Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds.

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

The additive function of YIGE2 and YIGE1 in regulating maize ear length.

Ear length (EL) is a key trait that greatly contributes to yield in maize. Although dozens of EL quantitative trait loci have been mapped, very few causal genes have been cloned, and the molecular mechanisms remain largely unknown. Our previous study showed that YIGE1 is involved in sugar and auxin pathways to regulate ear inflorescence meristem (IM) development and thus affects EL in maize. Here, we reveal that YIGE2, the paralog of YIGE1, regulates maize ear development and EL through auxin pathway. Knockout of YIGE2 causes a significant decrease of auxin level, IM length, floret number, EL, and grain yield. yige1 yige2 double mutants had even shorter IM and ears implying that these two genes redundantly regulate IM development and EL. The genes controlling auxin levels are differential expressed in yige1 yige2 double mutants, leading to lower auxin level. These results elucidated the critical role of YIGE2 and the redundancy between YIGE2 and YIGE1 in maize ear development, providing a new genetic resource for maize yield improvement.

Genome-wide association of the metabolic shifts underpinning dark-induced senescence in Arabidopsis.

Dark-induced senescence provokes profound metabolic shifts to recycle nutrients and to guarantee plant survival. To date, research on these processes has largely focused on characterizing mutants deficient in individual pathways. Here, we adopted a time-resolved genome-wide association-based approach to characterize dark-induced senescence by evaluating the photochemical efficiency and content of primary and lipid metabolites at the beginning, or after 3 or 6 days in darkness. We discovered six patterns of metabolic shifts and identified 215 associations with 81 candidate genes being involved in this process. Among these associations, we validated the roles of four genes associated with glycine, galactinol, threonine, and ornithine levels. We also demonstrated the function of threonine and galactinol catabolism during dark-induced senescence. Intriguingly, we determined that the association between tyrosine contents and TYROSINE AMINOTRANSFERASE 1 influences enzyme activity of the encoded protein and transcriptional activity of the gene under normal and dark conditions, respectively. Moreover, the single-nucleotide polymorphisms affecting the expression of THREONINE ALDOLASE 1 and the amino acid transporter gene AVT1B, respectively, only underlie the variation in threonine and glycine levels in the dark. Taken together, these results allow us to present a very detailed model of the metabolic aspects of dark-induced senescence, as well as the process itself.

A genome-wide association study identifies a transporter for zinc uploading to maize kernels.

The Zn content in cereal seeds is an important trait for crop production as well as for human health. However, little is known about how Zn is loaded to plant seeds. Here, through a genome-wide association study (GWAS), we identify the Zn-NA (nicotianamine) transporter gene ZmYSL2 that is responsible for loading Zn to maize kernels. High promoter sequence variation in ZmYSL2 most likely drives the natural variation in Zn concentrations in maize kernels. ZmYSL2 is specifically localized on the plasma membrane facing the maternal tissue of the basal endosperm transfer cell layer (BETL) and functions in loading Zn-NA into the BETL. Overexpression of ZmYSL2 increases the Zn concentration in the kernels by 31.6%, which achieves the goal of Zn biofortification of maize. These findings resolve the mystery underlying the loading of Zn into plant seeds, providing an efficient strategy for breeding or engineering maize varieties with enriched Zn nutrition.

Going broad and deep: sequencing-driven insights into plant physiology, evolution, and crop domestication.

Deep sequencing is a term that has become embedded in the plant genomic literature in recent years and with good reason. A torrent of (largely) high-quality genomic and transcriptomic data has been collected and most of this has been publicly released. Indeed, almost 1000 plant genomes have been reported (www.plabipd.de) and the 2000 Plant Transcriptomes Project has long been completed. The EarthBioGenome project will dwarf even these milestones. That said, massive progress in understanding plant physiology, evolution, and crop domestication has been made by sequencing broadly (across a species) as well as deeply (within a single individual). We will outline the current state of the art in genome and transcriptome sequencing before we briefly review the most visible of these broad approaches, namely genome-wide association and transcriptome-wide association studies, as well as the compilation of pangenomes. This will include both (i) the most commonly used methods reliant on single nucleotide polymorphisms and short InDels and (ii) more recent examples which consider structural variants. We will subsequently present case studies exemplifying how their application has brought insight into either plant physiology or evolution and crop domestication. Finally, we will provide conclusions and an outlook as to the perspective for the extension of such approaches to different species, tissues, and biological processes.

