Environmental context of phenotypic plasticity in flowering time in sorghum and rice.

Phenotypic plasticity is an important topic in biology and evolution. However, how to generate broadly applicable insights from individual studies remains a challenge. Here, with flowering time observed from a large geographical region for sorghum and rice genetic populations, we examine the consistency of parameter estimation for reaction norms of genotypes across different subsets of environments and searched for potential strategies to inform the study design. Both sample size and environmental mean range of the subset affected the consistency. The subset with either a large range of environmental mean or a large sample size resulted in genetic parameters consistent with the overall pattern. Furthermore, high accuracy through genomic prediction was obtained for reaction norm parameters of untested genotypes using models built from tested genotypes under the subsets of environments with either a large range or a large sample size. With 1428 and 1674 simulated settings, our analyses suggested that the distribution of environmental index values of a site should be considered in designing experiments. Overall, we showed that environmental context was critical, and considerations should be given to better cover the intended range of the environmental variable. Our findings have implications for the genetic architecture of complex traits, plant-environment interaction, and climate adaptation.

Novel allelic variations in Tannin1 and Tannin2 contribute to tannin absence in sorghum.

Sorghum is an important food crop commonly used for brewing, feed, and bioenergy. Certain genotypes of sorghum contain high concentrations of condensed tannins in seeds, which are beneficial, such as protecting grains from herbivore bird pests, but also impair grain quality and digestibility. Previously, we identified Tannin1 and Tannin2, each with three recessive causal alleles, regulate tannin absence in sorghum. In this study, via characterizing 421 sorghum accessions, we further identified three novel recessive alleles from these two genes. The tan1-d allele contains a 12-bp deletion at position 659 nt and the tan1-e allele contains a 10-bp deletion at position 771 nt in Tannin1. The tan2-d allele contains a C-to-T transition, which results in a premature stop codon before the bHLH domain in Tannin2, and was predominantly selected in China. We further developed KASP assays targeting these identified recessive alleles to efficiently genotype large populations. These studies provide new insights in sorghum domestication and convenient tools for breeding programs. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-024-01463-y.

Dynamic effects of interacting genes underlying rice flowering-time phenotypic plasticity and global adaptation.

The phenotypic variation of living organisms is shaped by genetics, environment, and their interaction. Understanding phenotypic plasticity under natural conditions is hindered by the apparently complex environment and the interacting genes and pathways. Herein, we report findings from the dissection of rice flowering-time plasticity in a genetic mapping population grown in natural long-day field environments. Genetic loci harboring four genes originally discovered for their photoperiodic effects (Hd1, Hd2, Hd5, and Hd6) were found to differentially respond to temperature at the early growth stage to jointly determine flowering time. The effects of these plasticity genes were revealed with multiple reaction norms along the temperature gradient. By coupling genomic selection and the environmental index, accurate performance predictions were obtained. Next, we examined the allelic variation in the four flowering-time genes across the diverse accessions from the 3000 Rice Genomes Project and constructed haplotypes at both individual-gene and multigene levels. The geographic distribution of haplotypes revealed their preferential adaptation to different temperature zones. Regions with lower temperatures were dominated by haplotypes sensitive to temperature changes, whereas the equatorial region had a majority of haplotypes that are less responsive to temperature. By integrating knowledge from genomics, gene cloning and functional characterization, and environment quantification, we propose a conceptual model with multiple levels of reaction norms to help bridge the gaps among individual gene discovery, field-level phenotypic plasticity, and genomic diversity and adaptation.

A Large Transposon Insertion in the stiff1 Promoter Increases Stalk Strength in Maize.

