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Brown, R.

Publications and source records attributed to Brown, R..

72 records · Page 4Linked to original sources

Impact of glycan positioning on HIV-1 Env glycan shield density, function, and antibody recognition

N-glycans, which represent >50% mass of the HIV-1 envelope (Env) trimer, play important roles for virus-cell entry and immune evasion. How each glycan unit interacts to shape the Env protein-sugar complex and affects Env function is not well understood. Here, high-resolution glycomics analysis of two Env variants from the same donor, with differing functional characteristics and N-glycosylation-site composition, revealed that changes to key N-glycosylation-site not only affected the Env structure at distant locations, but also had a ripple effect on Env-wide glycan processing, virus infectivity, and antibody recognition and virus neutralization. Specifically, the N262 glycan, although not located in the CD4-binding site, controlled Env binding to the CD4 receptor, affected the recognition of Env by several glycan-dependent broadly neutralizing antibodies, and altered heterogeneity of glycosylation at several sites, with N156, N160, and N448 displaying limited glycan processing. Molecular dynamic simulations visualized how specific oligosaccharide positions can move to compensate for loss of a glycan. This study demonstrates how changes in individual glycan units can alter molecular dynamics and processing of the Env-glycan shield and, consequently, Env function.

microbiology↗

Potent inhibitors of toxic alpha-synuclein oligomers identified via cellular time-resolved FRET biosensor.

Preventing or reversing the pathological misfolding and self-association of alpha-synuclein (aSyn) can rescue a broad spectrum of pathological cellular insults that manifest in Parkinsons Disease (PD), Dementia with Lewy bodies (DLB), and other alpha-synucleinopathies. We have developed a high-throughput, FRET-based drug discovery platform that combines high-resolution protein structural detection in living cells with an array of functional and biophysical assays to identify novel lead compounds that protect SH-SY5Y cells from aSyn induced cytotoxicity as well as inhibiting seeded aSyn aggregation, even at nanomolar concentrations. Our combination of cellular and cell-free assays allow us to distinguish between direct aSyn binding or indirect mechanisms of action (MOA). We focus on targeting oligomers with the requisite sensitivity to detect subtle protein structural changes that may lead to effective therapeutic discoveries for PD, DLB, and other alpha-synucleinopathies. Pilot high-throughput screens (HTS) using our aSyn cellular FRET biosensors has led to the discovery of the first nanomolar-affinity small molecules that disrupt toxic aSyn oligomers in cells and inhibit cell death. Primary neuron assays of aSyn pathology (e.g. phosphorylation of mouse aSyn PFF) show rescue of pathology for two of our tested compounds. Subsequent seeded thioflavin-t (ThioT) aSyn aggregation assays demonstrate these compounds deter or block aSyn fibril assembly. Other hit compounds identified in our HTS are known to modulate oxidative stress, autophagy, and ER stress, providing validation that our biosensor is sensitive to indirect MOA as well.

neuroscience↗

Identification of human tendon cell populations in healthy and diseased tissue using combined single cell transcriptomics and proteomics

The long-term morbidity of tendon disease in an increasingly active and ageing population represents a growing area of unmet clinical need. Tendon disorders commonly affect the lower limb, ranging from isolated tendon rupture to degenerative joint deformity. In the absence of valid animal models of chronic tendinopathy, traditional methods to isolate and identify crucial sub types involved in disease are limited by the heterogeneity of tendon cells, by their relative paucity in tissue and by the density of the surrounding collagen matrix. To overcome this, we have used next generation CITE-sequencing to combine surface proteomics with in-depth, unbiased gene expression analysis of single cells derived ex vivo from healthy and diseased tendon. For the first time we have been able to show that human tendon consists of at least eight sub-populations of cells. In addition to endothelial cells, Tc cells, and macrophages, there are five distinct tenocyte populations expressing COL1A genes. These consist of a population of resident cells expressing microfibril associated genes (FBN1, VCAN, DCN, EMILIN1, MFAP5), a group of SCX+ cells co-expressing high levels of pro-inflammatory markers, a population of APOD+ fibro-adipogenic progenitors (FAPs), TPPP3/PRG4+ chondrogenic cells (COMP, CILP, PRG4) and ITGA7+ Smooth Muscle-Mesenchymal Cells, recently described in mouse muscle but not, as yet, in human tendon. Surface proteomic analysis identified markers by which these sub-classes could be isolated and targeted in future. In comparison to healthy tendon, diseased tendon harboured a greater proportion of SCX+ tendon cells and these expressed high levels of pro-inflammatory markers including CXCL1, CXCL6, CXCL8, PDPN and previously undescribed PTX3. We were also able to show that whereas disease associated genes such as CD248 and PDPN were expressed by COL1+ tenocytes, IL33 was restricted to endothelial cells of chronically diseased tendon.

