AgAnimalGenomes: browsers for viewing and manually annotating farm animal genomes.

Current genome sequencing technologies have made it possible to generate highly contiguous genome assemblies for non-model animal species. Despite advances in genome assembly methods, there is still room for improvement in the delineation of specific gene features in the genomes. Here we present genome visualization and annotation tools to support seven livestock species (bovine, chicken, goat, horse, pig, sheep, and water buffalo), available in a new resource called AgAnimalGenomes. In addition to supporting the manual refinement of gene models, these browsers provide visualization tracks for hundreds of RNAseq experiments, as well as data generated by the Functional Annotation of Animal Genomes (FAANG) Consortium. For species with predicted gene sets from both Ensembl and RefSeq, the browsers provide special tracks showing the thousands of protein-coding genes that disagree across the two gene sources, serving as a valuable resource to alert researchers to gene model issues that may affect data interpretation. We describe the data and search methods available in the new genome browsers and how to use the provided tools to edit and create new gene models.

Toward a data infrastructure for the Plant Cell Atlas.

We review how a data infrastructure for the Plant Cell Atlas might be built using existing infrastructure and platforms. The Human Cell Atlas has developed an extensive infrastructure for human and mouse single cell data, while the European Bioinformatics Institute has developed a Single Cell Expression Atlas, that currently houses several plant data sets. We discuss issues related to appropriate ontologies for describing a plant single cell experiment. We imagine how such an infrastructure will enable biologists and data scientists to glean new insights into plant biology in the coming decades, as long as such data are made accessible to the community in an open manner.

Identification of large offspring syndrome during pregnancy through ultrasonography and maternal blood transcriptome analyses.

In vitro production (IVP) of embryos in cattle can result in large/abnormal offspring syndrome (LOS/AOS) which is characterized by macrosomia. LOS can cause dystocia and lead to the death of dam and calf. Currently, no test exists to identify LOS pregnancies. We hypothesized that fetal ultrasonography and/or maternal blood markers are useful to identify LOS. Bovine fetuses were generated by artificial insemination (control) or IVP. Fetal ultrasonographies were taken on gestation D55 (D55) and fetal collections performed on D56 or D105 (gestation in cattle ≈ D280). IVP fetuses weighing ≥ 97 percentile of the control weight were considered LOS. Ultrasonography results show that the product of six D55 measurements can be used to identify extreme cases of LOS. To determine whether maternal blood can be used to identify LOS, leukocyte mRNA from 23 females was sequenced. Unsupervised hierarchical clustering grouped the transcriptomes of the two females carrying the two largest LOS fetuses. Comparison of the leukocyte transcriptomes of these two females to the transcriptome of all other females identified several misregulated transcripts on gestation D55 and D105 with LOC783838 and PCDH1 being misregulated at both time-points. Together our data suggest that LOS is identifiable during pregnancy in cattle.

Nuclear translocation of vitellogenin in the honey bee (Apis mellifera).

Vitellogenin (Vg) is a conserved protein used by nearly all oviparous animals to produce eggs. It is also pleiotropic and performs functions in oxidative stress resistance, immunity, and, in honey bees, behavioral development of the worker caste. It has remained enigmatic how Vg affects multiple traits. Here, we asked whether Vg enters the nucleus and acts via DNA-binding. We used cell fractionation, immunohistology, and cell culture to show that a structural subunit of honey bee Vg translocates into cell nuclei. We then demonstrated Vg-DNA binding theoretically and empirically with prediction software and chromatin immunoprecipitation with sequencing (ChIP-seq), finding binding sites at genes influencing immunity and behavior. Finally, we investigated the immunological and enzymatic conditions affecting Vg cleavage and nuclear translocation and constructed a 3D structural model. Our data are the first to show Vg in the nucleus and suggest a new fundamental regulatory role for this ubiquitous protein. Supplementary information: The online version contains supplementary material available at 10.1007/s13592-022-00914-9.

Hymenoptera Genome Database: new genomes and annotation datasets for improved go enrichment and orthologue analyses.

