In interphase, the human genome sequence folds in three dimensions into a rich variety of locus-specific contact patterns. Cohesin and CTCF (CCCTC-binding factor) are key regulators; perturbing the ...levels of either greatly disrupts genome-wide folding as assayed by chromosome conformation capture methods. Still, how a given DNA sequence encodes a particular locus-specific folding pattern remains unknown. Here we present a convolutional neural network, Akita, that accurately predicts genome folding from DNA sequence alone. Representations learned by Akita underscore the importance of an orientation-specific grammar for CTCF binding sites. Akita learns predictive nucleotide-level features of genome folding, revealing effects of nucleotides beyond the core CTCF motif. Once trained, Akita enables rapid in silico predictions. Accounting for this, we demonstrate how Akita can be used to perform in silico saturation mutagenesis, interpret eQTLs, make predictions for structural variants and probe species-specific genome folding. Collectively, these results enable decoding genome function from sequence through structure.
We report a multi-omic resource generated by applying quantitative trait locus (xQTL) analyses to RNA sequence, DNA methylation and histone acetylation data from the dorsolateral prefrontal cortex of ...411 older adults who have all three data types. We identify SNPs significantly associated with gene expression, DNA methylation and histone modification levels. Many of these SNPs influence multiple molecular features, and we demonstrate that SNP effects on RNA expression are fully mediated by epigenetic features in 9% of these loci. Further, we illustrate the utility of our new resource, xQTL Serve, by using it to prioritize the cell type(s) most affected by an xQTL. We also reanalyze published genome wide association studies using an xQTL-weighted analysis approach and identify 18 new schizophrenia and 2 new bipolar susceptibility variants, which is more than double the number of loci that can be discovered with a larger blood-based expression eQTL resource.
There are no known specific therapies or vaccines to treat or prevent Zika virus infection. In this report, encouraging data are presented from a phase 1 study of a DNA vaccine against ZIKV infection.
Abstract
In this study, we propose iDNA-ABF, a multi-scale deep biological language learning model that enables the interpretable prediction of DNA methylations based on genomic sequences only. ...Benchmarking comparisons show that our iDNA-ABF outperforms state-of-the-art methods for different methylation predictions. Importantly, we show the power of deep language learning in capturing both sequential and functional semantics information from background genomes. Moreover, by integrating the interpretable analysis mechanism, we well explain what the model learns, helping us build the mapping from the discovery of important sequential determinants to the in-depth analysis of their biological functions.
The simultaneous live-cell imaging of multiple intracellular and disease-related microRNAs (miRNAs) with low abundances is highly important to enhance specificity and accuracy for disease diagnosis. ...On the basis of the improved cell internalization and accelerated reaction kinetics, we develop a three-dimensional (3D) DNA nanoprobe that integrates intramolecular DNAzyme (intra-Dz) and catalytic hairpin assembly (intra-CHA) amplifications to simultaneously monitor multiple miRNAs in living cells. The sensing components are loaded on a DNA scaffold via the sticky-end hybridization of the DNA sequences to increase the local concentrations of the signal probes. The miRNA-21 and miRNA-155 target sequences can trigger intra-Dz and -CHA amplifications on the nanoprobes to show significantly amplified and distinct fluorescence at different wavelengths for simultaneously monitoring low levels of miRNAs. Real-time fluorescence microscopy reveals that such a 3D DNA nanoprobe design with the intra-Dz and -CHA amplifications can accelerate the reaction rate compared to that of the conventional free Dz and CHA because of the increased local concentrations of the sensing components. Importantly, the 3D DNA nanoprobe has desirable stability and biocompatibility and can be readily delivered into living cells to achieve multiplexed and highly sensitive sensing of intracellular miRNA-155 and miRNA-21 sequences. With the demonstration of its intracellular application, the developed 3D DNA nanoprobe thus holds promising potential for biological studies and accurate disease diagnosis.
Transfer RNA (tRNA)-derived small RNAs (tsRNAs) are among the most ancient small RNAs in all domains of life and are generated by the cleavage of tRNAs. Emerging studies have begun to reveal the ...versatile roles of tsRNAs in fundamental biological processes, including gene silencing, ribosome biogenesis, retrotransposition, and epigenetic inheritance, which are rooted in tsRNA sequence conservation, RNA modifications, and protein-binding abilities. We summarize the mechanisms of tsRNA biogenesis and the impact of RNA modifications, and propose how thinking of tsRNA functionality from an evolutionary perspective urges the expansion of tsRNA research into a wider spectrum, including cross-tissue/cross-species regulation and harnessing of the 'tsRNA code' for precision medicine.
tRNA-derived small RNAs (tsRNAs) are present across all three domains of life: Archaea, Bacteria, and Eukarya.The biogenesis of tsRNAs involves specific cleavage of mature tRNAs or tRNA precursors at preferred loci followed by further processing.RNA modifications are essential for both tsRNA biogenesis and functionality.tsRNA functionality is intricately linked to basic life elements including the ribosomal machinery and viral replication, in addition to binding to ribonucleoprotein and Argonaute proteins (i.e., AGO and PIWI).tsRNAs can move across tissues/cells and may mediate intergenerational phenotype transmission and pathogen–host interplay and symbiosis.tsRNAs and their RNA modifications can serve as disease biomarkers.
