D1128–D1136 Nucleic Acids Research, 2019, Vol. 47, Database issue Published online 13 October 2018 doi: 10.1093/nar/gky944 Cucurbit Genomics Database (CuGenDB): a central portal for comparative and functional genomics of cucurbit crops Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 Yi Zheng1 , Shan Wu1 , Yang Bai1 , Honghe Sun1,2 , Chen Jiao1 , Shaogui Guo1,2 , Kun Zhao1 , Jose Blanca 3 , Zhonghua Zhang4 , Sanwen Huang4,5 , Yong Xu2 , Yiqun Weng6,7 , Michael Mazourek8 , Umesh K. Reddy9 , Kaori Ando10 , James D. McCreight10 , Arthur A. Schaffer11 , Joseph Burger12 , Yaakov Tadmor12 , Nurit Katzir12 , Xuemei Tang1 , Yang Liu1,13 , James J. Giovannoni1,14 , Kai-Shu Ling15 , W. Patrick Wechter15 , Amnon Levi15 , Jordi Garcia-Mas16,17 , Rebecca Grumet18 and Zhangjun Fei 1,14,* 1 Boyce Thompson Institute, Cornell University, Ithaca, NY 14853, USA, 2 National Engineering Research Center for Vegetables, Beijing Academy of Agriculture and Forestry Sciences, Key Laboratory of Biology and Genetic Improvement of Horticultural Crops (North China), Beijing Key Laboratory of Vegetable Germplasm Improvement, Beijing 100097, China, 3 Institute for the Conservation and Breeding of Agricultural Biodiversity (COMAV-UPV), Universitat Politècnica de València, Valencia 46022, Spain, 4 Key Laboratory of Biology and Genetic Improvement of Horticultural Crops of the Ministry of Agriculture, Sino-Dutch Joint Laboratory of Horticultural Genomics, Institute of Vegetables and Flowers, Chinese Academy of Agricultural Sciences, Beijing 100081, China, 5 Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, Shenzhen, Guangdong 518124, China, 6 U.S. Department of Agriculture-Agricultural Research Service, Vegetable Crops Research Unit, Madison, WI 53706, USA, 7 Department of Horticulture, University of Wisconsin, Madison, WI 53706, USA, 8 Plant Breeding and Genetics Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA, 9 Department of Biology, West Virginia State University, Institute, WV 25112, USA, 10 U.S. Department of Agriculture-Agricultural Research Service, Crop Improvement and Protection Research Unit, Salinas, CA 93905, USA, 11 Plant Science Institute, Agricultural Research Organization, The Volcani Center, P.O.B. 6, Bet-Dagan 50250, Israel, 12 Plant Science Institute, Agricultural Research Organization, Newe Yaar Research Center, Ramat Yishai 30095, Israel, 13 Horticulture Section, School of Integrative Plant Science, Cornell University, Ithaca, NY 14853, USA, 14 U.S. Department of Agriculture-Agricultural Research Service, Robert W. Holley Center for Agriculture and Health, Ithaca, NY 14853, USA, 15 U.S. Department of Agriculture-Agricultural Research Service, U.S. Vegetable Laboratory, 2700 Savannah Highway, Charleston, SC 29414, USA, 16 Centre for Research in Agricultural Genomics CSIC-IRTA-UAB-UB, Barcelona 08193, Spain, 17 Institut de Recerca i Tecnologia Agroalimentàries, Barcelona 08193, Spain and 18 Department of Horticulture, Michigan State University, East Lansing, MI 48824, USA Received September 05, 2018; Revised September 27, 2018; Editorial Decision September 28, 2018; Accepted October 04, 2018 ABSTRACT we have developed the Cucurbit Genomics Database (CuGenDB; http://cucurbitgenomics.org) using the The Cucurbitaceae family (cucurbit) includes several Tripal toolkit. The database currently contains all economically important crops, such as melon, cu- available genome and expressed sequence tag (EST) cumber, watermelon, pumpkin, squash and gourds. sequences, genetic maps, and transcriptome pro- During the past several years, genomic and genetic files for cucurbit species, as well as sequence an- data have been rapidly accumulated for cucurbits. To notations, biochemical pathways and comparative store, mine, analyze, integrate and disseminate these genomic analysis results such as synteny blocks large-scale datasets and to provide a central portal and homologous gene pairs between different cu- for the cucurbit research and breeding community, curbit species. A set of analysis and visualization * To whom correspondence should be addressed. Tel: +1 607 2543234; Fax: +1 607 2541242; Email: zf25@cornell.edu C The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com Nucleic Acids Research, 2019, Vol. 47, Database issue D1129 tools and user-friendly query interfaces have been resources of cucurbits including genetic maps, genomes, implemented in the database to facilitate the usage gene models, and functional annotations. Recently, Cu- of these large-scale data by the community. In par- GenDB has been rebuilt using Tripal (16), a toolkit for ticular, two new tools have been developed in the construction of online genomic and genetic databases database, a ‘SyntenyViewer’ to view genome synteny by integrating the