Genomic innovation for crop improvement

Insights into maydis leaf blight resistance in maize: a comprehensive genome-wide association study in sub-tropics of India

BACKGROUND

In the face of contemporary climatic vulnerabilities and escalating global temperatures, the prevalence of maydis leaf blight (MLB) poses a potential threat to maize production. This study endeavours to discern marker-trait associations and elucidate the candidate genes that underlie resistance to MLB in maize by employing a diverse panel comprising 336 lines. The panel was screening for MLB across four environments, employing standard artificial inoculation techniques. Genome-wide association studies (GWAS) and haplotype analysis were conducted utilizing a total of 128,490 SNPs obtained from genotyping-by-sequencing (GBS).

RESULTS

GWAS identified 26 highly significant SNPs associated with MLB resistance, among the markers examined. Seven of these SNPs, reported in novel chromosomal bins (9.06, 5.01, 9.01, 7.04, 4.06, 1.04, and 6.05) were associated with genes: bzip23, NAGS1, CDPK7, aspartic proteinase NEP-2, VQ4, and Wun1, which were characterized for their roles in diminishing fungal activity, fortifying defence mechanisms against necrotrophic pathogens, modulating phyto-hormone signalling, and orchestrating oxidative burst responses. Gene mining approach identified 22 potential candidate genes associated with SNPs due to their functional relevance to resistance against necrotrophic pathogens. Notably, bin 8.06, which hosts five SNPs, showed a connection to defense-regulating genes against MLB, indicating the potential formation of a functional gene cluster that triggers a cascade of reactions against MLB. In silico studies revealed gene expression levels exceeding ten fragments per kilobase million (FPKM) for most genes and demonstrated coexpression among all candidate genes in the coexpression network. Haplotype regression analysis revealed the association of 13 common significant haplotypes at Bonferroni ≤ 0.05. The phenotypic variance explained by these significant haplotypes ranged from low to moderate, suggesting a breeding strategy that combines multiple resistance alleles to enhance resistance to MLB. Additionally, one particular haplotype block (Hap_8.3) was found to consist of two SNPs (S8_152715134, S8_152460815) identified in GWAS with 9.45% variation explained (PVE).

CONCLUSION

The identified SNPs/ haplotypes associated with the trait of interest contribute to the enrichment of allelic diversity and hold direct applicability in Genomics Assisted Breeding for enhancing MLB resistance in maize.

Molecular mechanisms controlling grain size and weight and their biotechnological breeding applications in maize and other cereal crops

BACKGROUND

Cereal crops are a primary energy source for humans. Grain size and weight affect both evolutionary fitness and grain yield of cereals. Although studies on gene mining and molecular mechanisms controlling grain size and weight are constantly emerging in cereal crops, only a few systematic reviews on the underlying molecular mechanisms and their breeding applications are available so far.

AIM OF REVIEW

This review provides a general state-of-the-art overview of molecular mechanisms and targeted strategies for improving grain size and weight of cereals as well as insights for future yield-improving biotechnology-assisted breeding.

KEY SCIENTIFIC CONCEPTS OF REVIEW

In this review, the evolution of research on grain size and weight over the last 20 years is traced based on a bibliometric analysis of 1158 publications and the main signaling pathways and transcriptional factors involved are summarized. In addition, the roles of post-transcriptional regulation and photosynthetic product accumulation affecting grain size and weight in maize and rice are outlined. State-of-the-art strategies for discovering novel genes related to grain size and weight in maize and other cereal crops as well as advanced breeding biotechnology strategies being used for improving yield including marker-assisted selection, genomic selection, transgenic breeding, and genome editing are also discussed.

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.

Deepening genomic sequences of 1081 Gossypium hirsutum accessions reveals novel SNPs and haplotypes relevant for practical breeding utility

Fiber quality is a major breeding goal in cotton, but phenotypically direct selection is often hindered. In this study, we identified fiber quality and yield related loci using GWAS based on 2.97 million SNPs obtained from 10.65× resequencing data of 1081 accessions. The results showed that 585 novel fiber loci, including two novel stable SNP peaks associated with fiber length on chromosomes At12 and Dt05 and one novel genome regions linked with fiber strength on chromosome Dt12 were identified. Furthermore, by means of gene expression analysis, GhM_A12G0090, GhM_D05G1692, GhM_D12G3135 were identified and GhM_D11G2208 function was identified in Arabidopsis. Additionally, 14 consistent and stable superior haplotypes were identified, and 25 accessions were detected as possessing these 14 superior haplotype in breeding. This study providing fundamental insight relevant to identification of genes associated with fiber quality and yield will enhance future efforts toward improvement of upland cotton.

The complex hexaploid oil-Camellia genome traces back its phylogenomic history and multi-omics analysis of Camellia oil biosynthesis

Oil-Camellia (Camellia oleifera), belonging to the Theaceae family Camellia, is an important woody edible oil tree species. The Camellia oil in its mature seed kernels, mainly consists of more than 90% unsaturated fatty acids, tea polyphenols, flavonoids, squalene and other active substances, which is one of the best quality edible vegetable oils in the world. However, genetic research and molecular breeding on oil-Camellia are challenging due to its complex genetic background. Here, we successfully report a chromosome-scale genome assembly for a hexaploid oil-Camellia cultivar Changlin40. This assembly contains 8.80 Gb genomic sequences with scaffold N50 of 180.0 Mb and 45 pseudochromosomes comprising 15 homologous groups with three members each, which contain 135 868 genes with an average length of 3936 bp. Referring to the diploid genome, intragenomic and intergenomic comparisons of synteny indicate homologous chromosomal similarity and changes. Moreover, comparative and evolutionary analyses reveal three rounds of whole-genome duplication (WGD) events, as well as the possible diversification of hexaploid Changlin40 with diploid occurred approximately 9.06 million years ago (MYA). Furthermore, through the combination of genomics, transcriptomics and metabolomics approaches, a complex regulatory network was constructed and allows to identify potential key structural genes (SAD, FAD2 and FAD3) and transcription factors (AP2 and C2H2) that regulate the metabolism of Camellia oil, especially for unsaturated fatty acids biosynthesis. Overall, the genomic resource generated from this study has great potential to accelerate the research for the molecular biology and genetic improvement of hexaploid oil-Camellia, as well as to understand polyploid genome evolution.

Exploring crop genomes: assembly features, gene prediction accuracy, and implications for proteomics studies

Plant genomics plays a pivotal role in enhancing global food security and sustainability by offering innovative solutions for improving crop yield, disease resistance, and stress tolerance. As the number of sequenced genomes grows and the accuracy and contiguity of genome assemblies improve, structural annotation of plant genomes continues to be a significant challenge due to their large size, polyploidy, and rich repeat content. In this paper, we present an overview of the current landscape in crop genomics research, highlighting the diversity of genomic characteristics across various crop species. We also assessed the accuracy of popular gene prediction tools in identifying genes within crop genomes and examined the factors that impact their performance. Our findings highlight the strengths and limitations of BRAKER2 and Helixer as leading structural genome annotation tools and underscore the impact of genome complexity, fragmentation, and repeat content on their performance. Furthermore, we evaluated the suitability of the predicted proteins as a reliable search space in proteomics studies using mass spectrometry data. Our results provide valuable insights for future efforts to refine and advance the field of structural genome annotation.

