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Hughes, J.

Publications and source records attributed to Hughes, J..

At least 37 records · Page 2Linked to original sources

An oviduct glycan increases sperm lifespan by diminishing ubiquinone and production of reactive oxygen species

Sperm storage by females after mating for species-dependent periods is used widely among animals with internal fertilization to allow asynchrony between mating and ovulation. Many mammals store sperm in the lower oviduct where specific glycans on epithelial cells retain sperm to form a reservoir. Binding to oviduct cells suppresses sperm intracellular Ca2+ and increases sperm longevity. We investigated the mechanisms by which a specific oviduct glycan, 3-O-sulfated Lewis X trisaccharide (suLeX), prolongs the lifespan of porcine sperm. Using targeted metabolomics, we report that binding to suLeX diminishes the abundance of the precursor to ubiquinone and suppresses formation of fumarate, a specific citric acid cycle component, diminishing the activity of the electron transport chain and reducing the production of harmful reactive oxygen species (ROS). The enhanced sperm lifespan in the oviduct may be due to suppressed ROS production as many reports have demonstrated toxic effects of high ROS concentrations on sperm.

cell biology↗

The OSUMMER lines: a series of ultraviolet-accelerated NRAS-mutant mouse melanoma cell lines syngeneic to C57BL/6

An increasing number of cancer subtypes are treated with front-line immunotherapy. However, approaches to overcome primary and acquired resistance remain limited. Pre-clinical mouse models are often used to investigate resistance mechanisms, novel drug combinations, and delivery methods; yet most of these models lack the genetic diversity and mutational patterns observed in human tumors. Here we describe a series of thirteen C57BL/6J melanoma cell lines to address this gap in the field. The Ohio State University-Moffitt Melanoma Exposed to Radiation (OSUMMER) cell lines are derived from mice expressing endogenous, melanocyte-specific, and clinically relevant Nras driver mutations (Q61R, Q61K, or Q61L). Exposure of these animals to a single, non-burning dose of ultraviolet B accelerates the onset of spontaneous melanomas with mutational patterns akin to human disease. Furthermore, in vivo irradiation selects against potent tumor antigens, which could prevent the outgrowth of syngeneic cell transfers. Each OSUMMER cell line possesses distinct in vitro growth properties, trametinib sensitivity, mutational signatures, and predicted antigenicity. Analysis of OSUMMER allografts shows a correlation between strong, predicted antigenicity and poor tumor outgrowth. These data suggest that the OSUMMER lines will be a valuable tool for modeling the heterogeneous responses of human melanomas to targeted and immune-based therapies. SIGNIFICANCENRAS-activating mutations are the second most common genetic driver event in cutaneous melanoma, occurring in 15% to 25% of cases. With few therapeutic options beyond immunotherapy, patients with NRAS-mutant melanoma have a poorer prognosis. Pre-clinical mouse models that mimic the high mutational burden of human NRAS-mutant melanomas are lacking in the field. Here, we describe a series of NRAS-mutant melanoma cell lines, derived from ultraviolet (UV)-induced, spontaneous tumors. These lines permit the study of targeted, NRAS mutant-specific, immune, and combination therapies in C57BL/6J mice. With the release of this resource, we hope to catalyze new therapeutic approaches for NRAS-mutant melanoma.

cancer biology↗

SOS1 and KSR1 modulate MEK inhibitor responsiveness to target resistant cell populations based on PI3K and KRAS mutation status