GMOD Chado database schema (17) and Drupal (https://www.drupal.org/), a popular Content Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 between different cucurbit species and an ‘RNA-Seq’ Management Systems (CMS). Tripal has been used to module to analyze and visualize gene expression implement a number of widely used databases such as profiles. Both tools have been packed as Tripal exten- Genome Database for Rosaceae (18), CottonGen (19) and sion modules that can be adopted in other genomics Coffee Genome Hub (20). Furthermore, we have generated databases developed using the Tripal system. comprehensive functional annotations for all cucurbit gene models, identified synteny blocks and homologous genes among different cucurbits, incorporated expression profiles INTRODUCTION based on public RNA-Seq data, and developed new mod- The Cucurbitaceae family (cucurbit) includes several eco- ules in CuGenDB to analyze and visualize comparative nomically important vegetable and fruit crops, such as genomics and expression datasets of different cucurbit cucumber (Cucumis sativus L.), melon (C. melo L.), wa- species. termelon (Citrullus lanatus (Thunb.) Matsum. & Nakai), pumpkin/squash (Cucurbita spp.), bottle gourd (Lagenaria siceraria) and bitter gourd (Momordica charantia). In 2016, DATABASE CONTENTS AND FEATURES the agricultural production of cucurbits utilized 11 million Genome sequences and gene annotations hectares of land, and yielded 256 million tons of vegeta- bles and fruits (http://faostat.fao.org). In addition to be- Currently CuGenDB contains a total of 10 publicly avail- ing used as vegetables and fruits, cucurbit crops can also able high-quality reference genome sequences of cucur- be used for medicine, containers, musical instruments and bits including two cultivated cucumbers (C. sativus L. var. decoration (1). Moreover, several species such as pumpkin sativus cv. 9930 and cv. Gy14), one wild cucumber (C. and bottle gourd have been used as rootstocks for other sativus var. hardwickii PI 183967), one cultivated melon cucurbit crops in order to enhance tolerance to soil-borne (C. melo L. cv. DHL92), two cultivated watermelons (C. diseases and abiotic stresses and to improve fruit yield and lanatus subsp. vulgaris cv. 97103 and cv. Charleston Gray), quality (2). Furthermore, the cucurbit species have long three cultivated Cucurbita species (C. maxima cv. Rimu, C. served as model systems for studies of fundamental biolog- moschata cv. Rifu, and C. pepo cv. MU-CU-16), and one ical processes such as fruit ripening (3), sex determination cultivated bottle gourd (Lagenaria siceraria cv. USVL1VR- (4), and vascular development (5). In addition, both xylem Ls) (7–14). Seven of the 10 genomes were first released in and phloem sap of cucurbits can be readily collected for CuGenDB, while the genome sequences of cultivated cu- studies on long-distance signaling events (6). cumber Gy14, melon DHL92, and zucchini MU-CU-16 are Due to the rapid advances in sequencing technologies, downloaded from phytozome (https://phytozome.jgi.doe. high-quality reference genome sequences of a number of gov), MELONOMICS (https://www.melonomics.net/), and cucurbit crops have been generated and released (7–14). CucurbiGen (https://cucurbigene.upv.es), respectively. Cu- Together with large volumes of transcriptome and genetic GenDB provides a feature page for each cucurbit genome, data generated from a variety of studies, a database is which contains various sections of information and a sub- needed to store, mine, analyze, and disseminate these menu to access both the genome data and bioinformatics large-scale datasets and to provide a central portal for analysis tools. The information sections provide basic in- the cucurbit research and breeding community. Sev- formation regarding the sequenced material such as genus, eral genomics and functional genomics databases have species, cultivar and common name, and the genome such been developed for cucurbit crops including Cucumber as the number of predicted genes, the description of genome Genome Database (http://cucumber.genomics.org.cn), assembly and the list of related publications, where avail- MELONOMICS (https://www.melonomics.net/), able. The submenu provides links to a pathway database, a MeloGene (http://melogene.upv.es), CucurbiGen genome browser, an FTP site for downloading genome and (https://cucurbigene.upv.es/) and Melonet-DB gene sequences and annotations, and bioinformatics tools (http://gene.melonet-db.jp; (15)). These databases, de- such as BLAST, batch query and basic search functions. spite being very useful, are limited to a specific cucurbit A total of 265 334 protein-coding genes have been pre- species, e.g. cucumber or melon, or a specific data type, e.g., dicted