Biology subjects

Zhou, X.

Publications and source records attributed to Zhou, X..

At least 613 records · Page 34Linked to original sources

bioRxiv2020

A novel bioinformatics approach to reveal the role of circadian oscillations in AD development

Altered circadian gene expression may contribute to Alzheimers disease (AD) progression. Unfortunately, sampling the central nervous system (CNS) at multiple time points is not feasible. Moreover, there are no AD-related time-series transcriptome datasets available for studying these circadian patterns and their impacts on AD development. In this study, we introduce a novel computational platform, Event-driven Sample Ordering for Circadian Variation Detection (ESOCVD), to reveal rhythmic patterns of gene expression of AD using untimed transcriptome datasets. ESOCVD was applied to 20 untimed gene expression profiles of 16 brain regions from approximately 3000 AD patients in public transcriptome databases. Our analysis revealed five types of circadian alteration patterns in ~2,000 circadian genes in different brain regions of AD patients. Further analyses of additional databases confirmed that our analytical platform can be applied to identify the evolutionary dynamics of circadian variation during the process of AD development. Through the gene expression correlation analysis for our 8 circadian genes identified from AMP-AD MSBB cohorts, we identified stage-specifically enriched biological processes with anticipated context. Gene expression analysis of AD mouse brain tissues further substantiated the predictions of the ESOCVD model. In summary, ESOCVD is highly versatile in bridging circadian research and precision medicine.

bioinformatics↗

bioRxiv2020

De novo characterization of cell-free DNA fragmentation hotspots boosts the power for early detection and localization of multi-cancer

Non-random cell-free DNA fragmentation is a promising signature for cancer diagnosis. However, its aberration at the fine-scale in early-stage cancers is poorly understood. Here, we developed an approach to de novo characterize the cell-free DNA fragmentation hotspots from whole-genome sequencing. In healthy, hotspots are enriched in gene-regulatory elements, including open chromatin regions, promoters, hematopoietic-specific enhancers, and, interestingly, 3end of transposons. Hotspots identified in early-stage hepatocellular carcinoma patients showed overall hypo-fragmentation patterns compared to healthy controls. These cancer-specific hypo-fragmented hotspots are associated with genes enriched in gene ontologies and KEGG pathways that are related to the initiations of hepatocellular carcinoma and cancer stem cells. Further, we identified the fragmentation hotspots at 297 cancer samples across 8 different cancer types (92% in stage I to III), 103 benign samples, and 247 healthy samples. The fine-scale fragmentation level at most variable hotspots showed cancer-specific fragmentation patterns across multiple cancer types and non-cancer controls. With the fine-scale fragmentation signals alone in a machine learning model, we achieved 48% to 95% sensitivity at 100% specificity in different early-stage cancer. We further validated the model at independent datasets we generated at a small number of early-stage cancers and healthy plasma samples with matched age, gender, and lifestyle. In cancer-positive cases, we further localized cancer to a small number of anatomic sites with a median of 80% accuracy. The results highlight the significance of de novo characterizing the cell-free DNA fragmentation hotspots for detecting early-stage cancers and dissection of gene-regulatory aberrations in cancers.

genomics↗

bioRxiv2020

How old are dragonflies and damselflies? Odonata (Insecta) transcriptomics resolve familial relationships

Dragonflies and damselflies, representing the insect order Odonata, are among the earliest flying insects with living (extant) representatives. However, unravelling details of their long evolutionary history, such as egg laying (oviposition) strategies, is impeded by unresolved phylogenetic relationships, an issue particularly prevalent in damselfly families and fossil lineages. Here we present the first transcriptome-based phylogenetic reconstruction of Odonata, analyzing 2,980 protein-coding genes in 105 species representing nearly all of the orders families (except Austropetaliidae and Neopetaliidae). All damselfly families and most dragonfly families are recovered as monophyletic groups. Our Molecular clock estimates suggest that crown-Zygoptera (damselflies) and -Anisoptera (dragonflies) both arose during the late Triassic. Several of the observed long inner branches in our topology are indicative of the extinction of once flourishing lineages. We also find that exophytic egg laying behaviour with a reduced ovipositor evolved in certain dragonflies during the late Jurassic / early Cretaceous. Lastly, we find that certain fossils have an unexpected deterring impact in divergence dating analysis.

