Towards an open grapevine information system

The wild side of grape genomics

With broad genetic diversity and as a source of key agronomic traits, wild grape species (Vitis spp.) are crucial to enhance viticulture's climatic resilience and sustainability. This review discusses how recent breakthroughs in the genome assembly and analysis of wild grape species have led to discoveries on grape evolution, from wild species' adaptation to environmental stress to grape domestication. We detail how diploid chromosome-scale genomes from wild Vitis spp. have enabled the identification of candidate disease-resistance and flower sex determination genes and the creation of the first Vitis graph-based pangenome. Finally, we explore how wild grape genomics can impact grape research and viticulture, including aspects such as data sharing, the development of functional genomics tools, and the acceleration of genetic improvement.

Plant Reactome Knowledgebase: empowering plant pathway exploration and OMICS data analysis

Plant Reactome (https://plantreactome.gramene.org) is a freely accessible, comprehensive plant pathway knowledgebase. It provides curated reference pathways from rice (Oryza sativa) and gene-orthology-based pathway projections to 129 additional species, spanning single-cell photoautotrophs, non-vascular plants, and higher plants, thus encompassing a wide-ranging taxonomic diversity. Currently, Plant Reactome houses a collection of 339 reference pathways, covering metabolic and transport pathways, hormone signaling, genetic regulations of developmental processes, and intricate transcriptional networks that orchestrate a plant's response to abiotic and biotic stimuli. Beyond being a mere repository, Plant Reactome serves as a dynamic data discovery platform. Users can analyze and visualize omics data, such as gene expression, gene-gene interaction, proteome, and metabolome data, all within the rich context of plant pathways. Plant Reactome is dedicated to fostering data interoperability, upholding global data standards, and embracing the tenets of the Findable, Accessible, Interoperable and Re-usable (FAIR) data policy.

Genotype and phenotype data standardization, utilization and integration in the big data era for agricultural sciences

Large-scale genotype and phenotype data have been increasingly generated to identify genetic markers, understand gene function and evolution and facilitate genomic selection. These datasets hold immense value for both current and future studies, as they are vital for crop breeding, yield improvement and overall agricultural sustainability. However, integrating these datasets from heterogeneous sources presents significant challenges and hinders their effective utilization. We established the Genotype-Phenotype Working Group in November 2021 as a part of the AgBioData Consortium (https://www.agbiodata.org) to review current data types and resources that support archiving, analysis and visualization of genotype and phenotype data to understand the needs and challenges of the plant genomic research community. For 2021-22, we identified different types of datasets and examined metadata annotations related to experimental design/methods/sample collection, etc. Furthermore, we thoroughly reviewed publicly funded repositories for raw and processed data as well as secondary databases and knowledgebases that enable the integration of heterogeneous data in the context of the genome browser, pathway networks and tissue-specific gene expression. Based on our survey, we recommend a need for (i) additional infrastructural support for archiving many new data types, (ii) development of community standards for data annotation and formatting, (iii) resources for biocuration and (iv) analysis and visualization tools to connect genotype data with phenotype data to enhance knowledge synthesis and to foster translational research. Although this paper only covers the data and resources relevant to the plant research community, we expect that similar issues and needs are shared by researchers working on animals. Database URL: https://www.agbiodata.org.

Exploring Pan-Genomes: An Overview of Resources and Tools for Unraveling Structure, Function, and Evolution of Crop Genes and Genomes

The availability of multiple sequenced genomes from a single species made it possible to explore intra- and inter-specific genomic comparisons at higher resolution and build clade-specific pan-genomes of several crops. The pan-genomes of crops constructed from various cultivars, accessions, landraces, and wild ancestral species represent a compendium of genes and structural variations and allow researchers to search for the novel genes and alleles that were inadvertently lost in domesticated crops during the historical process of crop domestication or in the process of extensive plant breeding. Fortunately, many valuable genes and alleles associated with desirable traits like disease resistance, abiotic stress tolerance, plant architecture, and nutrition qualities exist in landraces, ancestral species, and crop wild relatives. The novel genes from the wild ancestors and landraces can be introduced back to high-yielding varieties of modern crops by implementing classical plant breeding, genomic selection, and transgenic/gene editing approaches. Thus, pan-genomic represents a great leap in plant research and offers new avenues for targeted breeding to mitigate the impact of global climate change. Here, we summarize the tools used for pan-genome assembly and annotations, web-portals hosting plant pan-genomes, etc. Furthermore, we highlight a few discoveries made in crops using the pan-genomic approach and future potential of this emerging field of study.

