cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100696
title: Supporting data for "Substantial GC-bias impacts genomic and metagenomic reconstructions, significantly underrepresenting GC-poor organisms"

description: Metagenomic sequencing is a well-established tool in the modern biosciences. While it promises unparalleled insights into the genetic content of the biological samples studied, conclusions drawn are at risk from biases inherent to the DNA sequencing methods, including inaccurate abundance estimates as a function of genomic GC contents. We explored such GC-biases across many commonly used platforms in experiments sequencing multiple genomes (with mean GC contents ranging from 28.9% to 62.4%) and metagenomes. GC-bias profiles varied among different library preparation protocols and sequencing platforms. We found that our workflows employing MiSeq and NextSeq suffered major GC-biases, with problems becoming increasingly severe outside the 45-65% GC range, leading to a falsely low coverage in GC-rich and especially GC-poor sequences, where genomic windows with 30% GC content had over 10-fold less coverage than windows close to 50% GC content. We also showed that GC content correlates very tightly with coverage biases. The PacBio and HiSeq platforms also evidenced similar profiles of GC-biases to each other which were distinct from those seen in the MiSeq and NextSeq workflows. The Oxford Nanopore workflow was not afflicted with GC-bias. These findings indicate potential sources of difficulty, arising from GC-biases, in genome sequencing which could be pre-emptively addressed with methodological optimisations provided that the GC-biases inherent to the relevant workflow are understood. Furthermore, it is recommended that a more critical approach is taken in quantitative abundance estimates in metagenomic studies. In the future, metagenomic studies should take steps to account for the effects of GC-bias before drawing conclusions, or they should employ a demonstrably unbiased workflow.
DOI: 10.5524/100697
title: Supporting data for "A highly contiguous genome assembly of the bat hawkmoth (Lepidoptera Sphingidae)"

description: Adapted to different ecological niches, moth species belonging to the Hyles genus exhibit a spectacular diversity of larval color patterns. These species diverged about 7.5 Mya, making this rather young genus an interesting system to study a wide range of questions including the process of speciation, ecological adaptation and adaptive radiation. Here we present a high-quality genome assembly of the bat hawkmoth Hyles vespertilio, the first reference genome of a member of the Hyles genus. We generated 51X PacBio long reads with an average read length of 8.9 kb. PacBio reads longer than 4 kb were assembled into contigs, resulting in a 651.4 Mb assembly consisting of 530 contigs with an N50 value of 7.5 Mb. The circular mitochondrial contig has a length of 15,303 bases. The H. vespertilio genome is very repeat-rich and exhibits a higher repeat content (50.3%) than other Bombycoidea species such as Bombyx mori (45.7%) and Manduca sexta (27.5%). We developed a comprehensive gene annotation workflow to obtain consensus gene models from different evidences including gene projections, protein homology, transcriptome data, and ab initio predictions. The resulting gene annotation is highly complete with 94.5% of BUSCO genes being completely present, which is higher than the BUSCO completeness of the B. mori (92.2%) and M. sexta (90%) annotation. Our gene annotation strategy has general applicability to other genomes and the H. vespertilio genome provides a valuable molecular resource to study a range of questions in this genus, including phylogeny, incomplete lineage sorting, speciation and hybridization. A genome browser displaying the genome, alignments and annotations is available at https://genome-public.pks.mpg.de/cgi-bin/hgTracks?db=HLhylVes1.
DOI: 10.5524/100698
title: Supporting data for "Interpretable and accurate prediction models for metagenomics data"