We report an update of the Hymenoptera Genome Database (HGD; http://HymenopteraGenome.org), a genomic database of hymenopteran insect species. The number of species represented in HGD has nearly tripled, with fifty-eight hymenopteran species, including twenty bees, twenty-three ants, eleven wasps and four sawflies. With a reorganized website, HGD continues to provide the HymenopteraMine genomic data mining warehouse and JBrowse/Apollo genome browsers integrated with BLAST. We have computed Gene Ontology (GO) annotations for all species, greatly enhancing the GO annotation data gathered from UniProt with more than a ten-fold increase in the number of GO-annotated genes. We have also generated orthology datasets that encompass all HGD species and provide orthologue clusters for fourteen taxonomic groups. The new GO annotation and orthology data are available for searching in HymenopteraMine, and as bulk file downloads.

Multi-tiered analyses of honey bees that resist or succumb to parasitic mites and viruses.

BACKGROUND: Varroa destructor mites, and the numerous viruses they vector to their honey bee hosts, are among the most serious threats to honey bee populations, causing mortality and morbidity to both the individual honey bee and colony, the negative effects of which convey to the pollination services provided by honey bees worldwide. Here we use a combination of targeted assays and deep RNA sequencing to determine host and microbial changes in resistant and susceptible honey bee lineages. We focus on three study sets. The first involves field sampling of sympatric western bees, some derived from resistant stock and some from stock susceptible to mites. The second experiment contrasts three colonies more deeply, two from susceptible stock from the southeastern U.S. and one from mite-resistant bee stock from Eastern Texas. Finally, to decouple the effects of mites from those of the viruses they vector, we experimentally expose honey bees to DWV in the laboratory, measuring viral growth and host responses. RESULTS: We find strong differences between resistant and susceptible bees in terms of both viral loads and bee gene expression. Interestingly, lineages of bees with naturally low levels of the mite-vectored Deformed wing virus, also carried lower levels of viruses not vectored by mites. By mapping gene expression results against current ontologies and other studies, we describe the impacts of mite parasitism, as well as viruses on bee health against two genetic backgrounds. We identify numerous genes and processes seen in other studies of stress and disease in honey bee colonies, alongside novel genes and new patterns of expression. CONCLUSIONS: We provide evidence that honey bees surviving in the face of parasitic mites do so through their abilities to resist the presence of devastating viruses vectored by these mites. In all cases, the most divergence between stocks was seen when bees were exposed to live mites or viruses, suggesting that gene activation, rather than constitutive expression, is key for these interactions. By revealing responses to viral infection and mite parasitism in different lineages, our data identify candidate proteins for the evolution of mite tolerance and virus resistance.

The genomic basis of evolutionary differentiation among honey bees.

In contrast to the western honey bee, Apis mellifera, other honey bee species have been largely neglected despite their importance and diversity. The genetic basis of the evolutionary diversification of honey bees remains largely unknown. Here, we provide a genome-wide comparison of three honey bee species, each representing one of the three subgenera of honey bees, namely the dwarf (Apis florea), giant (A. dorsata), and cavity-nesting (A. mellifera) honey bees with bumblebees as an outgroup. Our analyses resolve the phylogeny of honey bees with the dwarf honey bees diverging first. We find that evolution of increased eusocial complexity in Apis proceeds via increases in the complexity of gene regulation, which is in agreement with previous studies. However, this process seems to be related to pathways other than transcriptional control. Positive selection patterns across Apis reveal a trade-off between maintaining genome stability and generating genetic diversity, with a rapidly evolving piRNA pathway leading to genomes depleted of transposable elements, and a rapidly evolving DNA repair pathway associated with high recombination rates in all Apis species. Diversification within Apis is accompanied by positive selection in several genes whose putative functions present candidate mechanisms for lineage-specific adaptations, such as migration, immunity, and nesting behavior.

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database.

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

A chromosome-level assembly of the cat flea genome uncovers rampant gene duplication and genome size plasticity.