Genomic and Bioinformatic Resources for Perennial Fruit Species

In the post-genomic era, data management and development of bioinformatic tools are critical for the adequate exploitation of genomics data. In this review, we address the actual situation for the subset of crops represented by the perennial fruit species. The agronomical singularity of these species compared to plant and crop model species provides significant challenges on the implementation of good practices generally not addressed in other species. Studies are usually performed over several years in non-controlled environments, usage of rootstock is common, and breeders heavily rely on vegetative propagation. A reference genome is now available for all the major species as well as many members of the economically important genera for breeding purposes. Development of pangenome for these species is beginning to gain momentum which will require a substantial effort in term of bioinformatic tool development. The available tools for genome annotation and functional analysis will also be presented.

A Putative Effector LtCSEP1 from Lasiodiplodia theobromae Inhibits BAX-Triggered Cell Death and Suppresses Immunity Responses in Nicotiana benthamiana

Lasiodiplodia theobromae is a causal agent of grapevine trunk disease, and it poses a significant threat to the grape industry worldwide. Fungal effectors play an essential role in the interaction between plants and pathogens. However, few studies have been conducted to understand the functions of individual effectors in L. theobromae. In this study, we identified and characterized a candidate secreted effector protein, LtCSEP1, in L. theobromae. Gene expression analysis suggested that transcription of LtCSEP1 in L. theobromae was induced at the early infection stages in the grapevine. Yeast secretion assay revealed that LtCSEP1 contains a functional signal peptide. Transient expression of LtCSEP1 in Nicotiana benthamiana suppresses BAX-trigged cell death and significantly inhibits the flg22-induced PTI-associated gene expression. Furthermore, the ectopic expression of LtCSEP1 in N. benthamiana enhanced disease susceptibility to L. theobromae by downregulating the defense-related genes. These results demonstrated that LtCSEP1 is a potential effector of L. theobromae, which contributes to suppressing the plant’s defenses.

A COMPASS for VESPUCCI: A FAIR Way to Explore the Grapevine Transcriptomic Landscape

Successfully integrating transcriptomic experiments is a challenging task with the ultimate goal of analyzing gene expression data in the broader context of all available measurements, all from a single point of access. In its second major release VESPUCCI, the integrated database of gene expression data for grapevine, has been updated to be FAIR-compliant, employing standards and created with open-source technologies. It includes all public grapevine gene expression experiments from both microarray and RNA-seq platforms. Transcriptomic data can be accessed in multiple ways through the newly developed COMPASS GraphQL interface, while the expression values are normalized using different methodologies to flexibly satisfy different analysis requirements. Sample annotations are manually curated and use standard formats and ontologies. The updated version of VESPUCCI provides easy querying and analyzing of integrated grapevine gene expression (meta)data and can be seamlessly embedded in any analysis workflow or tools. VESPUCCI is freely accessible and offers several ways of interaction, depending on the specific goals and purposes and/or user expertise; an overview can be found at https://vespucci.readthedocs.io/.

Grapevine virome and production of healthy plants by somatic embryogenesis

Grapevine (Vitis spp.) is a widespread fruit tree hosting many viral entities that interact with the plant modifying its responses to the environment. The production of virus‐free plants is becoming increasingly crucial for the use of grapevine as a model species in different studies. Using high‐throughput RNA sequencing, the viromes of seven mother plants grown in a germplasm collection vineyard were sequenced. In addition to the viruses and viroids already detected in grapevine, we identified 13 putative new mycoviruses. The different spread among grapevine tissues collected in vineyard, greenhouse and in vitro conditions suggested a clear distinction between viruses/viroids and mycoviruses that can successfully be exploited for their identification. Mycoviruses were absent in in vitro cultures, while plant viruses and viroids were particularly accumulated in these plantlets. Somatic embryogenesis applied to the seven mother plants was effective in the elimination of the complete virome, including mycoviruses. However, different sanitization efficiencies for viroids and grapevine pinot gris virus were observed among genotypes. The absence of mycoviruses in in vitro plantlets, associated with the absence of all viral entities in somaclones, suggested that this regeneration technique is also effective to eradicate endophytic/epiphytic fungi, resulting in gnotobiotic or pseudo‐gnotobiotic plants.