from these 10 genomes and included in the database. genome sequences or gene expression, and lack functions A standard and unified procedure has been developed to for comparative genomics and functional genomics, and comprehensively annotate predicted protein-coding genes. comprehensive integration of different data types. To First, protein sequences of the predicted genes are com- facilitate the usage and application of genomic resources pared against the GenBank non-redundant protein (nr), for cucurbit research and breeding, we have developed UniProt (TrEMBL and SwissProt), and Arabidopsis pro- a family-wide cucurbit genomics database (CuGenDB; tein databases using the BLAST program with an E-value http://cucurbitgenomics.org). CuGenDB was first released cutoff of 1e-4. The protein sequences are further compared in 2007 with only expressed sequence tag (EST) and unigene against the InterPro database using InterProScan (21) to data and has since integrated rich genomics and genetics identify functional protein domains. The BLAST results D1130 Nucleic Acids Research, 2019, Vol. 47, Database issue against the nr database and the identified InterPro do- dicted protein-coding genes, CuGenDB also provides a fea- mains are fed to the Blast2GO program (22) for assigning ture page for each EST or unigene to list the related se- gene ontology (GO) terms to protein-coding genes, and the quence and annotation information. In addition, similar to BLAST results against the UniProt and Arabidopsis pro- the genome feature page, for the EST and unigene collec- tein databases are loaded into the AHRD program (https: tion of each cucurbit species, the database provides a fea- //github.com/groupschoof/AHRD) to assign concise, infor- ture page containing related information and a submenu to Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 mative and precise functional descriptions of genes. The access the data and analysis tools. top BLAST hits (homologs), GO terms and InterPro do- mains assigned to each of the protein-coding genes have Gene expression profiles been imported into CuGenDB using Tripal Analysis Ex- tension Modules (16). The functional descriptions gener- We have collected all available RNA-Seq data from NCBI ated by AHRD are loaded into the database using an in- Sequence Read Archive (SRA) for the cucurbit species house Perl script. Each gene has a detailed feature page in that have available reference genome sequences. A unified the database that contains all the related sequence and an- pipeline for RNA-Seq data processing and analysis has been notation information; the gene feature page is divided into applied to these RNA-Seq datasets. Briefly, raw RNA-Seq different sections based on the content types (Figure 1). reads are processed to remove adaptor and low-quality se- quences using Trimmomatic v0.32 (26), and trimmed reads shorter than 80% of their original length are discarded. Synteny blocks and homologous genes The remaining high-quality reads are aligned to the SILVA We have identified synteny blocks and homologous gene rRNA database (27) using Bowtie v1.1.2 (28) allowing up pairs within the synteny blocks for all pairwise comparisons to 3 mismatches, and the mapped reads are removed. The of the cucurbit genomes (currently 45 comparisons between final cleaned reads or read pairs are aligned to the corre- 10 different genomes), as well as within each genome. Pro- sponding genome using HISAT (29) allowing up to two mis- tein sequences are first aligned against each other (pairwise matches. Raw counts are then derived for each predicted comparisons) or against themselves (within each genome) gene model and normalized to FPKM (fragments per kilo- using BLASTP with an E-value cutoff of 1e–05 and a max- base of exon per million mapped fragments). Gene expres- imum of five alignments. Based on the BLASTP results, sion profiles for a specific gene can be accessed under the synteny blocks are determined using MCScanX (23) with ‘Gene Expression’ section of the gene feature page described default parameters. In total, 36,051 synteny blocks and 1 above (Figure 1), where after selecting an RNA-Seq project, 106 351 homologous gene pairs have been identified and a histogram showing expression profiles across different ex- stored in CuGenDB. As shown in Figure 1, a ‘Synteny’ sec- perimental conditions/tissues is displayed (Figure 1). tion has been included in the gene feature page to display To import these expression data (raw counts and FPKM) all available synteny blocks and homologous gene pairs re- and the associated meta-information into CuGenDB, we lated to a specific gene. Each synteny block is further linked have developed two Tripal extension modules, ‘SRA’ and to the page that lists all genes, including