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Summary: With the rapid development of long-read sequencing technologies, the era of individual complete genomes is approaching. We have developed wgatools , a cross-platform, ultrafast toolkit that supports a range of whole genome alignment (WGA) formats, offering practical tools for conversion, processing, statistical evaluation, and visualization of alignments, thereby facilitating population-level genome analysis and advancing functional and evolutionary genomics., Availability and Implementation: wgatools supports diverse formats and can process, filter, and statistically evaluate alignments, perform alignment-based variant calling, and visualize alignments both locally and genome-wide. Built with Rust for efficiency and safe memory usage, it ensures fast performance and can handle large datasets consisting of hundreds of genomes. wgatools is published as free software under the MIT open-source license, and its source code is freely available at https://github.com/wjwei-handsome/wgatools., Competing Interests: Competing Interests The authors declare no competing interests.

Chromatin interactions create spatial proximity between distal regulatory elements and target genes in the genome, which has an important impact on gene expression, transcriptional regulation, and phenotypic traits. To date, several methods have been developed for predicting gene expression. However, existing methods do not take into consideration the effect of chromatin interactions on target gene expression, thus potentially reducing the accuracy of gene expression prediction and mining of important regulatory elements. In this study, we developed a highly accurate deep learning-based gene expression prediction model (DeepCBA) based on maize chromatin interaction data. Compared with existing models, DeepCBA exhibits higher accuracy in expression classification and expression value prediction. The average Pearson correlation coefficients (PCCs) for predicting gene expression using gene promoter proximal interactions, proximal-distal interactions, and both proximal and distal interactions were 0.818, 0.625, and 0.929, respectively, representing an increase of 0.357, 0.16, and 0.469 over the PCCs obtained with traditional methods that use only gene proximal sequences. Some important motifs were identified through DeepCBA; they were enriched in open chromatin regions and expression quantitative trait loci and showed clear tissue specificity. Importantly, experimental results for the maize flowering-related gene ZmRap2.7 and the tillering-related gene ZmTb1 demonstrated the feasibility of DeepCBA for exploration of regulatory elements that affect gene expression. Moreover, promoter editing and verification of two reported genes (ZmCLE7 and ZmVTE4) demonstrated the utility of DeepCBA for the precise design of gene expression and even for future intelligent breeding. DeepCBA is available at http://www.deepcba.com/ or http://124.220.197.196/., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

How to feed 10 billion human populations is one of the challenges that need to be addressed in the following decades, especially under an unpredicted climate change. Crop breeding, initiating from the phenotype-based selection by local farmers and developing into current biotechnology-based breeding, has played a critical role in securing the global food supply. However, regarding the changing environment and ever-increasing human population, can we breed outstanding crop varieties fast enough to achieve high productivity, good quality, and widespread adaptability? This review outlines the recent achievements in understanding cereal crop breeding, including the current knowledge about crop agronomic traits, newly developed techniques, crop big biological data research, and the possibility of integrating them for intelligence-driven breeding by design, which ushers in a new era of crop breeding practice and shapes the novel architecture of future crops. This review focuses on the major cereal crops, including rice, maize, and wheat, to explain how intelligence-driven breeding by design is becoming a reality., Competing Interests: Conflict of interest The authors declared that they have no conflicts of interest to this work., (Copyright © 2024 Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, and Genetics Society of China. Published by Elsevier Ltd. All rights reserved.)

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., (© 2024 Society for Experimental Biology and John Wiley & Sons Ltd.)

Doubled haploid (DH) technology and synthetic apomixis approaches can considerably shorten breeding cycles and enhance breeding efficiency. Compared with traditional breeding methods, DH technology offers the advantage of rapidly generating inbred lines, while synthetic apomixis can effectively fix hybrid vigor. In this review, we focus on (i) recent advances in identifying and characterizing genes responsible for haploid induction (HI), (ii) the molecular mechanisms of HI, (iii) spontaneous haploid genome doubling, and (iv) crop synthetic apomixis. We also discuss the challenges and potential solutions for future crop breeding programs utilizing DH technology and synthetic apomixis. Finally, we provide our perspectives about how to integrate DH and synthetic apomixis for precision breeding and de novo domestication., (Copyright © 2024 The Author. Published by Elsevier Inc. All rights reserved.)

