Inhibition of DNMTs increases neoantigen-reactive T-cell toxicity against microsatellite-stable colorectal cancer in combination with radiotherapy.

The therapeutic efficacy of immunotherapy is limited in the majority of colorectal cancer patients due to the low mutational and neoantigen burdens in this immunogenically "cold" microsatellite stability-colorectal cancer (MSS-CRC) cohort. Here, we showed that DNA methyltransferase (DNMT) inhibition upregulated neoantigen-bearing gene expression in MSS-CRC, resulting in increased neoantigen presentation by MHC class I in tumor cells and leading to increased neoantigen-specific T-cell activation in combination with radiotherapy. The cytotoxicity of neoantigen-reactive T cells (NRTs) to DNMTi-treated cancer cells was highly cytotoxic, and these cells secreted high IFNγ levels targeting MSS-CRC cells after ex vivo expansion of NRTs with DNMTi-treated tumor antigens. Moreover, the therapeutic efficacy of NRTs further increased when NRTs were combined with radiotherapy in vivo. Administration of DNMTi-augmented NRTs and radiotherapy achieved an ∼50 % complete response and extended survival time in an immunocompetent MSS-CRC animal model. Moreover, remarkably, splenocytes from these mice exhibited neoantigen-specific T-cell responses, indicating that radiotherapy in combination with DNMTi-augmented NRTs prolonged and increased neoantigen-specific T-cell toxicity in MSS-CRC patients. In addition, these DNMTi-augmented NRTs markedly increase the therapeutic efficacy of cancer vaccines and immune checkpoint inhibitors (ICIs). These data suggest that a combination of radiotherapy and epi-immunotherapeutic agents improves the function of ex vivo-expanded neoantigen-reactive T cells and increases the tumor-specific cytotoxic effector population to enhance therapeutic efficacy in MSS-CRC.

Neoantigen-augmented iPSC cancer vaccine combined with radiotherapy promotes antitumor immunity in poorly immunogenic cancers.

Although irradiated induced-pluripotent stem cells (iPSCs) as a prophylactic cancer vaccine elicit an antitumor immune response, the therapeutic efficacy of iPSC-based cancer vaccines is not promising due to their insufficient antigenicity and the immunosuppressive tumor microenvironment. Here, we found that neoantigen-engineered iPSC cancer vaccines can trigger neoantigen-specific T cell responses to eradicate cancer cells and increase the therapeutic efficacy of RT in poorly immunogenic colorectal cancer (CRC) and triple-negative breast cancer (TNBC). We generated neoantigen-augmented iPSCs (NA-iPSCs) by engineering AAV2 vector carrying murine neoantigens and evaluated their therapeutic efficacy in combination with radiotherapy. After administration of NA-iPSC cancer vaccine and radiotherapy, we found that ~60% of tumor-bearing mice achieved a complete response in microsatellite-stable CRC model. Furthermore, splenocytes from mice treated with NA-iPSC plus RT produced high levels of IFNγ secretion in response to neoantigens and had a greater cytotoxicity to cancer cells, suggesting that the NA-iPSC vaccine combined with radiotherapy elicited a superior neoantigen-specific T-cell response to eradicate cancer cells. The superior therapeutic efficacy of NA-iPSCs engineered by mouse TNBC neoantigens was also observed in the syngeneic immunocompetent TNBC mouse model. We found that the risk of spontaneous lung and liver metastasis was dramatically decreased by NA-iPSCs plus RT in the TNBC animal model. Altogether, these results indicated that autologous iPSC cancer vaccines engineered by neoantigens can elicit a high neoantigen-specific T-cell response, promote tumor regression, and reduce the risk of distant metastasis in combination with local radiotherapy.

Twnbiome: a public database of the healthy Taiwanese gut microbiome.

