cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5524/100898
title: Supporting data for "Utilizing a chromosomal-length genome assembly to annotate the Wnt signaling pathway in the Asian citrus psyllid, Diaphorina citri"

description: The Asian citrus psyllid, <i>Diaphorina citri</i>, is an insect vector that transmits <i>Candidatus</i> Liberibacter asiaticus, the causal agent of the Huanglongbing (HLB) or citrus greening disease. This disease has devastated Floridas citrus industry and threatens Californias industry as well as other citrus producing regions around the world. To find novel solutions to the disease, a better understanding of the vector is needed. The <i>D. citri</i> genome has been used to identify and characterize genes involved in Wnt signaling pathways. Wnt signaling is utilized for many important biological processes in metazoans, such as patterning and tissue generation. Curation based on RNA sequencing data and sequence homology confirm twenty four Wnt signaling genes within the <i>D. citri</i> genome, including homologs for beta-catenin, Frizzled receptors, and seven Wnt-ligands. Through phylogenetic analysis, we classify <i>D. citri</i> Wnt-ligands as <i><em>Wg/Wnt1</em>, <em>Wnt5</em>, <em>Wnt6</em>, <em>Wnt7</em>, <em>Wnt10</em>, <em>Wnt11</em>, and <em>WntA</em></i>. The <i>D. citri</i> version 3.0 genome with chromosomal length scaffolds reveals a conserved <em>Wnt1</em>-<em>Wnt6</em>-<em>Wnt10</em> gene cluster with gene configuration similar to that in <i>Drosophila melanogaster</i>. These findings provide a greater insight into the evolutionary history of <em><i>D. citri</i></em> and Wnt signaling in this important hemipteran vector. Manual annotation was essential for identifying high quality gene models. These gene models can be used to develop molecular systems, such as CRISPR and RNAi, that target and control psyllid populations, to manage the spread of HLB. Manual annotation of Wnt signaling pathways was done as part of a collaborative community annotation project.
DOI: 10.5524/100900
title: Supporting data for "Annotation of chitin biosynthesis genes in Diaphorina citri, Asian citrus psyllid"

description: The polysaccharide chitin is critical for the formation of many insect structures, including the exoskeleton, and is required for normal development. Here we report the annotation of three genes from the chitin synthesis pathway in the Asian citrus psyllid, <i>Diaphorina citri</i> (Hemiptera: Liviidae), the vector of Huanglongbing (citrus greening disease). Most insects have two chitin synthase (CHS) genes but, like other hemipterans, <i>D. citri</i> has only one. In contrast, <i>D. citri</i> is unusual among insects in having two UDP-N-acetylglucosamine pyrophosphorylase (UAP) genes. One of the <i>D. citri</i> UAP genes is broadly expressed, while the other is expressed predominantly in males. Our work helps pave the way for potential utilization of these genes as pest control targets to reduce the spread of Huanglongbing.
DOI: 10.5524/100901
title: Supporting data for "<i>In silico</i> characterization of chitin deacetylase genes in the <i>Diaphorina citri</i> genome"

description: Chitin deacetylases (CDAs) are one of the least understood components of insect chitin metabolism. The partial deacetylation of chitin polymers appears to be important for the proper formation of higher order chitin structures, such as long fibers and bundles, that contribute to the integrity of the insect exoskeleton and other structures. Some CDAs may also play a role in bacterial defense. Here we report the manual annotation of four CDA genes from the Asian citrus psyllid, <i>Diaphorina citri</i>, laying the groundwork for future study of these genes.
DOI: 10.5524/100903
title: Supporting data for "Mantis: flexible and consensus-driven genome annotation"