homologous gene ‘RNA-Seq’. The ‘SRA’ module is a mimic of the SRA pairs located in the syntenic region, and contains an image database but does not require the storage of raw sequencing to display homologous gene pairs, which is generated by the files. The main purpose of this module is to provide a man- ‘SyntenyViewer’ module described below. agement system for the collected project, sample, and exper- iment information. The average expression values and the standard deviation from biological replicates are calculated ESTs and unigenes for each gene and loaded into CuGenDB using the ‘RNA- Approximately 1.74 million EST sequences have been col- Seq’ extension module. The home page of ‘RNA-Seq’ lists lected in CuGenDB for four cucurbit species, among which all collected projects with mouse-over descriptions. 129,240, 513,801, 588,800, and 508,456 are from melon, cucumber, watermelon, and Cucurbita pepo, respectively. Genetic maps These EST sequences are first screened against the NCBI A total of 21 published genetic maps have been collected for UniVec database (http://www.ncbi.nlm.nih.gov/VecScreen/ cucurbit species, including 15 for melon, four for cucumber, UniVec.html), Escherichia coli genome and rRNA se- and two for watermelon. The map view and search func- quences using SeqClean (http://sourceforge.net/projects/ tions in the CuGenDB database have been developed us- seqclean/) to remove possible contaminations. The cleaned ing the CMap module from the GMOD project, which is EST sequences from each species are independently assem- a genetic extensible web-based comparative map viewer for bled into unigenes using the iAssembler program v1.3.3 displaying and comparing genetic and physical maps (30). (24), resulting in a total of 24 444, 93 903, 75 068 and Currently, we are in the process of implementing the Tri- 136 038 unigenes for melon, cucumber, watermelon, and C. palMAP extension module (https://tripal.info/extensions/ pepo, respectively. Cleaned ESTs and assembled unigenes modules/tripalmap) in CuGenDB to replace CMap for are mapped to the corresponding genomes of the same viewing and managing genetic maps. species using GMAP (25). The relationship between uni- genes and gene models are established if they are mapped Biochemical pathways to same locations. The unigenes are comprehensively an- notated using the same procedure for annotating predicted We use PathwayTools (31) to predict biochemical pathways protein-coding genes as described above. As with the pre- for cucurbit species. For each cucurbit genome or unigene Nucleic Acids Research, 2019, Vol. 47, Database issue D1131 Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 Figure 1. Gene feature page in CuGenDB. The page contains different sections with different content types. The inset histogram shows expression profiles of a specific gene under a selected project in the ‘Gene Expression’ section. set, gene functional descriptions assigned by AHRD, GO DATABASE FUNCTIONS terms assigned by Blast2GO, and enzyme commission (EC) Search numbers derived from the top hits in the UniProt database are integrated into a file in the PathoLogic format, which To facilitate the query for gene functional annotation is used by PathwayTools for pathway prediction. A total data stored in CuGenDB, we have used the Apache Solr of 320–430 biochemical pathways have been predicted from search engine (http://lucene.apache.org/solr/) to build the each genome or unigene set. A cucurbit biochemical path- search index for different types of annotation data includ- way database (CucurbitCyc) has been implemented in Cu- ing AHRD descriptions, homologous genes, GO terms and GenDB using the PathwayTools web server (31). Users can InterPro domains. A basic search form is provided for each search and browse the predicted pathways, as well as per- genome or unigene collection, which allows users to input a form comparative and omics data analyses through the Cu- specific gene or unigene ID for retrieving the corresponding curbitCyc database. gene or unigene information, or to input a keyword for re- D1132 Nucleic Acids Research, 2019, Vol. 47, Database issue trieving a list of genes whose annotations contain such key- biological processes or biochemical pathways under cer- word. In addition, a global search function, which queries tain experimental conditions or developmental stages. In against all the records stored in the database, is provided CuGenDB, we have developed two extension modules to under the main menu of CuGenDB. identify significantly overrepresented GO terms and path- Batch query, which allows for retrieving sequences, anno- ways, respectively. The ‘GO tool’ extension module has been tations and other features for a list of user-provided genes, implemented by