With new advances in next generation sequencing (NGS) technology at reduced costs, research on bacterial genomes in the environment has become affordable. Compared to traditional methods, NGS provides high-throughput sequencing reads and the ability to identify many species in the microbiome that were previously unknown. Numerous bioinformatics tools and algorithms have been developed to conduct such analyses. However, in order to obtain biologically meaningful results, the researcher must select the proper tools and combine them to construct an efficient pipeline. This complex procedure may include tens of tools, each of which require correct parameter settings. Furthermore, an NGS data analysis involves multiple series of command-line tools and requires extensive computational resources, which imposes a high barrier for biologists and clinicians to conduct NGS analysis and even interpret their own data. Therefore, we established a public gut microbiome database, which we call Twnbiome, created using healthy subjects from Taiwan, with the goal of enabling microbiota research for the Taiwanese population. Twnbiome provides users with a baseline gut microbiome panel from a healthy Taiwanese cohort, which can be utilized as a reference for conducting case-control studies for a variety of diseases. It is an interactive, informative, and user-friendly database. Twnbiome additionally offers an analysis pipeline, where users can upload their data and download analyzed results. Twnbiome offers an online database which non-bioinformatics users such as clinicians and doctors can not only utilize to access a control set of data, but also analyze raw data with a few easy clicks. All results are customizable with ready-made plots and easily downloadable tables. Database URL: http://twnbiome.cgm.ntu.edu.tw/ .

Multi-ethnic Imputation System (MI-System): A genotype imputation server for high-dimensional data.

OBJECTIVE: Genotype imputation is a commonly used technique that infers un-typed variants into a study's genotype data, allowing better identification of causal variants in disease studies. However, due to overrepresentation of Caucasian studies, there's a lack of understanding of genetic basis of health-outcomes in other ethnic populations. Therefore, facilitating imputation of missing key-predictor-variants that can potentially improve a risk health-outcome prediction model, specifically for Asian ancestry, is of utmost relevance. METHODS: We aimed to construct an imputation and analysis web-platform, that primarily facilitates, but is not limited to genotype imputation on East-Asians. The goal is to provide a collaborative imputation platform for researchers in the public domain towards rapidly and efficiently conducting accurate genotype imputation. RESULTS: We present an online genotype imputation platform, Multi-ethnic Imputation System (MI-System) (https://misystem.cgm.ntu.edu.tw/), that offers users 3 established pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1 for conducting imputation analyses. In addition to 1000 Genomes and Hapmap3, a new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. MI-System further offers functions to create customized reference panels to be used for imputation, conduct quality control, split whole genome data into chromosomes, and convert genome builds. CONCLUSION: Users can upload their genotype data and perform imputation with minimum effort and resources. The utility functions further can be utilized to preprocess user uploaded data with easy clicks. MI-System potentially contributes to Asian-population genetics research, while eliminating the requirement for high performing computational resources and bioinformatics expertise. It will enable an increased pace of research and provide a knowledge-base for genetic carriers of complex diseases, therefore greatly enhancing patient-driven research. STATEMENT OF SIGNIFICANCE: Multi-ethnic Imputation System (MI-System), primarily facilitates, but is not limited to, imputation on East-Asians, through 3 established prephasing-imputation pipelines, SHAPEIT2-IMPUTE2, SHAPEIT4-IMPUTE5, and Beagle5.1, where users can upload their genotype data and perform imputation and other utility functions with minimum effort and resources. A new customized Taiwan Biobank (TWB) reference panel, specifically created for Taiwanese-Chinese ancestry is provided. Utility functions include (a) create customized reference panels, (b) conduct quality control, (c) split whole genome data into chromosomes, and (d) convert genome builds. Users can also combine 2 reference panels using the system and use combined panels as reference to conduct imputation using MI-System.

Hypoxia-responsive circular RNA circAAGAB reduces breast cancer malignancy by activating p38 MAPK and sponging miR-378 h.

BACKGROUND: Breast cancer is a prevalent disease in women, with high prevalence worldwide. The hypoxic microenvironment of solid tumors develops during the progress of carcinogenesis and leads to greater malignancy and treatment resistance. Recently, accumulating evidence indicates that non-coding RNAs, such as circular RNAs (circRNAs), play a pivotal role in altering cellular functions. However, the underlying mechanisms of circRNAs in breast cancer are still unclear. Therefore, the purpose of this study was to investigate the role of a tumor-suppressive circRNA, circAAGAB, in breast cancer by assuming down-regulation of circAAGAB under hypoxia and the properties of a tumor suppressor. METHODS: Firstly, circAAGAB was identified from expression profiling by next generation sequencing. Next, the stability of circAAGAB increased by interacting with the RNA binding protein FUS. Moreover, cellular and nuclear fractionation showed that most circAAGAB resided in the cytoplasm and that it up-regulated KIAA1522, NKX3-1, and JADE3 by sponging miR-378 h. Lastly, the functions of circAAGAB were explored by identifying its down-stream genes using Affymetrix microarrays and validated by in vitro assays. RESULTS: The results showed that circAAGAB reduced cell colony formation, cell migration, and signaling through p38 MAPK pathway, as well as increased radiosensitivity. CONCLUSION: These findings suggest that the oxygen-responsive circAAGAB acts as a tumor suppressor in breast cancer, and may contribute to the development of a more specific therapeutic regimen for breast cancer.

