StemMapper: a curated gene expression database for stem cell lineage analysis

Cancer Stemness Online: A Resource for Investigating Cancer Stemness and Associations with Immune Response

Cancer progression involves the gradual loss of a differentiated phenotype and the acquisition of progenitor and stem cell-like features, which are potential culprits of immunotherapy resistance. Although the state-of-the-art predictive computational methods have facilitated the prediction of cancer stemness, there remains a lack of efficient resources to accommodate various usage requirements. Here, we present the Cancer Stemness Online, an integrated resource for efficiently scoring cancer stemness potential at both bulk and single-cell levels. This resource integrates eight robust predictive algorithms as well as 27 signature gene sets associated with cancer stemness for predicting stemness scores. Downstream analyses were performed from five distinct aspects: identifying the signature genes of cancer stemness; exploring the associations with cancer hallmarks and cellular states; exploring the associations with immune response and the communications with immune cells; investigating the contributions to patient survival; and performing a robustness analysis of cancer stemness among different methods. Moreover, the pre-calculated cancer stemness atlas for more than 40 cancer types can be accessed by users. Both the tables and diverse visualizations of the analytical results are available for download. Together, Cancer Stemness Online is a powerful resource for scoring cancer stemness and expanding downstream functional interpretation, including immune response and cancer hallmarks. Cancer Stemness Online is freely accessible at http://bio-bigdata.hrbmu.edu.cn/CancerStemnessOnline.

Initial Characterization of WDR5B Reveals a Role in the Proliferation of Retinal Pigment Epithelial Cells

The chromatin-associated protein WDR5 has been widely studied due to its role in histone modification and its potential as a pharmacological target for the treatment of cancer. In humans, the protein with highest sequence homology to WDR5 is encoded by the retrogene WDR5B, which remains unexplored. Here, we used CRISPR-Cas9 genome editing to generate WDR5B knockout and WDR5B-FLAG knock-in cell lines for further characterization. In contrast to WDR5, WDR5B exhibits low expression in pluripotent cells and is upregulated upon neural differentiation. Loss or shRNA depletion of WDR5B impairs cell growth and increases the fraction of non-viable cells in proliferating retinal pigment epithelial (RPE) cultures. CUT&RUN chromatin profiling in RPE and neural progenitors indicates minimal WDR5B enrichment at established WDR5 binding sites. These results suggest that WDR5 and WDR5B exhibit several divergent biological properties despite sharing a high degree of sequence homology.

Transcriptomic landscape of posterior regeneration in the annelid Platynereis dumerilii

BACKGROUND

Restorative regeneration, the capacity to reform a lost body part following amputation or injury, is an important and still poorly understood process in animals. Annelids, or segmented worms, show amazing regenerative capabilities, and as such are a crucial group to investigate. Elucidating the molecular mechanisms that underpin regeneration in this major group remains a key goal. Among annelids, the nereididae Platynereis dumerilii (re)emerged recently as a front-line regeneration model. Following amputation of its posterior part, Platynereis worms can regenerate both differentiated tissues of their terminal part as well as a growth zone that contains putative stem cells. While this regeneration process follows specific and reproducible stages that have been well characterized, the transcriptomic landscape of these stages remains to be uncovered.

RESULTS

We generated a high-quality de novo Reference transcriptome for the annelid Platynereis dumerilii. We produced and analyzed three RNA-sequencing datasets, encompassing five stages of posterior regeneration, along with blastema stages and non-amputated tissues as controls. We included two of these regeneration RNA-seq datasets, as well as embryonic and tissue-specific datasets from the literature to produce a Reference transcriptome. We used this Reference transcriptome to perform in depth analyzes of RNA-seq data during the course of regeneration to reveal the important dynamics of the gene expression, process with thousands of genes differentially expressed between stages, as well as unique and specific gene expression at each regeneration stage. The study of these genes highlighted the importance of the nervous system at both early and late stages of regeneration, as well as the enrichment of RNA-binding proteins (RBPs) during almost the entire regeneration process.

CONCLUSIONS

In this study, we provided a high-quality de novo Reference transcriptome for the annelid Platynereis that is useful for investigating various developmental processes, including regeneration. Our extensive stage-specific transcriptional analysis during the course of posterior regeneration sheds light upon major molecular mechanisms and pathways, and will foster many specific studies in the future.

