictor of build success was version control activity. Tools with commits in the preceding two years were roughly twice as likely to build. Deeper assessment of failures identified a variety of issues, including missing assets and broken dependency chains. While many tools had published images accessible in open registries, 24% could neither be built nor pulled. Images tended to be large, with median size of 1.57GB for those that were able to be built. Where image specification files were available, we found that more advanced container orchestration and build techniques were uncommon. Our results highlight areas of improvement in how containerized tools are built and maintained in bioinformatics and scientific computing software in general.

bioinformatics↗

bioRxiv2026

Single-Cell Profiling Reveals Developmental Trajectories and identifies SYK and TIM3 as Targets in some T Cell Lymphomas

T cell lymphomas (TCL) are a heterogeneous collection of malignancies whose origins and pathogenesis are poorly understood and for which few efficacious therapeutic options exist. Here, we conduct single-cell transcriptomic profiling spanning eight TCL entities and describe entity-associated programmes. We predict the cell of origin for these tumours through an integrative analysis of transcriptome and T cell receptor (TCR) maturation states. By identifying tumours with TCR states ranging from the pre-TCR through non-productive and productive TCR alpha and beta chain rearrangements we shed new light on their developmental origins. Furthermore, we apply our drug2cell computational drug target predictions with drug screens using patient-derived cell models, systematically benchmarking the performance of drug2cell and validating compounds and targets. This process identifies SYK inhibitors as a therapeutic opportunity and prioritises TIM3 for immunotherapy based on combined spatial transcriptomics analysis. Overall, our data provide a resource for diagnostics and therapies for tumours of critical unmet need.

cancer biology↗

bioRxiv2026

TGS1 mediates mRNA 5'-cap trimethylation to promote oxidative phosphorylation in acute myeloid leukaemia.

The Trimethyl guanosine Synthase (TGS1) is a highly conserved enzyme mediating di-methylation of the 5-cap 7-methylguanosine of RNA to generate 2,2,7-trimethylguanosine (m2,2,7G). Known TGS1 targets include snRNAs, snoRNAs, the telomeric RNA component and a limited number of mRNAs encoding selenoproteins. TGS1 is highly expressed in acute myeloid leukaemia (AML) cells, and its expression correlates with poor prognosis. Here, we report that TGS1 directly methylates the cap of more than 500 mRNAs in AML cells. Specifically, we demonstrate that TGS1 modifies nuclear mRNAs encoding mitochondrial proteins, including critical components of complexes involved in both the TCA cycle and oxidative phosphorylation, promoting their translation mediated by mitochondria associated cytosolic ribosomes. Functionally, we report that TGS1 depletion impairs mitochondrial respiration and increases oxidative stress. This, in turn, impairs the growth of AML cells causing differentiation and cell cycle arrest in vitro and in vivo. Finally, we demonstrate that TGS1 depletion sensitizes AML cells to RSL3, a small molecule promoting ferroptosis. Taken together, our findings establish TGS1 as a key regulator of oxidative phosphorylation and mitochondrial redox status of AML cells and highlight its potential as a therapeutic target in leukaemia.

cancer biology↗

bioRxiv2024

FGFR2 promotes resistance to ALK tyrosine kinase inhibitors and its inhibition acts synergistically with lorlatinib in the treatment of ALK-expressing neuroblastoma

Anaplastic Lymphoma Kinase inhibitors (ALK TKIs) are approved for the treatment of ALK-positive non-small cell lung cancer (NSCLC) and are in clinical trial for ALK-aberrant high-risk neuroblastoma (NB) patients, particularly loratinib. However, resistance to ALK inhibitors can occur in patients, via the activation of bypass-signalling pathways, and there is a need to identify these mechanisms as well as drugs that inhibit them to design therapeutic approaches that prevent resistance, and to treat ALK TKI relapsed/refractory disease. Using genome-wide CRISPR-Cas9 overexpression screens, we identified and validated FGFR2 as a desensitizer to lorlatinib in aberrant ALK-expressing high-risk NB. FGFR2 and FGFR2-associated pathways are up-regulated in lorlatinib-resistant NB cells. Moreover, high-throughput screens using a library of 1,430 FDA approved drugs identified kinase inhibitors including those targeting FGFR2 as efficacious in reducing the survival of lorlatinib resistant NB cells. Hence, the FGFR pathway was investigated as a therapeutic target applying the pan-FGFR inhibitor erdafitinib or the multi-kinase inhibitor ponatinib, resulting in reduced survival of lorlatinib-resitant cells in comparison to their lorlatinib-sensitive counterparts. Moreover, both FGFR inhibitors act synergistically with lorlatinib in vitro and in vivo, using patient-derived xenografts (PDXs) and genetically engineered models (GEMM) of ALK-expressing NB. FGFR2 mRNA expression also correlate with a poorer prognosis for NB patients, regardless of sub-type, suggesting that a broader range of patients may benefit from FGFR inhibitors. Overall, our data suggests that FGFR2 potentially plays roles in lorlatinib resistance in NB and that combined pharmacological inhibition of ALK and FGFR constitutes a therapeutic approach to treat high-risk NB.