wrapping the GO::TermFinder Perl mod- Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 is an important function in genomics databases, e.g. the ule, which determines enriched GO terms using the hyper- Batch Entrez tool in NCBI (https://www.ncbi.nlm.nih.gov/ geometric distribution test (34). The ‘Pathway tool’ exten- sites/batchentrez). The batch query function in CuGenDB sion module has been developed based on the biochemi- is modified from the ‘Sequence Retrieval’ page of Tripal cal pathways predicted by PathwayTools (31), and also uses (16). In addition to sequences and functional descriptions the hypergeometric distribution test to calculate the signifi- assigned by AHRD, starting with a list of user input genes, cance of enrichment. These two modules have been packed the query also allows for retrieval of transcription factors into Tripal, and can be implemented in other genomics and transcriptional regulators, which are predicted from all databases built with Tripal. cucurbit genes stored in the database using the iTAK pro- Classifying a list of interesting genes into different func- gram (32). tional categories is also important to help understand spe- cific biological processes. In CuGenDB, we developed a tool which can functionally classify a list of genes based on a set Genome browser of plant-specific GO subset (http://www.geneontology.org/ In CuGenDB, we have implemented a genome browser us- page/go-subset-guide). This tool has been integrated into ing JBrowse (33) to display genome sequences, gene models, the ‘GO tool’ extension module. unigene and EST alignments, and expression profile data. Currently, all collected cucurbit genomes and gene mod- SyntenyViewer els are imported into JBrowse. The tracks of reference se- quence and gene models are also embedded in the gene fea- To view genome synteny and homologous gene pairs be- ture page to provide a graphical and informative view of the tween different cucurbit species, we have developed ‘Syn- gene structure (Figure 1). In addition, the genome browser tenyViewer’ as an extension module of Tripal. The synteny has several supporting tracks including expression abun- blocks can be retrived in CuGenDB by selecting a query dances derived from the RNA-Seq datasets and alignments genome and one or more compared genomes, or by provid- of ESTs and unigenes. Other interesting data, such as single- ing a specific block ID. SyntenyViewer draws circos plots to base resolution genome variants that are being generated by display synteny blocks for every pair of query and compared the community, can be easily added to the genome browser genomes (Figure 2A), and provides a full list of the synteny for view in future updates. blocks. For a specific synteny block, SyntenyViewer gener- ates an image to show the homologous gene pairs, and the image can be zoomed in or out for different views (Figure BLAST 2B). The full list of genes including the homologous gene pairs within the synteny block is also provided, with each We have implemented an instance of NCBI’s BLAST tool gene linked to the gene feature page. In summary, the Syn- in CuGenDB using the BLAST UI extension module in Tri- tenyViewer module can not only display synteny blocks for pal (16). We have modified the interface of the BLAST UI multiple genomes in an intuitive manner, but also connect module to integrate the BLAST program and database op- homologous gene pairs among different cucurbit species. tions into one query interface. All genome, mRNA, CDS With this module, for a specific genome region of interest in and protein sequences as well as EST and unigene sequences one cucurbit species, features of homologous regions such stored in CuGenDB are available for comparison through as interesting genes can be easily identified and intuitively this BLAST interface. To prevent users from choosing in- viewed in another cucurbit genome. It is worth noting that compatible BLAST programs and databases in the inter- the SyntenyViewer has already been adopted by a number face, the list of databases is automatically updated based on of other genome databases including Genome Database for the selected BLAST programs. The BLAST UI module pro- Rosaceae (https://www.rosaceae.org), CottonGen (https: vides downloadable output files in three different formats, //www.cottongen.org), Citrus Genome Database (https:// HTML, TSV and XML. www.citrusgenomedb.org), and Cool Season Food Legume Database (https://www.coolseasonfoodlegume.org). Enrichment analysis and gene functional classification Differential gene expression analysis Genomic and functional genomic studies normally gener- ate large lists of interesting genes, and translating such lists In addition to loading and storing gene expression profile into biologically