5Gs for crop genetic improvement

Understanding the salinity resilience and productivity of halophytes in saline environments

The escalating salinity levels in cultivable soil pose a significant threat to agricultural productivity and, consequently, human sustenance. This problem is being exacerbated by natural processes and human activities, coinciding with a period of rapid population growth. Developing halophytic crops is needed to ensure food security is not impaired and land resources can be used sustainably. Evolution has created many close halophyte relatives of our major glycophytic crops, such as Puccinellia tenuiflora (relative of barley and wheat), Oryza coarctata (relative of rice) and Glycine soja (relative of soybean). There are also some halophytes have been subjected to semi-domestication and are considered as minor crops, such as Chenopodium quinoa. In this paper, we examine the prevailing comprehension of robust salinity resilience in halophytes. We summarize the existing strategies and technologies that equip researchers with the means to enhance the salt tolerance capabilities of primary crops and investigate the genetic makeup of halophytes.

Unlocking plant genetics with telomere-to-telomere genome assemblies

Contiguous genome sequence assemblies will help us to realize the full potential of crop translational genomics. Recent advances in sequencing technologies, especially long-read sequencing strategies, have made it possible to construct gapless telomere-to-telomere (T2T) assemblies, thus offering novel insights into genome organization and function. Plant genomes pose unique challenges, such as a continuum of ancient to recent polyploidy and abundant highly similar and long repetitive elements. Owing to progress in sequencing approaches, for most crop plants, chromosome-scale reference genome assemblies are available, but T2T assembly construction remains challenging. Here we describe methods for haplotype-resolved, gapless T2T assembly construction in plants, including various crop species. We outline the impact of T2T assemblies in elucidating the roles of repetitive elements in gene regulation, as well as in pangenomics, functional genomics, genome-assisted breeding and targeted genome manipulation. In conjunction with sequence-enriched germplasm repositories, T2T assemblies thus hold great promise for basic and applied plant sciences.

Leveraging Multiomics Insights and Exploiting Wild Relatives' Potential for Drought and Heat Tolerance in Maize

Climate change, particularly drought and heat stress, may slash agricultural productivity by 25.7% by 2080, with maize being the hardest hit. Therefore, unraveling the molecular nature of plant responses to these stressors is vital for the development of climate-smart maize. This manuscript's primary objective was to examine how maize plants respond to these stresses, both individually and in combination. Additionally, the paper delved into harnessing the potential of maize wild relatives as a valuable genetic resource and leveraging AI-based technologies to boost maize resilience. The role of multiomics approaches particularly genomics and transcriptomics in dissecting the genetic basis of stress tolerance was also highlighted. The way forward was proposed to utilize a bunch of information obtained through omics technologies by an interdisciplinary state-of-the-art forward-looking big-data, cyberagriculture system, and AI-based approach to orchestrate the development of climate resilient maize genotypes.

Multiomics Analyses Reveal MsC3H29 Positively Regulates Flavonoid Biosynthesis to Improve Drought Resistance of Autotetraploid Cultivated Alfalfa (Medicago sativa L.)

Alfalfa (Medicago sativa subsp. sativa), the "queen of forage," is the most important perennial legume, with high productivity and an excellent nutritional profile. Medicago sativa subsp. falcata is a subspecies of the alfalfa complex and exhibits better drought tolerance. However, drought stress significantly hampers their development and yield. The molecular mechanisms underlying the aboveground and underground tissues of sativa and falcata responding to drought stress remain obscure. Here, we performed a comprehensive comparative analysis of the physiological and transcriptomic responses of sativa and falcata under drought stress. The results showed that photosynthesis was inhibited, and antioxidant enzymes were activated under drought stress. MsC3H29, a CCCH-type zinc finger protein, was identified as a hub gene through weighted gene coexpression network analysis (WGCNA) and was significantly induced by drought in underground tissue. The MsC3H29 protein was localized in the nucleus. Overexpression (OE) of MsC3H29 can increase the primary root length and fresh weight of transgenic alfalfa hairy roots, while RNA interference (RNAi) decreases them under drought stress. The 2',7'-dichlorodihydrofluorescein diacetate (H2DCFDA) staining revealed that MsC3H29 promoted drought tolerance of alfalfa hairy roots through decreasing ROS accumulation. The targeted metabolome analysis showed that the overexpression of MsC3H29 resulted in higher levels of accumulation for flavonoid monomers, including vicenin, daidzein, apigenin, isorhamnetin, quercetin, and tricin, in transgenic alfalfa hairy roots before and after drought stress, while RNAi led to a reduction. Our study provided a key candidate gene for molecular breeding to improve drought resistance in alfalfa.

Exploring the interplay between angiosperm chlorophyll metabolism and environmental factors

MAIN CONCLUSION

In this review, we summarize how chlorophyll metabolism in angiosperm is affected by the environmental factors: light, temperature, metal ions, water, oxygen, and altitude. The significance of chlorophyll (Chl) in plant leaf morphogenesis and photosynthesis cannot be overstated. Over time, researchers have made significant advancements in comprehending the biosynthetic pathway of Chl in angiosperms, along with the pivotal enzymes and genes involved in this process, particularly those related to heme synthesis and light-responsive mechanisms. Various environmental factors influence the stability of Chl content in angiosperms by modulating Chl metabolic pathways. Understanding the interplay between plants Chl metabolism and environmental factors has been a prominent research topic. This review mainly focuses on angiosperms, provides an overview of the regulatory mechanisms governing Chl metabolism, and the impact of environmental factors such as light, temperature, metal ions (iron and magnesium), water, oxygen, and altitude on Chl metabolism. Understanding these effects is crucial for comprehending and preserving the homeostasis of Chl metabolism.

Celebrating Professor Rajeev K. Varshney's transformative research odyssey from genomics to the field on his induction as Fellow of the Royal Society

Professor Rajeev K. Varshney's transformative impact on crop genomics, genetics, and agriculture is the result of his passion, dedication, and unyielding commitment to harnessing the potential of genomics to address the most pressing challenges faced by the global agricultural community. Starting from a small town in India and reaching the global stage, Professor Varshney's academic and professional trajectory has inspired many scientists active in research today. His ground-breaking work, especially his effort to list orphan tropical crops to genomic resource-rich entities, has been transformative. Beyond his scientific achievements, Professor Varshney is recognized by his colleagues as an exemplary mentor, fostering the growth of future researchers, building institutional capacity, and strengthening scientific capability. His focus on translational genomics and strengthening seed system in developing countries for the improvement of agriculture has made a tangible impact on farmers' lives. His skills have been best utilized in roles at leading research centres where he has applied his expertise to deliver a new vision for crop improvement. These efforts have now been recognized by the Royal Society with the award of the Fellowship (FRS). As we mark this significant milestone in his career, we not only celebrate Professor Varshney's accomplishments but also his wider contributions that continue to transform the agricultural landscape.