Omics-driven utilization of wild relatives for empowering pre-breeding in pearl millet

MAIN CONCLUSION

Pearl millet wild relatives harbour novel alleles which could be utilized to broaden genetic base of cultivated species. Genomics-informed pre-breeding is needed to speed up introgression from wild to cultivated gene pool in pearl millet. Rising episodes of intense biotic and abiotic stresses challenge pearl millet production globally. Wild relatives provide a wide spectrum of novel alleles which could address challenges posed by climate change. Pre-breeding holds potential to introgress novel diversity in genetically narrow cultivated Pennisetum glaucum from diverse gene pool. Practical utilization of gene pool diversity remained elusive due to genetic intricacies. Harnessing promising traits from wild pennisetum is limited by lack of information on underlying candidate genes/QTLs. Next-Generation Omics provide vast scope to speed up pre-breeding in pearl millet. Genomic resources generated out of draft genome sequence and improved genome assemblies can be employed to utilize gene bank accessions effectively. The article highlights genetic richness in pearl millet and its utilization with a focus on harnessing next-generation Omics to empower pre-breeding.

Revisiting growth-defence trade-offs and breeding strategies in crops

Plants have evolved a multi-layered immune system to fight off pathogens. However, immune activation is costly and is often associated with growth and development penalty. In crops, yield is the main breeding target and is usually affected by high disease resistance. Therefore, proper balance between growth and defence is critical for achieving efficient crop improvement. This review highlights recent advances in attempts designed to alleviate the trade-offs between growth and disease resistance in crops mediated by resistance (R) genes, susceptibility (S) genes and pleiotropic genes. We also provide an update on strategies for optimizing the growth-defence trade-offs to breed future crops with desirable disease resistance and high yield.

Pattern recognition receptors as potential therapeutic targets for developing immunological engineered plants

There is an urgent need to combat pathogen infestations in crop plants to ensure food security worldwide. To counter this, plants have developed innate immunity mediated by Pattern Recognition Receptors (PRRs) that recognize pathogen-associated molecular patterns (PAMPs) and damage- associated molecular patterns (DAMPs). PRRs activate Pattern-Triggered Immunity (PTI), a defence mechanism involving intricate cell-surface and intracellular receptors. The diverse ligand-binding ectodomains of PRRs, including leucine-rich repeats (LRRs) and lectin domains, facilitate the recognition of MAMPs and DAMPs. Pathogen resistance is mediated by a variety of PTI responses, including membrane depolarization, ROS production, and the induction of defence genes. An integral part of intracellular immunity is the Nucleotide-binding Oligomerization Domain, Leucine-rich Repeat proteins (NLRs) which recognize and respond to effectors in a potent manner. Enhanced understanding of PRRs, their ligands, and downstream signalling pathways has contributed to the identification of potential targets for genetically modified plants. By transferring PRRs across plant species, it is possible to create broad-spectrum resistance, potentially offering innovative solutions for plant protection and global food security. The purpose of this chapter is to provide an update on PRRs involved in disease resistance, clarify the mechanisms by which PRRs recognize ligands to form active receptor complexes and present various applications of PRRs and PTI in disease resistance management for plants.

Integrated meta-analysis and transcriptomics pinpoint genomic loci and novel candidate genes associated with submergence tolerance in rice

BACKGROUND

Due to rising costs, water shortages, and labour shortages, farmers across the globe now prefer a direct seeding approach. However, submergence stress remains a major bottleneck limiting the success of this approach in rice cultivation. The merger of accumulated rice genetic resources provides an opportunity to detect key genomic loci and candidate genes that influence the flooding tolerance of rice.

RESULTS

In the present study, a whole-genome meta-analysis was conducted on 120 quantitative trait loci (QTL) obtained from 16 independent QTL studies reported from 2004 to 2023. These QTL were confined to 18 meta-QTL (MQTL), and ten MQTL were successfully validated by independent genome-wide association studies from diverse natural populations. The mean confidence interval (CI) of the identified MQTL was 3.44 times narrower than the mean CI of the initial QTL. Moreover, four core MQTL loci with genetic distance less than 2 cM were obtained. By combining differentially expressed genes (DEG) from two transcriptome datasets with 858 candidate genes identified in the core MQTL regions, we found 38 common differentially expressed candidate genes (DECGs). In silico expression analysis of these DECGs led to the identification of 21 genes with high expression in embryo and coleoptile under submerged conditions. These DECGs encode proteins with known functions involved in submergence tolerance including WRKY, F-box, zinc fingers, glycosyltransferase, protein kinase, cytochrome P450, PP2C, hypoxia-responsive family, and DUF domain. By haplotype analysis, the 21 DECGs demonstrated distinct genetic differentiation and substantial genetic distance mainly between indica and japonica subspecies. Further, the MQTL7.1 was successfully validated using flanked marker S2329 on a set of genotypes with phenotypic variation.

CONCLUSION

This study provides a new perspective on understanding the genetic basis of submergence tolerance in rice. The identified MQTL and novel candidate genes lay the foundation for marker-assisted breeding/engineering of flooding-tolerant cultivars conducive to direct seeding.

Innovative computational tools provide new insights into the polyploid wheat genome

Bread wheat (Triticum aestivum) is an important crop and serves as a significant source of protein and calories for humans, worldwide. Nevertheless, its large and allopolyploid genome poses constraints on genetic improvement. The complex reticulate evolutionary history and the intricacy of genomic resources make the deciphering of the functional genome considerably more challenging. Recently, we have developed a comprehensive list of versatile computational tools with the integration of statistical models for dissecting the polyploid wheat genome. Here, we summarize the methodological innovations and applications of these tools and databases. A series of step-by-step examples illustrates how these tools can be utilized for dissecting wheat germplasm resources and unveiling functional genes associated with important agronomic traits. Furthermore, we outline future perspectives on new advanced tools and databases, taking into consideration the unique features of bread wheat, to accelerate genomic-assisted wheat breeding.

Multi-model genome-wide association studies for appearance quality in rice

Improving the quality of the appearance of rice is critical to meet market acceptance. Mining putative quality-related genes has been geared towards the development of effective breeding approaches for rice. In the present study, two SL-GWAS (CMLM and MLM) and three ML-GWAS (FASTmrEMMA, mrMLM, and FASTmrMLM) genome-wide association studies were conducted in a subset of 3K-RGP consisting of 198 rice accessions with 553,831 SNP markers. A total of 594 SNP markers were identified using the mixed linear model method for grain quality traits. Additionally, 70 quantitative trait nucleotides (QTNs) detected by the ML-GWAS models were strongly associated with grain aroma (AR), head rice recovery (HRR, %), and percentage of grains with chalkiness (PGC, %). Finally, 39 QTNs were identified using single- and multi-locus GWAS methods. Among the 39 reliable QTNs, 20 novel QTNs were identified for the above-mentioned three quality-related traits. Based on annotation and previous studies, four functional candidate genes (LOC_Os01g66110, LOC_Os01g66140, LOC_Os07g44910, and LOC_Os02g14120) were found to influence AR, HRR (%), and PGC (%), which could be utilized in rice breeding to improve grain quality traits.

