During protein synthesis, translating ribosomes encounter many challenges imposed by various types of defective mRNAs that can lead to reduced cellular fitness and, in some cases, even threaten cell viability. Aberrant translation leads to activation of one of several quality control pathways depending on the nature of the problem. These pathways promote the degradation of the problematic mRNA as well as the incomplete translation product, the nascent polypeptide chain. Many of these quality control systems feature critical roles for specialized regulatory factors that work in concert with conventional factors. This review focuses on the mechanisms used by these quality control pathways to recognize aberrant ribosome stalling and discusses the conservation of these systems.

Recruitment of the human ribonucleolytic RNA exosome to nuclear polyadenylated (pA+) RNA is facilitated by the Poly(A) Tail eXosome Targeting (PAXT) connection. Besides its core dimer, formed by the exosome co-factor MTR4 and the ZFC3H1 protein, the PAXT connection remains poorly defined. By characterizing nuclear pA+-RNA bound proteomes as well as MTR4-ZFC3H1 containing complexes in conditions favoring PAXT assembly, we here uncover three additional proteins required for PAXT function: ZC3H3, RBM26 and RBM27 along with the known PAXT-associated protein, PABPN1. The zinc-finger protein ZC3H3 interacts directly with MTR4-ZFC3H1 and loss of any of the newly identified PAXT components results in the accumulation of PAXT substrates. Collectively, our results establish new factors involved in the turnover of nuclear pA+ RNA and suggest that these are limiting for PAXT activity.

I-motif DNAs have been widely employed as robust modulating components to construct reconfigurable DNA nanodevices that function well in acidic cellular environments. However, they generally display poor interactivity with fluorescent ligands under these complex conditions, illustrating a major difficulty in utilizing i-motifs as the light-up system for label-free DNA nanoassemblies and bioimaging. Towards addressing this challenge, here we devise new types of i-motif/miniduplex hybrid structures that display an unprecedentedly high interactivity with commonly-used benzothiazole dyes (e.g. thioflavin T). A well-chosen tetranucleotide, whose optimal sequence depends on the used ligand, is appended to the 5′-terminals of diverse i-motifs and forms a minimal parallel duplex thereby creating a preferential site for binding ligands, verified by molecular dynamics simulation. In this way, the fluorescence of ligands can be dramatically enhanced by the i-motif/miniduplex hybrids under complex physiological conditions. This provides a generic light-up system with a high signal-to-background ratio for programmable DNA nanoassemblies, illustrated through utilizing it for a pH-driven framework nucleic acid nanodevice manipulated in acidic cellular membrane microenvironments. It enables label-free fluorescence bioimaging in response to extracellular pH change.

Understanding the mechanism by which biological macromolecules fold into their functional native conformations represents a problem of fundamental interest. DNA oligonucleotides derived from human telomeric repeat d[TAGGG(TTAGGG)3] and d[TAGGG(TTAGGG)3TT] fold into G-quadruplexes through diverse steps. Varying the pH and temperature by the use of nuclear magnetic resonance and other methods enabled detection of pre-folded structures that exist in solution before completely formed G-quadruplexes upon addition of cations. Pre-folded structures are in general hard to detect, however their knowledge is crucial to set up folding pathways into final structure since they are believed to be a starting point. Unexpectedly well-defined pre-folded structures composed of base triples for both oligonucleotides were detected at certain pH and temperature. These kinds of structures were up to now only hypothesized as intermediates in the folding process. All revealed pre-folded structures irrespective of the pH and temperature exhibited one common structural feature that could govern folding process.

The development of structure-specific RNA binding reagents remains a central challenge in RNA biochemistry and drug discovery. Previously, we showed in vitro selection techniques could be used to evolve l-RNA aptamers that bind tightly to structured d-RNAs. However, whether similar RNA-binding properties can be achieved using aptamers composed of l-DNA, which has several practical advantages compared to l-RNA, remains unknown. Here, we report the discovery and characterization of the first l-DNA aptamers against a structured RNA molecule, precursor microRNA-155, thereby establishing the capacity of DNA and RNA molecules of the opposite handedness to form tight and specific ‘cross-chiral’ interactions with each other. l-DNA aptamers bind pre-miR-155 with low nanomolar affinity and high selectivity despite the inability of l-DNA to interact with native d-RNA via Watson–Crick base pairing. Furthermore, l-DNA aptamers inhibit Dicer-mediated processing of pre-miRNA-155. The sequence and structure of l-DNA aptamers are distinct from previously reported l-RNA aptamers against pre-miR-155, indicating that l-DNA and l-RNA interact with the same RNA sequence through unique modes of recognition. Overall, this work demonstrates that l-DNA may be pursued as an alternative to l-RNA for the generation of RNA-binding aptamers, providing a robust and practical approach for targeting structured RNAs.

Negative supercoiling by DNA gyrase is essential for maintaining chromosomal compaction, transcriptional programming, and genetic integrity in bacteria. Questions remain as to how gyrases from different species have evolved profound differences in their kinetics, efficiency, and extent of negative supercoiling. To explore this issue, we analyzed homology-directed mutations in the C-terminal, DNA-wrapping domain of the GyrA subunit of Escherichia coli gyrase (the ‘CTD’). The addition or removal of select, conserved basic residues markedly impacts both nucleotide-dependent DNA wrapping and supercoiling by the enzyme. Weakening CTD–DNA interactions slows supercoiling, impairs DNA-dependent ATP hydrolysis, and limits the extent of DNA supercoiling, while simultaneously enhancing decatenation and supercoil relaxation. Conversely, strengthening DNA wrapping does not result in a more extensively supercoiled DNA product, but partially uncouples ATP turnover from strand passage, manifesting in futile cycling. Our findings indicate that the catalytic cycle of E. coli gyrase operates at high thermodynamic efficiency, and that the stability of DNA wrapping by the CTD provides one limit to DNA supercoil introduction, beyond which strand passage competes with ATP-dependent supercoil relaxation. These results highlight a means by which gyrase can evolve distinct homeostatic supercoiling setpoints in a species-specific manner.

Somatic synonymous mutations are one of the most frequent genetic variants occurring in the coding region of cancer genomes, while their contributions to cancer development remain largely unknown. To assess whether synonymous mutations involved in post-transcriptional regulation contribute to the genetic etiology of cancers, we collected whole exome data from 8,320 patients across 22 cancer types. By employing our developed algorithm, PIVar, we identified a total of 22,948 posttranscriptionally impaired synonymous SNVs (pisSNVs) spanning 2,042 genes. In addition, 35 RNA binding proteins impacted by these identified pisSNVs were significantly enriched. Remarkably, we discovered markedly elevated ratio of somatic pisSNVs across all 22 cancer types, and a high pisSNV ratio was associated with worse patient survival in five cancer types. Intriguing, several well-established cancer genes, including PTEN, RB1 and PIK3CA, appeared to contribute to tumorigenesis at both protein function and posttranscriptional regulation levels, whereas some pisSNV-hosted genes, including UBR4, EP400 and INTS1, exerted their function during carcinogenesis mainly via posttranscriptional mechanisms. Moreover, we predicted three drugs associated with two pisSNVs, and numerous compounds associated with expression signature of pisSNV-hosted genes. Our study reveals the prevalence and clinical relevance of pisSNVs in cancers, and emphasizes the importance of considering posttranscriptional impaired synonymous mutations in cancer biology.