Genome optimization via virtual simulation to accelerate maize hybrid breeding.

The employment of doubled-haploid (DH) technology in maize has vastly accelerated the efficiency of developing inbred lines. The selection of superior lines has to rely on genotypes with genomic selection (GS) model, rather than phenotypes due to the high expense of field phenotyping. In this work, we implemented 'genome optimization via virtual simulation (GOVS)' using the genotype and phenotype data of 1404 maize lines and their F1 progeny. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' or 'advantageous alleles' in a genetic pool. Such a virtually optimized genome, although can never be developed in reality, may help plot the optimal route to direct breeding decisions. GOVS assists in the selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. The assumption is that the more fragments of optimal genotypes a line contributes to the assembly, the higher the likelihood of the line favored in the F1 phenotype, e.g. grain yield. Compared to traditional GS method, GOVS-assisted selection may avoid using an arbitrary threshold for the predicted F1 yield to assist selection. Additionally, the selected lines contributed complementary sets of advantageous alleles to the virtual genome. This feature facilitates plotting the optimal route for DH production, whereby the fewest lines and F1 combinations are needed to pyramid a maximum number of advantageous alleles in the new DH lines. In summary, incorporation of DH production, GS and genome optimization will ultimately improve genomically designed breeding in maize. Short abstract: Doubled-haploid (DH) technology has been widely applied in maize breeding industry, as it greatly shortens the period of developing homozygous inbred lines via bypassing several rounds of self-crossing. The current challenge is how to efficiently screen the large volume of inbred lines based on genotypes. We present the toolbox of genome optimization via virtual simulation (GOVS), which complements the traditional genomic selection model. GOVS simulates a virtual genome encompassing the most abundant 'optimal genotypes' in a breeding population, and then assists in selection of superior lines based on the genomic fragments that a line contributes to the simulated genome. Availability of GOVS (https://govs-pack.github.io/) to the public may ultimately facilitate genomically designed breeding in maize.

Genomic basis determining root system architecture in maize.

KEY MESSAGE: A total of 389 and 344 QTLs were identified by GWAS and QTL mapping explaining accumulatively 32.2-65.0% and 23.7-63.4% of phenotypic variation for 14 shoot-borne root traits using more than 1300 individuals across multiple field trails. Efficient nutrient and water acquisition from soils depends on the root system architecture (RSA). However, the genetic determinants underlying RSA in maize remain largely unexplored. In this study, we conducted a comprehensive genetic analysis for 14 shoot-borne root traits using 513 inbred lines and 800 individuals from four recombinant inbred line (RIL) populations at the mature stage across multiple field trails. Our analysis revealed substantial phenotypic variation for these 14 root traits, with a total of 389 and 344 QTLs identified through genome-wide association analysis (GWAS) and linkage analysis, respectively. These QTLs collectively explained 32.2-65.0% and 23.7-63.4% of the trait variation within each population. Several a priori candidate genes involved in auxin and cytokinin signaling pathways, such as IAA26, ARF2, LBD37 and CKX3, were found to co-localize with these loci. In addition, a total of 69 transcription factors (TFs) from 27 TF families (MYB, NAC, bZIP, bHLH and WRKY) were found for shoot-borne root traits. A total of 19 genes including PIN3, LBD15, IAA32, IAA38 and ARR12 and 19 GWAS signals were overlapped with selective sweeps. Further, significant additive effects were found for root traits, and pyramiding the favorable alleles could enhance maize root development. These findings could contribute to understand the genetic basis of root development and evolution, and provided an important genetic resource for the genetic improvement of root traits in maize.

Enhancing crop diversity for food security in the face of climate uncertainty.

Global agriculture is dominated by a handful of species that currently supply a huge proportion of our food and feed. It additionally faces the massive challenge of providing food for 10 billion people by 2050, despite increasing environmental deterioration. One way to better plan production in the face of current and continuing climate change is to better understand how our domestication of these crops included their adaptation to environments that were highly distinct from those of their centre of origin. There are many prominent examples of this, including the development of temperate Zea mays (maize) and the alteration of day-length requirements in Solanum tuberosum (potato). Despite the pre-eminence of some 15 crops, more than 50 000 species are edible, with 7000 of these considered semi-cultivated. Opportunities afforded by next-generation sequencing technologies alongside other methods, including metabolomics and high-throughput phenotyping, are starting to contribute to a better characterization of a handful of these species. Moreover, the first examples of de novo domestication have appeared, whereby key target genes are modified in a wild species in order to confer predictable traits of agronomic value. Here, we review the scale of the challenge, drawing extensively on the characterization of past agriculture to suggest informed strategies upon which the breeding of future climate-resilient crops can be based.

