The strength and pattern of natural selection on gene expression in rice

Transcription factor OsWRKY11 induces rice heading at low concentrations but inhibits rice heading at high concentrations

The heading date of rice is a crucial agronomic characteristic that influences its adaptability to different regions and its productivity potential. Despite the involvement of WRKY transcription factors in various biological processes related to development, the precise mechanisms through which these transcription factors regulate the heading date in rice have not been well elucidated. The present study identified OsWRKY11 as a WRKY transcription factor which exhibits a pivotal function in the regulation of the heading date in rice through a comprehensive screening of a clustered regularly interspaced palindromic repeats (CRISPR) ‒ CRISPR-associated nuclease 9 mutant library that specifically targets the WRKY genes in rice. The heading date of oswrky11 mutant plants and OsWRKY11-overexpressing plants was delayed compared with that of the wild-type plants under short-day and long-day conditions. Mechanistic investigation revealed that OsWRKY11 exerts dual effects on transcriptional promotion and suppression through direct and indirect DNA binding, respectively. Under normal conditions, OsWRKY11 facilitates flowering by directly inducing the expression of OsMADS14 and OsMADS15. The presence of elevated levels of OsWRKY11 protein promote formation of a ternary protein complex involving OsWRKY11, Heading date 1 (Hd1), and Days to heading date 8 (DTH8), and this complex then suppresses the expression of Ehd1, which leads to a delay in the heading date. Subsequent investigation revealed that a mild drought condition resulted in a modest increase in OsWRKY11 expression, promoting heading. Conversely, under severe drought conditions, a significant upregulation of OsWRKY11 led to the suppression of Ehd1 expression, ultimately causing a delay in heading date. Our findings uncover a previously unacknowledged mechanism through which the transcription factor OsWRKY11 exerts a dual impact on the heading date by directly and indirectly binding to the promoters of target genes.

Systems genomics of salinity stress response in rice

Populations can adapt to stressful environments through changes in gene expression. However, the role of gene regulation in mediating stress response and adaptation remains largely unexplored. Here, we use an integrative field dataset obtained from 780 plants of Oryza sativa ssp. indica (rice) grown in a field experiment under normal or moderate salt stress conditions to examine selection and evolution of gene expression variation under salinity stress conditions. We find that salinity stress induces increased selective pressure on gene expression. Further, we show that trans-eQTLs rather than cis-eQTLs are primarily associated with rice's gene expression under salinity stress, potentially via a few master-regulators. Importantly, and contrary to the expectations, we find that cis-trans reinforcement is more common than cis-trans compensation which may be reflective of rice diversification subsequent to domestication. We further identify genetic fixation as the likely mechanism underlying this compensation/reinforcement. Additionally, we show that cis- and trans-eQTLs are under different selection regimes, giving us insights into the evolutionary dynamics of gene expression variation. By examining genomic, transcriptomic, and phenotypic variation across a rice population, we gain insights into the molecular and genetic landscape underlying adaptive salinity stress responses, which is relevant for other crops and other stresses.

Synergistic response to climate stressors in coral is associated with genotypic variation in baseline expression

As environments are rapidly reshaped due to climate change, phenotypic plasticity plays an important role in the ability of organisms to persist and is considered an especially important acclimatization mechanism for long-lived sessile organisms such as reef-building corals. Often, this ability of a single genotype to display multiple phenotypes depending on the environment is modulated by changes in gene expression, which can vary in response to environmental changes via two mechanisms: baseline expression and expression plasticity. We used transcriptome-wide expression profiling of eleven genotypes of common-gardened Acropora cervicornis to explore genotypic variation in the expression response to thermal and acidification stress, both individually and in combination. We show that the combination of these two stressors elicits a synergistic gene expression response, and that both baseline expression and expression plasticity in response to stress show genotypic variation. Additionally, we demonstrate that frontloading of a large module of coexpressed genes is associated with greater retention of algal symbionts under combined stress. These results illustrate that variation in the gene expression response of individuals to climate change stressors can persist even when individuals have shared environmental histories, affecting their performance under future climate change scenarios.

Combined GWAS and eGWAS reveals the genetic basis underlying drought tolerance in emmer wheat (Triticum turgidum L.)

Drought is one of the major environmental constraints for wheat production world-wide. As the progenitor and genetic reservoir of common wheat, emmer wheat is considered as an invaluable gene pool for breeding drought-tolerant wheat. Combining GWAS and eGWAS analysis of 107 accessions, we identified 86 QTLs, 105 462 eQTLs as well as 68 eQTL hotspots associating with drought tolerance (DT) in emmer wheat. A complex regulatory network composed of 185 upstream regulator and 2432 downstream drought-responsive candidates was developed, of which TtOTS1 was found to play a negative effect in determining DT through affecting root development. This study sheds light on revealing the genetic basis underlying DT, which will provide the indispensable genes and germplasm resources for elite drought tolerance wheat improvement and breeding.

Life-Cycle Multiomics of Rice Shoots Reveals Growth Stage-Specific Effects of Drought Stress and Time-Lag Drought Responses

Field-grown rice plants are exposed to various stresses at different stages of their life cycle, but little is known about the effects of stage-specific stresses on phenomes and transcriptomes. In this study, we performed integrated time-course multiomics on rice at 3-d intervals from seedling to heading stage under six drought conditions in a well-controlled growth chamber. Drought stress at seedling and reproductive stages reduced yield performance by reducing seed number and setting rate, respectively. High temporal resolution analysis revealed that drought response occurred in two steps: a rapid response via the abscisic acid (ABA) signaling pathway and a slightly delayed DEHYDRATION-RESPONSIVE ELEMENT-BINDING PROTEIN (DREB) pathway, allowing plants to respond flexibly to deteriorating soil water conditions. Our long-term time-course multiomics showed that temporary drought stress delayed flowering due to prolonged expression of the flowering repressor gene GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (Ghd7) and delayed expression of the florigen genes HEADING DATE 3a (Hd3a) and RICE FLOWERING LOCUS T 1 (RFT1). Our life-cycle multiomics dataset on rice shoots under drought conditions provides a valuable resource for further functional genomic studies to improve crop resilience to drought stress.

Differentiation of Morphological Traits and Genome-Wide Expression Patterns between Rice Subspecies Indica and Japonica

Changes in gene expression patterns can lead to the variation of morphological traits. This phenomenon is particularly evident in recent evolution events such as crop domestication and responses to environmental stress, where alterations in expression levels can efficiently give rise to domesticated syndromes and adaptive phenotypes. Rice (Oryza sativa L.), one of the world's most crucial cereal crops, comprises two morphologically distinct subspecies, Indica and Japonica. To investigate the morphological divergence between these two rice subspecies, this study planted a total of 315 landrace individuals of both Indica and Japonica under identical cultivation conditions. Out of the 16 quantitative traits measured in this study, 12 exhibited significant differences between the subspecies. To determine the genetic divergence between Indica and Japonica at the whole-genome sequence level, we constructed a phylogenetic tree using a resequencing dataset encompassing 95 rice landrace accessions. The samples formed two major groups that neatly corresponded to the two subspecies, Indica and Japonica. Furthermore, neighbor-joining (NJ) trees based on the expression quantity of effectively expressed genes (EEGs) across five different tissues categorized 12 representative samples into two major clades aligning with the two subspecies. These results imply that divergence in genome-wide expression levels undergoes stabilizing selection under non-stressful conditions, with evolutionary trends in expression levels mirroring sequence variation levels. This study further supports the pivotal role of changes in genome-wide expression regulation in the divergence of the two rice subspecies, Indica and Japonica.