Detecting genes that affect specific traits (such as human diseases and crop yields) is important for treating complex diseases and improving crop quality. A genome-wide association study (GWAS) provides new insights and directions for understanding complex traits by identifying important single nucleotide polymorphisms. Many GWAS summary statistics data related to various complex traits have been gathered recently. Studies have shown that GWAS risk loci and expression quantitative trait loci (eQTLs) often have a lot of overlaps, which makes gene expression gradually become an important intermediary to reveal the regulatory role of GWAS. In this review, we review three types of gene-trait association detection methods of integrating GWAS summary statistics and eQTLs data, namely colocalization methods, transcriptome-wide association study-oriented approaches, and Mendelian randomization-related methods. At the theoretical level, we discussed the differences, relationships, advantages, and disadvantages of various algorithms in the three kinds of gene-trait association detection methods. To further discuss the performance of various methods, we summarize the significant gene sets that influence high-density lipoprotein, low-density lipoprotein, total cholesterol, and triglyceride reported in 16 studies. We discuss the performance of various algorithms using the datasets of the four lipid traits. The advantages and limitations of various algorithms are analyzed based on experimental results, and we suggest directions for follow-up studies on detecting gene-trait associations., (© 2024. Science China Press.)

A comprehensive understanding of inflorescence development is crucial for crop genetic improvement, as inflorescence meristems give rise to reproductive organs and determine grain yield. However, dissecting inflorescence development at the cellular level has been challenging owing to a lack of specific marker genes to distinguish among cell types, particularly in different types of meristems that are vital for organ formation. In this study, we used spatial enhanced resolution omics-sequencing (Stereo-seq) to construct a precise spatial transcriptome map of the developing maize ear primordium, identifying 12 cell types, including 4 newly defined cell types found mainly in the inflorescence meristem. By extracting the meristem components for detailed clustering, we identified three subtypes of meristem and validated two MADS-box genes that were specifically expressed at the apex of determinate meristems and involved in stem cell determinacy. Furthermore, by integrating single-cell RNA transcriptomes, we identified a series of spatially specific networks and hub genes that may provide new insights into the formation of different tissues. In summary, this study provides a valuable resource for research on cereal inflorescence development, offering new clues for yield improvement., (© 2024. The Author(s), under exclusive licence to Springer Nature Limited.)

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., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Tocopherol is an important lipid-soluble antioxidant beneficial for both human health and plant growth. Here, we fine mapped a major QTL-qVE1 affecting γ-tocopherol content in maize kernel, positionally cloned and confirmed the underlying gene ZmPORB1 (por1), as a protochlorophyllide oxidoreductase. A 13.7 kb insertion reduced the tocopherol and chlorophyll content, and the photosynthetic activity by repressing ZmPORB1 expression in embryos of NIL-K22, but did not affect the levels of the tocopherol precursors HGA (homogentisic acid) and PMP (phytyl monophosphate). Furthermore, ZmPORB1 is inducible by low oxygen and light, thereby involved in the hypoxia response in developing embryos. Concurrent with natural hypoxia in embryos, the redox state has been changed with NO increasing and H 2 O 2 decreasing, which lowered γ-tocopherol content via scavenging reactive nitrogen species. In conclusion, we proposed that the lower light-harvesting chlorophyll content weakened embryo photosynthesis, leading to fewer oxygen supplies and consequently diverse hypoxic responses including an elevated γ-tocopherol consumption. Our findings shed light on the mechanism for fine-tuning endogenous oxygen concentration in the maize embryo through a novel feedback pathway involving the light and low oxygen regulation of ZmPORB1 expression and chlorophyll content., (© 2024. Science China Press.)

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., (© 2023 Society for Experimental Biology and John Wiley & Sons Ltd.)

