Kazusa Marker DataBase: a database for genomics, genetics, and molecular breeding in plants

Plant GARDEN: a portal website for cross-searching between different types of genomic and genetic resources in a wide variety of plant species

BACKGROUND

Plant genome information is fundamental to plant research and development. Along with the increase in the number of published plant genomes, there is a need for an efficient system to retrieve various kinds of genome-related information from many plant species across plant kingdoms. Various plant databases have been developed, but no public database covers both genomic and genetic resources over a wide range of plant species.

MAIN BODY

We have developed a plant genome portal site, Plant GARDEN (Genome And Resource Database Entry: https://plantgarden.jp/en/index ), to provide diverse information related to plant genomics and genetics in divergent plant species. Elasticsearch is used as a search engine, and cross-keyword search across species is available. Web-based user interfaces (WUI) for PCs and tablet computers were independently developed to make data searches more convenient. Several types of data are stored in Plant GARDEN: reference genomes, gene sequences, PCR-based DNA markers, trait-linked DNA markers identified in genetic studies, SNPs, and in/dels on publicly available sequence read archives (SRAs). The data registered in Plant GARDEN as of March 2023 included 304 assembled genome sequences, 11,331,614 gene sequences, 419,132 DNA markers, 8,225 QTLs, and 5,934 SNP lists (gvcf files). In addition, we have re-annotated all the genes registered in Plant GARDEN by using a functional annotation tool, Hayai-Annotation, to compare the orthologous relationships among genes.

CONCLUSION

The aim of Plant GARDEN is to provide plant genome information for use in the fields of plant science as well as for plant-based industries, education, and other relevant areas. Therefore, we have designed a WUI that allows a diverse range of users to access such information in an easy-to-understand manner. Plant GARDEN will eventually include a wide range of plant species for which genome sequences are assembled, and thus the number of plant species in the database will continue to expand. We anticipate that Plant GARDEN will promote the understanding of genomes and gene diversity by facilitating comparisons of the registered sequences.

Four genetic loci control compact plant size with yellow pear-shaped fruit in ornamental tomato (Solanum lycopersicum L.)

Tomato is an attractive fruiting vegetable crop that can be used as an ornamental plant. Agronomical traits have been subjected to extensive genetic dissection to enhance vegetable breeding programs. By contrast, there are few genetic studies of ornamental traits for the development of ornamental tomato varieties. To investigate genetic loci linked to desired ornamental traits, we performed genetic analyses using an intraspecific mapping population that segregated for fruit color (yellow or red), fruit shape (round or pear), and plant height (high or compact). A genetic map was constructed with 965 single nucleotide polymorphisms (SNPs) and 33 simple sequence repeat markers. Subsequent linkage analysis using quantitative locus analysis and genome-wide association study detected four genetic loci for the three selected traits, all of which were located near the reported genes. We performed KASP-kompetitive allele-specific PCR-to develop SNP markers that were tightly linked to the four loci. Highly accurate genotyping data were obtained from the four SNPs across 187 F2 plants, which enabled us to select two lines with homozygous alleles for compact plant size and yellow pear-shaped fruits. These newly developed SNP markers and genetic strategies could be used to accelerate breeding programs for ornamental tomato plants.

MSDB: a comprehensive, annotated database of microsatellites

Microsatellites are short tandem repeats of 1–6 nucleotide motifs, studied for their utility as genome markers and in forensics. Recent evidence points to the role of microsatellites in important regulatory functions, and their length polymorphisms at coding regions are linked to various neurodegenerative disorders in humans. Microsatellites show a taxon-specific enrichment in eukaryotic genomes, and their evolution remains poorly understood. Though other databases of microsatellites exist, they fall short on several fronts. MSDB (MicroSatellite DataBase) is a collection of >4 billion microsatellites from 37 680 genomes presented in a user-friendly web portal for easy, interactive analysis and visualization. This is by far the most comprehensive, annotated, updated database to access and analyze microsatellite data of multiple species. The features of MSDB enable users to explore the data as tables that can be filtered and exported, and also as interactive charts to view and compare the data of multiple species simultaneously. Its modularity and architecture permit seamless updates with new data, making it a powerful tool and useful resource to researchers working on this important class of DNA elements, particularly in context of their evolution and emerging roles in genome organization and gene regulation.

