Search bioRxiv⌕ Search

Biology subjects

Baxter, L.

Publications and source records attributed to Baxter, L..

15 recordsLinked to original sources

Unlocking the secrets of paired terminal genomic repeats utilised by the Burkholderia jumbo phage Matilda

Bacteriophages (phages) are viruses that infect bacteria. Jumbo phages have genomes exceeding 220 kb, which can support greater functional independence and complexity. This work identified vB_BceM_Matilda ({phi}Matilda), a novel Burkholderia-targeting jumbo phage. Before injecting its genome into the host bacterium, {phi}Matilda binds to the bacterial flagellum, the rotation of which is required to drive a productive phage infection. Its linear 267 kb dsDNA genome has a previously undescribed tripartite architecture, with bidirectional terminal elements of 1.3 kb and 25 kb, each flanked by distinct inverted repeats of 1.5 kb and 18 kb, respectively. These architectural elements bookend the genome. Transcriptomic and proteomic analyses tracked the phage infection process and confirmed that genes within these terminal elements are transcribed and translated during infection. The presence of bidirectional terminal sequences in related jumbo phages suggests that the tripartite genome architecture may be conserved and functionally important. This work represents the first description of this genome architecture in any organism, expanding our understanding of genome organisation and raising new questions about the replication, packaging, and evolution of jumbo phage genomes.

microbiology↗

What makes a banana false? How the genome of Ethiopian orphan staple Ensete ventricosum differs from the banana A and B sub-genomes

BackgroundEnsete ventricosum, also known as the "tree against hunger" plays a key role in Ethiopian food security and farming systems, feeding more than 20 million people. Since domestication via clonal selection in the south-west Ethiopian highlands, todays diverse enset landraces contribute multiple benefits including food, fibre by-product, animal bedding and cattle fodder to farmers and local communities. Improved genomic resources for this highly drought-tolerant plant are essential to supplement the conventional clonal selection-based breeding programme and pave the way towards targeted breeding. ResultsWe sequenced the genome of enset landrace Mazia, which is partially resistant/tolerant to Xanthomonas wilt and predicted 38,940 protein-coding genes. The Mazia assembly (540.14 Mb) is more complete than the previously published genome assembly of landrace Bedadeti (451.28 Mb) and displayed 1.41% heterozygosity and 64.64% repetitive DNA content. Comparative analyses with the Bedadeti assembly and chromosome-level genome sequences of the two main banana progenitors (Musa acuminata, AA genome; Musa balbisiana, BB genome) unexpectedly revealed [~]25% of the Mazia genome is unique to enset. Gene Ontology (GO) and sequence similarity search analysis of enset-specific protein-coding genes identified distinct functional signatures that underpin the lifestyle, adaptation, and corm productive quality of enset, including functions related to DNA integration, carbohydrate metabolism, disease resistance and transcriptional regulation. In contrast, Musa-specific genes showed enrichment for defence response, protein phosphorylation and fruit development pathways. Focusing on the classical nucleotide binding site leucine rich repeat (NLR) disease resistance genes, we identified and characterised NLRs in enset and Musa species genomes, revealing a considerable expansion in the Musa acuminata genome. We also identified unique genes in enset and banana genomes whose functional and evolutionary roles are yet to be determined. ConclusionsHere, we report a de novo genome assembly for the enset (Ensete ventricosum) landrace Mazia and provide a high-quality annotation of both Mazia and the previously published assembly of the landrace Bedadeti. Collectively, these genomic resources provide a valuable foundation for comparative genomics within the Musaceae family and open new opportunities for the development of marker-assisted breeding strategies to accelerate the improvement of agronomically important traits in enset.

