Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

The era of panomics-driven gene discovery in plants

Panomics is an approach to integrate multiple 'omics' datasets, generated using different individuals or natural variations. Considering their diverse phenotypic spectrum, the phenome is inherently associated with panomics-based science, which is further combined with genomics, transcriptomics, metabolomics, and other omics techniques, either independently or collectively. Panomics has been accelerated through recent technological advancements in the field of genomics that enable the detection of population-wide structural variations (SVs) and hence offer unprecedented insights into the genetic variations contributing to important agronomic traits. The present review provides the recent trends of panomics-driven gene discovery toward various traits related to plant development, stress tolerance, accumulation of specialized metabolites, and domestication/dedomestication. In addition, the success stories are highlighted in the broader context of enhancing crop productivity.

Oryza CLIMtools: A genome-environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To address this issue, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that enable the user to (1) explore the local environments of traditional rice varieties (landraces) in South-East Asia and (2) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We demonstrate the value of these resources by identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior quantitative trait locus analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits, including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.

Structured 3' UTRs destabilize mRNAs in plants

BACKGROUND

RNA secondary structure (RSS) can influence the regulation of transcription, RNA processing, and protein synthesis, among other processes. 3' untranslated regions (3' UTRs) of mRNA also hold the key for many aspects of gene regulation. However, there are often contradictory results regarding the roles of RSS in 3' UTRs in gene expression in different organisms and/or contexts.

RESULTS

Here, we incidentally observe that the primary substrate of miR159a (pri-miR159a), when embedded in a 3' UTR, could promote mRNA accumulation. The enhanced expression is attributed to the earlier polyadenylation of the transcript within the hybrid pri-miR159a-3' UTR and, resultantly, a poorly structured 3' UTR. RNA decay assays indicate that poorly structured 3' UTRs could promote mRNA stability, whereas highly structured 3' UTRs destabilize mRNA in vivo. Genome-wide DMS-MaPseq also reveals the prevailing inverse relationship between 3' UTRs' RSS and transcript accumulation in the transcriptomes of Arabidopsis, rice, and even human. Mechanistically, transcripts with highly structured 3' UTRs are preferentially degraded by 3'-5' exoribonuclease SOV and 5'-3' exoribonuclease XRN4, leading to decreased expression in Arabidopsis. Finally, we engineer different structured 3' UTRs to an endogenous FT gene and alter the FT-regulated flowering time in Arabidopsis.

CONCLUSIONS

We conclude that highly structured 3' UTRs typically cause reduced accumulation of the harbored transcripts in Arabidopsis. This pattern extends to rice and even mammals. Furthermore, our study provides a new strategy of engineering the 3' UTRs' RSS to modify plant traits in agricultural production and mRNA stability in biotechnology.

Oryza CLIMtools: A Genome-Environment Association Resource Reveals Adaptive Roles for Heterotrimeric G Proteins in the Regulation of Rice Agronomic Traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To this end, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that allow the user to: i) explore the local environments of traditional rice varieties (landraces) in South-Eastern Asia, and; ii) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We exemplify the value of these resources, identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior QTL analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing Potential Evapotranspiration gradient and their regulation of key agronomic traits including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce crops that are climate resilient.

miRNA-like secondary structures in maize (Zea mays) genes and transposable elements correlate with small RNAs, methylation, and expression

RNA molecules carry information in their primary sequence and also their secondary structure. Secondary structure can confer important functional information, but it is also a signal for an RNAi-like host epigenetic response mediated by small RNAs (smRNAs). In this study, we used two bioinformatic methods to predict local secondary structures across features of the maize genome, focusing on small regions that had similar folding properties to pre-miRNA loci. We found miRNA-like secondary structures to be common in genes and most, but not all, superfamilies of RNA and DNA transposable elements (TEs). The miRNA-like regions map to a higher diversity of smRNAs than regions without miRNA-like structure, explaining up to 27% of variation in smRNA mapping for some TE superfamilies. This mapping bias is more pronounced among putatively autonomous TEs relative to nonautonomous TEs. Genome-wide, miRNA-like regions are also associated with elevated methylation levels, particularly in the CHH context. Among genes, those with miRNA-like secondary structure are 1.5-fold more highly expressed, on average, than other genes. However, these genes are also more variably expressed across the 26 nested association mapping founder lines, and this variability positively correlates with the number of mapping smRNAs. We conclude that local miRNA-like structures are a nearly ubiquitous feature of expressed regions of the maize genome, that they correlate with higher smRNA mapping and methylation, and that they may represent a trade-off between functional requirements and the potentially negative consequences of smRNA production.