Stress responses and epigenomic instability mark the loss of somatic embryogenesis competence in grapevine

Somatic embryogenesis (SE) represents the most appropriate tool for next-generation breeding methods in woody plants such as grapevine (Vitis vinifera L.). However, in this species, the SE competence is strongly genotype-dependent and the molecular basis of this phenomenon is poorly understood. We explored the genetic and epigenetic basis of SE in grapevine by profiling the transcriptome, epigenome, and small RNAome of undifferentiated, embryogenic, and non-embryogenic callus tissues derived from two genotypes differing in competence for SE, Sangiovese and Cabernet Sauvignon. During the successful formation of embryonic callus, we observed the upregulation of epigenetic-related transcripts and short interfering RNAs in association with DNA hypermethylation at transposable elements in both varieties. Nevertheless, the switch to nonembryonic development matched the incomplete reinforcement of transposon silencing, and the evidence of such effect was more apparent in the recalcitrant Cabernet Sauvignon. Transcriptomic differences between the two genotypes were maximized already at early stage of culture where the recalcitrant variety expressed a broad panel of genes related to stress responses and secondary metabolism. Our data provide a different angle on the SE molecular dynamics that can be exploited to leverage SE as a biotechnological tool for fruit crop breeding.

Building a successful international research community through data sharing: The case of the Wheat Information System (WheatIS)

The International Wheat Information System (WheatIS) Expert Working Group (EWG) was initiated in 2012 under the Wheat Initiative with a broad range of contributing organizations. The mission of the WheatIS EWG was to create an informational infrastructure, establish data standards, and build a single portal that allows search, retrieval, and display of globally distributed wheat data sets that are indexed in standard data formats at servers around the world. The web portal at WheatIS.org was released publicly in 2015, and by 2020, it expanded to 8 geographically-distributed nodes and around 20 organizations under its umbrella.  

In this paper, we present our experience, the challenges we faced, and the answer we brought for establishing an international research community to build an informational infrastructure. Our hope is that our experience with building wheatis.org will guide current and future research communities to facilitate institutional and international challenges to create global tools and resources to help their respective scientific communities.

The Grapevine E3 Ubiquitin Ligase VriATL156 Confers Resistance against the Downy Mildew Pathogen Plasmopara viticola

Downy mildew, caused by Plasmopara viticola, is one of the most severe diseases of grapevine (Vitis vinifera L.). Genetic resistance is an effective and sustainable control strategy, but major resistance genes (encoding receptors for specific pathogen effectors) introgressed from wild Vitis species, although effective, may be non-durable because the pathogen can evolve to avoid specific recognition. Previous transcriptomic studies in the resistant species Vitis riparia highlighted the activation of signal transduction components during infection. The transfer of such components to V. vinifera might confer less specific and therefore more durable resistance. Here, we describe the generation of transgenic V. vinifera lines constitutively expressing the V. riparia E3 ubiquitin ligase gene VriATL156. Phenotypic and molecular analysis revealed that the transgenic plants were less susceptible to P. viticola than vector-only controls, confirming the role of this E3 ubiquitin ligase in the innate immune response. Two independent transgenic lines were selected for detailed analysis of the resistance phenotype by RNA-Seq and microscopy, revealing the profound reprogramming of transcription to achieve resistance that operates from the earliest stages of pathogen infection. The introduction of VriATL156 into elite grapevine cultivars could therefore provide an effective and sustainable control measure against downy mildew.