Evolutionary Analyses of Gene Expression Divergence in Panicum hallii: Exploring Constitutive and Plastic Responses Using Reciprocal Transplants

The evolution of gene expression is thought to be an important mechanism of local adaptation and ecological speciation. Gene expression divergence occurs through the evolution of cis- polymorphisms and through more widespread effects driven by trans-regulatory factors. Here, we explore expression and sequence divergence in a large sample of Panicum hallii accessions encompassing the species range using a reciprocal transplantation experiment. We observed widespread genotype and transplant site drivers of expression divergence, with a limited number of genes exhibiting genotype-by-site interactions. We used a modified FST-QST outlier approach (QPC analysis) to detect local adaptation. We identified 514 genes with constitutive expression divergence above and beyond the levels expected under neutral processes. However, no plastic expression responses met our multiple testing correction as QPC outliers. Constitutive QPC outlier genes were involved in a number of developmental processes and responses to abiotic environments. Leveraging earlier expression quantitative trait loci results, we found a strong enrichment of expression divergence, including for QPC outliers, in genes previously identified with cis and cis-environment interactions but found no patterns related to trans-factors. Population genetic analyses detected elevated sequence divergence of promoters and coding sequence of constitutive expression outliers but little evidence for positive selection on these proteins. Our results are consistent with a hypothesis of cis-regulatory divergence as a primary driver of expression divergence in P. hallii.

Environmental control of rice flowering time

Correct measurement of environmental parameters is fundamental for plant fitness and survival, as well as for timing developmental transitions, including the switch from vegetative to reproductive growth. Important parameters that affect flowering time include day length (photoperiod) and temperature. Their response pathways have been best described in Arabidopsis, which currently offers a detailed conceptual framework and serves as a comparison for other species. Rice, the focus of this review, also possesses a photoperiodic flowering pathway, but 150 million years of divergent evolution in very different environments have diversified its molecular architecture. The ambient temperature perception pathway is strongly intertwined with the photoperiod pathway and essentially converges on the same genes to modify flowering time. When observing network topologies, it is evident that the rice flowering network is centered on EARLY HEADING DATE 1, a rice-specific transcriptional regulator. Here, we summarize the most important features of the rice photoperiodic flowering network, with an emphasis on its uniqueness, and discuss its connections with hormonal, temperature perception, and stress pathways.

A low-coverage 3' RNA-seq to detect homeolog expression in polyploid wheat

Although allopolyploid species are common among natural and crop species, it is not easy to distinguish duplicated genes, known as homeologs, during their genomic analysis. Yet, cost-efficient RNA sequencing (RNA-seq) is to be developed for large-scale transcriptomic studies such as time-series analysis and genome-wide association studies in allopolyploids. In this study, we employed a 3' RNA-seq utilizing 3' untranslated regions (UTRs) containing frequent mutations among homeologous genes, compared to coding sequence. Among the 3' RNA-seq protocols, we examined a low-cost method Lasy-Seq using an allohexaploid bread wheat, Triticum aestivum. HISAT2 showed the best performance for 3' RNA-seq with the least mapping errors and quick computational time. The number of detected homeologs was further improved by extending 1 kb of the 3' UTR annotation. Differentially expressed genes in response to mild cold treatment detected by the 3' RNA-seq were verified with high-coverage conventional RNA-seq, although the latter detected more differentially expressed genes. Finally, downsampling showed that even a 2 million sequencing depth can still detect more than half of expressed homeologs identifiable by the conventional 32 million reads. These data demonstrate that this low-cost 3' RNA-seq facilitates large-scale transcriptomic studies of allohexaploid wheat and indicate the potential application to other allopolyploid species.

Transposons are important contributors to gene expression variability under selection in rice populations

Transposable elements (TEs) are an important source of genome variability. Here, we analyze their contribution to gene expression variability in rice by performing a TE insertion polymorphism expression quantitative trait locus mapping using expression data from 208 varieties from the Oryza sativa ssp. indica and O. sativa ssp. japonica subspecies. Our data show that TE insertions are associated with changes of expression of many genes known to be targets of rice domestication and breeding. An important fraction of these insertions were already present in the rice wild ancestors, and have been differentially selected in indica and japonica rice populations. Taken together, our results show that small changes of expression in signal transduction genes induced by TE insertions accompany the domestication and adaptation of rice populations.

Weaker selection on genes with treatment-specific expression consistent with a limit on plasticity evolution in Arabidopsis thaliana

Differential gene expression between environments often underlies phenotypic plasticity. However, environment-specific expression patterns are hypothesized to relax selection on genes, and thus limit plasticity evolution. We collated over 27 terabases of RNA-sequencing data on Arabidopsis thaliana from over 300 peer-reviewed studies and 200 treatment conditions to investigate this hypothesis. Consistent with relaxed selection, genes with more treatment-specific expression have higher levels of nucleotide diversity and divergence at nonsynonymous sites but lack stronger signals of positive selection. This result persisted even after controlling for expression level, gene length, GC content, the tissue specificity of expression, and technical variation between studies. Overall, our investigation supports the existence of a hypothesized trade-off between the environment specificity of a gene's expression and the strength of selection on said gene in A. thaliana. Future studies should leverage multiple genome-scale datasets to tease apart the contributions of many variables in limiting plasticity evolution.

Plant domestication: setting biological clocks

Through domestication of wild species, humans have induced large changes in the developmental and circadian clocks of plants. As a result of these changes, modern crops are more productive and adaptive to contrasting environments from the center of origin of their wild ancestors, albeit with low genetic variability and abiotic stress tolerance. Likewise, a complete restructuring of plant metabolic timekeeping probably occurred during crop domestication. Here, we highlight that contrasting timings among organs in wild relatives of crops allowed them to recognize environmental adversities faster. We further propose that connections among biological clocks, which were established during plant domestication, may represent a fundamental source of genetic variation to improve crop resilience and yield.

Evolution of flowering time genes in rice: From the paleolithic to the anthropocene

The evolutionary paths of humans and plants have crossed more than once throughout millennia. While agriculture contributed to the evolution of societies in prehistory, human selection of desirable traits contributed to the evolution of crops during centuries of cultivation. Among cereal crops, rice is currently grown around the globe and represents staple food for almost half of the world population. Over time, rice cultivation has expanded from subtropical to temperate regions thanks to artificial selection of mutants with impaired response to photoperiod. Additional regulatory mechanisms control flowering in response to diverse environmental cues, anticipating or delaying the floral transition to produce seeds in more favourable conditions. Nevertheless, the changing climate is threatening grain production because modern cultivars are sensitive to external fluctuations that go beyond their physiological range. One possibility to guarantee food production could be the exploitation of novel varieties obtained by crossing highly productive Asian rice with stress tolerant African rice. This review explores the genetic basis of the key traits that marked the long journey of rice cultivation from the end of the paleolithic to the anthropocene, with a focus on heading date. By 2050, will rice plants of the future flower in the outer space?

