Biology subjects

Schuh, A.

Publications and source records attributed to Schuh, A..

At least 19 recordsLinked to original sources

bioRxiv2024

Multiple roles for TFG ring complexes in neuronal cargo trafficking

Pathological variants in Trk-fused gene (TFG) have been implicated in a variety of neurodegenerative conditions. In particular, mutations within its amino-terminal PB1 domain have been suggested to cause hereditary spastic paraplegia (HSP), resulting in progressive lower limb spasticity and weakness. The structural basis for this effect is unknown. Here, we combine X-ray crystallography and cryo-electron microscopy to determine a structural model of TFG, demonstrating the mechanism by which it forms octameric ring complexes. A network of electrostatic and hydrophobic interactions defines the interface between protomers. Moreover, we show that mutations identified previously in HSP patients disrupt this interface, destabilizing octamers, which ultimately leads to axonopathy. Surprisingly, the impacts of these variants are not equivalent in vivo, highlighting the existence of multiple, distinct mechanisms by which TFG mutations contribute to neurodegenerative disease.

biochemistry↗

bioRxiv2024

Loss of pleiotropic regulatory functions in Tannin1, the sorghum ortholog of Arabidopsis master regulator TTG1

Transcriptional master regulators are often targeted to improve plant traits, but antagonistic pleiotropic effects of these regulators can hamper this approach. The Myb-bHLH-WDR (MBW) complex is a broadly-conserved transcriptional regulator affecting pigmentation, biotic stress resistance, and abiotic stress tolerance. We investigated the function of sorghum grain pigmentation regulator Tannin1, the ortholog of Arabidopsis pleiotropic WD40 regulator TTG1, to test for conserved pleiotropic regulatory effects and to better understand the evolution of the MBW complex in Poaceae. We characterized genome-wide differential expression of leaf tissue using RNA sequencing in near-isogenic lines (NILs) that contrasted wildtype Tan1 and loss-of-function tan1-b alleles, under optimal temperature and chilling stress. Notably, Gene Ontology analyses revealed no pathways with differential expression between Tan1 and tan1-b NILs, suggesting that, in contrast to Arabidopsis TTG1, Tannin1 has no pleiotropic regulatory role in leaves. Further, NILs had no visible difference in anthocyanin pigmentation, and no genes with known or expected function in flavonoid synthesis were differentially expressed. Genome-wide, only 18 total genes were differentially expressed between NILs, with six of these genes located inside the NIL introgression region, an observation most parsimoniously explained by cis-regulatory effects unrelated to Tannin1 regulation. Comparing our findings with known function of TTG1 orthologs in maize, rice, and Arabidopsis, we conclude that pleiotropic regulatory function in leaf tissue was likely lost in panicoid grass evolution before the sorghum-maize split. These findings inform future molecular breeding of MBW regulated traits and highlight the benefit of subfunctionalization to relieve pleiotropic constraints.

plant biology↗

bioRxiv2022

Complex genotype-phenotype relationships shape the response to treatment of Down Syndrome Childhood Acute Lymphoblastic Leukaemia

Extensive genetic and epigenetic variegation has been demonstrated in many malignancies. Importantly, their interplay has the potential to contribute to disease progression and treatment resistance. To shed light on the complex relationships between these different sources of intra-tumour heterogeneity, we explored their relative contributions to the evolutionary dynamics of Acute Lymphoblastic Leukemia (ALL) in children with Down syndrome, which has particularly poor prognosis. We quantified the tumour propagating potential of genetically distinct sub-clones using serial transplantation assays and SNP-arrays. While most leukaemias were characterized by a single dominant subclone, others were highly heterogeneous. Importantly, we provide clear and direct evidence that genotypes and phenotypes with functional relevance to leukemic progression and treatment resistance can co-segregate within the disease. Hence, individual genetic lesions can be restricted to well-defined cell immunophenotypes, corresponding to different stages of the leukemic differentiation hierarchy and varied proliferation potentials. As a result of this difference in fitness, which can be accurately quantified via competitive transplantation assays, matching diagnostic, post-treatment, and relapse leukemias can be dominated by different genotypes, including pre-leukemic clones persisting throughout the disease progression and treatment. Intriguingly, plasticity also appears to be a temporally defined property that can segregate with genotype. These results suggest that Down Syndrome ALL should be viewed as a complex matrix of cells exhibiting genetic and epigenetic heterogeneity that foster extensive clonal evolution and competition. Therapeutic intervention reshapes this eco-system and may provide the right conditions for the preferential expansion of selected compartments and subsequently relapse.

