Biology subjects

Chen, R.

Publications and source records attributed to Chen, R..

At least 343 records · Page 19Linked to original sources

bioRxiv2020

Multi-epitope vaccine design using an immunoinformatics approach for 2019 novel coronavirus in China (SARS-CoV-2)

A new coronavirus SARS-CoV-2 has caused over 9.2 million infection cases and 475758 deaths worldwide. Due to the rapid dissemination and the unavailability of specific therapy, there is a desperate need for vaccines to combat the epidemic of SARS-CoV-2. An in silico approach based on the available virus genome was applied to identify 19 high immunogenic B-cell epitopes and 499 human-leukocyte-antigen (HLA) restricted T-cell epitopes. Thirty multi-epitope peptide vaccines were designed by iNeo Suite, and manufactured by solid-phase synthesis. Docking analysis showed stable hydrogen bonds of epitopes with their corresponding HLA alleles. When four vaccine peptide candidates from the spike protein of SARS-CoV-2 were selected to immunize mice, a significantly larger amount of IgG in serum as well as an increase of CD19+ cells in ILNs was observed in peptide-immunized mice compared to the control mice. The ratio of IFN-{gamma}-secreting lymphocytes in CD4+ or CD8+ cells in the peptides-immunized mice were higher than that in the control mice. There were also a larger number of IFN-{gamma}-secreting T cells in spleen in the peptides-immunized mice. This study screened antigenic B-cell and T-cell epitopes in all encoded proteins of SARS-CoV-2, and further designed multi-epitope based peptide vaccine against viral structural proteins. The obtained vaccine peptides successfully elicited specific humoral and cellular immune responses in mice. Primate experiments and clinical trial are urgently required to validate the efficacy and safety of these vaccine peptides. ImportanceSo far, a new coronavirus SARS-CoV-2 has caused over 9.2 million infection cases and 475758 deaths worldwide. Due to the rapid dissemination and the unavailability of specific therapy, there is a desperate need for vaccines to combat the epidemic of SARS-CoV-2. Different from the development approaches for traditional vaccines, the development of our peptide vaccine is faster and simpler. In this study, we performed an in silico approach to identify the antigenic B-cell epitopes and human-leukocyte-antigen (HLA) restricted T-cell epitopes, and designed a panel of multi-epitope peptide vaccines. The resulting SARS-CoV-2 multi-epitope peptide vaccine could elicit specific humoral and cellular immune responses in mice efficiently, displaying its great potential in our fight of COVID-19.

bioinformatics↗

bioRxiv2020

Profiling the immune vulnerability landscape of the 2019 Novel Coronavirus

The outbreak of the 2019 Novel Coronavirus (SARS-CoV-2) rapidly spread from Wuhan, China to more than 150 countries, areas, or territories, causing staggering numbers of infections and deaths. In this study, bioinformatics analyses were performed on 5,568 complete genomes of SARS-CoV-2 virus to predict the T cell and B cell immunogenic epitopes of all viral proteins, which formed a systematic immune vulnerability landscape of SARS-CoV-2. The immune vulnerability and genetic variation profiles of SARS-CoV were compared with those of SARS-CoV and MERS-CoV. In addition, a web portal was developed to broadly share the data and results as a resource for the research community. Using this resource, we showed that genetic variations in SARS-CoV-2 are associated with loss of B cell immunogenicity, an increase in CD4+ T cell immunogenicity, and a minimum loss in CD8+ T cell immunogenicity, indicating the existence of a curious correlation between SARS-CoV-2 genetic evolutions and the immunity pressure from the host. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic/vaccine development and mechanistic research.

