NOTE: This dataset is no longer publicly available. This database houses over 500,000 sequences that were generated and assembled into approximately 15,000 contigs, annotated and functionally mapped to Gene Ontology (GO) terms. Blueberry (Vaccinium corymbosum) is a major berry crop in the United States. Next generation sequencing methodologies, such as 454, have been demonstrated to be successful and efficient in producing a snap-shot of transcriptional activities during an organism’s developmental stage(s) or its response to biotic or abiotic stresses. Such application of this new sequencing technique allows for high-throughput, genome-wide experimental verification of known and novel transcripts. We have applied a high-throughput pyrosequencing technology (454 EST sequencing) for transcriptome profiling of blueberry during different stages of fruit development to gain an understanding of the genes that are up or down regulated during this process. We have also sequenced flower buds at four different stages of cold acclimation to gain a better understanding of the genes and biochemical pathways that are up- or down-regulated during cold acclimation, since extreme low temperatures are known to reduce crop yield and cause major losses to US farmers. We have also sequenced a leaf sample to compare its transcriptome profile with that of bud and fruit samples. Over 500,000 sequences were generated and assembled into approximately 15,000 contigs and were annotated and functionally mapped to Gene Ontology (GO) terms. A database was developed to house these sequences and their annotations. A web based interface was also developed to allow collaborators to search\browse the data and aid in the analysis and interpretation of the data. The availability of these sequences will allow for future advances, such as the development of a blueberry microarray to study gene expression, and will aid in the blueberry genome sequencing effort that is underway. This work was supported by grant 2008-51180-04861 from the USDA - Cooperative State Research, Education, and Extension Service (CSREES) Specialty Crop Research Initiative program.

CottonGen has an instance of the JBrowse genome browser for viewing genome data. A list of the genomes available in CottonGen can be accessed by clicking the JBrowse link in the Tools menu. Whole Genomes 2019-03: Gossypium barbadense AD2 Hai-7124 genome ZJU v1.1_a1 2018-12: Gossypium barbadense AD2 3-79 genome HAU v2_a1 2015-12: Gossypium barbadense AD2 3-79 genome HAU v1_a1 2019-03: Gossypium hirsutum AD1 genome ZJU-Improved v2.1_a1 2018-12: Gossypium hirsutum AD1 genome HAU v1_a1 2017-09: Gossypium hirsutum AD1 genome TX-JGI v1.1_a1 2015-04: Gossypium hirsutum AD1 genome NAU-NBI v1.1_a1.1 2015-04: Gossypium hirsutum AD1 genome CGP-BGI v1_a1 2018-05: Gossypium arboreum A2 genome CRI-Updated v1_a1 2014-05: Gossypium arboreum A2 genome CGP-BGI v2_a1 2012-12: Gossypium raimondii D5 genome JGI v2_a2.1 2012-08: Gossypium raimondii D5 genome CGP-BGI v1_a1 Chloroplast Genomes Gossypium arboreum chloroplast Gossypium barbadense chloroplast Gossypium hirsutum chloroplast Gossypium raimondii chloroplast Please watch the JBrowse tutorial for more details about how to navigate and use JBrowse.

The erosion of habitat heterogeneity can reduce species diversity directly but can also lead to the loss of distinctiveness of sympatric species through speciation reversal. We know little about changes in genomic differentiation during the early stages of these processes, which can be mediated by anthropogenic perturbation. Here, we analyse three sympatric whitefish species (Coregonus spp) sampled across two neighbouring and connected Swiss pre‐alpine lakes, which have been differentially affected by anthropogenic eutrophication. Our data set comprises 16,173 loci genotyped across 138 whitefish using restriction‐site associated DNA sequencing (RADseq). Our analysis suggests that in each of the two lakes the population of a different, but ecologically similar, whitefish species declined following a recent period of eutrophication. Genomic signatures consistent with hybridisation are more pronounced in the more severely impacted lake. Comparisons between sympatric pairs of whitefish species with contrasting ecology, where one is shallow benthic and the other one more profundal pelagic, reveal genomic differentiation that is largely correlated along the genome, while differentiation is uncorrelated between pairs of allopatric provenance with similar ecology. We identify four genomic loci that provide evidence of parallel divergent adaptation between the shallow benthic species and the two different more profundal species. Functional annotations available for two of those loci are consistent with divergent ecological adaptation. Our genomic analysis indicates the action of divergent natural selection between sympatric whitefish species in pre‐alpine lakes and reveals the vulnerability of these species to anthropogenic alterations of the environment and associated adaptive landscape.