Effects of increased ozone on rice panicle morphology

Ground-level ozone threatens rice production, which provides staple food for more than half of the world's population. Improving the adaptability of rice crops to ozone pollution is essential to ending global hunger. Rice panicles not only affect grain yield and grain quality but also the adaptability of plants to environmental changes, but the effects of ozone on rice panicles are not well understood. Through an open top chamber experiment, we investigated the effects of long-term and short-term ozone on the traits of rice panicles, finding that both long-term and short-term ozone significantly reduced the number of panicle branches and spikelets in rice, and especially the fertility of spikelets in hybrid cultivar. The reduction in spikelet quantity and fertility because of ozone exposure is caused by changes in secondary branches and attached spikelet. These results suggest the potential for effective adaptation to ozone by altering breeding targets and developing growth stage-specific agricultural techniques.

Gene expression differentials driven by mass rearing and artificial selection in black soldier fly colonies

The micro-evolutionary forces that shape genetic diversity during domestication have been assessed in many plant and animal systems. However, the impact of these processes on gene expression, and consequent functional adaptation to artificial environments, remains under-investigated. In this study, whole-transcriptome dynamics associated with the early stages of domestication of the black soldier fly (BSF), Hermetia illucens, were assessed. Differential gene expression (DGE) was evaluated in relation to (i) generational time within the cultured environment (F2 vs. F3), and (ii) two selection strategies [no artificial selective pressure (NS); and selection for greater larval mass (SEL)]. RNA-seq was conducted on 5th instar BSF larvae (n = 36), representing equal proportions of the NS (F2 = 9; F3 = 9) and SEL (F2 = 9; F3 = 9) groups. A multidimensional scaling plot revealed greater gene expression variability within the NS and F2 subgroups, while the SEL group clustered separately with lower levels of variation. Comparisons between generations revealed 898 differentially expressed genes (DEGs; FDR-corrected p < 0.05), while between selection strategies, 213 DEGs were observed (FDR-corrected p < 0.05). Enrichment analyses revealed that metabolic, developmental, and defence response processes were over-expressed in the comparison between F2 and F3 larvae, while metabolic processes were the main differentiating factor between NS and SEL lines. This illustrates the functional adaptations that occur in BSF colonies across generations due to mass rearing; as well as highlighting genic dynamics associated with artificial selection for production traits that might inform future selective breeding strategies.

Gene-by-environment interactions in plants: Molecular mechanisms, environmental drivers, and adaptive plasticity

Plants demonstrate a broad range of responses to environmental shifts. One of the most remarkable responses is plasticity, which is the ability of a single plant genotype to produce different phenotypes in response to environmental stimuli. As with all traits, the ability of plasticity to evolve depends on the presence of underlying genetic diversity within a population. A common approach for evaluating the role of genetic variation in driving differences in plasticity has been to study genotype-by-environment interactions (G × E). G × E occurs when genotypes produce different phenotypic trait values in response to different environments. In this review, we highlight progress and promising methods for identifying the key environmental and genetic drivers of G × E. Specifically, methodological advances in using algorithmic and multivariate approaches to understand key environmental drivers combined with new genomic innovations can greatly increase our understanding about molecular responses to environmental stimuli. These developing approaches can be applied to proliferating common garden networks that capture broad natural environmental gradients to unravel the underlying mechanisms of G × E. An increased understanding of G × E can be used to enhance the resilience and productivity of agronomic systems.

Burning questions for a warming and changing world: 15 unknowns in plant abiotic stress

We present unresolved questions in plant abiotic stress biology as posed by 15 research groups with expertise spanning eco-physiology to cell and molecular biology. Common themes of these questions include the need to better understand how plants detect water availability, temperature, salinity, and rising carbon dioxide (CO2) levels; how environmental signals interface with endogenous signaling and development (e.g. circadian clock and flowering time); and how this integrated signaling controls downstream responses (e.g. stomatal regulation, proline metabolism, and growth versus defense balance). The plasma membrane comes up frequently as a site of key signaling and transport events (e.g. mechanosensing and lipid-derived signaling, aquaporins). Adaptation to water extremes and rising CO2 affects hydraulic architecture and transpiration, as well as root and shoot growth and morphology, in ways not fully understood. Environmental adaptation involves tradeoffs that limit ecological distribution and crop resilience in the face of changing and increasingly unpredictable environments. Exploration of plant diversity within and among species can help us know which of these tradeoffs represent fundamental limits and which ones can be circumvented by bringing new trait combinations together. Better defining what constitutes beneficial stress resistance in different contexts and making connections between genes and phenotypes, and between laboratory and field observations, are overarching challenges.

Polymorphisms in alternative oxidase genes from ecotypes of Arabidopsis and rice revealed an environment-induced linkage to altitude and rainfall

We investigated SNPs in alternative oxidase (AOX) genes and their connection to ecotype origins (climate, altitude, and rainfall) by using genomic data sets of Arabidopsis and rice populations from 1190 and 90 ecotypes, respectively. Parameters were defined to detect non-synonymous SNPs in the AOX ORF, which revealed amino acid (AA) changes in AOX1c, AOX1d, and AOX2 from Arabidopsis and AOX1c from rice in comparison to AOX references from Columbia-0 and Japonica ecotypes, respectively. Among these AA changes, Arabidopsis AOX1c_A161E&G165R and AOX1c_R242S revealed a link to high rainfall and high altitude, respectively, while all other changes in Arabidopsis and rice AOX was connected to high altitude and rainfall. Comparative 3D modeling showed that all mutant AOX presented structural differences in relation to the respective references. Molecular docking analysis uncovered lower binding affinity values between AOX and the substrate ubiquinol for most of the identified structures compared to their reference, indicating better enzyme-substrate binding affinities. Thus, our in silico data suggest that the majority of the AA changes found in the available ecotypes will confer better enzyme-subtract interactions and thus indicate environment-related, more efficient AOX activity.

Natural variation of DROT1 confers drought adaptation in upland rice

Upland rice is a distinct ecotype that grows in aerobic environments and tolerates drought stress. However, the genetic basis of its drought resistance is unclear. Here, using an integrative approach combining a genome-wide association study with analyses of introgression lines and transcriptomic profiles, we identify a gene, DROUGHT1 (DROT1), encoding a COBRA-like protein that confers drought resistance in rice. DROT1 is specifically expressed in vascular bundles and is directly repressed by ERF3 and activated by ERF71, both drought-responsive transcription factors. DROT1 improves drought resistance by adjusting cell wall structure by increasing cellulose content and maintaining cellulose crystallinity. A C-to-T single-nucleotide variation in the promoter increases DROT1 expression and drought resistance in upland rice. The potential elite haplotype of DROT1 in upland rice could originate in wild rice (O. rufipogon) and may be beneficial for breeding upland rice varieties.