Identification and Analysis of Candidate Genes Associated with Yield Structure Traits and Maize Yield Using Next-Generation Sequencing Technology

The main challenge of agriculture in the 21st century is the continuous increase in food production. In addition to ensuring food security, the goal of modern agriculture is the continued development and production of plant-derived biomaterials. Conventional plant breeding methods do not allow breeders to achieve satisfactory results in obtaining new varieties in a short time. Currently, advanced molecular biology tools play a significant role worldwide, markedly contributing to biological progress. The aim of this study was to identify new markers linked to candidate genes determining grain yield. Next-generation sequencing, gene association, and physical mapping were used to identify markers. An additional goal was to also optimize diagnostic procedures to identify molecular markers on reference materials. As a result of the conducted research, 19 SNP markers significantly associated with yield structure traits in maize were identified. Five of these markers (28629, 28625, 28640, 28649, and 29294) are located within genes that can be considered candidate genes associated with yield traits. For two markers (28639 and 29294), different amplification products were obtained on the electrophorograms. For marker 28629, a specific product of 189 bp was observed for genotypes 1, 4, and 10. For marker 29294, a specific product of 189 bp was observed for genotypes 1 and 10. Both markers can be used for the preliminary selection of well-yielding genotypes.

The Dissection of Nitrogen Response Traits Using Drone Phenotyping and Dynamic Phenotypic Analysis to Explore N Responsiveness and Associated Genetic Loci in Wheat

Inefficient nitrogen (N) utilization in agricultural production has led to many negative impacts such as excessive use of N fertilizers, redundant plant growth, greenhouse gases, long-lasting toxicity in ecosystem, and even effect on human health, indicating the importance to optimize N applications in cropping systems. Here, we present a multiseasonal study that focused on measuring phenotypic changes in wheat plants when they were responding to different N treatments under field conditions. Powered by drone-based aerial phenotyping and the AirMeasurer platform, we first quantified 6 N response-related traits as targets using plot-based morphological, spectral, and textural signals collected from 54 winter wheat varieties. Then, we developed dynamic phenotypic analysis using curve fitting to establish profile curves of the traits during the season, which enabled us to compute static phenotypes at key growth stages and dynamic phenotypes (i.e., phenotypic changes) during N response. After that, we combine 12 yield production and N-utilization indices manually measured to produce N efficiency comprehensive scores (NECS), based on which we classified the varieties into 4 N responsiveness (i.e., N-dependent yield increase) groups. The NECS ranking facilitated us to establish a tailored machine learning model for N responsiveness-related varietal classification just using N-response phenotypes with high accuracies. Finally, we employed the Wheat55K SNP Array to map single-nucleotide polymorphisms using N response-related static and dynamic phenotypes, helping us explore genetic components underlying N responsiveness in wheat. In summary, we believe that our work demonstrates valuable advances in N response-related plant research, which could have major implications for improving N sustainability in wheat breeding and production.

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.

Meta-QTL s and haplotypes for efficient zinc biofortification of rice

Biofortification of rice with improved grain zinc (Zn) content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.

The Triticeae CBF Gene Cluster-To Frost Resistance and Beyond

The pivotal role of CBF/DREB1 transcriptional factors in Triticeae crops involved in the abiotic stress response has been highlighted. The CBFs represent an important hub in the ICE-CBF-COR pathway, which is one of the most relevant mechanisms capable of activating the adaptive response to cold and drought in wheat, barley, and rye. Understanding the intricate mechanisms and regulation of the cluster of CBF genes harbored by the homoeologous chromosome group 5 entails significant potential for the genetic improvement of small grain cereals. Triticeae crops seem to share common mechanisms characterized, however, by some peculiar aspects of the response to stress, highlighting a combined landscape of single-nucleotide variants and copy number variation involving CBF members of subgroup IV. Moreover, while chromosome 5 ploidy appears to confer species-specific levels of resistance, an important involvement of the ICE factor might explain the greater tolerance of rye. By unraveling the genetic basis of abiotic stress tolerance, researchers can develop resilient varieties better equipped to withstand extreme environmental conditions. Hence, advancing our knowledge of CBFs and their interactions represents a promising avenue for improving crop resilience and food security.

Deciphering the evolution and complexity of wheat germplasm from a genomic perspective

Bread wheat provides an essential fraction of the daily calorific intake for humanity. Due to its huge and complex genome, progress in studying on the wheat genome is substantially trailed behind those of the other two major crops, rice and maize, for at least a decade. With rapid advances in genome assembling and reduced cost of high-throughput sequencing, emerging de novo genome assemblies of wheat and whole-genome sequencing data are leading to a paradigm shift in wheat research. Here, we review recent progress in dissecting the complex genome and germplasm evolution of wheat since the release of the first high-quality wheat genome. New insights have been gained in the evolution of wheat germplasm during domestication and modern breeding progress, genomic variations at multiple scales contributing to the diversity of wheat germplasm, and complex transcriptional and epigenetic regulations of functional genes in polyploid wheat. Genomics databases and bioinformatics tools meeting the urgent needs of wheat genomics research are also summarized. The ever-increasing omics data, along with advanced tools and well-structured databases, are expected to accelerate deciphering the germplasm and gene resources in wheat for future breeding advances.

Lifting of the 1,000 wheat exome project SNPs from Triticum aestivum cv. Chinese Spring assembly RefSeq v1.0 to RefSeq v2.1

OBJECTIVE

The 1,000 wheat exome project captured the single nucleotide variants in the coding regions of a diverse set of 890 wheat accessions to analyse the contribution of introgression to adaptation of wheat. However, this highly useful single nucleotide polymorphism (SNP) dataset is based on RefSeq v1.0 of the International Wheat Genome Sequencing Consortium (IWGSC) assembly of the bread wheat genome of Chinese Spring. This reference sequence has recently been updated using optical maps and long-read sequencing to produce the improved RefSeq v2.1. Our objective was to develop a reliable high-density SNP dataset positioned onto RefSeq v2.1 because it is the current standard reference sequence used by wheat researchers.

RESULTS

The 3,039,822 SNPs originally positioned on RefSeq v1.0 were projected to v2.1 using Liftoff with four different flanking regions, and 2,946,536 SNPs were consistently lifted to the same location irrespective of the flanking region lengths. Of these, 2,799,166 were located on the '+' ve strand. The distribution of the SNPs across the 21 chromosomes on RefSeq v2.1 was similar to that of RefSeq v1.0. Among the SNPs that were based on unanchored scaffolds in RefSeq v1.0, 11,938 were projected to one of the 21 pseudomolecules in the upgraded assembly. This SNP dataset constitutes a much-needed standardized resource for the wheat research community.