evolutionary biology↗

bioRxiv2020

Multi-scale Genomic Inference using Biologically Annotated Neural Networks

In this article, we present Biologically Annotated Neural Networks (BANNs), a nonlinear probabilistic framework for association mapping in genome-wide association (GWA) studies. BANNs are feedforward models with partially connected architectures that are based on biological annotations. This setup yields a fully interpretable neural network where the input layer encodes SNP-level effects, and the hidden layer models the aggregated effects among SNP-sets. We treat the weights and connections of the network as random variables with prior distributions that reflect how genetic effects manifest at different genomic scales. The BANNs software uses variational inference to provide posterior summaries which allow researchers to simultaneously perform (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets on complex traits. Through simulations, we show that our method improves upon state-of-the-art association mapping and enrichment approaches across a wide range of genetic architectures. We then further illustrate the benefits of BANNs by analyzing real GWA data assayed in approximately 2,000 heterogenous stock of mice from the Wellcome Trust Centre for Human Genetics and approximately 7,000 individuals from the Framingham Heart Study. Lastly, using a random subset of individuals of European ancestry from the UK Biobank, we show that BANNs is able to replicate known associations in high and low-density lipoprotein cholesterol content. Author SummaryA common goal in genome-wide association (GWA) studies is to characterize the relationship between genotypic and phenotypic variation. Linear models are widely used tools in GWA analyses, in part, because they provide significance measures which detail how individual single nucleotide polymorphisms (SNPs) are statistically associated with a trait or disease of interest. However, traditional linear regression largely ignores non-additive genetic variation, and the univariate SNP-level mapping approach has been shown to be underpowered and challenging to interpret for certain trait architectures. While nonlinear methods such as neural networks are well known to account for complex data structures, these same algorithms have also been criticized as "black box" since they do not naturally carry out statistical hypothesis testing like classic linear models. This limitation has prevented nonlinear regression approaches from being used for association mapping tasks in GWA applications. Here, we present Biologically Annotated Neural Networks (BANNs): a flexible class of feedforward models with partially connected architectures that are based on biological annotations. The BANN framework uses approximate Bayesian inference to provide interpretable probabilistic summaries which can be used for simultaneous (i) mapping with SNPs and (ii) enrichment analyses with SNP-sets (e.g., genes or signaling pathways). We illustrate the benefits of our method over state-of-the-art approaches using extensive simulations. We also demonstrate the ability of BANNs to recover novel and previously discovered genomic associations using quantitative traits from the Wellcome Trust Centre for Human Genetics, the Framingham Heart Study, and the UK Biobank.

genetics↗

bioRxiv2020

Environment-conditioned male fertility of HD-ZIP IV transcription factor mutant ocl4: impact on 21-nt phasiRNA accumulation in pre-meiotic maize anthers

Environment-conditioned genic male sterility is a key strategy used to produce hybrid seeds efficiently in many crops, with the exception of maize. The underlying molecular mechanisms of environment-conditioned sterility are poorly understood. Here, we report a derivative line of the male sterile outer cell layer 4 (ocl4) mutant of maize, in which fertility was restored and perpetuated over several generations, under warm growing conditions. Conditionally fertile ocl4 anthers exhibit the anatomical abnormality of a partially duplicated endothecial layer, just like their sterile counterparts. We profiled the dynamics of phased, small interfering RNAs (phasiRNAs) during pre-meiotic development in fully sterile and various grades of semi-fertile ocl4 anthers. We found that the biogenesis of 21-nt phasiRNAs is largely dependent on Ocl4 at three key steps: (1) production of PHAS precursor transcripts, (2) expression of miR2118 that modulates precursor processing, and (3) accumulation of 21-nt phasiRNAs. We propose that 21-nt reproductive phasiRNAs buffer development under unfavorable environmental conditions and are dispensable under favorable conditions.Competing Interest StatementThe authors have declared no competing interest.View Full Text

plant biology↗

bioRxiv2020

The genome of North American beaver provides insights into the mechanisms of its longevity and cancer resistance