Engineering drought and salinity tolerance traits in crops through CRISPR-mediated genome editing: Targets, tools, challenges, and perspectives

Prolonged periods of drought triggered by climate change hamper plant growth and cause substantial agricultural yield losses every year. In addition to drought, salinity is one of the major abiotic stresses that severely affect crop health and agricultural production. Plant responses to drought and salinity involve multiple processes that operate in a spatiotemporal manner, such as stress sensing, perception, epigenetic modifications, transcription, post-transcriptional processing, translation, and post-translational changes. Consequently, drought and salinity stress tolerance are polygenic traits influenced by genome-environment interactions. One of the ideal solutions to these challenges is the development of high-yielding crop varieties with enhanced stress tolerance, together with improved agricultural practices. Recently, genome-editing technologies, especially clustered regularly interspaced short palindromic repeats (CRISPR) tools, have been effectively applied to elucidate how plants deal with drought and saline environments. In this work, we aim to portray that the combined use of CRISPR-based genome engineering tools and modern genomic-assisted breeding approaches are gaining momentum in identifying genetic determinants of complex traits for crop improvement. This review provides a synopsis of plant responses to drought and salinity stresses at the morphological, physiological, and molecular levels. We also highlight recent advances in CRISPR-based tools and their use in understanding the multi-level nature of plant adaptations to drought and salinity stress. Integrating CRISPR tools with modern breeding approaches is ideal for identifying genetic factors that regulate plant stress-response pathways and for the introgression of beneficial traits to develop stress-resilient crops.

A single-nucleotide polymorphism in WRKY33 promoter is associated with the cold sensitivity in cultivated tomato

Natural variations in cis-regulatory regions often affect crop phenotypes by altering gene expression. However, the mechanism of how promoter mutations affect gene expression and crop stress tolerance is still poorly understood. In this study, by analyzing RNA-sequencing (RNA-Seq) data and reverse transcription quantitative real-time PCR validation in the cultivated tomato and its wild relatives, we reveal that the transcripts of WRKY33 are almost unchanged in cold-sensitive cultivated tomato Solanum lycopersicum L. 'Ailsa Craig' but are significantly induced in cold-tolerant wild tomato relatives Solanum habrochaites LA1777 and Solanum pennellii LA0716 under cold stress. Overexpression of SlWRKY33 or ShWRKY33 positively regulates cold tolerance in tomato. Variant of the critical W-box in SlWRKY33 promoter results in the loss of self-transcription function of SlWRKY33 under cold stress. Analysis integrating RNA-Seq and chromatin immunoprecipitation sequencing data reveals that SlWRKY33 directly targets and induces multiple kinases, transcription factors, and molecular chaperone genes, such as CDPK11, MYBS3, and BAG6, thus enhancing cold tolerance. In addition, heat- and Botrytis-induced WRKY33s expression in both wild and cultivated tomatoes are independent of the critical W-box variation. Our findings suggest nucleotide polymorphism in cis-regulatory regions is crucial for different cold sensitivity between cultivated and wild tomato plants.

Population-level transcriptomes reveal gene expression and splicing underlying cadmium accumulation in barley

Genetic variation is an important determinant of gene transcription, which in turn contributes to functional and phenotypic diversity. Identification of the genetic variants controlling gene expression and alternative splicing in crops responding to cadmium (Cd), an important issue for food safety and human health, is of great value to improve our understanding of Cd accumulation-related genes. Here we report an in-depth survey of population-level transcriptome variation of barley (Hordeum vulgare) core accessions under Cd exposure. We reveal marked transcriptomic changes in response to Cd exposure, and these are largely independent of tissues. A genome-wide association study (GWAS) revealed 59 498 expression quantitative trait loci (eQTLs) and 23 854 splicing quantitative trait loci (sQTLs), leading to a complex network that covers 66.6% of the expressed genes, including 68 metal transporter genes. On average, 41.0% of sQTLs overlapped with eQTLs across different tissues, indicating that these two dimensions of transcript variation are largely independent. Moreover, we found that 34.5% of GWAS QTLs that underlie 10 Cd accumulation traits in barley are co-localized with eQTLs and sQTLs, which could imply a mechanistic role of different genetic variants affecting gene expression and alternative splicing in these traits. This study highlights the role of distal and proximal genetic effects on gene expression, splicing, and phenotypic plasticity. We anticipate that our results on the genetic control of expression and splicing underlying Cd accumulation provide a bridge to better understand genetic variation and phenotypic diversity to elucidate the mechanisms underlying Cd accumulation in plants.

Molecular Regulation and Evolution of Redox Homeostasis in Photosynthetic Machinery

The recent advances in plant biology have significantly improved our understanding of reactive oxygen species (ROS) as signaling molecules in the redox regulation of complex cellular processes. In plants, free radicals and non-radicals are prevalent intra- and inter-cellular ROS, catalyzing complex metabolic processes such as photosynthesis. Photosynthesis homeostasis is maintained by thiol-based systems and antioxidative enzymes, which belong to some of the evolutionarily conserved protein families. The molecular and biological functions of redox regulation in photosynthesis are usually to balance the electron transport chain, photosystem II, photosystem I, mesophyll and bundle sheath signaling, and photo-protection regulating plant growth and productivity. Here, we review the recent progress of ROS signaling in photosynthesis. We present a comprehensive comparative bioinformatic analysis of redox regulation in evolutionary distinct photosynthetic cells. Gene expression, phylogenies, sequence alignments, and 3D protein structures in representative algal and plant species revealed conserved key features including functional domains catalyzing oxidation and reduction reactions. We then discuss the antioxidant-related ROS signaling and important pathways for achieving homeostasis of photosynthesis. Finally, we highlight the importance of plant responses to stress cues and genetic manipulation of disturbed redox status for balanced and enhanced photosynthetic efficiency and plant productivity.

The Function of BBX Gene Family under Multiple Stresses in Nicotiana tabacum

B-box (BBX) is a zinc finger transcription factor, which is involved in regulating the growth and development of plants and resisting various stresses. In this study, 43 NtBBX genes were identified and divided into five subgroups in tobacco. The members in each subgroup had similar characteristics. The promoter region of NtBBX genes had cis-acting elements related to light response, hormone regulation and stress response. Transcriptome analysis showed that NtBBX30 was significantly up-regulated, and NtBBX12, NtBBX13, NtBBX16 and NtBBX17 were significantly down-regulated under abiotic stresses. The NtBBX genes also responded to the infection of Ralstonia solanacearum. NtBBX9, NtBBX1, NtBBX15 and NtBBX17 showed the greatest response under stresses. The NtBBX genes are expressed in various degrees under different tissues. This research will provide a solid foundation for further study of the biological function of NtBBX genes in tobacco.

