Gene function annotations for the maize NAM founder lines.

OBJECTIVES: We annotated the latest published sequences of the 26 Zea mays Nested Association Mapping (NAM) founder lines using GOMAP, the Gene Ontology Meta Annotator for Plants. The maize NAM panel enables researchers to understand and identify the genetic basis of complex traits. Annotations of predicted functions for genes can help researchers investigate gene-phenotype associations, prioritize candidate genes for phenotypes of interest, and formulate testable hypotheses about gene function/phenotype associations. The creation and release of high-confidence, high-coverage gene function annotation sets for the NAM founder lines is critical to accelerate the generation of knowledge in maize genetics research. GOMAP is a high-throughput computational pipeline that annotates gene functions genome-wide in plant genomes using Gene Ontology functional class terms. Here we report and share GOMAP-generated functional annotations for the NAM founder lines. DATA DESCRIPTION: Datasets include the protein sequences used as input, GOMAP-generated annotation files, scripts used to update obsolete terms, and GAF-formatted tab-delimited text files of gene function annotations along with README files that describe formatting, content, and how files relate to each other.

Standardized genome-wide function prediction enables comparative functional genomics: a new application area for Gene Ontologies in plants.

BACKGROUND: Genome-wide gene function annotations are useful for hypothesis generation and for prioritizing candidate genes potentially responsible for phenotypes of interest. We functionally annotated the genes of 18 crop plant genomes across 14 species using the GOMAP pipeline. RESULTS: By comparison to existing GO annotation datasets, GOMAP-generated datasets cover more genes, contain more GO terms, and are similar in quality (based on precision and recall metrics using existing gold standards as the basis for comparison). From there, we sought to determine whether the datasets across multiple species could be used together to carry out comparative functional genomics analyses in plants. To test the idea and as a proof of concept, we created dendrograms of functional relatedness based on terms assigned for all 18 genomes. These dendrograms were compared to well-established species-level evolutionary phylogenies to determine whether trees derived were in agreement with known evolutionary relationships, which they largely are. Where discrepancies were observed, we determined branch support based on jackknifing then removed individual annotation sets by genome to identify the annotation sets causing unexpected relationships. CONCLUSIONS: GOMAP-derived functional annotations used together across multiple species generally retain sufficient biological signal to recover known phylogenetic relationships based on genome-wide functional similarities, indicating that comparative functional genomics across species based on GO data holds promise for generating novel hypotheses about comparative gene function and traits.

Gene Ontology Meta Annotator for Plants (GOMAP).

Annotating gene structures and functions to genome assemblies is necessary to make assembly resources useful for biological inference. Gene Ontology (GO) term assignment is the most used functional annotation system, and new methods for GO assignment have improved the quality of GO-based function predictions. The Gene Ontology Meta Annotator for Plants (GOMAP) is an optimized, high-throughput, and reproducible pipeline for genome-scale GO annotation of plants. We containerized GOMAP to increase portability and reproducibility and also optimized its performance for HPC environments. Here we report on the pipeline's availability and performance for annotating large, repetitive plant genomes and describe how GOMAP was used to annotate multiple maize genomes as a test case. Assessment shows that GOMAP expands and improves the number of genes annotated and annotations assigned per gene as well as the quality (based on [Formula: see text]) of GO assignments in maize. GOMAP has been deployed to annotate other species including wheat, rice, barley, cotton, and soy. Instructions and access to the GOMAP Singularity container are freely available online at https://bioinformapping.com/gomap/ . A list of annotated genomes and links to data is maintained at https://dill-picl.org/projects/gomap/ .

A high-resolution gene expression atlas links dedicated meristem genes to key architectural traits.

The shoot apical meristem (SAM) orchestrates the balance between stem cell proliferation and organ initiation essential for postembryonic shoot growth. Meristems show a striking diversity in shape and size. How this morphological diversity relates to variation in plant architecture and the molecular circuitries driving it are unclear. By generating a high-resolution gene expression atlas of the vegetative maize shoot apex, we show here that distinct sets of genes govern the regulation and identity of stem cells in maize versus Arabidopsis. Cell identities in the maize SAM reflect the combinatorial activity of transcription factors (TFs) that drive the preferential, differential expression of individual members within gene families functioning in a plethora of cellular processes. Subfunctionalization thus emerges as a fundamental feature underlying cell identity. Moreover, we show that adult plant characters are, to a significant degree, regulated by gene circuitries acting in the SAM, with natural variation modulating agronomically important architectural traits enriched specifically near dynamically expressed SAM genes and the TFs that regulate them. Besides unique mechanisms of maize stem cell regulation, our atlas thus identifies key new targets for crop improvement.

Gene network variation and alternative paths to convergent evolution in turtles.

Diversification of the turtle's shell comprises remarkable phenotypic transformations. For instance, two divergent species convergently evolved shell-closing systems with shoulder blade (scapula) segments that enable coordinated movements with the shell. We expected these unusual structures to originate via similar changes in underlying gene networks, as skeletal segment formation is an evolutionarily conserved developmental process. We tested this hypothesis by comparing transcriptomes of scapula tissue across three stages of embryonic development in three emydid turtles from natural populations. We found that alternative strategies for skeletal segmentation were associated with interspecific differences in gene co-expression networks. Notably, mesenchyme homeobox 2 (MEOX2) and HOXA3-5 were central hubs driving the activity of 2,806 genes in a candidate network for scapula segmentation, albeit in only one species. Even so, scapula muscle overgrowth corresponded to the activity of similar myogenic networks in both species. This and other derived developmental processes were not observed in the third species, which displayed the ancestral (unsegmented) scapula condition. Differential gene expression tests against this reference lineage supported histological and network analyses. Our findings illustrate that molecular underpinnings of convergent evolution, including during the diversification of the atypical turtle "body plan," are influenced by variation in underlying developmental processes.

