cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/102190
title: Genomic data of the kissing gourami, <i>Helostoma temminkii</i>

description: Kissing gourami, also known as kissing fish or kissers (<i>Helostoma temminkii</i>), are medium-sized tropical freshwater fish. They can be food fish which are farmed in their native Southeast Asia. Typical of gourami, the body is deep and strongly compressed laterally. The most distinctive feature of the kissing gourami is its mouth. Other than being terminal (forward-facing) rather than superior (upward-facing) as in other gourami families, the kissing gourami's mouth is highly protrusible as its family name suggests, the lips are lined with horny teeth. The visible scales of the body are ctenoid, whereas the scales of the top of the head are cycloid.<br>Kissing gourami reach a maximum of 30 cm (12 in) in total length. There is no outward sexual dimorphism and is difficult to almost impossible to distinguish the sexes. Two color morphs are encountered: greens, which have lengthwise lateral stripes and opaque, dark brown fins; and pink, which have a rose to orangy pink body and silvery scales, with transparent pinkish fins. <i>Helostoma teminkii</i> is an omnivorous microfagic filtering fish, whose nutrition is based on a wide variety of food sources, such as insects, algae, larvae from other species and other microorganisms found on submerged species. The mouth, teeth, gills and especially the intramedibular joint described above make this fish a very well adapted species: it is able to find nutrients in places where other species cannot be such as algal-covered surfaces. <br>Shallow, slow-moving, and thickly vegetated backwaters are the kissing gourami's natural habitat. They are midwater omnivores that primarily graze on benthic algae and aquatic plants, with insects taken from the surface. They are also filter feeders, using their use many gill rakers to supplement their diet with plankton. The fish use their toothed lips to rasp algae from stones and other surfaces. This rasping action, which (to humans) looks superficially like kissing, is also used by males to challenge the dominancy of conspecifics. <br>Spawning occurs from May to October in Thailand. Kissing gourami are open-water egg scatterers; spawning is initiated by the female and takes place under cover of floating vegetation. The eggs, which the adults do not guard, are spherical, smooth, and buoyant. Initial development is rapid: the eggs hatch after one day, and the fry are free-swimming two days thereafter. The kissing gourami does not care for its young. They are used fresh for steaming, baking, broiling, and pan frying. The kissing gourami is a popular aquarium fish. Here we present the genome, which has an estimated genome size of 729.7Mb, scaffold N50 913,351, contig N50 95,536
DOI: 10.5524/102192
title: Genomic data of the rosy bitterling, <i>Rhodeus ocellatus</i>

description: The rosy bitterling or Tairiku baratanago (<i>Rhodeus ocellatus</i>) is a small freshwater fish belonging to the family Cyprinidae (carp), native to East Asia from the Amur River basin to the Pearl River basin. Females are about 45 cm (1.62.0 in) long and males are 58 cm (2.03.1 in). Their bodies are flat with an argent-colored luster. However, males change to a reddish (sometimes purple) color during the spawning season (March to September) which functions to attract females. This reddish color is similar to the color of a red rose, which is why it is called a rosy bitterling. <br>Rosy bitterlings live in ponds (reservoirs) where freshwater mussels are abundant. Farm ponds are an important habitat for not only rosy bitterlings, but also mussels and plankton. Eggs grow in the mussels' gills and juveniles stay inside the mussel about 15 to 30 days after fertilization. Eggs hatch after about three days when juveniles are about 2.8 mm long. The body has a unique shape resembling the bud of a matsutake mushroom. Juveniles swim out of the mussel from the margin of the excurrent siphon. At this point, juveniles are about 7.5 mm long and about the same shape as adults.Usually, juveniles grow around 4050 mm within one year, when they become adults. Here we present the genome, which has an estimated genome size of 850.5Mb, scaffold N50 4,198,183, contig N50 4,198,183
DOI: 10.5524/102195
title: Supporting data for "Lessons learned about the biology and genomics of <i>Diaphorina citri</i> infection with “<i>Candidatus</i> Liberibacter asiaticus” by integrating new and archived organ-specific transcriptome data."