Plant Reactome: a knowledgebase and resource for comparative pathway analysis

Plant Reactome (https://plantreactome.gramene.org) is an open-source, comparative plant pathway knowledgebase of the Gramene project. It uses Oryza sativa (rice) as a reference species for manual curation of pathways and extends pathway knowledge to another 82 plant species via gene-orthology projection using the Reactome data model and framework. It currently hosts 298 reference pathways, including metabolic and transport pathways, transcriptional networks, hormone signaling pathways, and plant developmental processes. In addition to browsing plant pathways, users can upload and analyze their omics data, such as the gene-expression data, and overlay curated or experimental gene-gene interaction data to extend pathway knowledge. The curation team actively engages researchers and students on gene and pathway curation by offering workshops and online tutorials. The Plant Reactome supports, implements and collaborates with the wider community to make data and tools related to genes, genomes, and pathways Findable, Accessible, Interoperable and Re-usable (FAIR).

Gramene 2018: unifying comparative genomics and pathway resources for plant research

Gramene (http://www.gramene.org) is a knowledgebase for comparative functional analysis in major crops and model plant species. The current release, #54, includes over 1.7 million genes from 44 reference genomes, most of which were organized into 62,367 gene families through orthologous and paralogous gene classification, whole-genome alignments, and synteny. Additional gene annotations include ontology-based protein structure and function; genetic, epigenetic, and phenotypic diversity; and pathway associations. Gramene's Plant Reactome provides a knowledgebase of cellular-level plant pathway networks. Specifically, it uses curated rice reference pathways to derive pathway projections for an additional 66 species based on gene orthology, and facilitates display of gene expression, gene-gene interactions, and user-defined omics data in the context of these pathways. As a community portal, Gramene integrates best-of-class software and infrastructure components including the Ensembl genome browser, Reactome pathway browser, and Expression Atlas widgets, and undergoes periodic data and software upgrades. Via powerful, intuitive search interfaces, users can easily query across various portals and interactively analyze search results by clicking on diverse features such as genomic context, highly augmented gene trees, gene expression anatomograms, associated pathways, and external informatics resources. All data in Gramene are accessible through both visual and programmatic interfaces.

Review: New sensors and data-driven approaches-A path to next generation phenomics

At the 4th International Plant Phenotyping Symposium meeting of the International Plant Phenotyping Network (IPPN) in 2016 at CIMMYT in Mexico, a workshop was convened to consider ways forward with sensors for phenotyping. The increasing number of field applications provides new challenges and requires specialised solutions. There are many traits vital to plant growth and development that demand phenotyping approaches that are still at early stages of development or elude current capabilities. Further, there is growing interest in low-cost sensor solutions, and mobile platforms that can be transported to the experiments, rather than the experiment coming to the platform. Various types of sensors are required to address diverse needs with respect to targets, precision and ease of operation and readout. Converting data into knowledge, and ensuring that those data (and the appropriate metadata) are stored in such a way that they will be sensible and available to others now and for future analysis is also vital. Here we are proposing mechanisms for "next generation phenomics" based on our learning in the past decade, current practice and discussions at the IPPN Symposium, to encourage further thinking and collaboration by plant scientists, physicists and engineering experts.

Long Non-coding RNAs Coordinate Developmental Transitions and Other Key Biological Processes in Grapevine

Long non-coding RNAs (lncRNAs) are transcripts >200 nucleotides that have prominently surfaced as dynamic regulatory molecules. Using computational approaches, we identified and characterized 56,441 lncRNAs in grapevine (Vitis vinifera) by harnessing RNA-seq data from 10 developmental stages of leaf, inflorescence, and berry tissues. We conducted differential expression analysis and determined tissue- and developmental stage-specificity of lncRNAs in grapevine, which indicated their spatiotemporal regulation. Functional annotation using co-expression analysis revealed their involvement in regulation of developmental transitions in sync with transcription factors (TFs). Further, pathway enrichment analysis revealed lncRNAs associated with biosynthetic and secondary metabolic pathways. Additionally, we identified 115, 560, and 133 lncRNAs as putative miRNA precursors, targets, and endogenous target mimics, respectively, which provided an insight into the interplay of regulatory RNAs. We also explored lncRNA-mediated regulation of extra-chromosomal genes–i.e., mitochondrial and chloroplast coding sequences and observed their involvement in key biological processes like ‘photosynthesis’ and ‘oxidative phosphorylation’. In brief, these transcripts coordinate important biological functions via interactions with both coding and non-coding RNAs as well as TFs in grapevine. Our study would facilitate future experiments in unraveling regulatory mechanisms of development in this fruit crop of economic importance.