bioinformatics↗

bioRxiv2020

The Physical Structure and Behavior of the California Current System

This paper is the first of two that present a 16-year hindcast solution from a coupled physical and biogeochemical model of the California Current System (CCS) along the U. S. West Coast and validate the physical solution with respect to mean, seasonal, interannual, and sub-seasonal fields and, to a lesser degree, eddy variability. Its companion paper is Deutsch et al. (2021a). The intent is to construct and demonstrate a modeling tool that will be used for mechanistic explanations, attributive causal assessments, and forecasts of future evolution for circulation and biogeochemistry, with particular attention to the increasing oceanic stratification, deoxygenation, and acidification. A well-resolved mesoscale (dx = 4 km) simulation of the CCS circulation is made with the Regional Oceanic Modeling System over a hindcast period of 16 years from 1995 to 2010. The oceanic solution is forced by a high-resolution (dx = 6 km) regional configuration of the Weather and Research Forecast (WRF) atmospheric model. Both of these high-resolution regional oceanic and atmospheric simulations are forced by lateral open boundary conditions taken from larger-domain, coarser-resolution parent simulations that themselves have boundary conditions from the Mercator and Climate Forecast System reanalyses, respectively. We show good agreement between the simulated atmospheric forcing of the oceanic and satellite measurements for the spatial patterns and temporal variability for the surface fluxes of momentum, heat, and freshwater. The simulated oceanic physical fields are then evaluated with satellite and in situ measurements. The simulation reproduces the main structure of the climatological upwelling front and cross-shore isopycnal slopes, the mean current patterns (including the California Undercurrent), and the seasonal, interannual, and subseasonal variability. It also shows agreement between the mesoscale eddy activity and the windwork energy exchange between the ocean and atmosphere modulated by influences of surface current on surface stress. Finally, the impact of using a high frequency wind forcing is assessed for the importance of synoptic wind variability to realistically represent oceanic mesoscale activity and ageostrophic inertial currents.

ecology↗

bioRxiv2020

A Cretaceous bug indicates that exaggerated antennae may be a double-edged sword in evolution

In the competition for the opposite sex, sexual selection can favor production of exaggerated features, but the high cost of such features in terms of energy consumption and enemy avoidance makes them go to extinction under the influence of natural selection. However, to our knowledge, fossil on exaggerated traits that are conducive to attracting opposite sex are very rare. Here, we report the exaggerated leaf-like expansion antennae of Magnusantenna wuae Du & Chen gen. et sp. nov. (Hemiptera: Coreidae) with more abundant sensory hairs from a new nymph coreid preserved in a Cretaceous Myanmar amber. The antennae are the largest among species of coreid and one of the largest known insects. Such bizarre antennae indicate that sensitive and delicate sensory system and magnificent appearance in Hemiptera have been already well established in mid-Cretaceous. Our findings provide evidence for Darwins view that sensory organs play an important role in sexual selection. This nymph with the leaf-like antennae may also represents a new camouflage pattern for defense. However, the oversized antennae are costly to develop and maintain, increasing the risks from predators. Such unparalleled expanded antennae might be the key factor for the evolutionary fate of this Myanmar amber coreid species. SignificanceDarwin proposed the importance of sensory organs in sexual selection, but it was greatly ignored compared with weapons and other common ornaments. Here, we report a new type of insect antennae, the multiple segments leaf-like expansion antennae from a new nymph coreid preserved in a Cretaceous Myanmar amber. Our finding provides evidence for the prominent role of sensory organs in sexual selection and thus supports Darwins viewpoint. This discovery demonstrates that high-efficiency antennae were present in Coreidae 99 million years ago. In addition, the exaggerated antennae might represent a new evolutionary innovation for defensive behavior. This is a case in which the high benefits and high costs brought by the exaggerated antennae jointly determine the direction of species evolution.

paleontology↗

bioRxiv2020

A single-cell RNAseq atlas of the pathogenic stage of Schistosoma mansoni identifies a key regulator of blood feeding

Schistosomiasis is an ancient and chronic neglected tropical disease that infects over 240 million people and kills over 200,000 of the worlds poorest people every year1, 2. There are no vaccines and because there is only one drug available, the need for new therapeutics is great. The causative agents of this disease are flatworm parasites that dwell inside the hosts circulation, often for decades, where they feed on blood and lay eggs which are primarily responsible for disease pathology. As metazoans comprised of multiple tissue types, understanding the schistosomes tissues on a molecular level and their functions during what can be decades of successful parasitism could suggest novel therapeutic strategies. Here, we employ single-cell RNAseq to characterize 43,642 cells from the pathogenic (adult) stage of the schistosome lifecycle. From these data, we characterize 68 molecularly distinct cell populations that comprise nearly all tissues described morphologically, including the nervous and reproductive systems. We further uncover a lineage of somatic stem cells responsible for producing and maintaining the parasites gut - the primary tissue responsible for digestion of host blood. Finally, we show that a homologue of hepatocyte nuclear factor 4 (hnf4) is expressed in this gut lineage and required for gut maintenance, blood feeding and inducing egg-associated pathology in vivo. Together, the data highlight the utility of this single-cell RNAseq atlas to understand schistosome biology and identify potential therapeutic interventions.