Growth-limiting drought stress induces time-of-day-dependent transcriptome and physiological responses in hybrid poplar

Drought stress negatively impacts the health of long-lived trees. Understanding the genetic mechanisms that underpin response to drought stress is requisite for selecting or enhancing climate change resilience. We aimed to determine how hybrid poplars respond to prolonged and uniform exposure to drought; how responses to moderate and more severe growth-limiting drought stresses differed; and how drought responses change throughout the day. We established hybrid poplar trees (Populus × 'Okanese') from unrooted stem cutting with abundant soil moisture for 6 weeks. We then withheld water to establish well-watered, moderate and severe growth-limiting drought conditions. These conditions were maintained for 3 weeks during which growth was monitored. We then measured photosynthetic rates and transcriptomes of leaves that had developed during the drought treatments at two times of day. The moderate and severe drought treatments elicited distinct changes in growth and development, photosynthetic rates and global transcriptome profiles. Notably, the time of day of sampling produced the strongest effect in the transcriptome data. The moderate drought treatment elicited global transcriptome changes that were intermediate to the severe and well-watered treatments in the early evening but did not elicit a strong drought response in the morning. Stable drought conditions that are sufficient to limit plant growth elicit distinct transcriptional profiles depending on the degree of water limitation and on the time of day at which they are measured. There appears to be a limited number of genes and functional gene categories that are responsive to all of the tested drought conditions in this study emphasizing the complex nature of drought regulation in long-lived trees.

Genomics and transcriptomics reveal new molecular mechanism of vibriosis resistance in fish

Infectious diseases have caused dramatic production decline and economic loss for fish aquaculture. However, the poor understanding of fish disease resistance severely hampered disease prevention. Chinese tongue sole (Cynoglossus semilaevis) is an important economic flatfish suffering from vibriosis. Here we used genomic, transcriptomic and experimental approaches to investigate the molecular genetic mechanisms underlying fish vibriosis resistance. A genome-wide comparison revealed that the genes under selective sweeps were enriched for glycosaminoglycan (GAG) chondroitin sulfate (CS)/dermatan sulfate (DS) metabolism. Transcriptomic analyses prioritized synergic gene expression patterns in this pathway, which may lead to an increased CS/DS content in the resistant family. Further experimental evidence showed that carbohydrate sulfotransferases 12 (Chst12), a key enzyme for CS/DS biosynthesis, has a direct antibacterial activity. To the best of our knowledge, this is the first report that the chst12 gene has a bactericidal effect. In addition, CS/DS is a major component of the extracellular matrix (ECM) and the selection signatures and fine-tuned gene expressions of ECM-receptor interaction genes indicated a modification in the ECM structure with an enhancement of the barrier function. Furthermore, functional studies conducted on Col6a2, encoding a collagen gene which constitutes the ECM, pointed to that it may act as a cellular receptor for Vibrio pathogens, thus plays an important role for the Vibrio invasion. Taken together, these findings provide new insights into the molecular protective mechanism underlying vibriosis resistance in fish, which offers crucial genomic resources for the resistant germplasm breeding and infectious disease control in fish culturing.

Deleterious mutations and the rare allele burden on rice gene expression

Deleterious genetic variation is maintained in populations at low frequencies. Under a model of stabilizing selection, rare (and presumably deleterious) genetic variants are associated with increase or decrease in gene expression from some intermediate optimum. We investigate this phenomenon in a population of largely Oryza sativa ssp. indica rice landraces under normal unstressed wet and stressful drought field conditions. We include single nucleotide polymorphisms, insertion/deletion mutations, and structural variants in our analysis and find a stronger association between rare variants and gene expression outliers under the stress condition. We also show an association of the strength of this rare variant effect with linkage, gene expression levels, network connectivity, local recombination rate, and fitness consequence scores, consistent with the stabilizing selection model of gene expression.

Genomic insights into the evolutionary history and diversification of bulb traits in garlic

Background

Garlic is an entirely sterile crop with important value as a vegetable, condiment, and medicine. However, the evolutionary history of garlic remains largely unknown.

Results

Here we report a comprehensive map of garlic genomic variation, consisting of amazingly 129.4 million variations. Evolutionary analysis indicates that the garlic population diverged at least 100,000 years ago, and the two groups cultivated in China were domesticated from two independent routes. Consequently, 15.0 and 17.5% of genes underwent an expression change in two cultivated groups, causing a reshaping of their transcriptomic architecture. Furthermore, we find independent domestication leads to few overlaps of deleterious substitutions in these two groups due to separate accumulation and selection-based removal. By analysis of selective sweeps, genome-wide trait associations and associated transcriptomic analysis, we uncover differential selections for the bulb traits in these two garlic groups during their domestication.

Conclusions

This study provides valuable resources for garlic genomics-based breeding, and comprehensive insights into the evolutionary history of this clonal-propagated crop.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02756-1.

Unraveling the genetics of polyamine metabolism in barley for senescence-related crop improvement

We explored the polyamine (PA) metabolic pathway genes in barley (Hv) to understand plant development and stress adaptation in Gramineae crops with emphasis on leaf senescence. Bioinformatics and functional genomics tools were utilized for genome-wide identification, comprehensive gene features, evolution, development and stress effects on the expression of the polyamine metabolic pathway gene families (PMGs). Three S-adenosylmethionine decarboxylases (HvSAMDCs), two ornithine decarboxylases (HvODCs), one arginine decarboxylase (HvADC), one spermidine synthase (HvSPDS), two spermine synthases (HvSPMSs), five copper amine oxidases (HvCuAOs) and seven polyamine oxidases (HvPAOs) members of PMGs were identified and characterized in barley. All the HvPMG genes were found to be distributed on all chromosomes of barley. The phylogenetic and comparative assessment revealed that PA metabolic pathway is highly conserved in plants and the prediction of nine H. vulgare miRNAs (hvu-miR) target sites, 18 protein-protein interactions and 961 putative CREs in the promoter region were discerned. Gene expression of HvSAMDC3, HvCuAO7, HvPAO4 and HvSPMS1 was apparent at every developmental stage. SPDS/SPMS gene family was found to be the most responsive to induced leaf senescence. This study provides a reference for the functional investigation of the molecular mechanism(s) that regulate polyamine metabolism in plants as a tool for future breeding decision management systems.

Detecting signatures of selection on gene expression

A substantial amount of phenotypic diversity results from changes in gene expression levels and patterns. Understanding how the transcriptome evolves is therefore a key priority in identifying mechanisms of adaptive change. However, in contrast to powerful models of sequence evolution, we lack a consensus model of gene expression evolution. Furthermore, recent work has shown that many of the comparative approaches used to study gene expression are subject to biases that can lead to false signatures of selection. Here we first outline the main approaches for describing expression evolution and their inherent biases. Next, we bridge the gap between the fields of phylogenetic comparative methods and transcriptomics to reinforce the main pitfalls of inferring selection on expression patterns and use simulation studies to show that shifts in tissue composition can heavily bias inferences of selection. We close by highlighting the multi-dimensional nature of transcriptional variation and identifying major unanswered questions in disentangling how selection acts on the transcriptome.

