cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/102490
title: Supporting data for "Chromosome-level genome of the poultry shaft louse <i>Menopon gallinae</i> provides insight into the host-switching and adaptive evolution of parasitic lice"

description: Lice (Psocodea: Phthiraptera) are one important group of parasites that infects birds and mammals. It is believed that the ancestor of parasitic lice originated on the ancient avian host and ancient mammals acquired these parasites via host-switching from birds. Here we present the first chromosome-level genome of <i>Menopon gallinae</i> in Amblycera (earliest diverging lineage of parasitic lice). We explore the transition of louse host-switching from birds to mammals at the genomic level by identifying numerous idiosyncratic genomic variations. <br>The assembled genome is 155 Mb in length, with a contig N50 of 27.42 Mb. Hi-C scaffolding assigned 97% of the bases to five chromosomes. The genome of <i>M. gallinae</i> retains a basal insect repertoire of 11,950 protein-coding genes. By comparing the genomes of lice to those of multiple representative insects in other orders, we discovered that gene families of digestion, detoxification and immunity-related are generally conserved between bird lice and mammal lice, while mammal lice have undergone a significant reduction in genes related to chemosensory and temperature. This suggests that mammal lice have lost some of these genes through the adaption to environment and temperatures after host-switching. Furthermore, seven genes related to hematophagy were positively selected in mammal lice, suggesting their involvement in the hematophagous behavior.<br>Our high-quality genome of <i>M. gallinae</i> provides a valuable resource for comparative genomic research in Phthiraptera and facilitates further studies on adaptive evolution of host-switching within parasitic lice.
DOI: 10.5524/102492
title: Supporting data for "The genome assembly and annotation of the White-Lipped Tree viper <i>Trimeresurus albolabris</i>"

description: <i>Trimeresurus albolabris</i>, also known as the white-lipped pit viper or white-lipped tree viper, is a highly venomous snake distributed across Southeast Asia and the cause of many snakebite cases. In this study, we report the first whole genome assembly of <i>T. albolabris</i> obtained with next-generation sequencing from a specimen collected in Mengzi, Yunnan, China. After genome sequencing and assembly, the genome of this male <i>T. albolabris</i> individual was 1.51 Gb in length and included 38.42% repeat-element content. Using this genome, 21,695 genes were identified, and 99.17% of genes could be annotated using gene functional databases. Nuclear genome single-copy genes phylogenetic tree including six species verified the validity of our genome assembly and annotation process. This research will contribute to future studies on <i>Trimeresurus</i> biology and the genetic basis of snake venom.
DOI: 10.5524/102494
title: Supporting data for "Multi-omic dataset of patient-derived tumor organoids of neuroendocrine neoplasms"

description: Organoids are three-dimensional experimental models that summarize the anatomical and functional structure of an organ. Although a promising experimental model for precision medicine, patient-derived tumor organoids (PDTOs) have currently been developed only for a fraction of tumor types. <br>We have generated the first multi-omic dataset (whole-genome sequencing, WGS, and RNA-sequencing, RNA-seq) of PDTOs from the rare and understudied pulmonary neuroendocrine tumors (n = 12; 6 grade 1, 6 grade 2), and provide data from other rare neuroendocrine neoplasms: small intestine (ileal) neuroendocrine tumors (n = 6; 2 grade 1 and 4 grade 2) and large-cell neuroendocrine carcinoma (n = 5; 1 pancreatic and 4 pulmonary). This dataset includes a matched sample from the parental sample (primary tumor or metastasis) for a majority of samples (21/23) and longitudinal sampling of the PDTOs (1 to 2 time-points), for a total of n = 47 RNA-seq and n = 33 WGS. We here provide quality control for each technique, and provide the raw and processed data as well as all scripts for genomic analyses to ensure an optimal re-use of the data. In addition, we report gene expression data and somatic small variant calls and describe how they were generated, in particular how we used WGS somatic calls to train a random-forest classifier to detect variants in tumor-only RNA-seq. We also report all histopathological images used for medical diagnosis: hematoxylin and eosin-stained slides, brightfield images, and immunohistochemistry images of protein markers of clinical relevance. <br>This dataset will be critical to future studies relying on this PDTO biobank, such as drug screens for novel therapies and experiments investigating the mechanisms of carcinogenesis in these understudied diseases.
DOI: 10.5524/102497
title: Supporting data for "Data processing solutions to render metabolomics more quantitative: case studies in food and clinical metabolomics using Metabox 2.0"

