cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/102404
title: Supporting data for "KGML-xDTD: A Knowledge Graph-based Machine Learning Framework for Drug Treatment Prediction and Mechanism Description"

description: Computational drug repurposing is a cost- and time-efficient approach that aims to identify new therapeutic targets or diseases (indications) of existing drugs/compounds. It is especially critical for emerging and/or orphan diseases due to its cheaper investment and shorter research cycle compared with traditional wet-lab drug discovery approaches. However, the underlying mechanisms of action (MOAs) between repurposed drugs and their target diseases remain largely unknown, which is still a main obstacle for computational drug repurposing methods to be widely adopted in clinical settings. <br>In this work, we propose KGML-xDTD: a Knowledge Graph-based Machine Learning framework for explainably predicting Drugs Treating Diseases. It is a two-module framework that not only predicts the treatment probabilities between drugs/compounds and diseases but also biologically explains them via knowledge graph (KG) path-based, testable mechanisms of action (MOAs). We leverage knowledge-and-publication based information to extract biologically meaningful "demonstration paths" as the intermediate guidance in the Graph-based Reinforcement Learning (GRL) path-finding process. Comprehensive experiments and case study analyses show that the proposed framework can achieve state-of-the-art performance in both predictions of drug repurposing and recapitulation of human-curated drug MOA paths. <br> KGML-xDTD is the first model framework that can offer KG-path explanations for drug repurposing predictions by leveraging the combination of prediction outcomes and existing biological knowledge and publications. We believe it can effectively reduce "black-box" concerns and increase prediction confidence for drug repurposing based on predicted path-based explanations, and further accelerate the process of drug discovery for emerging diseases.
DOI: 10.5524/102408
title: Supporting data for "Metaphor - A workflow for streamlined assembly and binning of metagenomes"

description: Recent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyse genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customisable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly - combining the short input reads into longer, contiguous fragments (contigs), and binning - clustering these contigs into individual genome bins. The limitations of assembly and binning algorithms also pose different challenges depending on the selected strategy to execute them. Both of these processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully-automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data, and by combining multiple binning algorithms with a bin refinement step to achieve high quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets, and the impact of available assembly and binning strategies on the final results.
DOI: 10.5524/102410
title: Supporting data for "The genome assembly and annotation of the <i>Bungarus multicinctus</i>"

description: Snakes are one of the most important wildlife resources and are widely distributed. <i>Bungarus multicinctus</i> is a highly venomous snake and is distributed in central and southern China. In recent years, venomous snake bites have gradually increased. Genomic resources are significant for understanding the evolution of a species and the molecular mechanisms of toxin production. So far, the genomic resources of snakes are a rarity. In 2021 we collected a snake sample in Beiliu Longgukeng, Guangxi, which was identified as <i>Bungarus multicinctus</i> by morphological identification. Here, we present a highly contiguous <i>B. multicinctus</i> genome with a genome size of 1.51Gb. The repeat content in the genome is 40.15%, and the total length is more than 620Mb. A total of 24,869 functional genes were annotated. This study is of great significance for understanding the evolution of <i>B. multicinctus</i>, and also provides a molecular basis for the genes of the venom glands.
DOI: 10.5524/102412
title: Supporting data for "Genome resequencing reveals independent domestication and breeding improvement of naked oat"

description: As an important cereal crop, common oat has attracted more and more attention due to its healthy nutritional components and bioactive compounds. Here, high-depth resequencing of 115 oat accessions and closely related hexaploid species worldwide was performed. Based on genetic diversity and linkage disequilibrium analysis, it was found that hulled oat (<i>Avena sativa</i>) experienced a more severe bottleneck than naked oat (<i>Avena sativa</i> var. nuda). Combined with the divergence time of ~51,200 years ago, the previous speculation that naked oat was a variant of hulled oat was rejected. It was found that the common segments that hulled oat introgressed to naked oat cultivars contained 444 genes, mainly enriched in photosynthetic efficiency-related pathways. Selective sweeps during environmental adaptation and breeding improvement were identified in the naked oat genome. Candidate genes associated with smut resistance and the days to maturity phenotype were also identified. Our study provides genomic resources and new insights into naked oat domestication and breeding.
DOI: 10.5524/102413
title: Supporting data for "Haplogenome assembly reveals interspecific structural variation in Eucalyptus hybrids"

