Genes and gene models, an important distinction

Comparative genomics reveals substantial divergence in metal sensitive and metal tolerant isolates of the ericoid mycorrhizal fungus Oidiodendron maius

Some heavy metal tolerant fungal isolates capable of forming ericoid mycorrhiza can also confer increased metal tolerance to the host plant. One of these fungal isolates, Oidiodendron maius Zn, has been characterized and a few molecular mechanisms underlying its metal tolerant phenotype have been identified. Here, we investigate the genomic divergences between the available genome of O. maius Zn and the genomes of metal tolerant and sensitive isolates of O. maius, with the aim of identifying genes or intergenic regions possibly involved in the display of the tolerance. The resequenced genomes of 8 tolerant and 10 sensitive isolates were mapped on the reference, O. maius Zn, yielding 357 gene models from the reference that were either missing or too polymorphic to be identified in the genomes of the sensitive isolates. These regions included genes with functions related to defense mechanisms and with unknown functions. One third of the predicted gene models turned out to be highly polymorphic, including many enriched GO terms, i.e. DNA/RNA metabolism and modification, chromosome/chromatin organization, protein biosynthesis, metabolism and function, energy consumption/transfer and mitochondrion. Overall, our findings indicate that the tolerant phenotype in O. maius likely arises from multiple genetic adaptations rather than a singular mechanism.

Multifaceted Dinoflagellates and the Marine Model Prorocentrum cordatum

BACKGROUND

Dinoflagellates are a monophyletic group within the taxon Alveolata, which comprises unicellular eukaryotes. Dinoflagellates have long been studied for their organismic and morphologic diversity as well as striking cellular features. They have a main size range of 10-100 µm, a complex "cell covering", exceptionally large genomes (∼1-250 Gbp with a mean of 50,000 protein-encoding genes) spread over a variable number of highly condensed chromosomes, and perform a closed mitosis with extranuclear spindles (dinomitosis). Photosynthetic, marine, and free-living Prorocentrum cordatum is a ubiquitously occurring, bloom-forming dinoflagellate, and an emerging model system, particularly with respect to systems biology.

SUMMARY

Focused ion beam/scanning electron microscopy (FIB/SEM) analysis of P. cordatum recently revealed (i) a flattened nucleus with unusual structural features and a total of 62 tightly packed chromosomes, (ii) a single, barrel-shaped chloroplast devoid of grana and harboring multiple starch granules, (iii) a single, highly reticular mitochondrion, and (iv) multiple phosphate and lipid storage bodies. Comprehensive proteomics of subcellular fractions suggested (i) major basic nuclear proteins to participate in chromosome condensation, (ii) composition of nuclear pores to differ from standard knowledge, (iii) photosystems I and II, chloroplast complex I, and chlorophyll a-b binding light-harvesting complex to form a large megacomplex (>1.5 MDa), and (iv) an extraordinary richness in pigment-binding proteins. Systems biology-level investigation of heat stress response demonstrated a concerted down-regulation of CO2-concentrating mechanisms, CO2-fixation, central metabolism, and monomer biosynthesis, which agrees with reduced growth yields.

KEY MESSAGES

FIB/SEM analysis revealed new insights into the remarkable subcellular architecture of P. cordatum, complemented by proteogenomic unraveling of novel nuclear structures and a photosynthetic megacomplex. These recent findings are put in the wider context of current understanding of dinoflagellates.

The conservation of gene models can support genome annotation

Many genome annotations include false-positive gene models, leading to errors in phylogenetic and comparative studies. Here, we propose a method to support gene model prediction based on evolutionary conservation and use it to identify potentially erroneous annotations. Using this method, we developed a set of 15,345 representative gene models from 12 legume assemblies that can be used to support genome annotations for other legumes.