bioinformatics↗

EnteroBase in 2025: exploring the genomic epidemiology of bacterial pathogens

This paper presents an update on the content, accessibility and analytical tools of the EnteroBase platform for web-based pathogen genome analysis. EnteroBase provides manually curated databases of genome sequence data and associated metadata from currently >1.1 million bacterial isolates, more recently including Streptococcus spp. and Mycobacterium tuberculosis. We have implemented the genome-based detection of antimicrobial resistance determinants and the new bubble plot graphical tool for visualising bacterial genomic population structures, based on pre-computed hierarchical clusters. Access to data and analysis tools is provided through an enhanced graphical user interface and a new application programming interface (RESTful API). EnteroBase is now being developed and operated by an international consortium, to accelerate the development of the platform and ensure the longevity of the resources built. EnteroBase can be accessed at https://enterobase.warwick.ac.uk as well as https://enterobase.dsmz.de. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/608032v1_ufig1.gif" ALT="Figure 1"> View larger version (31K): org.highwire.dtl.DTLVardef@88ff78org.highwire.dtl.DTLVardef@3c426eorg.highwire.dtl.DTLVardef@2d8481org.highwire.dtl.DTLVardef@5644bb_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

Apnoea suppresses brain activity in infants

Apnoea - the cessation of breathing - is commonly observed in premature infants. These events can reduce cerebral oxygenation and are associated with poorer neurodevelopmental outcomes. However, relatively little is known about how apnoea and shorter pauses in breathing impact brain function in infants, which will provide greater mechanistic understanding of how apnoea affects brain development. We analysed simultaneous recordings of respiration, electroencephalography (EEG), heart rate, and peripheral oxygen saturation in 124 recordings from 118 infants (post-menstrual age: 38.6 {+/-} 2.7 weeks [mean {+/-} standard deviation]) during apnoeas (pauses in breathing greater than 15 seconds) and shorter pauses in breathing between 5 and 15 seconds. EEG amplitude significantly decreased during both apnoeas and shorter pauses in breathing compared with normal breathing periods. Change in EEG amplitude was significantly associated with change in heart rate during apnoea and breathing pauses and, during apnoeas only, with oxygen saturation change. No associations were found between EEG amplitude and pause duration or post-menstrual age. The decrease in EEG amplitude may be a result of the changing metabolism and/or homeostasis following changes in oxygen and carbon dioxide concentrations, which alters the release of neurotransmitters. As apnoeas often occur in premature infants, frequent disruption to brain activity may impact neural development and result in long-term neurodevelopmental consequences.

neuroscience↗

Sensory event-related potential morphology predicts age in premature infants

Preterm infants undergo substantial neurosensory development in the first weeks after birth. Infants born prematurely are more likely to have long-term adverse neurological outcomes and early detection of abnormal brain development is essential for timely interventions. We investigated whether sensory-evoked cortical potentials could be used to accurately estimate the age of an infant. Such a model could be used to identify infants who deviate from normal neurodevelopment by comparing the brain age to the infants postmenstrual age (PMA). Infants aged between 28- and 40-weeks PMA from a training and test sample (consisting of 101 and 65 recording sessions in 82 and 14 infants, respectively) received trains of approximately 10 visual and 10 tactile stimuli (interstimulus interval approximately 10 seconds). PMA could be predicted accurately from the magnitude of the evoked responses (training set mean absolute error (MAE and 95% confidence intervals): 1.41 [1.14; 1.74] weeks, p = 0.0001; test set MAE: 1.55 [1.21; 1.95] weeks, p = 0.0002. Moreover, we show with two examples that brain age, and the deviations between brain age and PMA, may be biologically and clinically meaningful. By firstly demonstrating that brain age is correlated with a measure known to relate to maturity of the nervous system (based on animal and human literature, the magnitude of reflex withdrawal is used) and secondly by linking brain age to long-term neurological outcomes, we show that brain age deviations are related to biologically meaningful individual differences in the rate of functional nervous system maturation rather than noise generated by the model. In summary, we demonstrate that sensory-evoked potentials are predictive of age in premature infants. It takes less than 5 minutes to collect the stimulus electroencephalographic data required for our model, hence, increasing its potential utility in the busy neonatal care unit. This model could be used to detect abnormal development of infants response to sensory stimuli in their environment and may be predictive of later life abnormal neurodevelopmental outcome.

neuroscience↗

Brain age as an estimator of neurodevelopmental outcome: A deep learning approach for neonatal cot-side monitoring