description: In classic semi-quantitative metabolomics, metabolite intensities are affected by biological factors and other unwanted variations. A systematic evaluation of the data processing methods is crucial to distinguish adequate processing procedures for a given experimental setup. Current comparative studies are mostly focused on peak area data, but not on absolute concentrations. In this study, we evaluated data processing methods to produce outputs that were most similar to the corresponding absolute quantified data. We examined the data distribution characteristics, fold difference patterns between two metabolites, and sample variance. We used two metabolomic data sets from a retail milk study and a lupus nephritis cohort as test cases. When studying the impact of data normalization, transformation, scaling, and combinations of these methods, we found that the cross-contribution compensating multiple standard normalization (ccmn) method, followed by square root data transformation, was most appropriate for a well-controlled study such as the milk study data set. Regarding the lupus nephritis cohort study, only ccmn normalization could slightly improve the data quality of the noisy cohort. Since the assessment accounted for the resemblance between processed data and the corresponding absolute quantified data, our results denote a helpful guideline for processing metabolomic data sets within a similar context (food and clinical metabolomics). Finally, Metabox 2.0 was introduced, which allows the thorough analysis of metabolomic data, including data processing, biomarker analysis, integrative analysis, and data interpretation. It was successfully used to process and analyze the data in this study. An online web version is available at http://metsysbio.com/metabox.
DOI: 10.5524/102498
title: Supporting data for "A Novel Variable Neighborhood Search Approach for Cell Clustering for Spatial Transcriptomics"

description: In addressing the evolving landscape of cell clustering methodologies, this paper unveils a pioneering strategy leveraging the Variable Neighborhood Search (VNS) metaheuristic. The motivation behind this exploration lies in the need to tackle the intricate task of clustering cells based on both gene expression and spatial coordinates. To present a comprehensive solution, we initially cast the cell clustering challenge as an Integer Linear Programming (ILP) minimization problem, harnessing the robust foundation of VNS. Our proposed approach introduces a novel model based on the VNS technique, demonstrating its efficacy in navigating the complexities inherent in cell clustering. Notably, our method transcends the confines of conventional cell type clustering, as evidenced by our initial results, extending its application to spatial domain clustering. This inherent adaptability enables our algorithm to orchestrate clusters based on information gleaned from both gene expression matrices and spatial coordinates. Validation through rigorous testing underscores the superior performance of our method when compared to existing techniques chronicled in the literature. In summary, our project not only advances the current progress of clustering methodologies but also holds immense potential for transformative applications across diverse fields, from biomedical research to spatial data analysis. The overall benefits of our approach underscore its capacity to significantly impact and propel scientific investigation forward.
DOI: 10.5524/102502
title: Supporting data for "Proteome-wide association study and functional validation identify novel protein markers for pancreatic ductal adenocarcinoma"

description: Pancreatic ductal adenocarcinoma (PDAC) remains a lethal malignancy, largely due to the paucity of reliable biomarkers for early detection and therapeutic targeting. Existing blood protein biomarkers for PDAC often suffer from replicability issues, arising from inherent limitations such as unmeasured confounding factors in conventional epidemiologic study designs. To circumvent these limitations, we use genetic instruments to identify proteins with genetically predicted levels to be associated with PDAC risk. Leveraging genome and plasma proteome data from the INTERVAL study, we established and validated models to predict protein levels using genetic variants. By examining 8,275 PDAC cases and 6,723 controls, we identified 40 associated proteins, of which 16 are novel. Functionally validating these candidates by focusing on two selected novel protein-encoding genes, <i>GOLM1</i> and <i>B4GALT1</i>, we demonstrated their pivotal roles in driving PDAC cell proliferation, migration, and invasion. Furthermore, we also identified potential drug repurposing opportunities for treating PDAC. <br>PDAC is a notoriously difficult-to-treat malignancy, and our limited understanding of causal protein markers hampers progress in developing effective early detection strategies and treatments. Our study identifies novel causal proteins using genetic instruments and subsequently functionally validates selected novel proteins. This dual approach enhances our understanding of PDAC etiology and potentially opens new avenues for therapeutic interventions.
DOI: 10.5524/102503
title: Supporting data for "Pangenome databases improve host removal and mycobacteria classification from clinical metagenomic data"