Nucleic Acids Research, 2019, gkz1097, https://doi.org/10.1093/nar/gkz1097

RNA aptamers that bind HIV-1 reverse transcriptase (RT) inhibit RT in enzymatic and viral replication assays. Some aptamers inhibit RT from only a few viral clades, while others show broad-spectrum inhibition. Biophysical determinants of recognition specificity are poorly understood. We investigated the interface between HIV-1 RT and a broad–spectrum UCAA-family aptamer. SAR and hydroxyl radical probing identified aptamer structural elements critical for inhibition and established the role of signature UCAA bulge motif in RT-aptamer interaction. HDX footprinting on RT ± aptamer shows strong contacts with both subunits, especially near the C-terminus of p51. Alanine scanning revealed decreased inhibition by the aptamer for mutants P420A, L422A and K424A. 2D proton nuclear magnetic resonance and SAXS data provided constraints on the solution structure of the aptamer and enable computational modeling of the docked complex with RT. Surprisingly, the aptamer enhanced proteolytic cleavage of precursor p66/p66 by HIV-1 protease, suggesting that it stabilizes the productive conformation to allow maturation. These results illuminate features at the RT-aptamer interface that govern recognition specificity by a broad-spectrum antiviral aptamer, and they open new possibilities for accelerating RT maturation and interfering with viral replication.

Besides analyses of specific alternative splicing (AS) variants, little is known about AS regulatory pathways and programs involved in anticancer drug resistance. Doxorubicin is widely used in breast cancer chemotherapy. Here, we identified 1723 AS events and 41 splicing factors regulated in a breast cancer cell model of acquired resistance to doxorubicin. An RNAi screen on splicing factors identified the little studied ZRANB2 and SYF2, whose depletion partially reversed doxorubicin resistance. By RNAi and RNA-seq in resistant cells, we found that the AS programs controlled by ZRANB2 and SYF2 were enriched in resistance-associated AS events, and converged on the ECT2 splice variant including exon 5 (ECT2-Ex5+). Both ZRANB2 and SYF2 were found associated with ECT2 pre-messenger RNA, and ECT2-Ex5+ isoform depletion reduced doxorubicin resistance. Following doxorubicin treatment, resistant cells accumulated in S phase, which partially depended on ZRANB2, SYF2 and the ECT2-Ex5+ isoform. Finally, doxorubicin combination with an oligonucleotide inhibiting ECT2-Ex5 inclusion reduced doxorubicin-resistant tumor growth in mouse xenografts, and high ECT2-Ex5 inclusion levels were associated with bad prognosis in breast cancer treated with chemotherapy. Altogether, our data identify AS programs controlled by ZRANB2 and SYF2 and converging on ECT2, that participate to breast cancer cell resistance to doxorubicin.

2′-O-Methylation (Nm) represents one of the most common RNA modifications. Nm affects RNA structure and function with crucial roles in various RNA-mediated processes ranging from RNA silencing, translation, self versus non-self recognition to viral defense mechanisms. Here, we identify two Nm methyltransferases (Nm-MTases) in Drosophila melanogaster (CG7009 and CG5220) as functional orthologs of yeast TRM7 and human FTSJ1. Genetic knockout studies together with MALDI-TOF mass spectrometry and RiboMethSeq mapping revealed that CG7009 is responsible for methylating the wobble position in tRNAPhe, tRNATrp and tRNALeu, while CG5220 methylates position C32 in the same tRNAs and also targets additional tRNAs. CG7009 or CG5220 mutant animals were viable and fertile but exhibited various phenotypes such as lifespan reduction, small RNA pathways dysfunction and increased sensitivity to RNA virus infections. Our results provide the first detailed characterization of two TRM7 family members in Drosophila and uncover a molecular link between enzymes catalyzing Nm at specific tRNAs and small RNA-induced gene silencing pathways.

The human apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3 (APOBEC3, A3) family member proteins can deaminate cytosines in single-strand (ss) DNA, which restricts human immunodeficiency virus type 1 (HIV-1), retrotransposons, and other viruses such as hepatitis B virus, but can cause a mutator phenotype in many cancers. While structural information exists for several A3 proteins, the precise details regarding deamination target selection are not fully understood. Here, we report the first parallel, comparative analysis of site selection of A3 deamination using six of the seven purified A3 member enzymes, oligonucleotides having 5′TC3′ or 5′CT3′ dinucleotide target sites, and different flanking bases within diverse DNA secondary structures. A3A, A3F and A3H were observed to have strong preferences toward the TC target flanked by A or T, while all examined A3 proteins did not show a preference for a TC target flanked by a G. We observed that the TC target was strongly preferred in ssDNA regions rather than dsDNA, loop or bulge regions, with flanking bases influencing the degree of preference. CT was also shown to be a potential deamination target. Taken together, our observations provide new insights into A3 enzyme target site selection and how A3 mutagenesis impacts mutation rates.

Type II CRISPR–Cas9 RNA-guided nucleases are widely used for genome engineering. Type II-A SpCas9 protein from Streptococcus pyogenes is the most investigated and highly used enzyme of its class. Nevertheless, it has some drawbacks, including a relatively big size, imperfect specificity and restriction to DNA targets flanked by an NGG PAM sequence. Cas9 orthologs from other bacterial species may provide a rich and largely untapped source of biochemical diversity, which can help to overcome the limitations of SpCas9. Here, we characterize CcCas9, a Type II-C CRISPR nuclease from Clostridium cellulolyticum H10. We show that CcCas9 is an active endonuclease of comparatively small size that recognizes a novel two-nucleotide PAM sequence. The CcCas9 can potentially broaden the existing scope of biotechnological applications of Cas9 nucleases and may be particularly advantageous for genome editing of C. cellulolyticum H10, a bacterium considered to be a promising biofuel producer.

Allele-specific protospacer adjacent motif (asPAM)-positioning SNPs and CRISPRs are valuable resources for gene therapy of dominant disorders. However, one technical hurdle is to identify the haplotype comprising the disease-causing allele and the distal asPAM SNPs. Here, we describe a novel CRISPR-based method (CRISPR-hapC) for haplotyping. Based on the generation (with a pair of CRISPRs) of extrachromosomal circular DNA in cells, the CRISPR-hapC can map haplotypes from a few hundred bases to over 200 Mb. To streamline and demonstrate the applicability of the CRISPR-hapC and asPAM CRISPR for allele-specific gene editing, we reanalyzed the 1000 human pan-genome and generated a high frequency asPAM SNP and CRISPR database (www.crispratlas.com/knockout) for four CRISPR systems (SaCas9, SpCas9, xCas9 and Cas12a). Using the huntingtin (HTT) CAG expansion and transthyretin (TTR) exon 2 mutation as examples, we showed that the asPAM CRISPRs can specifically discriminate active and dead PAMs for all 23 loci tested. Combination of the CRISPR-hapC and asPAM CRISPRs further demonstrated the capability for achieving highly accurate and haplotype-specific deletion of the HTT CAG expansion allele and TTR exon 2 mutation in human cells. Taken together, our study provides a new approach and an important resource for genome research and allele-specific (haplotype-specific) gene therapy.

