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Morris, A.

Publications and source records attributed to Morris, A..

At least 37 records · Page 2Linked to original sources

The Use of Class Imbalanced Learning Methods on ULSAM Data to Predict the Case-Control Status in Genome-Wide Association Studies

Machine learning (ML) methods for uncovering single nucleotide polymorphisms (SNPs) in genome-wide association study (GWAS) data that can be used to predict disease outcomes are becoming increasingly used in genetic research. Two issues with the use of ML models are finding the correct method for dealing with imbalanced data and data training. This article compares three ML models to identify SNPs that predict type 2 diabetes (T2D) status using the Support vector machine SMOTE (SVM SMOTE), The Adaptive Synthetic Sampling Approach (ADASYN), Random under sampling (RUS) on GWAS data from elderly male participants (165 cases and 951 controls) from the Uppsala Longitudinal Study of Adult Men (ULSAM). It was also applied to SNPs selected by the SMOTE, SVM SMOTE, ADASYN, and RUS clumping method. The analysis was performed using three different ML models: (i) support vector machine (SVM), (ii) multilayer perceptron (MLP) and (iii) random forests (RF). The accuracy of the case-control classification was compared between these three methods. The best classification algorithm was a combination of MLP and SMOTE (97% accuracy). Both RF and SVM achieved good accuracy results of over 90%. Overall, methods used against unbalanced data, all three ML algorithms were found to improve prediction accuracy.

bioinformatics↗

Different helminth parasites show contrasting relationships with age in a wild ungulate

As animals age they often exhibit substantial physiological and behavioural changes that can drive changes in infection status over the lifespan. Generally, immunosenescence is expected to lead to greater infection in older individuals, but this process could be confounded or counteracted by changes in behaviour, selective disappearance of certain individuals, or a range of immune processes. Here, we uncover contrasting age-related patterns of infection across three different helminth parasites in wild adult red deer (Cervus elaphus). Counts of strongyle nematodes (order: Strongylida) increased with age, while counts of liver fluke (Fasciola hepatica) and tissue worm (Elaphostrongylus cervi) decreased. These relationships could not be explained by selective disappearance of certain individuals or changes in behaviour, suggesting that immune changes could be responsible. Additionally, we found a positive relationship between social connectedness and strongyle infection, implying that previously documented age-related decreases in social behaviour may minimise exposure, reducing the negative effects of immunosenescence. These findings demonstrate that burdens of different parasites can show contrasting changes over an individuals lifespan depending on a complex suite of intrinsic and extrinsic factors.

ecology↗

Helminth parasites decrease survival probability in young red deer

Helminths are common parasites of wild ungulates that can have substantial costs for growth, mortality, and reproduction. While these costs are relatively well documented for mature animals, knowledge of helminths impacts on juveniles is more limited. Identifying these effects is important because young individuals are often heavily infected, and juvenile mortality is an important process regulating wild populations. Here, we investigated associations between helminth infection and overwinter survival in juvenile wild red deer (Cervus elaphus) on the Isle of Rum, Scotland. We collected faecal samples non-invasively from known individuals and used them to count propagules of three helminth taxa (strongyle nematodes, Fasciola hepatica, and Elaphostrongylus cervi). Using generalised linear models, we investigated associations between parasite counts and overwinter survival for calves and yearlings. Strongyles were associated with reduced survival in both age class, and F. hepatica was associated with reduced survival in yearlings, while E. cervi infection showed no association with survival in either age class. This study provides observational evidence for fitness costs of helminth infection in juveniles of a wild mammal, and suggests that these parasites could play a role in regulating population dynamics.

ecology↗

Omics-informed CNV calls reduce false positive rate and improve power for CNV-trait associations

Copy number variations (CNV) are believed to play an important role in a wide range of complex traits but discovering such associations remains challenging. Whilst whole genome sequencing (WGS) is the gold standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV), however these calls suffer from elevated false positive and negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNV) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (P < 3.0-10-90), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 34% compared to raw pCNVs or previous quality scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls and demonstrated its utility by improving the statistical power for downstream association analyses.

bioinformatics↗

Antibodies targeting conserved non-canonical antigens and endemic coronaviruses associate with favorable outcomes in severe COVID-19