cancer biology↗

bioRxiv2021

Structural and functional asymmetry of the neonatal cerebral cortex

Features of brain asymmetry have been implicated in a broad range of cognitive processes; however, their origins are still poorly understood. Using a new left-right symmetric, spatiotemporal cortical surface atlas, we investigated cortical asymmetries in 442 healthy term-born neonates using structural and functional magnetic resonance images from the Developing Human Connectome Project. Cortical asymmetries observed in the term cohort were contextualised in two ways: by comparing them against cortical asymmetries observed in 103 preterm neonates scanned at term-equivalent age, and by comparing structural asymmetries against those observed in 1110 healthy young adults from the Human Connectome Project. Our results demonstrate that the neonatal cortex is markedly asymmetric in both structure and function, and while associations with preterm birth and biological sex were minimal, significant differences exist between birth and adulthood. Although these changes may represent experience-dependent developmental milestones, longitudinal studies across the lifespan are required to fully address these hypotheses.

neuroscience↗

bioRxiv2021

Neonatal multi-modal cortical profiles predict 18-month developmental outcomes

Developmental delays in infanthood often persist, turning into life-long difficulties, and coming at great cost for the individual and community. By examining the developing brain and its relation to developmental outcomes we can start to elucidate how the emergence of brain circuits is manifested in variability of infant motor, cognitive and behavioural capacities. In this study, we examined if cortical structural covariance at birth, indexing coordinated development, is related to later infant behaviour. We included 193 healthy term-born infants from the Developing Human Connectome Project (dHCP). An individual cortical connectivity matrix derived from morphological and microstructural features was computed for each subject (morphometric similarity networks, MSNs) and was used as input for the prediction of behavioural scores at 18 months using Connectome-Based Predictive Modeling (CPM). Neonatal MSNs successfully predicted social-emotional performance. Predictive edges were distributed between and within known functional cortical divisions with a specific important role for primary and posterior cortical regions. These results reveal that multi-modal neonatal cortical profiles showing coordinated maturation are related to developmental outcomes and that network organization at birth provides an early infrastructure for future functional skills.

neuroscience↗

bioRxiv2021

Preterm birth alters the development of cortical microstructure and morphology at term-equivalent age

IntroductionThe dynamic nature and complexity of the cellular events that take place during the last trimester of pregnancy make the developing cortex particularly vulnerable to perturbations. Abrupt interruption to normal gestation can lead to significant deviations to many of these processes, resulting in atypical trajectory of cortical maturation in preterm birth survivors. MethodsWe sought to first map typical cortical micro and macrostructure development using invivo MRI in a large sample of healthy term-born infants scanned after birth (n=270). Then we offer a comprehensive characterisation of the cortical consequences of preterm birth in 78 preterm infants scanned at term-equivalent age (37-44 weeks postmenstrual age). We describe the group-average atypicality, the heterogeneity across individual preterm infants, and relate individual deviations from normative development to age at birth and neurodevelopment at 18 months. ResultsIn the term-born neonatal brain, we observed regionally specific age-associated changes in cortical morphology and microstructure, including rapid surface expansion, cortical thickness increase, reduction in cortical anisotropy and increase in neurite orientation dispersion. By term-equivalent age, preterm infants had on average increased cortical tissue water content and reduced neurite density index in the posterior parts of the cortex, and greater cortical thickness anteriorly compared to term-born infants. While individual preterm infants were more likely to show extreme deviations (over 3.1 standard deviations) from normative cortical maturation compared to term-born infants, these extreme deviations were highly variable and showed very little spatial overlap between individuals. Measures of regional cortical development were associated with age at birth, but not with neurodevelopment at 18 months. ConclusionWe showed that preterm birth alters cortical micro and macrostructural maturation near the time of fullterm birth. Deviations from normative development were highly variable between individual preterm infants.

