gene ontology | Ag Data Commons

Initial set of gene ontology (GO) terms for the D v virgifera GCF_003013835.1 RefSeq protein models

Gene ontologies generated using GOanna with a standard pipeline (https://agbase-docs.readthedocs.io/en/latest/goanna/using_goanna_cmd.html; default settings) with queries against the invertebrate subsection of the UniProt database.

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Functional annotation for 15 diverse arthropod genomes

We present the annotation results of 15 arthropod proteomes using 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.

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De novo transcriptome assembly of Schizaphis gramium Biotype I feeding on wheat

Transcriptome was generated from pooled adult aphids that were fed on wheat plants containing the Dn4 and DN7 resistance gene as well as Yuma plants containing no resistant genes (Dn0). The assembly was generated using Trinity. All assembled transcripts, including those that were not predicted to encode ORFs, are included along with their corresponding functional annotations from Trinotate.

Data from: Responses of Aspergillus flavus to Oxidative Stress Are Related to Fungal Development Regulator, Antioxidant Enzyme, and Secondary Metabolite Biosynthetic Gene Expression

In order to better understand isolate-specific oxidative stress responses, the transcriptional responses of field isolates of *Aspergillus flavus* are examined with varying levels of aflatoxin production (NRRL3357, AF13, and Tox4) to H2O2-induced oxidative stress using an RNA sequencing approach.

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Alliance of Genome Resources

The primary mission of the Alliance of Genome Resources (the Alliance) is to develop and maintain sustainable genome information resources that facilitate the use of diverse model organisms in understanding the genetic and genomic basis of human biology, health and disease. This understanding is fundamental for advancing genome biology research and for translating human genome data into clinical utility.

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AgBase

[AgBase](https://agbase.arizona.edu/index.html) Version 2.0 is a curated, open-source, Web-accessible resource for functional analysis of agricultural plant and animal gene products including gene ontology annotations. Its long-term goal is to serve the needs of the agricultural research communities by facilitating post-genome biology for agriculture researchers and for those researchers primarily using agricultural species as biomedical models. AgBase uses controlled vocabularies developed by the Gene Ontology (GO) Consortium to describe molecular function, biological process, and cellular component for genes and gene products in agricultural species.

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Annotations of Unigenes Assembled from Schizaphis graminum and Sipha flava

Transcriptomes were assembled de novo from pools of adult aphids that were feeding on sorghum and switchgrass. Reads from all replicates were pooled, normalized in silico to 25X coverage, and assembled using Trinity. Only the most abundant isoform for each unigene was retained for annotation and unigenes with transcripts per million mapped reads (TPM) less than 0.5 were removed from the dataset. The remaining unigenes were annotated using Trinotate with BLASTP comparisons against the Swiss-Prot/UniProt database. In addition, Pfam-A assignments were computed using hmmer, signal peptide predictions were performed using SignalP, and transmembrane domain predictions were performed using tmHMM. Gene ontology (GO assignments) were retrieved from Trinotate using the highest scoring BLASTp matches as queries.

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Data from: Generation and analysis of blueberry transcriptome sequences from leaves, developing fruit, and flower buds from cold acclimation through deacclimation

There has been increased consumption of blueberries in recent years fueled in part because of their many recognized health benefits. Blueberry fruit is very high in anthocyanins, which have been linked to improved night vision, prevention of macular degeneration, anti-cancer activity, and reduced risk of heart disease. Very few genomic resources have been available for blueberry, however. Further development of genomic resources like expressed sequence tags (ESTs), molecular markers, and genetic linkage maps could lead to more rapid genetic improvement. Marker-assisted selection could be used to combine traits for climatic adaptation with fruit and nutritional quality traits.

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Genomes To Fields 2016

Phenotypic, genotypic, and environment data for the 2016 field season: The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/GenomesToFields_G2F_2016_Data_Mar_2018).

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Genomes To Fields 2015

Phenotypic, genotypic, and environment data for the 2015 field season: The data is stored in [CyVerse](http://datacommons.cyverse.org/browse/iplant/home/shared/commons_repo/curated/Carolyn_Lawrence_Dill_G2F_Mar_2017).

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