SSRome: an integrated database and pipelines for exploring microsatellites in all organisms

Over the past decade, many databases focusing on microsatellite mining on a genomic scale were released online with at least one of the following major deficiencies: (i) lacking the classification of microsatellites as genic or non-genic, (ii) not comparing microsatellite motifs at both genic and non-genic levels in order to identify unique motifs for each class or (iii) missing SSR marker development. In this study, we have developed ‘SSRome’ as a web-based, user-friendly, comprehensive and dynamic database with pipelines for exploring microsatellites in 6533 organisms. In the SSRome database, 158 million microsatellite motifs are identified across all taxa, in addition to all the mitochondrial and chloroplast genomes and expressed sequence tags available from NCBI. Moreover, 45.1 million microsatellite markers were developed and classified as genic or non-genic. All the stored motif and marker datasets can be downloaded freely. In addition, SSRome provides three user-friendly tools to identify, classify and compare motifs on either a genome- or transcriptome-wide scale. With the implementation of PHP, HTML and JavaScript, users can upload their data for analysis via a user-friendly GUI. SSRome represents a powerful database and mega-tool that will assist researchers in developing and dissecting microsatellite markers on a high-throughput scale.

Profiling of Nutraceuticals and Proximates in Peanut Genotypes Differing for Seed Coat Color and Seed Size

A total of 60 genotypes of peanut comprising 46 genotypes selected from ICRISAT mini core collection and 14 elite cultivars with differing kernel color and size were used to profile the nutritional parameters such as proximates (moisture, fat, ash, crude protein, crude fiber, carbohydrate content) and nutraceuticals (total polyphenol content and total antioxidant activity). The genotypes showed varied kernel color ranging from white to purple. Kernel skin color was quantified using colorimetry, and the color parameters were expressed as CIELAB color parameters. In total, nine morphological traits, six yield related traits, eight nutritional traits and eleven color parameters were observed across 60 genotypes. The sixty genotypes were grouped into ten clusters based on the color strength. Among them, Cluster-III with dark red seeds had the maximum fat content and total polyphenol content (TPC). Cluster-VI with light pink colored seeds had high antioxidant activity (AOA) and Cluster-X with white colored seeds had highest moisture and crude protein content. Color strength (K/S) was found to be positively correlated with TPC. Another color parameter, redness/greenness (a*) was found to be positively correlated with AOA. However, seed size was positively correlated with the crude protein content, but not with any other nutritional traits under study. The population studies based on the genotypic data indicated two distinct groups pertaining to botanical types of peanut. The marker-trait association (MTA) using single marker analysis indicated 75 major MTAs for most of the nutritional traits except for moisture content. The markers associated with nutritional parameters and other important yield related traits can further be utilized for genomics-assisted breeding for nutrient-rich peanuts.

Transcriptomic Changes in Medicago truncatula and Lotus japonicus Root Nodules during Drought Stress

Drought is one of the major environmental factors limiting biomass and seed yield production in agriculture. In this research, we focused on plants from the Fabaceae family, which has a unique ability for the establishment of symbiosis with nitrogen-fixing bacteria, and are relatively susceptible to water limitation. We have presented the changes in nitrogenase activity and global gene expression occurring in Medicago truncatula and Lotus japonicus root nodules during water deficit. Our results proved a decrease in the efficiency of nitrogen fixation, as well as extensive changes in plant and bacterial transcriptomes, shortly after watering cessation. We showed for the first time that not only symbiotic plant components but also Sinorhizobium meliloti and Mesorhizobium loti bacteria residing in the root nodules of M. truncatula and L. japonicus, respectively, adjust their gene expression in response to water shortage. Although our results demonstrated that both M. truncatula and L. japonicus root nodules were susceptible to water deprivation, they indicated significant differences in plant and bacterial response to drought between the tested species, which might be related to the various types of root nodules formed by these species.