Integration of Stemness Gene Signatures Reveals Core Functional Modules of Stem Cells and Potential Novel Stemness Genes

Stem cells encompass a variety of different cell types which converge on the dual capacity to self-renew and differentiate into one or more lineages. These characteristic features are key for the involvement of stem cells in crucial biological processes such as development and ageing. To decipher their underlying genetic substrate, it is important to identify so-called stemness genes that are common to different stem cell types and are consistently identified across different studies. In this meta-analysis, 21 individual stemness signatures for humans and another 21 for mice, obtained from a variety of stem cell types and experimental techniques, were compared. Although we observed biological and experimental variability, a highly significant overlap between gene signatures was identified. This enabled us to define integrated stemness signatures (ISSs) comprised of genes frequently occurring among individual stemness signatures. Such integrated signatures help to exclude false positives that can compromise individual studies and can provide a more robust basis for investigation. To gain further insights into the relevance of ISSs, their genes were functionally annotated and connected within a molecular interaction network. Most importantly, the present analysis points to the potential roles of several less well-studied genes in stemness and thus provides promising candidates for further experimental validation.

The Transient Human Thyroid Progenitor Cell: Examining the Thyroid Continuum from Stem Cell to Follicular Cell

Background: The development of the thyroid follicular cell has been well characterized as it progresses from the original stem cell, either embryonic or adult, through a series of transitions to form a differentiated and functional thyroid cell. Summary: In this review, we briefly outline what is known about this transitional process with emphasis on characterizing the thyroid progenitor stem cell by using data obtained from both in vitro and in vivo studies and both mouse and human cells. It is of particular importance to note the influence of independent factors that guide the transcriptional control of the developing thyroid cell as it is subjected to extracellular signals, often working via epigenetic changes, and initiating intrinsic transcriptional changes leading to a functional cell. Conclusion: Thyroid stem cells fall into the category of dispositional stem cells and are greatly influenced by their environment.

SISTEMA: A large and standardized collection of transcriptome data sets for human pluripotent stem cell research

Human pluripotent stem cells have ushered in an exciting new era for disease modeling, drug discovery, and cell therapy development. Continued progress toward realizing the potential of human pluripotent stem cells will be facilitated by robust data sets and complementary resources that are easily accessed and interrogated by the stem cell community. In this context, we present SISTEMA, a quality-controlled curated gene expression database, built on a valuable catalog of human pluripotent stem cell lines, and their derivatives for which transcriptomic analyses have been generated using a single experimental pipeline. SISTEMA functions as a one-step resource that will assist the stem cell community to easily evaluate the expression level for genes of interest, while comparing them across different hPSC lines, cell types, pathological conditions, or after pharmacological treatments.

ACSA-2 and GLAST classify subpopulations of multipotent and glial-restricted cerebellar precursors

The formation of the cerebellum is highly coordinated to obtain its characteristic morphology and all cerebellar cell types. During mouse postnatal development, cerebellar progenitors with astroglial‐like characteristics generate mainly astrocytes and oligodendrocytes. However, a subset of astroglial‐like progenitors found in the prospective white matter (PWM) produces astroglia and interneurons. Characterizing these cerebellar astroglia‐like progenitors and distinguishing their developmental fates is still elusive. Here, we reveal that astrocyte cell surface antigen‐2 (ACSA‐2), lately identified as ATPase, Na+/K+ transporting, beta 2 polypeptide, is expressed by glial precursors throughout postnatal cerebellar development. In contrast to common astrocyte markers, ACSA‐2 appears on PWM cells but is absent on Bergmann glia (BG) precursors. In the adult cerebellum, ACSA‐2 is broadly expressed extending to velate astrocytes in the granular layer, white matter astrocytes, and to a lesser extent to BG. Cell transplantation and transcriptomic analysis revealed that marker staining discriminates two postnatal progenitor pools. One subset is defined by the co‐expression of ACSA‐2 and GLAST and the expression of markers typical of parenchymal astrocytes. These are PWM precursors that are exclusively gliogenic. They produce predominantly white matter and granular layer astrocytes. Another subset is constituted by GLAST positive/ACSA‐2 negative precursors that express neurogenic and BG‐like progenitor genes. This population displays multipotency and gives rise to interneurons besides all glial types, including BG. In conclusion, this work reports about ACSA‐2, a marker that in combination with GLAST enables for the discrimination and isolation of multipotent and glia‐committed progenitors, which generate different types of cerebellar astrocytes.