The origins of maize were the topic of vigorous debate for nearly a century, but neither the current genetic model nor earlier archaeological models account for the totality of available data, and recent work has highlighted the potential contribution of a wild relative, Zea mays ssp. mexicana . Our population genetic analysis reveals that the origin of modern maize can be traced to an admixture between ancient maize and Zea mays ssp. mexicana in the highlands of Mexico some 4000 years after domestication began. We show that variation in admixture is a key component of maize diversity, both at individual loci and for additive genetic variation underlying agronomic traits. Our results clarify the origin of modern maize and raise new questions about the anthropogenic mechanisms underlying dispersal throughout the Americas.

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., (© 2023 John Wiley & Sons Ltd.)

Phenotypic plasticity is the ability of a given genotype to produce multiple phenotypes in response to changing environmental conditions. Understanding the genetic basis of phenotypic plasticity and establishing a predictive model is highly relevant to future agriculture under a changing climate. Here we report findings on the genetic basis of phenotypic plasticity for 23 complex traits using a diverse maize population planted at five sites with distinct environmental conditions. We found that latitude-related environmental factors were the main drivers of across-site variation in flowering time traits but not in plant architecture or yield traits. For the 23 traits, we detected 109 quantitative trait loci (QTLs), 29 for mean values, 66 for plasticity, and 14 for both parameters, and 80% of the QTLs interacted with latitude. The effects of several QTLs changed in magnitude or sign, driving variation in phenotypic plasticity. We experimentally validated one plastic gene, ZmTPS14.1, whose effect was likely mediated by the compensation effect of ZmSPL6 from a downstream pathway. By integrating genetic diversity, environmental variation, and their interaction into a joint model, we could provide site-specific predictions with increased accuracy by as much as 9.9%, 2.2%, and 2.6% for days to tassel, plant height, and ear weight, respectively. This study revealed a complex genetic architecture involving multiple alleles, pleiotropy, and genotype-by-environment interaction that underlies variation in the mean and plasticity of maize complex traits. It provides novel insights into the dynamic genetic architecture of agronomic traits in response to changing environments, paving a practical way toward precision agriculture., (Copyright © 2022 The Author(s). Published by Elsevier Inc. All rights reserved.)

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., (© 2022 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

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., (© 2022 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

Genomics and deep learning are a natural match since both are data-driven fields. Regulatory genomics refers to functional noncoding DNA regulating gene expression. In recent years, deep learning applications on regulatory genomics have achieved remarkable advances so-much-so that it has revolutionized the rules of the game of the computational methods in this field. Here, we review two emerging trends: (i) the modeling of very long input sequence (up to 200 kb), which requires self-matched modularization of model architecture; (ii) on the balance of model predictability and model interpretability because the latter is more able to meet biological demands. Finally, we discuss how to employ these two routes to design synthetic regulatory DNA, as a promising strategy for optimizing crop agronomic properties., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

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., (© 2022 The Authors.)