description: Huanglongbing (HLB), a devastating disease of citrus, is caused by the obligate, intracellular bacterium <i>Candidatus</i> Liberibacter asiaticus (<i>C</i>Las). <i>C</i>Las is transmitted by <i>Diaphorina citri</i>, the Asian citrus psyllid. Development of transmission-blocking strategies to manage HLB relies on knowledge of <i>C</i>Las-<i>D. citri</i> interactions at the molecular level. Prior transcriptome analyses of <i>D. citri</i> point to changes in psyllid biology due to <i>C</i>Las-infection but have been hampered by incomplete versions of the <i>D. citri</i> genome, proper host plant controls, and/or a lack of a uniform data analysis approach. Therefore, using the scaffold of the newest chromosomal length <i>D. citri</i> genome assembly, Diaci_v3.0, we computationally identified differentially expressed genes in both <i>C</i>Las (+) and <i>C</i>Las (-) <i>D. citri</i>. In this work, we present lessons learned from a quantitative transcriptome analysis of excised heads, salivary glands, midguts and bacteriomes from <i>C</i>Las (+) and <i>C</i>Las (-) insects. <br>Each organ had unique transcriptome profiles and responses to <i>C</i>Las infection. Though most psyllids were infected with <i>C</i>Las, <i>C</i>Las-derived transcripts were not detected in all organs. By analyzing the midgut dataset using both the Diaci_v1.1 and v3.0 <i>D. citri</i> genomes, we showed that improved genome assembly led to significant and quantifiable differences in RNAseq data interpretation. <br>Our results support the hypothesis that future transcriptome studies on circulative, vector-borne pathogens should be conducted at the tissue specific level using complete, chromosomal-length genome assemblies for the most accurate understanding of pathogen-induced changes in vector gene expression.
DOI: 10.5524/102197
title: Supporting data for "AMR-meta: ak-mer and metafeature approach to classify antimicrobial resistance from high-throughput short-read metagenomics data"

description: Antimicrobial resistance (AMR) is a global health concern. High-throughput metagenomic sequencing of microbial samples enables profiling of AMR genes through comparison with curated AMR databases. However, performance of current methods are often hampered by database incompleteness, and presence of homology/homoplasy with other non-AMR genes in sequenced samples. <br>We present AMR-meta, a database-free and alignment-free approach, based on k-mers, which combines algebraic matrix factorization into metafeatures with regularized regression. Metafeatures capture multi-level gene diversity across main antibiotic classes. AMR-meta takes in reads from metagenomic shotgun sequencing and outputs predictions about whether those reads contribute to resistance against specific classes of antibiotics. In addition, AMR-meta employs an augmented training strategy that joins an AMR gene database with non-AMR genes (used as negative examples). We compare AMR-meta with AMRPlusPlus, DeepARG, and Meta-MARC, further testing their ensemble via a voting system. In cross-validation, AMR-meta has a median (interquartile) f-score of 0.7 (0.2-0.9). On semi-synthetic metagenomic data external test on average AMR-meta yields a 1.3-fold hit rate increase over existing methods. In terms of run-time, AMR-meta is 3x faster than DeepARG and 30x faster than Meta-MARC, and as fast as AMRPlusPlus. Finally, we note that differences in AMR ontologies and observed variance of all tools in classification outputs call for further development on standardization of benchmarking data and protocols. <br>AMR-meta is a fast, accurate classifier that exploits non-AMR negative sets to improve sensitivity and specificity. The differences in AMR ontologies and the high variance of all tools in classification outputs call for the deployment of standard benchmarking data and protocols, to fairly compare AMR prediction tools.
DOI: 10.5524/102199
title: Supporting data for "A high-quality, long-read genome assembly of the endangered ring-tailed lemur (Lemur catta)"