While there have been extensive analyses characterizing cellular and humoral responses across the severity spectrum in COVID-19, predictors of outcomes within severe COVID-19 remain to be comprehensively elucidated. Recently, we identified divergent monocyte states as predictors of outcomes within severe COVID-19, but corresponding humoral profiles of risk have not been delineated. Furthermore, the nature of antibodies (Abs) directed against viral antigens beyond the spike protein or endemic coronavirus antigens and their associations with disease severity and outcomes remain poorly defined. We performed deep molecular profiling of Abs directed against a wide range of antigenic specificities in severe COVID-19 patients admitted to the ICU. The profiles consisted of canonical (S, RBD, N) and non-canonical (orf3a, orf8, nsp3, nps13 and M) antigenic specificities. Notably, multivariate machine learning (ML) models, generated using profiles of Abs directed against canonical or non-canonical antigens, were equally discriminative of recovery and mortality COVID-19 outcomes. In both ML models, survivors were associated with increased virus-specific IgA and IgG3 antibodies and with higher antigen-specific antibody galactosylation. Intriguingly, pre-pandemic healthy controls had cross-reactive Abs directed against nsp13 which is a conserved protein in other alpha and beta coronaviruses. Notably, higher levels of nsp13-specific IgA antibodies were associated with recovery in severe COVID-19. In keeping with these findings, a model built on Ab profiles for endemic coronavirus antigens was also predictive of COVID-19 outcome bifurcation, with higher levels of IgA and IgG3 antibodies against OC43 S and NL63 S being associated with survival. Our results suggest the importance of Abs targeting non-canonical SARS-CoV-2 antigens as well as those directed against endemic coronaviruses in favorable outcomes of severe COVID-19.

immunology↗

Low diversity and instability of the sinus microbiota over time in adults with cystic fibrosis

BackgroundChronic rhinosinusitis (CRS) is a common, yet underreported and understudied manifestation of upper respiratory disease in people with cystic fibrosis (CF). There are currently no standard of care guidelines for the management of CF CRS, but treatment of upper airway disease may ameliorate lower airway disease. We sought to inform future treatment guidelines by determining whether changes to sinus microbial community diversity and specific taxa known to cause CF lung disease are associated with increased respiratory disease and inflammation. MethodsWe performed 16S rRNA gene sequencing, supplemented with cytokine analyses, microscopy, and bacterial culturing, on samples from the sinuses of 27 adults with CF CRS at the University of Pittsburghs CF Sinus Clinic. At each study visit, participants underwent endoscopic paranasal sinus sampling and clinical evaluation. We identified key drivers of microbial community composition and evaluated relationships between diversity and taxa with disease outcomes and inflammation. FindingsSinus community diversity was low and the composition was unstable, with many participants exhibiting alternating dominance between Pseudomonas aeruginosa and Staphylococci over time. Despite a tendency for dominance by these two taxa, communities were highly individualized and shifted composition during exacerbation of sinus disease symptoms. Exacerbations were also associated with communities dominated by Staphylococcus spp. Reduced microbial community diversity was linked to worse sinus disease and the inflammatory status of the sinuses (including increased IL-1{beta}). Increased IL-1{beta} was also linked to worse sinus endoscopic appearance, and other cytokines were linked to microbial community dynamics. InterpretationTo our knowledge, this is the largest longitudinal study of microbial communities and cytokine secretion in CF CRS. Our work revealed previously unknown instability of sinus microbial communities and a link between inflammation, lack of microbial community diversity, and worse sinus disease. FundingCystic Fibrosis Foundation and US National Institutes of Health. Research in ContextO_ST_ABSEvidence before this studyC_ST_ABSA search of the PubMed database on October 11, 2021 with the terms [cystic fibrosis sinus microbiome] yielded 16 results, and we have identified seven primary research articles on the CF CRS microbiome (including re-analyses of existing datasets). Most are cross-sectional cohort analyses, along with one prior longitudinal study of four adults at the University of Auckland, New Zealand. Together, these prior studies reveal similarities between CF CRS and CF sputum microbiomes, including low community diversity associated with sinus disease, the presence of common CF-associated microbes in the sinuses, and prevalence of sinus communities dominated by P. aeruginosa or Staphylococcus aureus. High levels of IL-1{beta} are linked to the presence of nasal polyps in CF CRS, and polymorphisms in the IL-1 receptor antagonist gene are associated with risk of CRS outside of the context of CF. Two prior studies of this cohort have been performed by our laboratory. One describes clinical indicators of CF sinus disease and the other links sinus infection biogeography to P. aeruginosa evolutionary genomics. Added value of this studyOur study is the first to examine longitudinal relationships between the host immune response (through cytokine profiling) and microbiota dynamics in CF CRS, including linking elevated IL-1{beta} to worse sinus disease through reduced sinus microbial community diversity. The longitudinal nature of our study also allowed us to uncover striking temporal instability of microbial communities in approximately half of our cohorts sinus microbial communities over two years, including switching between communities dominated by P. aeruginosa and Staphylococcus spp. This instability could hinder attempts to link the relative abundance of taxa to clinical outcomes of interest in cross-sectional studies (e.g., markers of disease progression). We also identified patterns of synergy and antagonism between specific taxa, and impacts of the host immune response in the sinuses on community composition. Implications of all the available evidenceTogether with prior CF CRS microbiome studies, our study underscores similarities between sinus and lower respiratory tract microbial community structure in CF, and we show how community structure tracks with inflammation and several disease measures. This work strongly suggests that clinical management of CRS could be leveraged to improve overall respiratory health in CF. Our work implicates elevated IL-1{beta} in reduced microbiota diversity and worse sinus disease in CF CRS, suggesting applications for existing therapies targeting IL-1{beta}. Finally, the widespread use of highly effective CFTR modulator therapy has led to less frequent availability of spontaneous expectorated sputum for microbiological surveillance of lung infections. A better understanding of CF sinus microbiology could provide a much-needed alternative site for monitoring respiratory infection status by important CF pathogens.