Synergizing breeding strategies via combining speed breeding, phenotypic selection, and marker-assisted backcrossing for the introgression of Glu-B1i in wheat

Wheat is a major food crop that plays a crucial role in the human diet. Various breeding technologies have been developed and refined to meet the increasing global wheat demand. Several studies have suggested breeding strategies that combine generation acceleration systems and molecular breeding methods to maximize breeding efficiency. However, real-world examples demonstrating the effective utilization of these strategies in breeding programs are lacking. In this study, we designed and demonstrated a synergized breeding strategy (SBS) that combines rapid and efficient breeding techniques, including speed breeding, speed vernalization, phenotypic selection, backcrossing, and marker-assisted selection. These breeding techniques were tailored to the specific characteristics of the breeding materials and objectives. Using the SBS approach, from artificial crossing to the initial observed yield trial under field conditions only took 3.5 years, resulting in a 53% reduction in the time required to develop a BC2 near-isogenic line (NIL) and achieving a higher recurrent genome recovery of 91.5% compared to traditional field conditions. We developed a new wheat NIL derived from cv. Jokyoung, a leading cultivar in Korea. Milyang56 exhibited improved protein content, sodium dodecyl sulfate-sedimentation value, and loaf volume compared to Jokyoung, which were attributed to introgression of the Glu-B1i allele from the donor parent, cv. Garnet. SBS represents a flexible breeding model that can be applied by breeders for developing breeding materials and mapping populations, as well as analyzing the environmental effects of specific genes or loci and for trait stacking.

The plant endomicrobiome: Structure and strategies to produce stress resilient future crop

Plants have a microbiome, a diverse community of microorganisms, including bacteria, fungi, and viruses, living inside and on their tissues. Versatile endophytic microorganisms inhabited in every plant part without causing disease and develop endophytic microbiome or endo-microbiome. Plant endo-microbiome are drawn by the nutrient rich micro-environment, and in turn some microbes mutualistically endorse and protect plant from adverse environmental stresses. Plant endo-microbiome interact within well-designed host equilibrium containing xylem, phloem, nutrients, phytohormones, metabolites and shift according to environmental and nutritional change. Plant endo-microbiome regulate and respond to environmental variations, pathogens, herbivores by producing stress regulators, organic acids, secondary metabolites, stress hormones as well as unknown substances and signalling molecules. Endomicrobiome efficiently synthesizes multiple bioactive compounds, stress phytohormones with high competence. The technological innovation as next generation genomics biology and high-throughput multiomics techniques stepping stones on the illumination of critical endo-microbiome communities and functional characterization that aid in improving plant physiology, biochemistry and immunity interplay for best crop productivity. This review article contains deeper insight in endomicrobiome related research work in last years, recruitment, niche development, nutrient dynamics, stress removal mechanisms, bioactive services in plant health development, community architecture and communication, and immunity interplay in producing stress resilient future crop.

Characterization of a wheat stable QTL for spike length and its genetic effects on yield-related traits

Spike length (SL) is one of the most important agronomic traits affecting yield potential and stability in wheat. In this study, a major stable quantitative trait locus (QTL) for SL, i.e., qSl-2B, was detected in multiple environments in a recombinant inbred line (RIL) mapping population, KJ-RILs, derived from a cross between Kenong 9204 (KN9204) and Jing 411 (J411). The qSl-2B QTL was mapped to the 60.06-73.06 Mb region on chromosome 2B and could be identified in multiple mapping populations. An InDel molecular marker in the target region was developed based on a sequence analysis of the two parents. To further clarify the breeding use potential of qSl-2B, we analyzed its genetic effects and breeding selection effect using both the KJ-RIL population and a natural mapping population, which consisted of 316 breeding varieties/advanced lines. The results showed that the qSl-2B alleles from KN9204 showed inconsistent genetic effects on SL in the two mapping populations. Moreover, in the KJ-RILs population, the additive effects analysis of qSl-2B showed that additive effect was higher when both qSl-2D and qSl-5A harbor negative alleles under LN and HN. In China, a moderate selection utilization rate for qSl-2B was found in the Huanghuai winter wheat area and the selective utilization rate for qSl-2B continues to increase. The above findings provided a foundation for the genetic improvement of wheat SL in the future via molecular breeding strategies.

Stomatal improvement for crop stress resistance

The growth and yield of crop plants are threatened by environmental challenges such as water deficit, soil flooding, high salinity, and extreme temperatures, which are becoming increasingly severe under climate change. Stomata contribute greatly to plant adaptation to stressful environments by governing transpirational water loss and photosynthetic gas exchange. Increasing evidence has revealed that stomata formation is shaped by transcription factors, signaling peptides, and protein kinases, which could be exploited to improve crop stress resistance. The past decades have seen unprecedented progress in our understanding of stomata formation, but most of these advances have come from research on model plants. This review highlights recent research in stomata formation in crops and its multifaceted functions in abiotic stress tolerance. Current strategies, limitations, and future directions for harnessing stomatal development to improve crop stress resistance are discussed.

Designing future peanut: the power of genomics-assisted breeding

KEY MESSAGE

Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

Plant genomic resources at National Genomics Data Center: assisting in data-driven breeding applications

Genomic data serve as an invaluable resource for unraveling the intricacies of the higher plant systems, including the constituent elements within and among species. Through various efforts in genomic data archiving, integrative analysis and value-added curation, the National Genomics Data Center (NGDC), which is a part of the China National Center for Bioinformation (CNCB), has successfully established and currently maintains a vast amount of database resources. This dedicated initiative of the NGDC facilitates a data-rich ecosystem that greatly strengthens and supports genomic research efforts. Here, we present a comprehensive overview of central repositories dedicated to archiving, presenting, and sharing plant omics data, introduce knowledgebases focused on variants or gene-based functional insights, highlight species-specific multiple omics database resources, and briefly review the online application tools. We intend that this review can be used as a guide map for plant researchers wishing to select effective data resources from the NGDC for their specific areas of study.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42994-023-00134-4.

2Gs and plant architecture: breaking grain yield ceiling through breeding approaches for next wave of revolution in rice (Oryza sativa L.)

Rice is a principal food crop for more than half of the global population. Grain number and grain weight (2Gs) are the two complex traits controlled by several quantitative trait loci (QTLs) and are considered the most critical components for yield enhancement in rice. Novel molecular biology and QTL mapping strategies can be utilized in dissecting the complex genetic architecture of these traits. Discovering the valuable genes/QTLs associated with 2Gs traits hidden in the rice genome and utilizing them in breeding programs may bring a revolution in rice production. Furthermore, the positional cloning and functional characterization of identified genes and QTLs may aid in understanding the molecular mechanisms underlying the 2Gs traits. In addition, knowledge of modern genomic tools aids the understanding of the nature of plant and panicle architecture, which enhances their photosynthetic activity. Rice researchers continue to combine important yield component traits (including 2Gs for the yield ceiling) by utilizing modern breeding tools, such as marker-assisted selection (MAS), haplotype-based breeding, and allele mining. Physical co-localization of GW7 (for grain weight) and DEP2 (for grain number) genes present on chromosome 7 revealed the possibility of simultaneous introgression of these two genes, if desirable allelic variants were found in the single donor parent. This review article will reveal the genetic nature of 2Gs traits and use this knowledge to break the yield ceiling by using different breeding and biotechnological tools, which will sustain the world's food requirements.

