Amanda Cooksey

Diabrotica undecimpunctata ssp. howardi, the southern corn rootworm or eastern 12-spotted cucumber beetle, is a generalist insect herbivore that causes damage and yield loss to several crops in North America, including maize. Unresolved phylogenetic relationships within and among D. undecimpunctata subspecies are impacting current quarantine policies. We report the chromosome-level haploid genome assembly, icDiaUnde3, constructed using HiFi and Hi-C read data from a single male D. undecimpunctata collected and identified as subspecies howardi based on geographic location and morphology. The primary 1.74 Gbp assembly contains 11 chromosome-length scaffolds representing 9 autosomes, a single X chromosome, and a supernumerary (B) chromosome (scaffold N50 = 162.8 Mb and L50 = 5). Ab initio and evidence-based structural reference sequence (RefSeq) annotations predicted 18,959 protein-coding genes, in which 99.2% of the 1,367 Benchmark Universal Single-Copy Orthologs from Insecta were complete. Repeat elements occupy 1.26 Gbp (72.33%) of the icDiaUnde3 assembly, with nearly 36% predicted to be retroelements. Alignment of whole chromosomes from icDiaUnde3 with those previously assembled from Diabrotica spp. predicted 2 and 6 autosomal inversions with D. balteata and D. virgifera, respectively. The mitochondrial genome had an annotated gene order and orientation conserved among beetles. The icDiaUnde3 reference genome assembly is a vital resource for taxonomic, comparative, and functional studies to enhance sustainable crop production.

This protocol is an update to the protocol described in Saha et al. The AgBase functional annotation workflow employs three annotation tools: GOanna: performs a BLAST search and transfers gene ontology (GO) annotations from BLAST matches to the query gene products. InterProScan: employs theInterPro database which integrates together predictive information about proteins' function from a number of partner resources, giving an overview of the families that a protein belongs to and the domains and sites it contains. InterProScan can also provide GO and pathway annotations. Pathannotator:annotates proteins with KEGG, FlyBase and Drosophila melanogaster Reactome pathways. Each of these tools accepts a peptide FASTA file and can be run independently of the other tools in the workflow. As both GOanna and InterProScan provide GO annotations, their outputs are provided in GAF format. TheCombine GAFstool can then be used to make a single GAF of GO annotations, if desired.

Genome sequencing of a diverse array of arthropod genomes is already underway and these genomes will be used to study human health, agriculture, biodiversity and ecology. These new genomes are intended to serve as community resources and provide the foundational information that is required to apply ‘omics technologies to a more diverse set of species. However, biologists require genome annotation to use these genomes and derive a better understanding of complex biological systems. Genome annotation incorporates two related but distinct processes: demarcating genes and other elements present in genome sequences (structural annotation); and associating function with genetic elements (functional annotation). While there are well established and freely available workflows for structural annotation of gene identification in newly assembled genomes, workflows for providing the functional annotation required to support functional genomics studies are less well understood. Genome-scale functional annotation is required for functional modeling (enrichment, networks, etc.) and a first-pass genome-wide functional annotation effort can rapidly identify under-represented gene sets for focused community annotation efforts. We present an open source, open access and containerized pipeline for genome-scale functional annotation of insect proteomes and apply it to a diverse range of arthropod species. We show that the performance of the predictions is consistent across a set of arthropod genomes with varying assembly and annotation quality.Complete instructions for running each component of the functional annotation pipeline on the command line, a high performance computing cluster and the CyVerse Discovery Environment can be found at the readthedocs site (https://agbase-docs.readthedocs.io/en/latest/agbase/workflow.html). Simple summary Genomic technologies are accumulating information about genes at a faster rate than ever before, and sequencing initiatives like the Earth Biogenome Project, i5k and Ag100Pest are expected to increase this rate of acquisition. However, if genomic sequencing is to be used for improvement of human health, agriculture and our understanding of biological systems, it is necessary to identify genes and understand how they contribute to biological outcomes. While there are several well-established workflows for assembling genomic sequences and identifying genes, understanding gene function is essential to create actionable knowledge. Moreover this functional annotation process must be easily accessible and provide information at a genomic scale to keep up with new sequence data. We report a well defined workflow for rapid functional annotation of whole proteomes to produce Gene Ontology and pathways information. We test this workflow on a diverse set of arthropod genomes and compare it to common arthropod reference genomes. The workflow we described is freely and publicly available via a web interface on CyVerse or as biocontainers that can be deployed scalably on local computing systems.

High-throughput sequencing and proteomics technologies are markedly increasing the amount of RNA and peptide data that are available to researchers, which are typically made publicly available via data repositories such as the NCBI Sequence Read Archive and proteome archives, respectively. These data sets contain valuable information about when and where gene products are expressed, but this information is not readily obtainable from archived data sets. Here we report Chickspress (http://geneatlas.arl.arizona.edu), the first publicly available gene expression resource for chicken tissues. Since there is no single source of chicken gene models, Chickspress incorporates both NCBI and Ensembl gene models and links these gene sets with experimental gene expression data and QTL information. By linking gene models from both NCBI and Ensembl gene prediction pipelines, researchers can, for the first time, easily compare gene models from each of these prediction workflows to available experimental data for these products. We use Chickspress data to show the differences between these gene annotation pipelines. Chickspress also provides rapid search, visualization and download capacity for chicken gene sets based upon tissue type, developmental stage and experiment type. This first Chickspress release contains 161 gene expression data sets, including expression of mRNAs, miRNAs, proteins and peptides. We provide several examples demonstrating how researchers may use this resource.