KRAS is the most commonly mutated oncogene. Targeted therapies have been developed against mediators of key downstream signaling pathways, predominantly components of the RAF/MEK/ERK kinase cascade. Unfortunately, single-agent efficacy of these agents is limited both by intrinsic and acquired resistance. Survival of drug-tolerant persister cells (DTPs) within the heterogeneous tumor population and/or acquired mutations that reactivate receptor tyrosine kinase (RTK)/RAS signaling can lead to outgrowth of tumor initiating cells (TICs) and drive therapeutic resistance. Here, we show that targeting the key RTK/RAS pathway signaling intermediates SOS1 or KSR1 both enhances the efficacy of, and prevents resistance to, the MEK inhibitor trametinib in KRAS-mutated lung (LUAD) and colorectal (COAD) adenocarcinoma cell lines depending on the specific mutational landscape. The SOS1 inhibitor BI-3406 enhanced the efficacy of trametinib and prevented trametinib resistance by targeting spheroid initiating cells (SICs) in KRASG12/G13-mutated LUAD and COAD cell lines that lacked PIK3CA co-mutations. Cell lines with KRASQ61 and/or PIK3CA mutations were insensitive to trametinib and BI-3406 combination therapy. In contrast, deletion of the RAF/MEK/ERK scaffold protein KSR1 prevented drug-induced SIC upregulation and restored trametinib sensitivity across all tested KRAS mutant cell lines in both PIK3CA- mutated and PIK3CA wildtype cancers. Our findings demonstrate that vertical inhibition of RTK/RAS signaling is an effective strategy to prevent therapeutic resistance in KRAS- mutated cancers, but therapeutic efficacy is dependent on both the specific KRAS mutant and underlying co-mutations. Thus, selection of optimal therapeutic combinations in KRAS-mutated cancers will require a detailed understanding of functional dependencies imposed by allele-specific KRAS mutations. Significance StatementWe provide an experimental framework for evaluating both adaptive and acquired resistance to RAS pathway-targeted therapies and demonstrate how targeting specific RAS pathway signaling intermediates SOS1 or KSR1 enhanced effectiveness of and prevented resistance to MEK inhibitors in KRAS-mutated cancer cells with genotypic precision. The contribution of either effector was dependent upon the mutational landscape: SOS1 inhibition synergized with trametinib in KRASG12/G13-mutated cells expressing WT PI3K but not in KRASQ61-mutated cells or if PIK3CA is mutated. KSR1 deletion inhibited MEK/ERK complex stability and was effective in cells that are unresponsive to SOS1 inhibition. These data demonstrate how a detailed understanding of functional dependencies imposed both by allele specific KRAS mutations and specific co-mutations facilitates the optimization of therapeutic combinations.

cancer biology↗

The SARS-CoV-2 Spike Protein Mutation Explorer: Using an Interactive Application to Improve the Public Understanding of SARS-CoV-2 Variants of Concern

SARS-CoV-2 is the virus responsible for the COVID-19 pandemic, which began in late 2019 and has resulted in millions of death globally. The need to understand the pandemic means that detailed descriptions of features of this virus are now of interest to non-expert audiences. In particular, there has been much public interest in the spike protein that protrudes from the surface of the SARS-CoV-2 virus particle. The spike is the major determinant of viral infectivity and the main target for protective immune responses, and included in vaccines, and so its properties influence the impact of the pandemic on peoples lives. This protein is rapidly evolving, with mutations that enhance transmissibility or weaken vaccine protection creating new variants of concern (VOCs) and associated sub-lineages. The spread of SARS-CoV-2 VOCs has been tracked by groups such as the COVID-19 Genomics UK consortium (COG-UK). Their online mutation explorer (COG-UK/ME), which analyses and shares SARS-CoV-2 sequence data, contains information about VOCs that is designed primarily for an expert audience but is potentially of general interest during a pandemic. We wished to make this detailed information about SARS-CoV-2 VOCs more widely accessible. Previously work has shown that visualisations and interactivity can facilitate active learning and boost engagement with molecular biology topics, while animations of these topics can boost understanding on protein structure, function, and dynamics. We therefore set out to develop an educational graphical resource, the SARS-CoV-2 Spike Protein Mutation Explorer (SSPME), which contains interactive 3D molecular models and animations explaining SARS-CoV-2 spike protein variants and VOCs. We performed user-testing of the original COG-UK/ME website and of the SSPME, using a within-groups design to measure knowledge acquisition and a between-groups design to contrast the effectiveness and usability. Statistical analysis demonstrated that, when compared to the COG-UK/ME, the SSPME had higher usability and significantly improved participant knowledge confidence and knowledge acquisition. The SSPME therefore provides an example of how 3D interactive visualisations can be used for effective science communication and education on complex biomedical topics, as well as being a resource to improve the public understanding of SARS-CoV-2 VOCs.

molecular biology↗

The Ecosystem Integrity Index: a novel measure of terrestrial ecosystem integrity with global coverage