microbiology↗

rareSurvival: rare variant association analysis for time-to-event outcomes.

SummaryRare variants have been proposed as contributing to the "missing heritability" of complex human traits. There has been much recent development of methodology to investigate association of complex traits with multiple rare variants within pre-defined "units" from sequence and array-based studies of the exome or genome. However, software for modelling time to event outcomes for rare variant associations has been under developed in comparison with binary and quantitative traits. We introduce a new command line application, rareSurvival, used for the analysis of rare variants with time to event outcomes. The program is compatible with high performance computing (HPC) clusters for batch processing. rareSurvival implements statistical methodology, which are a combination of widely used survival and gene-based analysis techniques such as the Cox proportional hazards model and the burden test. We introduce a novel piece of software that will be at the forefront of efforts to discover rare variants associated with a variety of complex diseases with survival endpoints. Availability & ImplementationrareSurvival is implemented in C#, available on Linux, Windows and Mac OS X operating systems. It is freely available (GNU General Public License, version 3) to download from https://www.liverpool.ac.uk/translational-medicine/research/statistical-genetics/software/. Download Mono for Linux or Mac OS X to run software. Contacthamzah.syed@liverpool.ac.uk Supplementary informationLinks to additional figures and tables are available at Bioinformatics online.

bioinformatics↗

Ageing red deer alter their spatial behaviour and become less social

Social relationships are important to many aspects of animals lives, and an individuals connections may change over the course of their lifespan. Currently, it is unclear whether social connectedness declines within individuals as they age, and what the underlying mechanisms might be, so the role of age in structuring animal social systems remains unresolved, particularly in non-primates. Here, we describe senescent declines in social connectedness using 43 years of data in a wild, individually monitored population of a long-lived mammal (European red deer, Cervus elaphus). Applying a series of spatial and social network analyses, we demonstrate that these declines occur due to within-individual changes in social behaviour, with correlated changes in spatial behaviour (smaller home ranges and movements to lower-density, lower-quality areas). These findings demonstrate that within-individual socio-spatial behavioural changes can lead older animals in fission-fusion societies to become less socially connected, shedding light on the ecological and evolutionary processes structuring wild animal populations.

ecology↗

Arthritis Flares Mediated by Tissue Resident Memory T Cells in the Joint

Although rheumatoid arthritis is a systemic disease, flares typically occur in a subset of joints that is distinctive for each patient. Pursuing this intriguing pattern, we show that arthritis recurrence is mediated by long-lived synovial resident memory T cells (TRM). In three murine models, CD8+ cells bearing TRM markers remain in previously inflamed joints during remission. These cells are bona fide TRM, exhibiting failure to migrate from joint to joint, preferential uptake of fatty acids, and long-term residency. Disease flares result from TRM activation by antigen, leading to CCL5-mediated recruitment of circulating effector cells. Correspondingly, TRM depletion ameliorates recurrence in a site-specific manner. Human rheumatoid arthritis joint tissues contain a comparable CD8+-predominant TRM population, most evident in late-stage non-inflamed synovium, exhibiting limited T cell receptor diversity and a pro-inflammatory transcriptomic signature. Together, these findings establish synovial TRM cells as a targetable mediator of disease chronicity in autoimmune arthritis.