CropQuant-Air: an AI-powered system to enable phenotypic analysis of yield- and performance-related traits using wheat canopy imagery collected by low-cost drones

As one of the most consumed stable foods around the world, wheat plays a crucial role in ensuring global food security. The ability to quantify key yield components under complex field conditions can help breeders and researchers assess wheat's yield performance effectively. Nevertheless, it is still challenging to conduct large-scale phenotyping to analyse canopy-level wheat spikes and relevant performance traits, in the field and in an automated manner. Here, we present CropQuant-Air, an AI-powered software system that combines state-of-the-art deep learning (DL) models and image processing algorithms to enable the detection of wheat spikes and phenotypic analysis using wheat canopy images acquired by low-cost drones. The system includes the YOLACT-Plot model for plot segmentation, an optimised YOLOv7 model for quantifying the spike number per m² (SNpM²) trait, and performance-related trait analysis using spectral and texture features at the canopy level. Besides using our labelled dataset for model training, we also employed the Global Wheat Head Detection dataset to incorporate varietal features into the DL models, facilitating us to perform reliable yield-based analysis from hundreds of varieties selected from main wheat production regions in China. Finally, we employed the SNpM² and performance traits to develop a yield classification model using the Extreme Gradient Boosting (XGBoost) ensemble and obtained significant positive correlations between the computational analysis results and manual scoring, indicating the reliability of CropQuant-Air. To ensure that our work could reach wider researchers, we created a graphical user interface for CropQuant-Air, so that non-expert users could readily use our work. We believe that our work represents valuable advances in yield-based field phenotyping and phenotypic analysis, providing useful and reliable toolkits to enable breeders, researchers, growers, and farmers to assess crop-yield performance in a cost-effective approach.

Insights into the Transcriptomics of Crop Wild Relatives to Unravel the Salinity Stress Adaptive Mechanisms

The narrow genomic diversity of modern cultivars is a major bottleneck for enhancing the crop's salinity stress tolerance. The close relatives of modern cultivated plants, crop wild relatives (CWRs), can be a promising and sustainable resource to broaden the diversity of crops. Advances in transcriptomic technologies have revealed the untapped genetic diversity of CWRs that represents a practical gene pool for improving the plant's adaptability to salt stress. Thus, the present study emphasizes the transcriptomics of CWRs for salinity stress tolerance. In this review, the impacts of salt stress on the plant's physiological processes and development are overviewed, and the transcription factors (TFs) regulation of salinity stress tolerance is investigated. In addition to the molecular regulation, a brief discussion on the phytomorphological adaptation of plants under saline environments is provided. The study further highlights the availability and use of transcriptomic resources of CWR and their contribution to pangenome construction. Moreover, the utilization of CWRs' genetic resources in the molecular breeding of crops for salinity stress tolerance is explored. Several studies have shown that cytoplasmic components such as calcium and kinases, and ion transporter genes such as Salt Overly Sensitive 1 (SOS1) and High-affinity Potassium Transporters (HKTs) are involved in the signaling of salt stress, and in mediating the distribution of excess Na⁺ ions within the plant cells. Recent comparative analyses of transcriptomic profiling through RNA sequencing (RNA-Seq) between the crops and their wild relatives have unraveled several TFs, stress-responsive genes, and regulatory proteins for generating salinity stress tolerance. This review specifies that the use of CWRs transcriptomics in combination with modern breeding experimental approaches such as genomic editing, de novo domestication, and speed breeding can accelerate the CWRs utilization in the breeding programs for enhancing the crop's adaptability to saline conditions. The transcriptomic approaches optimize the crop genomes with the accumulation of favorable alleles that will be indispensable for designing salt-resilient crops.

Validation of genes affecting rice mesocotyl length through candidate association analysis and identification of the superior haplotypes

Mesocotyl is an essential organ of rice for pushing buds out of soil and plays a crucial role in seeding emergence and development in direct-seeding. Thus, identify the loci associated with mesocotyl length (ML) could accelerate breeding progresses for direct-seeding cultivation. Mesocotyl elongation was mainly regulated by plant hormones. Although several regions and candidate genes governing ML have been reported, the effects of them in diverse breeding populations were still indistinct. In this study, 281 genes related to plant hormones at the genomic regions associated with ML were selected and evaluated by single-locus mixed linear model (SL-MLM) and multi-locus random-SNP-effect mixed linear model (mr-MLM) in two breeding panels (Trop and Indx) originated from the 3K re-sequence project. Furthermore, superior haplotypes with longer mesocotyl were also identified for marker assisted selection (MAS) breeding. Totally, LOC_Os02g17680 (explained 7.1-8.9% phenotypic variations), LOC_Os04g56950 (8.0%), LOC_Os07g24190 (9.3%) and LOC_Os12g12720 (5.6-8.0%) were identified significantly associated with ML in Trop panel, whereas LOC_Os02g17680 (6.5-7.4%), LOC_Os04g56950 (5.5%), LOC_Os06g24850 (4.8%) and LOC_Os07g40240 (4.8-7.1%) were detected in Indx panel. Among these, LOC_Os02g17680 and LOC_Os04g56950 were identified in both panels. Haplotype analysis for the six significant genes indicated that haplotype distribution of the same gene varies at Trop and Indx panels. Totally, 8 (LOC_Os02g17680-Hap1 and Hap2, LOC_Os04g56950-Hap1, Hap2 and Hap8, LOC_Os07g24190-Hap3, LOC_Os12g12720-Hap3 and Hap6) and six superior haplotypes (LOC_Os02g17680-Hap2, Hap5 and Hap7, LOC_Os04g56950-Hap4, LOC_Os06g24850-Hap2 and LOC_Os07g40240-Hap3) with higher ML were identified in Trop and Indx panels, respectively. In addition, significant additive effects for ML with more superior haplotypes were identified in both panels. Overall, the 6 significantly associated genes and their superior haplotypes could be used to enhancing ML through MAS breeding and further promote direct-seedling cultivation.

Genetic resources and breeding of maize for Striga resistance: a review

The potential yield of maize (Zea mays L.) and other major crops is curtailed by several biotic, abiotic, and socio-economic constraints. Parasitic weeds, Striga spp., are major constraints to cereal and legume crop production in sub-Saharan Africa (SSA). Yield losses reaching 100% are reported in maize under severe Striga infestation. Breeding for Striga resistance has been shown to be the most economical, feasible, and sustainable approach for resource-poor farmers and for being environmentally friendly. Knowledge of the genetic and genomic resources and components of Striga resistance is vital to guide genetic analysis and precision breeding of maize varieties with desirable product profiles under Striga infestation. This review aims to present the genetic and genomic resources, research progress, and opportunities in the genetic analysis of Striga resistance and yield components in maize for breeding. The paper outlines the vital genetic resources of maize for Striga resistance, including landraces, wild relatives, mutants, and synthetic varieties, followed by breeding technologies and genomic resources. Integrating conventional breeding, mutation breeding, and genomic-assisted breeding [i.e., marker-assisted selection, quantitative trait loci (QTL) analysis, next-generation sequencing, and genome editing] will enhance genetic gains in Striga resistance breeding programs. This review may guide new variety designs for Striga-resistance and desirable product profiles in maize.