The genomic basis underlying the selection for environmental adaptation and yield-related traits in maize remains poorly understood. Here we carried out genome-wide profiling of the small RNA (sRNA) transcriptome (sRNAome) and transcriptome landscapes of a global maize diversity panel under dry and wet conditions and uncover dozens of environment-specific regulatory hotspots. Transgenic and molecular studies of Drought-Related Environment-specific Super eQTL Hotspot on chromosome 8 (DRESH8) and ZmMYBR38, a target of DRESH8-derived small interfering RNAs, revealed a transposable element-mediated inverted repeats (TE-IR)-derived sRNA- and gene-regulatory network that balances plant drought tolerance with yield-related traits. A genome-wide scan revealed that TE-IRs associate with drought response and yield-related traits that were positively selected and expanded during maize domestication. These results indicate that TE-IR-mediated posttranscriptional regulation is a key molecular mechanism underlying the tradeoff between crop environmental adaptation and yield-related traits, providing potential genomic targets for the breeding of crops with greater stress tolerance but uncompromised yield., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Networks are powerful tools to uncover functional roles of genes in phenotypic variation at a system-wide scale. Here, we constructed a maize network map that contains the genomic, transcriptomic, translatomic and proteomic networks across maize development. This map comprises over 2.8 million edges in more than 1,400 functional subnetworks, demonstrating an extensive network divergence of duplicated genes. We applied this map to identify factors regulating flowering time and identified 2,651 genes enriched in eight subnetworks. We validated the functions of 20 genes, including 18 with previously unknown connections to flowering time in maize. Furthermore, we uncovered a flowering pathway involving histone modification. The multi-omics integrative network map illustrates the principles of how molecular networks connect different types of genes and potential pathways to map a genome-wide functional landscape in maize, which should be applicable in a wide range of species., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Appropriate root system architecture (RSA) can improve maize yields in densely planted fields, but little is known about its genetic basis in maize. Here we performed root phenotyping of 14,301 field-grown plants from an association mapping panel to study the genetic architecture of maize RSA. A genome-wide association study identified 81 high-confidence RSA-associated candidate genes and revealed that 28 (24.3%) of known root-related genes were selected during maize domestication and improvement. We found that modern maize breeding has selected for a steeply angled root system. Favourable alleles related to steep root system angle have continuously accumulated over the course of modern breeding, and our data pinpoint the root-related genes that have been selected in different breeding eras. We confirm that two auxin-related genes, ZmRSA3.1 and ZmRSA3.2, contribute to the regulation of root angle and depth in maize. Our genome-wide identification of RSA-associated genes provides new strategies and genetic resources for breeding maize suitable for high-density planting., (© 2022. The Author(s), under exclusive licence to Springer Nature Limited.)

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., (© The Author(s) 2022. Published by Oxford University Press on behalf of Japanese Society of Plant Physiologists. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding., (© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Background: Maize (Zea mays L.) is at the vanguard facing the upcoming breeding challenges. However, both a super pan-genome for the Zea genus and a comprehensive genetic variation map for maize breeding are still lacking., Results: Here, we construct an approximately 6.71-Gb pan-Zea genome that contains around 4.57-Gb non-B73 reference sequences from fragmented de novo assemblies of 721 pan-Zea individuals. We annotate a total of 58,944 pan-Zea genes and find around 44.34% of them are dispensable in the pan-Zea population. Moreover, 255,821 common structural variations are identified and genotyped in a maize association mapping panel. Further analyses reveal gene presence/absence variants and their potential roles during domestication of maize. Combining genetic analyses with multi-omics data, we demonstrate how structural variants are associated with complex agronomic traits., Conclusions: Our results highlight the underexplored role of the pan-Zea genome and structural variations to further understand domestication of maize and explore their potential utilization in crop improvement., (© 2022. The Author(s).)

Unilateral cross incompatibility (UCI) occurs between popcorn and dent corn, and represents a critical step towards speciation. It has been reported that ZmGa1P, encoding a pectin methylesterase (PME), is a male determinant of the Ga1 locus. However, the female determinant and the genetic relationship between male and female determinants at this locus are unclear. Here, we report three different types, a total of seven linked genes underlying the Ga1 locus, which control UCI phenotype by independently affecting pollen tube growth in both antagonistic and synergistic manners. These include five pollen-expressed PME genes (ZmGa1Ps-m), a silk-expressed PME gene (ZmPME3), and another silk-expressed gene (ZmPRP3), encoding a pathogenesis-related (PR) proteins. ZmGa1Ps-m confer pollen compatibility. Presence of ZmPME3 causes silk to reject incompatible pollen. ZmPRP3 promotes incompatibility pollen tube growth and thereby breaks the blocking effect of ZmPME3. In addition, evolutionary genomics analyses suggest that the divergence of the Ga1 locus existed before maize domestication and continued during breeding improvement. The knowledge gained here deepen our understanding of the complex regulation of cross incompatibility., (© 2022. The Author(s).)