Stalk lodging, which is generally determined by stalk strength, results in considerable yield loss and has become a primary threat to maize (Zea mays) yield under high-density planting. However, the molecular genetic basis of maize stalk strength remains unclear, and improvement methods remain inefficient. Here, we combined map-based cloning and association mapping and identified the gene stiff1 underlying a major quantitative trait locus for stalk strength in maize. A 27.2-kb transposable element insertion was present in the promoter of the stiff1 gene, which encodes an F-box domain protein. This transposable element insertion repressed the transcription of stiff1, leading to the increased cellulose and lignin contents in the cell wall and consequently greater stalk strength. Furthermore, a precisely edited allele of stiff1 generated through the CRISPR/Cas9 system resulted in plants with a stronger stalk than the unedited control. Nucleotide diversity analysis revealed that the promoter of stiff1 was under strong selection in the maize stiff-stalk group. Our cloning of stiff1 reveals a case in which a transposable element played an important role in maize improvement. The identification of stiff1 and our edited stiff1 allele pave the way for efficient improvement of maize stalk strength.

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

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

Phenotypic plasticity in plant height shaped by interaction between genetic loci and diurnal temperature range.

Phenotypic plasticity is observed widely in plants and often studied with reaction norms for adult plant or end-of-season traits. Uncovering genetic, environmental and developmental patterns behind the observed phenotypic variation under natural field conditions is needed. Using a sorghum (Sorghum bicolor) genetic population evaluated for plant height in seven natural field conditions, we investigated the major pattern that differentiated these environments. We then examined the physiological relevance of the identified environmental index by investigating the developmental trajectory of the population with multistage height measurements in four additional environments and conducting crop growth modelling. We found that diurnal temperature range (DTR) during the rapid growth period of sorghum development was an effective environmental index. Three genetic loci (Dw1, Dw3 and qHT7.1) were consistently detected for individual environments, reaction-norm parameters across environments and growth-curve parameters through the season. Their genetic effects changed dynamically along the environmental gradient and the developmental stage. A conceptual model with three-dimensional reaction norms was proposed to showcase the interconnecting components: genotype, environment and development. Beyond genomic and environmental analyses, further integration of development and physiology at the whole-plant and molecular levels into complex trait dissection would enhance our understanding of mechanisms underlying phenotypic variation.

Genomic and environmental determinants and their interplay underlying phenotypic plasticity.

Observed phenotypic variation in living organisms is shaped by genomes, environment, and their interactions. Flowering time under natural conditions can showcase the diverse outcome of the gene-environment interplay. However, identifying hidden patterns and specific factors underlying phenotypic plasticity under natural field conditions remains challenging. With a genetic population showing dynamic changes in flowering time, here we show that the integrated analyses of genomic responses to diverse environments is powerful to reveal the underlying genetic architecture. Specifically, the effect continuum of individual genes (Ma1 , Ma6 , FT, and ELF3) was found to vary in size and in direction along an environmental gradient that was quantified by photothermal time, a combination of two environmental factors (photoperiod and temperature). Gene-gene interaction was also contributing to the observed phenotypic plasticity. With the identified environmental index to quantitatively connect environments, a systematic genome-wide performance prediction framework was established through either genotype-specific reaction-norm parameters or genome-wide marker-effect continua. These parallel genome-wide approaches were demonstrated for in-season and on-target performance prediction by simultaneously exploiting genomics, environment profiling, and performance information. Improved understanding of mechanisms for phenotypic plasticity enables a concerted exploration that turns challenge into opportunity.

Genomic prediction of maize microphenotypes provides insights for optimizing selection and mining diversity.

Effective evaluation of millions of crop genetic stocks is an essential component of exploiting genetic diversity to achieve global food security. By leveraging genomics and data analytics, genomic prediction is a promising strategy to efficiently explore the potential of these gene banks by starting with phenotyping a small designed subset. Reliable genomic predictions have enhanced selection of many macroscopic phenotypes in plants and animals. However, the use of genomicprediction strategies for analysis of microscopic phenotypes is limited. Here, we exploited the power of genomic prediction for eight maize traits related to the shoot apical meristem (SAM), the microscopic stem cell niche that generates all the above-ground organs of the plant. With 435 713 genomewide single-nucleotide polymorphisms (SNPs), we predicted SAM morphology traits for 2687 diverse maize inbreds based on a model trained from 369 inbreds. An empirical validation experiment with 488 inbreds obtained a prediction accuracy of 0.37-0.57 across eight traits. In addition, we show that a significantly higher prediction accuracy was achieved by leveraging the U value (upper bound for reliability) that quantifies the genomic relationships of the validation set with the training set. Our findings suggest that double selection considering both prediction and reliability can be implemented in choosing selection candidates for phenotyping when exploring new diversity is desired. In this case, individuals with less extreme predicted values and moderate reliability values can be considered. Our study expands the turbocharging gene banks via genomic prediction from the macrophenotypes into the microphenotypic space.