BACKGROUND: Fleas (Insecta: Siphonaptera) are small flightless parasites of birds and mammals; their blood-feeding can transmit many serious pathogens (i.e., the etiological agents of bubonic plague, endemic and murine typhus). The lack of flea genome assemblies has hindered research, especially comparisons to other disease vectors. Accordingly, we sequenced the genome of the cat flea, Ctenocephalides felis, an insect with substantial human health and veterinary importance across the globe. RESULTS: By combining Illumina and PacBio sequencing of DNA derived from multiple inbred female fleas with Hi-C scaffolding techniques, we generated a chromosome-level genome assembly for C. felis. Unexpectedly, our assembly revealed extensive gene duplication across the entire genome, exemplified by ~ 38% of protein-coding genes with two or more copies and over 4000 tRNA genes. A broad range of genome size determinations (433-551 Mb) for individual fleas sampled across different populations supports the widespread presence of fluctuating copy number variation (CNV) in C. felis. Similarly, broad genome sizes were also calculated for individuals of Xenopsylla cheopis (Oriental rat flea), indicating that this remarkable "genome-in-flux" phenomenon could be a siphonapteran-wide trait. Finally, from the C. felis sequence reads, we also generated closed genomes for two novel strains of Wolbachia, one parasitic and one symbiotic, found to co-infect individual fleas. CONCLUSION: Rampant CNV in C. felis has dire implications for gene-targeting pest control measures and stands to complicate standard normalization procedures utilized in comparative transcriptomics analysis. Coupled with co-infection by novel Wolbachia endosymbionts-potential tools for blocking pathogen transmission-these oddities highlight a unique and underappreciated disease vector.

De novo assembly of the cattle reference genome with single-molecule sequencing.

BACKGROUND: Major advances in selection progress for cattle have been made following the introduction of genomic tools over the past 10-12 years. These tools depend upon the Bos taurus reference genome (UMD3.1.1), which was created using now-outdated technologies and is hindered by a variety of deficiencies and inaccuracies. RESULTS: We present the new reference genome for cattle, ARS-UCD1.2, based on the same animal as the original to facilitate transfer and interpretation of results obtained from the earlier version, but applying a combination of modern technologies in a de novo assembly to increase continuity, accuracy, and completeness. The assembly includes 2.7 Gb and is >250× more continuous than the original assembly, with contig N50 >25 Mb and L50 of 32. We also greatly expanded supporting RNA-based data for annotation that identifies 30,396 total genes (21,039 protein coding). The new reference assembly is accessible in annotated form for public use. CONCLUSIONS: We demonstrate that improved continuity of assembled sequence warrants the adoption of ARS-UCD1.2 as the new cattle reference genome and that increased assembly accuracy will benefit future research on this species.

Bovine Genome Database: new annotation tools for a new reference genome.

The Bovine Genome Database (BGD) (http://bovinegenome.org) has been the key community bovine genomics database for more than a decade. To accommodate the increasing amount and complexity of bovine genomics data, BGD continues to advance its practices in data acquisition, curation, integration and efficient data retrieval. BGD provides tools for genome browsing (JBrowse), genome annotation (Apollo), data mining (BovineMine) and sequence database searching (BLAST). To augment the BGD genome annotation capabilities, we have developed a new Apollo plug-in, called the Locus-Specific Alternate Assembly (LSAA) tool, which enables users to identify and report potential genome assembly errors and structural variants. BGD now hosts both the newest bovine reference genome assembly, ARS-UCD1.2, as well as the previous reference genome, UMD3.1.1, with cross-genome navigation and queries supported in JBrowse and BovineMine, respectively. Other notable enhancements to BovineMine include the incorporation of genomes and gene annotation datasets for non-bovine ruminant species (goat and sheep), support for multiple assemblies per organism in the Regions Search tool, integration of additional ontologies and development of many new template queries. To better serve the research community, we continue to focus on improving existing tools, developing new tools, adding new datasets and encouraging researchers to use these resources.

Differential gene expression in response to eCry3.1Ab ingestion in an unselected and eCry3.1Ab-selected western corn rootworm (Diabrotica virgifera virgifera LeConte) population.