Broad-spectrum resistance has great values for crop breeding. However, its mechanisms are largely unknown. Here, we report the cloning of a maize NLR gene, RppK, for resistance against southern corn rust (SCR) and its cognate Avr gene, AvrRppK, from Puccinia polysora (the causal pathogen of SCR). The AvrRppK gene has no sequence variation in all examined isolates. It has high expression level during infection and can suppress pattern-triggered immunity (PTI). Further, the introgression of RppK into maize inbred lines and hybrids enhances resistance against multiple isolates of P. polysora, thereby increasing yield in the presence of SCR. Together, we show that RppK is involved in resistance against multiple P. polysora isolates and it can recognize AvrRppK, which is broadly distributed and conserved in P. polysora isolates., (© 2022. The Author(s).)

Haploid induction (HI) is an important tool in crop breeding. Phospholipase A1 (ZmPLA1)/NOT LIKE DAD (NLD)/MATRILINEAL (MTL) is a key gene controlling HI in maize; however, the underlying molecular mechanism remains unclear. In this study, to dissect why loss of ZmPLA1 function could mediate HI we performed a comprehensive multiple omics analysis of zmpla1 mutant anthers by integrating transcriptome, metabolome, quantitative proteome, and protein modification data. Functional classes of significantly enriched or differentially abundant molecular entities were found to be associated with the oxidative stress response, suggesting that a reactive oxygen species (ROS) burst plays a critical role in HI. In support of this, we further discovered that a simple chemical treatment of pollen with ROS reagents could lead to HI. Moreover, we identified ZmPOD65, which encodes a sperm-specific peroxidase, as a new gene controlling HI. Taken together, our study revealed a likely mechanism of HI, discovered a new gene controlling HI, and created a new method for HI in maize, indicating the importance of ROS balance in maintaining normal reproduction and providing a potential route to accelerate crop breeding., (Copyright © 2022 The Author. Published by Elsevier Inc. All rights reserved.)

Southern corn rust (SCR), caused by the fungal pathogen Puccinia polysora, is a major threat to maize production worldwide. Efficient breeding and deployment of resistant hybrids are key to achieving durable control of SCR. Here, we report the molecular cloning and characterization of RppC, which encodes an NLR-type immune receptor and is responsible for a major SCR resistance quantitative trait locus. Furthermore, we identified the corresponding avirulence effector, AvrRppC, which is secreted by P. polysora and triggers RppC-mediated resistance. Allelic variation of AvrRppC directly determines the effectiveness of RppC-mediated resistance, indicating that monitoring of AvrRppC variants in the field can guide the rational deployment of RppC-containing hybrids in maize production. Currently, RppC is the most frequently deployed SCR resistance gene in China, and a better understanding of its mode of action is critical for extending its durability., (Copyright © 2022 The Author. Published by Elsevier Inc. All rights reserved.)

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., (© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.)

A better understanding of the extent of convergent selection among crops could greatly improve breeding programs. We found that the quantitative trait locus KRN2 in maize and its rice ortholog, OsKRN2 , experienced convergent selection. These orthologs encode WD40 proteins and interact with a gene of unknown function, DUF1644, to negatively regulate grain number in both crops. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-offs in other agronomic traits. Furthermore, genome-wide scans identified 490 pairs of orthologous genes that underwent convergent selection during maize and rice evolution, and these were enriched for two shared molecular pathways. KRN2 , together with other convergently selected genes, provides an excellent target for future crop improvement.

Genomic prediction in crop breeding is hindered by modeling on limited phenotypic traits. We propose an integrative multi-trait breeding strategy via machine learning algorithm, target-oriented prioritization (TOP). Using a large hybrid maize population, we demonstrate that the accuracy for identifying a candidate that is phenotypically closest to an ideotype, or target variety, achieves up to 91%. The strength of TOP is enhanced when omics level traits are included. We show that TOP enables selection of inbreds or hybrids that outperform existing commercial varieties. It improves multiple traits and accurately identifies improved candidates for new varieties, which will greatly influence breeding., (© 2022. The Author(s).)

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., (© 2022. The Author(s).)

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., (© American Society of Plant Biologists 2021. All rights reserved. For permissions, please email: journals.permissions@oup.com.)

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., (© The Author(s) 2021. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

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., (© 2021 The Authors. The Plant Journal published by Society for Experimental Biology and John Wiley & Sons Ltd.)