meaningful information is critical to un- data derived from RNA-Seq datasets, the ‘RNA-Seq’ mod- derstand the underlying regulatory mechanisms of the re- ule also provides statistical analysis functions for differen- lated biological processes. The enrichment analysis is a pow- tially expressed gene (DEG) identification, and tools to vi- erful method to identify classes of genes that are overrep- sualize expression profiles. Currently, two types of compar- resented in a list of genes, which represent highly affected isons can be performed to identify DEGs, including pair- Nucleic Acids Research, 2019, Vol. 47, Database issue D1133 Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 Figure 2. Synteny viewer in CuGenDB. (A) Synteny blocks displayed in circos plot. Blue arc indicates the query chromosome and red arcs indicate chro- mosomes of a compared genome. Dark grey lines between blue and red arcs indicate synteny blocks identified between the two genomes. The line will be changed to red when mouse over. (B) View of the selected synteny block. The query and compared chromosomes of the selected synteny blocks are shown in orange and blue, respectively. The yellow and black lines within each chromosome indicate homologous gene pairs, which are connected by grey lines. wise comparisons of two different samples, and time series CONCLUSIONS AND FUTURE DIRECTIONS comparisons of samples from different stages or under dif- We have developed Cucurbit Genomics Database (Cu- ferent conditions. edgeR (35) and DESeq (36), the two most GenDB), which serves as a central portal for genomics, popular tools for differential expression analysis of RNA- transcriptomics, and genetics of cucurbit species. Cu- Seq data, are provided in the ‘RNA-Seq’ module. Users can GenDB stores sequences of genomes, mRNAs, proteins, also change the cutoff of the adjusted P-value and the ex- ESTs and unigenes, and comprehensive functional anno- pression fold change to determine DEGs. The result page of tations of genes and unigenes, as well as genome syn- differential expression analysis includes the project descrip- teny blocks, homologous gene pairs, gene expression pro- tion, parameters used for statistical analysis, a list of the top files, biochemical pathways, and genetic datasets of cu- 100 most significant DEG (ordered by adjusted P-values), curbit species. The database also provides various query, and links to download files containing expression analy- visualization and analysis tools including BLAST, batch sis results for all genes or all identified DEGs. An impor- query, genome browser, pathway database (CucurbitCyc), tant feature of the ‘RNA-Seq’ modules is that the identified GO term and pathway enrichment analysis, genome syn- DEGs can be easily transferred to other modules for down- teny viewer and differential gene expression analysis. It stream functional analysis. The result page of DEGs con- is worth mentioning that two newly developed modules tains links to tools of GO and pathway enrichment analyses, in CuGenDB, ‘SyntenyViewer’ and ‘RNA-Seq’, have been gene functional classification, and batch query. The identi- packed as Tripal extension modules that have been adopted fied DEGs will be automatically loaded into these tools as in other genomics databases developed using the Tripal sys- the input. tem. In addition to viewing the expression profiles of individ- CuGenDB will be continuously updated when new ual genes on the gene feature page (Figure 1), the ‘RNA- genome, RNA-Seq and genetic datasets of cucurbit species Seq’ module provides two additional visualiztion tools of become available. We will continue to improve the func- gene expression profiles, a heatmap function developed by tionality of the ‘SyntenyViewer’ and ‘RNA-Seq’ modules, using the plotly JavaScript library (http://plot.ly) to display and develop novel related data mining and analysis tools expression profiles of multiple genes (Figure 3A), and the which can be used by the Tripal community. We are cur- JBrowse (33) to display single-base resolution expression rently in the process of developing a module for analyses abundances under different conditions (Figure 3B). of small RNA (sRNA) datasets, which will be made avail- D1134 Nucleic Acids Research, 2019, Vol. 47, Database issue Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 Figure 3. Gene expression analysis with the ‘RNA-Seq’ module in CuGenDB. (A) Heatmap showing expression profiles of multiple genes. (B) Single-base resolution expression abundance view in JBrowse. able in both CuGenDB and Tripal in the near future. Cur- typic data generated under CucCAP, together with numer- rently, under the CucCAP project (https://cuccap.org), the ous ongoing efforts from other research groups around