description: The past decades have seen a rapid development of the (meta-)omics fields, producing an unprecedented amount of high-resolution and high-fidelity data. Through the use of these datasets we can infer the role of previously functionally unannotated proteins from single organisms and consortia. In this context, protein function annotation can be described as the identification of regions of interest (i.e., domains) in protein sequences and the assignment of biological functions. Despite the existence of numerous tools, some challenges remain, specifically in terms of speed, flexibility, and reproducibility. In the era of big data analysis, it is also increasingly important to cease limiting our findings to a single reference, coalescing knowledge from different data sources, and thus overcoming some limitations in overly relying on computationally generated data from single sources.<br> We implemented a protein annotation tool - Mantis, which uses database identifiers intersection and text mining to integrate knowledge from multiple reference data sources into a single consensus-driven output. Mantis is flexible, allowing for the customization of reference data and execution parameters, and is reproducible across different research goals and user environments. We implemented a depth-first search algorithm for domain-specific annotation, which significantly improved annotation performance compared to sequence-wide annotation. The parallelized implementation of Mantis results in short runtimes while also outputting high coverage and high-quality protein function annotations. Mantis is a protein function annotation tool that produces high-quality consensus-driven protein annotations. It is easy to set up, customize, and use, scaling from single genomes to large metagenomes.
DOI: 10.5524/100904
title: Supporting data for "Optimizing experimental design for genome sequencing and assembly with Oxford Nanopore Technologies"

description: High quality reference genome sequences are the core of modern genomics. Oxford Nanopore Technologies (ONT) produces inexpensive DNA sequences in excess of 100,000 nucleotides but high error rates make sequence assembly and analysis a non-trivial problem as genome size and complexity increases. To date there has been no comprehensive attempt to generate robust experimental design for ONT genome sequencing and assembly. <br>In this study, we simulate ONT and Illumina DNA sequence reads for the model organisms <i>Escherichia coli, Caenorhabditis elegans, Arabidopsis thaliana</i>, and <i>Drosophila melanogaster</i> and assemble with Canu, Flye,and MaSuRCA software to quantify the influence of sequencing coverage and assembly approach. Heterozygosity in outbred eukaryotes is a common problem for genome assembly.<br>We show broad applicability of our methods using real ONT data generated for four strains of the highly heterozygous nematode <i>Caenorhabditis remanei</i> and <i>C. latens</i>
DOI: 10.5524/100906
title: Supporting data for "Improvements in the Sequencing and Assembly of Plant Genomes"

description: Advances in DNA sequencing have reduced the difficulty of sequencing and assembling plant genomes. A range of methods for long read sequencing and assembly have been recently compared and we now extend the earlier study and report a comparison with more recent methods. <br>Updated Oxford Nanopore Technology software supported improved assemblies. The use of more accurate sequences produced by repeated sequencing of the same molecule (PacBio HiFi) resulted in much less fragmented assembly of sequencing reads. The use of more data to give increased genome coverage resulted in longer contigs (higher N50) but reduced the total length of the assemblies and improved genome completeness (BUSCO). The original model species, <i>Macadamia jansenii</i>, a basal eudicot, was also compared with the 3 other Macadamia species and with avocado (<i>Persea americana</i>), a magnoliid, and jojoba (<i>Simmondsia chinensis</i>) a core eudicot. In these phylogenetically diverse angiosperms, increasing sequence data volumes also caused a highly linear increase in contig size, decreased assembly length and further improved already high completeness. Differences in genome size and sequence complexity apparently influenced the success of assembly from these different species. <br>Advances in long read sequencing technology have continued to significantly improve the results of sequencing and assembly of plant genomes. However, results were consistently improved by greater genome coverage (using an increased number of reads) with the amount needed to achieve a particular level of assembly being species dependant.
DOI: 10.5524/100908
title: Supporting data for "NPSV: A simulation-driven approach to genotyping structural variants in whole genome sequencing data"