While the importance of ecosystem integrity has long been recognised (Leopold, 1949), conservation science has tended to focus on measuring and monitoring species and habitats, avoiding the complexities of working at the ecosystem level. Ecosystems are highly dynamic, defined by both living and non-living components as well as their interactions (CBD, 1992), making it difficult to assess baseline levels of integrity. We present a novel index that represents the integrity of all terrestrial ecosystems globally at 1km2 resolution: the Ecosystem Integrity Index (EII). The index provides a simple, yet scientifically robust, way of measuring, monitoring and reporting on ecosystem integrity. It is formed of three components; structural, compositional and functional integrity, and measured against a natural (current potential) baseline on a scale of 0 to 1. We find that ecosystem integrity is severely impacted in terrestrial areas across the globe with approximately one fifth of all ecosystems and one quarter of all ecoregions having lost, on average, over half of their ecosystem integrity. At a national scale, we estimate similar challenges with 115 nations or territories having lost, on average, over half of their ecosystem integrity. This presents a significant threat for humanity as such levels of degradation are likely to be linked to substantial declines in the ecosystem services on which humanity is reliant. The EII has been developed principally to help national governments measure and report on Goal A of the Kunming-Montreal Global Biodiversity Framework (GBF) (CBD, 2022a), for which it has been listed as a Component Indicator. The EII will also be useful in helping non-state actors measure and report their contributions to the GBF and is listed as an indicator by both the Taskforce for Nature-Related Financial Disclosures (TNFD) (TNFD, 2023) and the Science Based Targets Network (SBTN) (SBTN, 2023). The EII aims to enable these actors to make informed decisions on the conservation, restoration and sustainable use of ecosystems for which they are wholly or partly responsible. We propose that with sufficient effort, ecosystem integrity can be restored and contribute towards the GBFs vision of living in harmony with nature, resulting in the safeguarding of the ecosystem services on which humanity depends.

ecology↗

High-resolution characterisation of short-term temporal variability in the taxonomic and resistome composition of wastewater influent

Wastewater-based epidemiology (WBE) for population-level surveillance of antimicrobial resistance (AMR) is gaining significant traction, but the impact of wastewater sampling methods on results is unclear. In this study we characterised taxonomic and resistome differences between single-timepoint-grab and 24H-composites of wastewater influent from a large UK-based wastewater treatment work (WWTW [population equivalent:223,435]). We autosampled hourly influent grab samples (n=72) over three consecutive weekdays, and prepared additional 24H-composites (n=3) from respective grabs. For taxonomic profiling, metagenomic DNA was extracted from all samples and 16S-rRNA gene sequenced. One composite and six grabs from day one underwent metagenomic sequencing for metagenomic dissimilarity estimation and resistome profiling. Taxonomic abundances of phyla varied significantly across hourly grab samples but followed a repeating diurnal pattern for all three days. Hierarchical clustering grouped grab samples into four time periods dissimilar in both 16S rRNA gene-based profiles and metagenomic distances. 24H-composites resembled mean daily phyla abundances and showed low variability of taxonomic profiles. Of the 122 AMR gene families (AGFs) identified across all day one samples, single grab samples identified a median of 6 (IQR:5-8) AGFs not seen in the composite. However, 36/36 of these hits were at lateral coverage <0.5 (median:0.19; IQR:0.16-0.22) and potential false positives. Conversely, the 24H-composite identified three AGFs not seen in any grab with higher lateral coverage (0.82; 0.55-0.84). Additionally, several clinically significant human AGFs (blaVIM, blaIMP, blaKPC) were intermittently or completely missed by grab sampling but captured by the 24H-composite. Wastewater influent undergoes significant taxonomic and resistome changes on short timescales potentially affecting interpretation of results based on sampling strategy. Grab samples are more convenient and potentially capture low-prevalence/transient targets but are less comprehensive and temporally variable. Therefore, we recommend 24H-composite sampling where feasible. Further validation and optimisation of WBE methods is vital for its development into a robust AMR surveillance approach. HighlightsO_LIInfluent undergoes significant taxonomic/resistome changes over short timescales. C_LIO_LITaxonomic abundances fluctuate diurnally but repeat for the 3 weekdays sampled. C_LIO_LIDetection of less prevalent AMR determinants is time-dependent for grab sampling. C_LIO_LISingle timepoint grab samples may produce temporally variable metagenomic profiles. C_LIO_LI24H-composites reflect mean daily taxa and more reliably captured AMR determinants. C_LI