The filtered VCF file of 10501 SNPs from the 432 individuals in this study. This dataset was used for genome-wide association study (GWAS) and genomic prediction of sugarcane ratooning ability. It was developed using Rapid Genomics Capture-Seq technology. Resources in this dataset: Resource Title: SNP data for 432 Sugarcane Clones File Name: sugarcane.10501.SNPs_.432.Inds_.vcf

A high-quality reference genome is an essential tool for applied and basic research on arthropods. Long-read sequencing technologies may be used to generate more complete and contiguous genome assemblies than alternate technologies, however, long-read methods have historically had greater input DNA requirements and higher costs than next generation sequencing, which are barriers to their use on many samples. Here, we present a 2.3 Gb de novo genome assembly of a field-collected adult female Spotted Lanternfly (Lycorma delicatula) using a single PacBio SMRT Cell. The Spotted Lanternfly is an invasive species recently discovered in the northeastern United States, threatening to damage economically important crop plants in the region. The DNA from one individual female specimen collected in Reading, Berks County, Pennsylvania was used to make one standard, size-selected library with an average DNA fragment size of ~20 kb. The library was run on one Sequel II SMRT Cell 8M, generating a total of 132 Gb of long-read sequences, of which 82 Gb were from unique library molecules, representing approximately 38x coverage of the genome. The assembly had high contiguity (contig N50 length = 1.5 Mb), completeness, and sequence level accuracy as estimated by conserved gene set analysis (96.8% of conserved genes both complete and without frame shift errors). Further, it was possible to segregate more than half of the diploid genome into the two separate haplotypes. The assembly also recovered two microbial symbiont genomes known to be associated with L. delicatula, each microbial genome being assembled into a single contig. We demonstrate that field-collected arthropods can be used for the rapid generation of high-quality genome assemblies, an attractive approach for projects on emerging invasive species, disease vectors, or conservation efforts of endangered species. Supporting files for the manuscript "A High-Quality Genome Assembly from a Single, Field-collected Spotted Lanternfly (Lycorma delicatula) using the PacBio Sequel II System", include several intermediate versions of the assembly (raw output from Falcon, raw output from Falcon unzip, etc.) as well as the final assembly primary contigs and haplotigs (for the regions of the genome that were phased).

This dataset is supplemental to the article "BBGD: an online database for blueberry genomic data," (2007); it is titled "list of genes printed on microarray slides." The article, "BBGD: an online database for blueberry genomic data," (2007) involving blueberry cold hardiness experiments has a list of all the genes that were printed on microarray slides. This dataset, supplemental to the article, is called: "list of genes printed on microarray slides." 1471-2229-7-5-s1.xls 663k. By using the BBGD database, researchers developed EST-based markers for mapping, and have identified a number of "candidate" cold tolerance genes that are highly expressed in blueberry flower buds after exposure to low temperatures. BBGD (http://bioinformatics.towson.edu/BBGD/) is a public online database, and was developed for blueberry genomics. BBGD is both a sequence and gene expression database: it stores both EST and microarray data, and allows scientists to correlate expression profiles with gene function. Presently, the main focus of the database is the identification of genes in blueberry that are significantly induced or suppressed after low temperature exposure. Data was collected sometime between 2000 and 2007 - exact dates are unknown.

The American cranberry (Vaccinium macrocarpon Ait.) is a recently domesticated, economically important, fruit crop with limited molecular resources. New genetic resources could accelerate genetic gain in cranberry through characterization of its genomic structure and by enabling molecular-assisted breeding strategies. To increase the availability of cranberry genomic resources, genotyping-by-sequencing (GBS) was used to discover and genotype thousands of single nucleotide polymorphisms (SNPs) within three interrelated cranberry full-sib populations. Additional simple sequence repeat (SSR) loci were added to the SNP datasets and used to construct bin maps for the parents of the populations, which were then merged to create the first high-density cranberry composite map containing 6073 markers (5437 SNPs and 636 SSRs) on 12 linkage groups (LGs) spanning 1124 cM. Interestingly, higher rates of recombination were observed in maternal than paternal gametes. The large number of markers in common (mean of 57.3) and the high degree of observed collinearity (mean Pair-wise Spearman rank correlations >0.99) between the LGs of the parental maps demonstrates the utility of GBS in cranberry for identifying polymorphic SNP loci that are transferable between pedigrees and populations in future trait-association studies. Furthermore, the high-density of markers anchored within the component maps allowed identification of segregation distortion regions, placement of centromeres on each of the 12 LGs, and anchoring of genomic scaffolds. Collectively, the results represent an important contribution to the current understanding of cranberry genomic structure and to the availability of molecular tools for future genetic research and breeding efforts in cranberry.

This data set contains 32 million annotated SNPs having an average SNP density of 30 SNPs per kb and 12 non-synonymous SNPs per gene model. These SNPs were identified from a genetically diverse, worldwide, collection of soybean germplasm representing wild, landrace, and improved cultivars. A combination of new and publicly available re-sequencing data was used in this analysis. The accession genotypes and their annotations are described in the manuscript titled: 'Analysis and characterization of 1500 diverse genome sequences as a versatile resource for post-genomics research'.

