Andrew Olson

Centralizing valuable community data and resources into a user-friendly interface and accessible repository has become essential for agricultural science; embracing Findable Accessible, Interoperable, and Reusable (FAIR) principles is now standard for effective databases. SorghumBase (https://www.sorghumbase.org) is a knowledgebase designed for the sorghum research community. The SorghumBase team curates genomic, transcriptomic, variation, and phenotypic information and aggregates community events, providing rich visualizations and bulk data access. The modular framework of the database is built with open-access software to yield a robust, modifiable, and sustainable data infrastructure. Release 9 of SorghumBase includes: (i) 88 sorghum reference genomes and an updated pan-gene index, (ii) over 100 million variants have been mapped onto the 2 genomes, BTx623 and Tx2783, (iii) assignment of 41 million Reference Cluster SNP identifiers (rsIDs) from BTx623 across the pan-genome, (iv) updated gene search homology, gene expression, and germplasm visualizations and features, (v) added and standardized 234 phenotypic data from 40 community-generated GWAS studies and 148 traits from the Sorghum QTL Atlas (Oz Sorghum), (vi) improved news, funding, and a research content management system for community access and interaction, (vii) outreach materials including training documents and videos, and (viii) community engagement initiatives through training and working groups. SorghumBase serves as a hub for sorghum data and stakeholder engagement while promoting community standards to drive research and multi-omics breeding approaches.

The rice genome underpins fundamental research and breeding, but the Nipponbare ( japonica ) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent the japonica , indica , aus , and aromatic varietal groups. The RPRP has been consistently annotated and supported by extensive experimental data, and here, we report the computational assignment, characterization, and dissemination of stably identified pangenes, collectively called the PanOryza data set. We identify 25,178 core pangenes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains, and AlphaFold structures, whereas cultivar-specific genes are enriched for domains under selective breeding pressure, such as for disease resistance. We identify more than 5000 genes absent in the IRGSP rice reference genome and present in at least two other Oryza cultivars. We demonstrate the utility of this resource through various examples of pangenes and their protein domains. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware “reference guide” across rice genomes, advancing both basic and applied research.

Gramene (gramene.org) is a comprehensive reference database for comparative plant genomics and pathway analysis, integrating functional annotations, evidence-based curated pathways and their projections, and multi-omics datasets. Since our last report, Gramene has added crop-specific pan-genome portals for maize, sorghum, rice, and grapevine. These pan-genome portals host population-scale datasets and multiple assembled genomes per species, all anchored by shared reference genomes. Importantly, these portals now adopt standardized rsIDs for genetic variants, advancing FAIR data principles and enabling cross-database interoperability. The main site is now Gramene Plants, emphasizing its broad genome coverage. Release 69 features 233 reference genomes, curated pathways for 139 species, expression data from 1026 studies across 27 species, and genetic variation data mapped to 27 genomes from 19 species. Key updates to the integrated search functionality include embedded expression viewers from the Bio-Analytic Resource for Plant Biology and EMBL-EBI Expression Atlas, a literature-curated catalog of gene functions, and a new Germplasm tab linking accessions with loss-of-function alleles to seed repositories. These advances reinforce Gramene as a comprehensive platform for exploring plant genomic diversity, gene function, and evolutionary conservation across the Green Tree of Life and within key agricultural species.

Rice is a vital staple crop, sustaining over half of the global population, and is a key model for genetic research. To support the growing need for comprehensive and accessible rice genomic data, GrameneOryza (https://oryza.gramene.org) was developed as an online resource adhering to FAIR (Findable, Accessible, Interoperable, and Reusable) principles of data management. It distinguishes itself through its comprehensive multispecies focus, encompassing a wide variety of Oryza genomes and related species, and its integration with FAIR principles to ensure data accessibility and usability. It offers a community curated selection of high-quality Oryza genomes, genetic variation, gene function, and trait data. The latest release, version 8, includes 28 Oryza genomes, covering wild rice and domesticated cultivars. These genomes, along with Leersia perrieri and seven additional outgroup species, form the basis for 38 K protein-coding gene family trees, essential for identifying orthologs, paralogs, and developing pan-gene sets. GrameneOryza’s genetic variation data features 66 million single-nucleotide variants (SNVs) anchored to the Os-Nipponbare-Reference-IRGSP-1.0 genome, derived from various studies, including the Rice Genome 3 K (RG3K) project. The RG3K sequence reads were also mapped to seven additional platinum-quality Asian rice genomes, resulting in 19 million SNVs for each genome, significantly expanding the coverage of genetic variation beyond the Nipponbare reference. Of the 66 million SNVs on IRGSP-1.0, 27 million acquired standardized reference SNP cluster identifiers (rsIDs) from the European Variation Archive release v5. Additionally, 1200 distinct phenotypes provide a comprehensive overview of quantitative trait loci (QTL) features. The newly introduced Oryza CLIMtools portal offers insights into environmental impacts on genome adaptation. The platform’s integrated search interface, along with a BLAST server and curation tools, facilitates user access to genomic, phylogenetic, gene function, and QTL data, supporting broad research applications. Database URL: https://oryza.gramene.org

The rice genome underpins fundamental research and breeding, but the Nipponbare (japonica) reference does not fully encompass the genetic diversity of Asian rice. To address this gap, the Rice Population Reference Panel (RPRP) was developed, comprising high-quality assemblies of 16 rice cultivars to represent japonica , indica , aus , and aromatic varietal groups. The RPRP has been consistently annotated, supported by extensive experimental data and here we report the computational assignment, characterization and dissemination of stably identified pan-genes. We identified 25,178 core pan-genes shared across all cultivars, alongside cultivar-specific and family-enriched genes. Core genes exhibit higher gene expression and proteomic evidence, higher confidence protein domains and AlphaFold structures, while cultivar-specific genes were enriched for domains under selective breeding pressure, such as for disease resistance. This resource, integrated into public databases, enables researchers to explore genetic and functional diversity via a population-aware “reference guide” across rice genomes, advancing both basic and applied research.