Fast integration and accumulation of beneficial breeding alleles through an AB-NAMIC strategy in wheat

Wheat (Triticum aestivum) is among the most important staple crops for safeguarding the food security of the growing world population. To bridge the gap between genebank diversity and breeding programs, we developed an advanced backcross-nested association mapping plus inter-crossed population (AB-NAMIC) by crossing three popular wheat cultivars as recurrent founders to 20 germplasm lines from a mini core collection. Selective backcrossing combined with selection against undesirable traits and extensive crossing within and between sub-populations created new opportunities to detect unknown genes and increase the frequency of beneficial alleles in the AB-NAMIC population. We performed phenotyping of 590 AB-NAMIC lines and a natural panel of 476 cultivars for six consecutive growing seasons and genotyped these 1066 lines with a 660K SNP array. Genome-wide association studies of both panels for plant development and yield traits demonstrated improved power to detect rare alleles and loci with medium genetic effects in AB-NAMIC. Notably, genome-wide association studies in AB-NAMIC detected the candidate gene TaSWEET6-7B (TraesCS7B03G1216700), which has high homology to the rice SWEET6b gene and exerts strong effects on adaptation and yield traits. The commercial release of two derived AB-NAMIC lines attests to its direct applicability in wheat improvement. Valuable information on genome-wide association study mapping, candidate genes, and their haplotypes for breeding traits are available through WheatGAB. Our research provides an excellent framework for fast-tracking exploration and accumulation of beneficial alleles stored in genebanks.

Heritage genetics for adaptation to marginal soils in barley

Future crops need to be sustainable in the face of climate change. Modern barley varieties have been bred for high productivity and quality; however, they have suffered considerable genetic erosion, losing crucial genetic diversity. This renders modern cultivars vulnerable to climate change and stressful environments. We highlight the potential to tailor crops to a specific environment by utilising diversity inherent in an adapted landrace population. Tapping into natural biodiversity, while incorporating information about local environmental and climatic conditions, allows targeting of key traits and genotypes, enabling crop production in marginal soils. We outline future directions for the utilisation of genetic resources maintained in landrace collections to support sustainable agriculture through germplasm development via the use of genomics technologies and big data.

Novel insights into maize (Zea mays) development and organogenesis for agricultural optimization

In maize, intrinsic hormone activities and sap fluxes facilitate organogenesis patterning and plant holistic development; these hormone movements should be a primary focus of developmental biology and agricultural optimization strategies. Maize (Zea mays) is an important crop plant with distinctive life history characteristics and structural features. Genetic studies have extended our knowledge of maize developmental processes, genetics, and molecular ecophysiology. In this review, the classical life cycle and life history strategies of maize are analyzed to identify spatiotemporal organogenesis properties and develop a definitive understanding of maize development. The actions of genes and hormones involved in maize organogenesis and sex determination, along with potential molecular mechanisms, are investigated, with findings suggesting central roles of auxin and cytokinins in regulating maize holistic development. Furthermore, investigation of morphological and structural characteristics of maize, particularly node ubiquity and the alternate attachment pattern of lateral organs, yields a novel regulatory model suggesting that maize organ initiation and subsequent development are derived from the stimulation and interaction of auxin and cytokinin fluxes. Propositions that hormone activities and sap flow pathways control organogenesis are thoroughly explored, and initiation and development processes of distinctive maize organs are discussed. Analysis of physiological factors driving hormone and sap movement implicates cues of whole-plant activity for hormone and sap fluxes to stimulate maize inflorescence initiation and organ identity determination. The physiological origins and biogenetic mechanisms underlying maize floral sex determination occurring at the tassel and ear spikelet are thoroughly investigated. The comprehensive outline of maize development and morphogenetic physiology developed in this review will enable farmers to optimize field management and will provide a reference for de novo crop domestication and germplasm improvement using genome editing biotechnologies, promoting agricultural optimization.

IGTCM: An integrative genome database of traditional Chinese medicine plants

Fully understanding traditional Chinese medicines (TCMs) is still challenging because of the extreme complexity of their chemical components and mechanisms of action. The TCM Plant Genome Project aimed to obtain genetic information, determine gene functions, discover regulatory networks of herbal species, and elucidate the molecular mechanisms involved in the disease prevention and treatment, thereby accelerating the modernization of TCMs. A comprehensive database that contains TCM-related information will provide a vital resource. Here, we present an integrative genome database of TCM plants (IGTCM) that contains 14,711,220 records of 83 annotated TCM-related herb genomes, including 3,610,350 genes, 3,534,314 proteins and corresponding coding sequences, and 4,032,242 RNAs, as well as 1033 non-redundant component records for 68 herbs, downloaded and integrated from the GenBank and RefSeq databases. For minimal interconnectivity, each gene, protein, and component was annotated using the eggNOG-mapper tool and Kyoto Encyclopedia of Genes and Genomes database to acquire pathway information and enzyme classifications. These features can be linked across several species and different components. The IGTCM database also provides visualization and sequence similarity search tools for data analyses. These annotated herb genome sequences in IGTCM database are a necessary resource for systematically exploring genes related to the biosynthesis of compounds that have significant medicinal activities and excellent agronomic traits that can be used to improve TCM-related varieties through molecular breeding. It also provides valuable data and tools for future research on drug discovery and the protection and rational use of TCM plant resources. The IGTCM database is freely available at http://yeyn.group:96/.

Focusing the GWAS Lens on days to flower using latent variable phenotypes derived from global multienvironment trials

Adaptation constraints within crop species have resulted in limited genetic diversity in some breeding programs and areas where new crops have been introduced, for example, for lentil (Lens culinaris Medik.) in North America. An improved understanding of the underlying genetics involved in phenology-related traits is valuable knowledge to aid breeders in overcoming limitations associated with unadapted germplasm and expanding their genetic diversity by introducing new, exotic material. We used a large, 18 site-year, multienvironment dataset phenotyped for phenology-related traits across nine locations and over 3 yr along with accompanying latent variable phenotypes derived from a photothermal model and principal component analysis (PCA) of days from sowing to flower (DTF) data for a lentil diversity panel (324 accessions), which has also been genotyped with an exome capture array. Genome-wide association studies (GWAS) on DTF across multiple environments helped confirm associations with known flowering-time genes and identify new quantitative trait loci (QTL), which may contain previously unknown flowering time genes. Additionally, the use of latent variable phenotypes, which can incorporate environmental data such as temperature and photoperiod as both GWAS traits and as covariates, strengthened associations, revealed additional hidden associations, and alluded to potential roles of the associated QTL. Our approach can be replicated with other crop species, and the results from our GWAS serve as a resource for further exploration into the complex nature of phenology-related traits across the major growing environments for cultivated lentil.