The North American beaver (Castor canadensis) is an exceptionally long-lived and cancer-resistant rodent species, and thus an excellent model organism for comparative genomic studies of longevity. Here, we utilize a significantly improved beaver genome assembly to assess evolutionary changes in gene coding sequences, copy number, and expression. We found that the beaver Aldh1a1, a stem cell marker gene encoding an enzyme required for detoxification of ethanol and aldehydes, is expanded (~10 copies vs. two in mouse and one in human). We also show that the beaver cells are more resistant to ethanol, and beaver liver extracts show higher ability to metabolize aldehydes than the mouse samples. Furthermore, Hpgd, a tumor suppressor gene, is uniquely duplicated in the beaver among rodents. Our evolutionary analysis identified beaver genes under positive selection which are associated with tumor suppression and longevity. Genes involved in lipid metabolism show positive selection signals, changes in copy number and altered gene expression in beavers. Several genes involved in DNA repair showed a higher expression in beavers which is consistent with the trend observed in other long-lived mammals. In summary, we identified several genes that likely contribute to beaver longevity and cancer resistance, including increased ability to detoxify aldehydes, enhanced tumor suppression and DNA repair, and altered lipid metabolism.

genomics↗

bioRxiv2020

Molecular evolution of SARS-CoV-2 structural genes: evidence of positive selection in spike glycoprotein

SARS-CoV-2 caused a global pandemic in early 2020 and has resulted in more than 8,000,000 infections as well as 430,000 deaths in the world so far. Four structural proteins, envelope (E), membrane (M), nucleocapsid (N) and spike (S) glycoprotein, play a key role in controlling the entry into human cells and virion assembly of SARS-CoV-2. However, how these genes evolve during its human to human transmission is largely unknown. In this study, we screened and analyzed roughly 3090 SARS-CoV-2 isolates from GenBank database. The distribution of the four gene alleles is determined:16 for E, 40 for M, 131 for N and 173 for S genes. Phylogenetic analysis shows that global SARS-CoV-2 isolates can be clustered into three to four major clades based on the protein sequences of these genes. Intragenic recombination event isnt detected among different alleles. However, purifying selection has conducted on the evolution of these genes. By analyzing full genomic sequences of these alleles using codon-substitution models (M8, M3 and M2a) and likelihood ratio tests (LRTs) of codeML package, it reveals that codon 614 of S glycoprotein has subjected to strong positive selection pressure and a persistent D614G mutation is identified. The definitive positive selection of D614G mutation is further confirmed by internal fixed effects likelihood (IFEL) and Evolutionary Fingerprinting methods implemented in Hyphy package. In addition, another potential positive selection site at codon 5 in the signal sequence of the S protein is also identified. The allele containing D614G mutation has undergone significant expansion during SARS-CoV-2 global pandemic, implying a better adaptability of isolates with the mutation. However, L5F allele expansion is relatively restricted. The D614G mutation is located at the subdomain 2 (SD2) of C-terminal portion (CTP) of the S1 subunit. Protein structural modeling shows that the D614G mutation may cause the disruption of salt bridge among S protein monomers increase their flexibility, and in turn promote receptor binding domain (RBD) opening, virus attachment and entry into host cells. Located at the signal sequence of S protein as it is, L5F mutation may facilitate the protein folding, assembly, and secretion of the virus. This is the first evidence of positive Darwinian selection in the spike gene of SARS-CoV-2, which contributes to a better understanding of the adaptive mechanism of this virus and help to provide insights for developing novel therapeutic approaches as well as effective vaccines by targeting on mutation sites.