How to integrate wet lab and bioinformatics procedures for wine DNA admixture analysis and compositional profiling: Case studies and perspectives

The varietal authentication of wines is fundamental for assessing wine quality, and it is part of its compositional profiling. The availability of historical, cultural and chemical composition information is extremely important for quality evaluation. DNA-based techniques are a powerful tool for proving the varietal composition of a wine. SSR-amplification of genomic residual Vitis vinifera DNA, namely Wine DNA Fingerprinting (WDF) is able to produce strong, analytical evidence concerning the monovarietal nature of a wine, and for blended wines by generating the probability of the presence/absence of a certain variety, all in association with a dedicated bioinformatics elaboration of genotypes associated with possible varietal candidates. Together with WDF we could exploit Bioinformatics techniques, due to the number of grape genomes grown. In this paper, the use of WDF and the development of a bioinformatics tool for allelic data validation, retrieved from the amplification of 7 to 10 SSRs markers in the Vitis vinifera genome, are reported. The wines were chosen based on increasing complexity; from monovarietal, experimental ones, to commercial monovarietals, to blended commercial wines. The results demonstrate that WDF, after calculation of different distance matrices and Neighbor-Joining input data, followed by Principal Component Analysis (PCA) can effectively describe the varietal nature of wines. In the unknown blended wines the WDF profiles were compared to possible varietal candidates (Merlot, Pinot Noir, Cabernet Sauvignon and Zinfandel), and the output graphs show the most probable varieties used in the blend as closeness to the tested wine. This pioneering work should be meant as to favor in perspective the multidisciplinary building-up of on-line databanks and bioinformatics toolkits on wine. The paper concludes with a discussion on an integrated decision support system based on bioinformatics, chemistry and cultural data to assess wine quality.

Computational aspects underlying genome to phenome analysis in plants

Recent advances in genomics technologies have greatly accelerated the progress in both fundamental plant science and applied breeding research. Concurrently, high-throughput plant phenotyping is becoming widely adopted in the plant community, promising to alleviate the phenotypic bottleneck. While these technological breakthroughs are significantly accelerating quantitative trait locus (QTL) and causal gene identification, challenges to enable even more sophisticated analyses remain. In particular, care needs to be taken to standardize, describe and conduct experiments robustly while relying on plant physiology expertise. In this article, we review the state of the art regarding genome assembly and the future potential of pangenomics in plant research. We also describe the necessity of standardizing and describing phenotypic studies using the Minimum Information About a Plant Phenotyping Experiment (MIAPPE) standard to enable the reuse and integration of phenotypic data. In addition, we show how deep phenotypic data might yield novel trait-trait correlations and review how to link phenotypic data to genomic data. Finally, we provide perspectives on the golden future of machine learning and their potential in linking phenotypes to genomic features.

Dealing with multi-source and multi-scale information in plant phenomics: the ontology-driven Phenotyping Hybrid Information System

Phenomic datasets need to be accessible to the scientific community. Their reanalysis requires tracing relevant information on thousands of plants, sensors and events. The open-source Phenotyping Hybrid Information System (PHIS) is proposed for plant phenotyping experiments in various categories of installations (field, glasshouse). It unambiguously identifies all objects and traits in an experiment and establishes their relations via ontologies and semantics that apply to both field and controlled conditions. For instance, the genotype is declared for a plant or plot and is associated with all objects related to it. Events such as successive plant positions, anomalies and annotations are associated with objects so they can be easily retrieved. Its ontology-driven architecture is a powerful tool for integrating and managing data from multiple experiments and platforms, for creating relationships between objects and enriching datasets with knowledge and metadata. It interoperates with external resources via web services, thereby allowing data integration into other systems; for example, modelling platforms or external databases. It has the potential for rapid diffusion because of its ability to integrate, manage and visualize multi-source and multi-scale data, but also because it is based on 10 yr of trial and error in our groups.

