Biology subjects

Gu, T.

Publications and source records attributed to Gu, T..

36 records · Page 2Linked to original sources

bioRxiv2025

Glycan-Mediated Mechanosensing Regulates Megakaryocyte-Biased Hematopoietic Stem Cell Subsets.

Definitive hematopoietic stem and progenitor cells (HSPCs) development relies on intrinsic and extrinsic programs to meet homeostatic and stress-related demands. The comprehensive mechanisms governing HSPCs fate remain poorly understood. Our study identifies B4GALT1, a glycosyltransferase essential for N-glycosylation, as a key modulator of HSPC lineage decisions. We demonstrate that B4GALT1 deficiency disrupts glycosylation patterns within the bone marrow (BM) niche, resulting in oncogenic glycan signatures and altered expression of Mucin13 in HSPCs. Loss of B4GALT1 expands HSPC pools and promotes megakaryocyte priming in HSPCs through transcriptional and chromatin modifications, enhancing the Wnt-Mucin13 axis. Mucin13, an oncogene characterized by aberrant glycosylation, underscores the critical role of B4GALT1 in sustaining BM glycosylation and mechanosensing, thereby regulating HSPC fate through functional, transcriptional, and chromatin dynamics. These observations provide insights into the impact of glycan structures on HSPC function, lineage reprogramming, and malignant transformation.

cell biology↗

bioRxiv2024

Radiation damage behavior of soft matter in ultrafast cryo-electron microscopy (cryo-UEM)

Whether time-modulated pulsed-electron imaging in ultrafast electron microscopy (UEM) can mitigate the electron radiation damage that occurs to samples, is still controversial. The effectiveness of such mitigation effect and relevant potential application in cryo-EM remain to be explored. Herein, we built an ultrafast cryo-EM (cryo-UEM) device based on an ultrafast laser system. Using such equipment and the saturated aliphatic hydrocarbon compounds (C44H90), the fading curves of diffraction intensity and corresponding critical electron doses (Ne) of the samples were carefully measured under different imaging modes, temperatures, imaging dose rates and pulsed repetition rates. Our experimental results show that, the fading curves and Ne values of the C44H90 crystals are uncorrelated with the imaging electron dose rates and do not show dependence on the dose-rate effect. As the temperature decreased, the Ne values of the sample increased, indicating the cryoprotective effect on radiation damage to the samples. Surprisingly, at a constant temperature, the fading curves and Ne values of the sample in multi-electrons-packet and near-single-electron-packet pulsed modes are all approximately the same as those in conventional continuous electron-beam mode, even when the results are obtained at different pulsed repetition rates. These results show that the time-modulated pulsed electron beam does not seem to mitigate the electron radiation damage that occurs on samples. Our findings offer new insights and experimental basis for the radiation damage behavior of samples under electron beams, and provide guidance and inspiration for elucidating the fundamental principles of radiation damage.

biophysics↗

bioRxiv2024

Enantioselective photoenzymatic C(sp3)-H functionalization via single-electron oxidation of carbanions

Established strategies for enantioselective hydroalkylation for C(sp3)-C(sp3) bond formation usually require pre-functionalized substrates as radical precursors in both transition-metal and photoenzymatic catalysis. Based on a sequential proton transfer/electron transfer (PT/ET) strategy, here we show a cooperative photoenzymatic system consisting of a flavin-dependent ene-reductase (ER) and an organophotoredox catalyst fluorescein (FI) to achieve atom-economic enantiodivergent hydroalkylation of electron-deficient C(sp3)-H with olefins. Mechanistic studies revealed a pathway for radical intermediate formation via excited-state FI*-induced single-electron oxidation of carbanions under alkaline conditions. The overall catalytic efficiency is enhanced by the electron transfer (ET) between FMNox and FI-*, while the stereoselectivity is controlled by ERs through enantioselective hydrogen atom transfer (HAT). We anticipate that this mode of photoenzymatic catalysis will inspire new pathways for generating free radical intermediates and foster innovative strategies for achieving photoenzymatic new-to-nature reactions. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=95 SRC="FIGDIR/small/627421v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@11b6c1eorg.highwire.dtl.DTLVardef@1575346org.highwire.dtl.DTLVardef@1c24a2org.highwire.dtl.DTLVardef@1a93c0d_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗

bioRxiv2024

Synthesis and Evaluation of Carmofur Analogs as Antiproliferative Agents, Inhibitors to the Main Protease (Mpro) of SARS-CoV-2, and Membrane Rupture-Inducing Agents

Initially developed as a derivatized analog of 5-fluorouracil for the treatment of colorectal cancer, carmofur has more recently demonstrated potent covalent inhibition of the main protease (Mpro) of SARS-CoV-2. Harnessing our previously described workflow for the optimized preparation of carmofur using benchtop 19F NMR spectroscopy, here, we prepared and evaluated a synthetic library of nine carmofur analogs with a selection of side chain motifs or single-atom substitution to explore the diversifiability of these compounds as Mpro inhibitors, where we discovered that a hexyl carbamate analog outperformed carmofur, and as antiproliferative agents in model human cell lines to identify differences in potency when the carbonyl electrophilicity and/or alkyl side chains are modified. Finally, we describe a novel workflow for the evaluation of membrane-rupturing small molecules through imaging of fluorescently labeled giant unilamellar vesicles (GUVs), and through this, we identified two lipophilic urethane analogs of carmofur bearing dodecyl urethane and octadecyl urethane side chains that have potent membrane-rupturing capability in the nanomolar range, providing insight into a potential mechanism for the in vitro activities of lipidated 5-fluorouracil analogs.

biochemistry↗

bioRxiv2024

Optimization of systemic AAV9 gene therapy in Niemann-Pick disease type C1 mice

Niemann-Pick disease, type C1 (NPC1) is a rare, fatal neurodegenerative disorder caused by pathological variants in NPC1, which encodes a lysosomal cholesterol transporter. FDA-approved treatments are limited and do not target the underlying genetic defect. Both systemic and central nervous system (CNS) delivery of AAV9-hNPC1 have shown significant disease amelioration in NPC1 murine models. To assess the impact of dose in null Npc1m1N/m1N mice, we systemically administered three different doses of AAV9-hNPC1 at 4 weeks old. Then, to assess the impact of age, we administered the medium dose before phenotypic onset or at early- or late-stage of disease progression (4, 6 or 8 weeks old, respectively). Higher vector doses and earlier treatment were associated with significantly increased lifespan, slower disease progression, and enhanced CNS transduction. In Npc1I1061T/I1061T mice, a model recapitulating a common human hypomorphic variant, similar benefits ensued. Our findings help define dose ranges, treatment ages, and efficacy in hypomorphic models of NPC1 deficiency and suggest that higher doses of AAV9-hNPC1 in pre-symptomatic disease states are likely to yield better outcomes in NPC1 individuals. Summary BlurbSystemic AAV9-hNPC1 gene therapy in null Npc1m1N mice at higher doses or with earlier administration and treatment of hypomorphic Npc1I1061T mice delays disease progression and increases lifespan.

neuroscience↗

bioRxiv2024

Multi-omic characterization of allele-specific regulatory variation in hybrid pigs