neuroscience↗

bioRxiv2020

Ligand-induced motions in pentameric ligand-gated ion channels revealed by EPR spectroscopy

Signaling in the brain depends on rapid opening and closing of pentameric ligand-gated ion channels (pLGICs). These proteins are the targets of various clinical drugs and, defects in their function is linked to a variety of diseases including myasthenia, epilepsy and sleep-disorders. While recent high-resolution structures of prokaryotic and eukaryotic pLGICs have shed light on the molecular architecture of these proteins, describing their conformational dynamics in physiological lipids is essential for understanding their function. Here, we used site-directed spin labeling electron paramagnetic resonance (SDSL EPR) spectroscopy and functional channels reconstituted in liposomes to reveal ligand-induced structural changes in the extracellular domain (ECD) of GLIC. Proton-activation caused an inward motion of labeled sites at the top of {beta}-strands ({beta}1, 2, 5, 6, 8) towards the channel lumen, consistent with an agonist-induced inward tilting motion of the ECD. Similar proton-dependent GLIC ECD motions were detected in the presence of a non-activating (gating deficient) mutation, suggesting that the inward tilting of the ECD does not accompany channel opening but is associated with an agonist-induced closed pre-activated channel state. These findings provide new insights into the protein dynamics underlying pLGIC gating transitions.

biophysics↗

bioRxiv2020

TET2 drives 5hmc marking of GATA6 and epigenetically defines pancreatic ductal adenocarcinoma transcriptional subtypes

Background and AimsPancreatic ductal adenocarcinoma (PDAC) is characterised by advanced disease stage at presentation, aggressive disease biology and resistance to therapy resulting in extremely poor five-year survival <10%. PDAC is classified into transcriptional subtypes with distinct survival characteristics, although how these arise is not known. Epigenetic deregulation, rather than genetics, has been proposed to underpin progression but exactly why is unclear and hindered by analysis of clinical samples. MethodsGenome-wide epigenetic mapping of DNA modifications 5-hydroxymethylcytosine (5mc) and 5-hydroxymethylcytosine (5hmc) using oxidative bisulphite sequencing (oxBS). Bioinformatics using iCluster and mutational profiling to identify overlap with transcriptional signatures in FFPE from resected patients and confirmation in vivo. ResultsWe find that more aggressive squamous-like PDAC subtypes result from epigenetic inactivation of loci including GATA6 that promote differentiated classical-pancreatic subtypes. We show that squamous-like PDAC transcriptional subtypes are associated with greater loss of 5hmc due to reduced expression of the 5mc-hydroxylase TET2. Furthermore, we find that SMAD4 directly supports TET2 levels in the pancreas and classical-pancreatic tumors and loss of SMAD4 expression is associated reduced 5hmc, GATA6 and squamous-like tumors. Importantly, enhancing TET2 stability using Metformin and VitaminC/ascorbic acid (AA) restores 5hmc and GATA6 levels, reverting squamous-like tumor phenotypes and WNT-dependence in vitro and in vivo. ConclusionsWe identify epigenetic deregulation of pancreatic differentiation as an underpinning event behind the emergence of transcriptomic subtypes in PDAC. Our data shows that restoring epigenetic control increases biomarkers of classical-pancreatic tumors and raises the possibility that combination of Vitamin C and Metformin may prolong survival in patients with squamous-like pancreatic cancer.