evolutionary biology↗

bioRxiv2020

Predicting Gene Expression from DNA Sequence using Residual Neural Network

It is known that cis-acting DNA motifs play an important role in regulating gene expression. The genome in a cell thus contains the information that not only encodes for the synthesis of proteins but also is necessary for regulating expression of genes. Therefore, the mRNA level of a gene may be predictable from the DNA sequence. Indeed, three deep neural network models were developed recently to predict the mRNA level of a gene directly or indirectly from the DNA sequence around the transcription start side of the gene. In this work, we develop a deep residual network model, named ExpResNet, to predict gene expression directly from DNA sequence. Applying ExpResNet to the GTEx data, we demonstrate that ExpResNet outperforms the three existing models across four tissues tested. Our model may be useful in the investigation of gene regulation.

bioinformatics↗

bioRxiv2020

Herbivore-induced activation of viral phosphatase disarms plant antiviral immunities for pathogen transmission

The survival of pathogens depends on their ability to overcome host immunity, especially arthropod-borne viruses (arboviruses) which must withstand the immune responses of both the host and the arthropod vector. Successful arboviruses often modify host immunity to accelerate pathogen transmission; however, few studies have explored the underlying mechanism. Here we report attracted herbivore infestation on the virus-infected plants promote transmission by the associated vector herbivore. This herbivore-induced defense suppression underpins a subversive mechanism used by Begomovirus, the largest genus of plant viruses, to compromise host defense for pathogen transmission. Begomovirus-infected plants accumulated {beta}C1 proteins in the phloem where they were bound to host defense regulators, transcription factor WRKY20 and two mitogen-activated protein kinases MPK3 and MPK6. Once perceiving whitefly herbivory or endogenous secreted peptide PEP1, the plants started dephosphorylation on serine33 and stimulated {beta}C1 protein as a phosphatase. {beta}C1 dephosphorylated MPK3/6 and WRKY20, the latter negatively regulated salicylic acid signaling and vascular callose deposition. This viral hijacking of WRKY20 accumulated more vascular callose by which enforced whitefly prolonged salivation and phloem sap ingestion, therefore impelling more virus transmission among plants. We present a scenario in which viruses dynamically respond to the presence of their vectors, suppressing host immunity and promoting pathogen transmission only when needed.

microbiology↗

bioRxiv2020

Crystal structure of SARS-CoV-2 main protease in complex with a Chinese herb inhibitor shikonin

Main protease (Mpro, also known as 3CLpro) has a major role in the replication of coronavirus life cycle and is one of the most important drug targets for anticoronavirus agents. Here we report the crystal structure of main protease of SARS-CoV-2 bound to a previously identified Chinese herb inhibitor shikonin at 2.45 angstrom resolution. Although the structure revealed here shares similar overall structure with other published structures, there are several key differences which highlight potential features that could be exploited. The catalytic dyad His41-Cys145 undergoes dramatic conformational changes, and the structure reveals an unusual arrangement of oxyanion loop stabilized by the substrate. Binding to shikonin and binding of covalent inhibitors show different binding modes, suggesting a diversity in inhibitor binding. As we learn more about different binding modes and their structure-function relationships, it is probable that we can design more effective and specific drugs with high potency that can serve as effect SARS-CoV-2 anti-viral agents.

biophysics↗

bioRxiv2020

Dissecting Autism Genetic Risk Using Single-cell RNA-seq Data

Autism spectrum disorder (autism) is a condition with strong but heterogenous genetic contribution. Recent exome and genome sequencing studies have uncovered many new risk genes through de novo variants. However, a large fraction of enrichment of de novo variants observed in cases are not accounted for by known or candidate risk genes, suggesting that the majority of risk genes are still unknown. Here we hypothesize that autism risk genes share a few common cell-type specific gene expression patterns during brain development, and such information can be quantified to improve statistical power of detecting new risk genes. We obtained large-scale single-cell RNA-seq data from human fetal brain collected through a range of developmental stages, and developed a supervised machine-learning approach "A-risk" (Autism risk), to predict the plausibility of autism risk genes across the genome. Using data from recent exome sequencing studies of autism, A-risk achieves better performance in prioritizing de novo variants than other methods, especially for genes that are less intolerant of loss of function variants. We stratified genes based on A-risk and mutation intolerance metrics to improve estimation of priors in extTADA and identified 71 candidate risk genes. In particular, CLCN4, PRKAR1B, and NR2F1 are potentially new risk genes with further support from neurodevelopmental disorders. Expression patterns of both known and candidate risk genes reveals the important role of deep-layer excitatory neurons from adult human cortex in autism etiology. With the unprecedented revolution of single-cell transcriptomics and expanding autism cohorts with exome or genome sequencing, our method will facilitate systematic discovery of novel risk genes and understanding of biological pathogenesis in autism.