the cucurbit community has been genotyping >1000 accessions world. Therefore, a breeder-friendly database for pheno- for each of the four major cucurbit crops, cucumber (37), typic, genotypic and QTL information is an urgent need watermelon, melon and squash, using the genotyping-by- for cucurbit crops. Therefore, we will implement tools and sequencing (GBS) technology, among which a core collec- query interfaces in CuGenDB to analyze and integrate tion of ∼400 accessions for each crop is being established genotypic and phenotypic data for cucurbit crops using the and under deep genome resequencing. A large number of Breeding Information Management System (BIMS; https: molecular markers will be derived and large-scale pheno- //www.rosaceae.org/bims). Nucleic Acids Research, 2019, Vol. 47, Database issue D1135 ACKNOWLEDGEMENTS mapping of a Papaya ring-spot virus resistance locus. Plant J., 92, 963–975. We thank the Tripal community for developing, maintain- 14. Montero-Pau,J., Blanca,J., Bombarely,A., Ziarsolo,P., Esteras,C., ing and updating the Tripal modules. Martı́-Gómez,C., Ferriol,M., Gómez,P., Jamilena,M., Mueller,L. et al. (2018) De novo assembly of the zucchini genome reveals a whole-genome duplication associated with the origin of the Cucurbita FUNDING genus. Plant Biotechnol. J., 16, 1161–1171. Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020 15. Yano,R., Nonaka,S. and Ezura,H. (2018) Melonet-DB, a grand USDA National Institute of Food and Agriculture Spe- RNA-Seq gene expression atlas in melon (Cucumis melo L.). Plant cialty Crop Research Initiative [2015-51181-24285]; US- Cell Physiol., 59, e4. Israel Binational Agricultural Research and Development 16. Sanderson,L.A., Ficklin,S.P., Cheng,C.H., Jung,S., Feltus,F.A., Bett,K.E. and Main,D. (2013) Tripal v1.1: a standards-based toolkit Fund [IS-3333-02, IS-3877-06CR and IS-4223-09C]; USDA for construction of online genetic and genomic databases. Database, Agricultural Research Service, and by SNC Laboratoire 2013, bat075. ASL, de Ruiter Seeds B.V., Enza Zaden B.V., Gautier Se- 17. Jung,S., Lee,T., Ficklin,S., Yu,J., Cheng,C.-H. and Main,D. (2016) mences S.A., Nunhems B.V., Rijk Zwaan B.V., Sakata Seed Chado use case: storing genomic, genetic and breeding data of Inc, Semillas Fitó S.A., Seminis Vegetable Seeds Inc, Syn- Rosaceae and Gossypium crops in Chado. Database, 2016, baw010. 18. Jung,S., Ficklin,S.P., Lee,T., Cheng,C.-H., Blenda,A., Zheng,P., Yu,J., genta Seeds B.V., Takii and Company Ltd, Vilmorin and Bombarely,A., Cho,I., Ru,S. et al. (2014) The Genome Database for Cie S.A. and Zeraim Gedera Ltd, all of them as part of the Rosaceae (GDR): year 10 update. Nucleic Acids Res., 42, support to the International Cucurbit Genomics Initiative D1237–D1244. (ICuGI). Funding for open access charge: USDA National 19. Yu,J., Jung,S., Cheng,C.-H., Ficklin,S.P., Lee,T., Zheng,P., Jones,D., Percy,R.G. and Main,D. (2014) CottonGen: a genomics, genetics and Institute of Food and Agriculture. breeding database for cotton research. Nucleic Acids Res., 42, Conflict of interest statement. None declared. D1229–D1236. 20. Dereeper,A., Bocs,S., Rouard,M., Guignon,V., Ravel,S., Tranchant-Dubreuil,C., Poncet,V., Garsmeur,O., Lashermes,P. and REFERENCES Droc,G. (2015) The coffee genome hub: a resource for coffee 1. McCreight,J.D. (2017) Cultivation and uses of cucurbit crops. In: genomes. Nucleic Acids Res., 43, D1028–1035. Grumet,R, Katzir,N and Garcia-Mas (eds). Genetics and Genomics of 21. Mitchell,A., Chang,H.-Y., Daugherty,L., Fraser,M., Hunter,S., Cucurbitaceae. Plant Genetics and Genomics: Crops and Models. Lopez,R., McAnulla,C., McMenamin,C., Nuka,G., Pesseat,S. et al. Springer International Publishing. pp. 1–12. (2014) The InterPro protein families database: the classification 2. Lee,J.-M., Kubota,C., Tsao,S.J., Bie,Z., Echevarria,P.H., Morra,L. resource after 15 years. Nucleic Acids Res., 43, D213–D221. and Oda,M. (2010) Current status of vegetable grafting: diffusion, 22. Conesa,A. and Götz,S. (2008) Blast2GO: A comprehensive suite for grafting techniques, automation. Sci. Hortic., 127, 93–105. functional analysis in plant genomics. Int. J. Plant Genomics, 2008, 3. Pech,J.C., Bouzayen,M. and Latché,A. (2008) Climacteric fruit 619832. ripening: ethylene-dependent and independent regulation of ripening 23. Wang,Y., Tang,H., Debarry,J.D., Tan,X., Li,J., Wang,X., Lee,T., pathways in melon fruit. Plant Sci., 175, 114–120. Jin,H., Marler,B., Guo,H. et al. (2012) MCScanX: a toolkit for 4. Bhowmick,B.K. and Jha,S. (2015) Dynamics of sex expression and detection and evolutionary analysis of gene synteny and collinearity. chromosome diversity in Cucurbitaceae: a story in the making. J. Nucleic Acids Res., 40, e49. Genet., 94, 793–808. 