The preterm neonate can experience stressors that affect the rate of brain maturation and lead to long-term neurodevelopmental deficits. However, some neonates who are born early follow normal developmental trajectories. Extraction of data from electroencephalography (EEG) signals can be used to calculate the neonates brain age which can be compared to their true age. Discrepancies between true age and brain age (the brain age delta) can then be used to quantify maturational deviation, which has been shown to correlate with long-term abnormal neurodevelopmental outcomes. Nevertheless, current brain age models that are based on traditional analytical techniques are less suited to clinical cot-side monitoring due to their dependency on long-duration EEG recordings, the need to record activity across multiple EEG channels, and the manual calculation of predefined EEG features which is time-consuming and may not fully capture the wealth of information in the EEG signal. In this study, we propose an alternative deep-learning approach to determine brain age, which operates directly on the EEG, using a Convolutional Neural Network (CNN) block based on the Inception architecture (called Sinc). Using this deep-learning approach on a dataset of preterm infants with normal neurodevelopmental outcomes (where we assume brain age = postmenstrual age), we can calculate infant brain age with a Mean Absolute Error (MAE) of 0.78 weeks (equivalent to a brain age estimation error for the infant within +/- 5.5 days of their true age). Importantly, this level of accuracy can be achieved by recording only 20 minutes of EEG activity from a single channel. This compares favourably to the degree of accuracy that can be achieved using traditional methods that require long duration recordings (typically >2 hours of EEG activity) recorded from a higher density 8-electrode montage (MAE = 0.73 weeks). Importantly, the deep learning models brain age deltas also distinguish between neonates with normal and severely abnormal outcomes (Normal MAE = 0.71 weeks, severely abnormal MAE = 1.27 weeks, p=0.02, one-way ANOVA), making it highly suited for potential clinical applications. Lastly, in an independent dataset collected at an independent site, we demonstrate the models generalisability in age prediction, as accurate age predictions were also observed (MAE of 0.97 weeks). HighlightsO_LIPreterm stress exposure leads to long-term neurodevelopmental deficits C_LIO_LIDeficits are quantifiable using EEG-based brain age prediction errors C_LIO_LIOur deep-learning solution for brain age prediction outperforms previous approaches C_LIO_LIPredictions are achieved with only 20 mins EEG and a single bipolar channel C_LIO_LIPrediction errors correlate with long-term Bayley scale neurodevelopmental outcomes C_LI

neuroscience↗

Concurrent mapping of brain ontogeny and phylogeny within a common connectivity space

Developmental and evolutionary effects on brain organisation are complex, yet linked, as evidenced by the striking correspondence in cortical expansion changes. However, it is still not possible to study concurrently the ontogeny and phylogeny of cortical areal connections, which is arguably more relevant to brain function than allometric changes. Here, we propose a novel framework that allows the integration of connectivity maps from humans (adults and neonates) and non-human primates (macaques) onto a common space. We use white matter bundles to anchor the definition of the common space and employ the uniqueness of the areal connection patterns to these bundles to probe areal specialisation. This enables us to quantitatively study divergences and similarities in cortical connectivity over both evolutionary and developmental scales. It further allows us to map brain maturation trajectories, including the effect of premature birth, and to translate cortical atlases between diverse brains.

neuroscience↗

Sex-Related Neurocircuitry Supporting Camouflaging in Adults with Autism: Female Protection Insights