Genetic variation in the regulation of gene expression contributes substantially to phenotypic variation. Understanding how variation in DNA sequences and epigentic modifications leads to gene expression variation remains a challenging task. In hybrid animals where cellular environments are homogeneous, differences between the expression of paternal and maternal alleles must be due to cis sequence or epigenic differences. Therefore, hybrid mapping is a powerful approach to efficiently identify and characterize genes under regulation through mechanisms in cis. In this study, using reciprocal crosses of the phenotypically divergent Duroc and Lulai pig breeds, we performed a comprehensive multi-omic characterization of regulatory variation across brain, liver, muscle, and placenta in four developmental stages. We produced one of the largest multi-omic datasets to date in pigs, including 16 whole genome sequenced genomes, 48 whole genome bisulfite sequencing, 168 ATAC-Seq and 168 RNA-Seq samples. We developed a novel read count-based method to reliably assess allele-specific methylation, chromatin accessibility, and RNA expression. We showed that tissue specificity was much stronger than developmental stage specificity in all of DNA methylation, chromatin accessibility, and gene expression. We identified 573 genes showing allele specific expression, including those influenced by parent-of-origin as well as allele genotype effects. By integrating methylation, chromatin accessibility, and gene expression data, many of these allele specific expression can be explained by allele specific methylation and/or chromatin accessibility. This study provides one of the most comprehensive characterizations of regulatory variation across multiple tissues and developmental stages in pigs and offers new opportunity of genetic improvement for this important food animal species.

developmental biology↗

bioRxiv2023

Machine Learning-Driven Phenotype Predictions based on Genome Annotations

Over the past two decades, there has been a remarkable and exponential expansion in the availability of genome sequences, encompassing a vast number of isolate genomes, amounting to hundreds of thousands, and now extending to millions of metagenome-assembled genomes. The rapid and accurate interpretation of this data, along with the profiling of diverse phenotypes such as respiration type, antimicrobial resistance, or carbon utilization, is essential for a wide range of medical and research applications. Here, we leverage sequenced-based functional annotations obtained from the RAST annotation algorithm as predictors and employ six machine learning algorithms (K-Nearest Neighbors, Gaussian Naive Bayes, Support Vector Machines, Neural Networks, Logistic Regression, and Decision Trees) to generate classifiers that can accurately predict phenotypes of unclassified bacterial organisms. We apply this approach in two case studies focused on respiration types (aerobic, anaerobic, and facultative anaerobic) and Gram-stain types (Gram negative and Gram positive). We demonstrate that all six classifiers accurately classify the phenotypes of Gram stain and respiration type, and discuss the biological significance of the predicted outcomes. We also present four new applications that have been deployed in The Department of Energy Systems Biology Knowledgebase (KBase) that enable users to: (i) Upload high-quality data to train classifiers; (ii) Annotate genomes in the training set with the RAST annotation algorithm; (iii) Build six different genome classifiers; and (iv) Predict the phenotype of unclassified genomes. (https://narrative.kbase.us/#catalog/modules/kb_genomeclassification)

systems biology↗

bioRxiv2022

The domain-separation low-dimensional language network dynamics in the resting-state support the flexible functional segregation and integration during language and speech processing

Modern linguistic theories and network science propose that the language and speech processing is organized into hierarchical, segregated large-scale subnetworks, with a core of dorsal (phonological) stream and ventral (semantic) stream. The two streams are asymmetrically recruited in receptive and expressive language or speech tasks, which showed flexible functional segregation and integration. We hypothesized that the functional segregation of the two streams was supported by the underlying network segregation. A dynamic conditional correlation approach was employed to construct frame-wise time-varying language networks and investigate the temporal reoccurring patterns. We found that the time-varying language networks in the resting-state robustly clustered into four low-dimensional states, which dynamically reconfigured following a domain-separation manner. Spatially, the hub distributions of the first three states highly resembled the neurobiology of primary auditory processing and lexical-phonological processing, motor and speech production processing, and semantic processing, respectively. The fourth state was characterized by the weakest functional connectivity and subserved as a baseline state. Temporally, the first three states appeared exclusively in limited time bins ([~]15%), and most of the time (> 55%), the language network kept inactive in state 4. Machine learning-based dFC-linguistics prediction analyses showed that dFCs of the four states significantly predicted individual linguistic performance. These findings suggest a domain-separation manner of language network dynamics in the resting-state, which forms a dynamic "meta-networking" (network of networks) framework. HighlightsO_LIThe time-varying language network in the resting-state is robustly clustered into four low-dimensional states. C_LIO_LISpatially, the first three dFC states are cognitively meaningful, which highly resemble the neurobiology of primary auditory processing and lexical-phonological representation, speech production processing, and semantic processing, respectively. C_LIO_LITemporally, the first three states appeared exclusively in limited time bins ([~]15%), and most of the time (> 55%), the language network kept inactive in state 4. C_LIO_LIA dynamic "meta-networking" framework of language network in the resting-state is proposed. C_LI