genomics↗

bioRxiv2020

Histone deacetylase inhibitor givinostat attenuates nonalcoholic steatohepatitis and liver fibrosis

Non-alcoholic steatohepatitis (NASH) is a common chronic liver disease that causes worldwide morbidity and mortality, yet there is still a lack of pharmacological therapies. Liver inflammation is an important contributor for disease progression from non-alcoholic fatty liver disease (NAFLD) to non-alcoholic steatohepatitis (NASH). We identified HDAC inhibitor givinostat as a potent inhibitor of macrophages inflammatory activation, and aimed to evaluate the therapeutic potential of givinostat for treatment of NASH. Daily administration of givoinostat (10mg/kg) alleviated inflammation and attenuated hepatic fibrosis in methionine- and choline-deficient diet (MCD)-induced NASH mice. RNA-seq analysis of liver tissues form MCD-fed mice revealed givinostat potently blocked expression of inflammation-related genes and regulated a broad set of lipid metabolism-related genes. In hepatocyte givinostat reduced palmitic acid induced intracellular lipid accumulation. The benefit of givinostat was further confirmed in fructose, palmitate, cholesterol diet (FPC) induced NASH mice. Givinostat attenuated hepatic steatosis, inflammation as well as liver injury in FPC-induced NASH. In conclusion, givinostat appears to be efficacious in reversing diet-induced NASH, and may serve as a therapeutic agent for treatment of human NASH.View Full Text

animal behavior and cognition↗

bioRxiv2020

Single nucleus multi-omics regulatory atlas of the murine pituitary

The pituitary regulates growth, reproduction and other endocrine systems. To investigate transcriptional network epigenetic mechanisms, we generated paired single nucleus (sn) transcriptome and chromatin accessibility profiles in single mouse pituitaries and genome-wide sn methylation datasets. Our analysis provided insight into cell type epigenetics, regulatory circuit and gene control mechanisms. Latent variable pathway analysis detected corresponding transcriptome and chromatin accessibility programs showing both inter-sexual and inter-individual variation. Multi-omics analysis of gene regulatory networks identified cell type-specific regulons whose composition and function were shaped by the promoter accessibility state of target genes. Co-accessibility analysis comprehensively identified putative cis-regulatory regions, including a domain 17kb upstream of Fshb that overlapped the fertility-linked rs11031006 human polymorphism. In vitro CRISPR-deletion at this locus increased Fshb levels, supporting this domains inferred regulatory role. The sn pituitary multi-omics atlas (snpituitaryatlas.princeton.edu) is a public resource for elucidating cell type-specific gene regulatory mechanisms and principles of transcription circuit control.

cell biology↗

bioRxiv2020

Rare variant analysis of 4,241 pulmonary arterial hypertension cases from an international consortium implicate FBLN2, PDGFD and rare de novo variants in PAH