cell biology↗

Accurate modeling of replication rates in genome-wide association studies by accounting for winner's curse and study-specific heterogeneity

Genome-wide association studies (GWAS) have identified thousands of genetic variants associated with complex human traits, but only a fraction of variants identified in discovery studies achieve significance in replication studies. Replication in GWAS has been well-studied in the context of Winners Curse, which is the inflation of effect size estimates for significant variants due to statistical chance. However, Winners Curse is often not sufficient to explain lack of replication. Another reason why studies fail to replicate is that there are fundamental differences between the discovery and replication studies. A confounding factor can create the appearance of a significant finding while actually being an artifact that will not replicate in future studies. We propose a statistical framework that utilizes GWAS and replication studies to jointly model Winners Curse and study-specific heterogeneity due to confounding factors. We apply this framework to 100 GWAS from the Human GWAS Catalog and observe that there is a large range in the level of estimated confounding. We demonstrate how this framework can be used to distinguish when studies fail to replicate due to statistical noise and when they fail due to confounding.

bioinformatics↗

Species delimitation in the grey zone: introgression obfuscates phylogenetic inference and species boundaries in a cryptic frog complex (Ranidae: Pulchrana picturata)

As molecular methods continue to elucidate genetic structure at increasingly finer resolutions, delimiting species in the grey zone of the speciation continuum is becoming more relevant in biodiversity research, especially in under-studied biodiversity hotspots such as Southeast Asia where new species are being described at an unprecedented rate. Obvious species at both ends of the speciation continuum have mostly been described and attention is now turning towards the \"grey zone:\" an intermediate stage in which species criteria are in conflict and boundaries between populations and species are less clear. This study demonstrates that widely-used criteria (phylogenetic placement, genetic divergence, phylogeny- and distance-based species delimitation methods) can overestimate species diversity/boundaries when introgression is present. However, a comprehensive species delimitation framework that considers spatial and genetic population structure, introgression, and the use of species delimitation methods based on parameter estimation, can provide a more accurate characterization of species boundaries in this grey zone. We applied this approach to a group of Southeast Asian frogs from the Pulchrana picturata Complex that exhibits continuous morphological variation and high genetic divergences. Results showed that introgression was rampant among Bornean populations, which led to phylogenetic discordance and an overestimation of species. We suspect that our results do not form an isolated case; and that introgression among cryptic populations, occurring continuously across a wide geographic area (e.g., the topographically complex island of Borneo, and Earths major continents), may be more common than previously thought.

evolutionary biology↗

Impacts of Gut Microbiota on Gender Bias in Intestinal Pro-Inflammatory Immune Phenotype and Systemic Autoimmune Progression in Lupus-prone SNF1 mice

1.The risk of developing systemic lupus erythematosus (SLE) is about 9 times higher among women compared to men. Our recent report, which used (SWRxNZB) F1 (SNF1) mouse model of spontaneous lupus, showed a potential link between immune response initiated in the gut mucosa at juvenile age (sex hormone independent) and SLE susceptibility. Here, this mouse model, we show that gut microbiota contributes to a pro-inflammatory immune response in the intestine and autoimmune progression, primarily in females, leading to an associated gender bias. We found that gut microbiota composition in male and female littermates are significantly different only at adult age and depletion of gut microbes causes suppression of autoimmune progression only in females. In agreement, microbiota depletion suppressed the pro-inflammatory cytokine response of gut mucosa in both juvenile and adult females. In male SNF1 mice, on the other hand, orchidectomy (castration) caused changes in the composition of gut microbiota and a modest acceleration of autoimmune progression. However, cecum microbiota transplantation studies failed to show superior protection of females from autoimmunity by androgen-influenced gut microbiota. Overall, our work shows that microbiota-dependent pro-inflammatory immune response in the gut mucosa of females initiated at juvenile ages and androgen-dependent protection of males contributes to gender differences in the intestinal immune phenotype and systemic autoimmune progression.