Genetic basis of resistance to southern corn leaf blight in the maize multi-parent population and diversity panel.

Southern corn leaf blight (SLB), caused by the necrotrophic pathogen Cochliobolus heterostrophus, is one of the maize foliar diseases and poses a great threat to corn production around the world. Identification of genetic variations underlying resistance to SLB is of paramount importance to maize yield and quality. Here, we used a random-open-parent association mapping population containing eight recombinant inbred line populations and one association mapping panel consisting of 513 diversity maize inbred lines with high-density genetic markers to dissect the genetic basis of SLB resistance. Overall, 109 quantitative trait loci (QTLs) with predominantly small or moderate additive effects, and little epistatic effects were identified. We found 35 (32.1%) novel loci in comparison with the reported QTLs. We revealed that resistant alleles were significantly enriched in tropical accessions and the frequency of about half of resistant alleles decreased during the adaptation process owing to the selection of agronomic traits. A large number of annotated genes located in the SLB-resistant QTLs were shown to be involved in plant defence pathways. Integrating genome-wide association study, transcriptomic profiling, resequencing and gene editing, we identified ZmFUT1 and MYBR92 as the putative genes responsible for the major QTLs for resistance to C. heterostrophus. Our results present a comprehensive insight into the genetic basis of SLB resistance and provide resistant loci or genes as direct targets for crop genetic improvement.

ZmEREB57 regulates OPDA synthesis and enhances salt stress tolerance through two distinct signalling pathways in Zea mays.

In plant, APETALA2/ethylene-responsive factor (AP2/ERF)-domain transcription factors are important in regulating abiotic stress tolerance. In this study, ZmEREB57 encoding a AP2/ERF transcription factor was identified and its function was investigated in maize. ZmEREB57 is a nuclear protein with transactivation activity induced by several abiotic stress types. Furthermore, two CRISPR/Cas9 knockout lines of ZmEREB57 showed enhanced sensitivity to saline conditions, whereas the overexpression of ZmEREB57 increased salt tolerance in maize and Arabidopsis. DNA affinity purification sequencing (DAP-Seq) analysis revealed that ZmEREB57 notably regulates target genes by binding to promoters containing an O-box-like motif (CCGGCC). ZmEREB57 directly binds to the promoter of ZmAOC2 involved in the synthesis of 12-oxo-phytodienoic acid (OPDA) and jasmonic acid (JA). Transcriptome analysis revealed that several genes involved in regulating stress and redox homeostasis showed differential expression patterns in OPDA- and JA-treated maize seedlings exposed to salt stress compared to those treated with salt stress alone. Analysis of mutants deficient in the biosynthesis of OPDA and JA revealed that OPDA functions as a signalling molecule in the salt response. Our results indicate that ZmEREB57 involves in salt tolerance by regulating OPDA and JA signalling and confirm early observations that OPDA signalling functions independently of JA signalling.

High-Throughput CRISPR/Cas9 Mutagenesis Streamlines Trait Gene Identification in Maize.

Maize (Zea mays) is one of the most important crops in the world. However, few agronomically important maize genes have been cloned and used for trait improvement, due to its complex genome and genetic architecture. Here, we integrated multiplexed CRISPR/Cas9-based high-throughput targeted mutagenesis with genetic mapping and genomic approaches to successfully target 743 candidate genes corresponding to traits relevant for agronomy and nutrition. After low-cost barcode-based deep sequencing, 412 edited sequences covering 118 genes were precisely identified from individuals showing clear phenotypic changes. The profiles of the associated gene-editing events were similar to those identified in human cell lines and consequently are predictable using an existing algorithm originally designed for human studies. We observed unexpected but frequent homology-directed repair through endogenous templates that was likely caused by spatial contact between distinct chromosomes. Based on the characterization and interpretation of gene function from several examples, we demonstrate that the integration of forward and reverse genetics via a targeted mutagenesis library promises rapid validation of important agronomic genes for crops with complex genomes. Beyond specific findings, this study also guides further optimization of high-throughput CRISPR experiments in plants.

De novo domestication: a new way for crop design and breeding.

