Tools and Resources at the Maize Genetics and Genomics Database (MaizeGDB).

The Maize Genetics and Genomics Database (MaizeGDB) is the community resource for maize researchers, offering a suite of tools, informatics resources, and curated data sets to support maize genetics, genomics, and breeding research. Here, we provide an overview of the key resources available at MaizeGDB, including maize genomes, comparative genomics, and pan-genomics tools. This review aims to familiarize users with the range of options available for maize research and highlights the importance of MaizeGDB as a central hub for the maize research community.

Functional annotation and meta-analysis of maize transcriptomes reveal genes involved in biotic and abiotic stress.

Background: Environmental stress factors, such as biotic and abiotic stress, are becoming more common due to climate variability, significantly affecting global maize yield. Transcriptome profiling studies provide insights into the molecular mechanisms underlying stress response in maize, though the functions of many genes are still unknown. To enhance the functional annotation of maize-specific genes, MaizeGDB has outlined a data-driven approach with an emphasis on identifying genes and traits related to biotic and abiotic stress.

Enhanced pan-genomic resources at the maize genetics and genomics database.

Pan-genomes, encompassing the entirety of genetic sequences found in a collection of genomes within a clade, are more useful than single reference genomes for studying species diversity. This is especially true for a species like Zea mays, which has a particularly diverse and complex genome. Presenting pan-genome data, analyses, and visualization is challenging, especially for a diverse species, but more so when pan-genomic data is linked to extensive gene model and gene data, including classical gene information, markers, insertions, expression and proteomic data, and protein structures as is the case at MaizeGDB.

PanEffect: a pan-genome visualization tool for variant effects in maize.

Summary: Understanding the effects of genetic variants is crucial for accurately predicting traits and functional outcomes. Recent approaches have utilized artificial intelligence and protein language models to score all possible missense variant effects at the proteome level for a single genome, but a reliable tool is needed to explore these effects at the pan-genome level. To address this gap, we introduce a new tool called PanEffect.

Maize protein structure resources at the maize genetics and genomics database.

Protein structures play an important role in bioinformatics, such as in predicting gene function or validating gene model annotation. However, determining protein structure was, until now, costly and time-consuming, which resulted in a structural biology bottleneck. With the release of such programs AlphaFold and ESMFold, this bottleneck has been reduced by several orders of magnitude, permitting protein structural comparisons of entire genomes within reasonable timeframes.

A pan-genomic approach to genome databases using maize as a model system.

Research in the past decade has demonstrated that a single reference genome is not representative of a species' diversity. MaizeGDB introduces a pan-genomic approach to hosting genomic data, leveraging the large number of diverse maize genomes and their associated datasets to quickly and efficiently connect genomes, gene models, expression, epigenome, sequence variation, structural variation, transposable elements, and diversity data across genomes so that researchers can easily track the structural and functional differences of a locus and its orthologs across maize. We believe our framework is unique and provides a template for any genomic database poised to host large-scale pan-genomic data.

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database.

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org).

: A Sequence-Indexed Resource of Transposon-Induced Maize Mutations for Functional Genomics Studies.

Sequence-indexed insertional libraries in maize () are fundamental resources for functional genetics studies. Here, we constructed a () insertional library in the B73 inbred background designated A total of 1,152 -tagged F-families were sequenced using the -seq approach. We detected 225,936 genomic insertion sites and 41,086 high quality germinal insertions covering 16,392 of the annotated maize genes (37% of the B73v4 genome).

MaizeDIG: Maize Database of Images and Genomes.

An organism can be described by its observable features (phenotypes) and the genes and genomic information (genotypes) that cause these phenotypes. For many decades, researchers have tried to find relationships between genotypes and phenotypes, and great strides have been made. However, improved methods and tools for discovering and visualizing these phenotypic relationships are still needed.

MaizeGDB 2018: the maize multi-genome genetics and genomics database.

Since its 2015 update, MaizeGDB, the Maize Genetics and Genomics database, has expanded to support the sequenced genomes of many maize inbred lines in addition to the B73 reference genome assembly. Curation and development efforts have targeted high quality datasets and tools to support maize trait analysis, germplasm analysis, genetic studies, and breeding. MaizeGDB hosts a wide range of data including recent support of new data types including genome metadata, RNA-seq, proteomics, synteny, and large-scale diversity.

Maize Genomes to Fields: 2014 and 2015 field season genotype, phenotype, environment, and inbred ear image datasets.

Objectives: Crop improvement relies on analysis of phenotypic, genotypic, and environmental data. Given large, well-integrated, multi-year datasets, diverse queries can be made: Which lines perform best in hot, dry environments? Which alleles of specific genes are required for optimal performance in each environment? Such datasets also can be leveraged to predict cultivar performance, even in uncharacterized environments. The maize Genomes to Fields (G2F) Initiative is a multi-institutional organization of scientists working to generate and analyze such datasets from existing, publicly available inbred lines and hybrids.

The effect of artificial selection on phenotypic plasticity in maize.

Remarkable productivity has been achieved in crop species through artificial selection and adaptation to modern agronomic practices. Whether intensive selection has changed the ability of improved cultivars to maintain high productivity across variable environments is unknown. Understanding the genetic control of phenotypic plasticity and genotype by environment (G × E) interaction will enhance crop performance predictions across diverse environments.

Surveying the Maize community for their diversity and pedigree visualization needs to prioritize tool development and curation.