The male preponderance in autism led to the hypothesis that aspects of female biology are protective against autism. Females with autism report engaging in more compensatory behaviors (i.e., "camouflaging") to overcome autism-related social differences, which may be a downstream result of protective pathways. No studies have examined sex-related brain pathways supporting camouflaging in females with autism, despite its potential to inform mechanisms underlying the sex bias in autism. This case-control design included 45 non-intellectually-disabled adults with autism (male/female: 21/24) and 40 neurotypical adults (male/female: 19/21) ages 18-71. We used group multivariate voxel pattern analysis to conduct a data-driven, connectome-wide characterization of "sex-atypical" (sex-by-diagnosis) and "sex-typical" (sex) brain functional connectivity features linked to camouflaging, and validated findings in females with autism multi-modally via structural connectometry. Exploratory associations with cognitive control, memory, emotion recognition, and depression/anxiety examined the adaptive nature of functional connectivity patterns supporting camouflaging in females with autism. We found 1) "sex-atypical" functional connectivity patterns predicting camouflaging in the hypothalamus and precuneus and 2) "sex-typical" patterns in the anterior cingulate and right anterior parahippocampus. Higher hypothalamic functional connectivity with a limbic reward cluster was the strongest predictor of camouflaging in females with autism (a "sex-atypical" pattern), and also predicted better cognitive control/emotion recognition. Structural connectometry validated functional connectivity results with consistent brain pathways/effect patterns implicated across multi-modal findings in females with autism. This data-driven, connectome-wide characterization of "sex-atypical" and "sex-typical" brain connectivity features supporting compensatory social behavior in autism suggests hormones may play a role in the autism sex bias. Furthermore, both "male-typical" and "female-typical" brain connectivity patterns are implicated in camouflaging in females with autism in circuits associated with reward, emotion, and memory processing. "Sex-atypical" results are consistent with the fetal steroidogenic hypothesis, which would result in masculinized brain features in females with autism. However, female genetics/biology may contribute to "female-typical" patterns implicated in camouflaging.

neuroscience↗

The Forget-Me-Not dHCP study: 7 Tesla high resolution diffusion imaging in the unfixed post-mortem neonatal brain

Diffusion MRI of the neonatal brain allows investigation of the organisational structure of maturing fibres during brain development. Post-mortem imaging has the potential to achieve high resolution by using long scan times, enabling precise assessment of small structures. The Forget-Me-Not study, part of the Developing Human Connectome Project (dHCP), aims to acquire and publicly distribute high-resolution diffusion MRI data for unfixed post-mortem neonatal brain at 7T with a custom-built head coil. This paper describes how the study addressed logistical, technical and ethical challenges relating to recruitment pipeline, care pathway, tissue preservation, scan setup and protocol optimisation. Results from the first subject recruited to the study demonstrate high-quality diffusion MRI data. Preliminary voxel-wise and tractography-based analyses are presented for the cortical plate, subplate and white matter pathways, with comparison to age-matched in vivo dHCP data. These results demonstrate that high quality post-mortem data can be acquired and provide a sensitive means to explore the developing human brain, as well as altered diffusion properties consistent with post-mortem changes, at high resolution.

bioengineering↗

Functional and diffusion MRI reveal the functional and structural basis of infants' noxious-evoked brain activity

Understanding the neurophysiology underlying pain perception in infants is central to improving early life pain management. In this multimodal MRI study, we use resting-state functional and white matter diffusion MRI to investigate individual variability in infants noxious-evoked brain activity. In an 18-infant nociception-paradigm dataset, we show it is possible to predict infants cerebral haemodynamic responses to experimental noxious stimulation using their resting-state activity across nine networks from a separate stimulus-free scan. In an independent 215-infant Developing Human Connectome Project dataset, we use this resting-state-based prediction model to generate noxious responses. We identify a significant correlation between these predicted noxious responses and infants white matter mean diffusivity, and this relationship is subsequently confirmed within our nociception-paradigm dataset. These findings reveal that a newborn infants pain-related brain activity is tightly coupled to both their spontaneous resting-state activity and underlying white matter microstructure. This work provides proof-of-concept that knowledge of an infants functional and structural brain architecture could be used to predict pain responses, informing infant pain management strategies and facilitating evidence-based personalisation of care.

neuroscience↗

Inferring the infant pain experience: a translational fMRI-based signature approach