OsEIL1 protects rice growth under NH4+ nutrition by regulating OsVTC1-3-dependent N-glycosylation and root NH4+ efflux

Rice is known for its superior adaptation to ammonium (NH₄⁺ ) as a nitrogen source. Compared to many other cereals, it displays lower NH₄⁺ efflux in roots and higher nitrogen-use efficiency on NH₄⁺ . A critical role for GDP-mannose pyrophosphorylase (VTC1) in controlling root NH₄⁺ fluxes was previously documented in Arabidopsis, but the molecular pathways involved in regulating VTC1-dependent NH₄⁺ efflux remain unclear. Here, we report that ETHYLENE-INSENSITIVE3-LIKE1 (OsEIL1) acts as a key transcription factor regulating OsVTC1-3-dependent NH₄⁺ efflux and protein N-glycosylation in rice grown under NH₄⁺ nutrition. We show that OsEIL1 in rice plays a contrasting role to Arabidopsis-homologous ETHYLENE-INSENSITIVE3 (AtEIN3) and maintains rice growth under NH₄⁺ by stabilizing protein N-glycosylation and reducing root NH₄⁺ efflux. OsEIL1 constrains NH₄⁺ efflux by activation of OsVTC1-3, but not OsVTC1-1 or OsVTC1-8. OsEIL1 binds directly to the promoter EIN3-binding site (EBS) of OsVTC1-3 in vitro and in vivo and acts to increase the transcription of OsVTC1-3. Our work demonstrates an important link between excessive root NH₄⁺ efflux and OsVTC1-3-mediated protein N-glycosylation in rice grown under NH₄⁺ nutrition and identifies OsEIL1 as a direct genetic regulator of OsVTC1-3 expression.

Gene regulatory networks shape developmental plasticity of root cell types under water extremes in rice

Understanding how roots modulate development under varied irrigation or rainfall is crucial for development of climate-resilient crops. We established a toolbox of tagged rice lines to profile translating mRNAs and chromatin accessibility within specific cell populations. We used these to study roots in a range of environments: plates in the lab, controlled greenhouse stress and recovery conditions, and outdoors in a paddy. Integration of chromatin and mRNA data resolves regulatory networks of the following: cycle genes in proliferating cells that attenuate DNA synthesis under submergence; genes involved in auxin signaling, the circadian clock, and small RNA regulation in ground tissue; and suberin biosynthesis, iron transporters, and nitrogen assimilation in endodermal/exodermal cells modulated with water availability. By applying a systems approach, we identify known and candidate driver transcription factors of water-deficit responses and xylem development plasticity. Collectively, this resource will facilitate genetic improvements in root systems for optimal climate resilience.

Twenty years of rice genomics research: From sequencing and functional genomics to quantitative genomics

Since the completion of the rice genome sequencing project in 2005, we have entered the era of rice genomics, which is still in its ascendancy. Rice genomics studies can be classified into three stages: structural genomics, functional genomics, and quantitative genomics. Structural genomics refers primarily to genome sequencing for the construction of a complete map of rice genome sequence. This is fundamental for rice genetics and molecular biology research. Functional genomics aims to decode the functions of rice genes. Quantitative genomics is large-scale sequence- and statistics-based research to define the quantitative traits and genetic features of rice populations. Rice genomics has been a transformative influence on rice biological research and contributes significantly to rice breeding, making rice a good model plant for studying crop sciences.

Evolutionary systems biology reveals patterns of rice adaptation to drought-prone agro-ecosystems

Rice (Oryza sativa) was domesticated around 10,000 years ago and has developed into a staple for half of humanity. The crop evolved and is currently grown in stably wet and intermittently dry agro-ecosystems, but patterns of adaptation to differences in water availability remain poorly understood. While previous field studies have evaluated plant developmental adaptations to water deficit, adaptive variation in functional and hydraulic components, particularly in relation to gene expression, has received less attention. Here, we take an evolutionary systems biology approach to characterize adaptive drought resistance traits across roots and shoots. We find that rice harbors heritable variation in molecular, physiological, and morphological traits that is linked to higher fitness under drought. We identify modules of co-expressed genes that are associated with adaptive drought avoidance and tolerance mechanisms. These expression modules showed evidence of polygenic adaptation in rice subgroups harboring accessions that evolved in drought-prone agro-ecosystems. Fitness-linked expression patterns allowed us to identify the drought-adaptive nature of optimizing photosynthesis and interactions with arbuscular mycorrhizal fungi. Taken together, our study provides an unprecedented, integrative view of rice adaptation to water-limited field conditions.

Gene regulatory circuitry of plant-environment interactions: scaling from cells to the field

Plant growth and development is the product of layers of sensing and regulation that are modulated by multifactorial environmental cues. Innovations in genomics currently allow gene regulatory control to be quantified at multiple scales and high resolution in defined cell populations and even in individual cells or nuclei in plants. The application of these 'omic technologies in highly controlled, as well as field environments is revolutionizing the recognition of factors critical to spatial and temporal responses to single or multiple environmental cues. Within and pan-species comparisons illuminate deeply conserved circuitry and targets of selection. This knowledge can benefit the breeding and engineering of crops with greater resilience to climate variability and the ability to augment nutrition through plant-microbial interactions.

Current status and future perspectives on the evolution of cis-regulatory elements in plants

Cis-regulatory elements (CREs) are short stretches (∼5-15 base pairs) of DNA capable of being bound by a transcription factor and influencing the expression of nearby genes. These regions are of great interest to anyone studying the relationship between phenotype and genotype as these sequences often dictate genes' spatio-temporal expression. Indeed, several associative signals between genotype and phenotype are known to lie outside of protein-coding regions. Therefore, a key to understand evolutionary biology requires their characterization in current and future genome assemblies. In this review, we cover some recent examples of how CRE variation contributes to phenotypic evolution, discuss evidence for the selective pressures experienced by non-coding regions of the genome, and consider several studies on accessible chromatin regions in plants and what they can tell us about CREs. Finally, we discuss how current advances in sequencing technologies will improve our knowledge of CRE variation.

Validation of a high-confidence regulatory network for gene-to-NUE phenotype in field-grown rice

Nitrogen (N) and Water (W) - two resources critical for crop productivity - are becoming increasingly limited in soils globally. To address this issue, we aim to uncover the gene regulatory networks (GRNs) that regulate nitrogen use efficiency (NUE) - as a function of water availability - in Oryza sativa, a staple for 3.5 billion people. In this study, we infer and validate GRNs that correlate with rice NUE phenotypes affected by N-by-W availability in the field. We did this by exploiting RNA-seq and crop phenotype data from 19 rice varieties grown in a 2x2 N-by-W matrix in the field. First, to identify gene-to-NUE field phenotypes, we analyzed these datasets using weighted gene co-expression network analysis (WGCNA). This identified two network modules ("skyblue" & "grey60") highly correlated with NUE grain yield (NUEg). Next, we focused on 90 TFs contained in these two NUEg modules and predicted their genome-wide targets using the N-and/or-W response datasets using a random forest network inference approach (GENIE3). Next, to validate the GENIE3 TF→target gene predictions, we performed Precision/Recall Analysis (AUPR) using nine datasets for three TFs validated in planta. This analysis sets a precision threshold of 0.31, used to "prune" the GENIE3 network for high-confidence TF→target gene edges, comprising 88 TFs and 5,716 N-and/or-W response genes. Next, we ranked these 88 TFs based on their significant influence on NUEg target genes responsive to N and/or W signaling. This resulted in a list of 18 prioritized TFs that regulate 551 NUEg target genes responsive to N and/or W signals. We validated the direct regulated targets of two of these candidate NUEg TFs in a plant cell-based TF assay called TARGET, for which we also had in planta data for comparison. Gene ontology analysis revealed that 6/18 NUEg TFs - OsbZIP23 (LOC_Os02g52780), Oshox22 (LOC_Os04g45810), LOB39 (LOC_Os03g41330), Oshox13 (LOC_Os03g08960), LOC_Os11g38870, and LOC_Os06g14670 - regulate genes annotated for N and/or W signaling. Our results show that OsbZIP23 and Oshox22, known regulators of drought tolerance, also coordinate W-responses with NUEg. This validated network can aid in developing/breeding rice with improved yield on marginal, low N-input, drought-prone soils.