Molecular prospective on the wheat grain development

Wheat grain development is an important biological process to determine grain yield and quality, which is controlled by the interplay of genetic, epigenetic, and environmental factors. Wheat grain development has been extensively characterized at the phenotypic and genetic levels. The advent of innovative molecular technologies allows us to characterize genes, proteins, and regulatory factors involved in wheat grain development, which have enhanced our understanding of the wheat seed development process. However, wheat is an allohexaploid with a large genome size, the molecular mechanisms underlying the wheat grain development have not been well understood as those in diploids. Understanding grain development, and how it is regulated, is of fundamental importance for improving grain yield and quality through conventional breeding or genetic engineering. Herein, we review the current discoveries on the molecular mechanisms underlying wheat grain development. Notably, only a handful of genes that control wheat grain development have, thus far, been well characterized, their interplay underlying the grain development remains elusive. The synergistic network-integrated genomics and epigenetics underlying wheat grain development and how the subgenome divergence dynamically and precisely regulates wheat grain development are unknown.

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.

Integrating linkage mapping and comparative transcriptome analysis for discovering candidate genes associated with salt tolerance in rice

Salinity is one of the most widespread abiotic stresses affecting rice productivity worldwide. Understanding the genetic basis of salt tolerance is key for breeding salt-tolerant rice varieties. Numerous QTLs have been identified to help dissect rice salt-tolerance genetic mechanisms, yet only rare genes located in significant QTLs have been thoroughly studied or fine-mapped. Here, a combination of linkage mapping and transcriptome profiling analysis was used to identify salt tolerance-related functional candidate genes underlying stable QTLs. A recombinant inbred line (RIL) population derived from a cross between Jileng 1 (salt-sensitive) and Milyang 23 (salt-tolerant) was constructed. Subsequently, a high-density genetic map was constructed by using 2921 recombination bin markers developed from whole genome resequencing. A total of twelve QTLs controlling the standard evaluation score under salt stress were identified by linkage analysis and distributed on chromosomes 2, 3, 4, 6, 8 and 11. Notably, five QTL intervals were detected as environmentally stable QTLs in this study, and their functions were verified by comparative transcriptome analysis. By comparing the transcriptome profiles of the two parents and two bulks, we found 551 salt stress-specific differentially expressed genes. Among them, fifteen DEGs located in stable QTL intervals were considered promising candidate genes for salt tolerance. According to gene annotations, the gene OsRCI2-8(Os06g0184800) was the most promising, as it is known to be associated with salt stress, and its differential expression between the tolerant and sensitive RIL bulks highlights its important role in salt stress response pathways. Our findings provide five stable salt tolerance-related QTLs and one promising candidate gene, which will facilitate breeding for improved salt tolerance in rice varieties and promote the exploration of salt stress tolerance mechanisms in rice.

Pan-3D genome analysis reveals structural and functional differentiation of soybean genomes

BACKGROUND

High-order chromatin structure plays important roles in gene regulation. However, the diversity of the three-dimensional (3D) genome across plant accessions are seldom reported.

RESULTS

Here, we perform the pan-3D genome analysis using Hi-C sequencing data from 27 soybean accessions and comprehensively investigate the relationships between 3D genomic variations and structural variations (SVs) as well as gene expression. We find that intersection regions between A/B compartments largely contribute to compartment divergence. Topologically associating domain (TAD) boundaries in A compartments exhibit significantly higher density compared to those in B compartments. Pan-3D genome analysis shows that core TAD boundaries have the highest transcription start site (TSS) density and lowest GC content and repeat percentage. Further investigation shows that non-long terminal repeat (non-LTR) retrotransposons play important roles in maintaining TAD boundaries, while Gypsy elements and satellite repeats are associated with private TAD boundaries. Moreover, presence and absence variation (PAV) is found to be the major contributor to 3D genome variations. Nevertheless, approximately 55% of 3D genome variations are not associated with obvious genetic variations, and half of them affect the flanking gene expression. In addition, we find that the 3D genome may also undergo selection during soybean domestication.

CONCLUSION

Our study sheds light on the role of 3D genomes in plant genetic diversity and provides a valuable resource for studying gene regulation and genome evolution.

The Pyramiding of Elite Allelic Genes Related to Grain Number Increases Grain Number per Panicle Using the Recombinant Lines Derived from Indica-japonica Cross in Rice

Indica(xian)-japonica(geng) hybrid rice has many heterosis traits that can improve rice yield. However, the traditional hybrid technology will struggle to meet future needs for the development of higher-yield rice. Available genomics resources can be used to efficiently understand the gene-trait association trait for rice breeding. Based on the previously constructed high-density genetic map of 272 high-generation recombinant inbred lines (RILs) originating from the cross of Luohui 9 (indica, as female) and RPY geng (japonica, as male) and high-quality genomes of parents, here, we further explore the genetic basis for an important complex trait: possible causes of grain number per panicle (GNPP). A total of 20 genes related to grains number per panicle (GNPP) with the differences of protein amino acid between LH9 and RPY were used to analyze genotype combinations, and PCA results showed a combination of PLY1, LAX1, DTH8 and OSH1 from the RPY geng with PYL4, SP1, DST and GNP1 from Luohui 9 increases GNPP. In addition, we also found that the combination of LAX1-T2 and GNP1-T3 had the most significant increase in GNPP. Notably, Molecular Breeding Knowledgebase (MBK) showed a few aggregated rice cultivars, LAX1-T2 and GNP1-T3, which may be a result of the natural geographic isolation between the two gene haplotypes. Therefore, we speculate that the pyramiding of japonica-type LAX-T2 with indica-type GNP1-T3 via hybridization can significantly improve rice yield by increasing GNPP.

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

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

Haplogenome assembly reveals structural variation in Eucalyptus interspecific hybrids

BACKGROUND

De novo phased (haplo)genome assembly using long-read DNA sequencing data has improved the detection and characterization of structural variants (SVs) in plant and animal genomes. Able to span across haplotypes, long reads allow phased, haplogenome assembly in highly outbred organisms such as forest trees. Eucalyptus tree species and interspecific hybrids are the most widely planted hardwood trees with F1 hybrids of Eucalyptus grandis and E. urophylla forming the bulk of fast-growing pulpwood plantations in subtropical regions. The extent of structural variation and its effect on interspecific hybridization is unknown in these trees. As a first step towards elucidating the extent of structural variation between the genomes of E. grandis and E. urophylla, we sequenced and assembled the haplogenomes contained in an F1 hybrid of the two species.

FINDINGS

Using Nanopore sequencing and a trio-binning approach, we assembled the separate haplogenomes (566.7 Mb and 544.5 Mb) to 98.0% BUSCO completion. High-density SNP genetic linkage maps of both parents allowed scaffolding of 88.0% of the haplogenome contigs into 11 pseudo-chromosomes (scaffold N50 of 43.8 Mb and 42.5 Mb for the E. grandis and E. urophylla haplogenomes, respectively). We identify 48,729 SVs between the two haplogenomes providing the first detailed insight into genome structural rearrangement in these species. The two haplogenomes have similar gene content, 35,572 and 33,915 functionally annotated genes, of which 34.7% are contained in genome rearrangements.