neuroscience↗

bioRxiv2021

Constitutive loss of DNMT3A causes morbid obesity through misregulation of adipogenesis

DNA Methyltransferase 3A (DNMT3A) is an important facilitator of differentiation of both embryonic and hematopoietic stem cells. Heterozygous germline mutations in DNMT3A lead to Tatton-Brown-Rahman Syndrome (TBRS), characterized by obesity and excessive height. While DNMT3A is known to impact feeding behavior via the hypothalamus, here we investigated a role in adipocyte progenitors utilizing heterozygous knockout mice that recapitulate cardinal TBRS phenotypes. These mice become morbidly obese due to adipocyte enlargement and tissue expansion. Adipose tissue in these mice exhibited defects in preadipocyte maturation and precocious activation of inflammatory gene networks, including interleukin-6 signaling. Adipocyte progenitor cell lines lacking DNMT3A exhibited aberrant differentiation. Furthermore, mice in which Dnmt3a was specifically ablated in adipocyte progenitors showed enlarged fat depots and increased progenitor numbers, partly recapitulating the TBRS obesity phenotypes. Loss of DNMT3A led to constitutive DNA hypomethylation, such that the DNA methylation landscape of young adipocyte progenitors resemble that of older wild-type mice. Together, our results demonstrate that DNMT3A coordinates both the central and local control of energy storage required to maintain normal weight and prevent inflammatory obesity.

cell biology↗

bioRxiv2021

Augmenting Neutralization breadth against Diverse HIV-1 by increasing the Ab-Ag interface on V2

Understanding maturation pathways of broadly neutralizing antibodies (bnAbs) against HIV-1 in non-human primates can be highly informative for HIV-1 vaccine development. We now obtained a lineage of J038 from Chinese rhesus macaques after 7-years of SHIV infection. J038 has short complementary determining loops and neutralizes 54% of global circulating HIV-1 strains. Its binding induces a unique "up" conformation for one of the V2 loops in the trimeric envelope glycoprotein (Env) and is heavily dependent on glycan, which provides nearly half of the binding surface. The unmutated common ancestor of the J038 lineage antibodies binds monomeric gp120 and neutralizes the autologous virus. Continuous maturation enhances neutralization potency and breadth of J038 lineage antibodies via expanding antibody-Env contact areas surrounding the core region contacted by germline-encoded residues. Developmental details and recognition features of J038 lineage antibodies revealed here provide a new pathway for maturation elicitation of V2-targeting bnAbs. Highlights* Long-term infected NHPs develop antibodies neutralizing up to 54% of HIV-1 strains * Antibody J038 binds one V2 loop on HIV-1 Env trimer in a unique "up" position * UCA of the J038 lineage effectively neutralizes the autologous virus * J038 lineage antibodies mature through gradually increased contact to glycans

immunology↗

bioRxiv2021

The first crested duck genome reveals clues to genetic compensation and crest cushion formation

