The Genome Database for Rosaceae (GDR, https://www.rosaceae.org) is an integrated web-based community database resource providing access to publicly available genomics, genetics and breeding data and data-mining tools to facilitate basic, translational and applied research in Rosaceae. The volume of data in GDR has increased greatly over the last 5 years. The GDR now houses multiple versions of whole genome assembly and annotation data from 14 species, made available by recent advances in sequencing technology. Annotated and searchable reference transcriptomes, RefTrans, combining peer-reviewed published RNA-Seq as well as EST datasets, are newly available for major crop species. Significantly more quantitative trait loci, genetic maps and markers are available in MapViewer, a new visualization tool that better integrates with other pages in GDR. Pathways can be accessed through the new GDR Cyc Pathways databases, and synteny among the newest genome assemblies from eight species can be viewed through the new synteny browser, SynView. Collated single-nucleotide polymorphism diversity data and phenotypic data from publicly available breeding datasets are integrated with other relevant data. Also, the new Breeding Information Management System allows breeders to upload, manage and analyze their private breeding data within the secure GDR server with an option to release data publicly.

Plants have evolved intimate interactions with soil microbes for a range of beneficial functions including nutrient acquisition, pathogen resistance and stress tolerance. Further understanding of this system is a promising way to advance sustainable agriculture by exploiting the versatile benefits offered by the plant microbiome. The rhizosphere is the interface between plant and soil, and functions as the first step of plant defense and root microbiome recruitment. It features a specialized microbial community, intensive microbe-plant and microbe-microbe interactions, and complex signal communication. To decipher the rhizosphere microbiome assembly of soybean (Glycine max), we comprehensively characterized the soybean rhizosphere microbial community using 16S rRNA gene sequencing and evaluated the structuring influence from both host genotype and soil source. Comparison of the soybean rhizosphere to bulk soil revealed significantly different microbiome composition, microbe-microbe interactions and metabolic capacity. Soil type and soybean genotype cooperatively modulated microbiome assembly with soil type predominantly shaping rhizosphere microbiome assembly while host genotype slightly tuned this recruitment process. The undomesticated progenitor species, Glycine soja, had higher rhizosphere diversity in both soil types tested in comparison to the domesticated soybean genotypes. Rhizobium, Novosphingobium, Phenylobacterium, Streptomyces, Nocardioides, etc. were robustly enriched in soybean rhizosphere irrespective of the soil tested. Co-occurrence network analysis revealed dominant soil type effects and genotype specific preferences for key microbe-microbe interactions. Functional prediction results demonstrated converged metabolic capacity in the soybean rhizosphere between soil types and among genotypes, with pathways related to xenobiotic degradation, plant-microbe interactions and nutrient transport being greatly enriched in the rhizosphere. This comprehensive comparison of the soybean microbiome between soil types and genotypes expands our understanding of rhizosphere microbe assembly in general and provides foundational information for soybean as a legume crop for this assembly process. The cooperative modulating role of the soil type and host genotype emphasizes the importance of integrated consideration of soil condition and plant genetic variability for future development and application of synthetic microbiomes. Additionally, the detection of the tuning role by soybean genotype in rhizosphere microbiome assembly provides a promising way for future breeding programs to integrate host traits participating in beneficial microbiota assembly.

The Genome Database for Rosaceae (GDR) is a central repository of curated and integrated genetics and genomics data of Rosaceae, an economically important family which includes apple, cherry, peach, pear, raspberry, rose and strawberry. GDR contains annotated databases of all publicly available Rosaceae ESTs, the genetically anchored peach physical map, Rosaceae genetic maps and comprehensively annotated markers and traits. The ESTs are assembled to produce unigene sets of each genus and the entire Rosaceae. Other annotations include putative function, microsatellites, open reading frames, single nucleotide polymorphisms, gene ontology terms and anchored map position where applicable. Most of the published Rosaceae genetic maps can be viewed and compared through CMap, the comparative map viewer. The peach physical map can be viewed using WebFPC/WebChrom, and also through our integrated GDR map viewer, which serves as a portal to the combined genetic, transcriptome and physical mapping information. ESTs, BACs, markers and traits can be queried by various categories and the search result sites are linked to the mapping visualization tools. GDR also provides online analysis tools such as a batch BLAST/FASTA server for the GDR datasets, a sequence assembly server and microsatellite and primer detection tools. GDR is available at http://www.rosaceae.org .