description: Structural variants (SV) play a causal role in numerous diseases but are difficult to detect and accurately genotype (determine zygosity) in whole genome next-generation sequencing (NGS) data. SV genotypers that assume the aligned sequencing data uniformly reflects the underlying SV or use existing SV call sets as training data can only partially account for variant and sample-specific biases. <br>We introduce NPSV, a machine learning-based approach for genotyping previously discovered SVs that employs NGS simulation to model the combined effects of the genomic region, sequencer and alignment pipeline on the observed SV evidence. We evaluate NPSV alongside existing SV genotypers on multiple benchmark call sets. We show that NPSV consistently achieves or exceeds state-of-the-art genotyping accuracy across SV call sets, samples and variant types. NPSV can specifically identify putative <i>de novo</i> SVs in a trio context and is robust to offset SV breakpoints. <br>Growing SV databases and the increasing availability of SV calls from long-read sequencing make stand-alone genotyping of previously identified SVs an increasingly important component of genome analyses. By treating potential biases as a simulate-able black box NPSV provides a framework for accurately genotyping a broad range of SVs in both targeted and genome-scale applications.
DOI: 10.5524/100912
title: Supporting data for "VC@Scale: Scalable and High Performance Variant Calling on Cluster Environments"

description: In the past couple of years many new deep learning based variant calling methods like DeepVariant have emerged as more accurate method as compared to conventional variant calling algorithms like GATK HaplotypeCaller, Sterlka2, Freebayes albeit at higher computational costs. Therefore, there is a need for more scalable and higher performance workflows of these deep learning methods. Almost all existing cluster scaled variant calling workflows that use Apache Spark/Hadoop as big data frameworks loosely integrate existing single node pre-processing and variant calling applications. Using Apache Spark just for distributing/scheduling data among loosely coupled applications or using I/O based storage for storing intermediate applications output does not exploit the full benefit of Apache Spark in-memory processing. In order to achieve this, we propose a native Spark-based workflow that uses Python and Apache Arrow to enable efficient transfer of data between different workflow stages. This benefits from the ease of programmability of Python and the high efficiency of Arrows columnar in-memory data transformations. <br>Here we present a scalable, parallel and efficient implementation of next generation sequencing data pre-processing and variant calling workflows. Our design tightly integrates most pre-processing workflow stages, using Spark built-in functions to sort reads by coordinates, and mark duplicates efficiently. Our approach outperforms state-of-the-art implementations by more than 2x for the pre-processing stages, creating a scalable and high performance solution for DeepVariant for both CPU-only and CPU+GPU clusters. <br>We show the feasibility and easy scalability of our approach to achieve high performance and efficient resource utilization for variant calling analysis on HPC clusters using the standardized Apache Arrow data representations. All codes, scripts and configurations used to run our workflow are open sourced and publicly available at VC@Scale.
DOI: 10.5524/100917
title: Supporting data for "A high-quality draft genome for <i>Melaleuca alternifolia</i> (tea tree) - a new platform for evolutionary genomics of myrtaceous terpene-rich species"

description: <i>Melaleuca alternifolia</i> (tea tree) is an Australian native tree, which is the source of a renowned terpene-rich essential oil used in therapeutic and cosmetic products around the world. Tea tree has been cultivated and bred in Australia since the 1990s, and because of its economic importance, along with its <i>Eucalyptus</i> and <i>Corymbia spp.</i> relatives, is one of the most extensively studied members of the Myrtaceae family for genetics and biochemistry of terpene biosynthesis. Here, a high-quality <i>de novo</i> genome assembly using PacBio and Illumina sequencing data is reported as a platform for comparative genomics in the Myrtaceae. The genome was assembled into 3,128 scaffolds with a total length of 362 Mb (N50 = 1.9 Mb) and had significantly higher contiguity than a previously reported assembly (N50 = 8.7 Kb) based on short Illumina paired-end reads. A total of 37,226 protein-coding genes were predicted, using a homology-based, RNAseq evidence-based and <i>ab initio</i> prediction approach. Genome assembly and annotation exhibited high completeness scores of 98.1% and 89.4%, respectively, when compared to the eudicot BUSCO database. The contiguity of the sequence was sufficient to reveal extensive gene order conservation and detection of chromosomal rearrangements in alignments with <i>E. grandis</i> and <i>C. citriodora</i> genomes. This new genome provides an enhanced resource to investigate the genome structure and gene family evolution of <i>M. alternifolia</i>, which will enable further comparative genomic studies in the family of Myrtaceae, and help to elucidate the genetic foundations of economically valuable traits in this essential oil crop.
DOI: 10.5524/100921
title: Supporting data for "Genetic demultiplexing of pooled single-cell RNA-sequencing samples in cancer facilitates effective experimental design"