Unlabelled: The Maize Genetics and Genomics Database (MaizeGDB) team prepared a survey to identify breeders’ needs for visualizing pedigrees, diversity data and haplotypes in order to prioritize tool development and curation efforts at MaizeGDB. The survey was distributed to the maize research community on behalf of the Maize Genetics Executive Committee in Summer 2015. The survey garnered 48 responses from maize researchers, of which more than half were self-identified as breeders.

MaizeGDB: The Maize Genetics and Genomics Database.

MaizeGDB is the community database for biological information about the crop plant Zea mays. Genomic, genetic, sequence, gene product, functional characterization, literature reference, and person/organization contact information are among the datatypes stored at MaizeGDB. At the project's website ( http://www.

MaizeGDB update: new tools, data and interface for the maize model organism database.

MaizeGDB is a highly curated, community-oriented database and informatics service to researchers focused on the crop plant and model organism Zea mays ssp. mays. Although some form of the maize community database has existed over the last 25 years, there have only been two major releases.

An ontology approach to comparative phenomics in plants.

Background: Plant phenotype datasets include many different types of data, formats, and terms from specialized vocabularies. Because these datasets were designed for different audiences, they frequently contain language and details tailored to investigators with different research objectives and backgrounds. Although phenotype comparisons across datasets have long been possible on a small scale, comprehensive queries and analyses that span a broad set of reference species, research disciplines, and knowledge domains continue to be severely limited by the absence of a common semantic framework.

Floral transition in maize infected with Sporisorium reilianum disrupts compatibility with this biotrophic fungal pathogen.

Sporisorium reilianum f. sp. zeae is an important biotrophic pathogen that causes head smut disease in maize.

Identification of epigenetic regulators of a transcriptionally silenced transgene in maize.

Transcriptional gene silencing is a gene regulatory mechanism essential to all organisms. Many transcriptional regulatory mechanisms are associated with epigenetic modifications such as changes in chromatin structure, acetylation and methylation of core histone proteins, and DNA methylation within regulatory regions of endogenous genes and transgenes. Although several maize mutants have been identified from prior forward genetic screens for epigenetic transcriptional silencing, these screens have been far from saturated.

POPcorn: An Online Resource Providing Access to Distributed and Diverse Maize Project Data.

The purpose of the online resource presented here, POPcorn (Project Portal for corn), is to enhance accessibility of maize genetic and genomic resources for plant biologists. Currently, many online locations are difficult to find, some are best searched independently, and individual project websites often degrade over time-sometimes disappearing entirely. The POPcorn site makes available (1) a centralized, web-accessible resource to search and browse descriptions of ongoing maize genomics projects, (2) a single, stand-alone tool that uses web Services and minimal data warehousing to search for sequence matches in online resources of diverse offsite projects, and (3) a set of tools that enables researchers to migrate their data to the long-term model organism database for maize genetic and genomic information: MaizeGDB.

MaizeGDB: curation and outreach go hand-in-hand.

First released in 1991 with the name MaizeDB, the Maize Genetics and Genomics Database, now MaizeGDB, celebrates its 20th anniversary this year. MaizeGDB has transitioned from a focus on comprehensive curation of the literature, genetic maps and stocks to a paradigm that accommodates the recent release of a reference maize genome sequence, multiple diverse maize genomes and sequence-based gene expression data sets. The MaizeGDB Team is relatively small, and relies heavily on the research community to provide data, nomenclature standards and most importantly, to recommend future directions, priorities and strategies.

The MaizeGDB Genome Browser tutorial: one example of database outreach to biologists via video.

Video tutorials are an effective way for researchers to quickly learn how to use online tools offered by biological databases. At MaizeGDB, we have developed a number of video tutorials that demonstrate how to use various tools and explicitly outline the caveats researchers should know to interpret the information available to them. One such popular video currently available is 'Using the MaizeGDB Genome Browser', which describes how the maize genome was sequenced and assembled as well as how the sequence can be visualized and interacted with via the MaizeGDB Genome Browser.

Gene expression analyses in maize inbreds and hybrids with varying levels of heterosis.

Background: Heterosis is the superior performance of F1 hybrid progeny relative to the parental phenotypes. Maize exhibits heterosis for a wide range of traits, however the magnitude of heterosis is highly variable depending on the choice of parents and the trait(s) measured. We have used expression profiling to determine whether the level, or types, of non-additive gene expression vary in maize hybrids with different levels of genetic diversity or heterosis.

Physical and genetic structure of the maize genome reflects its complex evolutionary history.

Maize (Zea mays L.) is one of the most important cereal crops and a model for the study of genetics, evolution, and domestication. To better understand maize genome organization and to build a framework for genome sequencing, we constructed a sequence-ready fingerprinted contig-based physical map that covers 93.

A BAC pooling strategy combined with PCR-based screenings in a large, highly repetitive genome enables integration of the maize genetic and physical maps.

Background: Molecular markers serve three important functions in physical map assembly. First, they provide anchor points to genetic maps facilitating functional genomic studies. Second, they reduce the overlap required for BAC contig assembly from 80 to 50 percent.

High-throughput gene discovery in the rat.

The rat is an important animal model for human diseases and is widely used in physiology. In this article we present a new strategy for gene discovery based on the production of ESTs from serially subtracted and normalized cDNA libraries, and we describe its application for the development of a comprehensive nonredundant collection of rat ESTs. Our new strategy appears to yield substantially more EST clusters per ESTs sequenced than do previous approaches that did not use serial subtraction.