Involving community in genes and pathway curation

Biocuration plays a crucial role in building databases and complex systems-level platforms required for processing, annotating and analyzing ‘Big Data’ in biology. However, biocuration efforts cannot keep pace with a dramatic increase in the production of omics data; this presents one of the bottlenecks in genomics. In two pathway curation jamborees, Plant Reactome curators tested strategies for introducing researchers to pathway curation tools, harnessing biologists’ expertise in curating plant pathways and developing a network of community biocurators. We summarize the strategy, workflow and outcomes of these exercises, and discuss the role of community biocuration in advancing databases and genomic resources.

Applying FAIR Principles to Plant Phenotypic Data Management in GnpIS

GnpIS is a data repository for plant phenomics that stores whole field and greenhouse experimental data including environment measures. It allows long-term access to datasets following the FAIR principles: Findable, Accessible, Interoperable, and Reusable, by using a flexible and original approach. It is based on a generic and ontology driven data model and an innovative software architecture that uncouples data integration, storage, and querying. It takes advantage of international standards including the Crop Ontology, MIAPPE, and the Breeding API. GnpIS allows handling data for a wide range of species and experiment types, including multiannual perennial plants experimental network or annual plant trials with either raw data, i.e., direct measures, or computed traits. It also ensures the integration and the interoperability among phenotyping datasets and with genotyping data. This is achieved through a careful curation and annotation of the key resources conducted in close collaboration with the communities providing data. Our repository follows the Open Science data publication principles by ensuring citability of each dataset. Finally, GnpIS compliance with international standards enables its interoperability with other data repositories hence allowing data links between phenotype and other data types. GnpIS can therefore contribute to emerging international federations of information systems.

realDB: a genome and transcriptome resource for the red algae (phylum Rhodophyta)

With over 6000 species in seven classes, red algae (Rhodophyta) have diverse economic, ecological, experimental and evolutionary values. However, red algae are usually absent or rare in comparative analyses because genomic information of this phylum is often under-represented in various comprehensive genome databases. To improve the accessibility to the ome data and omics tools for red algae, we provided 10 genomes and 27 transcriptomes representing all seven classes of Rhodophyta. Three genomes and 18 transcriptomes were de novo assembled and annotated in this project. User-friendly BLAST suit, Jbrowse tools and search system were developed for online analyses. Detailed introductions to red algae taxonomy and the sequencing status are also provided. In conclusion, realDB (realDB.algaegenome.org) provides a platform covering the most genome and transcriptome data for red algae and a suite of tools for online analyses, and will attract both red algal biologists and those working on plant ecology, evolution and development.

Database URL: http://realdb.algaegenome.org/

Plant Phenomics, From Sensors to Knowledge

Major improvements in crop yield are needed to keep pace with population growth and climate change. While plant breeding efforts have greatly benefited from advances in genomics, profiling the crop phenome (i.e., the structure and function of plants) associated with allelic variants and environments remains a major technical bottleneck. Here, we review the conceptual and technical challenges facing plant phenomics. We first discuss how, given plants' high levels of morphological plasticity, crop phenomics presents distinct challenges compared with studies in animals. Next, we present strategies for multi-scale phenomics, and describe how major improvements in imaging, sensor technologies and data analysis are now making high-throughput root, shoot, whole-plant and canopy phenomic studies possible. We then suggest that research in this area is entering a new stage of development, in which phenomic pipelines can help researchers transform large numbers of images and sensor data into knowledge, necessitating novel methods of data handling and modelling. Collectively, these innovations are helping accelerate the selection of the next generation of crops more sustainable and resilient to climate change, and whose benefits promise to scale from physiology to breeding and to deliver real world impact for ongoing global food security efforts.