LightGBM is an ensemble model of decision trees for classification and regression prediction. We demonstrate its utility in genomic selection-assisted breeding with a large dataset of inbred and hybrid maize lines. LightGBM exhibits superior performance in terms of prediction precision, model stability, and computing efficiency through a series of benchmark tests. We also assess the factors that are essential to ensure the best performance of genomic selection prediction by taking complex scenarios in crop hybrid breeding into account. LightGBM has been implemented as a toolbox, CropGBM, encompassing multiple novel functions and analytical modules to facilitate genomically designed breeding in crops., (© 2021. The Author(s).)

Background: Drought is a major environmental disaster that causes crop yield loss worldwide. Metabolites are involved in various environmental stress responses of plants. However, the genetic control of metabolomes underlying crop environmental stress adaptation remains elusive., Results: Here, we perform non-targeted metabolic profiling of leaves for 385 maize natural inbred lines grown under well-watered as well as drought-stressed conditions. A total of 3890 metabolites are identified and 1035 of these are differentially produced between well-watered and drought-stressed conditions, representing effective indicators of maize drought response and tolerance. Genetic dissections reveal the associations between these metabolites and thousands of single-nucleotide polymorphisms (SNPs), which represented 3415 metabolite quantitative trait loci (mQTLs) and 2589 candidate genes. 78.6% of mQTLs (2684/3415) are novel drought-responsive QTLs. The regulatory variants that control the expression of the candidate genes are revealed by expression QTL (eQTL) analysis of the transcriptomes of leaves from 197 maize natural inbred lines. Integrated metabolic and transcriptomic assays identify dozens of environment-specific hub genes and their gene-metabolite regulatory networks. Comprehensive genetic and molecular studies reveal the roles and mechanisms of two hub genes, Bx12 and ZmGLK44, in regulating maize metabolite biosynthesis and drought tolerance., Conclusion: Our studies reveal the first population-level metabolomes in crop drought response and uncover the natural variations and genetic control of these metabolomes underlying crop drought adaptation, demonstrating that multi-omics is a powerful strategy to dissect the genetic mechanisms of crop complex traits., (© 2021. The Author(s).)

Accumulation of iron in seeds is essential for both plant reproduction and human nutrition. Transport of iron to seeds requires the chelator nicotianamine (NA) to prevent its precipitation in the plant vascular tissues. However, how NA is transported to the apoplast for forming metal-NA complexes remains unknown. Here, we report that two members of the nitrate/peptide transporter family, NAET1 and NAET2, function as NA transporters required for translocation of both iron and copper to seeds. We show that NAET1 and NAET2 are predominantly expressed in the shoot and root vascular tissues and mediate secretion of NA out of the cells in resembling the release of neurotransmitters from animal synaptic vesicles. These findings reveal an unusual mechanism of transmembrane transport in plants and uncover a fundamental aspect of plant nutrition that has implications for improving food nutrition and human health.

Background: Drought threatens the food supply of the world population. Dissecting the dynamic responses of plants to drought will be beneficial for breeding drought-tolerant crops, as the genetic controls of these responses remain largely unknown., Results: Here we develop a high-throughput multiple optical phenotyping system to noninvasively phenotype 368 maize genotypes with or without drought stress over a course of 98 days, and collected multiple optical images, including color camera scanning, hyperspectral imaging, and X-ray computed tomography images. We develop high-throughput analysis pipelines to extract image-based traits (i-traits). Of these i-traits, 10,080 were effective and heritable indicators of maize external and internal drought responses. An i-trait-based genome-wide association study reveals 4322 significant locus-trait associations, representing 1529 quantitative trait loci (QTLs) and 2318 candidate genes, many that co-localize with previously reported maize drought responsive QTLs. Expression QTL (eQTL) analysis uncovers many local and distant regulatory variants that control the expression of the candidate genes. We use genetic mutation analysis to validate two new genes, ZmcPGM2 and ZmFAB1A, which regulate i-traits and drought tolerance. Moreover, the value of the candidate genes as drought-tolerant genetic markers is revealed by genome selection analysis, and 15 i-traits are identified as potential markers for maize drought tolerance breeding., Conclusion: Our study demonstrates that combining high-throughput multiple optical phenotyping and GWAS is a novel and effective approach to dissect the genetic architecture of complex traits and clone drought-tolerance associated genes.