Rock, scissors, paper: How RNA structure informs function

RNA can fold back on itself to adopt a wide range of structures. These range from relatively simple hairpins to intricate 3D folds and can be accompanied by regulatory interactions with both metabolites and macromolecules. The last 50 yr have witnessed elucidation of an astonishing array of RNA structures including transfer RNAs, ribozymes, riboswitches, the ribosome, the spliceosome, and most recently entire RNA structuromes. These advances in RNA structural biology have deepened insight into fundamental biological processes including gene editing, transcription, translation, and structure-based detection and response to temperature and other environmental signals. These discoveries reveal that RNA can be relatively static, like a rock; that it can have catalytic functions of cutting bonds, like scissors; and that it can adopt myriad functional shapes, like paper. We relate these extraordinary discoveries in the biology of RNA structure to the plant way of life. We trace plant-specific discovery of ribozymes and riboswitches, alternative splicing, organellar ribosomes, thermometers, whole-transcriptome structuromes and pan-structuromes, and conclude that plants have a special set of RNA structures that confer unique types of gene regulation. We finish with a consideration of future directions for the RNA structure-function field.

Genotype-environment associations to reveal the molecular basis of environmental adaptation

A fundamental goal in plant biology is to identify and understand the variation underlying plants' adaptation to their environment. Climate change has given new urgency to this goal, as society aims to accelerate adaptation of ecologically important plant species, endangered plant species, and crops to hotter, less predictable climates. In the pre-genomic era, identifying adaptive alleles was painstaking work, leveraging genetics, molecular biology, physiology, and ecology. Now, the rise of genomics and new computational approaches may facilitate this research. Genotype-environment associations (GEAs) use statistical associations between allele frequency and environment of origin to test the hypothesis that allelic variation at a given gene is adapted to local environments. Researchers may scan the genome for GEAs to generate hypotheses on adaptive genetic variants (environmental genome-wide association studies). Despite the rapid adoption of these methods, many important questions remain about the interpretation of GEA findings, which arise from fundamental unanswered questions on the genetic architecture of adaptation and limitations inherent to association-based analyses. We outline strategies to ground GEAs in the underlying hypotheses of genetic architecture and better test GEA-generated hypotheses using genetics and ecophysiology. We provide recommendations for new users who seek to learn about the molecular basis of adaptation. When combined with a rigorous hypothesis testing framework, GEAs may facilitate our understanding of the molecular basis of climate adaptation for plant improvement.

On the hidden temporal dynamics of plant adaptation

Adaptation to a wide range of environments is a major driver of plant diversity. It is now possible to catalog millions of potential adaptive genomic differences segregating between environments within a plant species in a single experiment. Understanding which of these changes contributes to adaptive phenotypic divergence between plant populations is a major goal of evolutionary biologists and crop breeders. In this review, we briefly highlight the approaches frequently used to understand the genetic basis of adaptive phenotypes in plants, and we discuss some of the limitations of these methods. We propose that direct observation of the process of adaptation using multigenerational studies and whole genome sequencing is a crucial missing component of recent studies of plant adaptation because it complements several shortcomings of sampling-based techniques.

RNA biology takes root in plant systems

Advances in RNA biology such as RNAi, CRISPR, and the first mRNA vaccine represent the enormous potential of RNA research to address current problems. Additionally, plants are a diverse and undeniably essential resource for life threatened by climate change, loss of arable land, and pollution. Different aspects of RNA such as its processing, modification and structure are intertwined with plant development, physiology and stress response. This report details the findings of researchers around the world during the 23rd Penn State Symposium in Plant Biology with a focus in RNA biology.

Experimental demonstration and pan-structurome prediction of climate-associated riboSNitches in Arabidopsis

Background

Genome-wide association studies (GWAS) aim to correlate phenotypic changes with genotypic variation. Upon transcription, single nucleotide variants (SNVs) may alter mRNA structure, with potential impacts on transcript stability, macromolecular interactions, and translation. However, plant genomes have not been assessed for the presence of these structure-altering polymorphisms or “riboSNitches.”

Results

We experimentally demonstrate the presence of riboSNitches in transcripts of two Arabidopsis genes, ZINC RIBBON 3 (ZR3) and COTTON GOLGI-RELATED 3 (CGR3), which are associated with continentality and temperature variation in the natural environment. These riboSNitches are also associated with differences in the abundance of their respective transcripts, implying a role in regulating the gene's expression in adaptation to local climate conditions. We then computationally predict riboSNitches transcriptome-wide in mRNAs of 879 naturally inbred Arabidopsis accessions. We characterize correlations between SNPs/riboSNitches in these accessions and 434 climate descriptors of their local environments, suggesting a role of these variants in local adaptation. We integrate this information in CLIMtools V2.0 and provide a new web resource, T-CLIM, that reveals associations between transcript abundance variation and local environmental variation.

Conclusion

We functionally validate two plant riboSNitches and, for the first time, demonstrate riboSNitch conditionality dependent on temperature, coining the term “conditional riboSNitch.” We provide the first pan-genome-wide prediction of riboSNitches in plants. We expand our previous CLIMtools web resource with riboSNitch information and with 1868 additional Arabidopsis genomes and 269 additional climate conditions, which will greatly facilitate in silico studies of natural genetic variation, its phenotypic consequences, and its role in local adaptation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02656-4.