The Chinese crested (CC) duck is a unique indigenous waterfowl breed with a phenotypic crest trait that affects its high survival rate. Therefore, the CC duck is an ideal model to investigate the genetic compensation response to maintain genetic stability. In the present study, we first generated a chromosome-level genome of CC ducks. Comparative genomics revealed genes related to tissue repair, immune function, and tumors were under strong positive selection, which suggested that these adaptive changes might enhance cancer resistance and immune response to maintain the genetic stability of CC ducks. We sub-assembled a Chinese spot-billed duck genome and detected genome-assembled structure variants among three ducks. Functional analysis revealed that a large number of structural variants were related to the immune system, which strongly suggests the occurrence of genetic compensation in the anti-tumor and immune systems to further support the survival of CC ducks. Moreover, we confirmed that the CC duck originated from the mallard ducks. Finally, we revealed the physiological and genetic basis of crest traits and identified a causative mutation in TAS2R40 that leads to crest formation. Overall, the findings of this study provide new insights into the role of genetic compensation in adaptive evolution.

genomics↗

bioRxiv2021

Derived loss of signal complexity and plasticity in a genus of weakly electric fish

Signal plasticity can maximize the usefulness of costly animal signals such as the electric organ discharges (EODs) of weakly electric fishes. Some species of the order Gymnotiformes rapidly alter their EOD amplitude and duration in response to circadian cues and social stimuli. How this plasticity is maintained across related species with different degrees of signal complexity is poorly understood. In one genus of weakly electric gymnotiform fish (Brachyhypopomus) only one species, B. bennetti, produces a monophasic signal while all other species emit complex biphasic or multiphasic EOD waveforms produced by two overlapping but asynchronous action potentials in each electric organ cell (electrocyte). One consequence of this signal complexity is the suppression of low-frequency signal content that is detectable by electroreceptive predators. In complex EODs, reduction of the EOD amplitude and duration during daytime inactivity can decrease both predation risk and the metabolic cost of EOD generation. We compared EOD plasticity and its underlying physiology in Brachyhypopomus focusing on B. bennetti. We found that B. bennetti exhibits minimal EOD plasticity, but that its electrocytes retained vestigial mechanisms of biphasic signaling and vestigial mechanisms for modulating the EOD amplitude. These results suggest that this species represents a transitional phenotypic state within a clade where signal complexity and plasticity were initially gained and then lost. We discuss potential the roles of signal mimicry, species recognition, and sexual selection in maintaining the monophasic EOD phenotype in the face of detection by electroreceptive predators.

physiology↗

bioRxiv2020

Molecular mechanism of SARS-Cov-2 components caused ARDS in murine model

COVID-19 has become a major challenge to global health, and until now, no efficient antiviral agents have been developed. The SARS-CoV-2 infection is characterized by pulmonary and systemic inflammation in severe patients, and acute respiratory distress syndrome (ARDS) caused respiratory failure contributes to most mortalities. There is an urgent need for developing effective drugs and vaccines against SARS-CoV-2 and COVID-19 caused ARDS. However, most researchers cannot perform SARS-CoV-2 related researches due to lacking P3 or P4 facility. We developed a non-infectious, highly safety, time-saving SARS-CoV-2 components induced murine model to study the SARS-CoV-2 caused ARDS and cytokine storm syndrome (CSS). We also investigated mAbs and inhibitors which potentially neutralize the pro-inflammatory phenotype of COVID-19, and found that anti-IL-1, anti-IL-6, anti-TNF, anti-GM-CSF mAbs, p38 inhibitor, and JAK inhibitor partially relieved CSS. Besides, anti-IL-6, anti-TNF, anti-GM-CSF mAbs and inhibitors of p38, ERK, and MPO somewhat reduced neutrophilic alveolitis in the lung. In all, we established the murine model mimic of COVID-19, opening a biosafety and less time-consuming avenue for clarifying the mechanism of ARDS and CSS in COVID-19 and developing the therapeutic drugs.