FILER: a framework for harmonizing and querying large-scale functional genomics knowledge.

Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made difficult by the heterogeneity and breadth of data sources, experimental assays, biological conditions/tissues/cell types and file formats. FILER (FunctIonaL gEnomics Repository) is a framework for querying large-scale genomics knowledge with a large, curated integrated catalog of harmonized functional genomic and annotation data coupled with a scalable genomic search and querying interface. FILER uniquely provides: (i) streamlined access to >50 000 harmonized, annotated genomic datasets across >20 integrated data sources, >1100 tissues/cell types and >20 experimental assays; (ii) a scalable genomic querying interface; and (iii) ability to analyze and annotate user's experimental data. This rich resource spans >17 billion GRCh37/hg19 and GRCh38/hg38 genomic records. Our benchmark querying 7 × 109 hg19 FILER records shows FILER is highly scalable, with a sub-linear 32-fold increase in querying time when increasing the number of queries 1000-fold from 1000 to 1 000 000 intervals. Together, these features facilitate reproducible research and streamline integrating/querying large-scale genomic data within analyses/workflows. FILER can be deployed on cloud or local servers (https://bitbucket.org/wanglab-upenn/FILER) for integration with custom pipelines and is freely available (https://lisanwanglab.org/FILER).

MiDSystem: A comprehensive online system for de novo assembly and analysis of microbial genomes.

The substantial reduction in experimental cost of next-generation sequencing techniques makes it feasible to assemble a bacterial genome of unknown species de novo and acquire substantial genetic information from environmental samples. Many bioinformatics tools and algorithms have also been developed for prokaryotes, but complex parameter settings and command line-based user interfaces cause a significant entry barrier for novices. Efficient construction of pipelines that integrate all the available genomic data poses a major challenge to the understanding of unknown pathogens. MiDSystem is a comprehensive online system for analyzing genomic data from microbiomes. With a user-friendly interface, MiDSystem supports both de novo assembly and metagenomic analysis pipelines. It is designed to automatically analyze whole genome shotgun sequencing data of bacteria submitted by users. Multiple analytical steps can be performed directly on the system, and the results generated from the embedded tools are visualized in an online summary report to make it more interpretable. Constructing a genome de novo has gradually become the foundation of bacterial studies. Taking both single species and metagenomic samples into consideration, MiDSystem can greatly reduce the time and effort for analysis of bacterial genomic data. Use of MiDSystem will enable more focus to be placed on understanding the etiology of bacterial infections and microorganism ecologies.

Rare variants discovery by extensive whole-genome sequencing of the Han Chinese population in Taiwan: Applications to cardiovascular medicine.

Introduction: A population-specific genomic reference is important for research and clinical practice, yet it remains unavailable for Han Chinese (HC) in Taiwan. Objectives: We report the first whole genome sequencing (WGS) database of HC (1000 Taiwanese genome (1KTW-WGS)) and demonstrate several applications to cardiovascular medicine. Methods: Whole genomes of 997 HC were sequenced to at least 30X depth. A total of 20,117 relatively healthy HC individuals were genotyped using a customized Axiom GWAS array. We performed a genome-wide genotype imputation technique using IMPUTE2. Results: We identified 26.7 million single-nucleotide variants (SNVs) and 4.2 million insertions-deletions. Of the SNVs, 16.1% were novel relative to dbSNP (build 152), and 34.2% were novel relative to gnomAD. A total of 18,450 healthy HC individuals were genotyped using a customized Genome-Wide Association Study (GWAS) array. We identified hypertension-associated variants and developed a hypertension prediction model based on the correlation between the WGS data and GWAS data (combined clinical and genetic models, AUC 0.887), and also identified 3 novel hyperlipidemia-associated variants. Each individual carried an average of 16.42 (SD = 3.72) disease-causing variants. Additionally, we established an online SCN5A (an important cardiac gene) database that can be used to explore racial differences. Finally, pharmacogenetics studies identified HC population-specific SNVs in genes (CYP2C9 and VKORC1) involved in drug metabolism and blood clotting. Conclusion: This research demonstrates the benefits of constructing a population-specific genomic reference database for precision medicine.