Maize GO Annotation-Methods, Evaluation, and Review (maize-GAMER).

We created a new high-coverage, robust, and reproducible functional annotation of maize protein-coding genes based on Gene Ontology (GO) term assignments. Whereas the existing Phytozome and Gramene maize GO annotation sets only cover 41% and 56% of maize protein-coding genes, respectively, this study provides annotations for 100% of the genes. We also compared the quality of our newly derived annotations with the existing Gramene and Phytozome functional annotation sets by comparing all three to a manually annotated gold standard set of 1,619 genes where annotations were primarily inferred from direct assay or mutant phenotype. Evaluations based on the gold standard indicate that our new annotation set is measurably more accurate than those from Phytozome and Gramene. To derive this new high-coverage, high-confidence annotation set, we used sequence similarity and protein domain presence methods as well as mixed-method pipelines that were developed for the Critical Assessment of Function Annotation (CAFA) challenge. Our project to improve maize annotations is called maize-GAMER (GO Annotation Method, Evaluation, and Review), and the newly derived annotations are accessible via MaizeGDB (http://download.maizegdb.org/maize-GAMER) and CyVerse (B73 RefGen_v3 5b+ at doi.org/10.7946/P2S62P and B73 RefGen_v4 Zm00001d.2 at doi.org/10.7946/P2M925).

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. In 1991, the original maize genetics database MaizeDB was created. In 2003, the combined contents of MaizeDB and the sequence data from ZmDB were made accessible as a single resource named MaizeGDB. Over the next decade, MaizeGDB became more sequence driven while still maintaining traditional maize genetics datasets. This enabled the project to meet the continued growing and evolving needs of the maize research community, yet the interface and underlying infrastructure remained unchanged. In 2015, the MaizeGDB team completed a multi-year effort to update the MaizeGDB resource by reorganizing existing data, upgrading hardware and infrastructure, creating new tools, incorporating new data types (including diversity data, expression data, gene models, and metabolic pathways), and developing and deploying a modern interface. In addition to coordinating a data resource, the MaizeGDB team coordinates activities and provides technical support to the maize research community. MaizeGDB is accessible online at http://www.maizegdb.org.

YouGenMap: a web platform for dynamic multi-comparative mapping and visualization of genetic maps.

Comparative genetic maps are used in examination of genome organization, detection of conserved gene order, and exploration of marker order variations. YouGenMap is an open-source web tool that offers dynamic comparative mapping capability of users' own genetic mapping between 2 or more map sets. Users' genetic map data and optional gene annotations are uploaded, either publically or privately, as long as they follow our template which is available in several standard file formats. Data is parsed and loaded into MySQL relational database to be displayed and compared against users' genetic maps or other public data available on YouGenMap. With the highly interactive GUIs, all public data on YouGenMap are maps available for visualization, comparison, search, filtration and download. YouGenMap web tool is available on the website (http://conifergdb.miamioh.edu/yougenmap) with the source-code repository at (http://sourceforge.net/projects/yougenmap/?source=directory).

An annotated genetic map of loblolly pine based on microsatellite and cDNA markers.

BACKGROUND: Previous loblolly pine (Pinus taeda L.) genetic linkage maps have been based on a variety of DNA polymorphisms, such as AFLPs, RAPDs, RFLPs, and ESTPs, but only a few SSRs (simple sequence repeats), also known as simple tandem repeats or microsatellites, have been mapped in P. taeda. The objective of this study was to integrate a large set of SSR markers from a variety of sources and published cDNA markers into a composite P. taeda genetic map constructed from two reference mapping pedigrees. A dense genetic map that incorporates SSR loci will benefit complete pine genome sequencing, pine population genetics studies, and pine breeding programs. Careful marker annotation using a variety of references further enhances the utility of the integrated SSR map. RESULTS: The updated P. taeda genetic map, with an estimated genome coverage of 1,515 cM(Kosambi) across 12 linkage groups, incorporated 170 new SSR markers and 290 previously reported SSR, RFLP, and ESTP markers. The average marker interval was 3.1 cM. Of 233 mapped SSR loci, 84 were from cDNA-derived sequences (EST-SSRs) and 149 were from non-transcribed genomic sequences (genomic-SSRs). Of all 311 mapped cDNA-derived markers, 77% were associated with NCBI Pta UniGene clusters, 67% with RefSeq proteins, and 62% with functional Gene Ontology (GO) terms. Duplicate (i.e., redundant accessory) and paralogous markers were tentatively identified by evaluating marker sequences by their UniGene cluster IDs, clone IDs, and relative map positions. The average gene diversity, He, among polymorphic SSR loci, including those that were not mapped, was 0.43 for 94 EST-SSRs and 0.72 for 83 genomic-SSRs. The genetic map can be viewed and queried at http://www.conifergdb.org/pinemap. CONCLUSIONS: Many polymorphic and genetically mapped SSR markers are now available for use in P. taeda population genetics, studies of adaptive traits, and various germplasm management applications. Annotating mapped genes with UniGene clusters and GO terms allowed assessment of redundant and paralogous EST markers and further improved the quality and utility of the genetic map for P. taeda.