Enhanced differentiation of human induced pluripotent stem cells toward the midbrain dopaminergic neuron lineage through GLYPICAN-4 downregulation

Enhancing the differentiation potential of human induced pluripotent stem cells (hiPSC) into disease‐relevant cell types is instrumental for their widespread application in medicine. Here, we show that hiPSCs downregulated for the signaling modulator GLYPICAN‐4 (GPC4) acquire a new biological state characterized by increased hiPSC differentiation capabilities toward ventral midbrain dopaminergic (VMDA) neuron progenitors. This biological trait emerges both in vitro, upon exposing cells to VMDA neuronal differentiation signals, and in vivo, even when transplanting hiPSCs at the extreme conditions of floor‐plate stage in rat brains. Moreover, it is compatible with the overall neuronal maturation process toward acquisition of substantia nigra neuron identity. HiPSCs with downregulated GPC4 also retain self‐renewal and pluripotency in stemness conditions, in vitro, while losing tumorigenesis in vivo as assessed by flank xenografts. In conclusion, our results highlight GPC4 downregulation as a powerful approach to enhance generation of VMDA neurons. Outcomes may contribute to establish hiPSC lines suitable for translational applications.

CancerLivER: a database of liver cancer gene expression resources and biomarkers

Liver cancer is the fourth major lethal malignancy worldwide. To understand the development and progression of liver cancer, biomedical research generated a tremendous amount of transcriptomics and disease-specific biomarker data. However, dispersed information poses pragmatic hurdles to delineate the significant markers for the disease. Hence, a dedicated resource for liver cancer is required that integrates scattered multiple formatted datasets and information regarding disease-specific biomarkers. Liver Cancer Expression Resource (CancerLivER) is a database that maintains gene expression datasets of liver cancer along with the putative biomarkers defined for the same in the literature. It manages 115 datasets that include gene-expression profiles of 9611 samples. Each of incorporated datasets was manually curated to remove any artefact; subsequently, a standard and uniform pipeline according to the specific technique is employed for their processing. Additionally, it contains comprehensive information on 594 liver cancer biomarkers which include mainly 315 gene biomarkers or signatures and 178 protein- and 46 miRNA-based biomarkers. To explore the full potential of data on liver cancer, a web-based interactive platform was developed to perform search, browsing and analyses. Analysis tools were also integrated to explore and visualize the expression patterns of desired genes among different types of samples based on individual gene, GO ontology and pathways. Furthermore, a dataset matrix download facility was provided to facilitate the users for their extensive analysis to elucidate more robust disease-specific signatures. Eventually, CancerLivER is a comprehensive resource which is highly useful for the scientific community working in the field of liver cancer.Availability: CancerLivER can be accessed on the web at https://webs.iiitd.edu.in/raghava/cancerliver.

Organelle Cooperation in Stem Cell Fate: Lysosomes as Emerging Regulators of Cell Identity

Regulation of stem cell fate is best understood at the level of gene and protein regulatory networks, though it is now clear that multiple cellular organelles also have critical impacts. A growing appreciation for the functional interconnectedness of organelles suggests that an orchestration of integrated biological networks functions to drive stem cell fate decisions and regulate metabolism. Metabolic signaling itself has emerged as an integral regulator of cell fate including the determination of identity, activation state, survival, and differentiation potential of many developmental, adult, disease, and cancer-associated stem cell populations and their progeny. As the primary adenosine triphosphate-generating organelles, mitochondria are well-known regulators of stem cell fate decisions, yet it is now becoming apparent that additional organelles such as the lysosome are important players in mediating these dynamic decisions. In this review, we will focus on the emerging role of organelles, in particular lysosomes, in the reprogramming of both metabolic networks and stem cell fate decisions, especially those that impact the determination of cell identity. We will discuss the inter-organelle interactions, cell signaling pathways, and transcriptional regulatory mechanisms with which lysosomes engage and how these activities impact metabolic signaling. We will further review recent data that position lysosomes as critical regulators of cell identity determination programs and discuss the known or putative biological mechanisms. Finally, we will briefly highlight the potential impact of elucidating mechanisms by which lysosomes regulate stem cell identity on our understanding of disease pathogenesis, as well as the development of refined regenerative medicine, biomarker, and therapeutic strategies.

