Biology subjects

Wang, D.

Publications and source records attributed to Wang, D..

At least 595 records · Page 33Linked to original sources

bioRxiv2021

Gut microbial structural variations as determinants of human bile acid metabolism

Bile acids (BAs) facilitate intestinal fat absorption and act as important signaling molecules in host{square}gut microbiota crosstalk. BA-metabolizing pathways in the microbial community have been identified, but how the highly variable genomes of gut bacteria interact with host BA metabolism remains largely unknown. We characterized 8,282 structural variants (SVs) of 55 bacterial species in the gut microbiomes of 1,437 individuals from two Dutch cohorts and performed a systematic association study with 39 plasma BA parameters. Both variations in SV-based continuous genetic makeup and discrete subspecies showed correlations with BA metabolism. Metagenome-wide association analysis identified 797 replicable associations between bacterial SVs and BAs and SV regulators that mediate the effects of lifestyle factors on BA metabolism. This is the first large-scale microbial genetic association analysis to demonstrate the impact of bacterial SVs on human BA composition, and highlights the potential of targeting gut microbiota to regulate BA metabolism through lifestyle intervention.

microbiology↗

bioRxiv2021

High levels of truncated RHAMM cooperate with dysfunctional p53 to accelerate theprogression of pancreatic cancer

Pancreatic cancer has the lowest survival rate in all types of cancer. Pancreatic cancer patients are often diagnosed at advanced stages. A better therapeutic development for this devastating disease is urgently needed. Receptor for hyaluronan-mediated motility (RHAMM), not expressed in adult pancreas, has been suggested as a prognostic factor and a potential therapeutic target for pancreatic ductal adenocarcinoma (PDAC) and pancreatic neuroendocrine tumor (PNET). In this study, we initially sought to determine whether genetic deletion of RHAMM would slow down pancreatic cancer progression using Rhamm-/- mice. However, we found that Rhamm-/- mice expressed a truncated HMMR{Delta}exon8-16 protein at higher abundance levels than wild-type RHAMM. While HMMR{Delta}exon8-16 did not enable malignant progression of pancreatic intraepithelial neoplasia in p48-Cre; LSL-KRASG12D mice, it accelerated the formation of invasive PDAC and shortened the survival of p48-Cre; LSL-KRASG12D mice with heterozygous p53 knockout. KrasG12D PDAC mice with homozygous p53 knockout mice died around 10 weeks, and the effect of HMMR{Delta}exon8-16 was not apparent in these mice with short-life span. In addition, HMMR{Delta}exon8-16 shortened the survival of PNET-bearing RIP-Tag mice, which had inactivated p53. In our analysis of TCGA dataset, pancreatic cancer patients with mutant TP53 or loss of one copy of TP53 had higher RHAMM expression, which, combined, predicted worse outcomes. Taken together, by collaborating with dysfunctional p53, high levels of HMMR{Delta}exon8- 16 that lacks the centrosome targeting domain and degrons for interaction with the Anaphase-Promoting Complex (APC) accelerated pancreatic cancer progression.

cancer biology↗

bioRxiv2021

Pilot study: Trehalose-induced remodelling of the human microbiota affects Clostridioides difficile infection outcome in an in vitro colonic model

Within the human intestinal tract, dietary, microbial- and host-derived compounds are used as signals by many pathogenic organisms, including Clostridioides difficile. Trehalose has been reported to enhance virulence of certain C. difficile ribotypes; however, such variants are widespread and not correlated with clinical outcomes for patients suffering from C. difficile infection (CDI). Here, we make preliminary observations to how to trehalose supplementation affects the microbiota in an in vitro model and show that trehalose can reduce the outgrowth of C. difficile, preventing simulated CDI. Three clinically reflective human gut models simulated the effects of sugar (trehalose or glucose) or saline ingestion on the microbiota. Models were instilled with sugar or saline and further exposed to C. difficile spores. The recovery of the microbiota following antibiotic treatment and CDI induction was monitored in each model. The human microbiota remodeled to utilise the bioavailable trehalose. Clindamycin induction caused simulated CDI in models supplemented with either glucose or saline; however, trehalose supplementation did not result in CDI, although limited spore germination did occur. The absence of CDI in trehalose model was associated with enhanced abundances of Finegoldia, Faecalibacterium and Oscillospira, and reduced abundances of Klebsiella and Clostridium spp., compared with the other models. Functional analysis of the microbiota in the trehalose model revealed differences in the metabolic pathways, such as amino acid metabolism, which could be attributed to prevention of CDI. Our data show that trehalose supplementation remodelled the microbiota, which prevented simulated CDI, potentially due to enhanced recovery of nutritionally competitive microbiota against C. difficile.