BackgroundGroup 1 pulmonary arterial hypertension (PAH) is a lethal vasculopathy characterized by pathogenic remodeling of pulmonary arterioles leading to increased pulmonary pressures, right ventricular hypertrophy and heart failure. Recent high-throughput sequencing studies have identified additional PAH risk genes and suggested differences in genetic causes by age of onset. However, known risk genes explain only 15-20% of non-familial idiopathic PAH cases. MethodsTo identify new risk genes, we utilized an international consortium of 4,241 PAH cases with 4,175 sequenced exomes (n=2,572 National Biological Sample and Data Repository for PAH; n=469 Columbia University Irving Medical Center, enriched for pediatric trios) and 1,134 sequenced genomes (UK NIHR Bioresource - Rare Diseases Study). Most of the cases were adult-onset disease (93%), and 55% idiopathic (IPAH) and 35% associated with other diseases (APAH). We identified protein-coding variants and performed rare variant association analyses in unrelated participants of European ancestry, including 2,789 cases and 18,819 controls (11,101 unaffected parents from the Simons Powering Autism Research for Knowledge study and 7,718 gnomAD individuals). We analyzed de novo variants in 124 pediatric trios. ResultsSeven genes with rare deleterious variants were significantly associated (false discovery rate <0.1) with IPAH, including three known genes (BMPR2, GDF2, and TBX4), two recently identified candidate genes (SOX17, KDR), and two new candidate genes (FBLN2, fibulin 2; PDGFD, platelet-derived growth factor D). The candidate genes exhibit expression patterns in lung and heart similar to that of known PAH risk genes, and most of the variants occur in conserved protein domains. Variants in known PAH gene, ACVRL1, showed association with APAH. Predicted deleterious de novo variants in pediatric cases exhibited a significant burden compared to the background mutation rate (2.5x, p=7.0E-6). At least eight novel candidate genes carrying de novo variants have plausible roles in lung/heart development. ConclusionsRare variant analysis of a large international consortium identifies two new candidate genes - FBLN2 and PDGFD. The new genes have known functions in vasculogenesis and remodeling but have not been previously implicated in PAH. Trio analysis predicts that ~15% of pediatric IPAH may be explained by de novo variants.

genetics↗

bioRxiv2020

Intrinsic connectivity of the prefrontal cortex and striato-limbic system respectively differentiate Major Depressive from Generalized Anxiety Disorder

Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) are highly prevalent and debilitating disorders. The high overlap on the symptomatic and neurobiological level led to ongoing debates about their diagnostic and neurobiological uniqueness. The present study aims to identify common and disorder-specific neuropathological mechanisms and treatment targets in MDD and GAD. The present study combined categorial and dimensional disorder models with a fully data-driven intrinsic network level analysis (Intrinsic Connectivity Contrast, ICC) to resting state fMRI data acquired in 108 partn = 35 and n = 38 unmedicated patients with first-episode GAD, MDD respectively and n=35 healthy controls). Convergent evidence from categorical and dimensional analyses revealed MDD-specific decreased whole-brain connectivity profiles of the medial prefrontal and dorsolateral prefrontal cortex while GAD was specifically characterized by decreased whole-brain connectivity profiles of the putamen and decreased communication of this region with the amygdala. Together, findings from the present data-driven analysis suggest that intrinsic communication of frontal regions engaged in executive functions and emotion regulation represent depression-specific neurofunctional markers and treatment targets whereas dysregulated intrinsic communication of the striato-amygdala system engaged in reinforcement-based and emotional learning processes represent GAD-specific markers and a promising treatment target.

neuroscience↗

bioRxiv2020

p53 induces ARTS to promote mitochondrial apoptosis

Apoptosis Related protein in TGF-{beta} Signaling pathway (ARTS) was originally discovered in cells undergoing apoptosis in response to TGF-{beta}, but ARTS also acts downstream of many other apoptotic stimuli. ARTS induces apoptosis by antagonizing the anti-apoptotic proteins XIAP and Bcl-2. Here, we identified the pro-apoptotic Sept4/ARTS gene as a p53-responsive target gene. Ectopic p53 and a variety of p53-inducing agents increased both mRNA and protein levels of ARTS, whereas ablation of p53 reduced ARTS expression in response to multiple stress conditions. Also, {gamma}-irradiation induced p53-dependent ARTS expression in mice. Consistently, p53 binds to the responsive DNA element on the ARTS promoter and transcriptionally activated the promoter-driven expression of a luciferase reporter gene. Interestingly, ARTS binds to and sequesters p53 at mitochondria, enhancing the interaction of the latter with Bcl-XL. Ectopic ARTS markedly augments DNA damage stress- or Nutlin-3-triggered apoptosis, while ablation of ARTS preferentially impairs p53-induced apoptosis. Altogether, these findings demonstrate that ARTS collaborates with p53 in mitochondria-engaged apoptosis.