description: <i>De novo</i> phased (haplo)genome assembly using long-read DNA sequencing data has improved the detection and characterization of structural variants (SVs) in plant and animal genomes. Able to span across haplotypes, longreads allow phased, haplogenome assembly in highly outbred organisms such as forest trees. <i>Eucalyptus</i> tree species and interspecific hybrids are the most widely planted hardwood trees with F1 hybrids of <i>Eucalyptus grandis</i> and <i>Eucalyptus urophylla</i> forming the bulk of fast-growing pulpwood plantations in subtropical regions. The extent of structural variation and its effect on interspecific hybridization is unknown in these trees. As a first step towards elucidating the extent of structural variation between the genomes of <i>E.grandis</i> and <i>E. urophylla</i>, we sequenced and assembled the haplogenomes contained inan F1 hybrid of the two species. <br>Using Nanopore sequencing and a trio-binning approach, we assembled the separate haplogenomes (567 Mb and 545 Mb) to 97.9% BUSCO completion. High-density SNP genetic linkage maps of both parents allowed scaffolding of 88% of the haplogenome contigs into 11 pseudo-chromosomes (scaffold N50 of 43.82Mb and 42.45 Mb for the <i>E. grandis</i> and <i>E. urophylla</i> haplogenomes, respectively). We identify 48,729 SVs between the two haplogenomes providing the first detailed insight into genome structural rearrangement in these species. The two haplogenomes have similar gene content, 35,572 and 33,915 functionally annotated genes, of which 34% are contained in genome rearrangements. <br>Knowledge of SV and haplotype diversity in the two species will form the basis for understanding the genetic basis of hybrid superiority in these trees.
DOI: 10.5524/102415
title: Supporting data for "Genome assembly of the hybrid grapevine <i>Vitis</i> ‘Chambourcin’"

description: Chambourcin is a French-American interspecific hybrid grape grown in the eastern and midwestern United States and used for making wine. Few genomic resources are available for hybrid grapevines like Chambourcin. Here, we assembled the genome of Chambourcin using PacBio HiFi long-read, Bionano optical map, and Illumina short-read sequencing technologies. We generated an assembly for Chambourcin with 26 scaffolds, with an N50 length of 23.3 Mb and an estimated BUSCO completeness of 97.9%. We predicted 33,791 gene models and identified 16,056 common orthologs between Chambourcin, <i>V. vinifera</i> PN40024 12X.v2, VCOST.v3, Shine Muscat and <i>V. riparia</i> Gloire. We found 1,606 plant transcription factors from 58 gene families. Finally, we identified 304,571 simple sequence repeats (up to six base pairs long). Our work provides the genome assembly, annotation and the protein and coding sequences of Chambourcin. Our genome assembly is a valuable resource for genome comparisons, functional genomic analyses and genome-assisted breeding research.
DOI: 10.5524/102417
title: Supporting data for "Genomic analyses provide insights into the evolution and salinity adaptation of halophyte Tamarix chinensis"

description: The woody halophyte <i>Tamarix chinensis</i> is a pioneer tree species in the coastal wetland ecosystem of Northern China, exhibiting high resistance to salt stress. However, the genetic information underlying salt tolerance in <i>T. chinensis</i> remains to be seen. Here we present a genomic investigation of <i>T. chinensis</i> to elucidate the underlying mechanism of its high resistance to salinity. <br>Using a combination of PacBio and high-throughput chromosome conformation capture data, a chromosome-level <i>T. chinensis</i> genome was assembled with a size of 1.32 Gb and scaffold N50 of 110.03 Mb. Genome evolution analyses revealed that <i>T. chinensis</i> significantly expanded families of <i>HAT</i> and <i>LIMYB</i> genes. Whole-genome and tandem duplications contributed to the expansion of genes associated with the salinity adaptation of <i>T. chinensis</i>. Transcriptome analyses were performed on root and shoot tissues during salt stress and recovery, and several hub genes responding to salt stress were identified. <i>WRKY33/40, MPK3/4</i>, and <i>XBAT31</i> were critical in responding to salt stress during early exposure, while <i>WRKY40, ZAT10, AHK4, IRX9</i>, and <i>CESA4/8</i> were involved in responding to salt stress during late stress and recovery. In addition, <i>PER7/27/57/73</i> encoding class III peroxidase and <i>MCM3/4/5/7</i> encoding DNA replication licensing factor maintained up/downregulation during salt stress and recovery stages. <br>The results presented here reveal the genetic mechanisms underlying salt adaptation in <i>T. chinensis</i>, thus providing important genomic resources for evolutionary studies on tamarisk and plant salt tolerance genetic improvement.
DOI: 10.5524/102418
title: Supporting data for "Suggesting disease associations for overlooked metabolites using literature from metabolic neighbours"