microbiology↗

bioRxiv2020

A Refined View of Airway Microbiome in Chronic Obstructive Pulmonary Disease at Species and Strain-levels

Little is known about the species and strain-level diversity of the airway microbiome, and its implication in chronic obstructive pulmonary disease (COPD). Here we report the first comprehensive analysis of the COPD airway microbiome at species and strain-levels. The full-length 16S rRNA gene was sequenced from sputum in 98 stable COPD patients and 27 age-matched healthy controls, using the third-generation Pacific Biosciences sequencing platform. Individual species within the same genus exhibited reciprocal relationships with COPD and disease severity. Species dominant in health can be taken over by another species within the same genus in GOLD IV patients. Such turnover was also related to enhanced symptoms and exacerbation frequency. Ralstonia mannitolilytica, an opportunistic pathogen, was significantly increased in COPD frequent exacerbators. There were inflammatory phenotype-specific associations of microbiome at the species-level. One group of four pathogens including Haemophilus influenzae and Moraxella catarrhalis, were specifically associated with sputum mediators for neutrophilic inflammation. Another group of seven species, including Tropheryma whipplei, showed specific associations with mediators for eosinophilic inflammation. Strain-level detection uncovered three non-typeable H. influenzae strains PittEE, PittGG and 86-028NP in the airway microbiome, where PittGG and 86-028NP abundances may inversely predict eosinophilic inflammation. The full-length 16S data augmented the power of functional inference and led to the unique identification of butyrate-producing and nitrate reduction pathways as significantly depleted in COPD. Our analysis uncovered substantial intra-genus heterogeneity in the airway microbiome associated with inflammatory phenotypes and could be of clinical importance, thus enabled a refined view of the airway microbiome in COPD. "Take-home" messageThe species-level analysis using the third-generation sequencing enabled a refined view of the airway microbiome and its relationship with clinical outcome and inflammatory phenotype in COPD.

microbiology↗

bioRxiv2019

An optimized 16S rRNA sequencing protocol for vaginal microbiome to avoid biased abundance estimation

We applied three 16S rRNA sequencing protocols on vaginal microbiome samples, to evaluate whether they produce unbiased estimation of vaginal microbiome composition. We modified the 27F primer (hereafter denoted as 27F). Using vaginal samples from 28 healthy women and 10 women with bacterial vaginosis, we sequenced three 16S rRNA sequencing protocols, i.e., 27F-338R, 27F-338R and 341F-806R protocols, naming after their PCR primer sets, to test whether the sequencing results are consistent with the clinical diagnostics, morphology and qPCR results. First, the 27F primer would not align with Gardnerlla vaginalis very well, leading to poor amplification of such species. By modifying the primer sequences, the modified 27F primer (27F) was able to amplify Gardnerlla vaginalis very well. Second, the DNA sequence of characteristic species Lactobacillus crispatus is identical with Lactobacillus garrinarum, leading to biased estimation of abundance of Lactobacillus crispatus when using V3-V4 as PCR target region; in contrast, such bias did not occur when using V1-V2 as a target region. Third, optimized 27F-338R avoided above-mentioned biases and restored the well-established community state types (CSTs) clustering. ImportanceVaginal microbiome has profound effects on the health of women and their newborns. Our study found that two well-established 16S rDNA sequencing protocols led to systementical biased estimation of characteristic species of vaginal microbiome. Subsequent analysis proved that the PCR primer fetching efficacy and target region identity were major contributor for such bias. With carefully selected target region and optimized PCR primer set, we were able to eliminate such biases and provide accurate estimation of vaginal microbiome, which showed high consistency with clinical diagnostics. We modified the 27F primer (27F). Using the optimized PCR primer set of 27F and 338R to target the V1-V2 hyper-variable region, our 16S rRNA sequencing correctly evaluate the composition of vaginal microbiome.

microbiology↗

bioRxiv2019

DRAMS: A Tool to Detect and Re-Align Mixed-up Samples for Integrative Studies of Multi-omics Data