BackgroundIn the absence of verbal communication it is challenging to infer an individuals sensory and emotional experience. In adults, fMRI has been used to develop multivariate brain activity signatures, which reliably capture elements of human pain experience. We translate whole-brain fMRI signatures that encode pain perception in adults to the newborn infant brain, to advance understanding of functional brain development and pain perception in early life. MethodsA cohort of adults (n=10; mean age=28.3 years) and 2 cohorts of healthy infants (Cohort A: n=15; Cohort B: n=22; mean postnatal age=3 days) were stimulated with low intensity nociceptive stimuli (64-512mN) during acquisition of functional MRI data. fMRI pain signatures were applied directly to the adult data and transformed such that they could be applied to the infant brain. In each cohort, we assessed the concordance of the signatures with the brain responses using cosine-similarity scores, and we assessed stimulus intensity encoding of the signature responses using Spearman rank correlation. Brain activity in pro-pain and anti-pain brain regions were also examined. FindingsThe Neurologic Pain Signature (NPS), which reflects aspects of nociceptive pain experience, was activated in both the adults and infants, and reliably encoded stimulus intensity. However, the Stimulus Intensity Independent Pain Signature (SIIPS1), which reflects higher-level cognitive modulation of nociceptive input, was only expressed in adults. Pro-pain brain regions showed similar activation patterns in adults and infants, whereas, anti-pain brain regions exhibited divergent responses. InterpretationBasic intensity encoding of nociceptive information is similar in adults and infants. However, translation of adult brain signatures into infants reveals significant differences in infant cerebral processing of nociceptive information, which may reflect their lack of expectation, motivation and contextualisation. This study expands the use of brain activity pain signatures to non-verbal patients and provides a potential approach to assess analgesic interventions in infancy. FundingThis work was funded by Wellcome (Senior Research Fellowship awarded to Prof. Rebeccah Slater) and SSNAP "Support for Sick and Newborn Infants and their Parents" Medical Research Fund (University of Oxford Excellence Fellowship awarded to Dr Eugene Duff). Research in contextO_ST_ABSEvidence before this studyC_ST_ABSWe searched PubMed for research articles published prior to March 2020 using terms including fMRI, infant or neonate, and pain or nociception in the title or abstract. Due to the relatively new emergence of this field, and the experimental and analytical challenges involved in studying cerebral processing of pain in the MRI environment in healthy newborn infants, only five fMRI studies have examined infant brain responses to nociceptive input. In a foundational pilot study, Williams et al., applied an experimental noxious stimulus to a single infant, evoking widespread brain activity that included several brain regions involved in pain processing in adults. Goksan et al., subsequently performed an observational cohort study and used regional analyses to compare active brain regions in infants (n=10) and adults (n=10), concluding that the evoked patterns of brain activity were broadly similar in infants and adults. Further follow-up analysis in the infant cohort revealed that the functional connectivity of brain regions involved in descending pain modulation influences the magnitude of pain-related brain activity. Two further studies focused on methodological advances, providing evidence-based recommendations for fMRI acquisition parameters and image processing in order to maximise the quality of infant data, and these methods have been implemented in this study. Added value of this studyThis study translates validated adult pain fMRI brain signatures to a nonverbal patient population in which the assessment and management of pain presents a significant clinical challenge. Application of fMRI brain signatures to newborn infants expands on previous fMRI studies that provided only qualitative evidence that noxious stimulation commonly activates brain regions in the adult and infant brain. Here we demonstrate that the basic encoding of the sensory discriminative aspects of pain, as represented by the Neurologic Pain Signature (NPS), occurs in both adults and infants, whereas higher-level cognitive modulation of pain, represented by the Stimulus Intensity Independent Pain Signature (SIIPS1) is only present in adults and not observed in infants. The differences in how the immature infant brain processes pain, relative to the mature adult brain, are likely to reflect differences in their expectation, motivation and contextualisation of external events rather than differences in their core nociceptive cerebral processing of pain. This work allows us to use quantitative fMRI observations to make stronger inferences related to pain experience in nonverbal infants. Implications of all the available evidenceBehavioural pain scores used in neonatal clinical care offer limited sensitivity and specificity to pain. Neonatal clinical trials that use these scores as outcome measures frequently report a lack of efficacy of common analgesic interventions, resulting in few evidence-based drugs for treating pain. The value of using brain-based neuroimaging markers of pain as a means of providing objective evidence of analgesic efficacy in early proof of concept studies is well recognised in adults, even in the absence of behavioural pain modulation. Similarly, in infants EEG-based measures of noxious-evoked brain activity have been used as outcome measures in clinical trials of analgesics to overcome some of the inherent limitations of using behavioural observations to quantify analgesic efficacy. Considering the successful translation of the Neurologic Pain Signature (NPS) and its sensitivity to analgesic modulation in adults, this novel methodology represents an objective brain-based fMRI approach that could be used to advance the discovery and assessment of analgesic interventions in infancy.