Using INFERNO to Infer the Molecular Mechanisms Underlying Noncoding Genetic Associations.

The INFERNO method provides an integrative computational framework for characterizing the causal variants, tissue contexts, affected regulatory mechanisms, and target genes underlying noncoding genetic variants associated with any phenotype or disease of interest. Here we describe the computational steps required to run the full INFERNO pipeline on any dataset of interest.

RNASeqR: An R Package for Automated Two-Group RNA-Seq Analysis Workflow.

RNA-Seq analysis has revolutionized researchers' understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html).

SparkINFERNO: a scalable high-throughput pipeline for inferring molecular mechanisms of non-coding genetic variants.

SUMMARY: We report Spark-based INFERence of the molecular mechanisms of NOn-coding genetic variants (SparkINFERNO), a scalable bioinformatics pipeline characterizing non-coding genome-wide association study (GWAS) association findings. SparkINFERNO prioritizes causal variants underlying GWAS association signals and reports relevant regulatory elements, tissue contexts and plausible target genes they affect. To achieve this, the SparkINFERNO algorithm integrates GWAS summary statistics with large-scale collection of functional genomics datasets spanning enhancer activity, transcription factor binding, expression quantitative trait loci and other functional datasets across more than 400 tissues and cell types. Scalability is achieved by an underlying API implemented using Apache Spark and Giggle-based genomic indexing. We evaluated SparkINFERNO on large GWASs and show that SparkINFERNO is more than 60 times efficient and scales with data size and amount of computational resources. AVAILABILITY AND IMPLEMENTATION: SparkINFERNO runs on clusters or a single server with Apache Spark environment, and is available at https://bitbucket.org/wanglab-upenn/SparkINFERNO or https://hub.docker.com/r/wanglab/spark-inferno. CONTACT: lswang@pennmedicine.upenn.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

VariED: the first integrated database of gene annotation and expression profiles for variants related to human diseases.

Integrated analysis of DNA variants and gene expression profiles may facilitate precise identification of gene regulatory networks involved in disease mechanisms. Despite the widespread availability of public resources, we lack databases that are capable of simultaneously providing gene expression profiles, variant annotations, functional prediction scores and pathogenic analyses. VariED is the first web-based querying system that integrates an annotation database and expression profiles for genetic variants. The database offers a user-friendly platform and locates gene/variant names in the literature by connecting to established online querying tools, biological annotation tools and records from free-text literature. VariED acts as a central hub for organized genome information consisting of gene annotation, variant allele frequency, functional prediction, clinical interpretation and gene expression profiles in three species: human, mouse and zebrafish. VariED also provides a novel scoring scheme to predict the functional impact of a DNA variant. With one single entry, all results regarding queried DNA variants can be downloaded. VariED can potentially serve as an efficient way to obtain comprehensive variant knowledge for clinicians and scientists around the world working on important drug discoveries and precision treatments.

anamiR: integrated analysis of MicroRNA and gene expression profiling.

BACKGROUND: With advancements in high-throughput technologies, the cost of obtaining expression profiles of both mRNA and microRNA in the same individual has substantially decreased. Integrated analysis of these profiles can help to elucidate the functional effects of RNA expression in complex diseases, such as cancer. However, fundamental discrepancies are observed in the results from microRNA-mRNA target gene prediction algorithms, and few packages can be used to analyze microRNA and mRNA expression levels simultaneously. RESULTS: To address these issues, an R package, anamiR, was developed. A total of 10 experimental/prediction databases were integrated. Two analytical functions are provided in anamiR, including the single marker test and functional gene set enrichment analysis, and several parameters can be changed by users. Here we demonstrate the potential application of the anamiR package to 2 publicly available microarray datasets. CONCLUSION: The anamiR package is effective for an integrated analysis of both RNA and microRNA profiles. By characterizing biological functions and signaling pathways, this package helps identify dysregulated genes/miRNAs from biological and medical experiments. The source code and manual of the anamiR package are freely available at https://bioconductor.org/packages/release/bioc/html/anamiR.html .

Whole-genome de novo sequencing reveals unique genes that contributed to the adaptive evolution of the Mikado pheasant.