Expression Analysis of PIN Genes in Root Tips and Nodules of Lotus japonicus

Auxins are postulated to be one of the pivotal factors in nodulation. However, their transporters in Lotus japonicus, the model species for the study of the development of determinate-type root nodules, have been scarcely described so far, and thus their role in nodulation has remained unknown. Our research is the first focusing on polar auxin transporters in L. japonicus. We analyzed and compared expression of PINs in 20 days post rhizobial inoculation (dpi) and 54 dpi root nodules of L. japonicus by real-time quantitative polymerase chain reaction (qPCR) along with the histochemical β-glucuronidase (GUS) reporter gene assay in transgenic hairy roots. The results indicate that LjPINs are essential during root nodule development since they are predominantly expressed in the primordia and young, developing nodules. However, along with differentiation, expression levels of several PINs decreased and occurred particularly in the nodule vascular bundles, especially in connection with the root's stele. Moreover, our study demonstrated the importance of both polar auxin transport and auxin intracellular homeostasis during L. japonicus root nodule development and differentiation.

Fine-mapping and identifying candidate genes conferring resistance to Soybean mosaic virus strain SC20 in soybean

KEY MESSAGE

The Mendelian gene conferring resistance to Soybean mosaic virus Strain SC20 in soybean was fine-mapped onto a 79-kb segment on Chr.13 where two closely linked candidate genes were identified and qRT-PCR verified. Soybean mosaic virus (SMV) threatens the world soybean production, particularly in China. A country-wide SMV strain system composed of 22 strains was established in China, among which SC20 is a dominant strain in five provinces in Southern China. Resistance to SC20 was evaluated in parents, F1, F2 and the F2:7 RIL (recombinant inbred line) population derived from a cross between Qihuang-1 (resistant) and NN1138-2 (susceptible). The segregation ratio of resistant to susceptible in the populations suggested a single dominant gene involved in the resistance to SC20 in Qihuang-1. A "partial genome mapping strategy" was used to map the resistance gene on Chromosome 13. Linkage analysis between 178 RILs and genetic markers showed that the SC20-resistance gene located at 3.9 and 3.8 cM to the flanking markers BARCSOYSSR_13_1099 and BARCSOYSSR_13_1185 on Chromosome 13. Subsequently, a residual heterozygote segregating population with 346 individuals was developed by selfing four plants heterozygous at markers adjacent to the tentative SC20-resistance gene; then, the candidate region was delimited to a genomic interval of approximately 79 kb flanked by the new markers gm-ssr_13-14 and gm-indel_13-3. Among the seven annotated candidate genes in this region, two genes, Glyma.13G194700 and Glyma.13G195100, encoding Toll Interleukin Receptor-nucleotide-binding-leucine-rich repeat resistance proteins were identified as candidate resistance genes by quantitative real-time polymerase chain reaction and sequence analysis. The two closely linked genes work together to cause the phenotypic segregation as a single Mendelian gene. These results will facilitate marker-assisted selection, gene cloning and breeding for the resistance to SC20.

Plant Genome DataBase Japan (PGDBj)

A portal website that integrates a variety of information related to genomes of model and crop plants from databases (DBs) and the literature was generated. This website, named the Plant Genome DataBase Japan (PGDBj, http://pgdbj. jp/en/ ), is comprised of three component DBs and a cross-search engine which provides a seamless search over their contents. One of the three component DBs is the Ortholog DB, which provides gene cluster information based on the amino acid sequence similarity. Over 1,000,000 amino acid sequences of 40 Viridiplantae species were collected from the public DNA DBs, and plant genome DBs such as TAIR and RAP-DB were subjected to reciprocal BLAST searches for clustering. Another component DB is the Plant Resource DB for genomic- and bio-resources. This DB also integrates the SABRE DB, which provides cDNA and genome sequence resources maintained in the RIKEN BioResource Center and National BioResource Projects Japan. The third component DB of PGDBj is the DNA Marker DB, which manually or automatically collects curated information on DNA markers, quantitative trait loci (QTL), and related genetic linkage maps, from the literature and external DBs. By combining these component DBs and a cross-search engine, PGDBj serves as a useful platform to study genetic systems for both fundamental and applied researches for a wide range of plant species.