Boosting the power of transcriptomics by developing an efficient gene expression profiling approach

Recent advances in plant genomics are scaling up gene expression profiling from the individual level to the population level, making transcriptomics a more powerful tool while deciphering the genome function. This study developed an efficient 3'RNA-seq method, Simplified Poly(A) Anchored Sequencing (SiPAS), to perform large-scale experiments of gene expression quantification. Aside from being cost-effective, by conducting a comprehensive performance assessment of SiPAS in hexaploid wheat, we demonstrated that SiPAS is highly sensitive, accurate, and reproducible while quantifying gene expression. Our method is anticipated to boost studies of population transcriptomics in plants and improve our understanding of genome biology.

Mapping causal genes and genetic interactions for agronomic traits using a large F2 population in rice

Dissecting the genetic mechanisms underlying agronomic traits is of great importance for crop breeding. Agronomic traits are usually controlled by multiple quantitative trait loci (QTLs) and genetic interactions, and mapping the underlying causal genes is still labor-intensive and time-consuming. Here, we present a genetic tool for directly targeting the specific causal genes by using a single-gene resolution linkage map that was constructed from 3756 F2 rice plants via targeted sequencing technology and Tukey-Kramer multiple comparisons test. Three large- and moderate-effect QTLs, qHD6-2, qGL3-1, and qGW5-2, were successfully mapped to their specific causal genes, Hd1, GS3, and GW5, respectively. A complex genetic interaction network containing 30 QTL-QTL interactions was constructed, revealing that the alternative allele of hub QTL, qHD6-2, can hide or release the genetic contributions of the alleles at interacting loci. Moreover, arranging genetic interactions in the models lead to more accurate phenotypic predictions. These results provide a community resource and new feasible strategy for deciphering the genetic mechanisms of complex agronomic traits and accelerating crop breeding.

Toward Integrated Multi-Omics Intervention: Rice Trait Improvement and Stress Management

Rice (Oryza sativa) is an imperative staple crop for nearly half of the world's population. Challenging environmental conditions encompassing abiotic and biotic stresses negatively impact the quality and yield of rice. To assure food supply for the unprecedented ever-growing world population, the improvement of rice as a crop is of utmost importance. In this era, "omics" techniques have been comprehensively utilized to decipher the regulatory mechanisms and cellular intricacies in rice. Advancements in omics technologies have provided a strong platform for the reliable exploration of genetic resources involved in rice trait development. Omics disciplines like genomics, transcriptomics, proteomics, and metabolomics have significantly contributed toward the achievement of desired improvements in rice under optimal and stressful environments. The present review recapitulates the basic and applied multi-omics technologies in providing new orchestration toward the improvement of rice desirable traits. The article also provides a catalog of current scenario of omics applications in comprehending this imperative crop in relation to yield enhancement and various environmental stresses. Further, the appropriate databases in the field of data science to analyze big data, and retrieve relevant information vis-à-vis rice trait improvement and stress management are described.

LIRBase: a comprehensive database of long inverted repeats in eukaryotic genomes

Small RNAs (sRNAs) constitute a large portion of functional elements in eukaryotic genomes. Long inverted repeats (LIRs) can be transcribed into long hairpin RNAs (hpRNAs), which can further be processed into small interfering RNAs (siRNAs) with vital biological roles. In this study, we systematically identified a total of 6 619 473 LIRs in 424 eukaryotic genomes and developed LIRBase (https://venyao.xyz/lirbase/), a specialized database of LIRs across different eukaryotic genomes aiming to facilitate the annotation and identification of LIRs encoding long hpRNAs and siRNAs. LIRBase houses a comprehensive collection of LIRs identified in a wide range of eukaryotic genomes. In addition, LIRBase not only allows users to browse and search the identified LIRs in any eukaryotic genome(s) of interest available in GenBank, but also provides friendly web functionalities to facilitate users to identify LIRs in user-uploaded sequences, align sRNA sequencing data to LIRs, perform differential expression analysis of LIRs, predict mRNA targets for LIR-derived siRNAs, and visualize the secondary structure of candidate long hpRNAs encoded by LIRs. As demonstrated by two case studies, collectively, LIRBase bears the great utility for systematic investigation and characterization of LIRs and functional exploration of potential roles of LIRs and their derived siRNAs in diverse species.

Using phenotypic plasticity to understand the structure and evolution of the genotype-phenotype map

Deciphering the genotype-phenotype map necessitates relating variation at the genetic level to variation at the phenotypic level. This endeavour is inherently limited by the availability of standing genetic variation, the rate of spontaneous mutation to novo genetic variants, and possible biases associated with induced mutagenesis. An interesting alternative is to instead rely on the environment as a source of variation. Many phenotypic traits change plastically in response to the environment, and these changes are generally underlain by changes in gene expression. Relating gene expression plasticity to the phenotypic plasticity of more integrated organismal traits thus provides useful information about which genes influence the development and expression of which traits, even in the absence of genetic variation. We here appraise the prospects and limits of such an environment-for-gene substitution for investigating the genotype-phenotype map. We review models of gene regulatory networks, and discuss the different ways in which they can incorporate the environment to mechanistically model phenotypic plasticity and its evolution. We suggest that substantial progress can be made in deciphering this genotype-environment-phenotype map, by connecting theory on gene regulatory network to empirical patterns of gene co-expression, and by more explicitly relating gene expression to the expression and development of phenotypes, both theoretically and empirically.

