Gene space completeness in complex plant genomes

Application of orthology and network biology to infer gene functions in non-model plants

Approximately 60% of the genes and gene products in the model species Arabidopsis thaliana have been functionally characterized. In non-model plant species, the functional annotation of the gene space is largely based on homology, with the assumption that genes with shared common ancestry have conserved functions. However, the wide variety in possible morphological, physiological, and ecological differences between plant species gives rise to many species- and clade-specific genes, for which this transfer of knowledge is not possible. Other complications, such as difficulties with genetic transformation, the absence of large-scale mutagenesis methods, and long generation times, further lead to the slow characterization of genes in non-model species. Here, we discuss different resources that integrate plant gene function information. Different approaches that support the functional annotation of gene products, based on orthology or network biology, are described. While sequence-based tools to characterize the functional landscape in non-model species are maturing and becoming more readily available, easy-to-use network-based methods inferring plant gene functions are not as prevalent and have limited functionality.

Strategies of tolerance reflected in two North American maple genomes

The first chromosome‐scale assemblies for North American members of the Acer genus, sugar maple (Acer saccharum) and boxelder (Acer negundo), as well as transcriptomic evaluation of the abiotic stress response in A. saccharum are reported. This integrated study describes in‐depth aspects contributing to each species' approach to tolerance and applies current knowledge in many areas of plant genome biology with Acer physiology to help convey the genomic complexities underlying tolerance in broadleaf tree species.

PLAZA 5.0: extending the scope and power of comparative and functional genomics in plants

PLAZA is a platform for comparative, evolutionary, and functional plant genomics. It makes a broad set of genomes, data types and analysis tools available to researchers through a user-friendly website, an API, and bulk downloads. In this latest release of the PLAZA platform, we are integrating a record number of 134 high-quality plant genomes, split up over two instances: PLAZA Dicots 5.0 and PLAZA Monocots 5.0. This number of genomes corresponds with a massive expansion in the number of available species when compared to PLAZA 4.0, which offered access to 71 species, a 89% overall increase. The PLAZA 5.0 release contains information for 5 882 730 genes, and offers pre-computed gene families and phylogenetic trees for 5 274 684 protein-coding genes. This latest release also comes with a set of new and updated features: a new BED import functionality for the workbench, improved interactive visualizations for functional enrichments and genome-wide mapping of gene sets, and a fully redesigned and extended API. Taken together, this new version offers extended support for plant biologists working on different families within the green plant lineage and provides an efficient and versatile toolbox for plant genomics. All PLAZA releases are accessible from the portal website: https://bioinformatics.psb.ugent.be/plaza/.

K-mer counting and curated libraries drive efficient annotation of repeats in plant genomes

The annotation of repetitive sequences within plant genomes can help in the interpretation of observed phenotypes. Moreover, repeat masking is required for tasks such as whole-genome alignment, promoter analysis, or pangenome exploration. Although homology-based annotation methods are computationally expensive, k-mer strategies for masking are orders of magnitude faster. Here, we benchmarked a two-step approach, where repeats were first called by k-mer counting and then annotated by comparison to curated libraries. This hybrid protocol was tested on 20 plant genomes from Ensembl, with the k-mer-based Repeat Detector (Red) and two repeat libraries (REdat, last updated in 2013, and nrTEplants, curated for this work). Custom libraries produced by RepeatModeler were also tested. We obtained repeated genome fractions that matched those reported in the literature but with shorter repeated elements than those produced directly by sequence homology. Inspection of the masked regions that overlapped genes revealed no preference for specific protein domains. Most Red-masked sequences could be successfully classified by sequence similarity, with the complete protocol taking less than 2 h on a desktop Linux box. A guide to curating your own repeat libraries and the scripts for masking and annotating plant genomes can be obtained at https://github.com/Ensembl/plant-scripts.

TRAPID 2.0: a web application for taxonomic and functional analysis of de novo transcriptomes

Advances in high-throughput sequencing have resulted in a massive increase of RNA-Seq transcriptome data. However, the promise of rapid gene expression profiling in a specific tissue, condition, unicellular organism or microbial community comes with new computational challenges. Owing to the limited availability of well-resolved reference genomes, de novo assembled (meta)transcriptomes have emerged as popular tools for investigating the gene repertoire of previously uncharacterized organisms. Yet, despite their potential, these datasets often contain fragmented or contaminant sequences, and their analysis remains difficult. To alleviate some of these challenges, we developed TRAPID 2.0, a web application for the fast and efficient processing of assembled transcriptome data. The initial processing phase performs a global characterization of the input data, providing each transcript with several layers of annotation, comprising structural, functional, and taxonomic information. The exploratory phase enables downstream analyses from the web application. Available analyses include the assessment of gene space completeness, the functional analysis and comparison of transcript subsets, and the study of transcripts in an evolutionary context. A comparison with similar tools highlights TRAPID’s unique features. Finally, analyses performed within TRAPID 2.0 are complemented by interactive data visualizations, facilitating the extraction of new biological insights, as demonstrated with diatom community metatranscriptomes.