cancer biology↗

bioRxiv2023

METTL3/MYCN cooperation drives m6A modification during trunk neural crest differentiation and represents a therapeutic vulnerability in MYCN-amplified neuroblastoma

Neuroblastoma (NB) is the most common extracranial childhood cancer, caused by the improper differentiation of developing trunk neural crest cells (tNCC) in the sympathetic nervous system. The N6-methyladenosine (m6A) epitranscriptomic modification controls post-transcriptional gene expression but the mechanism by which the m6A methyltransferase complex METTL3/METTL14/WTAP is recruited to specific loci remains to be fully characterized. We explored whether the m6A epitranscriptome could fine-tune gene regulation in migrating/differentiating tNCC. We demonstrate that the m6A modification regulates the expression of HOX genes in tNCC, thereby contributing to their timely differentiation into sympathetic neurons. Furthermore, we show that posterior HOX genes are m6A modified in MYCN-amplified NB with reduced expression. In addition, we provide evidence that sustained overexpression of the MYCN oncogene in tNCC drives METTL3 recruitment to a specific subset of genes including posterior HOX genes creating an undifferentiated state. Moreover, METTL3 depletion/inhibition induces DNA damage and differentiation of MYCN overexpressing cells and increases vulnerability to chemotherapeutic drugs in MYCN-amplified patient-derived xenografts (PDX) cells, suggesting METTL3 inhibition could be a potential therapeutic approach for NB.

cancer biology↗

bioRxiv2023

tfboot: Bootstrapping and statistical analysis for transcription factor binding site-disrupting variants in gene sets

MotivationGenetic variants in noncoding regions can drive changes in phenotype disrupting transcription factor binding site (TFBS) motifs. Other tools including motifbreakR have been developed to assess the impact of TFBS-disrupting variants. Here we introduce the tfboot package for statistically evaluating the TFBS disruption across a set of variants in upstream promoter regions. ResultsThe tfboot package builds on motifbreakR, plyranges, and GenomicRanges to provide methods for bootstrapping TFBS disruption to statistically quantify the impact across gene sets of interest compared to an empirical null distribution. We demonstrate the analysis here on variants in the elephant genome. The tfboot package readily integrates with Bioconductor and tidyverse-based workflows. AvailabilityThe tfboot package is implemented as an R package and is released under the MIT license at https://github.com/colossal-compsci/tfboot.

bioinformatics↗

bioRxiv2022

k2v: A Containerized Workflow for Creating VCF Files from Kintelligence Targeted Sequencing Data

The ForenSeq Kintelligence kit developed by Verogen is a targeted Illumina sequencing assay that genotypes 10,230 single nucleotide polymorphisms designed for forensic genetic genealogy, forensic DNA phenotyping, and ancestry inference. We developed k2v, a containerized workflow for creating standard specification-compliant variant call format (VCF) files from the custom output data produced by the Kintelligence Universal Analysis Software. VCF files produced with k2v enable the use of many pre-existing, widely used, community-developed tools for manipulating and analyzing genetic data in the standard VCF format. Here we describe the k2v implementation, demonstrate its usage, and use the VCF produced by k2v to demonstrate downstream analyses that can easily be performed with pre-existing tools using VCF data as input: concordance analysis, ancestry inference, and relationship estimation. k2v is distributed as a Docker container available on Docker Hub. Documentation and source code for k2v is freely available under the GNU Public License (GPL-3.0) at https://github.com/signaturescience/k2v.

