Biology subjects

Mason, C.

Publications and source records attributed to Mason, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

Sunflower yield modeling with XAI: Historical weather impacts and forecasting

This study applies explainable artificial intelligence (XAI) to analyze the impact of inter-year variation in weather conditions on oilseed sunflower yields across the United States. By integrating historical yield data from 1976 to 2022 with meteorological data, we identified key weather predictors influencing sunflower yields at national and state levels along with critical yield-sensitive threshold temperature and precipitation values that predict reduced yield. Using machine learning algorithms, we developed predictive models to forecast future yields under different Shared Socioeconomic Pathways (SSPs) from 2021 to 2080. Our findings reveal significant yield declines due to increased temperatures and altered precipitation patterns, but with regional variability in the magnitude of these impacts. The most critical climate variables identified include maximum temperatures and total precipitation during summer months. Our XAI approach enhances model transparency, offering valuable insights for farmers and policymakers to develop adaptive strategies for sunflower cultivation under climate change. Future research incorporating additional factors like soil characteristics and agricultural practices can further refine yield predictions.

plant biology↗

bioRxiv2024

A benchmarking study of copy number variation inference methods using single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has emerged as a powerful tool for cancer research, enabling in-depth characterization of tumor heterogeneity at the single-cell level. Recently, scRNA-seq copy number variation (scCNV) inference methods have been developed, expanding the application of scRNA-seq to study genetic heterogeneity in cancer using transcriptomic data. However, the fidelity of these methods has not been investigated systematically. In this study, we benchmarked five commonly used scCNV inference methods, HoneyBADGER, CopyKAT, CaSpER, inferCNV, and sciCNV. We evaluated their performance across four different scRNA-seq platforms derived data from a multicenter study. We further evaluated the scCNV performance using scRNA-seq datasets derived from mixed samples consisting of five human lung adenocarcinoma cell lines and generated a clinical scRNA-seq dataset from a human small cell lung cancer patient to validate our findings. Our evaluation criteria included sensitivity and specificity of CNV detection, and subclone identification from mixed cancer samples. We found that the sensitivity and specificity of the five scCNV inference methods varied, depending on the selection of reference data, sequencing depths, and read lengths. Overall, CopyKAT and CaSpER exhibited superior performance to other methods, while inferCNV, sciCNV, and CopyKAT outperformed other methods in subclone identification accuracy. Remarkably, inferCNV achieved high accuracy in subclone identification when using data from a "single scRNA-seq protocol", however, when applying these methods to a dataset derived from multiple scRNA-seq platforms from the mixed samples, we found that batch effects significantly affected the performance of subclone identification for most methods, except for HoneyBADGER. Our benchmarking study revealed the strengths and weaknesses of each of the five scCNV inference methods and provided guidance for selecting the optimal CNV inference method using scRNA-seq data.

bioinformatics↗

bioRxiv2023

Preclinical lentiviral vector-mediated hematopoietic stem and progenitor cell gene therapy corrects Pompe disease-related muscle and neurological manifestations

Pompe disease, a rare genetic neuromuscular disorder, is caused by a deficiency of acid alpha-glucosidase (GAA), leading to the accumulation of glycogen in lysosomes and the progressive development of muscle weakness. The current standard treatment, enzyme replacement therapy (ERT), is not curative and demonstrates poor penetration into skeletal muscle and the central and peripheral nervous systems, susceptibility to immune responses against the recombinant enzyme, and the need for high doses and frequent infusions. To overcome these limitations, lentiviral vector-mediated hematopoietic stem and progenitor cell (HSPC) gene therapy has been proposed as a next-generation approach for treating Pompe disease. This study demonstrates the potential of lentiviral HSPC gene therapy to reverse the pathological effects of Pompe disease in a preclinical mouse model. It includes a comprehensive safety assessment via integration site analysis, along with single-cell RNA sequencing analysis of CNS samples to gain insights into the underlying mechanisms of phenotype correction. One Sentence Summary: Preclinical hematopoietic stem cell gene therapy for the treatment of Pompe disease.

neuroscience↗

bioRxiv2023

A novel method for quantitation of AAV genome integrity and residual DNAs using duplex digital PCR