Background: The Mikado pheasant (Syrmaticus mikado) is a nearly endangered species indigenous to high-altitude regions of Taiwan. This pheasant provides an opportunity to investigate evolutionary processes following geographic isolation. Currently, the genetic background and adaptive evolution of the Mikado pheasant remain unclear. Results: We present the draft genome of the Mikado pheasant, which consists of 1.04 Gb of DNA and 15,972 annotated protein-coding genes. The Mikado pheasant displays expansion and positive selection of genes related to features that contribute to its adaptive evolution, such as energy metabolism, oxygen transport, hemoglobin binding, radiation response, immune response, and DNA repair. To investigate the molecular evolution of the major histocompatibility complex (MHC) across several avian species, 39 putative genes spanning 227 kb on a contiguous region were annotated and manually curated. The MHC loci of the pheasant revealed a high level of synteny, several rapidly evolving genes, and inverse regions compared to the same loci in the chicken. The complete mitochondrial genome was also sequenced, assembled, and compared against four long-tailed pheasants. The results from molecular clock analysis suggest that ancestors of the Mikado pheasant migrated from the north to Taiwan about 3.47 million years ago. Conclusions: This study provides a valuable genomic resource for the Mikado pheasant, insights into its adaptation to high altitude, and the evolutionary history of the genus Syrmaticus, which could potentially be useful for future studies that investigate molecular evolution, genomics, ecology, and immunogenetics.

CellExpress: a comprehensive microarray-based cancer cell line and clinical sample gene expression analysis online system.

Database URL: http://cellexpress.cgm.ntu.edu.tw/.

Genome of the Asian longhorned beetle (Anoplophora glabripennis), a globally significant invasive species, reveals key functional and evolutionary innovations at the beetle-plant interface.

BACKGROUND: Relatively little is known about the genomic basis and evolution of wood-feeding in beetles. We undertook genome sequencing and annotation, gene expression assays, studies of plant cell wall degrading enzymes, and other functional and comparative studies of the Asian longhorned beetle, Anoplophora glabripennis, a globally significant invasive species capable of inflicting severe feeding damage on many important tree species. Complementary studies of genes encoding enzymes involved in digestion of woody plant tissues or detoxification of plant allelochemicals were undertaken with the genomes of 14 additional insects, including the newly sequenced emerald ash borer and bull-headed dung beetle. RESULTS: The Asian longhorned beetle genome encodes a uniquely diverse arsenal of enzymes that can degrade the main polysaccharide networks in plant cell walls, detoxify plant allelochemicals, and otherwise facilitate feeding on woody plants. It has the metabolic plasticity needed to feed on diverse plant species, contributing to its highly invasive nature. Large expansions of chemosensory genes involved in the reception of pheromones and plant kairomones are consistent with the complexity of chemical cues it uses to find host plants and mates. CONCLUSIONS: Amplification and functional divergence of genes associated with specialized feeding on plants, including genes originally obtained via horizontal gene transfer from fungi and bacteria, contributed to the addition, expansion, and enhancement of the metabolic repertoire of the Asian longhorned beetle, certain other phytophagous beetles, and to a lesser degree, other phytophagous insects. Our results thus begin to establish a genomic basis for the evolutionary success of beetles on plants.

Unique features of a global human ectoparasite identified through sequencing of the bed bug genome.

The bed bug, Cimex lectularius, has re-established itself as a ubiquitous human ectoparasite throughout much of the world during the past two decades. This global resurgence is likely linked to increased international travel and commerce in addition to widespread insecticide resistance. Analyses of the C. lectularius sequenced genome (650 Mb) and 14,220 predicted protein-coding genes provide a comprehensive representation of genes that are linked to traumatic insemination, a reduced chemosensory repertoire of genes related to obligate hematophagy, host-symbiont interactions, and several mechanisms of insecticide resistance. In addition, we document the presence of multiple putative lateral gene transfer events. Genome sequencing and annotation establish a solid foundation for future research on mechanisms of insecticide resistance, human-bed bug and symbiont-bed bug associations, and unique features of bed bug biology that contribute to the unprecedented success of C. lectularius as a human ectoparasite.

Deregulated microRNAs in triple-negative breast cancer revealed by deep sequencing.