microbiology↗

bioRxiv2021

Machine learning reveals cryptic dialects that guide mate choice in a songbird

Culturally transmitted communication signals - such as human language or bird song - can change over time through a process of cultural drift, and may consequently enhance the separation of populations, potentially leading to reproductive isolation1-4. Local song dialects have been identified in bird species with relatively simple songs where individuals show high cultural conformity5-10. In contrast, the emergence of cultural dialects has been regarded as unlikely11-13 for species with more variable song, such as the zebra finch (Taeniopygia guttata). Instead, it has been proposed that selection for individual recognition and distinctiveness may lead to a complete spread across the space of acoustic and syntactical possibilities11-15. However, another possibility is that analytical limitations have meant that subtle but possibly salient group differences have not yet been discovered in such species. Here we show that machine learning can distinguish the songs from multiple captive zebra finch populations with remarkable precision, and that these cryptic song dialects drive strong assortative mating in this species. We studied mating patterns across three consecutive generations using captive populations that have evolved in isolation for about 100 generations. Cross-fostering eggs within and between these populations and quantifying social interactions of the resulting offspring later in life revealed that mate choice primarily targets cultural traits that are transmitted during a short developmental time window. Detailed social networks showed that females preferentially approached males whose song resembled that of their adolescent peers. Our study shows that birds can be surprisingly sensitive to cultural traits for mating that have hitherto remained cryptic, even in this well-studied species that is used as a model for song-learning13,14,16-28.

animal behavior and cognition↗

bioRxiv2021

Genome-wide prediction and integrative functional characterization of Alzheimer's disease-associated genes

The mechanism of Alzheimers disease (AD) remains elusive, partly due to the incomplete identification of risk genes. We developed an approach to predict AD-associated genes by learning the functional pattern of curated AD-associated genes from brain gene networks. We created a pipeline to evaluate disease-gene association by interrogating heterogeneous biological networks at different molecular levels. Our analysis showed that top-ranked genes were functionally related to AD. We identified gene modules associated with AD pathways, and found that top-ranked genes were correlated with both neuropathological and clinical phenotypes of AD on independent datasets. We also identified potential causal variants for genes such as FYN and PRKAR1A by integrating brain eQTL and ATAC-seq data. Lastly, we created the ALZLINK web interface, enabling users to exploit the functional relevance of predicted genes to AD. The predictions and pipeline could become a valuable resource to advance the identification of therapeutic targets for AD.

bioinformatics↗

bioRxiv2021

Genome-wide transcriptome and translatome analyses reveal the role of protein extension and domestication in liver cancer oncogenesis

One gene could be transcribed to different RNA isoforms, and then produce various forms of protein sequences. This mechanism largely diversifies the cellular pool and allows natural selection to select from a wider range of substrates. Most of the deleterious changes should be either purged or only be observed in patients with deficiencies or diseases. In the cancer field, the "intra-gene" changes between tumor and normal tissues such as the alternative splicing, stop codon read-through, or protein domestication could not be captured by differential expression analyses. In this work, we collected public transcriptome and translatome data from ten patients with liver cancer, and performed genome-wide comparison on the stop codon read-through and protein domestication events. Both events could diversify the proteome without changing the genome sequence. Surprisingly, we found that compared to normal tissues, the tumor tissues globally have significantly higher occurrence of stop codon read-through events. Similarly, the translation signals of non-coding repetitive elements (protein domestication) are elevated in tumor samples. These read-through and domestication events show limited overlapping across the ten patients, suggesting the randomness of the occurrence. It also indicates that these tumor-specific read-through and domestication events should be deleterious, and should be purged by natural selection if they are not collected timely. Our work manifests the role of protein extension and domestication in liver cancer oncogenesis, and adds new aspects to the cancer field.

genomics↗

bioRxiv2021

deepManReg: a deep manifold-regularized learning model for improving phenotype prediction from multi-modal data