24. Zheng,Y., Zhao,L., Gao,J. and Fei,Z. (2011) iAssembler: a package 5. Sui,X., Nie,J., Li,X., Scanlon,M.J., Zhang,C., Zheng,Y., Ma,S., for de novo assembly of Roche-454/Sanger transcriptome sequences. Shan,N., Fei,Z., Turgeon,R. et al. (2018) Transcriptomic and BMC Bioinformatics, 12, 453. functional analysis of cucumber (Cucumis sativus L.) fruit phloem 25. Wu,T.D. and Watanabe,C.K. (2005) GMAP: a genomic mapping and during early development. Plant J., doi:10.1111/tpj.14084. alignment program for mRNA and EST sequences. Bioinformatics, 6. Lough,T.J. and Lucas,W.J. (2006) Integrative plant biology: role of 21, 1859–1875. phloem long-distance macromolecular trafficking. Annu. Rev. Plant 26. Bolger,A.M., Lohse,M. and Usadel,B. (2014) Trimmomatic: a flexible Biol., 57, 203–232. trimmer for Illumina sequence data. Bioinformatics, 30, 2114–2120. 7. Huang,S., Li,R., Zhang,Z., Li,L., Gu,X., Fan,W., Lucas,W.J., 27. Quast,C., Pruesse,E., Yilmaz,P., Gerken,J., Schweer,T., Yarza,P., Wang,X., Xie,B., Ni,P. et al. (2009) The genome of the cucumber, Peplies,J. and Glöckner,F.O. (2013) The SILVA ribosomal RNA gene Cucumis sativus L. Nat. Genet., 41, 1275–1281. database project: improved data processing and web-based tools. 8. Garcia-Mas,J., Benjak,A., Sanseverino,W., Bourgeois,M., Mir,G., Nucleic Acids Res., 41, D590–D596. Gonzalez,V.M., Henaff,E., Camara,F., Cozzuto,L., Lowy,E. et al. 28. Langmead,B., Trapnell,C., Pop,M. and Salzberg,S.L. (2009) Ultrafast (2012) The genome of melon (Cucumis melo L.). Proc. Natl. Acad. and memory-efficient alignment of short DNA sequences to the Sci. U.S.A., 109, 11872–11877. human genome. Genome Biol., 10, R25. 9. Yang,L., Koo,D.H., Li,Y., Zhang,X., Luan,F., Havey,M.J., Jiang,J. 29. Kim,D., Langmead,B. and Salzberg,S.L. (2015) HISAT: a fast spliced and Weng,Y. (2012) Chromosome rearrangements during aligner with low memory requirements. Nat. Methods, 12, 357–360. domestication of cucumber as revealed by high-density genetic 30. Youens-Clark,K., Faga,B., Yap,I. V, Stein,L. and Ware,D. (2009) mapping and draft genome assembly. Plant J., 71, 895–906. CMap 1.01: a comparative mapping application for the Internet. 10. Guo,S., Zhang,J., Sun,H., Salse,J., Lucas,W.J., Zhang,H., Zheng,Y., Bioinformatics, 25, 3040–3042. Mao,L., Ren,Y., Wang,Z. et al. (2012) The draft genome of 31. Karp,P.D., Paley,S. and Romero,P. (2002) The Pathway Tools watermelon (Citrullus lanatus) and resequencing of 20 diverse software. Bioinformatics, 18(Suppl. 1), S225–S232. accessions. Nat. Genet., 45, 51–58. 32. Zheng,Y., Jiao,C., Sun,H., Rosli,H.G., Pombo,M.A., Zhang,P., 11. Qi,J., Liu,X., Shen,D., Miao,H., Xie,B., Li,X., Zeng,P., Wang,S., Banf,M., Dai,X., Martin,G.B., Giovannoni,J.J. et al. (2016) iTAK: A Shang,Y., Gu,X. et al. (2013) A genomic variation map provides program for genome-wide prediction and classification of plant insights into the genetic basis of cucumber domestication and transcription factors, transcriptional regulators, and protein kinases. diversity. Nat. Genet., 45, 1510–1515. Mol. Plant, 9, 1667–1670. 12. Sun,H., Wu,S., Zhang,G., Jiao,C., Guo,S., Ren,Y., Zhang,J., 33. Buels,R., Yao,E., Diesh,C.M., Hayes,R.D., Munoz-Torres,M., Zhang,H., Gong,G., Jia,Z. et al. (2017) Karyotype stability and Helt,G., Goodstein,D.M., Elsik,C.G., Lewis,S.E., Stein,L. et al. unbiased fractionation in the paleo-allotetraploid Cucurbita genomes. (2016) JBrowse: a dynamic web platform for genome visualization Mol. Plant, 10, 1293–1306. and analysis. Genome Biol., 17, 66. 13. Wu,S., Shamimuzzaman,M., Sun,H., Salse,J., Sui,X., Wilder,A., 34. Boyle,E.I., Weng,S., Gollub,J., Jin,H., Botstein,D., Cherry,J.M. and Wu,Z., Levi,A., Xu,Y., Ling,K.-S. et al. (2017) The bottle gourd Sherlock,G. (2004) GO::TermFinder–open source software for genome provides insights into Cucurbitaceae evolution and facilitates accessing Gene Ontology information and finding significantly D1136 Nucleic Acids Research, 2019, Vol. 47, Database issue enriched Gene Ontology terms associated with a list of genes. 37. Wang,X., Bao,K., Reddy,U.K., Bai,Y., Hammar,S.A., Jiao,C., Bioinformatics, 20, 3710–3715. Wehner,T.C., Ramı́rez-Madera,A.O., Weng,Y., Grumet,R. et al. 35. Robinson,M.D., McCarthy,D.J. and Smyth,G.K. (2010) edgeR: a (2018) The USDA cucumber (Cucumis sativus L.) collection: genetic bioconductor package for differential expression analysis of digital diversity, population structure, genome-wide association studies and gene expression data. Bioinformatics, 26, 139–140. core collection development. Hort. Res., 5, 64 36. Anders,S. and Huber,W. (2010) Differential expression analysis for sequence count data. Genome Biol., 11, R106. Downloaded from https://academic.oup.com/nar/article-abstract/47/D1/D1128/5128937 by Universitat Autonoma de Barcelona user on 07 February 2020