Forest trees are an unparalleled group of organisms in their combined ecological, economic and societal importance. With widespread distributions, predominantly random mating systems and large population sizes, most tree species harbour extensive genetic variation both within and among populations. At the same time, demographic processes associated with Pleistocene climate oscillations and land‐use change have affected contemporary range‐wide diversity and may impinge on the potential for future adaptation. Understanding how these adaptive and neutral processes have shaped the genomes of trees species is therefore central to their management and conservation. As for many other taxa, the advent of high‐throughput sequencing methods is expected to yield an understanding of the interplay between the genome and environment at a level of detail and depth not possible only a few years ago. An international conference entitled ‘Genomics and Forest Tree Genetics’ was held in May 2016, in Arcachon (France), and brought together forest geneticists with a wide range of research interests to disseminate recent efforts that leverage contemporary genomic tools to probe the population, quantitative and evolutionary genomics of trees. An important goal of the conference was to discuss how such data can be applied to both genome‐enabled breeding and the conservation of forest genetic resources under land use and climate change. Here, we report discoveries presented at the meeting and discuss how the ecological genomic toolkit can be used to address both basic and applied questions in tree biology.

The Cotton Microsatellite Database (CMD) http://www.cottonssr.org is a curated and integrated web-based relational database providing centralized access to publicly available cotton microsatellites, an invaluable resource for basic and applied research in cotton breeding. At present CMD contains publication, sequence, primer, mapping and homology data for nine major cotton microsatellite projects, collectively representing 5,484 microsatellites. In addition, CMD displays data for three of the microsatellite projects that have been screened against a panel of core germplasm. The standardized panel consists of 12 diverse genotypes including genetic standards, mapping parents, BAC donors, subgenome representatives, unique breeding lines, exotic introgression sources, and contemporary Upland cottons with significant acreage. A suite of online microsatellite data mining tools are accessible at CMD. These include an SSR server which identifies microsatellites, primers, open reading frames, and GC-content of uploaded sequences; BLAST and FASTA servers providing sequence similarity searches against the existing cotton SSR sequences and primers, a CAP3 server to assemble EST sequences into longer transcripts prior to mining for SSRs, and CMap, a viewer for comparing cotton SSR maps. The collection of publicly available cotton SSR markers in a centralized, readily accessible and curated web-enabled database provides a more efficient utilization of microsatellite resources and will help accelerate basic and applied research in molecular breeding and genetic mapping in Gossypium spp.

Background: Peach is being developed as a model organism for Rosaceae, an economically important family that includes fruits and ornamental plants such as apple, pear, strawberry, cherry, almond and rose. The genomics and genetics data of peach can play a significant role in the gene discovery and the genetic understanding of related species. The effective utilization of these peach resources, however, requires the development of an integrated and centralized database with associated analysis tools. Description: The Genome Database for Rosaceae (GDR) is a curated and integrated web-based relational database. GDR contains comprehensive data of the genetically anchored peach physical map, an annotated peach EST database, Rosaceae maps and markers and all publicly available Rosaceae sequences. Annotations of ESTs include contig assembly, putative function, simple sequence repeats, and anchored position to the peach physical map where applicable. Our integrated map viewer provides graphical interface to the genetic, transcriptome and physical mapping information. ESTs, BACs and markers can be queried by various categories and the search result sites are linked to the integrated map viewer or to the WebFPC physical map sites. In addition to browsing and querying the database, users can compare their sequences with the annotated GDR sequences via a dedicated sequence similarity server running either the BLAST or FASTA algorithm. To demonstrate the utility of the integrated and fully annotated database and analysis tools, we describe a case study where we anchored Rosaceae sequences to the peach physical and genetic map by sequence similarity. Conclusions: The GDR has been initiated to meet the major deficiency in Rosaceae genomics and genetics research, namely a centralized web database and bioinformatics tools for data storage, analysis and exchange. GDR can be accessed at http://www.genome.clemson.edu/gdr/.