The Sequenced Angiosperm Genomes and Genome Databases

Angiosperms, the flowering plants, provide the essential resources for human life, such as food, energy, oxygen, and materials. They also promoted the evolution of human, animals, and the planet earth. Despite the numerous advances in genome reports or sequencing technologies, no review covers all the released angiosperm genomes and the genome databases for data sharing. Based on the rapid advances and innovations in the database reconstruction in the last few years, here we provide a comprehensive review for three major types of angiosperm genome databases, including databases for a single species, for a specific angiosperm clade, and for multiple angiosperm species. The scope, tools, and data of each type of databases and their features are concisely discussed. The genome databases for a single species or a clade of species are especially popular for specific group of researchers, while a timely-updated comprehensive database is more powerful for address of major scientific mysteries at the genome scale. Considering the low coverage of flowering plants in any available database, we propose construction of a comprehensive database to facilitate large-scale comparative studies of angiosperm genomes and to promote the collaborative studies of important questions in plant biology.

MGH: a genome hub for the medicinal plant maca (Lepidium meyenii)

Maca (Lepidium meyenii), a Brassicaceae herb plant originated from Andean mountains, has attracted wide interests due to its unique health benefits in reproduction and fertility. Because of its adaptation to the 4000 m high-altitude harsh environment, maca is attracting more and more attention from both crop breeders and basic biologists. After our previous release of the maca genome sequence, there's a growing need to store, query, analyze and integrate various maca resources efficiently. Here, we created Maca Genome Hub (MGH), a genomics and genetics database of maca. Currently, the MGH V1.0 harbors the genome sequence, predicted coding sequences and protein sequences, various annotations, markers and expression data. For the maca research community, we also provided the publications, researchers and related news. MGH is designed to enable users' easy access to analyze, retrieve and visualize the genomic or genetic information through a series of online tools, including the Basic Local Alignment Search Tool, the JBrowse, the query system, the synteny tool and the data downloads. These integrated heterogeneous data, tools and interfaces in MGH allow efficient mining of the latest genomics and genetics data. We hope that MGH will accelerate the research and development in maca.

Whole-genome sequencing and SNV genotyping of 'Nebbiolo' (Vitis vinifera L.) clones

‘Nebbiolo’ (Vitis vinifera) is among the most ancient and prestigious wine grape varieties characterised by a wide genetic variability exhibited by a high number of clones (vegetatively propagated lines of selected mother plants). However, limited information is available for this cultivar at the molecular and genomic levels. The whole-genomes of three ‘Nebbiolo’ clones (CVT 71, CVT 185 and CVT 423) were re-sequenced and a de novo transcriptome assembly was produced. Important remarks about the genetic peculiarities of ‘Nebbiolo’ and its intra-varietal variability useful for clonal identification were reported. In particular, several varietal transcripts identified for the first time in ‘Nebbiolo’ were disease resistance genes and single-nucleotide variants (SNVs) identified in ‘Nebbiolo’, but not in other cultivars, were associated with genes involved in the stress response. Ten newly discovered SNVs were successfully employed to identify some periclinal chimeras and to classify 98 ‘Nebbiolo’ clones in seven main genotypes, which resulted to be linked to the geographical origin of accessions. In addition, for the first time it was possible to discriminate some ‘Nebbiolo’ clones from the others.

Patterns of genomic and phenomic diversity in wine and table grapes

Grapes are one of the most economically and culturally important crops worldwide, and they have been bred for both winemaking and fresh consumption. Here we evaluate patterns of diversity across 33 phenotypes collected over a 17-year period from 580 table and wine grape accessions that belong to one of the world's largest grape gene banks, the grape germplasm collection of the United States Department of Agriculture. We find that phenological events throughout the growing season are correlated, and quantify the marked difference in size between table and wine grapes. By pairing publicly available historical phenotype data with genome-wide polymorphism data, we identify large effect loci controlling traits that have been targeted during domestication and breeding, including hermaphroditism, lighter skin pigmentation and muscat aroma. Breeding for larger berries in table grapes was traditionally concentrated in geographic regions where Islam predominates and alcohol was prohibited, whereas wine grapes retained the ancestral smaller size that is more desirable for winemaking in predominantly Christian regions. We uncover a novel locus with a suggestive association with berry size that harbors a signature of positive selection for larger berries. Our results suggest that religious rules concerning alcohol consumption have had a marked impact on patterns of phenomic and genomic diversity in grapes.