description: Culture-free real-time sequencing of clinical metagenomic samples promises both rapid pathogen detection and antimicrobial resistance profiling. However, this approach introduces the risk of patient DNA leakage. To mitigate this risk, we need near-comprehensive removal of human DNA sequences at the point of sequencing, typically involving the use of resource-constrained devices. Existing benchmarks have largely focused on the use of standardised databases and largely ignored the computational requirements of depletion pipelines as well as the impact of human genome diversity.<br>We benchmarked host removal pipelines on simulated and artificial real Illumina and Nanopore metagenomic samples. We found that construction of a custom kraken database containing diverse human genomes results in the best balance of accuracy and computational resource usage. In addition, we benchmarked pipelines using kraken and minimap2 for taxonomic classification of <i>Mycobacterium</i> reads using standard and custom databases. With a database representative of the <i>Mycobacterium</i> genus, both tools obtained improved specificity and sensitivity, compared to the standard databases for classification of <i>Mycobacterium tuberculosis</i>. Computational efficiency of these custom databases was superior to most standard approaches, allowing them to be executed on a laptop device.<br>Customised pangenome databases provide the best balance of accuracy and computational efficiency when compared to standard databases for the task of human read removal and M. tuberculosis read classification from metagenomic samples. Such databases allow for execution on a laptop, without sacrificing accuracy; an especially important consideration in low-resource settings. We make all customised databases and pipelines freely available.
DOI: 10.5524/102505
title: Supporting data for "Whole genome assembly and annotation of the King Angelfish (Holacanthus passer) gives insight into the evolution of marine fishes of the Tropical Eastern Pacific "

description: <i>Holacanthus</i> angelfishes are some of the most iconic marine fishes of the Tropical Eastern Pacific (TEP). However, very limited genomic resources currently exist for the genus. In this study we: i) assembled and annotated the nuclear genome of the King Angelfish (<i>Holacanthus passer</i>), and ii) examined the demographic history of <i>H. passer</i> in the TEP. We generated 43.8 Gb of ONT and 97.3 Gb Illumina reads representing 75X and 167X coverage, respectively. The final genome assembly size was 583 Mb with a contig N50 of 5.7 Mb, which captured 97.5% complete Actinoterygii Benchmarking Universal Single-Copy Orthologs (BUSCOs). Repetitive elements account for 5.09% of the genome, and 33,889 protein-coding genes were predicted, of which 22,984 have been functionally annotated. Our demographic model suggests that population expansions of <i>H. passer</i> occurred prior to the last glacial maximum (LGM) and were more likely shaped by events associated with the closure of the Isthmus of Panama. This result is surprising, given that most rapid population expansions in both freshwater and marine organisms have been reported to occur globally after the LGM. Overall, this annotated genome assembly will serve as a resource to improve our understanding of the evolution of <i>Holacanthus</i> angelfishes while facilitating novel research into local adaptation, speciation, and introgression in marine fishes.
DOI: 10.5524/102514
title: Supporting data for "Streamlining remote nanopore data access with slow5curl"