Risks of post-introduction evolution in insects introduced to control invasive pests have been discussed for some time, but little is known about responses to selection or genetic architectures of host adaptation and thus about the likelihood or rapidity of evolutionary shifts. We report here results on the response to selection and genetic architecture of parasitism of a sub-optimal, low-preference host species by an aphid parasitoid, Aphelinus rhamni, a candidate for introduction against the soybean aphid, Aphis glycines. The parasitoid was collected in Beijing, China, from the soybean aphid on a Rhamnus species. In the laboratory at the USDA-ARS, Newark, Delaware, we selected A. rhamni for increased parasitism of Rhopalsiphum padi by rearing the parasitoid on this aphid for three generations. We measured parasitism of R. padi at generations two and three, and at generation three, crossed and backcrossed parasitoids from the populations reared on R. padi with those from populations reared on Aphis glycines and compared parasitism of both R. padi and Aphis glycines among F1 and backcross females. Aphelinus rhamni responded rapidly to selection for parasitism of R. padi. Selection for R. padi parasitism reduced parasitism of Aphis glycines, the original host of A. rhamni. However, parasitism of R. padi did not increase from generation two to generation three of selection, suggesting reduced variance available for selection, which was indeed found. We tested the associations between 184 single nucleotide polymorphisms (SNP) and increased parasitism of R. padi and found 28 SNP loci, some of which were associated with increased and others with decreased parasitism of R. padi. We assembled and annotated the A. rhamni genome, mapped all SNP loci to contigs, and tested whether genes on contigs with SNP loci associated with parasitism were enriched for candidate genes or gene functions. We identified 80 genes on these contigs that mapped to 1.2 Mb of the 483 Mb genome of A. rhamni but found little enrichment of candidate genes or gene functions.

Gramene is a curated, open-source, integrated data resource for comparative functional genomics in crops and model plant species.

The Maize Genetics Cooperation Stock Center is operated by USDA/ARS, located at the University of Illinois, Urbana/Champaign, and integrated with the National Plant Germplasm System (NPGS). The center serves the maize research community by collecting, maintaining and distributing seeds of maize genetic stocks, and providing information about maize stocks and the mutations they carry through the Maize Genetics and Genomics Database (MaizeGDB). Users can browse to obtain detailed information about the following stocks: Chromosome 1 Markers Chromosome 2 Markers Chromosome 3 Markers Chromosome 4 Markers Chromosome 5 Markers Chromosome 6 Markers Chromosome 7 Markers Chromosome 8 Markers Chromosome 9 Markers Chromosome 10 Markers Unplaced Genes Multiple Genes Rare Isozyme B-Chromosome Alien Addition Trisomic Tetraploid Cytoplasmic-Sterile / Restorer Cytoplasmic Trait Toolkit B-A Translocations (Basic Set) B-A Translocations (Others) Inversion Reciprocal Translocations (wx1 and Wx1 marked) Stock records include information on availability, annotations, related records (genotypic variations, phenotypes), GRIN (Germplasm Resources Information Network) information, and offsite resources.

MaizeGDB is a community-oriented, long-term, federally funded informatics service to researchers focused on the crop plant and model organism Zea mays. Genomic, genetic, sequence, germplasm, gene product, metabolic pathways, functional characterization, literature reference, diversity, and expression are among the datatypes stored at MaizeGDB. At the project's website are custom interfaces enabling researchers to browse data and to seek out specific information matching explicit search criteria. First released in 1991 with the name MaizeDB, the Maize Genetics and Genomics Database, now MaizeGDB (since 2003), is funded, developed, and hosted by the USDA-ARS located at Ames, Iowa.

The data is in the form of genomic sequences deposited in a public database, growth curves, and bioinformatic analysis of sequences. This dataset is associated with the following publication: Henson, M., J. Santodomingo , P. Kourtev, R. Jensen, and D. Learman. Metabolic and genomic analysis elucidates strain-level variation in Microbacterium spp. isolated from chromate contaminated sediment. PeerJ. PeerJ Inc., Corte Madera, CA, USA, e1395, (2015).

PeanutBase (peanutbase.org) is the primary genetics and genomics database for cultivated peanut and its wild relatives. It houses information about genome sequences, genes and predicted functions, genetic maps, markers, links to germplasm resources, and maps of peanut germplasm origins. This resource is being developed for U.S. and International peanut researchers and breeders, with support from The Peanut Foundation and the many contributors that have made the Peanut Genomics Initiative possible. Funded by The Peanut Foundation as part of the Peanut Genomics Initiative. Additional support from USDA-ARS. Database developed and hosted by the USDA-ARS SoyBase and Legume Clade Database group at Ames, IA, with NCGR and other participants.