immunology↗

CD4+ T cell lymphopenia and dysfunction in severe COVID-19 disease is autocrine TNF-α/TNFRI-dependent

Lymphopenia is common in severe COVID-19 disease, yet the mechanisms are poorly understood. In 148 patients with severe COVID-19, we found lymphopenia was associated with worse survival. CD4+ lymphopenia predominated, with lower CD4+/CD8+ ratios in severe COVID-19 compared to recovered, mild disease (p<0.0001). In severe disease, immunodominant CD4+ T cell responses to Spike-1(S1) produced increased in vitro TNF-, but impaired proliferation and increased susceptibility to activation-induced cell death (AICD). CD4+TNF-+ T cell responses inversely correlated with absolute CD4+ counts from severe COVID-19 patients (n=76; R=-0.744, P<0.0001). TNF- blockade including infliximab or anti-TNFRI antibodies strikingly rescued S1-specific CD4+ proliferation and abrogated S1-AICD in severe COVID-19 patients (P<0.001). Single-cell RNAseq demonstrated downregulation of Type-1 cytokines and NF{kappa}B signaling in S1-stimulated CD4+ cells with infliximab treatment. Lung CD4+ T cells in severe COVID-19 were reduced and produced higher TNF- versus PBMC. Together, our findings show COVID-19-associated CD4+ lymphopenia and dysfunction is autocrine TNF-/TNFRI-dependent and therapies targeting TNF- may be beneficial in severe COVID-19. One Sentence SummaryAutocrine TNF-/TNFRI regulates CD4+ T cell lymphopenia and dysfunction in severe COVID-19 disease.

immunology↗

Inferring cell cycle phases from a partially temporal network of protein interactions

The temporal organisation of biological systems into phases and subphases is often crucial to their functioning. Identifying this multiscale organisation can yield insight into the underlying biological mechanisms at play. To date, however, this identification requires a priori biological knowledge of the system under study. Here, we recover the temporal organisation of the cell cycle of budding yeast into phases and subphases, in an automated way. To do so, we model the cell cycle as a partially temporal network of protein-protein interactions (PPIs) by combining a traditional static PPI network with protein concentration or RNA expression time series data. Then, we cluster the snapshots of this temporal network to infer phases, which show good agreement with our biological knowledge of the cell cycle. We systematically test the robustness of the approach and investigate the effect of having only partial temporal information. Our results show for the first time that a temporal network with only partial temporal information, i.e. for some of the PPIs, is sufficient to infer the temporal organization of a system. The generality of the method makes it suitable for application to other, less well-known biological systems for which the temporal organisation of processes plays an important role.

systems biology↗

Bifurcated monocyte states are predictive of mortality in severe COVID-19

Coronavirus disease 2019 (COVID-19) caused by SARS-CoV-2 infection presents with varied clinical manifestations1, ranging from mild symptoms to acute respiratory distress syndrome (ARDS) with high mortality2,3. Despite extensive analyses, there remains an urgent need to delineate immune cell states that contribute to mortality in severe COVID-19. We performed high-dimensional cellular and molecular profiling of blood and respiratory samples from critically ill COVID-19 patients to define immune cell genomic states that are predictive of outcome in severe COVID-19 disease. Critically ill patients admitted to the intensive care unit (ICU) manifested increased frequencies of inflammatory monocytes and plasmablasts that were also associated with ARDS not due to COVID-19. Single-cell RNAseq (scRNAseq)-based deconvolution of genomic states of peripheral immune cells revealed distinct gene modules that were associated with COVID-19 outcome. Notably, monocytes exhibited bifurcated genomic states, with expression of a cytokine gene module exemplified by CCL4 (MIP-1{beta}) associated with survival and an interferon signaling module associated with death. These gene modules were correlated with higher levels of MIP-1{beta} and CXCL10 levels in plasma, respectively. Monocytes expressing genes reflective of these divergent modules were also detectable in endotracheal aspirates. Machine learning algorithms identified the distinctive monocyte modules as part of a multivariate peripheral immune system state that was predictive of COVID-19 mortality. Follow-up analysis of the monocyte modules on ICU day 5 was consistent with bifurcated states that correlated with distinct inflammatory cytokines. Our data suggests a pivotal role for monocytes and their specific inflammatory genomic states in contributing to mortality in life-threatening COVID-19 disease and may facilitate discovery of new diagnostics and therapeutics.

immunology↗

Evolution and adaptation of Pseudomonas aeruginosa in the paranasal sinuses of people with cystic fibrosis