Evaluating Plant Gene Models Using Machine Learning

Gene models are regions of the genome that can be transcribed into RNA and translated to proteins, or belong to a class of non-coding RNA genes. The prediction of gene models is a complex process that can be unreliable, leading to false positive annotations. To help support the calling of confident conserved gene models and minimize false positives arising during gene model prediction we have developed Truegene, a machine learning approach to classify potential low confidence gene models using 14 gene and 41 protein-based characteristics. Amino acid and nucleotide sequence-based features were calculated for conserved (high confidence) and non-conserved (low confidence) annotated genes from the published Pisum sativum Cameor genome. These features were used to train eXtreme Gradient Boost (XGBoost) classifier models to predict whether a gene model is likely to be real. The optimized models demonstrated a prediction accuracy ranging from 87% to 90% and an F-1 score of 0.91–0.94. We used SHapley Additive exPlanations (SHAP) and feature importance plots to identify the features that contribute to the model predictions, and we show that protein and gene-based features can be used to build accurate models for gene prediction that have applications in supporting future gene annotation processes.

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.

Structural evolution drives diversification of the large LRR-RLK gene family

●Cells are continuously exposed to chemical signals that they must discriminate between and respond to appropriately. In embryophytes, the leucine-rich repeat receptor-like kinases (LRR-RLKs) are signal receptors critical in development and defense. LRR-RLKs have diversified to hundreds of genes in many plant genomes. Although intensively studied, a well-resolved LRR-RLK gene tree has remained elusive. ●To resolve the LRR-RLK gene tree, we developed an improved gene discovery method based on iterative hidden Markov model searching and phylogenetic inference. We used this method to infer complete gene trees for each of the LRR-RLK subclades and reconstructed the deepest nodes of the full gene family. ●We discovered that the LRR-RLK gene family is even larger than previously thought, and that protein domain gains and losses are prevalent. These structural modifications, some of which likely predate embryophyte diversification, led to misclassification of some LRR-RLK variants as members of other gene families. Our work corrects this misclassification. ●Our results reveal ongoing structural evolution generating novel LRR-RLK genes. These new genes are raw material for the diversification of signaling in development and defense. Our methods also enable phylogenetic reconstruction in any large gene family.

High expression in maize pollen correlates with genetic contributions to pollen fitness as well as with coordinated transcription from neighboring transposable elements

In flowering plants, gene expression in the haploid male gametophyte (pollen) is essential for sperm delivery and double fertilization. Pollen also undergoes dynamic epigenetic regulation of expression from transposable elements (TEs), but how this process interacts with gene expression is not clearly understood. To explore relationships among these processes, we quantified transcript levels in four male reproductive stages of maize (tassel primordia, microspores, mature pollen, and sperm cells) via RNA-seq. We found that, in contrast with vegetative cell-limited TE expression in Arabidopsis pollen, TE transcripts in maize accumulate as early as the microspore stage and are also present in sperm cells. Intriguingly, coordinate expression was observed between highly expressed protein-coding genes and their neighboring TEs, specifically in mature pollen and sperm cells. To investigate a potential relationship between elevated gene transcript level and pollen function, we measured the fitness cost (male-specific transmission defect) of GFP-tagged coding sequence insertion mutations in over 50 genes identified as highly expressed in the pollen vegetative cell, sperm cell, or seedling (as a sporophytic control). Insertions in seedling genes or sperm cell genes (with one exception) exhibited no difference from the expected 1:1 transmission ratio. In contrast, insertions in over 20% of vegetative cell genes were associated with significant reductions in fitness, showing a positive correlation of transcript level with non-Mendelian segregation when mutant. Insertions in maize gamete expressed2 (Zm gex2), the sole sperm cell gene with measured contributions to fitness, also triggered seed defects when crossed as a male, indicating a conserved role in double fertilization, given the similar phenotype previously demonstrated for the Arabidopsis ortholog GEX2. Overall, our study demonstrates a developmentally programmed and coordinated transcriptional activation of TEs and genes in pollen, and further identifies maize pollen as a model in which transcriptomic data have predictive value for quantitative phenotypes.