TCOD: an integrated resource for tropical crops

Tropical crops are vital for tropical agriculture, with resource scarcity, functional diversity and extensive market demand, providing considerable economic benefits for the world's tropical agriculture-producing countries. The rapid development of sequencing technology has promoted a milestone in tropical crop research, resulting in the generation of massive amount of data, which urgently needs an effective platform for data integration and sharing. However, the existing databases cannot fully satisfy researchers' requirements due to the relatively limited integration level and untimely update. Here, we present the Tropical Crop Omics Database (TCOD, https://ngdc.cncb.ac.cn/tcod), a comprehensive multi-omics data platform for tropical crops. TCOD integrates diverse omics data from 15 species, encompassing 34 chromosome-level de novo assemblies, 1 255 004 genes with functional annotations, 282 436 992 unique variants from 2048 WGS samples, 88 transcriptomic profiles from 1997 RNA-Seq samples and 13 381 germplasm items. Additionally, TCOD not only employs genes as a bridge to interconnect multi-omics data, enabling cross-species comparisons based on homology relationships, but also offers user-friendly online tools for efficient data mining and visualization. In short, TCOD integrates multi-species, multi-omics data and online tools, which will facilitate the research on genomic selective breeding and trait biology of tropical crops.

Identification of Superior Haplotypes and Haplotype Combinations for Grain Size- and Weight-Related Genes for Breeding Applications in Rice (Oryza sativa L.)

The identification of superior haplotypes and haplotype combinations is essential for haplotype-based breeding (HBB), which provides selection targets for genomics-assisted breeding. In this study, genotypes of 42 functional genes in rice were analyzed by targeted capture sequencing in a panel of 180 Indica rice accessions. In total, 69 SNPs/Indels in seven genes were detected to be associated with grain length (GL), grain width (GW), ratio of grain length-width (L/W) and thousand-grain weight (TGW) using candidate gene-based association analysis, including BG1 and GS3 for GL, GW5 for GW, BG1 and GW5 for L/W, and AET1, SNAC1, qTGW3, DHD1 and GW5 for TGW. Furthermore, two haplotypes were identified for each of the seven genes according to these associated SNPs/Indels, and the amount of genetic variation explained by different haplotypes ranged from 3.24% to 27.66%. Additionally, three, three and eight haplotype combinations for GL, L/W and TGW explained 25.38%, 5.5% and 22.49% of the total genetic variation for each trait, respectively. Further analysis showed that Minghui63 had the superior haplotype combination Haplotype Combination 4 (HC4) for TGW. The most interesting finding was that some widely used restorer lines derived from Minghui63 also have the superior haplotype combination HC4, and our breeding varieties and lines using the haplotype-specific marker panel also confirmed that the TGW of the lines was much higher than that of their sister lines without HC4, suggesting that TGW-HC4 is the superior haplotype combination for TGW and can be utilized in rice breeding.

Near-gapless genome assemblies of Williams 82 and Lee cultivars for accelerating global soybean research

Complete, gapless telomere-to-telomere chromosome assemblies are a prerequisite for comprehensively investigating the architecture of complex regions, like centromeres or telomeres and removing uncertainties in the order, spacing, and orientation of genes. Using complementary genomics technologies and assembly algorithms, we developed highly contiguous, nearly gapless, genome assemblies for two economically important soybean [Glycine max (L.) Merr] cultivars (Williams 82 and Lee). The centromeres were distinctly annotated on all the chromosomes of both assemblies. We further found that the canonical telomeric repeats were present at the telomeres of all chromosomes of both Williams 82 and Lee genomes. A total of 10 chromosomes in Williams 82 and eight in Lee were entirely reconstructed in single contigs without any gap. Using the combination of ab initio prediction, protein homology, and transcriptome evidence, we identified 58,287 and 56,725 protein-coding genes in Williams 82 and Lee, respectively. The genome assemblies and annotations will serve as a valuable resource for studying soybean genomics and genetics and accelerating soybean improvement.

Smart reprograming of plants against salinity stress using modern biotechnological tools

Climate change gives rise to numerous environmental stresses, including soil salinity. Salinity/salt stress is the second biggest abiotic factor affecting agricultural productivity worldwide by damaging numerous physiological, biochemical, and molecular processes. In particular, salinity affects plant growth, development, and productivity. Salinity responses include modulation of ion homeostasis, antioxidant defense system induction, and biosynthesis of numerous phytohormones and osmoprotectants to protect plants from osmotic stress by decreasing ion toxicity and augmented reactive oxygen species scavenging. As most crop plants are sensitive to salinity, improving salt tolerance is crucial in sustaining global agricultural productivity. In response to salinity, plants trigger stress-related genes, proteins, and the accumulation of metabolites to cope with the adverse consequence of salinity. Therefore, this review presents an overview of salinity stress in crop plants. We highlight advances in modern biotechnological tools, such as omics (genomics, transcriptomics, proteomics, and metabolomics) approaches and different genome editing tools (ZFN, TALEN, and CRISPR/Cas system) for improving salinity tolerance in plants and accomplish the goal of "zero hunger," a worldwide sustainable development goal proposed by the FAO.

Mainstreaming production and nutrient resilience of vegetable crops in megacities: pre-breeding for terrace cultivation

Modern megacities offer convenient lifestyles to their citizens. However, agriculture is becoming increasingly vulnerable, especially during unexpected public health emergencies such as pandemics. Fortunately, the adaptability of terrace vegetables cultivation presents an opportunity to grow horticultural crops in residential spaces, bringing numerous benefits to citizens, including enhanced nutrition and recreational engagement in the cultivation process. Although certain planting skills and equipment have been developed, the citizens tend to sow some seeds with unknown pedigree, it is rare to find new plant varieties specifically bred for cultivation as terrace vegetables. To expand the genetic basis of new breeding materials, elite parents, and varieties (pre-breeding) for terrace cultivation, this review not only discusses the molecular breeding strategy for the identification, creation, and application of rational alleles for improving horticultural characteristics including plant architecture, flavor quality, and ornamental character, but also assesses the potential for terrace cultivation of some representative vegetable crops. We conclude that the process of pre-breeding specifically for terrace cultivation environments is vital for generating a genetic basis for urban terrace vegetable crops.

Data-driven approaches to improve water-use efficiency and drought resistance in crop plants

With the increasing population, there lies a pressing demand for food, feed and fibre, while the changing climatic conditions pose severe challenges for agricultural production worldwide. Water is the lifeline for crop production; thus, enhancing crop water-use efficiency (WUE) and improving drought resistance in crop varieties are crucial for overcoming these challenges. Genetically-driven improvements in yield, WUE and drought tolerance traits can buffer the worst effects of climate change on crop production in dry areas. While traditional crop breeding approaches have delivered impressive results in increasing yield, the methods remain time-consuming and are often limited by the existing allelic variation present in the germplasm. Significant advances in breeding and high-throughput omics technologies in parallel with smart agriculture practices have created avenues to dramatically speed up the process of trait improvement by leveraging the vast volumes of genomic and phenotypic data. For example, individual genome and pan-genome assemblies, along with transcriptomic, metabolomic and proteomic data from germplasm collections, characterised at phenotypic levels, could be utilised to identify marker-trait associations and superior haplotypes for crop genetic improvement. In addition, these omics approaches enable the identification of genes involved in pathways leading to the expression of a trait, thereby providing an understanding of the genetic, physiological and biochemical basis of trait variation. These data-driven gene discoveries and validation approaches are essential for crop improvement pipelines, including genomic breeding, speed breeding and gene editing. Herein, we provide an overview of prospects presented using big data-driven approaches (including artificial intelligence and machine learning) to harness new genetic gains for breeding programs and develop drought-tolerant crop varieties with favourable WUE and high-yield potential traits.