Cell stemness is maintained upon concurrent expression of RB and the mitochondrial ribosomal protein S18-2

Stemness encompasses the capability of a cell for self-renewal and differentiation. The stem cell maintains a balance between proliferation, quiescence, and regeneration via interactions with the microenvironment. Previously, we showed that ectopic expression of the mitochondrial ribosomal protein S18-2 (MRPS18-2) led to immortalization of primary fibroblasts, accompanied by induction of an embryonic stem cell (ESC) phenotype. Moreover, we demonstrated interaction between S18-2 and the retinoblastoma-associated protein (RB) and hypothesized that the simultaneous expression of RB and S18-2 is essential for maintaining cell stemness. Here, we experimentally investigated the role of S18-2 in cell stemness and differentiation. Concurrent expression of RB and S18-2 resulted in immortalization of Rb1 ^-/- primary mouse embryonic fibroblasts and in aggressive tumor growth in severe combined immunodeficiency mice. These cells, which express both RB and S18-2 at high levels, exhibited the potential to differentiate into various lineages in vitro, including osteogenic, chondrogenic, and adipogenic lineages. Mechanistically, S18-2 formed a multimeric protein complex with prohibitin and the ring finger protein 2 (RNF2). This molecular complex increased the monoubiquitination of histone H2A^Lys119, a characteristic trait of ESCs, by enhanced E3-ligase activity of RNF2. Furthermore, we found enrichment of KLF4 at the S18-2 promoter region and that the S18-2 expression is positively correlated with KLF4 levels. Importantly, knockdown of S18-2 in zebrafish larvae led to embryonic lethality. Collectively, our findings suggest an important role for S18-2 in cell stemness and differentiation and potentially also in cancerogenesis.

Essential Gene Profiles for Human Pluripotent Stem Cells Identify Uncharacterized Genes and Substrate Dependencies

Human pluripotent stem cells (hPSCs) provide an invaluable tool for modeling diseases and hold promise for regenerative medicine. For understanding pluripotency and lineage differentiation mechanisms, a critical first step involves systematically cataloging essential genes (EGs) that are indispensable for hPSC fitness, defined as cell reproduction in this study. To map essential genetic determinants of hPSC fitness, we performed genome-scale loss-of-function screens in an inducible Cas9 H1 hPSC line cultured on feeder cells and laminin to identify EGs. Among these, we found FOXH1 and VENTX, genes that encode transcription factors previously implicated in stem cell biology, as well as an uncharacterized gene, C22orf43/DRICH1. hPSC EGs are substantially different from other human model cell lines, and EGs in hPSCs are highly context dependent with respect to different growth substrates. Our CRISPR screens establish parameters for genome-wide screens in hPSCs, which will facilitate the characterization of unappreciated genetic regulators of hPSC biology.

Lentiviral mediated RPE65 gene transfer in healthy hiPSCs-derived retinal pigment epithelial cells markedly increased RPE65 mRNA, but modestly protein level

The retinal pigment epithelium (RPE) is a monolayer of cobblestone-like epithelial cells that accomplishes critical functions for the retina. Several protocols have been published to differentiate pluripotent stem cells into RPE cells suitable for disease modelling and therapy development. In our study, the RPE identity of human induced pluripotent stem cell (hiPSC)-derived RPE (iRPE) was extensively characterized, and then used to test a lentiviral-mediated RPE65 gene augmentation therapy. A dose study of the lentiviral vector revealed a dose-dependent effect of the vector on RPE65 mRNA levels. A marked increase of the RPE65 mRNA was also observed in the iRPE (100-fold) as well as in an experimental set with RPE derived from another hiPSC source and from foetal human RPE. Although iRPE displayed features close to bona fide RPE, no or a modest increase of the RPE65 protein level was observed depending on the protein detection method. Similar results were observed with the two other cell lines. The mechanism of RPE65 protein regulation remains to be elucidated, but the current work suggests that high vector expression will not produce an excess of the normal RPE65 protein level.