Diabrotica virgifera virgifera LeConte, the western corn rootworm (WCR) is one of the most destructive pests in the U.S. Corn Belt. Transgenic maize lines expressing various Cry toxins from Bacillus thuringiensis have been adopted as a management strategy. However, resistance to many Bt toxins has occurred. To investigate the mechanisms of Bt resistance we carried out RNA-seq using Illumina sequencing technology on resistant, eCry3.1Ab-selected and susceptible, unselected, whole WCR neonates which fed on seedling maize with and without eCry3.1Ab for 12 and 24 hours. In a parallel experiment RNA-seq experiments were conducted when only the midgut of neonate WCR was evaluated from the same treatments. After de novo transcriptome assembly we identified differentially expressed genes (DEGs). Results from the assemblies and annotation indicate that WCR neonates from the eCry3.1Ab-selected resistant colony expressed a small number of up and down-regulated genes following Bt intoxication. In contrast, unselected susceptible WCR neonates expressed a large number of up and down-regulated transcripts in response to intoxication. Annotation and pathway analysis of DEGs between susceptible and resistant whole WCR and their midgut tissue revealed genes associated with cell membrane, immune response, detoxification, and potential Bt receptors which are likely related to eCry3.1Ab resistance. This research provides a framework to study the toxicology of Bt toxins and mechanism of resistance in WCR, an economically important coleopteran pest species.

Apollo: Democratizing genome annotation.

Genome annotation is the process of identifying the location and function of a genome's encoded features. Improving the biological accuracy of annotation is a complex and iterative process requiring researchers to review and incorporate multiple sources of information such as transcriptome alignments, predictive models based on sequence profiles, and comparisons to features found in related organisms. Because rapidly decreasing costs are enabling an ever-growing number of scientists to incorporate sequencing as a routine laboratory technique, there is widespread demand for tools that can assist in the deliberative analytical review of genomic information. To this end, we present Apollo, an open source software package that enables researchers to efficiently inspect and refine the precise structure and role of genomic features in a graphical browser-based platform. Some of Apollo's newer user interface features include support for real-time collaboration, allowing distributed users to simultaneously edit the same encoded features while also instantly seeing the updates made by other researchers on the same region in a manner similar to Google Docs. Its technical architecture enables Apollo to be integrated into multiple existing genomic analysis pipelines and heterogeneous laboratory workflow platforms. Finally, we consider the implications that Apollo and related applications may have on how the results of genome research are published and made accessible.

MaizeGDB 2018: the maize multi-genome genetics and genomics database.

Since its 2015 update, MaizeGDB, the Maize Genetics and Genomics database, has expanded to support the sequenced genomes of many maize inbred lines in addition to the B73 reference genome assembly. Curation and development efforts have targeted high quality datasets and tools to support maize trait analysis, germplasm analysis, genetic studies, and breeding. MaizeGDB hosts a wide range of data including recent support of new data types including genome metadata, RNA-seq, proteomics, synteny, and large-scale diversity. To improve access and visualization of data types several new tools have been implemented to: access large-scale maize diversity data (SNPversity), download and compare gene expression data (qTeller), visualize pedigree data (Pedigree Viewer), link genes with phenotype images (MaizeDIG), and enable flexible user-specified queries to the MaizeGDB database (MaizeMine). MaizeGDB also continues to be the community hub for maize research, coordinating activities and providing technical support to the maize research community. Here we report the changes MaizeGDB has made within the last three years to keep pace with recent software and research advances, as well as the pan-genomic landscape that cheaper and better sequencing technologies have made possible. MaizeGDB is accessible online at https://www.maizegdb.org.

AgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture.

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

Bovine Genome Database: Tools for Mining the Bos taurus Genome.

The Bovine Genome Database (BGD; http://bovinegenome.org ) is a web-accessible resource that supports bovine genomics research by providing genome annotation and data mining tools. BovineMine is a tool within BGD that integrates BGD data, including the genome, genes, precomputed gene expression levels and variant consequences, with external data sources that include quantitative trait loci (QTL), orthologues, Gene Ontology, gene interactions, and pathways. BovineMine enables researchers without programming skills to create custom integrated datasets for use in downstream analyses. This chapter describes how to enhance a bovine genomics project using the Bovine Genome Database, with data mining examples demonstrating BovineMine.

Hymenoptera Genome Database: Using HymenopteraMine to Enhance Genomic Studies of Hymenopteran Insects.