description: As adoption of nanopore sequencing technology continues to advance, the need to maintain large volumes of raw current signal data for reanalysis with updated algorithms is a growing challenge. Here we introduce slow5curl, a software package designed to streamline nanopore data sharing, accessibility and reanalysis. <i>Slow5curl</i> allows a user to fetch a specified read or group of reads from a raw nanopore dataset stored on a remote server, such as a public data repository, without downloading the entire file. <i>Slow5curl</i> uses an index to quickly fetch specific reads from a large dataset in SLOW5/BLOW5 format and highly parallelised data access requests to maximise download speeds. Using all public nanopore data from the Human Pangenome Reference Consortium (&gt;22 TB), we demonstrate how <i>Slow5curl</i> can be used to quickly fetch and reanalyse raw signal reads corresponding to a set of target genes from each individual in large cohort dataset (<i>n</i> = 91), minimising the time, egress costs, and local storage requirements for their reanalysis. We provide <i>Slow5curl</i> as a free, open-source package that will reduce frictions in data sharing for the nanopore community.
DOI: 10.5524/102515
title: Supporting data for "Generalized Open-Source Workflows for Atomistic Molecular Dynamics Simulations of Viral Helicases"

description: Viral helicases are promising targets for the development of antiviral therapies. Given their vital function of unwinding double stranded nucleic acids, inhibiting them blocks the viral replication cycle. Previous studies have elucidated key structural details of these helicases, including location of substrate binding sites, flexible domains, and the discovery of potential inhibitors. Here we present a series of new Galaxy tools and workflows for performing and analyzing molecular dynamics simulations of viral helicases. We first validate them by demonstrating recapitulation of data from previous simulations of Zika (NS3) and SARS-CoV-2 (NSP13) helicases in apo and complex with inhibitors. We further demonstrate the utility and generalizability of these Galaxy workflows by applying them to new cases, proving their usefulness as a widely accessible method for exploring antiviral activity.
DOI: 10.5524/102518
title: Supporting data for "Mechanisms of hepatic steatosis in chickens: integrated analysis of the host genome, molecular phenomes and gut microbiome"

description: Hepatic steatosis is the initial manifestation of abnormal liver functions and often leads to liver diseases such as non-alcoholic fatty liver disease in humans and fatty liver syndrome in animals. In this study, we conducted a comprehensive analysis of a large chicken population consisting of 705 adult hens by combining host genome resequencing, liver transcriptome, proteome, and metabolome analysis, as well as microbial 16S rRNA gene sequencing of each gut segment. The results showed the heritability (h2=0.25) and duodenal microbiability (m2=0.26) of hepatic steatosis were relatively high, indicating a large effect of host genetics and duodenal microbiota on chicken hepatic steatosis. Individuals with hepatic steatosis had low microbiota diversity and a decreased genetic potential to process triglyceride output from hepatocytes, fatty acid -oxidation activity, and resistance to fatty acid peroxidation. Furthermore, we revealed a molecular network linking host genomic variants (GGA6: 5.595.69 Mb), hepatic gene/protein expression (PEMT, phosphatidyl-ethanolamine N-methyltransferase), metabolite abundances (folate, S-adenosylmethionine, homocysteine, phosphatidyl-ethanolamine, and phosphatidylcholine) and duodenal microbes (genus Lactobacillus) to hepatic steatosis, which could provide new insights into the regulatory mechanism of fatty liver development.
DOI: 10.5524/102519
title: Supporting data for "Exploring polymorphic interspecies structural variants in Eucalyptus: Unravelling Their Role in Reproductive Isolation and Adaptive Divergence."

description: Structural variants (SVs) play a significant role in speciation and adaptation in many species, yet few studies have explored the prevalence and impact of different categories of SVs. We conducted a comparative analysis of long-read assembled reference genomes of closely related <i>Eucalyptus</i> species to identify candidate SVs potentially influencing speciation and adaptation. Interspecies SVs can be either fixed differences, or polymorphic in one or both species. To describe SV patterns, we employed short-read whole-genome sequencing on over 600 individuals of <i>E. melliodora</i> and <i>E. sideroxylon</i>, along with recent high quality genome assemblies. We aligned reads and genotyped interspecies SVs predicted between species reference genomes. Our results revealed that 49,756 of 58,025 and 39,536 of 47,064 interspecies SVs could be typed with short reads, in <i>E. melliodora</i> and <i>E. sideroxylon</i> respectively. Focusing on inversions and translocations, symmetric SVs which are readily genotyped within both populations, 24 were found to be structural divergences, 2,623 structural polymorphisms, and 928 shared structural polymorphisms. We assessed the functional significance of fixed interspecies SVs by examining differences in estimated recombination rates and genetic differentiation between species, revealing a complex history of natural selection. Shared structural polymorphisms displayed enrichment of potentially adaptive genes. Understanding how different classes of genetic mutations contribute to genetic diversity and reproductive barriers is essential for understanding how organisms enhance fitness, adapt to changing environments, and diversify. Our findings reveal the prevalence of interspecies SVs and elucidate their role in genetic differentiation, adaptive evolution, and species divergence within and between populations.
DOI: 10.5524/102524
title: Supporting data for "LRTK: A platform agnostic toolkit for linked-read analysis of both human genomes and metagenomes"