cancer biology↗

bioRxiv2020

Predicting age and clinical risk from the neonatal connectome

The development of perinatal brain connectivity underpins motor, cognitive and behavioural abilities in later life. Diffusion MRI allows the characterisation of subtle inter-individual differences in structural brain connectivity. Individual brain connectivity maps (connectomes) are by nature high in dimensionality and are complex to interpret. Machine learning methods are a powerful tool to uncover properties of the connectome which are not readily visible, and can give us clues as to how and why individual developmental trajectories differ. In this manuscript we used Deep Neural Networks and Random Forests to predict demographic and neurodevelopmental characteristics from neonatal structural connectomes in a large sample of babies (n = 524) from the developing Human Connectome Project. We achieved an accurate prediction of post menstrual age (PMA) at scan in term-born infants (Mean absolute error (MAE) = 0.72 weeks, r = 0.83 and p<0.001). We also achieved good accuracy when predicting gestational age at birth in a cohort of term and preterm babies scanned at term equivalent age (MAE = 2.21 weeks, r = 0.82, p<0.001). We subsequently used sensitivity analysis to obtain feature relevance from our prediction models, with the most important connections for prediction of PMA and GA found to be predominantly thalamocortical. From our models of PMA at scan for infants born at term, we computed a brain maturation index (predicted age minus actual age) of individual preterm neonates and found a significant correlation between this index and motor outcome at 18 months corrected age. Our results demonstrate the applicability of machine learning techniques in analyses of the neonatal connectome, and suggest that a neural substrate for later developmental outcome is detectable at term equivalent age.

neuroscience↗

bioRxiv2020

Individualized characterization of volumetric development in the preterm brain

The diverse cerebral consequences of preterm birth create significant challenges for understanding pathogenesis or predicting later outcome. Instead of focusing on describing effects common to the group, comparing individual infants against robust normative data offers a powerful alternative to study brain maturation. Here we used Gaussian process regression to create normative curves characterising brain volumetric development in 274 term-born infants, modelling for age at scan and sex. We then compared 89 preterm infants scanned at termequivalent age to these normative charts, relating individual deviations from typical volumetric development to perinatal risk factors and later neurocognitive scores. To test generalisability, we used a second independent dataset comprising of 253 preterm infants scanned using different acquisition parameters and scanner. We describe rapid, non-uniform brain growth during the neonatal period. In both preterm cohorts, cerebral atypicalities were widespread, often multiple, and varied highly between individuals. Deviations from normative development were associated with respiratory support, nutrition, birth weight, and later neurocognition, demonstrating their clinical relevance. Group-level understanding of the preterm brain disguise a large degree of individual differences. We provide a method and normative dataset that offer a more precise characterisation of the cerebral consequences of preterm birth by profiling the individual neonatal brain.

neuroscience↗

bioRxiv2020

Short and long-read genome sequencing methodologies for somatic variant detection; genomic analysis of a patient with diffuse large B-cell lymphoma

Recent advances in throughput and accuracy mean that the Oxford Nanopore Technologies (ONT) PromethION platform is a now a viable solution for genome sequencing. Much of the validation of bioinformatic tools for this long-read data has focussed on calling germline variants (including structural variants). Somatic variants are outnumbered many-fold by germline variants and their detection is further complicated by the effects of tumour purity/subclonality. Here, we evaluate the extent to which Nanopore sequencing enables genome-wide detection and analysis of somatic variation. We do this through sequencing tumour and germline genomes for a patient with diffuse B-cell lymphoma and comparing results with 150bp short-read sequencing of the same samples. Calling germline single nucleotide variants (SNVs) from the long-read data achieved good specificity and sensitivity. However, results of somatic SNV calling highlight the need for the development of specialized joint calling algorithms. We find the comparative performance of different tools varies significantly between structural variant types, and suggest long reads are especially advantageous for calling large somatic deletions and duplications. Finally, we highlight the utility of long reads for phasing clinically relevant variants, confirming that a somatic 1.6Mb deletion and a p.(Arg249Met) mutation involving TP53 are oriented in trans.

genetics↗

bioRxiv2020

SAMHD1 limits the efficacy of forodesine in leukaemia by protecting cells against cytotoxicity of dGTP