genomics↗

Zoonotic avian influenza viruses evade human BTN3A3 restriction

Cross-species transmission of avian influenza A viruses (IAVs) into humans could represent the first step of a future pandemic1. Multiple factors limiting the spillover and adaptation of avian IAVs in humans have been identified, but they are not sufficient to explain which virus lineages are more likely to cross the species barrier1,2. Here, we identified human BTN3A33 (butyrophilin subfamily 3 member A3) as a potent inhibitor of avian but not human IAVs. We determined that BTN3A3 is constitutively expressed in human airways and its antiviral activity evolved in primates. We show that BTN3A3 restriction acts at the early stages of virus replication by inhibiting avian IAV vRNA transcription. We identified residue 313 in the viral nucleoprotein (NP) as the genetic determinant of BTN3A3 sensitivity (313F, or rarely 313L in avian viruses) or evasion (313Y or 313V in human viruses). However, several serotypes of avian IAVs that spilled over into humans in recent decades evade BTN3A3 restriction. In these cases, BTN3A3 evasion is due to substitutions (N, H or Q) in NP residue 52 that is adjacent to residue 313 in the NP structure4. Importantly, we identified more than 150 avian IAV lineages with a BTN3A3-resistant genotype. In conclusion, sensitivity or resistance to BTN3A3 is another factor to consider in the risk assessment of the zoonotic potential of avian influenza viruses.

microbiology↗

Existing caribou habitat and demographic models are poorly suited for Ring of Fire impact assessment: A roadmap for improving the usefulness, transparency, and availability of models for conservation

Decision making in conservation science often relies on the best available information. This may include using models that were not designed for purpose and are not accompanied by an assessment of limitations. To begin addressing these issues, we sought to reproduce, and evaluate the suitability of, the best available models for predicting impacts of proposed mining on boreal woodland caribou (Rangifer tarandus caribou) resource selection and demography in northern Ontario. We then evaluated their suitability for projecting the impacts of development in the Ring of Fire region. To aid in accessibility, we developed an R package for data preparation, analyses of resource selection, and demographic parameters. We found existing models were either ill suited, or lacking, for ongoing regional planning. The specificity of the regional resource selection model limited its usefulness for predicting impacts of development, and the high variability across caribou ranges limited the usefulness of a national aspatial demographic model for predicting range-specific impacts. Variability in model coefficients across caribou ranges suggests selection responses vary with habitat availability (i.e. a functional response) while demographic responses continue to decline with increasing disturbance. Models designed for forecasting that are continuously updated by range-specific demographic and habitat information, are required to better inform conservation decisions and ongoing policy and planning practices in the Ring of Fire region.

ecology↗

Evaluation of metagenomic, 16S rRNA gene and ultra-plexed PCR-based sequencing approaches for profiling antimicrobial resistance gene and bacterial taxonomic composition of polymicrobial samples