pathology↗

bioRxiv2020

miTAR: a hybrid deep learning-based approach for predicting miRNA targets

microRNAs (miRNAs) are a major type of small RNA that alter gene expression at the post-transcriptional or translational level. They have been shown to play important roles in a wide range of biological processes. Many computational methods have been developed to predict targets of miRNAs in order to understand miRNAs function. However, the majority of the methods depend on a set of pre-defined features that require considerable effort and resources to compute, and these methods often do not effectively on the prediction of miRNA targets. Therefore, we developed a novel hybrid deep learning-based approach that is capable to predict miRNA targets at a higher accuracy. Our approach integrates two deep learning methods: convolutional neural networks (CNNs) that excel in learning spatial features, and recurrent neural networks (RNNs) that discern sequential features. By combining CNNs and RNNs, our approach has the advantages of learning both the intrinsic spatial and sequential features of miRNA:target. The inputs for the approach are raw sequences of miRNA and gene sequences. Data from two latest miRNA target prediction studies were used in our study: the DeepMirTar dataset and the miRAW dataset. Two models were obtained by training on the two datasets separately. The models achieved a higher accuracy than the methods developed in the previous studies: 0.9787 vs. 0.9348 for the DeepMirTar dataset; 0.9649 vs. 0.935 for the miRAW dataset. We also calculated a series of model evaluation metrics including sensitivity, specificity, F-score and Brier Score. Our approach consistently outperformed the current methods. In addition, we compared our approach with earlier developed deep learning methods, resulting in an overall better performance. Lastly, a unified model for both datasets was developed with an accuracy higher than the current methods (0.9545). We named the unified model miTAR for miRNA target prediction. The source code and executable are available at https://github.com/tjgu/miTAR.

bioinformatics↗

bioRxiv2019

Systematic identification of A-to-I editing associated regulators from multiple human cancers

A-to-I editing is the most common editing type in human that is catalyzed by ADAR family members (ADARs), ADAR1 and ADAR2. Millions of A-to-I editing sites have been discovered recently, however, the regulation mechanisms of the RNA editing process are still not clear. Here we developed a two-step logistic regression model to identify genes that are potentially involved in RNA editing process in four human cancers. The first step by classifying the editing sites into different categories assists the analysis at the second step. In the first step, ADAR1 was identified as the enzyme that associated with the majority of the A-to-I editing sites. Thus, ADAR1 was taken as a control gene in the second step to identify genes that have a stronger effect on editing sites than ADAR1. In addition, the detectable interferons and their receptors were used as covariates in the both steps to account for potential association caused by interferons. Using our advanced method, we successfully found a set of genes that were significantly positively or negatively associated (PA or NA) with specific sets of RNA editing sites. We highlighted two genes, SRSF5 and MIR22HG which were supported by multiple evidences. Most PA and NA genes were unique to each cancer, and only a few shared across two cancers. Pathway enrichment analysis showed that the PA genes from the four cancer types were enriched in Immune System, while the NA genes were enriched in two pathways: Metabolism of RNA, and Metabolism. The functional similarity of the PA and NA genes across all the four cancers indicates that even though most of the editing associated genes were unique to each cancer, they may impact on editing process through common pathways. Interestingly, the PA genes from kidney cancer were enriched for survival-associated genes while the NA genes were depleted of these genes, indicating that the PA genes may play more important roles in kidney cancer development.

bioinformatics↗

bioRxiv2019

Direct Metatranscriptome RNA-seq and Multiplex RT-PCR Amplicon Sequencing on Nanopore MinION - Promising Strategies for Multiplex Identification of Viable Pathogens in Food