description: Pooling cells from multiple biological samples prior to library preparation within the same single-cell RNA sequencing experiment provides several advantages, including lower library preparation costs and reduced unwanted technological variation, such as batch effects. Computational demultiplexing tools based on natural genetic variation between individuals provide a simple approach to demultiplex samples, which does not require complex additional experimental procedures. However, these tools have not been evaluated in cancer, where somatic variants, which could differ between cells from the same sample, may obscure the signal in natural genetic variation. Here, we performed <i>in silico</i> benchmark evaluations by combining raw sequencing reads from multiple single-cell samples in high-grade serous ovarian cancer, which has a high copy number burden, and lung adenocarcinoma, which has a high tumor mutational burden. Our results confirm that genetic demultiplexing tools can be effectively deployed on cancer tissue using a pooled experimental design, although high proportions of ambient RNA from cell debris reduce performance. This strategy provides significant cost savings through pooled library preparation. To facilitate similar analyses at the experimental design phase, we provide freely accessible code and a reproducible Snakemake workflow built around the best-performing tools found in our <i>in silico</i> benchmark evaluations, available from our GitHub repository.
DOI: 10.5524/100874
title: Supporting data for "Chromosome-level genome assembly of the hard-shelled mussel <i>Mytilus coruscus</i>, a widely distributed species from the temperate areas of East Asia"

description: The hard-shelled mussel (<i>Mytilus coruscus</i>) is widely distributed in the temperate seas of East Asia, and is an important commercial bivalve in China. Chromosome-level genome information of this species will not only contribute to the development of hard-shelled mussel genetic breeding, but also to studies on larval ecology, climate change biology, marine biology, aquaculture, biofouling, and antifouling. We applied a combination of Illumina sequencing, Oxford Nanopore Technologies sequencing, and high-throughput chromosome conformation capture technologies to construct a chromosome-level genome of the hard-shelled mussel, with a total length of 1.57 Gb and a median contig length of 1.49 Mb. Approximately 90.9% of the assemblies were anchored to 14 linkage groups. We assayed the genome completeness using Benchmark Universal Single-Copy Orthologs (BUSCO). In the metazoan dataset, the current assemblies have 89.4% complete, 1.9% incomplete and 8.7% missing BUSCOs. Gene modeling enabled the annotation of 37,478 protein-coding genes and 26,917 non-coding RNA loci. Phylogenetic analysis showed that <i>M. coruscus</i> is the sister taxon to the clade including <i>Modiolus philippinarum</i> and <i>Bathymodiolus platifrons</i>. Conserved chromosome synteny was observed between hard-shelled mussel and king scallop, suggesting that this is shared ancestrally. Transcriptomic profiling indicated that the pathways of catecholamine biosynthesis and adrenergic signaling in cardiomyocytes might be involved in metamorphosis. The chromosome-level assembly of the hard-shelled mussel genome will provide novel insights into mussel genome evolution and serve as a fundamental platform for studies regarding the planktonic-sessile transition, genetic diversity, and genomic breeding of this bivalve.
DOI: 10.5524/100876
title: Supporting data for "The germline mutational process in rhesus macaque and its implications for phylogenetic dating"