BackgroundShotgun metagenomic sequencing is increasingly popular in taxonomic and resistome-profiling of polymicrobial samples due to its agnostic nature and data versatility. However, caveats include high- cost, sequencing depth/sensitivity trade-offs, and challenging bioinformatic deconvolution. Targeted PCR-based profiling optimises sensitivity and cost-effectiveness, but can only identify prespecified targets and may introduce amplification biases. Ultra-high multiplexed PCR is a potential compromise. As no comprehensive comparative evaluation exists, we evaluated performance of each method in taxonomic/resistome-profiling of a well-defined DNA mock sample and seven "real- world" wastewater samples. ResultsWe tested three sequencing approaches (short-read shotgun metagenomics, Illumina Ampliseq ultra-plexed AMR Research Panel, 16S rRNA gene sequencing) with seven bioinformatic pipelines (ResPipe, Illumina DNA Amplicon App, One Codex Metagenomic-/Targeted Loci classification and Ampliseq Report, DADA2, and an in-house pipeline for AmpliSeq data [AmpliSeek]). Metagenomics outperformed 16S rRNA gene sequencing in accurately reconstituting a mock taxonomic profile and optimising the identification of diverse wastewater taxa, while 16S rRNA gene sequencing produced more even taxonomic outputs which may be quantitatively inaccurate but enhance detection of low abundance taxa. Shotgun metagenomic and AmpliSeq sequencing performed equally well in profiling AMR genes present in a mock sample, but AmpliSeq identified more genes in more complex, "real-world" samples, likely related to sensitivity of detection at the metagenomic sequencing depth used. ConclusionsA complementary sequencing approach employing 16S rRNA gene or shallow-metagenomic sequencing for taxonomic profiling, and the AmpliSeq AMR panel for high-resolution resistome profiling represents a potential lower-cost alternative to deep shotgun sequencing and may also be more sensitive for the detection of low-prevalence AMR genes. However, our evaluation highlights that both the sequencing and bioinformatics approach used can significantly influence results; for AmpliSeq AMR gene profiling, we developed AmpliSeek which outperformed the other pipelines tested and is open source. Sequencing approach and bioinformatic pipeline should be considered in the context of study goals and sample type, with study-specific validation when feasible.

genomics↗

Single cell analysis of senescent epithelia reveals targetable mechanisms promoting fibrosis

Progressive fibrosis and maladaptive organ repair result in significant morbidity and millions of premature deaths annually. Senescent cells accumulate with ageing and after injury and are implicated in organ fibrosis, but the mechanisms by which senescence influences repair are poorly understood. Using two murine models of injury and repair we show that obstructive injury generates senescent epithelia which persist after resolution of the original injury, promote ongoing fibrosis and impede adaptive repair. Depletion of senescent cells with ABT263 reduces fibrosis in reversed ureteric obstruction and after renal ischaemia-reperfusion injury. We validate these findings in humans, showing that senescence and fibrosis persist after relieved renal obstruction. We next characterise senescent epithelia in murine renal injury using single cell RNA-Seq. We extend our classification to human kidney and liver disease and identify conserved pro-fibrotic proteins which we validate in vitro and in human disease. We demonstrate that one such molecule, Protein Disulfide Isomerase Family A Member 3 (PDIA3), is essential for TGF-beta mediated fibroblast activation. Inhibition of PDIA3 in vivo significantly reduces kidney fibrosis during ongoing renal injury and as such represents a new potential therapeutic pathway. Analysis of the signalling pathways of senescent epithelia connects senescence to organ fibrosis, permitting rational design of anti-fibrotic therapies.

cell biology↗

The Interferon Resistance of Transmitted HIV-1 is a Consequence of Enhanced Replicative Fitness

HIV-1 transmission via sexual exposure is a relatively inefficient process. When successful transmission does occur, newly infected individuals are colonized by either a single or a very small number of establishing virion(s). These transmitted founder (TF) viruses are more interferon (IFN) resistant than chronic control (CC) viruses present 6 months after transmission. To identify the specific molecular defences that make CC viruses more susceptible to the IFN-induced antiviral state than TF viruses, we established a pair of fluorescent GFP-IRES-Nef TF and CC viruses and used arrayed interferon-stimulated gene (ISG) expression screening. The relatively uniform ISG resistance of transmitted HIV-1 directed us to investigate the underlying mechanism. Our subsequent in silico simulations, modelling, and in vitro characterisation of a model TF/CC pair (closely matched in replicative fitness), revealed that small differences in replicative growth rates can explain the broad IFN resistance displayed by transmitted HIV-1. We propose that the apparent IFN resistance of transmitted HIV-1 is a consequence of enhanced replicative fitness, as opposed to specific resistance to individual IFN-induced defences.

microbiology↗

Defining the Characteristics of Type I Interferon Stimulated Genes: Insight from Expression Data and Machine Learning