description: Microbiome biomarker discovery for patient diagnosis, prognosis and risk evaluation is attracting broad interest. Selected groups of microbial features provide signatures that characterize host disease states such as cancer or cardio-metabolic diseases. Yet, the current predictive models stemming from machine learning still behave as black boxes and seldom generalize well. Their interpretation is challenging for physicians and biologists, which makes them difficult to trust and use routinely in the physicianpatient decision-making process. Novel methods that provide interpretability and biological insight are needed. Here, we introduce predomics, an original machine learning approach inspired by microbial ecosystem interactions that is tailored for metagenomics data. It discovers accurate predictive signatures and provides unprecedented interpretability. The decision provided by the predictive model is based on a simple, yet powerful score computed by adding, subtracting or dividing cumulative abundance of microbiome measurements. <br>Tested on more than 100 datasets, we demonstrate that predomics models are simple and highly interpretable. Even with such simplicity, they are at least as accurate as state-of-the-art methods. The family of best models, discovered during the learning process, offers the ability to distil biological information and to decipher the predictability signatures of the studied condition. In a proof-of-concept experiment, we successfully predicted body corpulence and metabolic improvement after bariatric surgery using pre-surgery microbiome data. <br>Predomics is a new algorithm that helps in providing reliable and trustworthy diagnostic decisions in the microbiome field. Predomics agrees with societal and legal requirements that plead for an explainable Artificial Intelligence approach in the medical field.
DOI: 10.5524/100699
title: Supporting data for "Learning improves decoding of odor identity with phase-referenced oscillations in the olfactory bulb"

description: Local field potential oscillations reflect temporally coordinated neuronal ensembles coupling distant brain regions, gating processing windows, and providing a reference for spike timing-based codes. In phase amplitude coupling (PAC), the amplitude of the envelope of a faster oscillation is larger within a phase window of a slower carrier wave.<br> Here, we characterized PAC, and the related theta phase-referenced high gamma and beta power (PRP), in the olfactory bulb of mice learning to discriminate odorants. PAC changes throughout learning, and odorant-elicited changes in PRP increase for rewarded and decrease for unrewarded odorants. Contextual odorant identity (is the odorant rewarded?) can be decoded from peak PRP in animals proficient in odorant discrimination, but not in naïve mice. As the animal learns to discriminate the odorants the dimensionality of PRP decreases. Therefore, modulation of phase-referenced chunking of information in the course of learning plays a role in early sensory processing in olfaction.
DOI: 10.5524/100700
title: Supporting data for "Artificial intelligence deciphers codes for color and odor perceptions based on large-scale chemoinformatic data"

description: Color vision is the ability to detect, distinguish, and analyze the wavelength distributions of light independent of the total intensity. It mediates the interaction between an organism and its environment from multiple important aspects. However, the physicochemical basis of color coding has not been explored completely, and how color perception is integrated with other sensory input, typically odor, is unclear.<br>Here, we developed an artificial intelligence platform to train algorithms for distinguishing color and odor based on the large-scale physicochemical features of 1267 and 598 structurally diverse molecules, respectively. The predictive accuracies achieved using the random forest and deep belief network for the prediction of color were 100.0% ± 0.0% and 95.23% ± 0.40% (mean ± SD), respectively. The predictive accuracies achieved using the random forest and deep belief network for the prediction of odor were 93.40% ± 0.31% and 94.75% ± 0.44% (mean ± SD), respectively. Twenty-four physicochemical features were sufficient for the accurate prediction of color, while thirty-nine physicochemical features were sufficient for the accurate prediction of odor. A positive correlation between the color coding and odor coding properties of the molecules was predicted. A group of descriptors was found to interlink prominently in color and odor perceptions. <br>Our random forest model and DBN accurately predicted the colors and odors of structurally diverse molecules. These findings extend our understanding of the molecular and structural basis of color vision and reveal the interrelationship between color and odor perceptions in nature.
DOI: 10.5524/100703
title: Supporting data for "An image dataset related to automated macrophage detection in immunostained lymphoma tissue samples"