Multi-Omics Analysis Reveals the Mechanism Underlying the Edaphic Adaptation in Wild Barley at Evolution Slope (Tabigha)

At the microsite "Evolution Slope", Tabigha, Israel, wild barley (Hordeum spontaneum) populations adapted to dry Terra Rossa soil, and its derivative abutting wild barley population adapted to moist and fungi-rich Basalt soil. However, the mechanisms underlying the edaphic adaptation remain elusive. Accordingly, whole genome bisulfite sequencing, RNA-sequencing, and metabolome analysis are performed on ten wild barley accessions inhabiting Terra Rossa and Basalt soil. A total of 121 433 differentially methylated regions (DMRs) and 10 478 DMR-genes are identified between the two wild barley populations. DMR-genes in CG context (CG-DMR-genes) are enriched in the pathways related with the fundamental processes, and DMR-genes in CHH context (CHH-DMR-genes) are mainly associated with defense response. Transcriptome and metabolome analysis reveal that the primary and secondary metabolisms are more active in Terra Rossa and Basalt wild barley populations, respectively. Multi-omics analysis indicate that sugar metabolism facilitates the adaptation of wild barley to dry Terra Rossa soil, whereas the enhancement of phenylpropanoid/phenolamide biosynthesis is beneficial for wild barley to inhabit moist and fungi pathogen-rich Basalt soil. The current results make a deep insight into edaphic adaptation of wild barley and provide elite genetic and epigenetic resources for developing barley with high abiotic stress tolerance.

Evolutionarily informed machine learning enhances the power of predictive gene-to-phenotype relationships

Inferring phenotypic outcomes from genomic features is both a promise and challenge for systems biology. Using gene expression data to predict phenotypic outcomes, and functionally validating the genes with predictive powers are two challenges we address in this study. We applied an evolutionarily informed machine learning approach to predict phenotypes based on transcriptome responses shared both within and across species. Specifically, we exploited the phenotypic diversity in nitrogen use efficiency and evolutionarily conserved transcriptome responses to nitrogen treatments across Arabidopsis accessions and maize varieties. We demonstrate that using evolutionarily conserved nitrogen responsive genes is a biologically principled approach to reduce the feature dimensionality in machine learning that ultimately improved the predictive power of our gene-to-trait models. Further, we functionally validated seven candidate transcription factors with predictive power for NUE outcomes in Arabidopsis and one in maize. Moreover, application of our evolutionarily informed pipeline to other species including rice and mice models underscores its potential to uncover genes affecting any physiological or clinical traits of interest across biology, agriculture, or medicine.

Gene expression evolution in pattern-triggered immunity within Arabidopsis thaliana and across Brassicaceae species

Plants recognize surrounding microbes by sensing microbe-associated molecular patterns (MAMPs) to activate pattern-triggered immunity (PTI). Despite their significance for microbial control, the evolution of PTI responses remains largely uncharacterized. Here, by employing comparative transcriptomics of six Arabidopsis thaliana accessions and three additional Brassicaceae species to investigate PTI responses, we identified a set of genes that commonly respond to the MAMP flg22 and genes that exhibit species-specific expression signatures. Variation in flg22-triggered transcriptome responses across Brassicaceae species was incongruent with their phylogeny, while expression changes were strongly conserved within A. thaliana. We found the enrichment of WRKY transcription factor binding sites in the 5'-regulatory regions of conserved and species-specific responsive genes, linking the emergence of WRKY-binding sites with the evolution of gene expression patterns during PTI. Our findings advance our understanding of the evolution of the transcriptome during biotic stress.

Local adaptation contributes to gene expression divergence in maize

Gene expression links genotypes to phenotypes, so identifying genes whose expression is shaped by selection will be important for understanding the traits and processes underlying local adaptation. However, detecting local adaptation for gene expression will require distinguishing between divergence due to selection and divergence due to genetic drift. Here, we adapt a QST−FST framework to detect local adaptation for transcriptome-wide gene expression levels in a population of diverse maize genotypes. We compare the number and types of selected genes across a wide range of maize populations and tissues, as well as selection on cold-response genes, drought-response genes, and coexpression clusters. We identify a number of genes whose expression levels are consistent with local adaptation and show that genes involved in stress response show enrichment for selection. Due to its history of intense selective breeding and domestication, maize evolution has long been of interest to researchers, and our study provides insight into the genes and processes important for in local adaptation of maize.

Assessing evolutionary and developmental transcriptome dynamics in homologous cell types

Background

During development, complex organ patterns emerge through the precise temporal and spatial specification of different cell types. On an evolutionary timescale, these patterns can change, resulting in morphological diversification. It is generally believed that homologous anatomical structures are built—largely—by homologous cell types. However, whether a common evolutionary origin of such cell types is always reflected in the conservation of their intrinsic transcriptional specification programs is less clear.

Results

Here, we developed a user‐friendly bioinformatics workflow to detect gene co‐expression modules and test for their conservation across developmental stages and species boundaries. Using a paradigm of morphological diversification, the tetrapod limb, and single‐cell RNA‐sequencing data from two distantly related species, chicken and mouse, we assessed the transcriptional dynamics of homologous cell types during embryonic patterning. With mouse limb data as reference, we identified 19 gene co‐expression modules with varying tissue or cell type‐restricted activities. Testing for co‐expression conservation revealed modules with high evolutionary turnover, while others seemed maintained—to different degrees, in module make‐up, density or connectivity—over developmental and evolutionary timescales.

Conclusions

We present an approach to identify evolutionary and developmental dynamics in gene co‐expression modules during patterning‐relevant stages of homologous cell type specification using single‐cell RNA‐sequencing data.

We present an approach to identify evolutionary and developmental dynamics in gene co‐expression modules during patterning‐relevant stages of homologous cell type specification using single‐cell RNA‐sequencing data.

Innovative mark-recapture experiment shows patterns of selection on transcript abundance in the wild

A fundamental aspect of evolutionary biology is natural selection on trait variation. Classically, selection has been estimated primarily on external morphological traits such as beak size and coloration, or on easily assayable physiological traits such as heat-tolerance. As technologies and methods improved, evolutionary biologists began examining selection on molecular traits such as protein sequences and cellular processes. In a From the Cover paper in this issue of Molecular Ecology, Ahmad et al. continue this trend by estimating parasite-driven selection on the molecular trait of transcript abundance in a wild population of brown trout (Salmo trutta) by uniquely combining a mark-recapture experimental design with noninvasive RNA sampling. Using transcript abundance to estimate selection allows for many different traits (each unique gene's transcript counts) to be tested in a single experiment, providing the opportunity to examine trends in selection. Ahmad et al. find directional selection strength on transcript counts is generally low and normally distributed. Surprisingly, transcripts under nonlinear selection showed a disruptive selection bias, contradicting previous comparative studies and theoretical work. This highlights the importance of within-generation selection studies, where mechanisms may differ from longer time frames. Their paper also highlights the benefits of a cost-effective 3' RNA sequencing technique to measure gene expression.

Advancing crop genomics from lab to field

Crop genomics remains a key element in ensuring scientific progress to secure global food security. It has been two decades since the sequence of the first plant genome, that of Arabidopsis thaliana, was released, and soon after that the draft sequencing of the rice genome was completed. Since then, the genomes of more than 100 crops have been sequenced, plant genome research has expanded across multiple fronts and the next few years promise to bring further advances spurred by the advent of new technologies and approaches. We are likely to see continued innovations in crop genome sequencing, genetic mapping and the acquisition of multiple levels of biological data. There will be exciting opportunities to integrate genome-scale information across multiple scales of biological organization, leading to advances in our mechanistic understanding of crop biological processes, which will, in turn, provide greater impetus for translation of laboratory results to the field.