Stable unmethylated DNA demarcates expressed genes and their cis-regulatory space in plant genomes

The genomic sequences of crops continue to be produced at a frenetic pace. It remains challenging to develop complete annotations of functional genes and regulatory elements in these genomes. Chromatin accessibility assays enable discovery of functional elements; however, to uncover the full portfolio of cis-elements would require profiling of many combinations of cell types, tissues, developmental stages, and environments. Here, we explore the potential to use DNA methylation profiles to develop more complete annotations. Using leaf tissue in maize, we define ∼100,000 unmethylated regions (UMRs) that account for 5.8% of the genome; 33,375 UMRs are found greater than 2 kb from genes. UMRs are highly stable in multiple vegetative tissues, and they capture the vast majority of accessible chromatin regions from leaf tissue. However, many UMRs are not accessible in leaf, and these represent regions with potential to become accessible in specific cell types or developmental stages. These UMRs often occur near genes that are expressed in other tissues and are enriched for binding sites of transcription factors. The leaf-inaccessible UMRs exhibit unique chromatin modification patterns and are enriched for chromatin interactions with nearby genes. The total UMR space in four additional monocots ranges from 80 to 120 megabases, which is remarkably similar considering the range in genome size of 271 megabases to 4.8 gigabases. In summary, based on the profile from a single tissue, DNA methylation signatures provide powerful filters to distill large genomes down to the small fraction of putative functional genes and regulatory elements.

Global Role of Crop Genomics in the Face of Climate Change

The development of climate change resilient crops is necessary if we are to meet the challenge of feeding the growing world's population. We must be able to increase food production despite the projected decrease in arable land and unpredictable environmental conditions. This review summarizes the technological and conceptual advances that have the potential to transform plant breeding, help overcome the challenges of climate change, and initiate the next plant breeding revolution. Recent developments in genomics in combination with high-throughput and precision phenotyping facilitate the identification of genes controlling critical agronomic traits. The discovery of these genes can now be paired with genome editing techniques to rapidly develop climate change resilient crops, including plants with better biotic and abiotic stress tolerance and enhanced nutritional value. Utilizing the genetic potential of crop wild relatives (CWRs) enables the domestication of new species and the generation of synthetic polyploids. The high-quality crop plant genome assemblies and annotations provide new, exciting research targets, including long non-coding RNAs (lncRNAs) and cis-regulatory regions. Metagenomic studies give insights into plant-microbiome interactions and guide selection of optimal soils for plant cultivation. Together, all these advances will allow breeders to produce improved, resilient crops in relatively short timeframes meeting the demands of the growing population and changing climate.

Effect of sequence depth and length in long-read assembly of the maize inbred NC358

Improvements in long-read data and scaffolding technologies have enabled rapid generation of reference-quality assemblies for complex genomes. Still, an assessment of critical sequence depth and read length is important for allocating limited resources. To this end, we have generated eight assemblies for the complex genome of the maize inbred line NC358 using PacBio datasets ranging from 20 to 75 × genomic depth and with N50 subread lengths of 11-21 kb. Assemblies with ≤30 × depth and N50 subread length of 11 kb are highly fragmented, with even low-copy genic regions showing degradation at 20 × depth. Distinct sequence-quality thresholds are observed for complete assembly of genes, transposable elements, and highly repetitive genomic features such as telomeres, heterochromatic knobs, and centromeres. In addition, we show high-quality optical maps can dramatically improve contiguity in even our most fragmented base assembly. This study provides a useful resource allocation reference to the community as long-read technologies continue to mature.

Bioinformatics Resources for Plant Abiotic Stress Responses: State of the Art and Opportunities in the Fast Evolving -Omics Era

Abiotic stresses are among the principal limiting factors for productivity in agriculture. In the current era of continuous climate changes, the understanding of the molecular aspects involved in abiotic stress response in plants is a priority. The rise of -omics approaches provides key strategies to promote effective research in the field, facilitating the investigations from reference models to an increasing number of species, tolerant and sensitive genotypes. Integrated multilevel approaches, based on molecular investigations at genomics, transcriptomics, proteomics and metabolomics levels, are now feasible, expanding the opportunities to clarify key molecular aspects involved in responses to abiotic stresses. To this aim, bioinformatics has become fundamental for data production, mining and integration, and necessary for extracting valuable information and for comparative efforts, paving the way to the modeling of the involved processes. We provide here an overview of bioinformatics resources for research on plant abiotic stresses, describing collections from -omics efforts in the field, ranging from raw data to complete databases or platforms, highlighting opportunities and still open challenges in abiotic stress research based on -omics technologies.

Comparative genomics of six Juglans species reveals disease-associated gene family contractions

Juglans (walnuts), the most speciose genus in the walnut family (Juglandaceae), represents most of the family's commercially valuable fruit and wood-producing trees. It includes several species used as rootstock for their resistance to various abiotic and biotic stressors. We present the full structural and functional genome annotations of six Juglans species and one outgroup within Juglandaceae (Juglans regia, J. cathayensis, J. hindsii, J. microcarpa, J. nigra, J. sigillata and Pterocarya stenoptera) produced using BRAKER2 semi-unsupervised gene prediction pipeline and additional tools. For each annotation, gene predictors were trained using 19 tissue-specific J. regia transcriptomes aligned to the genomes. Additional functional evidence and filters were applied to multi-exonic and mono-exonic putative genes to yield between 27 000 and 44 000 high-confidence gene models per species. Comparison of gene models to the BUSCO embryophyta dataset suggested that, on average, genome annotation completeness was 85.6%. We utilized these high-quality annotations to assess gene family evolution within Juglans, and among Juglans and selected Eurosid species. We found notable contractions in several gene families in J. hindsii, including disease resistance-related wall-associated kinase (WAK), Catharanthus roseus receptor-like kinase (CrRLK1L) and others involved in abiotic stress response. Finally, we confirmed an ancient whole-genome duplication that took place in a common ancestor of Juglandaceae using site substitution comparative analysis.