The impending global climate change presents significant challenges to agricultural production. It is imperative to find approaches to ensure sustained growth in food production while reducing agricultural input, in order to meet the needs of worldwide people for nutritious food supply. One of the effective strategies to address this challenge is still the development of new crop varieties with high yield, stable yield, environmental friendliness and rich nutrition. The creation of new crop cultivars depends largely on the expansion of genetic resources and the innovation of breeding techniques. De novo domestication is an innovative breeding strategy for developing new crop varieties. It involves utilizing undomesticated or semi-domesticated plants with desirable traits as founder species for breeding. The process involves rapid domestication of wild plants through the redesign of agronomic traits and the introduction of domestication genes to meet diverse human needs. In this review, we overview the history of crop domestication and genetic improvement, clarify the necessity of enriching crop diversity, and emphasize the significance of wild plants' genetic diversity in expanding the scope for crop redesign. Breeding strategy innovation is the key to accelerate crop breeding. We also discuss the feasibility and prospects of rapid developing new crops through de novo domestication.

gcaPDA: a haplotype-resolved diploid assembler.

BACKGROUND: Generating chromosome-scale haplotype resolved assembly is important for functional studies. However, current de novo assemblers are either haploid assemblers that discard allelic information, or diploid assemblers that can only tackle genomes of low complexity. RESULTS: Here, Using robust programs, we build a diploid genome assembly pipeline called gcaPDA (gamete cells assisted Phased Diploid Assembler), which exploits haploid gamete cells to assist in resolving haplotypes. We demonstrate the effectiveness of gcaPDA based on simulated HiFi reads of maize genome which is highly heterozygous and repetitive, and real data from rice. CONCLUSIONS: With applicability of coping with complex genomes and fewer restrictions on application than most of diploid assemblers, gcaPDA is likely to find broad applications in studies of eukaryotic genomes.

Phenotypic Plasticity Contributes to Maize Adaptation and Heterosis.

Plant phenotypic plasticity describes altered phenotypic performance of an individual when grown in different environments. Exploring genetic architecture underlying plant plasticity variation may help mitigate the detrimental effects of a rapidly changing climate on agriculture, but little research has been done in this area to date. In the present study, we established a population of 976 maize F1 hybrids by crossing 488 diverse inbred lines with two elite testers. Genome-wide association study identified hundreds of quantitative trait loci associated with phenotypic plasticity variation across diverse F1 hybrids, the majority of which contributed very little variance, in accordance with the polygenic nature of these traits. We identified several quantitative trait locus regions that may have been selected during the tropical-temperate adaptation process. We also observed heterosis in terms of phenotypic plasticity, in addition to the traditional genetic value differences measured between hybrid and inbred lines, and the pattern of which was affected by genetic background. Our results demonstrate a landscape of phenotypic plasticity in maize, which will aid in the understanding of its genetic architecture, its contribution to adaptation and heterosis, and how it may be exploited for future maize breeding in a rapidly changing environment.

De Novo Domestication in the Multi-Omics Era.

Most cereal crops were domesticated within the last 12,000 years and subsequently spread around the world. These crops have been nourishing the world by supplying a primary energy and nutrient source, thereby playing a critical role in determining the status of human health and sustaining the global population. Here, we review the major challenges of future agriculture and emphasize the utilization of wild germplasm. De novo domestication is one of the most straightforward strategies to manipulate domestication-related and/or other genes with known function, and thereby introduce desired traits into wild plants. We also summarize known causal variations and their corresponding pathways in order to better understand the genetic basis of crop evolution, and how this knowledge could facilitate de novo domestication. Indeed knowledge-driven de novo domestication has great potential for the development of new sustainable crops that have climate-resilient high yield with low resource input and meet individual nutrient needs. Finally, we discuss current opportunities for and barriers to knowledge-driven de novo domestication.

Genetic variation in YIGE1 contributes to ear length and grain yield in maize.

Ear length (EL), which is controlled by quantitative trait loci (QTLs), is an important component of grain yield and as such is a key target trait in maize breeding. However, very few EL QTLs have been cloned, and their molecular mechanisms are largely unknown. Here, using a genome wide association study (GWAS), we identified a QTL, YIGE1, which encodes an unknown protein that regulates EL by affecting pistillate floret number. Overexpression of YIGE1 increased female inflorescence meristem (IM) size, increased EL and kernel number per row (KNPR), and thus enhanced grain yield. By contrast, CRISPR/Cas9 knockout and Mutator insertion mutant lines of YIGE1 displayed decreased IM size and EL. A single-nucleotide polymorphism (SNP) located in the regulatory region of YIGE1 had a large effect on its promoter strength, which positively affected EL by increasing gene expression. Further analysis shows that YIGE1 may be involved in sugar and auxin signal pathways to regulate maize ear development, thus affecting IM activity and floret production in maize inflorescence morphogenesis. These findings provide new insights into ear development and will ultimately facilitate maize molecular breeding.