Nucleic Acids Research, 2019, 47(19): e120, https://doi.org/10.1093/nar/gkz713

The spatiotemporal expression of genes is controlled by enhancer sequences that bind transcription factors. Identifying the target genes of enhancers remains difficult because enhancers regulate gene expression over long genomic distances. To address this, we used an evolutionary approach to build two genome-wide maps of predicted enhancer–gene associations in the human and zebrafish genomes. Evolutionary conserved sequences were linked to their predicted target genes using PEGASUS, a bioinformatics method that relies on evolutionary conservation of synteny. The analysis of these maps revealed that the number of predicted enhancers linked to a gene correlate with its expression breadth. Comparison of both maps identified hundreds of putative vertebrate ancestral regulatory relationships from which we could determine that predicted enhancer–gene distances scale with genome size despite strong positional conservation. The two maps represent a resource for further studies, including the prioritization of sequence variants in whole genome sequence of patients affected by genetic diseases.

Ongoing large-scale genome sequencing projects are forecasting a data deluge that will almost certainly overwhelm current analytical capabilities of evolutionary genomics. In contrast to population genomics, there are no standardized methods in evolutionary genomics for extracting evolutionary and functional (e.g. gene-trait association) signal from genomic data. Here, we examine how current practices of multi-species comparative genomics perform in this aspect and point out that many genomic datasets are under-utilized due to the lack of powerful methodologies. As a result, many current analyses emphasize gene families for which some functional data is already available, resulting in a growing gap between functionally well-characterized genes/organisms and the universe of unknowns. This leaves unknown genes on the ‘dark side’ of genomes, a problem that will not be mitigated by sequencing more and more genomes, unless we develop tools to infer functional hypotheses for unknown genes in a systematic manner. We provide an inventory of recently developed methods capable of predicting gene-gene and gene-trait associations based on comparative data, then argue that realizing the full potential of whole genome datasets requires the integration of phylogenetic comparative methods into genomics, a rich but underutilized toolbox for looking into the past.

MicroRNAs (miRNAs) are short, non-coding RNAs that modulate the translation-rate of messenger RNAs (mRNAs) by directing the RNA-induced silencing complex to sequence-specific targets. In plants, this typically results in cleavage and subsequent degradation of the mRNA. Degradome sequencing is a high-throughput technique developed to capture cleaved mRNA fragments and thus can be used to support miRNA target prediction. The current criteria used for miRNA target prediction were inferred on a limited number of experimentally validated A. thaliana interactions and were adapted to fit these specific interactions; thus, these fixed criteria may not be optimal across all datasets (organisms, tissues or treatments). We present a new tool, PAREameters, for inferring targeting criteria from small RNA and degradome sequencing datasets. We evaluate its performance using a more extensive set of experimentally validated interactions in multiple A. thaliana datasets. We also perform comprehensive analyses to highlight and quantify the differences between subsets of miRNA–mRNA interactions in model and non-model organisms. Our results show increased sensitivity in A. thaliana when using the PAREameters inferred criteria and that using data-driven criteria enables the identification of additional interactions that further our understanding of the RNA silencing pathway in both model and non-model organisms.

Recent years have witnessed increasing efforts to engineer artificial biological functions through recombination of modular-organized toolboxes of protein scaffolds and parts. A critical, yet frequently neglected aspect concerns the identity of peptide linkers or spacers connecting individual domains which remain poorly understood and challenging to assemble. Addressing these limitations, iFlinkC comprises a highly scalable DNA assembly process that facilitates the combinatorial recombination of functional domains with linkers of varying length and flexibility, thereby overcoming challenges with high GC-content and the repeat nature of linker elements. The capacity of iFLinkC is demonstrated in the construction of synthetic protease switches featuring PDZ-FN3-based affinity clamps and single-chain FKBP12-FRB receptors as allosteric inputs. Library screening experiments demonstrate that linker space is highly plastic as the induction of allosterically regulated protease switches can vary from >150-fold switch-ON to >13-fold switch-OFF solely depending on the identity of the connecting linkers and relative orientation of functional domains. In addition, Pro-rich linkers yield the most potent switches contradicting the conventional use of flexible Gly-Ser linkers. Given the ease and efficiency how functional domains can be readily recombined with any type of linker, iFLinkC is anticipated to be widely applicable to the assembly of any type of fusion protein.

Tight and coordinate regulation of virulence determinants is essential for bacterial biology and involves dynamic shaping of transcriptional regulatory networks during evolution. The horizontally transferred two-partner secretion system ExlB–ExlA is instrumental in the virulence of different Pseudomonas species, ranging from soil- and plant-dwelling biocontrol agents to the major human pathogen Pseudomonas aeruginosa. Here, we identify a Cro/CI-like repressor, named ErfA, which together with Vfr, a CRP-like activator, controls exlBA expression in P. aeruginosa. The characterization of ErfA regulon across P. aeruginosa subfamilies revealed a second conserved target, the ergAB operon, with functions unrelated to virulence. To gain insights into this functional dichotomy, we defined the pan-regulon of ErfA in several Pseudomonas species and found ergAB as the sole conserved target of ErfA. The analysis of 446 exlBA promoter sequences from all exlBA+ genomes revealed a wide variety of regulatory sequences, as ErfA- and Vfr-binding sites were found to have evolved specifically in P. aeruginosa and nearly each species carries different regulatory sequences for this operon. We propose that the emergence of different regulatory cis-elements in the promoters of horizontally transferred genes is an example of plasticity of regulatory networks evolving to provide an adapted response in each individual niche.

A significant number of X-linked genes escape from X chromosome inactivation and are associated with a distinct epigenetic signature. One epigenetic modification that strongly correlates with X-escape is reduced DNA methylation in promoter regions. Here, we created an artificial escape by editing DNA methylation on the promoter of CDKL5, a gene causative for an infantile epilepsy, from the silenced X-chromosomal allele in human neuronal-like cells. We identify that a fusion of the catalytic domain of TET1 to dCas9 targeted to the CDKL5 promoter using three guide RNAs causes significant reactivation of the inactive allele in combination with removal of methyl groups from CpG dinucleotides. Strikingly, we demonstrate that co-expression of TET1 and a VP64 transactivator have a synergistic effect on the reactivation of the inactive allele to levels >60% of the active allele. We further used a multi-omics assessment to determine potential off-targets on the transcriptome and methylome. We find that synergistic delivery of dCas9 effectors is highly selective for the target site. Our findings further elucidate a causal role for reduced DNA methylation associated with escape from X chromosome inactivation. Understanding the epigenetics associated with escape from X chromosome inactivation has potential for those suffering from X-linked disorders.

The XPA protein functions together with the single-stranded DNA (ssDNA) binding protein RPA as the central scaffold to ensure proper positioning of repair factors in multi-protein nucleotide excision repair (NER) machinery. We previously determined the structure of a short motif in the disordered XPA N-terminus bound to the RPA32C domain. However, a second contact between the XPA DNA-binding domain (XPA DBD) and the RPA70AB tandem ssDNA-binding domains, which is likely to influence the orientation of XPA and RPA on the damaged DNA substrate, remains poorly characterized. NMR was used to map the binding interfaces of XPA DBD and RPA70AB. Combining NMR and X-ray scattering data with comprehensive docking and refinement revealed how XPA DBD and RPA70AB orient on model NER DNA substrates. The structural model enabled design of XPA mutations that inhibit the interaction with RPA70AB. These mutations decreased activity in cell-based NER assays, demonstrating the functional importance of XPA DBD–RPA70AB interaction. Our results inform ongoing controversy about where XPA is bound within the NER bubble, provide structural insights into the molecular basis for malfunction of disease-associated XPA missense mutations, and contribute to understanding of the structure and mechanical action of the NER machinery.