description: The ring-tailed lemur (<i>Lemur catta</i>) is a charismatic strepsirrhine primate endemic to the island of Madagascar. These lemurs are of particular interest, given their status as a flagship species and widespread publicility in popular media. Unfortunately, a recent population decline has caused the census population to fall below 2500 individuals in the wild, and their classification as an endangered species by the IUCN. As is the case for most strepsirrhine primates, only a limited amount of genomic research has been conducted on <i>L. catta</i>, in part due to the lack of genomic resources. We generated a new high-quality reference genome assembly for <i>L. catta</i> (mLemCat1) that conforms to the standards of the Vertebrate Genomes Project. This new long-read assembly is composed of PacBio continuous long reads (CLR reads), Optical Mapping Bionano reads, Arima HiC data, and 10X linked-reads. The contiguity and completeness of the assembly is extremely high, with scaffold and contig N50 values of 90.982 Mbp and 10.570 Mbp, respectively. Additionally, when compared to other high-quality primate assemblies, <i>L. catta</i> has the lowest reported number of Alu elements, which results predominantly from a lack of AluS and AluY elements. mLemCat1 is an excellent genomic resource not only for the ring-tailed lemur community, but also for other members of the Lemuridae family and is the first very long read assembly for a strepsirrhine.
DOI: 10.5524/102200
title: Supporting data for "A chromosome-level genome assembly of <i>Artocarpus nanchuanensis</i> (Moraceae), an extremely endangered fruit tree"

description: <i>Artocarpus nanchuanensis</i> (Moraceae), which is naturally distributed in China, is a representative and extremely endangered tree species. In this study, we obtained a high-quality chromosome-scale genome assembly and annotation information for <i>A. nanchuanensis</i> using integrated approaches, including Illumina, Nanopore sequencing platform and Hi-C. A total of 128.71 gigabases (Gb) of raw Nanopore reads were generated from 20 kb libraries, and 123.38 Gb of clean reads were obtained after filtration with 160.34x coverage depth and a 17.48 kb average read length. The final assembled <i>A. nanchuanensis</i> genome was 769.44 Mb with a 2.09 Mb contig N50, and 99.62% (766.50 Mb) of the assembled data was assigned to 28 pseudochromosomes. 39,596 genes (95.10%, 39,596/41636) were successfully annotated, and 129 metabolic pathways were detected. Plants disease resistance/insect resistance genes, plant-pathogen interaction metabolic pathways, and abundant biosynthesis pathways of vitamins, flavonoid and gingerol were detected. Unigene reveals the basis of species-specific functions, and gene family in contraction and expansion generally implies strong functional differences in the evolution. Compared with other related species, a total of 512 unigenes, 309 gene families in contraction and 559 gene families in expansion were detected in <i>A. nanchuanensis</i>. This <i>A. nanchuanensis</i> genome information provides an important resource to expand our understanding of the unique biological processes, nutritional and medicinal benefits, and evolutionary relationship of this species. The study of gene function and metabolic pathway in <i>A. nanchuanensis</i> may reveal the theoretical basis of special trait in <i>A. nanchuanensis</i>, and promote the study and utilization of its rare medicinal value.
DOI: 10.5524/102204
title: Supporting data for "Sepsis-3 criteria in AmsterdamUMCdb: open-source code implementation"

description: Sepsis is a major healthcare problem with substantial mortality and a common reason for admission to the intensive care unit (ICU). For this reason, the management of sepsis is an important area of ICU research. A number of large-scale, freely-accessible ICU databases are available for observational research and the robust identification of septic patients in such data sets is crucial for research purposes, particularly for comparative studies between critical care sub-populations which may vary around the world. However, data structures are poorly standardised due to inevitable variances in clinical electronic health record system vendor and implementation as well as research database design choices. Robust and well-documented cohort selection (such as patients with sepsis) is crucial for reproducible research. In this work, we operationalise the Sepsis-3 definition on the AmsterdamUMCdb, a recently published large European ICU database, publishing open-access code for wider use by critical care researchers.
DOI: 10.5524/102206
title: Supporting data for "HaploMaker: An improved algorithm for rapid haplotype assembly of genomic sequences"