description: We present an image dataset related to automated segmentation and counting of macrophages in diffuse large B-cell lymphoma {(DLBCL)} tissue sections. For the classification of DLBCL subtypes as well as for as for providing a prognosis of the clinical outcome, the analysis of the tumor microenvironment and, particularly, of the different types and functions of tumor-associated macrophages, is indispensable. Until now, however, most information about macrophages is obtained either in a completely indirect way by gene expression profiling or by manual counts in immunohistochemically (IHC) fluorescence stained tissue samples while automated recognition of single IHC stained macrophages remains a difficult task. In an accompanying publication, a reliable approach to this problem has been established, and a large set of related images has been generated and analyzed. 
Provided image data comprise a) fluorescence microscopy images of 44 multiple immunohistostained DLBCL tumor subregions, captured at four channels corresponding to CD14, CD163, Pax5 and DAPI; b) "cartoon-like" TV-filtered versions of these images, generated by Rudin-Osher-Fatemi (ROF) denoising; c) an automatically generated mask of the evaluation subregion, based on information from the DAPI channel, and d) automatically generated segmentation masks for macrophages, B-cells and all cell nuclei, using information from CD14, CD163, Pax5 and DAPI channels, respectively. 
Thus, a large set of IHC stained DLBCL specimens is provided together with segmentation masks for different cell populations generated by a reference method for automated image analysis, featuring considerable reuse potential.
DOI: 10.5524/100705
title: Supporting data for "Comparative Proteomics Analysis of Tibetan Hulless Barley under Osmotic Stress via Data-Independent Acquisition Mass Spectrometry"

description: Tibetan hulless barley (<i>Hordeum vulgare</i> L. var. nudum ) is one of the primary crops cultivated in the mountains of Tibet and encounters low temperature, high salinity, and drought. Specifically, drought is one of the major abiotic stresses that affect and limit Tibetan barley growth. Osmotic stress is often simultaneously accompanied by drought conditions. Thus, to improve crop yield, it is critical to explore the molecular mechanism governing the responses of hulless barley to osmotic/drought stress conditions.<br>In this study, we employed quantitative proteomics by data-independent acquisition mass spectrometry (DIA-MS) to investigate protein abundance changes in tolerant (XL) and sensitive (DQ) cultivars. A total of 6921 proteins were identified and quantified in all samples. Two distinct strategies based on pairwise and time-course comparisons were utilized in the comprehensive analysis of differentially abundant proteins. Further functional analysis of differentially abundant proteins revealed that some hormone metabolism-associated and ABA-induced genes are primarily affected by osmotic stress. Enhanced regulation of reactive oxygen species (ROS) may promote the tolerance of hulless barley under osmotic stress. Moreover, we found that some regulators, such as GRF, PR10, MAPK and AMPK, were centrally positioned in the gene regulatory network, suggesting that they may have a dominant role in the osmotic stress response of Tibetan barley.<br>Our findings highlight a subset of proteins and processes that are involved in the alleviation of osmotic stress. In addition, this study provides a large-scale and multidimensional proteomic data resource for the further investigations and improvement of osmotic/drought stress tolerance in hulless barley or other plant species.
DOI: 10.5524/100706
title: Supporting data for "Light-responsive expression atlas reveals the effects of light quality and intensity in Kalanchoë fedtschenkoi, a plant with crassulacean acid metabolism"

description: Crassulacean acid metabolism (CAM), a specialized mode of photosynthesis, enables plant adaptation to water-limited environments and improves photosynthetic efficiency via an inorganic carbon-concentrating mechanism. <i>Kalanchoe fedtschenkoi</i> is an obligate CAM model featuring a relatively small genome and easy stable transformation. However, the molecular responses to light quality and intensity in CAM plants remain understudied.<br>Here we present a genome-wide expression atlas of <i>K. fedtschenkoi</i> plants grown under 12h/12h photoperiod with different light quality (blue, red, far-red, white light) and intensity (0, 150, 440, and 1000 mol m 2 s 1 ) based on RNASeq performed for mature leaf samples collected at dawn (2-h before the starting of lighting period) and dusk (2-h before the dark period). An eFP web browser was created for easy access of the gene expression data. Based on the expression atlas, we constructed a light-responsive co-expression network to reveal the potential regulatory relationships in <i>K. fedtschenkoi</i>. Measurements of leaf titratable acidity, soluble sugar and starch turnover provided metabolic indicators of the magnitude of CAM under the different light treatments and were used to provide biological context for the expression dataset. Furthermore, CAM-related subnetworks were highlighted to showcase genes relevant to CAM pathway, circadian clock and stomatal movement. In comparison with white light, monochrome blue/red/far-red light treatments repressed the expression of several CAM-related genes at dusk, along with a major reduction in acid accumulation. Increasing light intensity from an intermediate level ( 440 mmol m -2 s -1 ) of white light to a high light treatment (1000 mol m 2 s 1 ) increased expression of several genes involved in dark CO 2 fixation and malate transport at dawn, along with an increase in organic acid accumulation.<br>This study provides a highly useful genomics resource for investigating the molecular mechanism underlying the light regulation of physiology and metabolism in CAM plants. Our results support the hypothesis that both light intensity and light quality can modulate the CAM pathway through regulation of CAM-related genes in <i>K. fedtschenkoi</i>.
DOI: 10.5524/100707
title: Supporting data for "Multi-Dimensional Machine Learning Approaches for Fruit Shape Phenotyping in Strawberry"