CONCLUSIONS

Knowledge of SV and haplotype diversity in the two species will form the basis for understanding the genetic basis of hybrid superiority in these trees.

Multi-omics revolution to promote plant breeding efficiency

Crop production is the primary goal of agricultural activities, which is always taken into consideration. However, global agricultural systems are coming under increasing pressure from the rising food demand of the rapidly growing world population and changing climate. To address these issues, improving high-yield and climate-resilient related-traits in crop breeding is an effective strategy. In recent years, advances in omics techniques, including genomics, transcriptomics, proteomics, and metabolomics, paved the way for accelerating plant/crop breeding to cope with the changing climate and enhance food production. Optimized omics and phenotypic plasticity platform integration, exploited by evolving machine learning algorithms will aid in the development of biological interpretations for complex crop traits. The precise and progressive assembly of desire alleles using precise genome editing approaches and enhanced breeding strategies would enable future crops to excel in combating the changing climates. Furthermore, plant breeding and genetic engineering ensures an exclusive approach to developing nutrient sufficient and climate-resilient crops, the productivity of which can sustainably and adequately meet the world's food, nutrition, and energy needs. This review provides an overview of how the integration of omics approaches could be exploited to select crop varieties with desired traits.

Genome-Wide Characterization and Expression Profiling of the GRAS Gene Family in Salt and Alkali Stresses in Miscanthus sinensis

The GRAS family genes encode plant-specific transcription factors that play important roles in a diverse range of developmental processes and abiotic stress responses. However, the information of GRAS gene family in the bioenergy crop Miscanthus has not been available. Here, we report the genome-wide identification of GRAS gene family in Micanthus sinensis. A total of 123 MsGRAS genes were identified, which were divided into ten subfamilies based on the phylogenetic analysis. The co-linearity analysis revealed that 59 MsGRAS genes experienced segmental duplication, forming 35 paralogous pairs. The expression of six MsGRAS genes in responding to salt, alkali, and mixed salt-alkali stresses was analyzed by transcriptome and real-time quantitative PCR (RT-qPCR) assays. Furthermore, the role of MsGRAS60 in salt and alkali stress response was characterized in transgenic Arabidopsis. The MsGRAS60 overexpression lines exhibited hyposensitivity to abscisic acid (ABA) treatment and resulted in compromised tolerance to salt and alkali stresses, suggesting that MsGRAS60 is a negative regulator of salt and alkali tolerance via an ABA-dependent signaling pathway. The salt and alkali stress-inducible MsGRAS genes identified serve as candidates for the improvement of abiotic stress tolerance in Miscanthus.

Genome-wide analysis-based single nucleotide polymorphism marker sets to identify diverse genotypes in cabbage cultivars (Brassica oleracea var. capitata)

Plant variety protection is essential for breeders' rights granted by the International Union for the Protection of New Varieties of Plants. Distinctness, uniformity, and stability (DUS) are necessary for new variety registration; to this end, currently, morphological traits are examined, which is time-consuming and laborious. Molecular markers are more effective, accurate, and stable descriptors of DUS. Advancements in next-generation sequencing technology have facilitated genome-wide identification of single nucleotide polymorphisms. Here, we developed a core set of single nucleotide polymorphism markers to identify cabbage varieties and traits of test guidance through clustering using the Fluidigm assay, a high-throughput genotyping system. Core sets of 87, 24, and 10 markers are selected based on a genome-wide association-based approach. All core markers could identify 94 cabbage varieties and determine 17 DUS traits. A genotypes database was validated using the Fluidigm platform for variety identification, population structure analysis, cabbage breeding, and DUS testing for plant cultivar protection.

AirMeasurer: open-source software to quantify static and dynamic traits derived from multiseason aerial phenotyping to empower genetic mapping studies in rice

Low-altitude aerial imaging, an approach that can collect large-scale plant imagery, has grown in popularity recently. Amongst many phenotyping approaches, unmanned aerial vehicles (UAVs) possess unique advantages as a consequence of their mobility, flexibility and affordability. Nevertheless, how to extract biologically relevant information effectively has remained challenging. Here, we present AirMeasurer, an open-source and expandable platform that combines automated image analysis, machine learning and original algorithms to perform trait analysis using 2D/3D aerial imagery acquired by low-cost UAVs in rice (Oryza sativa) trials. We applied the platform to study hundreds of rice landraces and recombinant inbred lines at two sites, from 2019 to 2021. A range of static and dynamic traits were quantified, including crop height, canopy coverage, vegetative indices and their growth rates. After verifying the reliability of AirMeasurer-derived traits, we identified genetic variants associated with selected growth-related traits using genome-wide association study and quantitative trait loci mapping. We found that the AirMeasurer-derived traits had led to reliable loci, some matched with published work, and others helped us to explore new candidate genes. Hence, we believe that our work demonstrates valuable advances in aerial phenotyping and automated 2D/3D trait analysis, providing high-quality phenotypic information to empower genetic mapping for crop improvement.

Exploitation of epigenetic variation of crop wild relatives for crop improvement and agrobiodiversity preservation

Crop wild relatives (CWRs) are recognized as the best potential source of traits for crop improvement. However, successful crop improvement using CWR relies on identifying variation in genes controlling desired traits in plant germplasms and subsequently incorporating them into cultivars. Epigenetic diversity may provide an additional layer of variation within CWR and can contribute novel epialleles for key traits for crop improvement. There is emerging evidence that epigenetic variants of functional and/or agronomic importance exist in CWR gene pools. This provides a rationale for the conservation of epigenotypes of interest, thus contributing to agrobiodiversity preservation through conservation and (epi)genetic monitoring. Concepts and techniques of classical and modern breeding should consider integrating recent progress in epigenetics, initially by identifying their association with phenotypic variations and then by assessing their heritability and stability in subsequent generations. New tools available for epigenomic analysis offer the opportunity to capture epigenetic variation and integrate it into advanced (epi)breeding programmes. Advances in -omics have provided new insights into the sources and inheritance of epigenetic variation and enabled the efficient introduction of epi-traits from CWR into crops using epigenetic molecular markers, such as epiQTLs.

Pathways to sustainable land use and food systems in Canada

Meeting global sustainability targets under the United Nations Sustainable Development Goals and the Paris Agreement requires paying attention to major land-use sectors such as forestry and agriculture. These sectors play a large role in national emissions, biodiversity conservation, and human well-being. There are numerous possible pathways to sustainability in these sectors and potential synergies and trade-offs along those pathways. This paper reports on the use of a model for Canada's land use to 2050 to assess three different pathways (one based on current trends and two with differing levels of ambition for meeting sustainability targets). This was done as part of a large international consortium, Food, Agriculture, Biodiversity, Land and Energy (FABLE), which allows for incorporating international trade in meeting both national and global sustainability targets. The results show not only the importance of increasingly stringent policies in meeting the targets, but also the role that population and consumption (e.g., diets) play in meeting the targets. Both the medium and high ambition sustainability pathways can drastically reduce greenhouse gas emissions while protecting forestland.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11625-022-01213-z.