Recombinant adeno-associated virus (rAAV) vectors have become a reliable strategy for delivering gene therapies. As rAAV capsid content is known to be heterogeneous, assays for rAAV characterization are critical for assessing the efficacy and safety of drug products. Multiplex droplet digital PCR (ddPCR) has emerged as a popular molecular approach for characterizing capsid content due to its high level of throughput, accuracy, and replicability. Despite growing popularity, tools to accurately analyze multiplexed data are scarce. Here, we introduce a novel model to estimate genome integrity from duplex ddPCR assays. This work demonstrates that use of a Poisson-multinomial mixture distribution significantly improves the accuracy and quantifiable range of duplex ddPCR assays over currently available models.

molecular biology↗

bioRxiv2023

A modular metagenomics analysis system for integrated multi-step data exploration

MotivationComputational analysis of large-scale metagenomics sequencing datasets have proven to be both incredibly valuable for extracting isolate-level taxonomic, and functional insights from complex microbial communities. However, due to an ever-expanding ecosystem of metagenomics-specific methods and file-formats, designing seamless and scalable end-to-end workflows, and exploring the massive amounts of output data have become studies unto themselves. One-click bioinformatics pipelines have helped to organize these tools into targeted workflows, but they suffer from general compatibility and maintainability issues, and preclude replication. MethodsTo address the gap in easily extensible yet robustly distributable metagenomics workflows, we have developed a module-based metagenomics analysis system "Core Analysis Modular Pipeline" (CAMP), written in Snakemake, a popular workflow management system, along with a standardized module and working directory architecture. Each module can be run independently or conjointly with a series of others to produce the target data format (e.g. short-read preprocessing alone, or short-read preprocessing followed by de novo assembly), and outputs aggregated summary statistics reports and semi-guided Jupyter notebook-based visualizations. ResultsWe have applied CAMP to a set of ten metagenomics samples to demonstrate how a modular analysis system with built-in data visualization at intermediate steps facilitates rich and seamless inter-communication between output data from different analytic purposes. AvailabilityThe CAMP ecosystem (module template and analysis modules) can be found https://github.com/Meta-CAMP.

bioinformatics↗

bioRxiv2022

Supervised Machine Learning Enables Geospatial Microbial Provenance

The recent increase in publicly available metagenomic datasets with geospatial metadata has made it possible to determine location-specific, microbial fingerprints from around the world. Such fingerprints can be useful for comparing microbial niches for environmental research, as well as for applications within forensic science and public health. To determine the regional specificity for environmental metagenomes, we examined 4305 shotgun-sequenced samples from the MetaSUB Consortium dataset - the most extensive public collection of urban microbiomes, spanning 60 different cities, 30 countries, and 6 continents. We were able to identify city-specific microbial fingerprints using supervised machine learning (SML) on the taxonomic classifications, and we also compared the performance of ten SML classifiers. We then further evaluated the five algorithms with the highest accuracy, with the city and continental accuracy ranging from 85-89% to 90-94%, respectively. We then used these results to develop Cassandra, a random-forest-based classifier that identifies indicator species to aid in fingerprinting and can infer higher-order microbial interactions at each site. We further tested the Cassandra algorithm on the Tara Oceans dataset, the largest collection of marine-based microbial genomes, where it classified the oceanic sample locations with 83% accuracy. These results and code show the utility of SML methods and Cassandra to identify bioindicator species across both oceanic and urban environments, which can help guide ongoing efforts in biotracing, environmental monitoring, and microbial forensics (MF).

microbiology↗

bioRxiv2022

Hypoxic memory of tumor intrinsic type I interferon suppression promotes breast cancer metastasis

Hypoxia is a common feature of many solid tumors due to aberrant proliferation and angiogenesis and has been associated with tumor progression and metastasis. Most of the well-known hypoxia effects are mediated through hypoxia-inducible factors (HIFs), but the long-lasting effect of hypoxia beyond the immediate HIF regulation remains less understood. Here we show that hypoxia exerts a prolonged effect to promote metastasis. Using breast cancer patient-derived circulating tumor cell (CTC) lines and common breast cancer cell lines, we found that hypoxia downregulates tumor intrinsic type I interferon (IFN) signaling and its downstream antigen presentation (AP) machinery in luminal breast cancer cells, via both HIF-dependent and HIF-independent mechanisms. Hypoxia induced IFN/AP suppression can last longer than the hypoxic exposure, presenting a "hypoxic memory" phenotype. Hypoxic memory of IFN/AP downregulation is established by specific hypoxic priming, and cells with hypoxic memory have an enhanced ability for tumorigenesis and metastasis. The histone deacetylase inhibitor (HDACi) Entinostat can erase the hypoxic memory and improve the immune clearance of tumor cells when combined with checkpoint immunotherapies in a syngeneic breast cancer mouse model. These results point to a novel mechanism for hypoxia facilitated tumor progression, through a long-lasting memory that provides advantages for CTCs during the metastatic cascade. Significance: We revealed a novel hypoxic memory of prolonged suppression of tumor intrinsic type I IFN and AP signals that promote tumorigenesis and metastasis, suggesting novel mechanistic understanding of the immune evasive properties of CTCs.