cancer biology↗

bioRxiv2020

Impaired Layer Specific Retinal Vascular Reactivity Among Diabetic Subjects

PurposeTo investigate layer specific retinal vascular reactivity (RVR) in capillaries of diabetic subjects with no or mild non-proliferative diabetic retinopathy (NPDR). MethodsA previously described nonrebreathing apparatus was used to deliver room air, 5% CO2, or 100% O2 to 41 controls and 22 diabetic subjects (with mild or no NPDR) while simultaneously acquiring fovea-centered 3x3mm2 Swept-Source Optical Coherence Tomography Angiography. Vessel skeleton density (VSD) and vessel diameter index (VDI) were calculated for each gas condition for the superficial retinal layer (SRL) and deep retinal layer (DRL). The superficial layer analysis excluded regions of arterioles and venules. Data analysis was performed using mixed factorial analysis of covariance stratified by diabetic status. All models were adjusted for age, gender, and hypertension. ResultsAmong controls, there was a significant difference in capillary VSD between all gas conditions (p<0.001). This difference was present in both the SRL and DRL. Among diabetics, there was no significant difference in response to CO2 conditions in the SRL (p=0.072), and a blunted response to both CO2 and O2 in the DRL. A significant gas effect was detected in the capillary VDI in the SRL of controls (p=0.001), which was driven by higher VDI in the oxygen condition compared to that of carbon dioxide. ConclusionsImpairment in RVR in diabetic subjects is driven largely by a decrease in the magnitude of the capillary response to O2 in the DRL as well as almost complete attenuation of capillary CO2 response in all layers. These layer and gas specific impairments in diabetics seem to occur early in the disease and to be driven primarily at the capillary level.

physiology↗

bioRxiv2020

Genome-scale phylogeny and contrasting modes of genome evolution in the fungal phylum Ascomycota

Ascomycota, the largest and best-studied phylum of fungi, contains three subphyla: Saccharomycotina (budding yeasts), Pezizomycotina (filamentous fungi), and Taphrinomycotina (fission yeasts); organisms from all three subphyla have been invaluable as models in diverse fields (e.g., biotechnology, cell biology, genetics, and medicine). Despite its importance, we still lack a comprehensive genome-scale phylogeny or understanding of the similarities and differences in the mode of genome evolution within this phylum. To address these gaps, we examined 1,107 genomes from Saccharomycotina (332), Pezizomycotina (761), and Taphrinomycotina (14) species to infer the Ascomycota phylogeny, estimate its timetree, and examine the evolution of key genomic properties. We inferred a robust genome-wide phylogeny that resolves several contentious relationships and estimated that the Ascomycota last common ancestor likely originated in the Ediacaran (~563 {+/-} 68 million years ago). Comparisons of genomic properties revealed that Saccharomycotina and Pezizomycotina, the two taxon-rich subphyla, differed greatly in their genome properties. Saccharomycotina typically have smaller genomes, lower GC contents, lower numbers of genes, and higher rates of molecular sequence evolution compared to Pezizomycotina. Ancestral state reconstruction showed that the genome properties of the Saccharomycotina and Pezizomycotina last common ancestors were very similar, enabling inference of the direction of evolutionary change. For example, we found that a lineage-specific acceleration led to a 1.6-fold higher evolutionary rate in Saccharomycotina, whereas the 10% difference in GC content between Saccharomycotina and Pezizomycotina genomes stems from a trend toward AT bases within budding yeasts and toward GC bases within filamentous fungi. These results provide a robust evolutionary framework for understanding the diversification of the largest fungal phylum.

evolutionary biology↗