description: In diploid organisms, whole genome haplotype assembly relies on the accurate identification and assignment of heterozygous single nucleotide polymorphism (SNP) alleles to the correct homologous chromosomes. This appropriate phasing of the alleles ensures combinations of SNPs on any chromosome, called haplotypes, can then be used in down-stream genetic analyses approaches including determining their potential association with important phenotypic traits. A number of statistical algorithms and complementary computational software tools have been developed for whole genome haplotype construction from genomic sequence data. However, many algorithms lack the ability to phase long haplotype blocks and simultaneously achieve a competitive accuracy. <br>In this research we present HaploMakerr, a novel reference-based haplotype assembly algorithm capable of accurately and efficiently phasing long haplotypes using paired-end short reads and longer PacBio reads from diploid genomic sequences. To achieve this we frame the problem as a directed acyclic graph with edges weighted on read evidence and use efficient path traversal and minimization techniques to optimally phase haplotypes. We compared the HaploMaker algorithm with three other common reference-based haplotype assembly tools using public haplotype data of human individuals from the Platinum Genome project. With short read sequences, the HaploMaker algorithm maintained a competitively low switch error rate across all haplotype lengths and was found to be superior in phasing longer genomic regions. For longer PacBio reads, HaploMaker remained competitive for small block lengths and managed to generate longer block lengths than the competing algorithms. <br>HaploMaker provides an improved haplotype assembly algorithm for diploid genomic sequences by accurately phasing longer haplotypes. The computationally efficient and portable nature of the Java implementation of the algorithm will ensure it has maximal impact in reference-sequence based haplotype assembly applications
DOI: 10.5524/102210
title: Supporting data for "Chromosome‐level genome assembly of the black widow spider Latrodectus elegans illuminates composition and evolution of venom and silk proteins"

description: Black widow spider has both extraordinarily neurotoxic venom and three-dimensional cob-webs composing of diverse types of silk. However, high-quality reference genome for black widow spider was unavailable, which hindered deep understanding and application of the valuable biomass. <br>We assembled the <i>L. elegans</i> genome using Nanopore long-reads. The genome size is 1.57 Gb with contig N50 of 4.34Mb and scaffold N50 of 114.31 Mb. Hi-C scaffolding assigned 98.08% of the genome to 14 pseudo-chromosomes, and BUSCO (Benchmarking Universal Single-Copy Orthologs) completeness analysis revealed that 98.4% of the core eukaryotic genes were completely present in the genome assembly. Annotation of the <i>L. elegans</i> genome assembly identified that repetitive sequences account for 506.09 Mb (32.30%) and 20167 protein-coding genes, among which 81.03% have functional annotation terms. Phylogenetic analysis showed that <i>L. elegans</i> is closely related to the house spider <i>Parasteatoda tepidariorum</i> (Theridiidae) and that they diverged from a common ancestor 73.0 million years ago. The relatively high evolution rate suggests that <i>L. elegans</i> evolved under strong selection pressure. Based on genome-wide comparative analysis, we identified and 39 toxin proteins and 26 spidroin. Among the toxins, latrotoxins experienced substantial gene duplication and diversification in the two Theridiidae spiders. <i>L. elegans</i> latrotoxin genes had higher Ka/Ks ratios compared to those in other species, suggesting rapid evolution of them. We found that <i>L. elegans</i> have remarkably more MiSp and tandem duplication is the main duplication event of the spidroin. <br>The high-quality <i>L. elegans</i> assembled genome illuminates composition and evolution of venom and silk proteins provides a resource for in-depth exploration and application of them.
DOI: 10.5524/102211
title: Supporting data for "The Assembled and Annotated Genome of the Masked Palm Civet (Paguma larvata)"

description: The masked palm civet (<i>Paguma larvata</i>) acts as an intermediate host of severe acute respiratory syndrome coronavirus (SARS-CoV), which causes SARS, and transfers this virus from bats to humans. Additionally, <i>Paguma larvata</i> has the potential to carry a variety of zoonotic viruses that may threaten human health. However, genome resources for <i>Paguma larvata</i> have not been reported to date. <br>A chromosome-level genome assembly of <i>Paguma larvata</i> was generated using PacBio sequencing, Illumina sequencing, and Hi-C technology. The genome assembly was 2.44 Gb in size, of which 95.32% could be grouped into 22 pseudochromosomes, with contig N50 and scaffold N50 values of 12.97 Mb, respectively. A total of 21,582 protein-coding genes were predicted, and 95.20% of the predicted genes were functionally annotated. Phylogenetic analysis of 19 animal species confirmed the close genetic relationship between <i>P. larvata</i> and species belong to the Felidae family. Gene family clustering revealed 119 unique, 362 significantly expanded, and 58 significantly contracted genes in the <i>P. larvata</i> genome. We identified 971 positively selected genes in <i>P. larvata</i>, and one known human viral receptor gene PDGFRA is positively selected in <i>P. larvata</i>, which is required for human cytomegalovirus (HCMV) infection.<br> This high-quality genome assembly provides a valuable genomic resource for exploring virus-host interactions. It will also provide a reliable reference for studying the genetic bases of the morphological characteristics, adaptive evolution, and evolutionary history of this species.
DOI: 10.5524/102212
title: Supporting data for "Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification"