H-NS proteins act as osmotic sensors translating changes in osmolarity into altered DNA binding properties, thus, regulating enterobacterial genome organization and genes transcription. The molecular mechanism underlying the switching process and its conservation among H-NS family members remains elusive. Here, we focus on the H-NS family protein MvaT from Pseudomonas aeruginosa and demonstrate experimentally that its protomer exists in two different conformations, corresponding to two different functional states. In the half-opened state (dominant at low salt) the protein forms filaments along DNA, in the fully opened state (dominant at high salt) the protein bridges DNA. This switching is a direct effect of ionic strength on electrostatic interactions between the oppositely charged DNA binding and N-terminal domains of MvaT. The asymmetric charge distribution and intramolecular interactions are conserved among the H-NS family of proteins. Therefore, our study establishes a general paradigm for the molecular mechanistic basis of the osmosensitivity of H-NS proteins.

The excision of mutagenic DNA adducts by the nucleotide excision repair (NER) pathway is essential for genome stability, which is key to avoiding genetic diseases, premature aging, cancer and neurologic disorders. Due to the need to process an extraordinarily high damage density embedded in the nucleosome landscape of chromatin, NER activity provides a unique functional caliper to understand how histone modifiers modulate DNA damage responses. At least three distinct lysine methyltransferases (KMTs) targeting histones have been shown to facilitate the detection of ultraviolet (UV) light-induced DNA lesions in the difficult to access DNA wrapped around histones in nucleosomes. By methylating core histones, these KMTs generate docking sites for DNA damage recognition factors before the chromatin structure is ultimately relaxed and the offending lesions are effectively excised. In view of their function in priming nucleosomes for DNA repair, mutations of genes coding for these KMTs are expected to cause the accumulation of DNA damage promoting cancer and other chronic diseases. Research on the question of how KMTs modulate DNA repair might pave the way to the development of pharmacologic agents for novel therapeutic strategies.

Three-dimensional structures have been solved for several naturally occurring RNA triple helices, although all are limited to six or fewer consecutive base triples, hindering accurate estimation of global and local structural parameters. We present an X-ray crystal structure of a right-handed, U•A-U-rich RNA triple helix with 11 continuous base triples. Due to helical unwinding, the RNA triple helix spans an average of 12 base triples per turn. The double helix portion of the RNA triple helix is more similar to both the helical and base step structural parameters of A′-RNA rather than A-RNA. Its most striking features are its wide and deep major groove, a smaller inclination angle and all three strands favoring a C3′-endo sugar pucker. Despite the presence of a third strand, the diameter of an RNA triple helix remains nearly identical to those of DNA and RNA double helices. Contrary to our previous modeling predictions, this structure demonstrates that an RNA triple helix is not limited in length to six consecutive base triples and that longer RNA triple helices may exist in nature. Our structure provides a starting point to establish structural parameters of the so-called ‘ideal’ RNA triple helix, analogous to A-RNA and B-DNA double helices.

Steroid hormones are pivotal modulators of pathophysiological processes in many organs, where they interact with nuclear receptors to regulate gene transcription. However, our understanding of hormone action at the single cell level remains incomplete. Here, we focused on estrogen stimulation of the well-characterized GREB1 and MYC target genes that revealed large differences in cell-by-cell responses, and, more interestingly, between alleles within the same cell, both over time and hormone concentration. We specifically analyzed the role of receptor level and activity state during allele-by-allele regulation and found that neither receptor level nor activation status are the determinant of maximal hormonal response, indicating that additional pathways are potentially in place to modulate cell- and allele-specific responses. Interestingly, we found that a small molecule inhibitor of the arginine methyltransferases CARM1 and PRMT6 was able to increase, in a gene specific manner, the number of active alleles/cell before and after hormonal stimulation, suggesting that mechanisms do indeed exist to modulate hormone receptor responses at the single cell and allele level.

The double-helical structure of DNA results from canonical base pairing and stacking interactions. However, variations from steady-state conformations resulting from mechanical perturbations in cells have physiological relevance but their dependence on sequence remains unclear. Here, we use molecular dynamics simulations showing sequence differences result in markedly different structural motifs upon physiological twisting and stretching. We simulate overextension on different sequences of DNA ((AA)12, (AT)12, (CC)12 and (CG)12) with supercoiling densities at 200 and 50 mM salt concentrations. We find that DNA denatures in the majority of stretching simulations, surprisingly including those with over-twisted DNA. GC-rich sequences are observed to be more stable than AT-rich ones, with the specific response dependent on the base pair order. Furthermore, we find that (AT)12 forms stable periodic structures with non-canonical hydrogen bonds in some regions and non-canonical stacking in others, whereas (CG)12 forms a stacking motif of four base pairs independent of supercoiling density. Our results demonstrate that 20–30% DNA extension is sufficient for breaking B-DNA around and significantly above cellular supercoiling, and that the DNA sequence is crucial for understanding structural changes under mechanical stress. Our findings have important implications for the activities of protein machinery interacting with DNA in all cells.

The rolling-circle replication is the most common mechanism for the replication of small plasmids carrying antibiotic resistance genes in Gram-positive bacteria. It is initiated by the binding and nicking of double-stranded origin of replication by a replication initiator protein (Rep). Duplex unwinding is then performed by the PcrA helicase, whose processivity is critically promoted by its interaction with Rep. How Rep and PcrA proteins interact to nick and unwind the duplex is not fully understood. Here, we have used magnetic tweezers to monitor PcrA helicase unwinding and its relationship with the nicking activity of Staphylococcus aureus plasmid pT181 initiator RepC. Our results indicate that PcrA is a highly processive helicase prone to stochastic pausing, resulting in average translocation rates of 30 bp s−1, while a typical velocity of 50 bp s−1 is found in the absence of pausing. Single-strand DNA binding protein did not affect PcrA translocation velocity but slightly increased its processivity. Analysis of the degree of DNA supercoiling required for RepC nicking, and the time between RepC nicking and DNA unwinding, suggests that RepC and PcrA form a protein complex on the DNA binding site before nicking. A comprehensive model that rationalizes these findings is presented.

Nucleic Acids Research, 2005, 33: 4725–4739, https://doi.org/10.1093/nar/gki783

In order to discover new antibiotics with improved activity and selectivity, we created a reliable in vitro reporter system to detect trans-translation activity, the main mechanism for recycling ribosomes stalled on problematic messenger RNA (mRNA) in bacteria. This system is based on an engineered tmRNA variant that reassembles the green fluorescent protein (GFP) when trans-translation is active. Our system is adapted for high-throughput screening of chemical compounds by fluorescence.