In plants, vegetative and reproductive development are associated with agronomically important traits that contribute to grain yield and biomass. Zinc finger homeodomain (ZF-HD) transcription factors (TFs) constitute a relatively small gene family that has been studied in several model plants, including Arabidopsis thaliana L. and Oryza sativa L. The ZF-HD family members play important roles in plant growth and development, but their contribution to the regulation of plant architecture remains largely unknown due to their functional redundancy. To understand the gene regulatory network controlled by ZF-HD TFs, we analyzed multiple loss-of-function mutants of ZF-HD TFs in Arabidopsis that exhibited morphological abnormalities in branching and flowering architecture. We found that ZF-HD TFs, especially HB34, negatively regulate the expression of miR157 and positively regulate SQUAMOSA PROMOTER BINDING–LIKE 10 (SPL10), a target of miR157. Genome-wide chromatin immunoprecipitation sequencing (ChIP-Seq) analysis revealed that miR157D and SPL10 are direct targets of HB34, creating a feed-forward loop that constitutes a robust miRNA regulatory module. Network motif analysis contains overrepresented coherent type IV feedforward motifs in the amiR zf-HD and hbq mutant background. This finding indicates that miRNA-mediated ZF-HD feedforward modules modify branching and inflorescence architecture in Arabidopsis. Taken together, these findings reveal a guiding role of ZF-HD TFs in the regulatory network module and demonstrate its role in plant architecture in Arabidopsis.

An a-maize-ing set of genomes: Maize is an important crop cultivated worldwide. As maize spread across the world, selection for local environments resulted in variation, but the impact on differences between the genome has not been quantified. By producing high-quality genomic sequences of the 26 lines used in the maize nested association mapping panel, Hufford et al . map important traits and demonstrate the diversity of maize. Examining RNA and methylation of genes across accessions, the authors identified a core set of maize genes. Beyond this core set, comparative analysis across lines identified high levels of variation in the total set of genes, the maize pan-genome. The value of this resource was further exemplified by mapping quantitative traits of interest, including those related to pathogen resistance. —LMZ

Genome sequencing projects annotate protein-coding gene models with multiple transcripts, aiming to represent all of the available transcript evidence. However, downstream analyses often operate on only one representative transcript per gene locus, sometimes known as the canonical transcript. To choose canonical transcripts, Transcript Ranking and Canonical Election (TRaCE) holds an ‘election’ in which a set of RNA-seq samples rank transcripts by annotation edit distance. These sample-specific votes are tallied along with other criteria such as protein length and InterPro domain coverage. The winner is selected as the canonical transcript, but the election proceeds through multiple rounds of voting to order all the transcripts by relevance. Based on the set of expression data provided, TRaCE can identify the most common isoforms from a broad expression atlas or prioritize alternative transcripts expressed in specific contexts. Transcript ranking code can be found on GitHub at {{https://github.com/warelab/TRaCE}}. Supplementary data are available at Bioinformatics online.

Summary: Genome sequencing projects annotate protein-coding gene models with multiple transcripts, aiming to represent all of the available transcript evidence. However, downstream analyses often operate on only one representative transcript per gene locus, sometimes known as the canonical transcript. To choose canonical transcripts, TRaCE (Transcript Ranking and Canonical Election) holds an ‘election’ in which a set of RNA-seq samples rank transcripts by annotation edit distance. These sample-specific votes are tallied along with other criteria such as protein length and InterPro domain coverage. The winner is selected as the canonical transcript, but the election proceeds through multiple rounds of voting to order all the transcripts by relevance. Based on the set of expression data provided, TRaCE can identify the most common isoforms from a broad expression atlas or prioritize alternative transcripts expressed in specific contexts. Availability and Implementation: Transcript ranking code can be found on GitHub at {{ https://github.com/warelab/TRaCE }} Contact: olson@cshl.edu , ware@cshl.edu Supplementary information: Additional data are available in the github repository.

The sophistication of gene prediction algorithms and the abundance of RNA-based evidence for the maize genome may suggest that manual curation of gene models is no longer necessary. However, quality metrics generated by the MAKER-P gene annotation pipeline identified 17,225 of 130,330 (13%) protein-coding transcripts in the B73 Reference Genome V4 gene set with models of low concordance to available biological evidence. Working with eight graduate students, we used the Apollo annotation editor to curate 86 transcript models flagged by quality metrics and a complimentary method using the Gramene gene tree visualizer. All of the triaged models had significant errors – including missing or extra exons, non-canonical splice sites, and incorrect UTRs. A correct transcript model existed for about 60% of genes (or transcripts) flagged by quality metrics; we attribute this to the convention of elevating the transcript with the longest coding sequence (CDS) to the canonical, or first, position. The remaining 40% of flagged genes resulted in novel annotations and represent a manual curation space of about 10% of the maize genome (~4,000 protein-coding genes). MAKER-P metrics have a specificity of 100%, and a sensitivity of 85%; the gene tree visualizer has a specificity of 100%. Together with the Apollo graphical editor, our double triage provides an infrastructure to support the community curation of eukaryotic genomes by scientists, students, and potentially even citizen scientists.