Metabolomics analysis reveals differences in evolution between maize and rice.

Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice.

Genetic variants and underlying mechanisms influencing variance heterogeneity in maize.

Traditional genetic studies focus on identifying genetic variants associated with the mean difference in a quantitative trait. Because genetic variants also influence phenotypic variation via heterogeneity, we conducted a variance-heterogeneity genome-wide association study to examine the contribution of variance heterogeneity to oil-related quantitative traits. We identified 79 unique variance-controlling single nucleotide polymorphisms (vSNPs) from the sequences of 77 candidate variance-heterogeneity genes for 21 oil-related traits using the Levene test (P < 1.0 × 10-5 ). About 30% of the candidate genes encode enzymes that work in lipid metabolic pathways, most of which define clear expression variance quantitative trait loci. Of the vSNPs specifically associated with the genetic variance heterogeneity of oil concentration, 89% can be explained by additional linked mean-effects genetic variants. Furthermore, we demonstrated that gene × gene interactions play important roles in the formation of variance heterogeneity for fatty acid compositional traits. The interaction pattern was validated for one gene pair (GRMZM2G035341 and GRMZM2G152328) using yeast two-hybrid and bimolecular fluorescent complementation analyses. Our findings have implications for uncovering the genetic basis of hidden additive genetic effects and epistatic interaction effects, and we indicate opportunities to stabilize efficient breeding and selection of high-oil maize (Zea mays L.).

Genetic basis of kernel nutritional traits during maize domestication and improvement.

The nutritional traits of maize kernels are important for human and animal nutrition, and these traits have undergone selection to meet the diverse nutritional needs of humans. However, our knowledge of the genetic basis of selecting for kernel nutritional traits is limited. Here, we identified both single and epistatic quantitative trait loci (QTLs) that contributed to the differences of oil and carotenoid traits between maize and teosinte. Over half of teosinte alleles of single QTLs increased the values of the detected oil and carotenoid traits. Based on the pleiotropism or linkage information of the identified single QTLs, we constructed a trait-locus network to help clarify the genetic basis of correlations among oil and carotenoid traits. Furthermore, the selection features and evolutionary trajectories of the genes or loci underlying variations in oil and carotenoid traits revealed that these nutritional traits produced diverse selection events during maize domestication and improvement. To illustrate more, a mutator distance-relative transposable element (TE) in intron 1 of DXS2, which encoded a rate-limiting enzyme in the methylerythritol phosphate pathway, was identified to increase carotenoid biosynthesis by enhancing DXS2 expression. This TE occurs in the grass teosinte, and has been found to have undergone selection during maize domestication and improvement, and is almost fixed in yellow maize. Our findings not only provide important insights into evolutionary changes in nutritional traits, but also highlight the feasibility of reintroducing back into commercial agricultural germplasm those nutritionally important genes hidden in wild relatives.

QDtbn1 , an F-box gene affecting maize tassel branch number by a dominant model.

Tassel branch number (TBN) is one of the important agronomic traits that directly contribute to grain yield in maize (Zea mays L.), and identification of genes precisely regulating TBN in the parental lines is important for maize hybrid breeding. In this study, a quantitative trait nucleotide (QTN), QDtbn1 , related to tassel branch number was identified using a testcrossing association mapping population through association mapping with the Indels/SNPs in the 5'-UTR (untranslated region) of Zm00001d053358, which encodes a Kelch repeat-containing F-box protein. QDtbn1 was further confirmed to be associated with TBN by a dominant model using an F2 population, and over-expressing of the candidate gene resulted in a decreasing of TBN, implying that QDtbn1 was governed by the candidate gene with a negative model. This makes QDtbn1 very useful in maize hybrid breeding. QDtbn1 could interact with a maize Skp1-like protein and a SnRK1 protein, and the SnRK1 could also interact with a SnRK2.8 protein. In addition, quantitative real-time PCR assay showed that five substrates of SnRK2 were down-regulated in the over-expressed plants. These imply that the SCF (Skp1/Cul1/F-box protein/Roc1) complex and ABA signal pathway might be involved in the modulation of TBN in maize.