description: In human health research, metabolic signatures extracted from metabolomics data are a strong-added value for stratifying patients and identifying biomarkers. Nevertheless, one of the main challenges is to interpret and relate these lists of discriminant metabolites to pathological mechanisms. This task requires experts to combine their knowledge with information extracted from databases and scientific literature. However, we show that the vast majority of compounds (&gt; 99%) in the PubChem database lack annotated literature. This dearth of available information can have a direct impact on the interpretation of metabolic signatures, which is often restricted to a subset of significant metabolites. To suggest potential pathological phenotypes related to these overlooked metabolites which lack annotated literature, we extend the guilt by association principle to literature information by using a Bayesian framework. The underlying assumption is that the literature associated with the metabolic neighbours of a compound can provide valuable insights, or an <i>a prior</i>, into its biomedical context. The metabolic neighbourhood of a compound can be defined from a metabolic network and correspond to metabolites to which it is connected through biochemical reactions. With the proposed approach, we suggest more than 35,000 associations between 1,047 overlooked metabolites and 3,288 diseases (or disease families). All these newly inferred associations are freely available on the FORUM FTP server (See information at https://github.com/eMetaboHUB/Forum-LiteraturePropagation).
DOI: 10.5524/102419
title: Supporting data for "Ontology-Driven Analysis of Marine Metagenomics: What More Can We Learn from Our Data?"

description: The proliferation of metagenomic sequencing technologies have enabled novel insights into the functional genomic potentials and taxonomic structure of microbial communities. However, cyberinfrastructure efforts to manage and enable the reproducible analysis of sequence data have not kept pace. Thus, there is increasing recognition of the need to make metagenomic data discoverable within machine searchable frameworks compliant with the FAIR principles for data stewardship. Although a variety of metagenomic web services exist, none currently leverage the hierarchically structured terminology encoded within common life-science ontologies to programmatically discover data. Here, we integrate large-scale marine metagenomic datasets with community-driven life-science ontologies into a novel FAIR web service. This approach enables the retrieval of data discovered by intersecting the knowledge represented within ontologies against the functional genomic potential and taxonomic structure computed from marine sequencing data. Our findings highlight various microbial functional and taxonomic patterns relevant to the ecology of prokaryotes in various aquatic environments. Most importantly, we present and evaluate a novel web service accessible through an open API that can be used to ask novel biological questions of existing metagenomic datasets. Finally, the FAIR ontology searchable data products provided by our API can be leveraged by future research efforts.
DOI: 10.5524/102423
title: Supporting data for "Computational prediction of human deep intronic variation"

description: The adoption of whole genome sequencing in genetic screens has facilitated the detection of genetic variation in the intronic regions of genes, far from annotated splice sites. However, selecting an appropriate computational tool to discriminate functionally relevant genetic variants from those with no effect is challenging, particularly for deep intronic regions where independent benchmarks are scarce. <br>In this study, we have provided an overview of the computational methods available and the extent to which they can be used to analyze deep intronic variation. We leveraged diverse datasets to extensively evaluate tool performance across different intronic regions, distinguishing between variants that are expected to disrupt splicing through different molecular mechanisms. Notably, we compared the performance of SpliceAI, a widely used sequence-based deep learning model, with that of more recent methods that extend its original implementation. We observed considerable differences in tool performance depending on the region considered, with variants generating cryptic splice sites being better predicted than those that potentially affect splicing regulatory elements. Finally, we devised a novel quantitative assessment of tool interpretability and found that tools providing mechanistic explanations of their predictions are often correct with respect to the ground truth information, but the use of these tools results in decreased predictive power when compared to black box methods.<br> Our findings translate into practical recommendations for tool usage and provide a reference framework for applying prediction tools in deep intronic regions, enabling more informed decision-making by practitioners.
DOI: 10.5524/102425
title: Supporting data for "Evaluating Long Read <i>De Novo</i> Assembly Tools for Eukaryotic Genomes: Insights and Considerations"

description: Assembly algorithm choice should be a deliberate, well-justified decision when researchers create genome assemblies for eukaryotic organisms from third-generation sequencing technologies. While third-generation sequencing by Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio) have overcome the disadvantages of short read lengths specific to next generation sequencing (NGS), third-generation sequencers are known to produce more error-prone reads, thereby generating a new set of challenges for assembly algorithms and pipelines. However, the introduction of HiFi reads, which offer substantially reduced error rates, has provided a promising solution for more accurate assembly outcomes. Since the introduction of third-generation sequencing technologies, many tools have been developed that aim to take advantage of the longer reads, and researchers need to choose the correct assembler for their projects.<br>We benchmarked state-of-the-art long-read <i>de novo</i> assemblers, to help readers make a balanced choice for the assembly of eukaryotes. To this end, we used 12 real and 64 simulated datasets from different eukaryotic genomes, with different read length distributions, imitating PacBio CLR, PacBio HiFi, and ONT sequencing to evaluate the assemblers. We include five commonly used long read assemblers in our benchmark: Canu, Flye, Miniasm, Raven, and wtdbg2 for ONT and PacBio CLR reads. For PacBio HiFi reads LJA, we include five state-of-the-art HiFi assemblers: HiCanu, Flye, Hifiasm, LJA and MBG. Evaluation categories address the following metrics: reference-based metrics, assembly statistics, misassembly count, BUSCO completeness, runtime, and RAM usage. Additionally, we investigated the effect of increased read length on the quality of the assemblies, and report that read length can, but does not always, positively impact assembly quality.<br> Our benchmark concludes that there is no assembler that performs the best in all the evaluation categories. However, our results show that overall Flye is the best-performing assembler for PacBio CLR and ONT reads, both on real and simulated data. Meanwhile, best performing PacBio HiFi assemblers are Hifiasm, and LJA. Next, the benchmarking using longer reads shows that the increased read length improves assembly quality, but the extent to which that can be achieved depends on the size and complexity of the reference genome.
DOI: 10.5524/102427
title: Supporting data for "Allele-specific regulatory effects on the pig transcriptome"