The biological processes from genotype to phenotype are complex involving multi-scale mechanisms. Increasing multi-modal data enables deeper understanding of underlying complex mechanisms in various phenotypes. However, integrating and interpreting such large-scale multi-modal data remains challenging, especially given highly heterogeneous, nonlinear relationships across modalities. To address this, we developed an interpretable regularized learning model, deepManReg to predict phenotypes from multi-modal data. First, deepManReg employs deep neural networks to learn cross-modal manifolds and then align multi-modal features onto a common latent space. This space aims to preserve both global consistency and local smoothness across modalities and reveal higher-order nonlinear cross-modal relationships. Second, deepManReg uses cross-modal manifolds as a feature graph to regularize the classifiers for improving phenotype predictions and also prioritizing the multi-modal features and cross-modal interactions for the phenotypes. We applied deepManReg to recent single cell multi-modal data such as Patch-seq data including transcriptomics and electrophysiology for neuronal cells in the mouse brain. We show that deepManReg significantly improves predicting cellular phenotypes and also prioritizing genes and electrophysiological features for the phenotypes. Finally, deepManReg is open-source and general for phenotype prediction from multi-modal data. deepManReg is open-source available at https://github.com/daifengwanglab/deepManReg.

bioinformatics↗

bioRxiv2021

Th17 immunity in the colon is controlled by two novel subsets of colon-specific mononuclear phagocytes

Intestinal immunity is coordinated by specialized mononuclear phagocyte populations, constituted by a diversity of cell subsets. Although the cell subsets constituting the mononuclear phagocyte network are thought to be similar in both small and large intestine, these organs have distinct anatomy, microbial composition, and immunological demands. Whether these distinctions demand organ-specific mononuclear phagocyte populations with dedicated organ-specific roles in immunity are unknown. Here we implement a new strategy to subset murine intestinal mononuclear phagocytes and identify two novel subsets which are colon-specific: a macrophage subset and a Th17-inducing dendritic cell (DC) subset. Colon-specific DCs and macrophages co-expressed CD24 and CD14, and surprisingly, both were dependent on the transcription factor IRF4. Novel IRF4-dependent CD14+CD24+ macrophages were markedly distinct from conventional macrophages and failed to express classical markers including CX3CR1, CD64 and CD88, and surprisingly expressed little IL-10, which was otherwise robustly expressed by all other intestinal macrophages. We further found that colon-specific CD14+CD24+ mononuclear phagocytes were essential for Th17 immunity in the colon, and provide definitive evidence that colon and small intestine have distinct antigen presenting cell requirements for Th17 immunity. Our findings reveal unappreciated organ-specific diversity of intestine-resident mononuclear phagocytes and organ-specific requirements for Th17 immunity.

immunology↗

bioRxiv2021

Comparison of Two Illumina Whole Transcriptome RNA Sequencing Library Preparation Methods Using Human FFPE Specimens

RNA extraction and library preparation from formalin-fixed, paraffin-embedded (FFPE) samples are crucial pre-analytical steps towards achieving optimal downstream RNA Sequencing (RNASeq) results. We assessed the Illumina TruSeq Stranded Total RNA library preparation method and the Illumina TruSeq RNA Access library preparation method for RNA-Seq analysis using 25 FFPE samples from human cancer indications (NSCLC, CRC, RC, BC and HCC) at two independent vendors. These FFPE samples covered a wide range of sample storage durations (3-25 years-old), sample qualities, and specimen types (resection vs. core needle biopsy). Our data showed that TruSeq RNA Access libraries yield over 80% exonic reads across different quality samples, indicating higher selectivity of the exome pull down by the capture approach compared to the random priming of the TruSeq Stranded Total kit. The overall QC data for FFPE RNA extraction, library preparation, and sequencing generated by the two vendors are comparable, and downstream gene expression quantification results show high concordance as well. With the TruSeq Stranded Total kit, the average Spearman correlation between vendors was 0.87 and the average Pearson correlation was 0.76. With the TruSeq RNA Access kit, the average Spearman correlation between vendors was 0.89 and the average Pearson correlation was 0.73. Interestingly, examination of the crossvendor correlations compared to various common QC statistics suggested that library concentration is better correlated with consistency between vendors than is the RNA quantity. Our analyses provide evidence to guide selection of sequencing methods for FFPE samples in which the sample quality may be severely compromised.