Crops feed the world's population and shape human civilization. The improvement of crop productivity has been ongoing for almost 10,000 years and has evolved from an experience-based to a knowledge-driven practice over the past three decades. Natural alleles and their reshuffling are long-standing genetic changes that affect how crops respond to various environmental conditions and agricultural practices. Decoding the genetic basis of natural variation is central to understanding crop evolution and, in turn, improving crop breeding. Here, we review current advances in the approaches used to map the causal alleles of natural variation, provide refined insights into the genetics and evolution of natural variation, and outline how this knowledge promises to drive the development of sustainable agriculture under the dome of emerging technologies.

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), Q Dtbn1 , 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. Q Dtbn1 was further confirmed to be associated with TBN by a dominant model using an F 2 population, and over-expressing of the candidate gene resulted in a decreasing of TBN, implying that Q Dtbn1 was governed by the candidate gene with a negative model. This makes Q Dtbn1 very useful in maize hybrid breeding. Q Dtbn1 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., (© 2020 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

Low grain moisture at harvest is crucial for safe production, transport and storage, but the genetic architecture of this trait in maize (Zea mays) remains elusive. Here, we measured the dynamic changes in grain moisture content in an association-mapping panel of 513 diverse maize inbred lines at five successive stages across five geographical environments. Genome-wide association study (GWAS) revealed 71 quantitative trait loci (QTLs) that influence grain moisture in maize. Epistatic effects play vital roles in the variability in moisture levels, even outperforming main-effect QTLs during the early dry-down stages. Distinct QTL-environment interactions influence the spatio-temporal variability of maize grain moisture, which is primarily triggered at specific times. By combining genetic population analysis, transcriptomic profiling and gene editing, we identified GRMZM5G805627 and GRMZM2G137211 as candidate genes underlying major QTLs for grain moisture in maize. Our results provide insights into the genetic architecture of dynamic changes in grain moisture, which should facilitate maize breeding., (© 2021 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.)

The majority of the crops and vegetables of today were domesticated from their wild progenitors within the past 12 000 years. Considerable research effort has been expended on characterizing the genes undergoing positive and negative selection during the processes of crop domestication and improvement. Many studies have also documented how the contents of a handful of metabolites have been altered during human selection, but we are only beginning to unravel the true extent of the metabolic consequences of breeding. We highlight how crop metabolomes have been wittingly or unwittingly shaped by the processes of domestication, and highlight how we can identify new targets for metabolite engineering for the purpose of de novo domestication of crop wild relatives., Competing Interests: Declaration of Interests The authors declare no conflicts of interest., (Copyright © 2021 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Background: In maize hybrid breeding, complementary pools of parental lines with reshuffled genetic variants are established for superior hybrid performance. To comprehensively decipher the genetics of heterosis, we present a new design of multiple linked F1 populations with 42,840 F1 maize hybrids, generated by crossing a synthetic population of 1428 maternal lines with 30 elite testers from diverse genetic backgrounds and phenotyped for agronomic traits., Results: We show that, although yield heterosis is correlated with the widespread, minor-effect epistatic QTLs, it may be resulted from a few major-effect additive and dominant QTLs in early developmental stages. Floral transition is probably one critical stage for heterosis formation, in which epistatic QTLs are activated by paternal contributions of alleles that counteract the recessive, deleterious maternal alleles. These deleterious alleles, while rare, epistatically repress other favorable QTLs. We demonstrate this with one example, showing that Brachytic2 represses the Ubiquitin3 locus in the maternal lines; in hybrids, the paternal allele alleviates this repression, which in turn recovers the height of the plant and enhances the weight of the ear. Finally, we propose a molecular design breeding by manipulating key genes underlying the transition from vegetative-to-reproductive growth., Conclusion: The new population design is used to dissect the genetic basis of heterosis which accelerates maize molecular design breeding by diminishing deleterious epistatic interactions.