BCDIN3 domain containing RNA methyltransferase, BCDIN3D, monomethylates the 5′-monophosphate of cytoplasmic tRNAHis with a G−1:A73 mispair at the top of an eight-nucleotide-long acceptor helix, using S-adenosyl-l-methionine (SAM) as a methyl group donor. In humans, BCDIN3D overexpression is associated with the tumorigenic phenotype and poor prognosis in breast cancer. Here, we present the crystal structure of human BCDIN3D complexed with S-adenosyl-l-homocysteine. BCDIN3D adopts a classical Rossmann-fold methyltransferase structure. A comparison of the structure with that of the closely related methylphosphate capping enzyme, MePCE, which monomethylates the 5′-γ-phosphate of 7SK RNA, revealed the important residues for monomethyl transfer from SAM onto the 5′-monophosphate of tRNAHis and for tRNAHis recognition by BCDIN3D. A structural model of tRNAHis docking onto BCDIN3D suggested the molecular mechanism underlying the different activities between BCDIN3D and MePCE. A loop in BCDIN3D is shorter, as compared to the corresponding region that forms an α-helix to recognize the 5′-end of RNA in MePCE, and the G−1:A73 mispair in tRNAHis allows the N-terminal α-helix of BCDIN3D to wedge the G−1:A73 mispair of tRNAHis. As a result, the 5′-monophosphate of G−1 of tRNAHis is deep in the catalytic pocket for 5′-phosphate methylation. Thus, BCDIN3D is a tRNAHis-specific 5′-monomethylphosphate capping enzyme that discriminates tRNAHis from other tRNA species, and the structural information presented in this study also provides the molecular basis for the development of drugs against breast cancers.

Replication protein A (RPA) plays a critical role in all eukaryotic DNA processing involving single-stranded DNA (ssDNA). Contrary to the notion that RPA provides solely inert protection to transiently formed ssDNA, the RPA–ssDNA complex acts as a dynamic DNA processing unit. Here, we studied the diffusion of RPA along 60 nt ssDNA using a coarse-grained model in which the ssDNA–RPA interface was modeled by both aromatic and electrostatic interactions. Our study provides direct evidence of bulge formation during the diffusion of ssDNA along RPA. Bulges can form at a few sites along the interface and store 1–7 nt of ssDNA whose release, upon bulge dissolution, leads to propagation of ssDNA diffusion. These findings thus support the reptation mechanism, which involves bulge formation linked to the aromatic interactions, whose short range nature reduces cooperativity in ssDNA diffusion. Greater cooperativity and a larger diffusion coefficient for ssDNA diffusion along RPA are observed for RPA variants with weaker aromatic interactions and for interfaces homogenously stabilized by electrostatic interactions. ssDNA propagation in the latter instance is characterized by lower probabilities of bulge formation; thus, it may fit the sliding-without-bulge model better than the reptation model. Thus, the reptation mechanism allows ssDNA mobility despite the extensive and high affinity interface of RPA with ssDNA. The short-range aromatic interactions support bulge formation while the long-range electrostatic interactions support the release of the stored excess ssDNA in the bulge and thus the overall diffusion.

Diplonemids are highly abundant heterotrophic marine protists. Previous studies showed that their strikingly bloated mitochondrial genome is unique because of systematic gene fragmentation and manifold RNA editing. Here we report a comparative study of mitochondrial genome architecture, gene structure and RNA editing of six recently isolated, phylogenetically diverse diplonemid species. Mitochondrial gene fragmentation and modes of RNA editing, which include cytidine-to-uridine (C-to-U) and adenosine-to-inosine (A-to-I) substitutions and 3′ uridine additions (U-appendage), are conserved across diplonemids. Yet as we show here, all these features have been pushed to their extremes in the Hemistasiidae lineage. For example, Namystynia karyoxenos has its genes fragmented into more than twice as many modules than other diplonemids, with modules as short as four nucleotides. Furthermore, we detected in this group multiple A-appendage and guanosine-to-adenosine (G-to-A) substitution editing events not observed before in diplonemids and found very rarely elsewhere. With >1,000 sites, C-to-U and A-to-I editing in Namystynia is nearly 10 times more frequent than in other diplonemids. The editing density of 12% in coding regions makes Namystynia’s the most extensively edited transcriptome described so far. Diplonemid mitochondrial genome architecture, gene structure and post-transcriptional processes display such high complexity that they challenge all other currently known systems.

The occurrence of group II introns in plant mitochondrial genomes is strikingly different between the six major land plant clades, contrasting their highly conserved counterparts in chloroplast DNA. Their present distribution likely reflects numerous ancient intron gains and losses during early plant evolution before the emergence of seed plants. As a novelty for plant organelles, we here report on five cases of twintrons, introns-within-introns, in the mitogenomes of lycophytes and hornworts. An internal group II intron interrupts an intron-borne maturase of an atp9 intron in Lycopodiaceae, whose splicing precedes splicing of the external intron. An invasive, hypermobile group II intron in cox1, has conquered nine further locations including a previously overlooked sdh3 intron and, most surprisingly, also itself. In those cases, splicing of the external introns does not depend on splicing of the internal introns. Similar cases are identified in the mtDNAs of hornworts. Although disrupting a group I intron-encoded protein in one case, we could not detect splicing of the internal group II intron in this ‘mixed’ group I/II twintron. We suggest the name ‘zombie’ twintrons (half-dead, half-alive) for such cases where splicing of external introns does not depend any more on prior splicing of fossilized internal introns.

Time-resolved imino proton nuclear magnetic resonance spectra of the WT22m sequence d(GGGCCACCGGGCAGTGGGCGGG), derived from the WNT1 promoter region, revealed an intermediate G-quadruplex G4(I) structure during K+-induced conformational transition from an initial hairpin structure to the final G4(II) structure. Moreover, a single-base C-to-T mutation at either position C4 or C7 of WT22m could lock the intermediate G4(I) structure without further conformational change to the final G4(II) structure. Surprisingly, we found that the intermediate G4(I) structure is an atypical G4 structure, which differs from a typical hybrid G4 structure of the final G4(II) structure. Further studies of modified cytosine analogues associated with epigenetic regulation indicated that slight modification on a cytosine could modulate G4 structure. A simplified four-state transition model was introduced to describe such conformational transition and disclose the possible mechanism for G4 structural selection caused by cytosine modification.

G-quadruplex (G4) DNA structures are linked to key biological processes and human diseases. Small molecules that target specific G4 DNA structures and signal their presence would therefore be of great value as chemical research tools with potential to further advance towards diagnostic and therapeutic developments. However, the development of these types of specific compounds remain as a great challenge. In here, we have developed a compound with ability to specifically signal a certain c-MYC G4 DNA structure through a fluorescence light-up mechanism. Despite the compound's two binding sites on the G4 DNA structure, only one of them result in the fluorescence light-up effect. This G-tetrad selectivity proved to originate from a difference in flexibility that affected the binding affinity and tilt the compound out of the planar conformation required for the fluorescence light-up mechanism. The intertwined relation between the presented factors is likely the reason for the lack of examples using rational design to develop compounds with turn-on emission that specifically target certain G4 DNA structures. However, this study shows that it is indeed possible to develop such compounds and present insights into the molecular details of specific G4 DNA recognition and signaling to advance future studies of G4 biology.