description: Machine learning (ML) methodology development for classification of immune states in adaptive immune receptor repertoires (AIRR) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of scenarios where classical ML methods (such as penalized logistic regression) already perform adequately for AIRR classification. This hinders investigative reorientation to those scenarios where further method development of more sophisticated ML approaches may be required.<br>To identify those scenarios where a baseline method is able to perform well for AIRR classification, we generated a collection of synthetic benchmark datasets encompassing a wide range of dataset architecture-associated and immune state-associated sequence pattern (signal) complexity. We trained 1300ML models with varying assumptions regarding immune signal on850 datasets with a total of 210000 repertoires containing 42 billion TCR CDR3 amino acid sequences, thereby surpassing the sample sizes of current state-of-the-art AIRR ML setups by two orders of magnitude. We found that L1-penalized logistic regression achieved high prediction accuracy even when the immune signal occurs only in 1 out of 50000 AIR sequences.<br>We provide a reference benchmark to guide new AIRR ML classification methodology by: (i) identifying those scenarios characterised by immune signal and dataset complexity, where baseline methods already achieve high prediction accuracy and (ii) facilitating realistic expectations of the performance of AIRR ML models given training dataset properties and assumptions. Our study serves as a template for defining specialized AIRR benchmark datasets for comprehensive benchmarking of AIRR ML methods.
DOI: 10.5524/102213
title: Supporting data for "Spacemake: processing and analysis of large-scale spatial transcriptomics data"

description: Spatial sequencing methods increasingly gain popularity within RNA biology studies. State-of-the-art techniques can read mRNA expression levels from tissue sections and at the same time register information about the original locations of the molecules in the tissue. The resulting datasets are processed and analyzed by accompanying software which, however, is incompatible across inputs from different technologies. Here, we present spacemake, a modular, robust and scalable spatial transcriptomics pipeline built in snakemake and python. Spacemake is designed to handle all major spatial transcriptomics datasets and can be readily configured to run on other technologies. It can process and analyze several samples in parallel, even if they stem from different experimental methods. Spacemakes unified framework enables reproducible data processing from raw sequencing data to automatically generated downstream analysis reports. Moreover, spacemake is built with a modular design and offers additional functionality such as sample merging, saturation analysis and analysis of long-reads as separate modules. Moreover, spacemake employs novoSpaRc to integrate spatial and single-cell transcriptomics data, resulting in increased gene counts for the spatial dataset. Spacemake is open-source, extendable and can be readily integrated with existing computational workflows.
DOI: 10.5524/102214
title: Supporting data for "Generation and application of pseudo-long reads for metagenome assembly"

description: Metagenome assembly using high-throughput sequencing data is a powerful method to construct microbial genomes in environmental samples without cultivation. However, metagenome assembly, especially when only short reads are available, is a complex and challenging task because mixed genomes of multiple microorganisms constitute the metagenome. Although long read sequencing technologies have been developed and begun to be used for metagenome assembly, many metagenome studies have been performed based on short reads because long reads have higher sequencing cost and error rate than short reads. <br>In this study, we present a new method called PLR-GEN. It can create pseudo-long reads from metagenome short reads based on given reference genome sequences by considering small sequence variations existing in individual genomes of the same or different species. When applied to a mock community dataset in the Human Microbiome Project, PLR-GEN dramatically extended short reads in length of 101 bp to pseudo-long reads with N50 of 33 Kbp and 0.4 % error rate. The use of these pseudo-long reads generated by PLR-GEN resulted in an obvious improvement of metagenome assembly in terms of the number of sequences, assembly contiguity, and prediction of species and genes. <br>PLR-GEN can be used to generate artificial long-read sequences without spending extra sequencing cost, thus aiding various studies using metagenomes.