genomics↗

bioRxiv2021

The VTA-BLA-NAc circuit for sex reward inhibited by VTA GABAergic neurons under stress in male mice

Anhedonia, inability to experience pleasure from rewarding or enjoyable activities, is the prominent symptom of depression that involves dysfunction of the reward processing system. Both genetic predisposition and life events are thought to increase the risk for depression, in particular life stress. The cellular mechanism underlying stress modulating the reward processing neural circuits and subsequently disrupting reward-related behaviors remains elusive. We identify the VTA-BLA-NAc pathway as being activated by sex reward. Blockade of this circuit induces depressive-like behaviors, while reactivation of VTA neurons associated with sexual rewarding experience acutely ameliorates the impairment of reward-seeking behaviors induced by chronic restraint stress. Our histological and electrophysiological results show that the VTA neuron subpopulation responding to restraint stress inhibits the responsiveness of the VTA dopaminergic neurons to sexual reward. Together, these results reveal the cellular mechanism by which stress influences the brain reward processing system and provide a potential target for depression treatment.

neuroscience↗

bioRxiv2021

Combined Enhanced Biological Phosphorus Removal (EBPR) and Nitrite Accumulation for Treating High-strength Wastewater

The enhanced biological phosphorus removal (EBPR) has been widely applied in treating domestic wastewater, while the performance on high-strength P wastewater is less investigated and the feasibility of coupling with short-cut nitrogen removal process remains unknown. This study first achieved the simultaneous high-efficient P removal and stable nitrite accumulation in one sequencing batch reactor for treating the synthetic digested manure wastewater. The average effluent P could be down to 0.8 {+/-} 1.0 mg P/L and the P removal efficiency was 99.5 {+/-} 0.8%. Candidatus Accumulibacter was the dominant polyphosphate accumulating organism (PAO) with the relative abundance of 14.2-33.1% in the reactor. Examination of the micro-diversity of Candidatus Accumulibacter using 16s rRNA gene-based oligotyping analysis revealed one unique Accumulibacter oligotype that different from the conventional system, which accounted for 64.2-87.9% of the total Accumulibacter abundance. The presence of high-abundant glycogen accumulating organisms (GAO) (15.6-40.3%, Defluviicoccus and Candidatus Competibacter) did not deteriorate the EBPR performance. Moreover, nitrite accumulation happened in the system with the effluent nitrite up to 20.4 {+/-} 6.4 mg N/L and the nitrite accumulation ratio was nearly 100% maintained for 140 days (420 cycles). Nitrosomonas was the dominant ammonia-oxidizing bacteria with relative abundance of 0.3-2.4% while nitrite-oxidizing bacteria were almost undetected (<0.1%). The introduction of extended anaerobic phase and high volatile fatty acid concentrations were proposed to be the potential selector forces to promote partial nitrification. This is the first study that combined EBPR with nitrite-accumulation for digested manure wastewater treatment, and it provided new sights in strategies to combine the EBPR and short-cut nitrogen removal via nitrite to achieve simultaneous nitrogen and phosphorus removal.

bioengineering↗

bioRxiv2021

Lipid contact probability: an essential and predictive character for the structural and functional studies of membrane proteins

One of the unique traits of membrane proteins is that a significant fraction of their hydrophobic amino acids is exposed to the hydrophobic core of lipid bilayers rather than being embedded in the protein interior, which is often not explicitly considered in the protein structure and function predictions. Here, we propose a characteristic and predictive quantity, the membrane contact probability (MCP), to describe the likelihood of the amino acids of a given sequence being in direct contact with the acyl chains of lipid molecules. We show that MCP is complementary to solvent accessibility in characterizing the outer surface of membrane proteins, and it can be predicted for any given sequence with a machine learning-based method by utilizing a training dataset extracted from MemProtMD, a database generated from molecular dynamics simulations for the membrane proteins with a known structure. As the first of many potential applications, we demonstrate that MCP can be used to systematically improve the prediction precision of the protein contact maps and structures.