description: Understanding the rate and pattern of germline mutations is of fundamental importance for understanding evolutionary processes.<br>Here we analyzed 19 parent-offspring trios of rhesus macaques (<i>Macaca mulatta</i>) at high sequencing coverage of ca. 76X per individual, and estimated an average rate of 0.77 x 108 <i>de novo</i> mutations per site per generation (95 % CI: 0.69 x 108 - 0.85 x 108). By phasing 50 % of the mutations to parental origins, we found that the mutation rate is positively correlated with the paternal age. The paternal lineage contributed an average of 81 % of the <i>de novo</i> mutations, with a trend of an increasing male contribution for older fathers. About 3.5 % of <i>de novo</i> mutations were shared between siblings, with no parental bias, suggesting that they arose from early development (postzygotic) stages. Finally, the divergence times between closely related primates calculated based on the yearly mutation rate of rhesus macaque generally reconcile with divergence estimated with molecular clock methods, except for the Cercopithecoidea/Hominoidea molecular divergence dated at Mya using our new estimate of the yearly mutation rate. When compared to the traditional molecular clock methods, new estimated rates from pedigree samples can provide insights into the evolution of well-studied groups such as primates.
DOI: 10.5524/100878
title: Supporting data for "Synonymous variants that disrupt mRNA structure are significantly constrained in the human population"

description: The role of synonymous single nucleotide variants in human health and disease is poorly understood, yet there is a growing body of evidence to suggest that this class of silent genetic variation plays multiple regulatory roles in both transcription and translation. One mechanism by which synonymous codons direct and modulate the translational process is through alteration of the elaborate structure formed by single-stranded mRNA molecules. While tools to computationally predict the impact of non-synonymous variants on protein structure are plentiful, analogous tools to systematically assess how synonymous variants might disrupt mRNA structure are lacking. <br><br>To address this need, we developed novel software using a parallel processing framework for large-scale generation of secondary RNA structures and folding statistics for the transcriptome of any species. Focusing our analysis on the human transcriptome, we calculated 5 billion RNA folding statistics for 469 million single nucleotide variants in 45,800 transcripts. By considering the impact of all possible synonymous variants globally, we discover that synonymous variants predicted to disrupt mRNA structure have significantly lower rates of incidence in the human population.<br><br>These findings support the hypothesis that synonymous variants may play a role in genetic disorders due to their effects on mRNA structure. Given that the community lacks tools to evaluate the potential pathogenic impact of synonymous variants, we provide RNA stability, edge distance and diversity metrics for every nucleotide in the human transcriptome and introduce a Structural Predictivity Index (SPI) to quantify structural constraint operating on any synonymous variant. Because no single RNA-folding metric can capture the diversity of mechanisms by which a variant could alter secondary mRNA structure, we generated a SUmmarized RNA Folding (SURF) metric to provide a single measurement to predict the impact of secondary structure altering variants in human genetic studies.<br><br>To access the unique list of genomic coordinates and their associated scores download RNAStability_v10.5.1_hg38_distinct_SURF_SPI_Phred_GitHub_Export.tsv.gz
DOI: 10.5524/100879
title: Supporting data for "BiSulfite Bolt: A BiSulfite Sequencing Analysis Platform"

description: Bisulfite sequencing is commonly employed to measure DNA methylation. Processing bisulfite sequencing data is often challenging due to the computational demands of mapping a low complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt); a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries.<br>We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy.<br>BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.
DOI: 10.5524/100881
title: Supporting data for "SMARTdenovo: 1 a de novo assembler using long noisy reads"

description: Long-read single-molecule sequencing has revolutionized <i>de novo</i> genome assembly and enabled the automated reconstruction of reference-quality genomes. It also has been widely used to study structural variants, phased haplotypes and more. Here, we introduce the assembler SMARTdenovo, which is an SMS assembler that follows the overlap-layout-consensus (OLC) paradigm. SMARTdenovo (RRID: SCR_017622) was designed to be a fast assembler that did not require highly accurate raw reads for error correction, unlike other, contemporaneous SMS assemblers. It has performed well for evaluating congeneric assemblers and has been successful for a variety of assembly projects. It is compatible with Canu for assembling high-quality genomes, and several of the assembly strategies in this program have been incorporated into subsequent popular assemblers. The assembler has been in use since 2015, and here we provide information on the development of SMARTdenovo and how to implement its algorithms into current projects.