People with the genetic disorder cystic fibrosis (CF) harbor lifelong respiratory infections, with morbidity and mortality frequently linked to chronic lung infections dominated by the opportunistically pathogenic bacterium Pseudomonas aeruginosa. During chronic CF lung infections, a single clone of P. aeruginosa can persist for decades and dominate end-stage CF lung disease due to its propensity to adaptively evolve to the respiratory environment, a process termed "pathoadaptation". Chronic rhinosinusitis (CRS), chronic inflammation and infection of the sinonasal space, is highly prevalent in CF and the sinuses may serve as the first site in the respiratory tract to become colonized by bacteria that then proceed to seed lung infections. We identified three evolutionary genetic routes by which P. aeruginosa evolves in the sinuses of people with CF, including through the evolution of mutator lineages and proliferative insertion sequences and culminating in early genomic signatures of host-restriction. Our findings raise the question of whether a significant portion of the pathoadaptive phenotypes previously thought to have evolved in response to selective pressures in the CF lungs may have first arisen in the sinuses and underscore the link between sinonasal and lung disease in CF. Graphical abstract and highlightsO_LIPseudomonas aeruginosa undergoes adaptive evolution in the sinuses of people with CF C_LIO_LIOver time, pathoadapted strains display early signatures of genome degradation consistent with recent host restriction C_LIO_LIMutations previously thought to occur in CF lungs may have first evolved in sinuses C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/359844v1_ufig1.gif" ALT="Figure 1"> View larger version (50K): org.highwire.dtl.DTLVardef@13b36aborg.highwire.dtl.DTLVardef@8230e1org.highwire.dtl.DTLVardef@1570c3eorg.highwire.dtl.DTLVardef@1e4e530_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

Calcium ion chelation preserves platelet function during cold storage

ObjectivePlatelet transfusion is a life-saving therapy to prevent or treat bleeding in patients with thrombocytopenia or platelet dysfunction. However, for more than six decades, safe and effective strategies for platelet storage have been an impediment to widespread use of platelet transfusion. Refrigerated platelets are cleared rapidly from circulation, precluding cold storage of platelets for transfusion. Consequently, platelets are stored at room temperature (RT) with an upper limit of 5 days due to risks of bacterial contamination and loss of platelet function. This practice severely limits platelet availability for transfusion. This study is to identify the mechanism of platelet clearance after cold storage and develop a method for platelet cold storage. Approach and ResultsWe found that rapid clearance of cold-stored platelets was largely due to integrin activation and apoptosis. Deficiency of integrin {beta}3 or caspase-3 prolonged cold-stored platelets in circulation. Pre-treatment of platelets with EGTA, a cell impermeable calcium ion chelator, reversely inhibited cold storage-induced platelet activation and consequently prolonged circulation of cold-stored platelets. Moreover, transfusion of EGTA-treated, cold-stored platelets, but not RT-stored platelets, into the mice deficient in glycoprotein Ib significantly shortened tail-bleeding times and diminished blood loss. ConclusionIntegrin activation and apoptosis is the underlying mechanism of rapid clearance of platelets after cold storage. Addition of a cell impermeable calcium ion chelator to platelet products is potentially a simple and effective method to enable cold storage of platelets for transfusion.

cell biology↗

Spatial point locations explain a range of social network positions in a wild ungulate

The structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43-year dataset detailing a wild red deer population to investigate how individuals spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi-matrix animal models, we demonstrate that social network positions are shaped by two-dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual-level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality. Authorship StatementGFA conceived the study, analysed the data, and wrote the manuscript, advised by JAF. AM and SM collected the data. JAF, JMP, THCB, and DN commented on the manuscript. Data Accessibility StatementThe code used here is available at https://github.com/gfalbery/Spocial_Deer. On acceptance, the data will be uploaded to the same repo, which will be archived on Zenodo.

ecology↗

Proteasome-mediated regulation of Cdhr1a by Siah1 modulates photoreceptor development and survival in zebrafish.