Small RNAs: Promising Molecules to Tackle Climate Change Impacts in Coffee Production

Over the centuries, human society has evolved based on the ability to select and use more adapted species for food supply, which means making plant species tastier and more productive in particular environmental conditions. However, nowadays, this scenario is highly threatened by climate change, especially by the changes in temperature and greenhouse gasses that directly affect photosynthesis, which highlights the need for strategic studies aiming at crop breeding and guaranteeing food security. This is especially worrying for crops with complex phenology, genomes with low variability, and the ones that support a large production chain, such as Coffea sp. L. In this context, recent advances shed some light on the genome function and transcriptional control, revealing small RNAs (sRNAs) that are responsible for environmental cues and could provide variability through gene expression regulation. Basically, sRNAs are responsive to environmental changes and act on the transcriptional and post-transcriptional gene silencing pathways that regulate gene expression and, consequently, biological processes. Here, we first discuss the predicted impact of climate changes on coffee plants and coffee chain production and then the role of sRNAs in response to environmental changes, especially temperature, in different species, together with their potential as tools for genetic improvement. Very few studies in coffee explored the relationship between sRNAs and environmental cues; thus, this review contributes to understanding coffee development in the face of climate change and towards new strategies of crop breeding.

Characterization and fine mapping analysis of a major stable QTL qKnps-4A for kernel number per spike in wheat

KEY MESSAGE

A major stable QTL for kernel number per spike was narrowed down to a 2.19-Mb region containing two potential candidate genes, and its effects on yield-related traits were characterized. Kernel number per spike (KNPS) in wheat is a key yield component. Dissection and characterization of major stable quantitative trait loci (QTLs) for KNPS would be of considerable value for the genetic improvement of yield potential using molecular breeding technology. We had previously reported a major stable QTL controlling KNPS, qKnps-4A. In the current study, primary fine-mapping analysis, based on the primary mapping population, located qKnps-4A to an interval of approximately 6.8-Mb from 649.0 to 655.8 Mb on chromosome 4A refering to 'Kenong 9204' genome. Further fine-mapping analysis based on a secondary mapping population narrowed qKnps-4A to an approximately 2.19-Mb interval from 653.72 to 655.91 Mb. Transcriptome sequencing, gene function annotation analysis and homologous gene related reports showed that TraesKN4A01HG38570 and TraesKN4A01HG38590 were most likely to be candidate genes of qKnps-4A. Phenotypic analysis based on paired near-isogenic lines in the target region showed that qKnps-4A increased KNPS mainly by increasing the number of central florets per spike. We also evaluated the effects of qKnps-4A on other yield-related traits. Moreover, we dissected the QTL cluster of qKnps-4A and qTkw-4A and proved that the phenotypic effects were probably due to close linkage of two or more genes rather than pleiotropic effects of a single gene. This study provides molecular marker resource for wheat molecular breeding designed to improve yield potential, and lay the foundation for gene functional analysis of qKnps-4A.

Integration of transcriptomic and metabolomic analysis unveils the response mechanism of sugar metabolism in Cyclocarya paliurus seedlings subjected to PEG-induced drought stress

Cyclocarya paliurus (Batal.) Iljinskaja is a multiple function tree species used for functional food and valued timber production. Carbohydrates, especially water-soluble carbohydrates, play an important role in osmotic protection, signal transduction and carbon storage. Under the circumstance of global climate change the abiotic stress would restrict the development of C. paliurus plantation, whereas there is few knowledge on the regulatory mechanisms of sugar metabolism under drought stress in C. paliurus. To investigate the drought response of C. paliurus at molecular level, we conducted an integrated analysis of transcriptomic and metabolomic of C. paliurus at three PEG-induced drought stress levels (0%: control; 15%: moderate drought; 25%: severe drought) in short term. Both moderate and severe drought treatments activated the chemical defense with lowering relative water content, and enhancing the contents of soluble protein, proline and malondialdehyde in the leaves. Meanwhile, alterations in the expression of differentially expressed genes and carbohydrate metabolism profiles were observed among the treatments. Weighted gene co-expression network analysis (WGCNA) showed 3 key modules, 8 structural genes (such as genes encoding beta-fructofuranosidase (INV), sucrose synthase (SUS), raffinose synthase (RS)) and 14 regulatory transcription factors were closely linked to sugar metabolism. Our results provided the foundation to understand the response mechanism of sugar metabolism in C. paliurus under drought stress, and would drive progress in breeding of drought-tolerant varieties and plantation development of the species.

miRNAs for crop improvement

Climate change significantly impacts crop production by inducing several abiotic and biotic stresses. The increasing world population, and their food and industrial demands require focused efforts to improve crop plants to ensure sustainable food production. Among various modern biotechnological tools, microRNAs (miRNAs) are one of the fascinating tools available for crop improvement. miRNAs belong to a class of small non-coding RNAs playing crucial roles in numerous biological processes. miRNAs regulate gene expression by post-transcriptional target mRNA degradation or by translation repression. Plant miRNAs have essential roles in plant development and various biotic and abiotic stress tolerance. In this review, we provide propelling evidence from previous studies conducted around miRNAs and provide a one-stop review of progress made for breeding stress-smart future crop plants. Specifically, we provide a summary of reported miRNAs and their target genes for improvement of plant growth and development, and abiotic and biotic stress tolerance. We also highlight miRNA-mediated engineering for crop improvement and sequence-based technologies available for the identification of miRNAs associated with stress tolerance and plant developmental events.

The Progression in Developing Genomic Resources for Crop Improvement

Sequencing technologies have rapidly evolved over the past two decades, and new technologies are being continually developed and commercialized. The emerging sequencing technologies target generating more data with fewer inputs and at lower costs. This has also translated to an increase in the number and type of corresponding applications in genomics besides enhanced computational capacities (both hardware and software). Alongside the evolving DNA sequencing landscape, bioinformatics research teams have also evolved to accommodate the increasingly demanding techniques used to combine and interpret data, leading to many researchers moving from the lab to the computer. The rich history of DNA sequencing has paved the way for new insights and the development of new analysis methods. Understanding and learning from past technologies can help with the progress of future applications. This review focuses on the evolution of sequencing technologies, their significant enabling role in generating plant genome assemblies and downstream applications, and the parallel development of bioinformatics tools and skills, filling the gap in data analysis techniques.

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Genome-wide association studies (GWAS) have allowed the discovery of marker-trait associations in crops over recent decades. However, their power is hampered by a number of limitations, with the key one among them being an overreliance on single-nucleotide polymorphisms (SNPs) as molecular markers. Indeed, SNPs represent only one type of genetic variation and are usually derived from alignment to a single genome assembly that may be poorly representative of the population under study. To overcome this, k-mer-based GWAS approaches have recently been developed. k-mer-based GWAS provide a universal way to assess variation due to SNPs, insertions/deletions, and structural variations without having to specifically detect and genotype these variants. In addition, k-mer-based analyses can be used in species that lack a reference genome. However, the use of k-mers for GWAS presents challenges such as data size and complexity, lack of standard tools, and potential detection of false associations. Nevertheless, efforts are being made to overcome these challenges and a general analysis workflow has started to emerge. We identify the priorities for k-mer-based GWAS in years to come, notably in the development of user-friendly programs for their analysis and approaches for linking significant k-mers to sequence variation.