bioinformatics↗

bioRxiv2022

Internal Validation of the ForenSeq Kintelligence Kit for Application to Forensic Genetic Genealogy

Forensic Genetic Genealogy (FGG) requires high density single nucleotide polymorphism (SNP) profiles to infer distant relationships. The ForenSeq Kintelligence kit is a recently developed method targeting approximately 10,000 SNPs that were selected to be compatible with genetic genealogy databases, while avoiding medically relevant SNPs. The targeted PCR method is ideal for low input and degraded samples, which are particularly challenging for microarray analysis. We made modifications to library preparation and sample pooling to further enhance the performance of low input samples. To align this FGG method with forensic laboratory standards, we performed an internal validation study in accordance with the Scientific Working Group on DNA Analysis Methods Validation Guidelines for DNA Analysis Methods. The sensitivity and precision and accuracy studies produced accurate and reliable profiles down to 0.05 ng of DNA. The mixture and contamination studies demonstrated that the method could detect the presence of a minor contributor down to 0.02 ng, while system wide contamination was negligible. Nonprobative bone, fired shell casing, and adhesive tape samples performed well with inputs ranging from 0.05 to 1.0 ng of DNA. A bone with a high degradation index and tested at 0.1 ng DNA input resulted in a call rate of 92.9% and a heterozygosity rate of 0.387. We demonstrated the importance of both call rate and heterozygosity rate to assess profile performance. Validating FGG methods is critical to ensuring the reliability and utility of SNP profiles that will be uploaded to genetic genealogy databases for the purpose of generating investigative leads.

genomics↗

bioRxiv2022

Developmental Validation of the Illumina Infinium Assay using the Global Screening Array (GSA) on the iScan System for use in Forensic Laboratories

Microarray processing, which interrogates hundreds of thousands of single nucleotide polymorphisms (SNPs) across the human genome, has recently gained traction in forensics due to its use in forensic genetic genealogy, which is based on analysis using SNPs to compare distant relatives in publicly curated databases for the purposes of developing investigative leads or identifying human remains. To date, there has been no published developmental validation of microarray processing using the Scientific Working Group on DNA Analysis Methods (SWGDAM) Validation Guidelines for DNA Analysis Methods and Federal Bureau of Investigation Quality Assurance Standards. Validation of these methods are warranted to identify samples suitable for microarray analysis and to assess the quality of the data obtained prior to upload to genealogical databases. In this study, we validated the Global Screening Array (GSA) for use in forensic investigations according to SWGDAM guidelines, including the following studies: precision and accuracy, sensitivity, contamination, degradation, species specificity, mock case-type samples, mixtures, repeatability and reproducibility, and stability. Results indicated accurate genotype calls with SNP call rates >95% at DNA input as low as 0.20 ng. In addition to SNP call rate, we developed interpretation thresholds for signal intensity and heterozygosity to allow for sample quality assessment and identification of highly degraded and/or non-human DNA. This study demonstrates that high quality data can be generated from multiple sample types, including mock forensic evidence that simulated the challenges that are often encountered in forensic cold cases.

genomics↗

bioRxiv2022

STAT3 cooperates with the core transcriptional regulatory circuitry to drive MYC expression and oncogenesis in anaplastic large cell lymphoma

Anaplastic large cell lymphoma (ALCL) is an aggressive, CD30+ T-cell lymphoma of children and adults. ALK fusion transcripts or mutations in the JAK-STAT pathway are observed in most ALCL tumors, but the mechanisms underlying tumorigenesis are not fully understood. Here we show that dysregulated STAT3, together with a core transcriptional regulatory circuit consisting of BATF3-IRF4- IKZF1, co-occupies gene enhancers to establish an oncogenic transcription program and maintain the malignant state of ALCL. Critical downstream targets of this network in ALCL cells include the proto-oncogene MYC, which requires active STAT3 to facilitate high levels of MYC transcription. The activity of this auto-regulatory transcription loop is reinforced by MYC binding to the enhancer regions associated with STAT3 and each of the core regulatory transcription factors. These findings provide new insights for understanding how dysregulated signaling pathways hijack cell-type-specific transcriptional machinery to drive tumorigenesis and create therapeutic vulnerabilities in genetically defined tumors.