cancer biology↗

bioRxiv2022

Targeted Down Regulation Of Core Mitochondrial Genes During SARS-CoV-2 Infection

Defects in mitochondrial oxidative phosphorylation (OXPHOS) have been reported in COVID-19 patients, but the timing and organs affected vary among reports. Here, we reveal the dynamics of COVID-19 through transcription profiles in nasopharyngeal and autopsy samples from patients and infected rodent models. While mitochondrial bioenergetics is repressed in the viral nasopharyngeal portal of entry, it is up regulated in autopsy lung tissues from deceased patients. In most disease stages and organs, discrete OXPHOS functions are blocked by the virus, and this is countered by the host broadly up regulating unblocked OXPHOS functions. No such rebound is seen in autopsy heart, results in severe repression of genes across all OXPHOS modules. Hence, targeted enhancement of mitochondrial gene expression may mitigate the pathogenesis of COVID-19. One-Sentence SummaryCovid-19 is associated with targeted inhibition of mitochondrial gene transcription.

molecular biology↗

bioRxiv2022

Cross-kingdom metagenomic profiling of Lake Hillier reveals pigment-rich polyextremophiles and wide-ranging metabolic adaptations

Background Lake Hillier is a hypersaline lake known for its distinctive bright pink color. The cause of this phenomenon in other hypersaline sites has been attributed to halophiles, Dunaliella, and Salinibacter, however, a systematic analysis of the microbial communities, their functional features, and the prevalence of pigment-producing-metabolisms has not been previously studied. Our results are evidence that Lake Hillier is composed of a diverse set of microorganisms including archaea, bacteria, algae, and viruses. Our data indicate a core microbiome in Lake Hillier composed of multiple pigment-producer microbes, many of which are cataloged as polyextremophiles. Additionally, we estimated the diversity of metabolic pathways in the lake and determined that many of these are related to pigment production. We reconstructed complete or partial genomes for 21 discrete bacteria (N = 14) and archaea (N = 7), only 2 of which could be taxonomically annotated to previously observed species. Our findings provide the first metagenomic study to decipher the source of the pink color of Australias Lake Hillier. The study of this pink hypersaline environment is evidence of a microbial consortium of pigment producers, a repertoire of polyextremophiles, a core microbiome and potentially novel species.

microbiology↗

bioRxiv2021

Screening of Chimeric GAA Variants in a Preclinical Study of Pompe Disease Results in Candidate Vector for Hematopoietic Stem Cell Gene Therapy

Pompe disease is a rare genetic neuromuscular disorder caused by acid alpha-glucosidase (GAA) deficiency resulting in lysosomal glycogen accumulation and progressive myopathy. Enzyme replacement therapy (ERT) is the current standard of care, which prolongs the quality of life for Pompe patients. However, ERT has limitations due to lack of enzyme penetration into the central nervous system (CNS) and skeletal muscles, immunogenicity against the recombinant enzyme, and requires life-long biweekly infusions. In a preclinical mouse model, a clinically relevant promoter to drive lentiviral vector-mediated expression of engineered GAA in autologous hematopoietic stem and progenitor cells (HSPC) was tested with nine unique human chimeric GAA coding sequences incorporating distinct peptide tags and codon-optimization iterations. Vectors including glycosylation independent lysosomal targeting (GILT) tags resulted in effective GAA enzyme delivery into key disease tissues with enhanced reduction of glycogen, myofiber and CNS vacuolation, compared to non-tagged GAA in Gaa knockout mice, a model of Pompe disease. Genetically modified microglial cells in brains were detected at low levels, but provided robust correction. Furthermore, an aminoacid substitution in the tag added to reduced capacity to induce insulin signaling and there was no evidence of off-target effects. This study demonstrated the therapeutic potential of lentiviral HSPC gene therapy exploiting optimized GAA tagged coding sequences to reverse Pompe disease pathology in a preclinical mouse model providing a promising vector candidate for further investigation. One Sentence SummaryA candidate vector for hematopoietic stem cell gene therapy of Pompe disease.