Target Amplicon Sequencing for Genotyping Genome-Wide Single Nucleotide Polymorphisms Identified by Whole-Genome Resequencing in Peanut

Genome-wide genotyping data regarding breeding materials are essential resources for improving breeding efficiency, especially in plants with complex genomes with a high degree of polyploidy. Several current breeding efforts in cultivated peanut ( L.), which has a tetraploid genome, are devoted to developing high oleic acid cultivars. Genetic maps for such breeding programs have been developed using simple-sequence repeat (SSR) markers, the use of which requires time-consuming electrophoretic analyses. Next-generation sequencing (NGS) technology can overcome this technical hurdle. Initially, we attempted double-digest restriction site-associated DNA sequencing on peanut breeding materials used to develop high oleic acid cultivars. However, this method was not effective because few single nucleotide polymorphism (SNPs) were available because of low genetic diversity of the lines. The genome sequences of the probable diploid ancestors of cultivated peanut, Krapov. & W. C. Greg. and Krapov. & W. C. Greg., are available. Therefore, we next employed whole-genome resequencing analysis to obtain genome-wide SNP data. In this analysis, we observed large biases in the numbers and genomic positions of interspecific and intraspecific SNPs. For genome-wide genotyping, we selected a subset of SNPs covering the peanut genome as the targets of amplicon sequencing analysis. Using this technique, genome-wide genotypes of the breeding materials were easily and rapidly determined. The SNP information and analytic methods developed in this study should accelerate genetics, genomics, and breeding in peanut.

PMDBase: a database for studying microsatellite DNA and marker development in plants

Microsatellite DNAs (or SSRs) are important genomic components involved in many important biological functions. SSRs have been extensively exploited as molecular markers for diverse applications including genetic diversity, linkage/association mapping of gene/QTL, marker-assisted selection, variety identification and evolution analysis. However, a comprehensive database or web service for studying microsatellite DNAs and marker development in plants is lacking. Here, we developed a database, PMDBase, which integrates large amounts of microsatellite DNAs from genome sequenced plant species and includes a web service for microsatellite DNAs identification. In PMDBase, 26 230 099 microsatellite DNAs were identified spanning 110 plant species. Up to three pairs of primers were supplied for every microsatellite DNA. For 81 species, genomic features of the microsatellite DNAs (genic or non-genic) were supplied with the corresponding genes or transcripts from public databases. Microsatellite DNAs can be explored through browsing and searching modules with a user-friendly web interface and customized software. Furthermore, we developed MISAweb and embedded Primer3web to help users to identify microsatellite DNAs and design corresponding primers in their own genomic sequences online. All datasets of microsatellite DNAs can be downloaded conveniently. PMDBase will be updated regularly with new available genome data and can be accessed freely via the address http://www.sesame-bioinfo.org/PMDBase.

Omics data input for metabolic modeling

Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.

Naturally occurring diversity helps to reveal genes of adaptive importance in legumes

Environmental changes challenge plants and drive adaptation to new conditions, suggesting that natural biodiversity may be a source of adaptive alleles acting through phenotypic plasticity and/or micro-evolution. Crosses between accessions differing for a given trait have been the most common way to disentangle genetic and environmental components. Interestingly, such man-made crosses may combine alleles that never meet in nature. Another way to discover adaptive alleles, inspired by evolution, is to survey large ecotype collections and to use association genetics to identify loci of interest. Both of these two genetic approaches are based on the use of biodiversity and may eventually help us in identifying the genes that plants use to respond to challenges such as short-term stresses or those due to global climate change. In legumes, two wild species, Medicago truncatula and Lotus japonicus, plus the cultivated soybean (Glycine max) have been adopted as models for genomic studies. In this review, we will discuss the resources, limitations and future plans for a systematic use of biodiversity resources in model legumes to pinpoint genes of adaptive importance in legumes, and their application in breeding.