Viable pathogenic bacteria are major biohazards that pose a significant threat to food safety. Despite the recent developments in detection platforms, multiplex identification of viable pathogens in food remains a major challenge. A novel strategy is developed through direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing on Nanopore MinION to achieve real-time multiplex identification of viable pathogen in food. Specifically, this study reports an optimized universal Nanopore sample extraction and library preparation protocol applicable to both Gram-positive and Gram-negative pathogenic bacteria, demonstrated using a cocktail culture of E. coli O157:H7, Salmonella enteritidis, and Listeria monocytogenes, which were selected based on their impact on economic loss or prevalence in recent outbreaks. Further evaluation and validation confirmed the accuracy of direct metatranscriptome RNA-seq and multiplex RT-PCR amplicon sequencing using Sanger sequencing and selective media. The study also included a comparison of different bioinformatic pipelines for metatranscriptomic and amplicon genomic analysis. MEGAN without rRNA mapping showed the highest accuracy of multiplex identification using the metatranscriptomic data. EPI2ME also demonstrated high accuracy using multiplex RT-PCR amplicon sequencing. In addition, a systemic comparison was drawn between Nanopore sequencing of the direct metatranscriptome RNA-seq and RT-PCR amplicons. Both methods are comparable in accuracy and time. Nanopore sequencing of RT-PCR amplicon has higher sensitivity, but Nanopore metatranscriptome sequencing excels in read length and dealing with complex microbiome and non-bacterial transcriptome backgrounds. To the best of our knowledge, this is the first report of metatranscriptome sequencing of cocktail microbial RNAs on the emerging Nanopore platform. Direct RNA-seq and RT-PCR amplicons sequencing of metatranscriptome enable the direct identification of nucleotide analogs in RNAs, which is highly informative for determining microbial identities while detecting ecologically relevant processes. The information pertained in this study could be important for future revelatory research, including predicting antibiotic resistance, elucidating host-pathogen interaction, prognosing disease progression, and investigating microbial ecology, etc.

microbiology↗

bioRxiv2018

Expression profile analysis of circular RNAs in essential hypertension by microarray and bioinformatics.

Circular RNAs (circRNAs), widely found in human cells, are involved in disease and play an important role in progression. To determine whether circRNAs are related in essential hypertension (EH), we analyzed the expression profile of circRNAs and miRNAs in 5 EH and 5 healthy controls cases which were screened by microarray. Through microarray data and public data analysis, differently expressed transcripts were divided into modules, and circRNAs were functionally annotated by miRNAs. The expression of two circRNAs, has_circ_0037909 and has_circ_0105015, were validated in EH by qRT-PCR, which may be associated with EH. Further analysis showed that two circRNAs might through immune system by up-regulation circRNAs and down-regulation expression. These circRNAs biological functions need to be further validated.

genetics↗

bioRxiv2017

Phytophthora methylomes modulated by expanded 6mA methyltransferases are associated with adaptive genome regions

Filamentous plant pathogen genomes often display a bipartite architecture with gene sparse, repeat-rich compartments serving as a cradle for adaptive evolution. However, the extent to which this \"two-speed\" genome architecture is associated with genome-wide epigenetic modifications is unknown. Here, we show that the oomycete plant pathogens Phytophthora infestans and Phytophthora sojae possess functional adenine N6- methylation (6mA) methyltransferases that modulate patterns of 6mA marks across the genome. In contrast, 5-methylcytosine (5mC) could not be detected in the two Phytophthora species. Methylated DNA IP Sequencing (MeDIP-seq) of each species revealed that 6mA is depleted around the transcriptional starting sites (TSS) and is associated with low expressed genes, particularly transposable elements. Remarkably, genes occupying the gene-sparse regions have higher levels of 6mA compared to the remainder of both genomes, possibly implicating the methylome in adaptive evolution of Phytophthora. Among three putative adenine methyltransferases, DAMT1 and DAMT3 displayed robust enzymatic activities. Surprisingly, single knockouts of each of the 6mA methyltransferases in P. sojae significantly reduced in vivo 6mA levels, indicating that the three enzymes are not fully redundant. MeDIP-seq of the damt3 mutant revealed uneven patterns of 6mA methylation across genes, suggesting that PsDAMT3 may have a preference for gene body methylation after the TSS. Our findings provide evidence that 6mA modification is an epigenetic mark of Phytophthora genomes and that complex patterns of 6mA methylation by the expanded 6mA methyltransferases may be associated with adaptive evolution in these important plant pathogens.

molecular biology↗