BACKGROUND: MicroRNAs (miRNAs) are short, non-coding RNA molecules that play critical roles in human malignancy. However, the regulatory characteristics of miRNAs in triple-negative breast cancer, a phenotype of breast cancer that does not express the genes for estrogen receptor, progesterone receptor, and human epidermal growth factor receptor 2, are still poorly understood. METHODS: In this study, miRNA expression profiles of 24 triple-negative breast cancers and 14 adjacent normal tissues were analyzed using deep sequencing technology. Expression levels of miRNA reads were normalized with the quantile-quantile scaling method. Deregulated miRNAs in triple-negative breast cancer were identified from the sequencing data using the Student's t-test. Quantitative reverse transcription PCR validations were carried out to examine miRNA expression levels. Potential target candidates of a miRNA were predicted using published target prediction algorithms. Luciferase reporter assay experiments were performed to verify a putative miRNA-target relationship. Validated molecular targets of the deregulated miRNAs were retrieved from curated databases and their associations with cancer progression were discussed. RESULTS: A novel 25-miRNA expression signature was found to effectively distinguish triple-negative breast cancers from surrounding normal tissues in a hierarchical clustering analysis. We documented the evidence of seven polycistronic miRNA clusters preferentially harboring deregulated miRNAs in triple-negative breast cancer. Two of these miRNA clusters (miR-143-145 at 5q32 and miR-497-195 at 17p13.1) were markedly down-regulated in triple-negative breast cancer, while the other five miRNA clusters (miR-17-92 at 13q31.3, miR-183-182 at 7q32.2, miR-200-429 at 1p36.33, miR-301b-130b at 22q11.21, and miR-532-502 at Xp11.23) were up-regulated in triple-negative breast cancer. Moreover, miR-130b-5p from the miR-301b-130b cluster was shown to directly repress the cyclin G2 (CCNG2) gene, a crucial cell cycle regulator, in triple-negative breast cancer cells. Luciferase reporter assays showed that miR-130b-5p-mediated repression of CCNG2 was dependent on the sequence of the 3'-untranslated region. The findings described in this study implicate a miR-130b-5p-CCNG2 axis that may be involved in the malignant progression of triple-negative breast cancer. CONCLUSIONS: Our work delivers a clear picture of the global miRNA regulatory characteristics in triple-negative breast cancer and extends the current knowledge of microRNA regulatory network.

The i5k Workspace@NAL--enabling genomic data access, visualization and curation of arthropod genomes.

The 5000 arthropod genomes initiative (i5k) has tasked itself with coordinating the sequencing of 5000 insect or related arthropod genomes. The resulting influx of data, mostly from small research groups or communities with little bioinformatics experience, will require visualization, dissemination and curation, preferably from a centralized platform. The National Agricultural Library (NAL) has implemented the i5k Workspace@NAL (http://i5k.nal.usda.gov/) to help meet the i5k initiative's genome hosting needs. Any i5k member is encouraged to contact the i5k Workspace with their genome project details. Once submitted, new content will be accessible via organism pages, genome browsers and BLAST search engines, which are implemented via the open-source Tripal framework, a web interface for the underlying Chado database schema. We also implement the Web Apollo software for groups that choose to curate gene models. New content will add to the existing body of 35 arthropod species, which include species relevant for many aspects of arthropod genomic research, including agriculture, invasion biology, systematics, ecology and evolution, and developmental research.

DNMT3L promotes quiescence in postnatal spermatogonial progenitor cells.

The ability of adult stem cells to reside in a quiescent state is crucial for preventing premature exhaustion of the stem cell pool. However, the intrinsic epigenetic factors that regulate spermatogonial stem cell quiescence are largely unknown. Here, we investigate in mice how DNA methyltransferase 3-like (DNMT3L), an epigenetic regulator important for interpreting chromatin context and facilitating de novo DNA methylation, sustains the long-term male germ cell pool. We demonstrated that stem cell-enriched THY1(+) spermatogonial stem/progenitor cells (SPCs) constituted a DNMT3L-expressing population in postnatal testes. DNMT3L influenced the stability of promyelocytic leukemia zinc finger (PLZF), potentially by downregulating Cdk2/CDK2 expression, which sequestered CDK2-mediated PLZF degradation. Reduced PLZF in Dnmt3l KO THY1(+) cells released its antagonist, Sal-like protein 4A (SALL4A), which is associated with overactivated ERK and AKT signaling cascades. Furthermore, DNMT3L was required to suppress the cell proliferation-promoting factor SALL4B in THY1(+) SPCs and to prevent premature stem cell exhaustion. Our results indicate that DNMT3L is required to delicately balance the cycling and quiescence of SPCs. These findings reveal a novel role for DNMT3L in modulating postnatal SPC cell fate decisions.