Dissecting repulsion linkage in the dwarfing gene Dw3 region for sorghum plant height provides insights into heterosis.

Heterosis is a main contributor to yield increase in many crop species. Different mechanisms have been proposed for heterosis: dominance, overdominance, epistasis, epigenetics, and protein metabolite changes. However, only limited examples of molecular dissection and validation of these mechanisms are available. Here, we present an example of discovery and validation of heterosis generated by a combination of repulsion linkage and dominance. Using a recombinant inbred line population, a separate quantitative trait locus (QTL) for plant height (qHT7.1) was identified near the genomic region harboring the known auxin transporter Dw3 gene. With two loci having repulsion linkage between two inbreds, heterosis in the hybrid can appear as a single locus with an overdominance mode of inheritance (i.e., pseudo-overdominance). Individually, alleles conferring taller plant height exhibited complete dominance over alleles conferring shorter height. Detailed analyses of different height components demonstrated that qHT7.1 affects both the upper and lower parts of the plant, whereas Dw3 affects only the part below the flag leaf. Computer simulations show that repulsion linkage could influence QTL detection and estimation of effect in segregating populations. Guided by findings in linkage mapping, a genome-wide association study of plant height with a sorghum diversity panel pinpointed genomic regions underlying the trait variation, including Dw1, Dw2, Dw3, Dw4, and qHT7.1. Multilocus mixed model analysis confirmed the advantage of complex trait dissection using an integrated approach. Besides identifying a specific genetic example of heterosis, our research indicated that integrated molecular dissection of complex traits in different population types can enable plant breeders to fine tune the breeding process for crop production.

Evolutionary patterns of DNA base composition and correlation to polymorphisms in DNA repair systems.

DNA base composition is a fundamental genome feature. However, the evolutionary pattern of base composition and its potential causes have not been well understood. Here, we report findings from comparative analysis of base composition at the whole-genome level across 2210 species, the polymorphic-site level across eight population comparison sets, and the mutation-site level in 12 mutation-tracking experiments. We first demonstrate that base composition follows the individual-strand base equality rule at the genome, chromosome and polymorphic-site levels. More intriguingly, clear separation of base-composition values calculated across polymorphic sites was consistently observed between basal and derived groups, suggesting common underlying mechanisms. Individuals in the derived groups show an A&T-increase/G&C-decrease pattern compared with the basal groups. Spontaneous and induced mutation experiments indicated these patterns of base composition change can emerge across mutation sites. With base-composition across polymorphic sites as a genome phenotype, genome scans with human 1000 Genomes and HapMap3 data identified a set of significant genomic regions enriched with Gene Ontology terms for DNA repair. For three DNA repair genes (BRIP1, PMS2P3 and TTDN), ENCODE data provided evidence for interaction between genomic regions containing these genes and regions containing the significant SNPs. Our findings provide insights into the mechanisms of genome evolution.

Genic and nongenic contributions to natural variation of quantitative traits in maize.

The complex genomes of many economically important crops present tremendous challenges to understand the genetic control of many quantitative traits with great importance in crop production, adaptation, and evolution. Advances in genomic technology need to be integrated with strategic genetic design and novel perspectives to break new ground. Complementary to individual-gene-targeted research, which remains challenging, a global assessment of the genomic distribution of trait-associated SNPs (TASs) discovered from genome scans of quantitative traits can provide insights into the genetic architecture and contribute to the design of future studies. Here we report the first systematic tabulation of the relative contribution of different genomic regions to quantitative trait variation in maize. We found that TASs were enriched in the nongenic regions, particularly within a 5-kb window upstream of genes, which highlights the importance of polymorphisms regulating gene expression in shaping the natural variation. Consistent with these findings, TASs collectively explained 44%-59% of the total phenotypic variation across maize quantitative traits, and on average, 79% of the explained variation could be attributed to TASs located in genes or within 5 kb upstream of genes, which together comprise only 13% of the genome. Our findings suggest that efficient, cost-effective genome-wide association studies (GWAS) in species with complex genomes can focus on genic and promoter regions.