Studies of complex disorders benefit from integrative analyses of multiple omics data. Yet, sample mix-ups frequently occur in multi-omics studies, weakening statistical power and risking false findings. Accurately aligning sample information, genotype, and corresponding omics data is critical for integrative analyses. We developed DRAMS (https://github.com/Yi-Jiang/DRAMS) to Detect and Re-Align Mixed-up Samples to address the sample mix-up problem. It uses a logistic regression model followed by a modified topological sorting algorithm to identify the potential true IDs based on data relationships of multi-omics. According to tests using simulated data, the more types of omics data used or the smaller the proportion of mix-ups, the better that DRAMS performs. Applying DRAMS to real data from the PsychENCODE BrainGVEX project, we detected and corrected 201 (12.5% of total data generated) mix-ups. Of the 21 mix-ups involving errors of racial identity, DRAMS re-assigned all samples to the correct racial cluster in the 1000 Genomes project. In doing so, quantitative trait loci (QTL) (FDR<0.01) increased by an average of 1.62-fold. The use of DRAMS in multi-omics studies will strengthen statistical power of the study and improve quality of the results. Even though very limited studies have multi-omics data in place, we expect such data will increase quickly with the needs of DRAMS.\n\nAuthor summarySample mix-up happens inevitably during sample collection, processing, and data management. It leads to reduced statistical power and sometimes false findings. It is of great importance to correct mixed-up samples before conducting any downstream analyses. We developed DRAMS to detect and re-align mixed-up samples in multi-omics studies. The basic idea of DRAMS is to align the data and labels for each sample leveraging the genetic information of multi-omics data. DRAMS corrects sample IDs following a two-step strategy. At first, it estimates pairwise genetic relatedness among all the data generated from all the individuals. Because the different data generated from the same individual should share the same genetics, we can cluster all the highly related data and consider that the data from one cluster have only one potential ID. Then, we used a \"majority vote\" strategy to infer the potential ID for individuals in each cluster. Other information, such as match of genetics-based and reported sexes, omics priorority, etc., were also used to direct identifying the potential IDs. It has been proved that DRAMS performs very well in both simulation and PsychENCODE BrainGVEX multi-omics data.

bioinformatics↗

bioRxiv2019

Genome sequence and analysis of the eggplant (Solanum melongena L.)

The eggplant (Solanum melongena L.) is one of the most important Solanaceae crops, ranking third in the total production and economic value in the genus Solanum. Here, we report a high-quality, chromosome-scale eggplant reference genome sequence of 1,155.8 Mb, with N50 of 93.9 Mb, which was assembled by combining PacBio long reads and Hi-C sequencing data. Repetitive sequences occupied 70.1% of the assembly length, and 35,018 high-confidence protein-coding genes were annotated based on multiple evidence. Comparative analysis revealed 646 species-specific families and 364 positive selection genes, conferring distinguishing traits to the eggplant. We performed genome-wide identification of disease resistance genes and discovered an expanded gene family of bacterial spot resistance in the eggplant and pepper but not in tomato and potato. The genes involved in chlorogenic acid synthesis were comprehensively characterized. Highly similar chromosomal distribution patterns of polyphenol oxidase genes were observed in the eggplant, tomato, and potato genomes. The eggplant reference genome sequence will not only facilitate evolutionary studies in the Solanaceae but also facilitate their breeding and improvement.

genomics↗

bioRxiv2019

Identification and genetic validation of drug-comorbidity interactions in type 2 diabetes using data-driven disease trajectory analysis

Given various risk profiles, manifestations, comorbidities, and outcomes for individuals with Type 2 diabetes mellitus (T2D), a one-size-fits-all approach towards treatment and management is inadequate, and there is a clear need for personalized medications to reduce rates of complications and comorbidities. Here, we leveraged comprehensive Electronic Medical Records (EMR) to identify associations between T2D comorbidities and medications and evaluated their biological determinants using EMR-linked genetic information. We discovered clinically novel associations supported by the previous laboratory studies; e.g. 5-hydroxytryptamine 3 receptor antagonists, ondansetron and granisetron, are protective against cognitive disorders, and clopidogrel is protective against retinopathy. Furthermore, potentially novel associations were validated by genetic analysis; e.g. association between gabapentin and cognitive disorders was supported via variants of its target genes, GRIN1 and CACNA2D2. These results of the current study open the door for optimizing treatment combinations to mitigate risks and for individualizing therapy based on T2D subtype risk profiles.