CancerSEA: a cancer single-cell state atlas

High functional heterogeneity of cancer cells poses a major challenge for cancer research. Single-cell sequencing technology provides an unprecedented opportunity to decipher diverse functional states of cancer cells at single-cell resolution, and cancer scRNA-seq datasets have been largely accumulated. This emphasizes the urgent need to build a dedicated resource to decode the functional states of cancer single cells. Here, we developed CancerSEA (http://biocc.hrbmu.edu.cn/CancerSEA/ or http://202.97.205.69/CancerSEA/), the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level. CancerSEA portrays a cancer single-cell functional state atlas, involving 14 functional states (including stemness, invasion, metastasis, proliferation, EMT, angiogenesis, apoptosis, cell cycle, differentiation, DNA damage, DNA repair, hypoxia, inflammation and quiescence) of 41 900 cancer single cells from 25 cancer types. It allows querying which functional states are associated with the gene (or gene list) of interest in different cancers. CancerSEA also provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single-cell datasets. In summary, CancerSEA provides a user-friendly interface for comprehensively searching, browsing, visualizing and downloading functional state activity profiles of tens of thousands of cancer single cells and the corresponding PCGs/lncRNAs expression profiles.

Stemformatics: visualize and download curated stem cell data

Stemformatics is an established gene expression data portal containing over 420 public gene expression datasets derived from microarray, RNA sequencing and single cell profiling technologies. Developed for the stem cell community, it has a major focus on pluripotency, tissue stem cells, and staged differentiation. Stemformatics includes curated ‘collections’ of data relevant to cell reprogramming, as well as hematopoiesis and leukaemia. Rather than simply rehosting datasets as they appear in public repositories, Stemformatics uses a stringent set of quality control metrics and its own pipelines to process handpicked datasets from raw files. This means that about 30% of datasets processed by Stemformatics fail the quality control metrics and never make it to the portal, ensuring that Stemformatics data are of high quality and have been processed in a consistent manner. Stemformatics provides easy-to-use and intuitive tools for biologists to visually explore the data, including interactive gene expression profiles, principal component analysis plots and hierarchical clusters, among others. The addition of tools that facilitate cross-dataset comparisons provides users with snapshots of gene expression in multiple cell and tissues, assisting the identification of cell-type restricted genes, or potential housekeeping genes. Stemformatics is freely available at stemformatics.org.

Informatics Approaches for Harmonized Intelligent Integration of Stem Cell Research

As biomedical data integration and analytics play an increasing role in the field of stem cell research, it becomes important to develop ways to standardize, aggregate, and share data among researchers. For this reason, many databases have been developed in recent years in an attempt to systematically warehouse data from different stem cell projects and experiments at the same time. However, these databases vary widely in their implementation and structure. The aim of this scoping review is to characterize the main features of available stem cell databases in order to identify specifications useful for implementation in future stem cell databases. We conducted a scoping review of peer-reviewed literature and online resources to identify and review available stem cell databases. To identify the relevant databases, we performed a PubMed search using relevant MeSH terms followed by a web search for databases which may not have an associated journal article. In total, we identified 16 databases to include in this review. The data elements reported in these databases represented a broad spectrum of parameters from basic socio-demographic variables to various cells characteristics, cell surface markers expression, and clinical trial results. Three broad sets of functional features that provide utility for future stem cell research and facilitate bioinformatics workflows were identified. These features consisted of the following: common data elements, data visualization and analysis tools, and biomedical ontologies for data integration. Stem cell bioinformatics is a quickly evolving field that generates a growing number of heterogeneous data sets. Further progress in the stem cell research may be greatly facilitated by development of applications for intelligent stem cell data aggregation, sharing and collaboration process.

PSCRIdb: A database of regulatory interactions and networks of pluripotent stem cell lines

Pluripotency in stem cells is regulated by a complex network between the transcription factors, signaling molecules, mRNAs, and epigenetic regulators like non-coding RNAs. Different pluripotent stem cell (PSC) lines were isolated and characterized to study the regulatory network topology to understand the mechanism that control developmental potential of pluripotent cells. PSCRIdb is a manually curated database of regulatory interactions including protein-protein, protein-DNA, gene-gene, and miRNA-mRNA interactions in mouse and human pluripotent stem cells including embryonic stem cells and embryonic carcinoma cells. At present, 22 different mouse and human pluripotent stem-cell-line-specific regulatory interactions are compiled in the database. Detailed information of the four types of interaction data are presented in tabular format and graphical network view in Cytoscape layout. The database is available at http://bicresources.jcbose.ac.in/ ssaha4/pscridb. The database contains 3037 entries of experimentally validated molecular interactions that can be useful for systematic study of pluripotency integrating multi-omics data. In summary, the database can be a useful resource for identification of regulatory networks present in different pluripotent stem cell lines.