Presence of tannins in sorghum grains is conditioned by different natural alleles of Tannin1.

Sorghum, an ancient old-world cereal grass, is the dietary staple of over 500 million people in more than 30 countries in the tropics and semitropics. Its C4 photosynthesis, drought resistance, wide adaptation, and high nutritional value hold the promise to alleviate hunger in Africa. Not present in other major cereals, such as rice, wheat, and maize, condensed tannins (proanthocyanidins) in the pigmented testa of some sorghum cultivars have been implicated in reducing protein digestibility but recently have been shown to promote human health because of their high antioxidant capacity and ability to fight obesity through reduced digestion. Combining quantitative trait locus mapping, meta-quantitative trait locus fine-mapping, and association mapping, we showed that the nucleotide polymorphisms in the Tan1 gene, coding a WD40 protein, control the tannin biosynthesis in sorghum. A 1-bp G deletion in the coding region, causing a frame shift and a premature stop codon, led to a nonfunctional allele, tan1-a. Likewise, a different 10-bp insertion resulted in a second nonfunctional allele, tan1-b. Transforming the sorghum Tan1 ORF into a nontannin Arabidopsis mutant restored the tannin phenotype. In addition, reduction in nucleotide diversity from wild sorghum accessions to landraces and cultivars was found at the region that codes the highly conserved WD40 repeat domains and the C-terminal region of the protein. Genetic research in crops, coupled with nutritional and medical research, could open the possibility of producing different levels and combinations of phenolic compounds to promote human health.

Genetic mapping of dynamic control of leaf angle across multiple canopy levels in maize.

Optimizing leaf angle and other canopy architecture traits has helped modern maize (Zea mays L.) become adapted to higher planting densities over the last 60 years. Traditional investigations into genetic control of leaf angle have focused on one leaf or the average of multiple leaves; as a result, our understanding of genetic control across multiple canopy levels is still limited. To address this, genetic mapping across four canopy levels was conducted in the present study to investigate the genetic control of leaf angle across the canopy. We developed two populations of doubled haploid lines derived from three inbreds with distinct leaf angle phenotypes. These populations were genotyped with genotyping-by-sequencing and phenotyped for leaf angle at four different canopy levels over multiple years. To understand how leaf angle changes across the canopy, the four measurements were used to derive three additional traits. Composite interval mapping was conducted with the leaf-specific measurements and the derived traits. A set of 59 quantitative trait loci (QTLs) were uncovered for seven traits, and two genomic regions were consistently detected across multiple canopy levels. Additionally, seven genomic regions were found to contain consistent QTLs with either relatively stable or dynamic effects at different canopy levels. Prioritizing the selection of QTLs with dynamic effects across the canopy will aid breeders in selecting maize hybrids with the ideal canopy architecture that continues to maximize yield on a per area basis under increasing planting densities.

Evolutionary patterns of DNA base composition at polymorphic sites highlight the role of the environment in shaping barley and rice genomes.

Insights into changes in genome base composition underlying crop domestication can be gained by using comparative genomics. With this approach, previous studies have reported that crop genomes during domestication accumulate more nucleotides adenine (A) and thymine (T) (termed as [AT]-increase) across polymorphic sites. However, the potential influence of the environment or its factors, for example, solar ultraviolet (UV) radiation and temperature, on the [AT]-increase has not been well elucidated. Here, we investigated the [AT]-increase in barley (Hordeum vulgare L.) and rice (Oryza sativa L.) and the association with natural environments, where accessions are distributed. With 12,798,376 and 2,861,535 single-nucleotide polymorphisms from 368 barley and 1375 rice accessions, respectively, we discovered that [AT] increases from wild accessions to improved cultivars, and genomic regions with larger [AT]-increase tend to have higher UV-related motif frequencies, suggesting solar UV radiation as a potential factor in driving genome variation. To link [AT] change with the geographic distribution, we gathered georeferenced accessions and examined their local environments. Interestingly, negative correlations between [AT] and environmental factors were observed (r = -0.39 ∼ -0.75) and modern accessions with higher [AT] values, as compared with wild relatives, are from the environments with lower solar UV radiation or lower temperature. With [AT] and environmental factors as phenotypes, genome-wide association mapping identified three candidate genes that have the potential to contribute to [AT] variation under the effect of environmental conditions. Our findings provide genomic and environmental insights into evolutionary pattern of DNA base composition and underlying mechanisms.