immunology↗

Exons, Introns, and UCEs Reveal Conflicting Phylogenomic Signals in a Rapid Radiation of Frogs (Ranidae: Hylarana)

The manuscript titled \"Exons, Introns, and UCEs Reveal Conflicting Phylogenomic Signals in a Rapid Radiation of Frogs (Ranidae: Hylarana)\" has been withdrawn from BioRxiv temporarily. The manuscript has been withdrawn because it utilizes a new protocol for data collection, which has yet not been published. Once the paper describing the new method becomes available for circulation, this manuscript will be resubmitted to BioRxiv. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author.

evolutionary biology↗

An alternative AUG codon that produces an N-terminally extended form of the influenza A virus NP is a virulence factor for a swine-derived virus.

The 2009 influenza A virus (IAV) pandemic (pdm2009) was caused by a swine H1N1 virus with several atypical genetic features. Here, we investigate the origin and significance of an upstream AUG (uAUG) codon in the 5-untranslated region of the NP gene. Phylogeny indicated that the uAUG codon arose in the classical swine IAV lineage in the mid 20th Century, and has become fixed in the current triple reassortant, variant pdm2009 swine IAV and human pdm2009 lineages. Functionally, it supports leaky ribosomal initiation in vitro and in vivo to produce two isoforms of NP: canonical, and a longer \"eNP\". The uAUG codon had little effect on viral gene expression or replication in vitro. However, in both murine and porcine models of IAV infection, removing the uAUG codon gene attenuated pdm2009 virus pathogenicity. Thus, the NP uAUG codon is a virulence factor for swine IAVs with proven zoonotic ability.

microbiology↗

DeepC: Predicting chromatin interactions using megabase scaled deep neural networks and transfer learning.

Understanding 3D genome structure requires high throughput, genome-wide approaches. However, assays for all vs. all chromatin interaction mapping are expensive and time consuming, which severely restricts their usage for large-scale mutagenesis screens or for mapping the impact of sequence variants. Computational models sophisticated enough to grasp the determinants of chromatin folding provide a unique window into the functional determinants of 3D genome structure as well as the effects of genome variation.\n\nA chromatin interaction predictor should work at the base pair level but also incorporate large-scale genomic context to simultaneously capture the large scale and intricate structures of chromatin architecture. Similarly, to be a flexible and generalisable approach it should also be applicable to data it has not been explicitly trained on. To develop a model with these properties, we designed a deep neuronal network (deepC) that utilizes transfer learning to accurately predict chromatin interactions from DNA sequence at megabase scale. The model generalizes well to unseen chromosomes and works across cell types, Hi-C data resolutions and a range of sequencing depths. DeepC integrates DNA sequence context on an unprecedented scale, bridging the different levels of resolution from base pairs to TADs. We demonstrate how this model allows us to investigate sequence determinants of chromatin folding at genome-wide scale and to predict the importance of regulatory elements and the impact of sequence variations.

genomics↗

Impact of oral administration of yeast derived complex dietary-polysaccharide on gut inflammation, microbiota composition, and short-chain fatty acid production