biophysics↗

bioRxiv2021

In vivo structure and dynamics of the RNA genome of SARS-Cov-2

The SARS-CoV-2 coronavirus, which causes the COVID-19 pandemic, is one of the largest positive strand RNA viruses. Here we developed a simplified SPLASH assay and comprehensively mapped the in vivo RNA-RNA interactome of SARS-CoV-2 RNA during the viral life cycle. We observed canonical and alternative structures including 3-UTR and 5-UTR, frameshifting element (FSE) pseudoknot and genome cyclization in cells and in virions. We provide direct evidence of interactions between Transcription Regulating Sequences (TRS-L and TRS-Bs), which facilitate discontinuous transcription. In addition, we reveal alternative short and long distance arches around FSE, forming a "high-order pseudoknot" embedding FSE, which might help ribosome stalling at frameshift sites. More importantly, we found that within virions, while SARS-CoV-2 genome RNA undergoes intensive compaction, genome cyclization is weakened and genome domains remain stable. Our data provides a structural basis for the regulation of replication, discontinuous transcription and translational frameshifting, describes dynamics of RNA structures during life cycle of SARS-CoV-2, and will help to develop antiviral strategies.

genomics↗

bioRxiv2021

RNA-directed DNA methylation prevents rapid and heritable reversal of transposon silencing under heat stress in Zea mays.

In large complex plant genomes, RNA-directed DNA methylation (RdDM) ensures that epigenetic silencing is maintained at the boundary between genes and flanking transposable elements. In maize, RdDM is dependent on Modifer of Paramutation 1 (Mop1), a putative RNA dependent RNA polymerase. Here we show that although RdDM is essential for the maintenance of DNA methylation of a silenced MuDR transposon in maize, a loss of that methylation does not result in a restoration of activity. Instead, heritable maintenance of silencing is maintained by histone modifications. At one terminal inverted repeat (TIR) of this element, heritable silencing is mediated via H3K9 and H3K27 dimethylation, even in the absence of DNA methylation. At the second TIR, heritable silencing is mediated by H3K27 trimethylation, a mark normally associated with somatically inherited gene silencing. We find that a brief exposure of high temperature in a mop1 mutant rapidly reverses both of these modifications in conjunction with a loss of transcriptional silencing. These reversals are heritable, even in mop1 wild type progeny in which methylation is restored at both TIRs. These observations suggest that DNA methylation is neither necessary to maintain silencing, nor is it sufficient to initiate silencing once has been reversed. However, given that heritable reactivation only occurs in a mop1 mutant background, these observations suggest that DNA methylation is required to buffer the effects of environmental stress on transposable elements. Author SummaryMost plant genomes are mostly transposable elements (TEs), most of which are held in check by modifications of both DNA and histones. The bulk of silenced TEs are associated with methylated DNA and histone H3 lysine 9 demethylation (H3K9me2). In contrast, epigenetically silenced genes are often associated with histone lysine 27 trimethylation (H3K27me3). Although stress can affect each of these modifications, plants are generally competent to rapidly reset them following that stress. Here we demonstrate that although DNA methylation is not required to maintain silencing of the MuDR element, it is essential for preventing heat-induced, stable and heritable changes in both H3K9me2 and H3K27me3 at this element, and for concomitant changes in transcriptional activity. These finding suggest that RdDM acts to buffer the effects of heat on silenced transposable elements, and that a loss of DNA methylation under conditions of stress can have profound and long lasting effects on epigenetic silencing in maize.

genetics↗

bioRxiv2020

Machine Leaning-based Determination of Sampling Depth for Complex Environmental Systems: Case Study with Single-Cell Raman Spectroscopy Data in EBPR Systems