Evolutionary genomics of climatic adaptation and resilience to climate change in alfalfa.

Given the escalating impact of climate change on agriculture and food security, gaining insights into the evolutionary dynamics of climatic adaptation and uncovering climate-adapted variation can empower the breeding of climate-resilient crops to face future climate change. Alfalfa (Medicago sativa subsp. sativa), the queen of forages, shows remarkable adaptability across diverse global environments, making it an excellent model for investigating species responses to climate change. In this study, we performed population genomic analyses using genome resequencing data from 702 accessions of 24 Medicago species to unravel alfalfa's climatic adaptation and genetic susceptibility to future climate change. We found that interspecific genetic exchange has contributed to the gene pool of alfalfa, particularly enriching defense and stress-response genes. Intersubspecific introgression between M. sativa subsp. falcata (subsp. falcata) and alfalfa not only aids alfalfa's climatic adaptation but also introduces genetic burden. A total of 1671 genes were associated with climatic adaptation, and 5.7% of them were introgressions from subsp. falcata. By integrating climate-associated variants and climate data, we identified populations that are vulnerable to future climate change, particularly in higher latitudes of the Northern Hemisphere. These findings serve as a clarion call for targeted conservation initiatives and breeding efforts. We also identified pre-adaptive populations that demonstrate heightened resilience to climate fluctuations, illuminating a pathway for future breeding strategies. Collectively, this study enhances our understanding about the local adaptation mechanisms of alfalfa and facilitates the breeding of climate-resilient alfalfa cultivars, contributing to effective agricultural strategies for facing future climate change.

Machine learning for predicting phenotype from genotype and environment.

Predicting phenotype with genomic and environmental information is critically needed and challenging. Machine learning methods have emerged as powerful tools to make accurate predictions from large and complex biological data. Here, we review the progress of phenotype prediction models enabled or improved by machine learning methods. We categorized the applications into three scenarios: prediction with genotypic information, with environmental information, and with both. In each scenario, we illustrate the practicality of prediction models, the advantages of machine learning, and the challenges of modeling complex relationships. We discuss the promising potential of leveraging machine learning and genetics theories to develop models that can predict phenotype and also interpret the biological consequences of changes in genotype and environment.

Generation of Sesame Mutant Population by Mutagenesis and Identification of High Oleate Mutants by GC Analysis.

Sesame is one of the important oilseed crops in the world. Natural genetic variation exists in the sesame germplasm collection. Mining and utilizing the genetic allele variation from the germplasm collection is an important approach for seed quality improvement. The sesame germplasm accession, PI 263470, which has a significantly higher level of oleic acid (54.0%) than the average (39.5%), was identified by screening the entire USDA germplasm collection. The seeds from this accession were planted in a greenhouse. Leaf tissues and seeds were harvested from individual plants. DNA sequencing of the coding region of the fatty acid desaturase gene (FAD2) confirmed that this accession contained a natural mutation of G425A which may correspond to the deduced amino acid substitution of R142H leading to the high level of oleic acid, but it was a mixed accession with three genotypes (G/G, G/A, and A/A at the position). The genotype with A/A was selected and self-crossed for three generations. The purified seeds were used for EMS-induced mutagenesis to further enhance the level of oleic acid. A total of 635 M2 plants were generated from mutagenesis. Some mutant plants had significant morphological changes including leafy flat stems and others. M3 seeds were used for fatty acid composition analysis by gas chromatography (GC). Several mutant lines were identified with high oleic acid (70%). Six M3 mutant lines plus one control line were advanced to M7 or M8 generations. Their high oleate traits from M7 or M8 seeds harvested from M6 or M7 plants were further confirmed. The level of oleic acid from one mutant line (M7 915-2) was over 75%. The coding region of FAD2 was sequenced from these six mutants, but no mutation was identified. Additional loci may contribute to the high level of oleic acid. The mutants identified in this study can be used as breeding materials for sesame improvement and as genetic materials for forward genetic studies.