description: Allele-specific expression (ASE) refers to the preferential expression of one allele over the other and contributes to adaptive phenotypic plasticity. Here, we used a reciprocal cross model between phenotypically divergent European Berkshire and Asian Tibetan pigs to characterize two ASE classes: imprinting (i.e., the unequal expression between parental alleles) and sequence-dependent (i.e., unequal expression between breed-specific alleles). We examined three transcript types, including protein-coding genes (PCGs), long non-coding RNAs (lncRNAs) and transcripts of unknown coding potential (TUCPs) across seven representative somatic tissues from hybrid pigs generated by reciprocal crosses. <br>We identified a total of 92 putative imprinted transcripts, 69 (75.00%) of which are described here for the first time. By combining the transcriptome from purebred Berkshire and Tibetan pigs, we found ~6.59% of PCGs are differentially expressed between breeds that are regulated by <i>trans</i><em>&gt;-</em>elements (e.g., transcriptional factors) while only ~1.35% are attributable to <i>cis</i> (e.g., promoters)<em>. </em>The higher prevalence of <i>trans</i><em>-</em>PCGs indicate the dominated effects of <i>trans</i>-regulation in driving expression differences and shaping adaptive phenotypic plasticity between breeds, which were supported by functional enrichment analysis. We also found strong evidence that expression changes mediated by <i>cis</i><em>-</em>effects were associated with accumulated variants in promotes. <br>Our study provides a comprehensive map of expression regulation that constitutes a valuable resource for the agricultural improvement of pig breeds.
DOI: 10.5524/102429
title: Supporting data for "Integrating deep mutational scanning and low-throughput mutagenesis data to predict the impact of amino acid variants"

description: Evaluating the impact of amino acid variants has been a critical challenge for studying protein function and interpreting genomic data. High-throughput experimental methods like deep mutational scanning (DMS) can measure the effect of large numbers of variants in a target protein, but because DMS studies have not been performed on all proteins, researchers also model DMS data computationally to estimate variant impacts by predictors. <br>In this study, we extended a linear regression-based predictor to explore whether incorporating data from alanine scanning (AS), a widely used low-throughput mutagenesis method, would improve prediction results. To evaluate our model, we collected 146 AS datasets, mapping to 54 DMS datasets across 22 distinct proteins. <br>We show that improved model performance depends on the compatibility of the DMS and AS assays, and the scale of improvement is closely related to the correlation between DMS and AS results.
DOI: 10.5524/102431
title: Supporting data for "Diaci v3.0: Chromosome-level assembly, de novo transcriptome and manual annotation of Diaphorina citri, insect vector of Huanglongbing"

description: <i>Diaphorina citri</i> is a vector of <i>Candidatus</i> Liberibacter asiaticus (<i>C</i>Las), the gram-negative bacterial pathogen associated with citrus greening disease. Control measures rely on pesticides with negative impacts on the environment, natural ecosystems and human and animal health. In contrast, gene-targeting methods have the potential to specifically target the vector species and/or reduce pathogen transmission. <br>To improve the genomic resources needed for targeted pest control, we assembled a <i>D. citri</i> genome based on PacBio long reads followed by proximity ligation-based scaffolding. The 474 Mb genome has 13 chromosomal-length scaffolds. 1,036 genes were manually curated as part of a community annotation project, composed primarily of undergraduate students. We also computationally identified a total of 1,015 putative transcription factors (TFs) and were able to infer motifs for 337 TFs (33 %). In addition, we produced a genome-independent transcriptome and genomes for <i>D. citri</i> endosymbionts.<br>Manual annotation provided more accurate gene models for use by researchers and also provided an excellent training opportunity for students from multiple institutions. All resources are available on CitrusGreening.org and NCBI. The chromosomal-length <i>D. citri</i> genome assembly serves as a blueprint for the development of collaborative genomics projects for other medically and agriculturally significant insect vectors.