description: Shape is a critical element of the visual appeal of strawberry fruit and influenced by both genetic and non-genetic determinants. Current fruit phenotyping approaches for external characteristics in strawberry often rely on the human eye to make categorical assessments. However, fruit shape is inherently multi-dimensional, continuously variable trait, and not adequately described by a single categorical or quantitative feature. Morphometric approaches enable the study of complex, multi-dimensional forms but are often abstract and difficult to interpret. In this study, we developed a mathematical approach for transforming fruit shape classifications from digital images onto an ordinal scale called the Principal Progression of k Clusters (PPKC). We use these human-recognizable shape categories to select quantitative features extracted from multiple morphometric analyses that are best fit for genetic dissection and analysis. We transformed images of strawberry fruit into human-recognizable categories using unsupervised machine learning, discovered four principal shape categories, and inferred progression using PPKC. We extracted 68 quantitative features from digital images of strawberries using a suite of morphometric analyses and multi-variate statistical approaches. These analyses defined informative feature sets that effectively captured quantitative differences between shape classes. Classification accuracy ranged from 68-99% for the newly created phenotypic variables for describing a shape. Our results demonstrated that strawberry fruit shapes could be robustly quantified, accurately classified, and empirically ordered using image analyses, machine learning, and PPKC. We generated a dictionary of quantitative traits for studying and predicting shape classes and identifying genetic factors underlying phenotypic variability for fruit shape in strawberry. The methods and approaches we applied in strawberry should apply to other fruits, vegetables, and specialty crops.
DOI: 10.5524/100709
title: Supporting data for "SRPRISM (Single Read Paired Read Indel Substitution Minimizer): an efficient aligner for assemblies with explicit guarantees"

description: Alignment of sequence reads generated by next-generation sequencing (NGS) is an integral part of most pipelines analyzing NGS data. A number of tools designed to quickly align large volume of sequences are already available. However, most existing tools lack explicit guarantees about their output. They also do not support searching genome assemblies, such as the human genome assembly GRCh38, that include primary and alternate sequences and placement information for alternate sequences to primary sequences in the assembly. <br>This paper describes SRPRISM (Single Read Paired Read Indel Substitution Minimizer), an alignment tool for aligning reads without splices. SRPRISM has features not available in most tools, such as (i) support for searching genome assemblies with alternate sequences, (ii) partial alignment of reads with a specified region of reads to be included in the alignment, (iii) choice of ranking schemes for alignments, and (iv) explicit criteria for search sensitivity. We compare the performance of SRPRISM to GEM, Kart, STAR, BWA-MEM, Bowtie2, Hobbes, and Yara using benchmark sets for paired and single reads of lengths 100 bp and 250 bp generated using DWGSIM. We show that SRPRISM finds the best results for most benchmark sets with error rate of up to about 2.5% and GEM performs best for higher error rates. SRPRISM is also more sensitive than other tools even when sensitivity is reduced to improve run time performance. <br>We present SRPRISM as a flexible read mapping tool that provides explicit guarantees on results.
DOI: 10.5524/100710
title: Supporting data for "Continuous chromosome-scale haplotypes assembled from a single interspecies F1 hybrid of yak and cattle"