Rapid progress in various advanced analytical methods such as single-cell technologies enable unprecedented and deeper understanding of microbial ecology beyond the resolution of conventional approaches. A major application challenge exists in the determination of sufficient sample size without sufficient prior knowledge of the community complexity and, the need to balance between statistical power and limited time or resources. This hinders the desired standardization and wider application of these technologies. Here, we proposed, tested and validated a computational sampling size assessment protocol taking advantage of a metric, named kernel divergence. This metric has two advantages: First, it directly compares dataset-wise distributional differences with no requirements on human intervention or prior knowledge-based pre-classification. Second, minimal assumptions in distribution and sample space are made in data processing to enhance its application domain. This enables test-verified appropriate handling of datasets with both linear and non-linear relationships. The model was then validated in a case study with eight SCRS phenotyping datasets each sampled from a different enhanced biological phosphorus removal (EBPR) activated sludge community located across North America. The model allows the determination of sufficient sampling size for any targeted or customized information capture capacity or resolution level. For example, an approximated sampling size of 50 or 100 spectra for full-scale EBPR-related ecosystems at 5% or 2% OPU cluster resolution. Promised by its flexibility and minimal restriction of input data types, the proposed method is expected to be a standardized approach for sampling size optimization, enabling more comparable and reproducible experiments and analysis on complex environmental samples. Finally, these advantages exhibit the capability of generalizing to other single-cell technologies or environmental applications, provided that the input datasets contain only continuous features. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=182 SRC="FIGDIR/small/423496v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@1261a6eorg.highwire.dtl.DTLVardef@91369aorg.highwire.dtl.DTLVardef@197f64dorg.highwire.dtl.DTLVardef@1ab3c19_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Broad transcriptomic dysregulation across the cerebral cortex in ASD

Classically, psychiatric disorders have been considered to lack defining pathology, but recent work has demonstrated consistent disruption at the molecular level, characterized by transcriptomic and epigenetic alterations.1-3 In ASD, upregulation of microglial, astrocyte, and immune signaling genes, downregulation of specific synaptic genes, and attenuation of regional gene expression differences are observed.1,2,4-6 However, whether these changes are limited to the cortical association areas profiled is unknown. Here, we perform RNA-sequencing (RNA-seq) on 725 brain samples spanning 11 distinct cortical areas in 112 ASD cases and neurotypical controls. We identify substantially more genes and isoforms that differentiate ASD from controls than previously observed. These alterations are pervasive and cortex-wide, but vary in magnitude across regions, roughly showing an anterior to posterior gradient, with the strongest signal in visual cortex, followed by parietal cortex and the temporal lobe. We find a notable enrichment of ASD genetic risk variants among cortex-wide downregulated synaptic plasticity genes and upregulated protein folding gene isoforms. Finally, using snRNA-seq, we determine that regional variation in the magnitude of transcriptomic dysregulation reflects changes in cellular proportion and cell-type-specific gene expression, particularly impacting L3/4 excitatory neurons. These results highlight widespread, genetically-driven neuronal dysfunction as a major component of ASD pathology in the cerebral cortex, extending beyond association cortices to involve primary sensory regions.

neuroscience↗

bioRxiv2020

Isothermal Amplification of Nucleic Acids with Ladder-shape Melting Curve

A novel method termed isothermal amplification of nucleic acids with ladder-shape melting curve (LMCP) was developed in the study. In this method, one pair of primers or two pairs of nested primers and a thermostable DNA polymerase (large fragment) were employed to amplify the internal transcribed spacer (ITS) of Oryza sativa with ladder-shape melting curve. Our results demonstrated that the LMCP assay with nested primers was 50-fold more sensitive and one-hour faster than the LAMP assay with the same level of specificity. The LMCP method has the potential to be used for the prevention and control of the emerging epidemics.

biochemistry↗

bioRxiv2020

Neuronal Enhancers are Hotspots For DNA Single-Strand Break Repair

Genome stability is essential for all cell types. However, defects in DNA repair frequently lead to neurodevelopmental and neurodegenerative diseases, underscoring the particular importance of DNA repair in long-lived post-mitotic neurons. The neuronal genome is subjected to a constant barrage of endogenous DNA damage due to high levels of oxidative metabolism in the central nervous system. Surprisingly, we know little about the identity of the lesion(s) that accumulate in neurons and whether they accrue throughout the genome or at specific loci. Here, we show that neurons, but not other post-mitotic cells, accumulate unexpectedly high numbers of DNA single-strand breaks (SSBs) at specific sites within the genome. These recurrent SSBs are found within enhancers, and trigger DNA repair through recruitment and activation of poly(ADP-ribose) polymerase-1 (PARP1) and XRCC1, the central SSB repair scaffold protein. Notably, deficiencies in PARP1, XRCC1, or DNA polymerase {beta} elevate the localized incorporation of nucleotides, suggesting that the ongoing DNA synthesis at neuronal enhancers involves both short-patch and long-patch SSB repair processes. These data reveal unexpected levels of localized and continuous DNA single-strand breakage in neurons, suggesting an explanation for the neurodegenerative phenotypes that occur in patients with defective SSB repair.

neuroscience↗