The anti-leukaemia agent forodesine causes cytotoxic overload of intracellular deoxyguanosine triphosphate (dGTP) but is efficacious only in a subset of patients. We report that SAMHD1, a phosphohydrolase degrading deoxyribonucleoside triphosphates (dNTPs), protected cells against the effects of dNTP imbalances. SAMHD1-deficient cells induced intrinsic apoptosis upon provision of deoxyribonucleosides, particularly deoxyguanosine (dG). Moreover, dG and forodesine acted synergistically to kill cells lacking SAMHD1. Using mass cytometry, we found that these compounds killed SAMHD1-deficient malignant cells from patients with chronic lymphocytic leukaemia (CLL). Normal cells and CLL cells from patients without SAMHD1 mutation were unaffected. We therefore propose to use forodesine as a precision medicine for leukaemia, stratifying patients by SAMHD1 genotype or expression. O_FIG O_LINKSMALLFIG WIDTH=195 HEIGHT=200 SRC="FIGDIR/small/951517v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@69c367org.highwire.dtl.DTLVardef@19be007org.highwire.dtl.DTLVardef@91156corg.highwire.dtl.DTLVardef@1158ec6_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOSupplementary Figure 5.C_FLOATNO Graphical Abstract C_FIG Highlights O_LISAMHD1-deficient cells die upon exposure to deoxyribonucleosides (dNs) C_LIO_LIDeoxyguanosine (dG) is the most toxic dN, inducing apoptosis in cells lacking SAMHD1 C_LIO_LISAMHD1-mutated leukaemic cells can be killed by dG and the PNP-inhibitor forodesine C_LI In BriefSAMHD1 degrades deoxyribonucleoside triphosphates (dNTPs), the building blocks of DNA. Davenne et al. found that SAMHD1 protects cells against dNTP imbalances. Exposure of SAMHD1-deficient cells to deoxyguanosine (dG) results in increased intracellular dGTP levels and subsequent apoptosis. This can be exploited to selectively kill cancer cells that acquired SAMHD1 mutations.

cancer biology↗

bioRxiv2020

Cortical morphology at birth reflects spatio-temporal patterns of gene expression in the fetal brain

Interruption to gestation through preterm birth can significantly impact cortical development and have long-lasting adverse effects on neurodevelopmental outcome. We compared cortical morphology captured by high-resolution, multimodal MRI in n=292 healthy newborn infants (mean age at birth=39.9 weeks) with regional patterns of gene expression in the fetal cortex across gestation (n=156 samples from 16 brains, aged 12 to 37 post-conceptional weeks). We tested the hypothesis that noninvasive measures of cortical structure at birth mirror areal differences in cortical gene expression across gestation, and in a cohort of n=64 preterm infants (mean age at birth = 32.0 weeks), we tested whether cortical alterations observed after preterm birth were associated with altered gene expression in specific developmental cell populations. Neonatal cortical structure was aligned to differential patterns of cell-specific gene expression in the fetal cortex. Principal component analysis of six measures of cortical morphology and microstructure showed that cortical regions were ordered along a principal axis, with primary cortex clearly separated from heteromodal cortex. This axis was correlated to estimated tissue maturity, indexed by differential expression of genes expressed by progenitor cells and neurons; and engaged in stem cell differentiation, neuron migration and forebrain development. Preterm birth was associated with altered regional MRI metrics and patterns of differential gene expression in glial cell populations. The spatial patterning of gene expression in the developing cortex was thus mirrored by regional variation in cortical morphology and microstructure at term, and this was disrupted by preterm birth. This work provides a framework to link molecular mechanisms to noninvasive measures of cortical development in early life and highlights novel pathways to injury in neonatal populations at increased risk of neurodevelopmental disorder.

neuroscience↗

bioRxiv2020

A statistical approach for tracking clonal dynamics in cancer using longitudinal next-generation sequencing data