The Hymenoptera Genome Database (HGD; http://hymenopteragenome.org ) is a genome informatics resource for insects of the order Hymenoptera, which includes bees, ants and wasps. HGD provides genome browsers with manual annotation tools (JBrowse/Apollo), BLAST, bulk data download, and a data mining warehouse (HymenopteraMine). This chapter focuses on the use of HymenopteraMine to create annotation data sets that can be exported for use in downstream analyses. HymenopteraMine leverages the InterMine platform to combine genome assemblies and official gene sets with data from OrthoDB, RefSeq, FlyBase, Gene Ontology, UniProt, InterPro, KEGG, Reactome, dbSNP, PubMed, and BioGrid, as well as precomputed gene expression information based on publicly available RNAseq. Built-in template queries provide starting points for data exploration, while the QueryBuilder tool supports construction of complex custom queries. The List Analysis and Genomic Regions search tools execute queries based on uploaded lists of identifiers and genome coordinates, respectively. HymenopteraMine facilitates cross-species data mining based on orthology and supports meta-analyses by tracking identifiers across gene sets and genome assemblies.

Global misregulation of genes largely uncoupled to DNA methylome epimutations characterizes a congenital overgrowth syndrome.

Assisted reproductive therapies (ART) have become increasingly common worldwide and numerous retrospective studies have indicated that ART-conceived children are more likely to develop the overgrowth syndrome Beckwith-Wiedemann (BWS). In bovine, the use of ART can induce a similar overgrowth condition, which is referred to as large offspring syndrome (LOS). Both BWS and LOS involve misregulation of imprinted genes. However, it remains unknown whether molecular alterations at non-imprinted loci contribute to these syndromes. Here we examined the transcriptome of skeletal muscle, liver, kidney, and brain of control and LOS bovine fetuses and found that different tissues within LOS fetuses have perturbations of distinct gene pathways. Notably, in skeletal muscle, multiple pathways involved in myoblast proliferation and fusion into myotubes are misregulated in LOS fetuses. Further, characterization of the DNA methylome of skeletal muscle demonstrates numerous local methylation differences between LOS and controls; however, only a small percent of differentially expressed genes (DEGs), including the imprinted gene IGF2R, could be associated with the neighboring differentially methylated regions. In summary, we not only show that misregulation of non-imprinted genes and loss-of-imprinting characterize the ART-induced overgrowth syndrome but also demonstrate that most of the DEGs is not directly associated with DNA methylome epimutations.

Global assessment of imprinted gene expression in the bovine conceptus by next generation sequencing.

Genomic imprinting is an epigenetic mechanism that leads to parental-allele-specific gene expression. Approximately 150 imprinted genes have been identified in humans and mice but less than 30 have been described as imprinted in cattle. For the purpose of de novo identification of imprinted genes in bovine, we determined global monoallelic gene expression in brain, skeletal muscle, liver, kidney and placenta of day ∼105 Bos taurus indicus × Bos taurus taurus F1 conceptuses using RNA sequencing. To accomplish this, we developed a bioinformatics pipeline to identify parent-specific single nucleotide polymorphism alleles after filtering adenosine to inosine (A-to-I) RNA editing sites. We identified 53 genes subject to monoallelic expression. Twenty three are genes known to be imprinted in the cow and an additional 7 have previously been characterized as imprinted in human and/or mouse that have not been reported as imprinted in cattle. Of the remaining 23 genes, we found that 10 are uncharacterized or unannotated transcripts located in known imprinted clusters, whereas the other 13 genes are distributed throughout the bovine genome and are not close to any known imprinted clusters. To exclude potential cis-eQTL effects on allele expression, we corroborated the parental specificity of monoallelic expression in day 86 Bos taurus taurus × Bos taurus taurus conceptuses and identified 8 novel bovine imprinted genes. Further, we identified 671 candidate A-to-I RNA editing sites and describe random X-inactivation in day 15 bovine extraembryonic membranes. Our results expand the imprinted gene list in bovine and demonstrate that monoallelic gene expression can be the result of cis-eQTL effects.

JBrowse: a dynamic web platform for genome visualization and analysis.

BACKGROUND: JBrowse is a fast and full-featured genome browser built with JavaScript and HTML5. It is easily embedded into websites or apps but can also be served as a standalone web page. RESULTS: Overall improvements to speed and scalability are accompanied by specific enhancements that support complex interactive queries on large track sets. Analysis functions can readily be added using the plugin framework; most visual aspects of tracks can also be customized, along with clicks, mouseovers, menus, and popup boxes. JBrowse can also be used to browse local annotation files offline and to generate high-resolution figures for publication. CONCLUSIONS: JBrowse is a mature web application suitable for genome visualization and analysis.