bioengineering↗

bioRxiv2021

A wipe-based stool collection and preservation kit for microbiome community profiling

While a range of methods for stool collection exist, many require complicated, self-directed protocols and stool transfer. In this study, we introduce and validate a novel, wipe-based approach to fecal sample collection and stabilization for metagenomics analysis. A total of 72 samples were collected across four different preservation types: freezing at -20{degrees}C, room temperature storage, a commercial DNA preservation kit, and DESS (dimethyl sulfoxide, ethylenediaminetetraacetic acid, sodium chloride) solution. These samples were sequenced and analyzed for taxonomic abundance metrics, metabolic pathway classification, and diversity analysis. Overall, the DESS wipe results validated the use of a wipe-based capture method to collect stool samples for microbiome analysis, showing an R2 of 0.96 for species across all kingdoms, as well as exhibiting a maintenance of Shannon diversity (3.1-3.3) and species richness (151-159) compared to frozen samples. Moreover, DESS showed comparable performance to the commercially available preservation kit (R2 of 0.98), and samples consistently clustered by subject across each method. Future studies will be needed to further explore sample processing options and their applications in non-healthy subjects, particularly patients with irritable bowel syndrome, inflammatory bowel disease, and colorectal cancer, but these data suggest the DESS wipe method can be used for stable, room temperature collection and transport of human stool specimens.

microbiology↗

bioRxiv2021

A metagenomic DNA sequencing assay that is robust against environmental DNA contamination

Metagenomic DNA sequencing is a powerful tool to characterize microbial communities but is sensitive to environmental DNA contamination, in particular when applied to samples with low microbial biomass. Here, we present contamination-free metagenomic DNA sequencing (Coffee-seq), a metagenomic sequencing assay that is robust against environmental contamination. The core idea of Coffee-seq is to tag the DNA in the sample prior to DNA isolation and library preparation with a label that can be recorded by DNA sequencing. Any contaminating DNA that is introduced in the sample after tagging can then be bioinformatically identified and removed. We applied Coffee-seq to screen for infections from microorganisms with low burden in blood and urine, to identify COVID-19 co-infection, to characterize the urinary microbiome, and to identify microbial DNA signatures of inflammatory bowel disease in blood.

genomics↗

bioRxiv2021

Genetically engineered microglia-like cells have therapeutic potential for neurodegenerative disease

Hematopoietic stem/progenitor cell gene therapy (HSPC-GT) results in the engraftment of genetically modified microglia-like cells (MLCs) in the brain. While HSPC-GT has shown a clear neurological benefit in the clinic for specific rare diseases, the nature of MLC engraftment in the brain and the functional characteristics of MLCs remain contentious. Here we comprehensively characterized how different routes of administration affect the engraftment and biodistribution of genetically engineered HSPC-derivatives in mice. Using high-throughput single-cell profiling, we show that MLCs bear a transcriptional signature similar to resident microglia rather than invading macrophages. However, MLCs could clearly be distinguished from resident microglia by expression of a specific set of genes. Finally, in murine models of Parkinsons disease and frontotemporal dementia, we demonstrate that MLCs can provide therapeutically relevant levels of protein to the brain, thereby potentially opening avenues of HSPC-GT to address the underlying disease etiology of these and other similar disorders.

neuroscience↗

bioRxiv2021

Systems Biology Analysis of Human Genomes Points to Key Pathways Conferring Spina Bifida Risk

Spina bifida (SB) is a debilitating birth defect caused by multiple gene and environment interactions. Though SB shows non-Mendelian inheritance, genetic factors contribute to an estimated 70% of cases. Nevertheless, identifying human mutations conferring SB risk is challenging due to its relative rarity, genetic heterogeneity, incomplete penetrance and environmental influences that hamper GWAS approaches to untargeted discovery. Thus, SB genetic studies may suffer from population substructure and/or selection bias introduced by typical candidate gene searches. We report a population based, ancestry-matched whole-genome sequence analysis of SB genetic predisposition using a systems biology strategy to interrogate 298 case-control subject genomes (149 pairs). Genes that were enriched in likely gene disrupting (LGD), rare protein-coding variants were subjected to machine learning analysis to identify genes in which LGD variants occur with a different frequency in cases vs. controls and so discriminate between these groups. Those genes with high discriminatory potential for SB significantly enriched pathways pertaining to carbon metabolism, inflammation, innate immunity, cytoskeletal regulation and essential transcriptional regulation, indicating their impact on the pathogenesis of human SB. Additionally, interrogation of conserved non-coding sequences identified robust variant enrichment in regulatory regions of several transcription factors critical to embryonic development. This genome-wide perspective offers an effective approach to interrogation of coding and non-coding sequence variant contributions to rare complex genetic disorders.