A virus-infected cell triggers a signalling cascade resulting in the secretion of interferons (IFNs), which in turn induce the up-regulation of IFN-stimulated genes (ISGs) that play an important role in the inhibition of the viral infection and the return to cellular homeostasis. Here, we conduct detailed analyses on 7443 features relating to evolutionary conservation, nucleotide composition, gene expression, amino acid composition, and network properties to elucidate factors associated with the stimulation of genes in response to type I IFNs. Our results show that ISGs are less evolutionary conserved than genes that are not significantly stimulated in IFN experiments (non-ISGs). ISGs show significant depletion of GC-content in the coding region of their canonical transcripts, which leads to under-representation in the nucleotide compositions. Differences between ISGs and non-ISGs are also reflected in the properties of their coded amino acid sequence compositions. Network analyses show that ISG products tend to be involved in key paths but are away from hubs or bottlenecks of the human protein-protein interaction (PPI) network. Our analyses also show that interferon-repressed human genes (IRGs), which are down-regulated in the presence of IFNs, can have similar properties to ISGs, thus leading to false positives in ISG predictions. Based on these analyses, we design a machine learning framework integrating the usage of support vector machine (SVM) and feature selection algorithms. The ISG prediction achieves an area under the receiver operating characteristic curve (AUC) of 0.7455 and demonstrates the similarity between ISGs triggered by type I and III IFNs. Our machine learning model predicts a number of genes as potential ISGs that so far have shown no significant differential expression when stimulated with IFN in the cell types and tissue types compiled in the available IFN-related databases. A webserver implementing our method is accessible at http://isgpre.cvr.gla.ac.uk/. Author summaryInterferons (IFNs) are signalling proteins secreted from host cells. IFN-triggered signalling activates the host immune system in response to intra-cellular infection. It results in the stimulation of many genes that have anti-pathogen roles in host defenses. Interferon-stimulated genes (ISGs) have unique properties that make them different from those not significantly up-regulated in response to IFNs (non-ISGs). We find the down-regulated interferon-repressed genes (IRGs) have some shared properties with ISGs. This increases the difficulty of distinguishing ISGs from non-ISGs. The use of machine learning is a sensible strategy to provide high throughput classifications of putative ISGs, for investigation with in vivo or in vitro experiments. Machine learning can also be applied to human genes for which there are insufficient expression levels before and after IFN treatment in various experiments. Additionally, the interferon type has some impact on ISG predictability. We expect that our study will provide new insight into better understanding the inherent characteristics of human genes that are related to response in the presence of IFNs.

immunology↗

Quantifying and cataloguing unknown sequences within human microbiomes

Advances in genome sequencing technologies and lower costs have enabled the exploration of a multitude of known and novel environments and microbiomes. This has led to an exponential growth in the raw sequence data that is deposited in online repositories. Metagenomic and metatranscriptomic data sets are typically analysed with regards to a specific biological question. However, it is widely acknowledged that these data sets are comprised of a proportion of sequences that bear no similarity to any currently known biological sequence, and this so-called dark matter is often excluded from downstream analyses. In this study, a systematic framework was developed to assemble, identify, and measure the proportion of unknown sequences present in distinct human microbiomes. This framework was applied to forty distinct studies, comprising 963 samples, and covering ten different human microbiomes including fecal, oral, lung, skin and circulatory system microbiomes. The framework was used to determine the proportion of taxonomically unknown sequences present within samples, and to compare such sequences both within and across assembled metagenomes. We found that whilst the human microbiome is one of the most extensively studied, on average 2% of assembled sequences have not yet been taxonomically defined. However, this proportion varied extensively among different microbiomes and was as high as 25% for skin and oral microbiomes that have more interactions with the environment. The publicly available data sets used have not previously been systematically mined to quantify and compare such dark matter. Typically, these unknown sequences are found in several microbiomes and potentially belong to unidentified novel microbes that we interact with on a daily basis. A cross-study comparison led to the identification of similar unknown sequences in different samples and/or microbiomes. A rate of taxonomic characterisation of 1.64% of unknown sequences being characterised per month was calculated from these taxonomically unknown sequences discovered in this study. Additionally, the approach led to the discovery of several potentially novel viral genomes that bear no similarity to sequences in the public databases. Both our computational framework and the novel unknown sequences produced are publicly available for future cross-referencing.