bioinformatics↗

bioRxiv2019

A Chemoenzymatic Method for Glycoproteomic N-glycan Type Quantitation

Glycosylation is one of the most important post-translational modifications in biological systems. Current glycoproteome methods mainly focus on qualitative identification of glycosylation sites or intact glycopeptides. However, the systematic quantitation of glycoproteins has remained largely unexplored. Here, we developed a chemoenzymatic method to quantitatively investigate N-glycoproteome based on the N-glycan types. Taking advantage of the specificity of different endoglycosidases and isotope dimethyl labeling, six N-glycan types of structures linked on each glycopeptide, including high-mannose/hybrid, bi-antennary and tri-antennary with/without core fucose, were quantified. As a proof of principle, the glycoproteomic N-glycan type quantitative (glyco-TQ) method was first used to determine the N-glycan type composition of immunoglobulin G1 (IgG1) Fc fragment. Then we applied the method to analyze the glycan type profile of proteins in the breast cancer cell line MCF7, and quantitatively revealed the N-glycan type micro-heterogeneity at both the glycopeptide and glycoprotein levels. The novel quantitative strategy to evaluate the relative intensity of the six states of N-glycan type glycosylation on each site provides a new avenue to investigate function of glycoproteins in broad areas, such as cancer biomarker research, pharmaceuticals characterization and anti-glycan vaccine development.

systems biology↗

bioRxiv2019

Gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code that governs gene expression is a primary, yet challenging aspiration in molecular biology that opens up possibilities to cure human diseases and solve biotechnology problems. However, the fundamental question of how each of the individual coding and non-coding regions of the gene regulatory structure interact and contribute to the mRNA expression levels remains unanswered. Considering that all the information for gene expression regulation is already present in living cells, here we applied deep learning on over 20,000 mRNA datasets in 7 model organisms ranging from bacteria to Human. We show that in all organisms, mRNA abundance can be predicted directly from the DNA sequence with high accuracy, demonstrating that up to 82% of the variation of gene expression levels is encoded in the gene regulatory structure. Coding and non-coding regions carry both overlapping and orthogonal information and additively contribute to gene expression levels. By searching for DNA regulatory motifs present across the whole gene regulatory structure, we discover that motif interactions can regulate gene expression levels in a range of over three orders of magnitude. The uncovered co-evolution of coding and non-coding regions challenges the current paradigm that single motifs or regions are solely responsible for gene expression levels. Instead, we show that the correct combination of all regulatory regions must be established in order to accurately control gene expression levels. Therefore, the holistic system that spans the entire gene regulatory structure is required to analyse, understand, and design any future gene expression systems.

systems biology↗

bioRxiv2019

Deciphering anomalous heterogeneous intracellular transport with neural networks

Biological intracellular transport is predominantly heterogeneous in both time and space, exhibiting varying non-Brownian behaviour. Characterisation of this movement through averaging methods over an ensemble of trajectories or over the course of a single trajectory often fails to capture this heterogeneity adequately. Here, we have developed a deep learning feedforward neural network trained on fractional Brownian motion, which provides a novel, accurate and efficient characterization method for resolving heterogeneous behaviour of intracellular transport both in space and time. Importantly, the neural network requires significantly fewer data points compared to established methods, such as mean square displacements, rescaled range analysis and sequential range analysis. This enables robust estimation of Hurst exponents for very short time series data, making possible direct, dynamic segmentation and analysis of experimental tracks of rapidly moving cellular structures such as endosomes and lysosomes. By using this analysis, we were able to interpret anomalous intracellular dynamics as fractional Brownian motion with a stochastic Hurst exponent.

cell biology↗

bioRxiv2019

A CLN6-CLN8 complex recruits lysosomal enzymes at the ER for Golgi transfer

Lysosomal enzymes are synthesized in the endoplasmic reticulum (ER) and transferred to the Golgi complex by interaction with the Batten disease protein CLN8. Here we investigated the relationship of this pathway with CLN6, an ER-associated protein of unknown function that is defective in a different Batten disease subtype. Experiments focused on protein interaction and trafficking identified CLN6 as an obligate component of a CLN6-CLN8 complex (herein referred to as EGRESS: ER-to-Golgi relaying of enzymes of the lysosomal system) which recruits lysosomal enzymes at the ER to promote their Golgi transfer. Simultaneous deficiency of CLN6 and CLN8 did not aggravate mouse pathology compared to the single deficiencies, indicating that the EGRESS complex works as a functional unit. Mutagenesis experiments showed that the second luminal loop of CLN6 is required for the interaction of CLN6 with the enzymes but dispensable for interaction with CLN8, and in vitro and in vivo studies showed that CLN6 deficiency results in inefficient ER export of lysosomal enzymes and diminished levels of the enzymes at the lysosome. These results identify CLN6 and the EGRESS complex as key players in lysosome biogenesis and shed light on the molecular etiology of Batten disease caused by defects in CLN6.