genomics↗

bioRxiv2021

Betacoronavirus-specific alternate splicing

Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection as well as datasets from the betacoronaviruses SARS-CoV and MERS as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification and a smaller number of exons than differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by DAS and DGE in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS, potentially modifying a broad range of cellular functions and affecting a diverse set of genes and biological functions.

genomics↗

bioRxiv2021

Tools for efficient analysis of neurons in a 3D reference atlas of whole mouse spinal cord

Spinal neurons are highly heterogeneous in location, transcriptional identity and function. To understand their contributions to sensorimotor circuits, it is essential to map the positions of identified subsets of neurons in relation to others throughout the spinal cord (SC), but we lack tools for whole SC sample preparation, imaging and in toto analysis. To overcome this problem, we have (1) designed scaffolds (SpineRacks) that facilitate efficient and ordered cryo-sectioning of the entire SC in a single block, (2) constructed a 3D reference atlas of adult mouse SC and (3) developed software (SpinalJ) to register images of sections and for standardized analysis of cells and projections in atlas space. We have verified mapping accuracies for known neurons and demonstrated the usefulness of this platform to reveal unknown neuronal distributions. Together, these tools provide high-throughput analyses of whole mouse SC and enable direct comparison of 3D spatial information between animals and studies.

neuroscience↗

bioRxiv2021

DNA methylation calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation

BackgroundNanopore long-read sequencing technology greatly expands the capacity of long-range single-molecule DNA-modification detection. A growing number of analytical tools have been actively developed to detect DNA methylation from Nanopore sequencing reads. Here, we examine the performance of different methylation calling tools to provide a systematic evaluation to guide practitioners for human epigenome-wide research. ResultsWe compare five analytic frameworks for detecting DNA modification from Nanopore long-read sequencing data. We evaluate the association between genomic context, CpG methylation-detection accuracy, CpG sites coverage, and running time using Nanopore sequencing data from natural human DNA. Furthermore, we provide an online DNA methylation database (https://nanome.jax.org) with which to display genomic regions that exhibit differences in DNA-modification detection power among different methylation calling algorithms for nanopore sequencing data. ConclusionsOur study is the first benchmark of computational methods for mammalian whole genome DNA-modification detection in Nanopore sequencing. We provide a broad foundation for cross-platform standardization, and an evaluation of analytical tools designed for genome-scale modified-base detection using Nanopore sequencing.

bioinformatics↗

bioRxiv2021

Whole Genome and Exome Sequencing Reference Datasets from A Multi-center and Cross-platform Benchmark Study

With the rapid advancement of sequencing technologies in the past decade, next generation sequencing (NGS) analysis has been widely applied in cancer genomics research. More recently, NGS has been adopted in clinical oncology to advance personalized medicine. Clinical applications of precision oncology require accurate tests that can distinguish tumor-specific mutations from errors or artifacts introduced during NGS processes or data analysis. Therefore, there is an urgent need to develop best practices in cancer mutation detection using NGS and the need for standard reference data sets for systematically benchmarking sequencing platforms, library protocols, bioinformatics pipelines and for measuring accuracy and reproducibility across platforms and methods. Within the SEQC2 consortium context, we established paired tumor-normal reference samples, a human triple-negative breast cancer cell line and a matched normal cell line derived from B lymphocytes. We generated whole-genome (WGS) and whole-exome sequencing (WES) data using 16 NGS library preparation protocols, seven sequencing platforms at six different centers. We systematically interrogated somatic mutations in the paired reference samples to identify factors affecting detection reproducibility and accuracy in cancer genomes. These large cross-platform/site WGS and WES datasets using well-characterized reference samples will represent a powerful resource for benchmarking NGS technologies, bioinformatics pipelines, and for the cancer genomics studies.

bioinformatics↗