bioinformatics↗

Exploring the natural origins of SARS-CoV-2

The lack of an identifiable intermediate host species for the proximal animal ancestor of SARS-CoV-2, and the large geographical distance between Wuhan and where the closest evolutionary related coronaviruses circulating in horseshoe bats (Sarbecoviruses) have been identified, is fuelling speculation on the natural origins of SARS-CoV-2. We have comprehensively analysed phylogenetic relations between SARS-CoV-2, and the related bat and pangolin Sarbecoviruses sampled so far. Determining the likely recombination events reveals a highly reticulate evolutionary history within this group of coronaviruses. Clustering of the inferred recombination events is non-random with evidence that Spike, the main target for humoral immunity, is beside a recombination hotspot likely driving antigenic shift in the ancestry of bat Sarbecoviruses. Coupled with the geographic ranges of their hosts and the sampling locations, across southern China, and into Southeast Asia, we confirm horseshoe bats, Rhinolophus, are the likely SARS-CoV-2 progenitor reservoir species. By tracing the recombinant sequence patterns, we conclude that there has been relatively recent geographic movement and co-circulation of these viruses ancestors, extending across their bat host ranges in China and Southeast Asia over the last 100 years or so. We confirm that a direct proximal ancestor to SARS-CoV-2 is yet to be sampled, since the closest relative shared a common ancestor with SARS-CoV-2 approximately 40 years ago. Our analysis highlights the need for more wildlife sampling to (i) pinpoint the exact origins of SARS-CoV-2s animal progenitor, and (ii) survey the extent of the diversity in the related Sarbecoviruses phylogeny that present high risk for future spillover. HighlightsO_LIThe origin of SARS-CoV-2 can be traced to horseshoe bats, genus Rhinolophus, with ranges in both China and Southeast Asia. C_LIO_LIThe closest known relatives of SARS-CoV-2 exhibit frequent transmission among their Rhinolophus host species. C_LIO_LISarbecoviruses have undergone extensive recombination throughout their evolutionary history. C_LIO_LIAccounting for the mosaic patterns of these recombinants is important when inferring relatedness to SARS-CoV-2. C_LIO_LIBreakpoint patterns are consistent with recombination hotspots in the coronavirus genome, particularly upstream of the pike open reading frame with a coldspot in S1. C_LI

evolutionary biology↗

Large palindromes on the primate X Chromosome are preserved by natural selection

Mammalian sex chromosomes carry large palindromes that harbor protein-coding gene families with testis-biased expression. However, there are few known examples of sex-chromosome palindromes conserved between species. We identified 26 palindromes on the human X Chromosome, constituting more than 2% of its sequence, and characterized orthologous palindromes in the chimpanzee and the rhesus macaque using a clone-based sequencing approach that incorporates full-length nanopore reads. Many of these palindromes are missing or misassembled in the current reference assemblies of these species genomes. We find that 12 human X palindromes have been conserved for at least 25 million years, with orthologs in both chimpanzee and rhesus macaque. Insertions and deletions between species are significantly depleted within the X palindromes protein-coding genes compared to their non-coding sequence, demonstrating that natural selection has preserved these gene families. Unexpectedly, the spacers that separate the left and right arms of palindromes are a site of localized structural instability, with 7 of 12 conserved palindromes showing no spacer orthology between human and rhesus macaque. Analysis of the 1000 Genomes Project dataset revealed that human X-palindrome spacers are enriched for deletions relative to arms and flanking sequence, including a common spacer deletion that affects 13% of human X Chromosomes. This work reveals an abundance of conserved palindromes on primate X Chromosomes, and suggests that protein-coding gene families in palindromes (most of which remain poorly characterized) promote X-palindrome survival in the face of ongoing structural instability.

genomics↗

Insights into dispersed duplications and complex structural mutations from whole genome sequencing 706 families