The Era of Plant Breeding: Conventional Breeding to Genomics-assisted Breeding for Crop Improvement

Plant breeding has made a significant contribution to increasing agricultural production. Conventional breeding based on phenotypic selection is not effective for crop improvement. Because phenotype is considerably influenced by environmental factors, which will affect the selection of breeding materials for crop improvement. The past two decades have seen tremendous progress in plant breeding research. Especially the availability of high-throughput molecular markers followed by genomic-assisted approaches significantly contributed to advancing plant breeding. Integration of speed breeding with genomic and phenomic facilities allowed rapid quantitative trait loci (QTL)/gene identifications and ultimately accelerated crop improvement programs. The advances in sequencing technology helps to understand the genome organization of many crops and helped with genomic selection in crop breeding. Plant breeding has gradually changed from phenotype-to-genotype-based to genotype-to-phenotype-based selection. High-throughput phenomic platforms have played a significant role in the modern breeding program and are considered an essential part of precision breeding. In this review, we discuss the rapid advance in plant breeding technology for efficient crop improvements and provide details on various approaches/platforms that are helpful for crop improvement. This review will help researchers understand the recent developments in crop breeding and improvements.

Developing drought-smart, ready-to-grow future crops

Breeding crop plants with increased yield potential and improved tolerance to stressful environments is critical for global food security. Drought stress (DS) adversely affects agricultural productivity worldwide and is expected to rise in the coming years. Therefore, it is vital to understand the physiological, biochemical, molecular, and ecological mechanisms associated with DS. This review examines recent advances in plant responses to DS to expand our understanding of DS-associated mechanisms. Suboptimal water sources adversely affect crop growth and yields through physical impairments, physiological disturbances, biochemical modifications, and molecular adjustments. To control the devastating effect of DS in crop plants, it is important to understand its consequences, mechanisms, and the agronomic and genetic basis of DS for sustainable production. In addition to plant responses, we highlight several mitigation options such as omics approaches, transgenics breeding, genome editing, and biochemical to mechanical methods (foliar treatments, seed priming, and conventional agronomic practices). Further, we have also presented the scope of conventional and speed breeding platforms in helping to develop the drought-smart future crops. In short, we recommend incorporating several approaches, such as multi-omics, genome editing, speed breeding, and traditional mechanical strategies, to develop drought-smart cultivars to achieve the 'zero hunger' goal.

A prolific and robust whole-genome genotyping method using PCR amplification via primer-template mismatched annealing

Whole-genome genotyping methods are important for breeding. However, it has been challenging to develop a robust method for simultaneous foreground and background genotyping that can easily be adapted to different genes and species. In our study, we accidently discovered that in adapter ligation-mediated PCR, the amplification by primer-template mismatched annealing (PTMA) along the genome could generate thousands of stable PCR products. Based on this observation, we consequently developed a novel method for simultaneous foreground and background integrated genotyping by sequencing (FBI-seq) using one specific primer, in which foreground genotyping is performed by primer-template perfect annealing (PTPA), while background genotyping employs PTMA. Unlike DNA arrays, multiple PCR, or genome target enrichments, FBI-seq requires little preliminary work for primer design and synthesis, and it is easily adaptable to different foreground genes and species. FBI-seq therefore provides a prolific, robust, and accurate method for simultaneous foreground and background genotyping to facilitate breeding in the post-genomics era.

Machine learning bridges omics sciences and plant breeding

Some of the biological knowledge obtained from fundamental research will be implemented in applied plant breeding. To bridge basic research and breeding practice, machine learning (ML) holds great promise to translate biological knowledge and omics data into precision-designed plant breeding. Here, we review ML for multi-omics analysis in plants, including data dimensionality reduction, inference of gene-regulation networks, and gene discovery and prioritization. These applications will facilitate understanding trait regulation mechanisms and identifying target genes potentially applicable to knowledge-driven molecular design breeding. We also highlight applications of deep learning in plant phenomics and ML in genomic selection-assisted breeding, such as various ML algorithms that model the correlations among genotypes (genes), phenotypes (traits), and environments, to ultimately achieve data-driven genomic design breeding.

Plant Hormonomics: A Key Tool for Deep Physiological Phenotyping to Improve Crop Productivity

Agriculture is particularly vulnerable to climate change. To cope with the risks posed by climate-related stressors to agricultural production, global population growth, and changes in food preferences, it is imperative to develop new climate-smart crop varieties with increased yield and environmental resilience. Molecular genetics and genomic analyses have revealed that allelic variations in genes involved in phytohormone-mediated growth regulation have greatly improved productivity in major crops. Plant science has remarkably advanced our understanding of the molecular basis of various phytohormone-mediated events in plant life. These findings provide essential information for improving the productivity of crops growing in changing climates. In this review, we highlight the recent advances in plant hormonomics (multiple phytohormone profiling) and discuss its application to crop improvement. We present plant hormonomics as a key tool for deep physiological phenotyping, focusing on representative plant growth regulators associated with the improvement of crop productivity. Specifically, we review advanced methodologies in plant hormonomics, highlighting mass spectrometry- and nanosensor-based plant hormone profiling techniques. We also discuss the applications of plant hormonomics in crop improvement through breeding and agricultural management practices.

Developing future heat-resilient vegetable crops

Climate change seriously impacts global agriculture, with rising temperatures directly affecting the yield. Vegetables are an essential part of daily human consumption and thus have importance among all agricultural crops. The human population is increasing daily, so there is a need for alternative ways which can be helpful in maximizing the harvestable yield of vegetables. The increase in temperature directly affects the plants' biochemical and molecular processes; having a significant impact on quality and yield. Breeding for climate-resilient crops with good yields takes a long time and lots of breeding efforts. However, with the advent of new omics technologies, such as genomics, transcriptomics, proteomics, and metabolomics, the efficiency and efficacy of unearthing information on pathways associated with high-temperature stress resilience has improved in many of the vegetable crops. Besides omics, the use of genomics-assisted breeding and new breeding approaches such as gene editing and speed breeding allow creation of modern vegetable cultivars that are more resilient to high temperatures. Collectively, these approaches will shorten the time to create and release novel vegetable varieties to meet growing demands for productivity and quality. This review discusses the effects of heat stress on vegetables and highlights recent research with a focus on how omics and genome editing can produce temperature-resilient vegetables more efficiently and faster.

Crop germplasm: Current challenges, physiological-molecular perspective, and advance strategies towards development of climate-resilient crops

Germplasm is a long-term resource management mission and investment for civilization. An estimated ∼7.4 million accessions are held in 1750 plant germplasm centres around the world; yet, only 2% of these assets have been utilized as plant genetic resources (PGRs). According to recent studies, the current food yield trajectory will be insufficient to feed the world's population in 2050. Additionally, possible negative effects in terms of crop failure because of climate change are already being experienced across the world. Therefore, it is necessary to reconciliation of research advancement and innovation of practices for further exploration of the potential of crop germplasm especially for the complex traits associated with yield such as water- and nitrogen use efficiency. In this review, we tried to address current challenges, research gaps, physiological and molecular aspects of two broad spectrum complex traits such as water- and nitrogen-use efficiency, and advanced integrated strategies that could provide a platform for combined stress management for climate-smart crop development. Additionally, recent development in technologies that are directly related to germplasm characterization was highlighted for further molecular utilization towards the development of elite varieties.