N6-methyladenosine (m6A) is a reversible and dynamic RNA modification in eukaryotes. However, how cells establish cell-specific m6A methylomes is still poorly understood. Here, we developed a computational framework to systematically identify cell-specific trans regulators of m6A through integrating gene expressions, binding targets and binding motifs of large number of RNA binding proteins (RBPs) with a co-methylation network constructed using large-scale m6A methylomes across diverse cell states. We applied the framework and successfully identified 32 high-confidence m6A regulators that modulated the variable m6A sites away from stop codons in a cell-specific manner. To validate them, we knocked down three regulators respectively and found two of them (TRA2A and CAPRIN1) selectively promoted the methylations of the m6A sites co-localized with their binding targets on RNAs through physical interactions with the m6A writers. Knockdown of TRA2A increased the stabilities of the RNAs with TRA2A bound near the m6A sites and decreased the viability of cells. The successful identification of m6A regulators demonstrates a powerful and widely applicable strategy to elucidate the cell-specific m6A regulators. Additionally, our discovery of pervasive trans-acting regulating of m6A provides novel insights into the mechanisms by which spatial and temporal dynamics of m6A methylomes are established.

Malaria is a tropical parasitic disease caused by the Plasmodium genus, which resulted in an estimated 219 million cases of malaria and 435 000 malaria-related deaths in 2017. Despite the availability of the Plasmodium falciparum genome since 2002, 74% of the genes remain uncharacterized. To remedy this paucity of functional information, we used transcriptomic data to build gene co-expression networks for two Plasmodium species (P. falciparum and P. berghei), and included genomic data of four other Plasmodium species, P. yoelii, P. knowlesi, P. vivax and P. cynomolgi, as well as two non-Plasmodium species from the Apicomplexa, Toxoplasma gondii and Theileria parva. The genomic and transcriptomic data were incorporated into the resulting database, malaria.tools, which is preloaded with tools that allow the identification and cross-species comparison of co-expressed gene neighbourhoods, clusters and life stage-specific expression, thus providing sophisticated tools to predict gene function. Moreover, we exemplify how the tools can be used to easily identify genes relevant for pathogenicity and various life stages of the malaria parasite. The database is freely available at www.malaria.tools.

The ABCD (for AntiBodies Chemically Defined) database is a repository of sequenced antibodies, integrating curated information about the antibody and its antigen with cross-links to standardized databases of chemical and protein entities. It is freely available to the academic community, accessible through the ExPASy server (https://web.expasy.org/abcd/). The ABCD database aims at helping to improve reproducibility in academic research by providing a unique, unambiguous identifier associated to each antibody sequence. It also allows to determine rapidly if a sequenced antibody is available for a given antigen.

Numerous studies indicate that non-coding RNAs (ncRNAs) have critical functions across biological processes, and single-nucleotide polymorphisms (SNPs) could contribute to diseases or traits through influencing ncRNA expression. However, the associations between SNPs and ncRNA expression are largely unknown. Therefore, genome-wide expression quantitative trait loci (eQTL) analysis to assess the effects of SNPs on ncRNA expression, especially in multiple cancer types, will help to understand how risk alleles contribute toward tumorigenesis and cancer development. Using genotype data and expression profiles of ncRNAs of >8700 samples from The Cancer Genome Atlas (TCGA), we developed a computational pipeline to systematically identify ncRNA-related eQTLs (ncRNA-eQTLs) across 33 cancer types. We identified a total of 6 133 278 and 721 122 eQTL-ncRNA pairs in cis-eQTL and trans-eQTL analyses, respectively. Further survival analyses identified 8312 eQTLs associated with patient survival times. Furthermore, we linked ncRNA-eQTLs to genome-wide association study (GWAS) data and found 262 332 ncRNA-eQTLs overlapping with known disease- and trait-associated loci. Finally, a user-friendly database, ncRNA-eQTL (http://ibi.hzau.edu.cn/ncRNA-eQTL), was developed for free searching, browsing and downloading of all ncRNA-eQTLs. We anticipate that such an integrative and comprehensive resource will improve our understanding of the mechanistic basis of human complex phenotypic variation, especially for ncRNA- and cancer-related studies.

Epigenetic alterations, including 5-methylcytosine (5mC), 5-hydroxymethylcytosine (5hmC) and nucleosome positioning (NP), in cell-free DNA (cfDNA) have been widely observed in human diseases, and many available cfDNA-based epigenome-wide profiles exhibit high sensitivity and specificity in disease detection and classification. However, due to the lack of efficient collection, standardized quality control, and analysis procedures, efficiently integrating and reusing these data remain considerable challenges. Here, we introduce CFEA (http://www.bio-data.cn/CFEA), a cell-free epigenome database dedicated to three types of widely adopted epigenetic modifications (5mC, 5hmC and NP) involved in 27 human diseases. We developed bioinformatic pipelines for quality control and standard data processing and an easy-to-use web interface to facilitate the query, visualization and download of these cell-free epigenome data. We also manually curated related biological and clinical information for each profile, allowing users to better browse and compare cfDNA epigenomes at a specific stage (such as early- or metastasis-stage) of cancer development. CFEA provides a comprehensive and timely resource to the scientific community and supports the development of liquid biopsy-based biomarkers for various human diseases.

MicroRNAs (miRNAs) are small noncoding RNAs that act as master regulators in many biological processes. miRNAs function mainly by downregulating the expression of their gene targets. Thus, accurate prediction of miRNA targets is critical for characterization of miRNA functions. To this end, we have developed an online database, miRDB, for miRNA target prediction and functional annotations. Recently, we have performed major updates for miRDB. Specifically, by employing an improved algorithm for miRNA target prediction, we now present updated transcriptome-wide target prediction data in miRDB, including 3.5 million predicted targets regulated by 7000 miRNAs in five species. Further, we have implemented the new prediction algorithm into a web server, allowing custom target prediction with user-provided sequences. Another new database feature is the prediction of cell-specific miRNA targets. miRDB now hosts the expression profiles of over 1000 cell lines and presents target prediction data that are tailored for specific cell models. At last, a new web query interface has been added to miRDB for prediction of miRNA functions by integrative analysis of target prediction and Gene Ontology data. All data in miRDB are freely accessible at http://mirdb.org.

GMrepo (data repository for Gut Microbiota) is a database of curated and consistently annotated human gut metagenomes. Its main purpose is to facilitate the reusability and accessibility of the rapidly growing human metagenomic data. This is achieved by consistently annotating the microbial contents of collected samples using state-of-art toolsets and by manual curation of the meta-data of the corresponding human hosts. GMrepo organizes the collected samples according to their associated phenotypes and includes all possible related meta-data such as age, sex, country, body-mass-index (BMI) and recent antibiotics usage. To make relevant information easier to access, GMrepo is equipped with a graphical query builder, enabling users to make customized, complex and biologically relevant queries. For example, to find (1) samples from healthy individuals of 18 to 25 years old with BMIs between 18.5 and 24.9, or (2) projects that are related to colorectal neoplasms, with each containing >100 samples and both patients and healthy controls. Precomputed species/genus relative abundances, prevalence within and across phenotypes, and pairwise co-occurrence information are all available at the website and accessible through programmable interfaces. So far, GMrepo contains 58 903 human gut samples/runs (including 17 618 metagenomes and 41 285 amplicons) from 253 projects concerning 92 phenotypes. GMrepo is freely available at: https://gmrepo.humangut.info.