Background{beta}-Glucans (BGs), a group of complex non-digestible polysaccharides, are considered to have beneficial health effects due to their immune modulatory properties and are considered as dietary supplements. However, the impact of oral administration of high-pure, well-defined BGs on gut inflammation, and the influence of intestinal microbiota and short-chain fatty acid (SCFA) on the therapeutic effect are largely unknown.\n\nObjectivesThe aim of this study, using a mouse model of chemical induced colitis, was to investigate the impact of oral administration of high-pure yeast BG (YBG) on the susceptibility to colitis, gut immune function, and structure and function of microbiota.\n\nMethodsTo determine the impact of oral administration of YBG on colitis susceptibility, eight week old C57BL/6 (B6) mice were pre-treated with YBG (250 g/mouse/day) and given dextran sulfate sodium (DSS) in drinking water (2.5% w/v) and examined for the symptoms and features of colitis. To assess the effect of oral administration of YBG on gut mucosa and microbiota structure and function, and gut immune regulation, we determined the microbiota composition, fecal SCFA levels, and intestinal T cell phenotype and cytokine secretion. The role of gut microbiota in YBG treatment induced modulation of gut inflammation and immune function were determined in B6 mice treated with broad-spectrum antibiotic cocktail (1 g/L ampicillin, 0.5 g/L vancomycin, 1 g/L neomycin, and 1 g/L metronidazole) in drinking water.\n\nResultsCompared to untreated mice, B6 mice that received prolonged pre-treatment with YBG showed diminished severity of different features of DSS-induced colitis including overall loss of body weight (P<0.001), shortening of colon (P=0.016) and histopathology (P=0.01). However, high-pure YBG has no beneficial effect in terms of suppressing colitis severity when consumed only during the disease stage. Compared to untreated controls, YBG pre-treated mice showed higher regulatory T cell (Treg) frequencies (P=0.043) in the gut mucosa, a shift in the abundance of gut microbiota towards polysaccharide-fermenting bacterial phyla Bacteroides (P=0.049) and Verrucomicrobia (Mean{+/-}SD: control=13.0{+/-}0.33 vs YBG=10.9.7{+/-}0.69) and diminished Firmicutes (P<0.001) and Proteobacteria (P<0.001), and significantly higher production of SCFA such as acetic acid (P=0.016), propionic acid (P=0.026) and butyric acid (P=0.013). Depletion of gut microbiota in YBG-fed B6 mice using broad spectrum antibiotics caused not only elimination of YBG treatment associated SCFA production and Treg increase, but also profound aggravation of the pathological features of colitis such as loss of body weight (P<0.01) and colonic inflammation (P=0.04) compared to that of YBG treated control mice.\n\nConclusionsOral consumption of high-pure BG promotes a healthy gut homeostasis and immune regulation, and minimizes susceptibility to DSS induced colitis in B6 mice in a microbiota (and microbial SCFA) - dependent manner. On the contrary, YBG consumption when gut mucosa and microbiota are compromised not only reverses this protection but also increases the susceptibility to gut inflammation and disease severity, perhaps through its direct interaction with gut immune cells. In conclusion, while YBG consumption may be beneficial for gut health and to prevent gut inflammation in healthy individuals and under intact microbiota, this immune stimulatory dietary supplement may not have any health benefits in individuals with active gut inflammation and could cause adverse effect in those who are on oral antibiotics.

immunology↗

Using virtual reality and thermal imagery to improve statistical modelling of vulnerable and protected species

Biodiversity loss and sparse observational data mean that critical conservation decisions may be based on little to no information. Emerging technologies, such as airborne thermal imaging and virtual reality, may facilitate species monitoring and improve predictions of species distribution. Here we combined these two technologies to predict the distribution of koalas, specialized arboreal foliovores facing population declines in many parts of eastern Australia. For a study area in southeast Australia, we complemented ground-survey records with presence and absence observations from thermal-imagery obtained using Remotely-Piloted Aircraft Systems. These field observations were further complemented with information elicited from koala experts, who were immersed in 360-degree images of the study area. The experts were asked to state the probability of observing a koala at sites they viewed and to assign each probability a confidence rating. We fit logistic regression models to the ground survey data and the ground plus thermal-imagery survey data and a beta regression model to the expert elicitation data. We then combined parameter estimates from the expert-elicitation model with those from each of the survey models to predict koala presence and absence in the study area. The model that combined the ground, thermal-imagery and expert-elicitation data substantially reduced the uncertainty around parameter estimates and increased the accuracy of classifications (koala presence vs absence), relative to the model based on ground-survey data alone. Our findings suggest that data elicited from experts using virtual reality technology can be combined with data from other emerging technologies, such as airborne thermal-imagery, using traditional statistical models, to increase the information available for species distribution modelling and the conservation of vulnerable and protected species.

ecology↗

Amplification of genomic regions harbouring genes with dose-limiting effects provides selection pressure for acquiring aberrant epigenetic silencing in ovarian cancer