Gradual daylength sensing coupled with optimum cropping modes enhances multi-latitude adaptation of rice and maize

To expand crop planting areas, reestablishment of crop latitude adaptation based on genetic variation in photoperiodic genes can be performed, but it is quite time consuming. By contrast, a crop variety that already exhibits multi-latitude adaptation has the potential to increase its planting areas to be more widely and quickly available. However, the importance and potential of multi-latitude adaptation of crop varieties have not been systematically described. Here, combining daylength-sensing data with the cropping system of elite rice and maize varieties, we found that varieties with gradual daylength sensing coupled with optimum cropping modes have an enhanced capacity for multi-latitude adaptation in China. Furthermore, this multi-latitude adaptation expanded their planting areas and indirectly improved China's nationwide rice and maize unit yield. Thus, coupling the daylength-sensing process with optimum cropping modes to enhance latitude adaptability of excellent varieties represents an exciting approach for deploying crop varieties with the potential to expand their planting areas and quickly improve nationwide crop unit yield in developing countries.

LettuceGDB: The community database for lettuce genetics and omics

As a globally popular leafy vegetable and a representative plant of the Asteraceae family, lettuce has great economic and academic significance. In the last decade, high-throughput sequencing, phenotyping, and other multi-omics data in lettuce have accumulated on a large scale, thus increasing the demand for an integrative lettuce database. Here, we report the establishment of a comprehensive lettuce database, LettuceGDB (https://www.lettucegdb.com/). As an omics data hub, the current LettuceGDB includes two reference genomes with detailed annotations; re-sequencing data from over 1000 lettuce varieties; a collection of more than 1300 worldwide germplasms and millions of accompanying phenotypic records obtained with manual and cutting-edge phenomics technologies; re-analyses of 256 RNA sequencing datasets; a complete miRNAome; extensive metabolite information for representative varieties and wild relatives; epigenetic data on the genome-wide chromatin accessibility landscape; and various lettuce research papers published in the last decade. Five hierarchically accessible functions (Genome, Genotype, Germplasm, Phenotype, and O-Omics) have been developed with a user-friendly interface to enable convenient data access. Eight built-in tools (Assembly Converter, Search Gene, BLAST, JBrowse, Primer Design, Gene Annotation, Tissue Expression, Literature, and Data) are available for data downloading and browsing, functional gene exploration, and experimental practice. A community forum is also available for information sharing, and a summary of current research progress on different aspects of lettuce is included. We believe that LettuceGDB can be a comprehensive functional database amenable to data mining and database-driven exploration, useful for both scientific research and lettuce breeding.

Multi-locus genome-wide association studies reveal genomic regions and putative candidate genes associated with leaf spot diseases in African groundnut (Arachis hypogaea L.) germplasm

Early leaf spot (ELS) and late leaf spot (LLS) diseases are the two most destructive groundnut diseases in Ghana resulting in ≤ 70% yield losses which is controlled largely by chemical method. To develop leaf spot resistant varieties, the present study was undertaken to identify single nucleotide polymorphism (SNP) markers and putative candidate genes underlying both ELS and LLS. In this study, six multi-locus models of genome-wide association study were conducted with the best linear unbiased predictor obtained from 294 African groundnut germplasm screened for ELS and LLS as well as image-based indices of leaf spot diseases severity in 2020 and 2021 and 8,772 high-quality SNPs from a 48 K SNP array Axiom platform. Ninety-seven SNPs associated with ELS, LLS and five image-based indices across the chromosomes in the 2 two sub-genomes. From these, twenty-nine unique SNPs were detected by at least two models for one or more traits across 16 chromosomes with explained phenotypic variation ranging from 0.01 - 62.76%, with exception of chromosome (Chr) 08 (Chr08), Chr10, Chr11, and Chr19. Seventeen potential candidate genes were predicted at ± 300 kbp of the stable/prominent SNP positions (12 and 5, down- and upstream, respectively). The results from this study provide a basis for understanding the genetic architecture of ELS and LLS diseases in African groundnut germplasm, and the associated SNPs and predicted candidate genes would be valuable for breeding leaf spot diseases resistant varieties upon further validation.

A Haplotype-Based GWAS Identified Trait-Improving QTL Alleles Controlling Agronomic Traits under Contrasting Nitrogen Fertilization Treatments in the MAGIC Wheat Population WM-800

The multi-parent-advanced-generation-intercross (MAGIC) population WM-800 was developed by intercrossing eight modern winter wheat cultivars to enhance the genetic diversity present in breeding populations. We cultivated WM-800 during two seasons in seven environments under two contrasting nitrogen fertilization treatments. WM-800 lines exhibited highly significant differences between treatments, as well as high heritabilities among the seven agronomic traits studied. The highest-yielding WM-line achieved an average yield increase of 4.40 dt/ha (5.2%) compared to the best founder cultivar Tobak. The subsequent genome-wide-association-study (GWAS), which was based on haplotypes, located QTL for seven agronomic traits including grain yield. In total, 40, 51, and 46 QTL were detected under low, high, and across nitrogen treatments, respectively. For example, the effect of QYLD_3A could be associated with the haplotype allele of cultivar Julius increasing yield by an average of 4.47 dt/ha (5.2%). A novel QTL on chromosome 2B exhibited pleiotropic effects, acting simultaneously on three-grain yield components (ears-per-square-meter, grains-per-ear, and thousand-grain-weight) and plant-height. These effects may be explained by a member of the nitrate-transporter-1 (NRT1)/peptide-family, TaNPF5.34, located 1.05 Mb apart. The WM-800 lines and favorable QTL haplotypes, associated with yield improvements, are currently implemented in wheat breeding programs to develop advanced nitrogen-use efficient wheat cultivars.

New horizons for building pyrenoid-based CO2-concentrating mechanisms in plants to improve yields

Many photosynthetic species have evolved CO2-concentrating mechanisms (CCMs) to improve the efficiency of CO2 assimilation by Rubisco and reduce the negative impacts of photorespiration. However, the majority of plants (i.e. C3 plants) lack an active CCM. Thus, engineering a functional heterologous CCM into important C3 crops, such as rice (Oryza sativa) and wheat (Triticum aestivum), has become a key strategic ambition to enhance yield potential. Here, we review recent advances in our understanding of the pyrenoid-based CCM in the model green alga Chlamydomonas reinhardtii and engineering progress in C3 plants. We also discuss recent modeling work that has provided insights into the potential advantages of Rubisco condensation within the pyrenoid and the energetic costs of the Chlamydomonas CCM, which, together, will help to better guide future engineering approaches. Key findings include the potential benefits of Rubisco condensation for carboxylation efficiency and the need for a diffusional barrier around the pyrenoid matrix. We discuss a minimal set of components for the CCM to function and that active bicarbonate import into the chloroplast stroma may not be necessary for a functional pyrenoid-based CCM in planta. Thus, the roadmap for building a pyrenoid-based CCM into plant chloroplasts to enhance the efficiency of photosynthesis now appears clearer with new challenges and opportunities.

Resequencing of 558 Chinese mungbean landraces identifies genetic loci associated with key agronomic traits

Mungbean is a warm-season annual food legume and plays important role in supplying food and nutritional security in many tropical countries. However, the genetic basis of its agronomic traits remains poorly understood. Therefore, we resequenced 558 Chinese mungbean landraces and produced a comprehensive map of mungbean genomic variation. We phenotyped all landraces in six different environments. Genome-wide association studies (GWAS) produced 110 signals significantly associated with nine agronomic traits, for which several candidate genes were identified. Overall, this study provides new insight into the genetic architecture of mungbean agronomic traits. Moreover, the genome-wide variations identified here should be valuable resources for future breeding studies of this important food legume.