cancer biology↗

bioRxiv2022

STAT3 restricts prostate cancer metastasis and antiandrogen resistance by controlling LKB1/CREB signaling pathway

Prostate cancer (PCa) lethality is driven by its progression to a metastatic castration-resistant state, yet the signaling mechanisms underlying metastatic spread remain unknown. Here we show that STAT3 converges with the LKB1/mTORC1 and CREB to control metastatic disease in PCa mouse models. Unexpectedly, STAT3 was found to be upregulated in diabetic PCa patients undergoing metformin therapy with a concomitant reduction in mTORC1 expression. In preclinical mouse models of PCa, genetic ablation or activation of STAT3 had opposing effects on LKB1/AMPK/mTORC1- dependent tumorigenesis. Using genetic and pharmacological approaches, we identified LKB1 as a direct STAT3 target while repressing CREB. Furthermore, PCa patients with high CREB expression had inferior clinical outcome with significantly increased risk of disease and metastatic recurrence. We observe that castration state lowers STAT3 abundance and increases AR and CREB levels, leading to castration-resistant PCa (CRPC). Our findings revealed that STAT3 controls mTORC1 and CREB in metastatic disease, suggesting CREB as a promising target for lethal CRPC.

cancer biology↗

bioRxiv2022

vcferr: Development, Validation, and Application of a SNP Genotyping Error Simulation Framework

MotivationGenotyping error can impact downstream SNP-based analyses. Simulating various modes and and levels of error can help investigators better understand potential biases caused by miscalled genotypes. ResultsWe have developed and validated vcferr, a tool to probabilistically simulate genotyping error and missigness in VCF files. We demonstrate how vcferr could be used to address a research question by introducing varying levels of error of different type into a sample in a simulated pedigree, and assessed how kinship analysis degrades as a function of kind and type of error. Software Availabilityvcferr is available for installation via PyPi (https://pypi.org/project/vcferr/) or conda (https://anaconda.org/bioconda/vcferr). The software is released under the MIT license with source code available on GitHub (https://github.com/signaturescience/vcferr).

bioinformatics↗

bioRxiv2022

Environmental DNA sequencing data from algal blooms in Lake Erie using Oxford Nanopore MinION

Harmful Algal Blooms (HABs) pose a significant and increasing risk, both to human health and to the Blue Economy. Genomics approaches to early detection promise to help mitigate these risks. We have developed and prototyped HABSSED (HAB Surveillance by Sequencing of Environmental DNA), a portable, reliable, rapid, low-cost pipeline for detecting HABs in the field using 3rd generation sequencing with the Oxford Nanopore MinION device. We demonstrated the efficacy of our approach by sequencing existing samples collected from a National Oceanic and Atmospheric Administration (NOAA) Great Lakes Environmental Research Laboratory (GLERL) on Lake Erie. We sequenced environmental DNA (eDNA) from samples drawn before, during, and after a Microcystis bloom, and estimate the abundanced of HAB-associated taxa. While sequencing results showed some evidence of human and E. coli contamination, we find that the abundance of Mycrocystis and other HAB-associated orgnisms significantly differs between pre- and post-bloom environments. Here we describe the publicly available sequencing data that was generated as part of this research, which is available in the Sequence Read Archive (SRA) under accession number PRJNA812770.

genomics↗

bioRxiv2021

skater: An R package for SNP-based Kinship Analysis, Testing, and Evaluation

MotivationSNP-based kinship analysis with genome-wide relationship estimation and IBD segment analysis methods produces results that often require further downstream processing and manipulation. A dedicated software package that consistently and intuitively implements this analysis functionality is needed. ResultsHere we present the skater R package for SNP-based kinship analysis, testing, and evaluation with R. The skater package contains a suite of well-documented tools for importing, parsing, and analyzing pedigree data, performing relationship degree inference, benchmarking relationship degree classification, and summarizing IBD segment data. AvailabilityThe skater package is implemented as an R package and is released under the MIT license at https://github.com/signaturescience/skater. Documentation is available at https://signaturescience.github.io/skater.

bioinformatics↗

bioRxiv2021

The Evolutionary History of Wild, Domesticated, and Feral Brassica oleracea (Brassicaceae)