High-grade serous ovarian cancer (HGSOC) feature widespread genomic rearrangements that alter the copy number of genes. Genes for which elevated expression is detrimental to growth may be passengers in rearrangements that increase the copy number of strongly selective driver genes. There would then be selection pressure for compensatory epigenetic silencing of such passenger genes, such as through promoter DNA methylation.\n\nWe have used two independent cohorts of primary HGSOC tumour samples to provide evidence of consistent dosage-compensating promoter methylation (DCPM) genome-wide. Mapping CpG methylation to genomic copy number, we show that bias due to variable tumour cellularity of tissue samples results in false positive associations between methylation and copy number. Adjusting for this bias, we found that approximately 5-10% of all measured promoter CpGs with copy number gain showed a statistically significant increase in methylation. DCPM nullifies the association between increased copy number and increased gene expression. We confirmed a functional basis for selective pressure against over-expressing two candidate passenger genes in the 3q12 locus, as overexpressing either gene reduced spheroid formation efficiency in two HGSOC cell lines. DCPM represents a novel class of specific functional interactions between genetic and epigenetic landscapes of cancers.

cancer biology↗

Linking patterns of genetic variation to processes of diversification in Malaysian torrent frogs (Anura: Ranidae: Amolops): a landscape genomics approach

The interplay between environmental attributes and evolutionary processes can provide valuable insights into how biodiversity is generated, partitioned, and distributed. This study investigates the role of spatial, environmental, and historical factors that could potentially drive diversification and shape genetic variation in Malaysian torrent frogs. Torrent frogs are ecologically conserved, and we hypothesize that this could impose tight constraints on dispersal routes, gene flow, and consequently genetic structure. Moreover, levels of gene flow were shown to vary among populations from separate mountain ranges, indicating that genetic differentiation could be influenced by landscape features. Using genome-wide SNPs in conjunction with landscape variables derived from GIS, we performed distance-based redundancy analyses and variance partitioning to disentangle the effects of isolation-by-distance (IBD), isolation-by-environment (IBE), and isolation-by-colonization (IBC). Our results demonstrated that IBE, contributed minimally to genetic variation. Intraspecific population structure can be largely attributed to IBD, whereas interspecific diversification was primarily driven by IBC. We also detected two distinct population bottlenecks, indicating that speciation events were likely driven by vicariance or founder events.

evolutionary biology↗

Tumor mutational landscape is a record of the pre-malignant state

Chromatin structure has a major influence on the cell-specific density of somatic mutations along the cancer genome. Here, we present a pan-cancer study in which we searched for the putative cancer cell-of-origin of 2,550 whole genomes, representing 32 cancer types by matching their mutational landscape to the regional patterns of chromatin modifications ascertained in 104 normal tissue types. We found that, in almost all cancer types, the cell-of-origin can be predicted solely from their DNA sequences. Our analysis validated the hypothesis that high-grade serous ovarian cancer originates in the fallopian tube and identified distinct origins of breast cancer subtypes. We also demonstrated that the technique is equally capable of identifying the cell-of-origin for a series of 2,044 metastatic samples from 22 of the tumor types available as primaries. Moreover, cancer drivers, whether inherited or acquired, reside in active chromatin regions in the respective cell-of-origin. Taken together, our findings highlight that many somatic mutations accumulate while the chromatin structure of the cell-of-origin is maintained and that this historical record, captured in the DNA, can be used to identify the often elusive cancer cell-of-origin.

genomics↗

Complex dietary-polysaccharide modulates gut immune function and microbiota, and promotes protection from autoimmune diabetes

Since the dietary supplement and prebiotic value of {beta}-glucan-rich products have been widely recognized and the dietary approaches for modulating autoimmunity have been increasingly explored, we assessed the impact of oral administration of high-pure yeast {beta}-glucan (YBG) on gut immune function, microbiota and type 1 diabetes (T1D) using mouse models. Oral administration of this non-digestible complex polysaccharide caused a Dectin-1-dependent immune response involving increased expression of IL10, retinaldehyde dehydrogenase (Raldh) and pro-inflammatory cytokines in the gut mucosa. YBG-exposed intestinal DCs induced/expanded primarily Foxp3+, IL10+ and IL17+ T cells, ex vivo. Importantly, prolonged oral administration of low-dose YBG at pre-diabetic stage suppressed insulitis and significantly delayed the T1D incidence in non-obese diabetic (NOD) mice. Further, prolonged treatment with YBG showed increased Foxp3+ T cell frequencies, and a significant change in the gut microbiota, particularly an increase in the abundance of Bacteroidetes and a decrease in the Firmicute members. Oral administration of YBG, together with Raldh-substrate and {beta}-cell antigen, resulted in a better protection of NOD mice from T1D. These observations suggest that YBG not only has a prebiotic property, but also has an oral tolerogenic-adjuvant-like effect, and these features could be exploited for modulating autoimmunity in T1D.