Congenital retinal dystrophies are a major cause of unpreventable and incurable blindness worldwide. Mutations in CDHR1, a retina specific cadherin, are associated with cone-rod dystrophy. The ubiquitin proteasome system (UPS) is responsible for mediating orderly and precise targeting of protein degradation to maintain biological homeostasis and coordinate proper development, including retinal development. Recently, our lab uncovered that the seven in absentia (Siah) family of E3 ubiquitin ligases play a role in optic fissure fusion, and identified Cdhr1a as a potential target of Siah. Using two-color whole mount in situ hybridization and immunohistochemistry, we detected siah1 and cdhr1a co-expression as well as protein co-localization in the retinal outer nuclear layer (ONL), and more precisely in the connecting cilium of rods and cones between 3-5 days post fertilization (dpf). We confirmed that Siah1 targets Cdhr1a for proteasomal degradation by co-transfection and co-immunoprecipitation in cell culture. To analyze the functional importance of this interaction, we created two transgenic zebrafish lines that express siah1 or an inactive siah1 (siah1{Delta}RING) under the control of the heat shock promoter to modulate Siah activity during photoreceptor development. Overexpression of siah1, but not siah1{Delta}RING, resulted in a decrease in the number of rods and cones at 72 hours post fertilization (hpf). The number of retinal ganglion cells, amacrine and bipolar was not affected by Siah1 overexpression, and there was no significant reduction of proliferating cells in the Siah1 overexpressing retina. We did however detect increased cell death, confirmed by an increase in the number of TUNEL+ cells in the ONL, which was proteasome-dependent, as MG132 treatment rescued the cell death phenotype. Lastly, reduction in rods and cones resulting from increased Siah1 expression was rescued by injection of cdhr1 mRNA, and to an even greater extent by injection of a Siah1-insensitive cdhr1a variant mRNA. Taken together, our work provides the first evidence that Cdhr1a plays a role during early photoreceptor development and that Cdhr1a is regulated by Siah1 via the UPS. This work provides new avenues for investigation into the roles of CDHR1, and now also Siah1, in the predisposition and pathogenesis of inherited cone-rod dystrophy.

developmental biology↗

Belowground changes to community structure alter methane-cycling dynamics in Amazonia

Amazonian rainforest is undergoing increasing rates of deforestation, driven primarily by cattle pasture expansion. Forest-to-pasture conversion has been associated with changes to ecosystem processes, including substantial increases in soil methane (CH4) emission. The drivers of this change in CH4 flux are not well understood. To address this knowledge gap, we measured soil CH4 flux, environmental conditions, and belowground microbial community attributes across a land use change gradient (old growth primary forest, cattle pasture, and secondary forest regrowth) in two Amazon Basin regions. Primary forest soils exhibited CH4 uptake at modest rates, while pasture soils exhibited CH4 emission at high but variable rates. Secondary forest soils exhibited low rates of CH4 uptake, suggesting that forest regrowth following pasture abandonment could reverse the CH4 sink-to-source trend. While few environmental variables were significantly associated with CH4 flux, we identified numerous microbial community attributes in the surface soil that explained substantial variation in CH4 flux with land use change. Among the strongest predictors were the relative abundance and diversity of methanogens, which both increased in pasture relative to forests. We further identified individual taxa that were associated with CH4 fluxes and which collectively explained ~50% of flux variance. These taxa included methanogens and methanotrophs, as well as taxa that may indirectly influence CH4 flux through acetate production, iron reduction, and nitrogen transformations. Each land type had a unique subset of taxa associated with CH4 fluxes, suggesting that land use change alters CH4 cycling through shifts in microbial community composition. Taken together, our results suggest that changes in CH4 flux from agricultural conversion could be driven by microbial responses to land use change in the surface soil, with both direct and indirect effects on CH4 cycling. This demonstrates the central role of microorganisms in mediating ecosystem responses to land use change in the Amazon Basin.

ecology↗

Chromatin-based techniques map DNA interaction landscapes in psoriasis susceptibility loci and highlight KLF4 as a target gene in 9q31

Genome-wide association studies (GWAS) have uncovered many genetic risk loci for psoriasis, yet many remain uncharacterised in terms of the causal gene and their biological mechanism in disease. Here, we use a disease-focused Capture Hi-C experiment to link psoriasis-associated variants with their target genes in psoriasis-relevant cell lines (HaCaT keratinocytes and My-La CD8+ T cells). We confirm previously assigned genes, suggest novel candidates and provide evidence for complexity at psoriasis GWAS loci. In the 9q31 risk locus we combine further epigenomic evidence to demonstrate how the psoriasis association forms a functional interaction with the distant (>500 kb) KLF4 gene. We use CRISPR activation coupled with RNA-seq to demonstrate how activation of psoriasis-associated enhancers upregulates KLF4 in HaCaT cells. Our study design provides a robust pipeline for following up on GWAS disease-associated variants, paving the way for functional translation of genetic findings into clinical benefit.

genomics↗