Tumours are composed of genotypically and phenotypically distinct cancer cell populations (clones), which are subject to a process of Darwinian evolution in response to changes in their local micro-environment, such as drug treatment. In a cancer patient, this process of continuous adaptation can be studied through next-generation sequencing of multiple tumour samples combined with appropriate bioinformatics and statistical methodologies. One family of statistical methods for clonal deconvolution seeks to identify groups of mutations and estimate the prevalence of each group in the tumour, while taking into account its purity and copy number profile. These methods have been used in the analysis of cross-sectional data, as well as for longitudinal data by discarding information on the timing of sample collection. Two key questions are how (in the case of longitudinal data) can we incorporate such information in our analyses and if there is any benefit in doing so. Regarding the first question, we incorporated information on the temporal spacing of longitudinally collected samples into standard non-parametric approaches for clonal deconvolution by modelling the time dependence of the prevalence of each clone as a Gaussian process. This permitted reconstruction of the temporal profile of the abundance of each clone continuously from several sparsely collected samples and without any strong prior assumptions on the functional form of this profile. Regarding the second question, we tested various model configurations on a range of whole genome, whole exome and targeted sequencing data from patients with chronic lymphocytic leukaemia, on liquid biopsy data from a patient with melanoma and on synthetic data. We demonstrate that incorporating temporal information in our analysis improves model performance, as long as data of sufficient volume and complexity are available for estimating free model parameters. We expect that our approach will be useful in cases where collecting a relatively long sequence of tumour samples is feasible, as in the case of liquid cancers (e.g. leukaemia) and liquid biopsies. The statistical methodology presented in this paper is freely available at github.com/dvav/clonosGP.

bioinformatics↗

bioRxiv2020

The Developing Human Connectome Project: typical and disrupted functional connectivity across the perinatal period

The Developing Human Connectome Project (dHCP) is an Open Science project which provides the first large sample of neonatal functional MRI (fMRI) data with high temporal and spatial resolution. This data enables mapping of intrinsic functional connectivity between spatially distributed brain regions under normal and adverse perinatal circumstances, offering a framework to study the ontogeny of large-scale brain organisation in humans. Here, we characterise in unprecedented detail the maturation and integrity of resting-state networks (RSNs) at normal term age in 337 infants (including 65 born preterm). First, we applied group independent component analysis (ICA) to define 11 RSNs in term-born infants scanned at 43.5-44.5 weeks postmenstrual age (PMA). Adult-like topography was observed in RSNs encompassing primary sensorimotor, visual and auditory cortices. Among six higher-order, association RSNs, analogues of the adult networks for language and ocular control were identified, but a complete default mode network precursor was not. Next, we regressed the subject-level datasets from an independent cohort of infants scanned at 37-43.5 weeks PMA against the group-level RSNs to test for the effects of age, sex and preterm birth. Brain mapping in term-born infants revealed areas of positive association with age across four of six association RSNs, indicating active maturation in functional connectivity from 37 to 43.5 weeks PMA. Female infants showed increased connectivity in inferotemporal regions of the visual association network. Preterm birth was associated with striking impairments of functional connectivity across all RSNs in a dose-dependent manner; conversely, connectivity of the superior parietal lobules within the lateral motor network was abnormally increased in preterm infants, suggesting a possible mechanism for specific difficulties such as developmental coordination disorder which occur frequently in preterm children. Overall, we find a robust, modular, symmetrical functional brain organisation at normal term age. A complete set of adult-equivalent primary RSNs is already instated, alongside emerging connectivity in immature association RSNs, consistent with a primary-to-higher-order ontogenetic sequence of brain development. The early developmental disruption imposed by preterm birth is associated with extensive alterations in functional connectivity.

neuroscience↗

bioRxiv2020

Development of Microstructural and Morphological Cortical Profiles in the Neonatal Brain