neuroscience↗

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↗

Motor cortex can modulate somatosensory processing via cortico-thalamo-cortical pathway

The somatosensory and motor systems are intricately linked, providing several routes for the sensorimotor interactions necessary for haptic processing. Here, we used electrical and optogenetic stimulation to study the circuits that enable primary motor cortex (M1) to exert top-down modulation of whisker-evoked responses, at the levels of brain stem, thalamus and somatosensory cortex (S1). We find that activation of M1 drives somatosensory responsive cells at all levels, and that this excitation is followed by a period of tactile suppression, which gradually increases in strength along the ascending somatosensory pathway. Using optogenetic stimulation in the layer-specific Cre driver lines, we find that activation of layer VI cortico-thalamic neurons is sufficient to drive spiking in higher order thalamus, and that this is reliably followed by excitation of S1, suggesting a cross-modal cortico-thalamo-cortical pathway. Cortico-thalamic excitation predicts the degree of subsequent tactile suppression, consistent with a strong role for thalamic circuits in the expression of inhibitory sensorimotor interactions. These results provide evidence of a role for M1 in dynamic modulation of S1, largely under cortico-thalamic control.

neuroscience↗

Comparative genomics of Pseudomonas syringae reveals convergent gene gain and loss associated with specialisation onto cherry (Prunus avium)

O_LIGenome-wide analyses of the effector- and toxin-encoding genes were used to examine the phylogenetics and evolution of pathogenicity amongst diverse strains of Pseudomonas syringae causing bacterial canker of cherry (Prunus avium) including pathovars P.s pv. morsprunorum (Psm) races 1 and 2, P.s pv. syringae (Pss) and P.s pv. avii.\nC_LIO_LIGenome-based phylogenetic analyses revealed Psm races and P.s pv. avii clades were distinct and were each monophyletic, whereas cherry-pathogenic strains of Pss were interspersed amongst strains from other host species.\nC_LIO_LIA maximum likelihood approach was used to predict effectors associated with host specialisation on cherry. Pss possesses a smaller repertoire of type III effectors but has more toxin biosynthesis clusters compared with Psm and P.s pv. avii. Evolution of cherry pathogenicity was correlated with gain of genes such as hopAR1 and hopBB1 through putative phage transfer and horizontal transfer, respectively. By contrast, loss of the avrPto/hopAB redundant effector group was observed in cherry-pathogenic clades. Ectopic expression of hopAB and hopC1 triggered the hypersensitive reaction in cherry leaves, confirming computational predictions.\nC_LIO_LICherry canker provides a fascinating example of convergent evolution of pathogenicity that is explained by the mix of effector and toxin repertoires acting on a common host.\nC_LI

microbiology↗

Pangenomic analysis reveals pathogen-specific regions and novel effector candidates in Fusarium oxysporum f.sp. cepae

A reference-quality assembly of Fusarium oxysporum f. sp. cepae (Foc), the causative agent of onion basal rot has been generated along with genomes of additional pathogenic and non-pathogenic isolates. Phylogenetic analysis confirmed a single origin of the Foc pathogenic lineage.\n\nGenome alignments with other F. oxysporum ff. spp. and non pathogens revealed high levels of syntenic conservation of core chromosomes but little synteny between lineage specific (LS) chromosomes. Four LS contigs in Foc totaling 3.9 Mb were designated as pathogen-specific (PS). A two-fold increase in segmental duplication events was observed between LS regions of the genome compared to within core regions or from LS regions to the core.\n\nRNA-seq expression studies identified candidate effectors expressed in planta, consisting of both known effector homologs and novel candidates. FTF1 and a subset of other transcription factors implicated in regulation of effector expression were found to be expressed in planta.

pathology↗