The era of cultivating smart rice with high light efficiency and heat tolerance has come of age

How to improve the yield of crops has always been the focus of breeding research. Due to the population growth and global climate change, the demand for food has increased sharply, which has brought great challenges to agricultural production. In order to make up for the limitation of global cultivated land area, it is necessary to further improve the output of crops. Photosynthesis is the main source of plant assimilate accumulation, which has a profound impact on the formation of its yield. This review focuses on the cultivation of high light efficiency plants, introduces the main technical means and research progress in improving the photosynthetic efficiency of plants, and discusses the main problems and difficulties faced by the cultivation of high light efficiency plants. At the same time, in view of the frequent occurrence of high-temperature disasters caused by global warming, which seriously threatened plant normal production, we reviewed the response mechanism of plants to heat stress, introduced the methods and strategies of how to cultivate heat tolerant crops, especially rice, and briefly reviewed the progress of heat tolerant research at present. Given big progress in these area, the era of cultivating smart rice with high light efficiency and heat tolerance has come of age.

Multi-Omics Approaches and Resources for Systems-Level Gene Function Prediction in the Plant Kingdom

In higher plants, the complexity of a system and the components within and among species are rapidly dissected by omics technologies. Multi-omics datasets are integrated to infer and enable a comprehensive understanding of the life processes of organisms of interest. Further, growing open-source datasets coupled with the emergence of high-performance computing and development of computational tools for biological sciences have assisted in silico functional prediction of unknown genes, proteins and metabolites, otherwise known as uncharacterized. The systems biology approach includes data collection and filtration, system modelling, experimentation and the establishment of new hypotheses for experimental validation. Informatics technologies add meaningful sense to the output generated by complex bioinformatics algorithms, which are now freely available in a user-friendly graphical user interface. These resources accentuate gene function prediction at a relatively minimal cost and effort. Herein, we present a comprehensive view of relevant approaches available for system-level gene function prediction in the plant kingdom. Together, the most recent applications and sought-after principles for gene mining are discussed to benefit the plant research community. A realistic tabulation of plant genomic resources is included for a less laborious and accurate candidate gene discovery in basic plant research and improvement strategies.

Grain quality of spring wheat (<i>Triticum aestivum</i> L.) cultivars developed in Western Siberia under the conditions of Northern Kazakhstan

Background. Environmental testing is the first stage of wheat breeding, the purpose of which is to identify wheat samples suitable for local environments and capable of forming a fairly stable yield and high-quality grain. The proposed study presents the test results for spring bread wheat cultivars of Russian breeding grown in arid environments of Northern Kazakhstan in order to preserve their yield and baking qualities.

Materials and methods. The material of the study included 15 spring bread wheat cultivars. Protein and gluten content and the quality of gluten were determined using an infrared analyzer; the physical properties of the test were assessed using a Chopin alveograph and Brabender farinograph.

Results.  As a result of biochemical assessment, increased protein and gluten content and grain weight were observed in cvs. ‘Tyumenskaya 30’, ‘Aviada’, ‘Lutescens 585’, ‘Serebrina’, and ‘Tyumenets 2’. Dough deformation energy (W) characteristic of high-quality wheat and the balance in the P/L ratio (elasticity/elongation) were shown by cvs. ‘Tyumenskaya 33’ (290 a.u.; 1.15 P/L), ‘SKENT-3’ (307 a.u.; 0.89 P/L), and ‘Lutescens 585’ (374 a.u., 1.10 P/L). In laboratory baking, the volume of bread ranged from 620 ml (‘Tyumenskaya 27’) to 768 ml (‘Tyumenskaya 29’) with an average value of 707 ml. A baking quality analysis of the cultivars grown in the Northern Trans-Urals and Northern Kazakhstan demonstrated that the conditions in Northern Kazakhstan were more favorable for obtaining bread with an increased volume. On the basis of environmental tests and an assessment of a set of biochemical and technological indicators, cvs. ‘SKENT-3’ and ‘Tyumenskaya 29’ were selected. It makes sense to continue studying wheat cultivars that can be sources and donors of high-quality grain for the development of cultivars for the arid steppe of Northern Kazakhstan.

Genome-Wide Characterization of Ascorbate Peroxidase Gene Family in Peanut (Arachis hypogea L.) Revealed Their Crucial Role in Growth and Multiple Stress Tolerance

Ascorbate peroxidase (APX), an important antioxidant enzyme, plays a significant role in ROS scavenging by catalyzing the decrease of hydrogen peroxide under various environmental stresses. Nevertheless, information about the APX gene family and their evolutionary and functional attributes in peanut (Arachis hypogea L.) was not reported. Therefore, a comprehensive genome-wide study was performed to discover the APX genes in cultivated peanut genome. This study identified 166 AhAPX genes in the peanut genome, classified into 11 main groups. The gene duplication analysis showed that AhAPX genes had experienced segmental duplications and purifying selection pressure. Gene structure and motif investigation indicated that most of the AhAPX genes exhibited a comparatively well-preserved exon-intron pattern and motif configuration contained by the identical group. We discovered five phytohormones-, six abiotic stress-, and five growth and development-related cis-elements in the promoter regions of AhAPX. Fourteen putative ah-miRNAs from 12 families were identified, targeting 33 AhAPX genes. Furthermore, we identified 3,257 transcription factors from 38 families (including AP2, ARF, B3, bHLH, bZIP, ERF, MYB, NAC, WRKY, etc.) in 162 AhAPX genes. Gene ontology and KEGG enrichment analysis confirm the role of AhAPX genes in oxidoreductase activity, catalytic activity, cell junction, cellular response to stimulus and detoxification, biosynthesis of metabolites, and phenylpropanoid metabolism. Based on transcriptome datasets, some genes such as AhAPX4/7/17/77/82/86/130/133 and AhAPX160 showed significantly higher expression in diverse tissues/organs, i.e., flower, leaf, stem, roots, peg, testa, and cotyledon. Likewise, only a few genes, including AhAPX4/17/19/55/59/82/101/102/137 and AhAPX140, were significantly upregulated under abiotic (drought and cold), and phytohormones (ethylene, abscisic acid, paclobutrazol, brassinolide, and salicylic acid) treatments. qRT-PCR-based expression profiling presented the parallel expression trends as generated from transcriptome datasets. Our discoveries gave new visions into the evolution of APX genes and provided a base for further functional examinations of the AhAPX genes in peanut breeding programs.

Integrated Approach in Genomic Selection to Accelerate Genetic Gain in Sugarcane

Marker-assisted selection (MAS) has been widely used in the last few decades in plant breeding programs for the mapping and introgression of genes for economically important traits, which has enabled the development of a number of superior cultivars in different crops. In sugarcane, which is the most important source for sugar and bioethanol, marker development work was initiated long ago; however, marker-assisted breeding in sugarcane has been lagging, mainly due to its large complex genome, high levels of polyploidy and heterozygosity, varied number of chromosomes, and use of low/medium-density markers. Genomic selection (GS) is a proven technology in animal breeding and has recently been incorporated in plant breeding programs. GS is a potential tool for the rapid selection of superior genotypes and accelerating breeding cycle. However, its full potential could be realized by an integrated approach combining high-throughput phenotyping, genotyping, machine learning, and speed breeding with genomic selection. For better understanding of GS integration, we comprehensively discuss the concept of genetic gain through the breeder’s equation, GS methodology, prediction models, current status of GS in sugarcane, challenges of prediction accuracy, challenges of GS in sugarcane, integrated GS, high-throughput phenotyping (HTP), high-throughput genotyping (HTG), machine learning, and speed breeding followed by its prospective applications in sugarcane improvement.