PANI-Coated VOx Nanobelts with Core-Shell Architecture for Flexible All-Solid-State Supercapacitor.

As a typical pseudocapacitor material, VOx possesses mixed valence states, making it an ideal electrode material for symmetric screen-printed supercapacitors. However, its high internal resistance and low energy density are the main hurdles to its widespread application. In this study, a two-dimensional PANI@VOx nanobelt with a core-shell architecture was constructed via a two-step route. This strategy involves the preparation of VOx using a solvothermal method, and a subsequent in situ polymerization process of the PANI. By virtue of the synergistic effect between the VOx core and the PANI shell, the optimal VOx@PANI has an enhanced conductivity of 0.7 ± 0.04 S/Ω, which can deliver a high specific capacitance of 347.5 F/g at 0.5 A/g, a decent cycling life of ~72.0%, and an outstanding Coulomb efficiency of ~100% after 5000 cycles at 5 A/g. Moreover, a flexible all-solid-state symmetric supercapacitor (VOx@PANI SSC) with an in-planar interdigitated structure was screen-printed and assembled on a nickel current collector; it yielded a remarkable areal energy density of 115.17 µWh/cm2 at an areal power density of 0.39 mW/cm2, and possessed outstanding flexibility and mechanical performance. Notably, a "Xiaomi" hygrothermograph (3.0 V) was powered easily by tandem SSCs with an operating voltage of 3.1 V. Therefore, this advanced pseudocapacitor material with core-shell architecture opens novel ideas for flexible symmetric supercapacitors in powering portable/wearable products.

Research on the control strategies of data flow transmission paths for MPTCP-based communication networks.

The performance of multipath transmission control protocol (MPTCP) subflow through the enhancement mechanism of the MPTCP communication is improved. When dealing with multiple MPTCP subflows occupying the same transmission path, critical issues such as selection and optimization of multipath, and efficient scheduling of available multiple tracks are effectively addressed by incorporating the technology called software defined network (SDN) that is constructed based on four key parameters, namely, network transmission bandwidth, transmission paths, path capacity, and network latency. Besides, critical equipment such as the network physical device layer and SDN controller are integrated with the four parameters. So, the network model defines the transmission control process and data information. Considering the predetermined total network bandwidth capacity to select multiple paths, the adequate bandwidth capacity is determined by defining the data transfer rate between MPTCP terminals and MPTCP servers. However, the processing latency of the OpenFlow switch and the SDN controller is excluded. The effective network transmission paths are calculated through two rounds of path selection algorithms. Moreover, according to the demand capacity of the data transmission and the supply capacity of the required occupied network resource, a supply and demand strategy is formulated by considering the bandwidth capacity of the total network and invalid network latency factors. Then, the available network transmission path from the valid network transmission path is calculated. The shortest path calculation problem, which is the calculation and sorting of the shortest path, is transformed into a clustering, Inter-Cluster Average Classification (ICA), problem. The instruction of the OpenFlow communication flow is designed to schedule MPTCP subflows. Thus, various validation objectives, including the network model, effective network latency, effective transmission paths, supply-demand strategies, ineffective transmission paths, shortest feasible paths, and communication rules are addressed by the proposed method whose reliability, stability, and data transmission performance are validated through comparative analysis with other conventional algorithms. Found that the network latency is around 20 s, the network transmission rate is approximately 10 Mbps, the network bandwidth capacity reaches around 25Mbps, the network resource utilization rate is about 75%, and the network swallowing volume is approximately 3 M/s.