Transition of soluble proteins into insoluble amyloid fibrils is driven by self-propagating short sequence stretches. However, accurate prediction of aggregation determinants remains challenging. Here, we describe WALTZ-DB 2.0, an updated and significantly expanded open-access database providing information on experimentally determined amyloid-forming hexapeptide sequences (http://waltzdb.switchlab.org/). We have updated WALTZ-DB 2.0 with new entries, including: (i) experimental validation of an in-house developed dataset of 229 hexapeptides, using electron microscopy and Thioflavin-T binding assays; (ii) manual curation of 98 amyloid-forming peptides isolated from literature. Furthermore, the content has been expanded by adding novel structural information for peptide entries, including sequences of the previous version. Using a computational methodology developed in the Switch lab, we have generated 3D-models of the putative amyloid fibril cores of WALTZ-DB 2.0 entries. Structural models, coupled with information on the energetic contributions and fibril core stabilities, can be accessed through individual peptide entries. Customized filtering options for subset selections and new modelling graphical features were added to upgrade online accessibility, providing a user-friendly interface for browsing, downloading and updating. WALTZ-DB 2.0 remains the largest open-access repository for amyloid fibril formation determinants and will continue to enhance the development of new approaches focused on accurate prediction of aggregation prone sequences.

Liquid-liquid phase separation (LLPS) leads to a conversion of homogeneous solution into a dense phase that often resembles liquid droplets, and a dilute phase. An increasing number of investigations have shown that biomolecular condensates formed by LLPS play important roles in both physiology and pathology. It has been suggested the phase behavior of proteins would be not only determined by sequences, but controlled by micro-environmental conditions. Here, we introduce LLPSDB (http://bio-comp.ucas.ac.cn/llpsdb or http://bio-comp.org.cn/llpsdb), a web-accessible database providing comprehensive, carefully curated collection of proteins involved in LLPS as well as corresponding experimental conditions in vitro from published literatures. The current release of LLPSDB incorporates 1182 entries with 273 independent proteins and 2394 specific conditions. The database provides a variety of data including biomolecular information (protein sequence, protein modification, nucleic acid, etc.), specific phase separation information (experimental conditions, phase behavior description, etc.) and comprehensive annotations. To our knowledge, LLPSDB is the first available database designed for LLPS related proteins specifically. It offers plenty of valuable resources for exploring the relationship between protein sequence and phase behavior, and will enhance the development of phase separation prediction methods, which may further provide more insights into a comprehensive understanding of LLPS in cellular function and related diseases.

The absorption, distribution and excretion of drugs are largely determined by their transporters (DTs), the variability of which has thus attracted considerable attention. There are three aspects of variability: epigenetic regulation and genetic polymorphism, species/tissue/disease-specific DT abundances, and exogenous factors modulating DT activity. The variability data of each aspect are essential for clinical study, and a collective consideration among multiple aspects becomes crucial in precision medicine. However, no database is constructed to provide the comprehensive data of all aspects of DT variability. Herein, the Variability of Drug Transporter Database (VARIDT) was introduced to provide such data. First, 177 and 146 DTs were confirmed, for the first time, by the transporting drugs approved and in clinical/preclinical, respectively. Second, for the confirmed DTs, VARIDT comprehensively collected all aspects of their variability (23 947 DNA methylations, 7317 noncoding RNA/histone regulations, 1278 genetic polymorphisms, differential abundance profiles of 257 DTs in 21 781 patients/healthy individuals, expression of 245 DTs in 67 tissues of human/model organism, 1225 exogenous factors altering the activity of 148 DTs), which allowed mutual connection between any aspects. Due to huge amount of accumulated data, VARIDT made it possible to generalize characteristics to reveal disease etiology and optimize clinical treatment, and is freely accessible at: https://db.idrblab.org/varidt/ and http://varidt.idrblab.net/.

Alternative polyadenylation (APA) is an important post-transcriptional regulation that recognizes different polyadenylation signals (PASs), resulting in transcripts with different 3′ untranslated regions, thereby influencing a series of biological processes and functions. Recent studies have revealed that some single nucleotide polymorphisms (SNPs) could contribute to tumorigenesis and development through dysregulating APA. However, the associations between SNPs and APA in human cancers remain largely unknown. Here, using genotype and APA data of 9082 samples from The Cancer Genome Atlas (TCGA) and The Cancer 3′UTR Altas (TC3A), we systematically identified SNPs affecting APA events across 32 cancer types and defined them as APA quantitative trait loci (apaQTLs). As a result, a total of 467 942 cis-apaQTLs and 30 721 trans-apaQTLs were identified. By integrating apaQTLs with survival and genome-wide association studies (GWAS) data, we further identified 2154 apaQTLs associated with patient survival time and 151 342 apaQTLs located in GWAS loci. In addition, we designed an online tool to predict the effects of SNPs on PASs by utilizing PAS motif prediction tool. Finally, we developed SNP2APA, a user-friendly and intuitive database (http://gong_lab.hzau.edu.cn/SNP2APA/) for data browsing, searching, and downloading. SNP2APA will significantly improve our understanding of genetic variants and APA in human cancers.

Research on RNA-associated interactions has exploded in recent years, and increasing numbers of studies are not limited to RNA–RNA and RNA–protein interactions but also include RNA–DNA/compound interactions. To facilitate the development of the interactome and promote understanding of the biological functions and molecular mechanisms of RNA, we updated RAID v2.0 to RNAInter (RNA Interactome Database), a repository for RNA-associated interactions that is freely accessible at http://www.rna-society.org/rnainter/ or http://www.rna-society.org/raid/. Compared to RAID v2.0, new features in RNAInter include (i) 8-fold more interaction data and 94 additional species; (ii) more definite annotations organized, including RNA editing/localization/modification/structure and homology interaction; (iii) advanced functions including fuzzy/batch search, interaction network and RNA dynamic expression and (iv) four embedded RNA interactome tools: RIscoper, IntaRNA, PRIdictor and DeepBind. Consequently, RNAInter contains >41 million RNA-associated interaction entries, involving more than 450 thousand unique molecules, including RNA, protein, DNA and compound. Overall, RNAInter provides a comprehensive RNA interactome resource for researchers and paves the way to investigate the regulatory landscape of cellular RNAs.

Gephebase is a manually-curated database compiling our accumulated knowledge of the genes and mutations that underlie natural, domesticated and experimental phenotypic variation in all Eukaryotes—mostly animals, plants and yeasts. Gephebase aims to compile studies where the genotype–phenotype association (based on linkage mapping, association mapping or a candidate gene approach) is relatively well supported. Human clinical traits and aberrant mutant phenotypes in laboratory organisms are not included and can be found in other databases (e.g. OMIM, OMIA, Monarch Initiative). Gephebase contains more than 1700 entries. Each entry corresponds to an allelic difference at a given gene and its associated phenotypic change(s) between two species or two individuals of the same species, and is enriched with molecular details, taxonomic information, and bibliographic information. Users can easily browse entries and perform searches at various levels using boolean operators (e.g. transposable elements, snakes, carotenoid content, Doebley). Data is exportable in spreadsheet format. This database allows to perform meta-analyses to extract global trends about the living world and the research fields. Gephebase should also help breeders, conservationists and others to identify promising target genes for crop improvement, parasite/pest control, bioconservation and genetic diagnostic. It is freely available at www.gephebase.org.