In the perinatal brain, regional cortical architecture and connectivity lay the foundations for functional circuits and emerging behaviour. Interruptions or atypical development during or before this period may therefore have long-lasting consequences. However, to be able to investigate these deviations, we need a measure of how this architecture evolves in the typically developing brain. To this end, in a large cohort of 241 term-born infants we used Magnetic Resonance Imaging to estimate cortical profiles based on morphometry and microstructure over the perinatal period (37-44 weeks post-menstrual age, PMA). Using the covariance of these profiles as a measure of inter-areal network similarity (Morphometric Similarity Networks; MSN), we clustered these networks into distinct modules. The resulting modules were consistent and symmetric, and corresponded to known functional distinctions, including sensory-motor, limbic and association regions and were spatially mapped onto known cytoarchitectonic tissue classes. Posterior (parietal, occipital) regions became more morphometrically similar with increasing PMA, while peri-cingulate and medial temporal regions became more dissimilar. Network strength was associated with PMA: Within-network similarity increased over PMA suggesting emerging network distinction. These changes in cortical network architecture over an eight-week period are consistent with, and likely underpin, the highly dynamic behavioural and cognitive development occurring during this critical period. The resulting cortical profiles might provide normative reference to investigate atypical early brain development.

neuroscience↗

bioRxiv2019

The developing Human Connectome Project (dHCP) automated resting-state functional processing framework for newborn infants.

The developing Human Connectome Project (dHCP) aims to create a detailed 4-dimensional connectome of early life spanning 20 to 45 weeks post-menstrual age. This is being achieved through the acquisition of multi-modal MRI data from over 1000 in- and ex-utero subjects combined with the development of optimised pre-processing pipelines. In this paper we present an automated and robust pipeline to minimally pre-process highly confounded neonatal resting-state fMRI data, robustly, with low failure rates and high quality-assurance. The pipeline has been designed to specifically address the challenges that neonatal data presents including low and variable contrast and high levels of head motion. We provide a detailed description and evaluation of the pipeline which includes integrated slice-to-volume motion correction and dynamic susceptibility distortion correction, a robust multimodal registration approach, bespoke ICA-based denoising, and an automated QC framework. We assess these components on a large cohort of dHCP subjects and demonstrate that processing refinements integrated into the pipeline provide substantial reduction in movement related distortions, resulting in significant improvements in SNR, and detection of high quality RSNs from neonates. HighlightsO_LIAn automated and robust pipeline to minimally pre-process highly confounded neonatal fMRI data C_LIO_LIIncludes integrated dynamic distortion and slice-to-volume motion correction C_LIO_LIA robust multimodal registration approach which includes custom neonatal templates C_LIO_LIIncorporates an automated and self-reporting QC framework to quantify data quality and identify issues for further inspection C_LIO_LIData analysis of 538 infants imaged at 26-45 weeks post-menstrual age C_LI

neuroscience↗

bioRxiv2019

The diagnostic chronic lymphocytic leukaemia genome by nanopore sequencing

Chronic lymphocytic leukaemia (CLL) is characterised by considerable clinical and biological heterogeneity, with specific recurrent genomic alterations, including TP53 mutations, deletions of chromosome 17p, and IgHV mutational status, impacting on response to chemo-immunotherapy and targeted agents. Consequently, diagnostic screening for these predictive biomarkers is recommended in both national and international clinical guidelines. Current conventional methods, including fluorescent in-situ hybridisation and Sanger sequencing, exhibit shortcomings in terms of cost, speed and sensitivity, and even second-generation sequencing methods encounter technical limitations imposed by short-read lengths and bio-informatics analysis. The MinION platform from Oxford Nanopore Technologies generates exceptionally long (1-100kbp) read lengths in a short period of time and at low cost, making it a good candidate for diagnostic testing. In this paper, we present a nanopore-based CLL-specific screening assay, to simultaneously screen for both TP53 mutations and del17p13.1, as well as determining the IgHV mutation status for a single patient in one sequencing run. We sequenced 11 CLL patients and were able to generate a full diagnostic dataset for all. We identified somatic SNVs and indels in the coding region of TP53, and demonstrate that, following error correction of the data, we could accurately define the somatically hypermutated IgHV region in all patients. We also demonstrated the ability of the MinION platform to detect large-scale genomic deletions through low-coverage whole-genome sequencing. We conclude that nanopore sequencing has the potential to provide accurate, low-cost and rapid diagnostic information, which could be applied to other cancer types.

cancer biology↗