True fungi (Fungi) and fungus-like organisms (e.g. Mycetozoa, Oomycota) constitute the second largest group of organisms based on global richness estimates, with around 3 million predicted species. ...Compared to plants and animals, fungi have simple body plans with often morphologically and ecologically obscure structures. This poses challenges for accurate and precise identifications. Here we provide a conceptual framework for the identification of fungi, encouraging the approach of integrative (polyphasic) taxonomy for species delimitation, i.e. the combination of genealogy (phylogeny), phenotype (including autecology), and reproductive biology (when feasible). This allows objective evaluation of diagnostic characters, either phenotypic or molecular or both. Verification of identifications is crucial but often neglected. Because of clade-specific evolutionary histories, there is currently no single tool for the identification of fungi, although DNA barcoding using the internal transcribed spacer (ITS) remains a first diagnosis, particularly in metabarcoding studies. Secondary DNA barcodes are increasingly implemented for groups where ITS does not provide sufficient precision. Issues of pairwise sequence similarity-based identifications and OTU clustering are discussed, and multiple sequence alignment-based phylogenetic approaches with subsequent verification are recommended as more accurate alternatives. In metabarcoding approaches, the trade-off between speed and accuracy and precision of molecular identifications must be carefully considered. Intragenomic variation of the ITS and other barcoding markers should be properly documented, as phylotype diversity is not necessarily a proxy of species richness. Important strategies to improve molecular identification of fungi are: (1) broadly document intraspecific and intragenomic variation of barcoding markers; (2) substantially expand sequence repositories, focusing on undersampled clades and missing taxa; (3) improve curation of sequence labels in primary repositories and substantially increase the number of sequences based on verified material; (4) link sequence data to digital information of voucher specimens including imagery. In parallel, technological improvements to genome sequencing offer promising alternatives to DNA barcoding in the future. Despite the prevalence of DNA-based fungal taxonomy, phenotype-based approaches remain an important strategy to catalog the global diversity of fungi and establish initial species hypotheses.
Vertebrate genomes exhibit marked CG suppression-that is, lower than expected numbers of 5'-CG-3' dinucleotides. This feature is likely to be due to C-to-T mutations that have accumulated over ...hundreds of millions of years, driven by CG-specific DNA methyl transferases and spontaneous methyl-cytosine deamination. Many RNA viruses of vertebrates that are not substrates for DNA methyl transferases mimic the CG suppression of their hosts. This property of viral genomes is unexplained. Here we show, using synonymous mutagenesis, that CG suppression is essential for HIV-1 replication. The deleterious effect of CG dinucleotides on HIV-1 replication was cumulative, associated with cytoplasmic RNA depletion, and was exerted by CG dinucleotides in both translated and non-translated exonic RNA sequences. A focused screen using small inhibitory RNAs revealed that zinc-finger antiviral protein (ZAP) inhibited virion production by cells infected with CG-enriched HIV-1. Crucially, HIV-1 mutants containing segments whose CG content mimicked random nucleotide sequence were defective in unmanipulated cells, but replicated normally in ZAP-deficient cells. Crosslinking-immunoprecipitation-sequencing assays demonstrated that ZAP binds directly and selectively to RNA sequences containing CG dinucleotides. These findings suggest that ZAP exploits host CG suppression to identify non-self RNA. The dinucleotide composition of HIV-1, and perhaps other RNA viruses, appears to have adapted to evade this host defence.
Multiple methods have been developed to estimate narrow-sense heritability, h
, using single nucleotide polymorphisms (SNPs) in unrelated individuals. However, a comprehensive evaluation of these ...methods has not yet been performed, leading to confusion and discrepancy in the literature. We present the most thorough and realistic comparison of these methods to date. We used thousands of real whole-genome sequences to simulate phenotypes under varying genetic architectures and confounding variables, and we used array, imputed, or whole genome sequence SNPs to obtain 'SNP-heritability' estimates. We show that SNP-heritability can be highly sensitive to assumptions about the frequencies, effect sizes, and levels of linkage disequilibrium of underlying causal variants, but that methods that bin SNPs according to minor allele frequency and linkage disequilibrium are less sensitive to these assumptions across a wide range of genetic architectures and possible confounding factors. These findings provide guidance for best practices and proper interpretation of published estimates.
Structural variants (SVs) can contribute to oncogenesis through a variety of mechanisms. Despite their importance, the identification of SVs in cancer genomes remains challenging. Here, we present a ...framework that integrates optical mapping, high-throughput chromosome conformation capture (Hi-C), and whole-genome sequencing to systematically detect SVs in a variety of normal or cancer samples and cell lines. We identify the unique strengths of each method and demonstrate that only integrative approaches can comprehensively identify SVs in the genome. By combining Hi-C and optical mapping, we resolve complex SVs and phase multiple SV events to a single haplotype. Furthermore, we observe widespread structural variation events affecting the functions of noncoding sequences, including the deletion of distal regulatory sequences, alteration of DNA replication timing, and the creation of novel three-dimensional chromatin structural domains. Our results indicate that noncoding SVs may be underappreciated mutational drivers in cancer genomes.
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