Two intriguing forms of genome structural variation (SV) - dispersed duplications, and de novo rearrangements of complex, multi-allelic loci - have long escaped genomic analysis. We describe a new way to find and characterize such variation by utilizing identity-by-descent (IBD) relationships between siblings together with high-precision measurements of segmental copy number. Analyzing whole-genome sequence data from 706 families, we find hundreds of "IBD-discordant" (IBDD) CNVs: loci at which siblings CNV measurements and IBD states are mathematically inconsistent. We found that commonly-IBDD CNVs identify dispersed duplications; we mapped 95 of these common dispersed duplications to their true genomic locations through family-based linkage and population linkage disequilibrium (LD), and found several to be in strong LD with genome-wide association (GWAS) signals for common diseases or gene expression variation at their revealed genomic locations. Other CNVs that were IBDD in a single family appear to involve de novo mutations in complex and multi-allelic loci; we identified 26 de novo structural mutations that had not been previously detected in earlier analyses of the same families by diverse SV analysis methods. These included a de novo mutation of the amylase gene locus and multiple de novo mutations at chromosome 15q14. Combining these complex mutations with more-conventional CNVs, we estimate that segmental mutations larger than 1kb arise in about one per 22 human meioses. These methods are complementary to previous techniques in that they interrogate genomic regions that are home to segmental duplication, high CNV allele frequencies, and multi-allelic CNVs. Author SummaryCopy number variation is an important form of genetic variation in which individuals differ in the number of copies of segments of their genomes. Certain aspects of copy number variation have traditionally been difficult to study using short-read sequencing data. For example, standard analyses often cannot tell whether the duplicated copies of a segment are located near the original copy or are dispersed to other regions of the genome. Another aspect of copy number variation that has been difficult to study is the detection of mutations in the copy number of DNA segments passed down from parents to their children, particularly when the mutations affect genome segments which already display common copy number variation in the population. We develop an analytical approach to solving these problems when sequencing data is available for all members of families with at least two children. This method is based on determining the number of parental haplotypes the two siblings share at each location in their genome, and using that information to determine the possible inheritance patterns that might explain the copy numbers we observe in each family member. We show that dispersed duplications and mutations can be identified by looking for copy number variants that do not follow these expected inheritance patterns. We use this approach to determine the location of 95 common duplications which are dispersed to distant regions of the genome, and demonstrate that these duplications are linked to genetic variants that affect disease risk or gene expression levels. We also identify a set of copy number mutations not detected by previous analyses of sequencing data from a large cohort of families, and show that repetitive and complex regions of the genome undergo frequent mutations in copy number.

genomics↗

Kidney single-cell atlas reveals myeloid heterogeneity in progression and regression of kidney disease.

The kidney has a limited capacity to repair following injury, however, the endogenous reparative pathways are not well understood. Here we employ integrated droplet- and plate-based scRNA-seq in the murine reversible unilateral ureteric obstruction model to dissect the transcriptomic landscape at the single cell level during renal injury and resolution of fibrosis. We generate a comprehensive catalogue of the changes induced during injury and repair, revealing significant myeloid cell heterogeneity, which would not have been identifiable by conventional flow cytometry. We identify new markers for the myeloid populations within the kidney as well as identification of novel subsets including an Arg1+ monocyte population specific to early injury and a Mmp12+ macrophage subset exclusive to repair. Finally, using paired blood exchange to track circulating immune cells, we confirm that monocytes are recruited to the kidney early after injury and are the source of Ccr2+ macrophages that accumulate in late injury. Our data demonstrate the utility of complementary technologies to identify novel myeloid subtypes that may represent therapeutic targets to inhibit progression or promote regression of kidney disease.

immunology↗

Synonymous Dinucleotide Usage: A Codon-Aware Metric for Quantifying Dinucleotide Representation in Viruses

Distinct patterns of dinucleotide representation, such as CpG and UpA suppression, are characteristic of certain viral genomes. Recent research has uncovered vertebrate immune mechanisms that select against specific dinucleotides in targeted viruses. This evidence highlights the importance of systematically examining the dinucleotide composition of viral genomes. We have developed a novel metric, called Synonymous Dinucleotide Usage (SDU), for quantifying dinucleotide representation in coding sequences. Our method compares the abundance of a given dinucleotide to the null hypothesis of equal synonymous codon usage in the sequence. We present a Python3 package, DinuQ, for calculating SDU and other relevant metrics. We have applied this method on two sets of invertebrate- and vertebrate-specific flaviviruses and rhabdoviruses. The SDU shows that the vertebrate viruses exhibit consistently greater under-representation of CpG dinucleotides in all three codon positions in both datasets. In comparison to existing metrics for dinucleotide quantification, the SDU allows for a statistical interpretation of its values by comparing it to a null expectation based on the codon table. Here we apply the method to viruses, but coding sequences of other living organisms can be analysed in the same way.

bioinformatics↗