immunology↗

Derivation of a simple postoperative delirium incidence and severity prediction model

BackgroundDelirium is an important postoperative complication, yet a simple and effective delirium prediction model remains elusive. We hypothesized that the combination of the National Surgical Quality Improvement Program (NSQIP) risk calculator for serious complications (NSQIP-SC) or risk of death (NSQIP-D), and cognitive tests of executive function (Trail Making Test A and B [TMTA, TMTB]), could provide a parsimonious model to predict postoperative delirium incidence or severity.\n\nMethodsData were collected from 100 adults ([&ge;]65yo) undergoing major non-cardiac surgery. In addition to NSQIP-SC, NSQIP-D, TMTA and TMTB, we collected participant age, sex, ASA score, tobacco use, type of surgery, depression, Framingham risk score, and preoperative blood pressure. Delirium was diagnosed with the Confusion Assessment Method (CAM), and the Delirium Rating Scale-R-98 (DRS) was used to assess symptom severity. LASSO and Best Subsets logistic and linear regression were employed in line with TRIPOD guidelines.\n\nResultsThree participants were excluded due to intraoperative deaths (2) and alcohol withdrawal (1). Ninety-seven participants with a mean age of 71.68{+/-}4.55, 55% male (31/97 CAM+, 32%) and a mean Peak DRS of 21.5{+/-}6.40 were analyzed. Of the variables included, only NSQIP-SC and TMTB were identified to be predictors of postoperative delirium incidence (p<0.001, AUROC 0.81, 95% CI: 0.72, 0.90) and severity (p<0.001, Adj. R2: 0.30).\n\nConclusionsIn this cohort, preoperative NSQIP-SC and TMTB were identified as predictors of postoperative delirium incidence and severity. Future studies should verify whether this two-factor model could be used for accurate delirium prediction.

clinical trials↗

Modulation of actin polymerization affects nucleocytoplasmic transport in multiple forms of Amyotrophic Lateral Sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease of unknown etiology. Although defects in nucleocytoplasmic transport (NCT) may be central to the pathogenesis of ALS and other neurodegenerative diseases, the molecular mechanisms modulating the nuclear pore function are still largely unknown. Here we show that genetic and pharmacological modulation of actin polymerization disrupts nuclear pore integrity, nuclear import, and downstream pathways such as mRNA post-transcriptional regulation. Importantly, we demonstrate that modulation of actin homeostasis can rescue nuclear pore instability and dysfunction caused by mutant PFN1 as well as by C9ORF72 repeat expansions, the most common mutations in ALS patients. Collectively, our data link NCT defects to ALS-associated pathology and propose the regulation of actin homeostasis as a novel therapeutic strategy for ALS and other neurodegenerative diseases.

neuroscience↗

An Equivariant Bayesian Convolutional Network predicts recombination hotspots and accurately resolves binding motifs

MotivationConvolutional neural networks (CNNs) have been trememdously successful in many contexts, particularly where training data is abundant and signal-to-noise ratios are large. However, when predicting noisily observed biological phenotypes from DNA sequence, each training instance is only weakly informative, and the amount of training data is often fundamentally limited, emphasizing the need for methods that make optimal use of training data and any structure inherent in the model.\n\nResultsHere we show how to combine equivariant networks, a general mathematical framework for handling exact symmetries in CNNs, with Bayesian dropout, a version of MC dropout suggested by a reinterpretation of dropout as a variational Bayesian approximation, to develop a model that exhibits exact reverse-complement symmetry and is more resistant to overtraining. We find that this model has increased power and generalizability, resulting in significantly better predictive accuracy compared to standard CNN implementations and state-of-art deep-learning-based motif finders. We use our network to predict recombination hotspots from sequence, and identify high-resolution binding motifs for the recombination-initiation protein PRDM9, which were recently validated by high-resolution assays. The network achieves a predictive accuracy comparable to that attainable by a direct assay of the H3K4me3 histone mark, a proxy for PRDM9 binding.\n\nAvailabilityhttps://github.com/luntergroup/EquivariantNetworks\n\nContactrichard.brown@well.ox.ac.uk, gerton.lunter@well.ox.ac.uk\n\nSupplementary informationSupplementary data are available at Bioinformatics online.

genomics↗