Genome-Wide Identification of Candidate Genes Underlying Soluble Sugar Content in Vegetable Soybean (Glycine max L.) via Association and Expression Analysis

Soluble sugar is a major indicator of the intrinsic quality of vegetable soybean [Glycine max (L.) Merr. ]. The improvement of soluble sugar content in soybean is very important due to its healthcare functions for humans. The genetic mechanism of soluble sugar in soybean is unclear. In this study, 278 diverse soybean accessions were utilized to identify the quantitative trait nucleotides (QTNs) for total soluble sugar content in soybean seeds based on a genome-wide association study (GWAS). A total of 25,921 single-nucleotide polymorphisms (SNPs) with minor allele frequencies (MAFs) ≥ 5% and missing data ≤ 10% were selected for GWAS. Totally, thirteen QTNs associated with total soluble sugar content were identified, which were distributed on ten chromosomes. One hundred and fifteen genes near the 200-kb flanking region of these identified QTNs were considered candidate genes associated with total soluble sugar content in soybean seed. Gene-based association analysis and haplotype analysis were utilized to further identify the effect of candidate genes on total soluble sugar content. Totally, 84 SNPs from seventeen genes across four chromosomes were significantly associated with the total soluble sugar content. Among them, three SNPs from Glyma.02G292900 were identified at two locations, and other eighty-one SNPs from sixteen genes were detected at three locations. Furthermore, expression level analysis of candidate genes revealed that Glyma.02G293200 and Glyma.02G294900 were significantly positively associated with soluble sugar content and Glyma.02G294000 was significantly negatively associated with soluble sugar content. Six genes (i.e., Glyma.02G292600, Glyma.02G292700, Glyma.02G294000, Glyma.02G294300, Glyma.02G294400, and Glyma.15G264200) identified by GWAS were also detected by the analysis of differential expression genes based on soybean germplasms with higher and lower soluble sugar content. Among them, Glyma.02G294000 is the only gene that was identified by gene-based association analysis with total soluble sugar content and was considered an important candidate gene for soluble sugar content. These candidate genes and beneficial alleles would be useful for improving the soluble sugar content of soybean.

Toward a smart skin: Harnessing cuticle biosynthesis for crop adaptation to drought, salinity, temperature, and ultraviolet stress

Drought, salinity, extreme temperatures, and ultraviolet (UV) radiation are major environmental factors that adversely affect plant growth and crop production. As a protective shield covering the outer epidermal cell wall of plant aerial organs, the cuticle is mainly composed of cutin matrix impregnated and sealed with cuticular waxes, and greatly contributes to the plant adaption to environmental stresses. Past decades have seen considerable progress in uncovering the molecular mechanism of plant cutin and cuticular wax biosynthesis, as well as their important roles in plant stress adaptation, which provides a new direction to drive strategies for stress-resilient crop breeding. In this review, we highlighted the recent advances in cuticle biosynthesis in plant adaptation to drought, salinity, extreme temperatures, and UV radiation stress, and discussed the current status and future directions in harnessing cuticle biosynthesis for crop improvement.

Breeding history for shattering trait in sesame: classic to genomic approach

Sesame is an important oilseed crop that has high oil and protein content and unique antioxidant lignans. Capsule shattering at harvest is one of the most important problems affecting sesame production, with seed losses of up to 50%, making the crop unsuitable for mechanized harvesting. This paper provides an overview of breeding approaches addressing the capsule shattering trait in sesame and gives an outlook about the future perspectives of improvement for this trait. Sesame research has proceeded along the following parallel tracks: breeding for additional shatter resistance for manual harvest, breeding for mechanized harvest, and using molecular biology to improve the shatter resistance trait. In the future, genes controlling the shattering trait should be studied with techniques like RNA interference (RNAi), site-oriented mutagenesis, and gene editing with zinc finger nucleases (ZFNs) or CRISPR/Cas9, to develop new sesame varieties with capsules suitable for fully mechanized harvest.

Functional Allele Validation by Gene Editing to Leverage the Wealth of Genetic Resources for Crop Improvement

Advances in molecular technologies over the past few decades, such as high-throughput DNA marker genotyping, have provided more powerful plant breeding approaches, including marker-assisted selection and genomic selection. At the same time, massive investments in plant genetics and genomics, led by whole genome sequencing, have led to greater knowledge of genes and genetic pathways across plant genomes. However, there remains a gap between approaches focused on forward genetics, which start with a phenotype to map a mutant locus or QTL with the goal of cloning the causal gene, and approaches using reverse genetics, which start with large-scale sequence data and work back to the gene function. The recent establishment of efficient CRISPR-Cas-based gene editing promises to bridge this gap and provide a rapid method to functionally validate genes and alleles identified through studies of natural variation. CRISPR-Cas techniques can be used to knock out single or multiple genes, precisely modify genes through base and prime editing, and replace alleles. Moreover, technologies such as protoplast isolation, in planta transformation, and the use of developmental regulatory genes promise to enable high-throughput gene editing to accelerate crop improvement.

A wiring diagram to integrate physiological traits of wheat yield potential

As crop yields are pushed closer to biophysical limits, achieving yield gains becomes increasingly challenging and will require more insight into deterministic pathways to yields. Here, we propose a wiring diagram as a platform to illustrate the interrelationships of the physiological traits that impact wheat yield potential and to serve as a decision support tool for crop scientists. The wiring diagram is based on the premise that crop yield is a function of photosynthesis (source), the investment of assimilates into reproductive organs (sinks) and the underlying processes that enable expression of both. By illustrating these linkages as coded wires, the wiring diagram can show connections among traits that may not have been apparent, and can inform new research hypotheses and guide crosses designed to accumulate beneficial traits and alleles in breeding. The wiring diagram can also serve to create an ever-richer common point of reference for refining crop models in the future.

Multidimensional Role of Silicon to Activate Resilient Plant Growth and to Mitigate Abiotic Stress

Sustainable agricultural production is critically antagonistic by fluctuating unfavorable environmental conditions. The introduction of mineral elements emerged as the most exciting and magical aspect, apart from the novel intervention of traditional and applied strategies to defend the abiotic stress conditions. The silicon (Si) has ameliorating impacts by regulating diverse functionalities on enhancing the growth and development of crop plants. Si is categorized as a non-essential element since crop plants accumulate less during normal environmental conditions. Studies on the application of Si in plants highlight the beneficial role of Si during extreme stressful conditions through modulation of several metabolites during abiotic stress conditions. Phytohormones are primary plant metabolites positively regulated by Si during abiotic stress conditions. Phytohormones play a pivotal role in crop plants' broad-spectrum biochemical and physiological aspects during normal and extreme environmental conditions. Frontline phytohormones include auxin, cytokinin, ethylene, gibberellin, salicylic acid, abscisic acid, brassinosteroids, and jasmonic acid. These phytohormones are internally correlated with Si in regulating abiotic stress tolerance mechanisms. This review explores insights into the role of Si in enhancing the phytohormone metabolism and its role in maintaining the physiological and biochemical well-being of crop plants during diverse abiotic stresses. Moreover, in-depth information about Si's pivotal role in inducing abiotic stress tolerance in crop plants through metabolic and molecular modulations is elaborated. Furthermore, the potential of various high throughput technologies has also been discussed in improving Si-induced multiple stress tolerance. In addition, a special emphasis is engrossed in the role of Si in achieving sustainable agricultural growth and global food security.