The Alliance of Genome Resources (Alliance) is a consortium of the major model organism databases and the Gene Ontology that is guided by the vision of facilitating exploration of related genes in human and well-studied model organisms by providing a highly integrated and comprehensive platform that enables researchers to leverage the extensive body of genetic and genomic studies in these organisms. Initiated in 2016, the Alliance is building a central portal (www.alliancegenome.org) for access to data for the primary model organisms along with gene ontology data and human data. All data types represented in the Alliance portal (e.g. genomic data and phenotype descriptions) have common data models and workflows for curation. All data are open and freely available via a variety of mechanisms. Long-term plans for the Alliance project include a focus on coverage of additional model organisms including those without dedicated curation communities, and the inclusion of new data types with a particular focus on providing data and tools for the non-model-organism researcher that support enhanced discovery about human health and disease. Here we review current progress and present immediate plans for this new bioinformatics resource.

The Therapeutic Structural Antibody Database (Thera-SAbDab; http://opig.stats.ox.ac.uk/webapps/therasabdab) tracks all antibody- and nanobody-related therapeutics recognized by the World Health Organisation (WHO), and identifies any corresponding structures in the Structural Antibody Database (SAbDab) with near-exact or exact variable domain sequence matches. Thera-SAbDab is synchronized with SAbDab to update weekly, reflecting new Protein Data Bank entries and the availability of new sequence data published by the WHO. Each therapeutic summary page lists structural coverage (with links to the appropriate SAbDab entries), alignments showing where any near-matches deviate in sequence, and accompanying metadata, such as intended target and investigated conditions. Thera-SAbDab can be queried by therapeutic name, by a combination of metadata, or by variable domain sequence - returning all therapeutics that are within a specified sequence identity over a specified region of the query. The sequences of all therapeutics listed in Thera-SAbDab (461 unique molecules, as of 5 August 2019) are downloadable as a single file with accompanying metadata.

GWAS Atlas (https://bigd.big.ac.cn/gwas/) is a manually curated resource of genome-wide variant-trait associations for a wide range of species. Unlike existing related resources, it features comprehensive integration of a high-quality collection of 75 467 variant-trait associations for 614 traits across 7 cultivated plants (cotton, Japanese apricot, maize, rapeseed, rice, sorghum and soybean) and two domesticated animals (goat and pig), which were manually curated from 254 publications. We integrated these associations into GWAS Atlas and presented them in terms of variants, genes, traits, studies and publications. More importantly, all associations and traits were annotated and organized based on a suite of ontologies (Plant Trait Ontology, Animal Trait Ontology for Livestock, etc.). Taken together, GWAS Atlas integrates high-quality curated GWAS associations for animals and plants and provides user-friendly web interfaces for data browsing and downloading, accordingly serving as a valuable resource for genetic research of important traits and breeding application.

High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations. A key issue is the complexity of the genomic regions in which they lie, which, because of the presence of multiple repeats, insertions and deletions, have not proved tractable with short-read whole genome sequencing. Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets have become available, and a community approach has been developed for the expert review and publication of such inferences. Here, we present OGRDB, the Open Germline Receptor Database (https://ogrdb.airr-community.org), a public resource for the submission, review and publication of previously unknown receptor germline sequences together with supporting evidence.

Nucleic Acids Research, 2019, gkz779, https://doi.org/10.1093/nar/gkz779

To sustain and develop the largest fully open human genomic resources the International Genome Sample Resource (IGSR) (https://www.internationalgenome.org) was established. It is built on the foundation of the 1000 Genomes Project, which created the largest openly accessible catalogue of human genomic variation developed from samples spanning five continents. IGSR (i) maintains access to 1000 Genomes Project resources, (ii) updates 1000 Genomes Project resources to the GRCh38 human reference assembly, (iii) adds new data generated on 1000 Genomes Project cell lines, (iv) shares data from samples with a similarly open consent to increase the number of samples and populations represented in the resources and (v) provides support to users of these resources. Among recent updates are the release of variation calls from 1000 Genomes Project data calculated directly on GRCh38 and the addition of high coverage sequence data for the 2504 samples in the 1000 Genomes Project phase three panel. The data portal, which facilitates web-based exploration of the IGSR resources, has been updated to include samples which were not part of the 1000 Genomes Project and now presents a unified view of data and samples across almost 5000 samples from multiple studies. All data is fully open and publicly accessible.

As the largest ethnic group in the world, the Han Chinese population is nonetheless underrepresented in global efforts to catalogue the genomic variability of natural populations. Here, we developed the PGG.Han, a population genome database to serve as the central repository for the genomic data of the Han Chinese Genome Initiative (Phase I). In its current version, the PGG.Han archives whole-genome sequences or high-density genome-wide single-nucleotide variants (SNVs) of 114 783 Han Chinese individuals (a.k.a. the Han100K), representing geographical sub-populations covering 33 of the 34 administrative divisions of China, as well as Singapore. The PGG.Han provides: (i) an interactive interface for visualization of the fine-scale genetic structure of the Han Chinese population; (ii) genome-wide allele frequencies of hierarchical sub-populations; (iii) ancestry inference for individual samples and controlling population stratification based on nested ancestry informative markers (AIMs) panels; (iv) population-structure-aware shared control data for genotype-phenotype association studies (e.g. GWASs) and (v) a Han-Chinese-specific reference panel for genotype imputation. Computational tools are implemented into the PGG.Han, and an online user-friendly interface is provided for data analysis and results visualization. The PGG.Han database is freely accessible via http://www.pgghan.org or https://www.hanchinesegenomes.org.

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

It's widely appreciated that liquid–liquid phase separation (LLPS) underlies the formation of membraneless organelles, which function to concentrate proteins and nucleic acids. In the past few decades, major efforts have been devoted to identify the phase separation associated proteins and elucidate their functions. To better utilize the knowledge dispersed in published literature, we developed PhaSepDB (http://db.phasep.pro/), a manually curated database of phase separation associated proteins. Currently, PhaSepDB includes 2914 non-redundant proteins localized in different organelles curated from published literature and database. PhaSepDB provides protein summary, publication reference and sequence features of phase separation associated proteins. The sequence features which reflect the LLPS behavior are also available for other human protein candidates. The online database provides a convenient interface for the research community to easily browse, search and download phase separation associated proteins. As a centralized resource, we believe PhaSepDB will facilitate the future study of phase separation.

The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages—the PDBe-KB aggregated views of structure data—which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession.

The ‘Genus for biomolecules’ database (http://genus.fuw.edu.pl) collects information about topological structure and complexity of proteins and RNA chains, which is captured by the genus of a given chain and its subchains. For each biomolecule, this information is shown in the form of a genus trace plot, as well as a genus matrix diagram. We assemble such information for all and RNA structures deposited in the Protein Data Bank (PDB). This database presents also various statistics and extensive information about the biological function of the analyzed biomolecules. The database is regularly self-updating, once new structures are deposited in the PDB. Moreover, users can analyze their own structures.