Understanding the evolutionary history of crops, including identifying wild relatives, helps to provide insight for designing new approaches in crop breeding efforts. Cultivated Brassica oleracea has intrigued researchers for centuries due to its wide diversity in forms, which include cabbage, broccoli, cauliflower, kale, kohlrabi, and Brussels sprouts. Yet, the evolutionary history of this species remains understudied. With such different vegetables produced from a single species, B. oleracea is a model organism for understanding the power of artificial selection. Persistent challenges in the study of B. oleracea include conflicting hypotheses regarding domestication and the identity of the closest living wild relative. Using a diversity panel of 224 accessions, which represents 14 different B. oleracea crop types and nine potential wild progenitor species, we integrate phylogenetic and population genetic techniques with ecological niche modeling, archaeological, and literary evidence to examine relationships among cultivars and wild relatives to clarify the origin of this horticulturally important species. Our analyses point to the Aegean endemic B. cretica as the closest living relative of cultivated B. oleracea, supporting an origin of cultivation in the Eastern Mediterranean region. Additionally, we identify several feral lineages, suggesting that cultivated plants of this species are able to revert to a wild-like state with relative ease. By expanding our understanding of the evolutionary history in B. oleracea, these results contribute to a growing body of knowledge on crop domestication that will facilitate continued breeding efforts including adaptation to changing environmental conditions.

evolutionary biology↗

bioRxiv2020

Subtractive CRISPR screen identifies factors involved in non-canonical LC3 lipidation.

Although commonly associated with autophagosomes, LC3 can also be recruited to membranes in a variety of non-canonical contexts. These include responses to ionophores such as the M2 proton channel of influenza A virus. LC3 is attached to membranes by covalent lipidation that depends on recruitment of the ATG5-12-16L1 complex. Non-canonical LC3 lipidation requires the C-terminal WD40 domain of ATG16L1 that is dispensable for canonical autophagy. We devised a subtractive CRISPR knock-out screening strategy to investigate the requirements for non-canonical LC3-lipidation. This correctly identified the enzyme complexes directly responsible for LC3-lipidation. We additionally identified the RALGAP complex as important for M2-induced, but not ionophore drug induced LC3 lipidation. In contrast, we identified ATG4D as responsible for LC3 recycling in M2-induced and basal LC3-lipidation. Identification of a vacuolar ATPase subunit in the screen suggested a common mechanism for non-canonical LC3 recruitment. Influenza-induced and ionophore drug induced LC3-lipidation leads to association of the vacuolar ATPase and ATG16L1 and can be antagonised by Salmonella SopF. LC3 recruitment to erroneously neutral compartments may therefore represent a response to damage caused by diverse invasive pathogens.

cell biology↗

bioRxiv2019

Thyroid and androgen receptor signaling are antagonized by CRYM in prostate cancer

Androgen deprivation therapy (ADT) remains a key approach in the treatment of prostate cancer (PCa). However, PCa inevitably relapses and becomes ADT resistant. Besides androgens, there is evidence that thyroid hormone thyroxine (T4) and its active form 3,5,3-triiodo-L-thyronine (T3) are involved in the progression of PCa. Epidemiologic evidence indicates a higher incidence of PCa in men with elevated thyroid hormone levels. The thyroid hormone binding protein -Crystallin (CRYM) mediates intracellular thyroid hormone action by sequestering T3 and blocks its binding to cognate receptors (TRa/TRb) in target tissues. We show in this study that low CRYM expression levels in PCa patient samples are associated with early BCR and poor prognosis. Moreover, we found a disease stage-specific expression of CRYM in PCa. CRYM counteracted thyroid and androgen signaling and blocked intracellular choline uptake. CRYM inversely correlated with [18F]fluoromethylcholine (FMC) levels in PET/MRI imaging of PCa patients. Our data suggest CRYM as a novel antagonist of T3 and androgen-mediated signalling. The role of CRYM could therefore be an essential control mechanism for the prevention of aggressive PCa growth. HighlightsO_LIThyroid and androgen hormone driven pathways in prostate cancer (PCa) are antagonized by - Crystallin (CRYM). C_LIO_LI[18F]fluoromethylcholine uptake and prognostic values in PCa correlate with CRYM protein levels. C_LIO_LIReduced CRYM expression predicts early biochemical recurrence (BCR) in PCa patients. C_LI

cancer biology↗