The Tumor Suppressor Role of Zinc Finger Protein 671 (ZNF671) in Multiple Tumors Based on Cancer Single-Cell Sequencing

In humans, zinc finger protein 671 (ZNF671) is a type of transcription factor. However, the contribution of tumor heterogeneity to the functional role of ZNF671 remains unknown. The present study aimed to determine the functional states of ZNF671 in cancer single cells based on single-cell sequencing datasets (scRNA-seq). We collected cancer-related ZNF671 scRNA-seq datasets and analyzed ZNF671 in the datasets. We evaluated 14 functional states of ZNF671 in cancers and performed ZNF671 expression and function state correlation analysis. We further applied t-distributed stochastic neighbor embedding to describe the distribution of cancer cells and to explore the functional state of ZNF671 in cancer subgroups. We found that ZNF671 was downregulated in eight cancer-related ZNF671 scRNA-seq datasets. Functional analysis identified that ZNF671 might play a tumor suppressor role in cancer. The heterogeneous functional states of cell subgroups and correlation analysis showed that ZNF671 played tumor suppressor roles in heterogeneous cancer cell populations. Western blot and transwell assays identified that ZNF671 inhibited EMT, migration, and invasion of CNS cancers, lung cancer, melanoma, and breast carcinoma in vitro. These results from cancer single-cell sequencing indicated that ZNF671 played a tumor suppressor role in multiple tumors and may provide us with new insights into the role of ZNF671 for cancer treatment.

Exogenous WNT5A and WNT11 proteins rescue CITED2 dysfunction in mouse embryonic stem cells and zebrafish morphants

Mutations and inadequate methylation profiles of CITED2 are associated with human congenital heart disease (CHD). In mouse, Cited2 is necessary for embryogenesis, particularly for heart development, and its depletion in embryonic stem cells (ESC) impairs cardiac differentiation. We have now determined that Cited2 depletion in ESC affects the expression of transcription factors and cardiopoietic genes involved in early mesoderm and cardiac specification. Interestingly, the supplementation of the secretome prepared from ESC overexpressing CITED2, during the onset of differentiation, rescued the cardiogenic defects of Cited2-depleted ESC. In addition, we demonstrate that the proteins WNT5A and WNT11 held the potential for rescue. We also validated the zebrafish as a model to investigate cited2 function during development. Indeed, the microinjection of morpholinos targeting cited2 transcripts caused developmental defects recapitulating those of mice knockout models, including the increased propensity for cardiac defects and severe death rate. Importantly, the co-injection of anti-cited2 morpholinos with either CITED2 or WNT5A and WNT11 recombinant proteins corrected the developmental defects of Cited2-morphants. This study argues that defects caused by the dysfunction of Cited2 at early stages of development, including heart anomalies, may be remediable by supplementation of exogenous molecules, offering the opportunity to develop novel therapeutic strategies aiming to prevent CHD.

The 2018 Nucleic Acids Research database issue and the online molecular biology database collection

The 2018 Nucleic Acids Research Database Issue contains 181 papers spanning molecular biology. Among them, 82 are new and 84 are updates describing resources that appeared in the Issue previously. The remaining 15 cover databases most recently published elsewhere. Databases in the area of nucleic acids include 3DIV for visualisation of data on genome 3D structure and RNArchitecture, a hierarchical classification of RNA families. Protein databases include the established SMART, ELM and MEROPS while GPCRdb and the newcomer STCRDab cover families of biomedical interest. In the area of metabolism, HMDB and Reactome both report new features while PULDB appears in NAR for the first time. This issue also contains reports on genomics resources including Ensembl, the UCSC Genome Browser and ENCODE. Update papers from the IUPHAR/BPS Guide to Pharmacology and DrugBank are highlights of the drug and drug target section while a number of proteomics databases including proteomicsDB are also covered. The entire Database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, reviewing 138 entries, adding 88 new resources and eliminating 47 discontinued URLs, bringing the current total to 1737 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.