cell biology↗

bioRxiv2019

Epigenetic adaptation prolongs photoreceptor survival during retinal degeneration

Neural degenerative diseases often display a progressive loss of cells as a stretched exponential distribution. The mechanisms underlying the survival of a subset of genetically identical cells in a population beyond what is expected by chance alone remains unknown. To gain mechanistic insights underlying prolonged cellular survival, we used Spata7 mutant mice as a model and performed single-cell transcriptomic profiling of retinal tissue along the time course of photoreceptor degeneration. Intriguingly, rod cells that survive beyond the initial rapid cell apoptosis phase progressively acquire a distinct transcriptome profile. In these rod cells, expression of photoreceptor-specific phototransduction pathway genes is downregulated while expression of other retinal cell type-specific marker genes is upregulated. These transcriptomic changes are achieved by modulation of the epigenome and changes of the chromatin state at these loci, as indicated by immunofluorescence staining and single-cell ATAC-seq. Consistent with this model, when induction of the repressive epigenetic state is blocked by in vivo histone deacetylase inhibition, all photoreceptors in the mutant retina undergo rapid degeneration, strongly curtailing the stretched exponential distribution. Our study reveals an intrinsic mechanism by which neural cells progressively adapt to genetic stress to achieve prolonged survival through epigenomic regulation and chromatin state modulation.

neuroscience↗

bioRxiv2019

Multiple overlapping hypothalamus-brainstem circuits drive rapid threat avoidance

Animals survive environmental challenges by adapting their physiology and behavior through homeostatic regulatory processes, mediated in part by specific neuropeptide release from the hypothalamus. Animals can also avoid environmental stressors within seconds, a fast behavioral adaptation for which hypothalamic involvement is not established. Using brain-wide neural activity imaging in behaving zebrafish, here we find that hypothalamic neurons are rapidly engaged during common avoidance responses elicited by various environmental stressors. By developing methods to register cellular-resolution neural dynamics to multiplexed in situ gene expression, we find that each category of stressor recruits similar combinations of multiple peptidergic cell types in the hypothalamus. Anatomical analysis and functional manipulations demonstrate that these diverse cell types play shared roles in behavior, are glutamatergic, and converge upon spinal-projecting brainstem neurons required for avoidance. These data demonstrate that hypothalamic neural populations, classically associated with slow and specific homeostatic adaptations, also together give rise to fast and generalized avoidance behavior.

neuroscience↗

bioRxiv2019

Trading Genome Vulnerability for Stable Genetic Inheritance: Active Retrotransposons Help Maintain Pericentromeric Heterochromatin Required for Faithful Cell Division

Retrotransposons are extensively populated in vertebrate genomes, which, when active, are thought to cause genome instability with potential benefit to genome evolution. Retrotransposon-derived RNAs are also known to give rise to small endo-siRNAs to help maintain heterochromatin at their sites of transcription; however, as not all heterochromatic regions are equally active in transcription, it remains unclear how heterochromatin is maintained across the genome. Here, we attack these problems by defining the origins of repeat-derived RNAs and their specific chromatin registers in Drosophila S2 cells. We demonstrate that repeat RNAs are predominantly derived from active Gypsy elements, and upon their processing by Dicer-2, these endo-siRNAs act in cis and trans to help maintain pericentromeric heterochromatin. Remarkably, we show that synthetic repeat-derived siRNAs are sufficient to rescue Dicer-2 deficiency-induced defects in heterochromatin formation in interphase and chromosome segregation during mitosis, thus demonstrating that active retrotransposons are actually required for stable genetic inheritance.

genomics↗

bioRxiv2019

A database for ITS2 sequences from nematodes

Marker gene surveys have a wide variety of applications in species identification, population genetics, and molecular epidemiology. As these methods expand to new types of organisms and additional markers beyond 16S and 18S rRNA genes, comprehensive databases are a critical requirement for proper analysis of these data. Here we present an ITS2 rDNA database for maker gene surveys of both free-living and parasitic nematode populations and the software used to build the database. This is an important resource for researchers working on nematodes and also provides a tool to create ITS2 databases for any given taxonomy.\n\nAvailability and ImplementationThe database is available as an interactive web app at https://cooperia.chgi.ucalgary.ca/Nematode_ITS2/. The full database can also be downloaded from zenodo https://doi.org/10.5281/zenodo.3235802, and the open source software used to create the database, markerDB is available at https://github.com/ucvm/markerDB/releases/latest.

bioinformatics↗