description: Linked-read sequencing technologies generate high-base quality short-reads that contain extrapolative information on long-range DNA connectedness. These advantages of linked-read technologies are well-known and have been demonstrated in many human genomic and metagenomic studies. However, existing linked-read analysis pipelines (e.g., Long Ranger) were primarily developed to process sequencing data from the human genome and are not suited for analyzing metagenomic sequencing data. Moreover, linked-read analysis pipelines are typically limited to one specific sequencing platform. To address these limitations, we present the Linked-Read ToolKit (LRTK), a unified and versatile toolkit for platform agnostic processing of linked-read sequencing data from both human genome and metagenome. LRTK provides functions to perform linked-read simulation, barcode sequencing error correction, barcode-aware read alignment and metagenome assembly, reconstruction of long DNA fragments, taxonomic classification and quantification, as well as barcode-assisted genomic variant calling and phasing. LRTK has the ability to process multiple samples automatically, and provides users with the option to generate reproducible reports during processing of raw sequencing data and at multiple checkpoints throughout downstream analysis. We applied LRTK on linked-reads from simulation, mock community and real datasets for both human genome and metagenome. We showcased LRTKs ability to generate comparative performance results from preceding benchmark studies and to report these results in publication-ready HTML document plots. LRTK provides comprehensive and flexible modules along with an easy-to-use Python-based workflow for processing linked-read sequencing datasets, thereby filling the current gap in the field caused by platform-centric genome-specific linked-read data analysis tools.
DOI: 10.5524/102526
title: Supporting data for "The genomes of <i>Dahlia pinnata, Cosmos bipinnatus</i> and <i>Bidens alba</i> in tribe Coreopsideae provide insights into polyploid evolution and inulin biosynthesis"

description: The Coreopsideae tribe, a subset of the Asteraceae family, encompasses economically vital genera like Dahlia, Cosmos, and Bidens, which are widely employed in medicine, horticulture, ecology, and food applications. Nevertheless, the lack of reference genomes hinders evolutionary and biological investigations in this tribe. <br>Here, we present three haplotype-resolved chromosome-level reference genomes of the tribe Coreopsideae, including two famous flower plants <i>Dahlia pinnata</i> and <i>Cosmos bipinnatus</i>, and one invasive weed plant <i>Bidens alba</i>, with assembled genome sizes 3.93 G, 1.02 G and 1.87 G, respectively. We found that <i>Gypsy</i> transposable elements contribute mostly to the larger genome size of <i>D. pinnata</i>, and multiple chromosome rearrangements have occurred in tribe Coreopsideae. Besides the shared whole genome duplication (WGD-2) in the Heliantheae alliance, our analyses showed that <i>D. pinnata</i> and <i>B. alba</i> each underwent an independent recent WGD-3 event: in <i>D. pinnata</i> it is more likely to be a self-WGD, while in <i>B. alba</i> it is from the hybridization of two ancestor species. Further, we identified key genes in the inulin metabolic pathway, and found that the pseudogenization of <i>1-FEH1</i> and <i>1-FEH2</i> genes in <i>D. pinnata</i> and the deletion of three key residues of 1-FFT proteins in <i>C. bipinnatus</i> and <i>B. alba</i> may probably explain why <i>D. pinnata</i> produces much more inulin than the other two plants. <br>Collectively, the genomic resources for the Coreopsideae tribe will promote phylogenomics in Asteraceae plants, facilitate ornamental molecular breeding improvements and inulin production, and help prevent invasive weeds.