description: The development of trio binning as an approach for assembling diploid genomes has enabled creation of fully haplotype-resolved reference genomes. Unlike other methods of assembly for diploid genomes, this approach is enhanced, rather than hindered, by the heterozygosity of the individual sequenced. In order to maximize heterozygosity and simultaneously assemble reference genomes for two species, we applied trio binning to an interspecies F1 hybrid of yak (Bos grunniens) and cattle (Bos taurus), two species that diverged nearly 5Mya. The genomes of both of these species are comprised of acrocentric autosomes. We produced the most continuous haplotype-resolved assemblies for a diploid animal yet reported. Both the maternal (yak) and paternal (cattle) assemblies have the largest two chromosomes in single haplotigs, and over one third of the autosomes similarly lack gaps. The maximum length haplotig produced was 153 Mb without any scaffolding or gap-filling steps, and represents the longest haplotig reported for any species. The assemblies are also more complete and accurate than those reported for most other vertebrates, with 97% of mammalian universal single-copy orthologs present. The high heterozygosity inherent to interspecies crosses maximizes the effectiveness of the trio binning method. The interspecies trio binning approach we describe is likely to provide the highest-quality assemblies for any pair of species that can interbreed to produce hybrid offspring that develop to sufficient cell numbers for DNA extraction.
DOI: 10.5524/100711
title: Supporting data for "The chromosome-level genome assembly and annotation of the loquat (Eriobotrya japonica) genome"

description: The loquat (Eriobotrya japonica) is a species of flowering plant in the family Rosaceae that is widely cultivated in Asian, European, and African countries. It blossoms in the winter and ripens in the early summer. The genome of loquat has not been reported, which limits the study of molecular biology in the loquat. Here, we used the third-generation sequencing technology of Nanopore and High-through chromosome conformation capture (Hi-C) technology to sequence the genome of Eriobotrya to provide a reference for researchers. We generated 100.10 Gb of long reads using Nanopore sequencing technologies. Three types of Illumina high-throughput sequencing data, including Genome short reads (47.42 Gb), transcriptome short reads (11.06 Gb) and Hi-C short reads (67.25 Gb), were also generated to construct the loquat genome. All data were assembled into a 760.1 Mb genome assembly. The contigs were mapped to chromosomes by using Hi-C technology based on the contacts between contigs, and then assembled a genome exhibiting 17 chromosomes and a scaffold N50 length of 39.7 Mb. A total of 45,743 protein-coding genes were annotated in the Eriobotrya genome, and we investigated the phylogenetic relationships between the Eriobotrya and six other Rosaceae species. Eriobotrya shows a close relationship with Malus and Pyrus, and the divergence time of Eriobotrya and Malus was 6.76 million years ago. Furthermore, chromosome rearrangement was found in Eriobotrya and Malus . We constructed the first high-quality chromosome-level Eriobotrya genome using Illumina, Nanopore, and Hi-C technologies. This work provides a valuable reference genome for molecular studies of the loquat and provides new insight into chromosome evolution in this species.
DOI: 10.5524/100714
title: Supporting data for "*-DCC: A platform to collect, annotate and explore a large variety of sequencing experiments"

description: Over the last few years the variety of experimental designs and protocols for sequencing experiments increased greatly. To assure the wide usability of the produced data beyond an individual project, rich and systematic annotation of the underlying experiments is of outstanding importance. <br>We first developed an annotation structure which captures the overall experimental design as well as the relevant details of the steps from the biological sample to the library preparation, the sequencing procedure and to the sequencing and processed files. Through various design features, such as controlled vocabularies and different field requirements, we ensured a high annotation quality, comparability and ease of annotation. The structure can be easily adapted to a large variety of species. We then implemented the annotation strategy in a user-hosted web-platform with data import, query and export functionality. <br>We present here an annotation structure and user-hosted platform for sequencing experiment data, suitable for lab-internal documentation, collaborations and large-scale annotation efforts.