Alteration of synonymous codon usage bias accompanies polyploidization in wheat

The diploidization of polyploid genomes is accompanied by genomic variation, including synonymous nucleotide substitutions that may lead to synonymous codon usage bias (SCUB). SCUB can mirror the evolutionary specialization of plants, but its effect on the formation of polyploidies is not well documented. We explored this issue here with hexaploid wheat and its progenitors. Synonymous codons (SCs) ending in either cytosine (NNC) or guanidine (NNG) were more frequent than those ending in either adenosine (NNA) or thymine (NNT), and the preference for NNC/G codons followed the increase in genome ploidy. The ratios between NNC/G and NNA/T codons gradually decreased in genes with more introns, and the difference in these ratios between wheat and its progenitors diminished with increasing ploidy. SCUB frequencies were heterogeneous among exons, and the bias preferred to NNA/T in more internal exons, especially for genes with more exons; while the preference did not appear to associate with ploidy. The SCUB alteration of the progenitors was different during the formation of hexaploid wheat, so that SCUB was the homogeneous among A, B and D subgenomes. DNA methylation-mediated conversion from cytosine to thymine weakened following the increase of genome ploidy, coinciding with the stronger bias for NNC/G SCs in the genome as a function of ploidy, suggesting that SCUB contribute to the epigenetic variation in hexaploid wheat. The patterns in SCUB mirrored the formation of hexaploid wheat, which provides new insight into genome shock-induced genetic variation during polyploidization. SCs representing non-neutral synonymous mutations can be used for genetic dissection and improvement of agricultural traits of wheat and other polyploidies.

The phytotherapeutic potential of commercial South African medicinal plants: current knowledge and future prospects

South Africa, a country considered affluent in nature, ranks third in global biodiversity and encompasses approximately 9% of higher plants on planet Earth. Many indigenous plants have been utilised as herbal medicine, proving successful in treating numerous ailments. From the common cold to pandemic maladies such as COVID-19 in the 21st century and the treatment of incurable diseases, South African inhabitants have found great promise in the healing properties of these plants. Phytomedicine is a rapidly evolving topic, with in-depth bioactive composition analysis, identifying therapeutic action mechanisms, and disease prevention. While we are now poised to take advantage of nature’s medicine cabinet with greater scientific vigour, it remains critical that these practises are done with caution. Overharvesting significantly impacts biodiversity and cultivation practices amidst the beautiful nature of these nutraceuticals. This book chapter focuses on the therapeutic potential of commonly used South African medicinal plants, their ethnopharmacological properties, and how we can conserve this treasure cove we call home for future generations.

Improved pea reference genome and pan-genome highlight genomic features and evolutionary characteristics

Complete and accurate reference genomes and annotations provide fundamental resources for functional genomics and crop breeding. Here we report a de novo assembly and annotation of a pea cultivar ZW6 with contig N50 of 8.98 Mb, which features a 243-fold increase in contig length and evident improvements in the continuity and quality of sequence in complex repeat regions compared with the existing one. Genome diversity of 118 cultivated and wild pea demonstrated that Pisum abyssinicum is a separate species different from P. fulvum and P. sativum within Pisum. Quantitative trait locus analyses uncovered two known Mendel's genes related to stem length (Le/le) and seed shape (R/r) as well as some candidate genes for pod form studied by Mendel. A pan-genome of 116 pea accessions was constructed, and pan-genes preferred in P. abyssinicum and P. fulvum showed distinct functional enrichment, indicating the potential value of them as pea breeding resources in the future.

TaNAC020 homoeologous genes are associated with higher thousand kernel weight and kernel length in Chinese wheat

NAC proteins constitute one of the largest plant-specific transcription factor (TF) families and play significant roles in plant growth and development. In the present study, three TaNAC020 homoeologous genes located on chromosomes 7A, 7B, and 7D were isolated from wheat (Triticum aestivum L.). TaNAC020s were predominantly expressed in developing grains. The developed transgenic rice lines for TaNAC020-B showed higher starch density and lower amylose contents than those of the wild type (WT). Sequence polymorphism studies showed seven and eight SNPs in TaNAC020-A/B, making three and two haplotypes, respectively. No sequence polymorphism was identified in TaNAC020-D. Association analysis revealed that HAP-2 of TaNAC020-A and TaNAC020-B was the favored haplotype for higher thousand kernel weight and length. Geographic distribution and allelic frequency showed that our favored haplotype experienced strong selection in China, and likewise, diversity increased in TaNAC020s during wheat polyploidization. The results obtained in this study demonstrate that TaNAC020s positively influence starch synthesis and accumulation and are one of the key regulators of the kernel (seed) size and kernel number and have the potential for utilization in wheat breeding to improve grain yield. Molecular markers developed in this study stand instrumental in marker-assisted selection for genetic improvement and germplasm enhancement in wheat.

Genome-wide association study, haplotype analysis, and genomic prediction reveal the genetic basis of yield-related traits in soybean (Glycine max L.)

Identifying the genetic components underlying yield-related traits in soybean is crucial for improving its production and productivity. Here, 211 soybean genotypes were evaluated across six environments for four yield-related traits, including seed yield per plant (SYP), number of pods per plant number of seeds per plant and 100-seed weight (HSW). Genome-wide association study (GWAS) and genomic prediction (GP) analyses were performed using 12,617 single nucleotide polymorphism markers from NJAU 355K SoySNP Array. A total of 57 SNPs were significantly associated with four traits across six environments and a combined environment using five Genome-wide association study models. Out of these, six significant SNPs were consistently identified in more than three environments using multiple GWAS models. The genomic regions (±670 kb) flanking these six consistent SNPs were considered stable QTL regions. Gene annotation and in silico expression analysis revealed 15 putative genes underlying the stable QTLs that might regulate soybean yield. Haplotype analysis using six significant SNPs revealed various allelic combinations regulating diverse phenotypes for the studied traits. Furthermore, the GP analysis revealed that accurate breeding values for the studied soybean traits is attainable at an earlier generation. Our study paved the way for increasing soybean yield performance within a short breeding cycle.

Harnessing adult-plant resistance genes to deploy durable disease resistance in crops

Adult-plant resistance (APR) is a type of genetic resistance in cereals that is effective during the later growth stages and can protect plants from a range of disease-causing pathogens. Our understanding of the functions of APR-associated genes stems from the well-studied wheat-rust pathosystem. Genes conferring APR can offer pathogen-specific resistance or multi-pathogen resistance, whereby resistance is activated following a molecular recognition event. The breeding community prefers APR to other types of resistance because it offers broad-spectrum protection that has proven to be more durable. In practice, however, deployment of new cultivars incorporating APR is challenging because there is a lack of well-characterised APRs in elite germplasm and multiple loci must be combined to achieve high levels of resistance. Genebanks provide an excellent source of genetic diversity that can be used to diversify resistance factors, but introgression of novel alleles into elite germplasm is a lengthy and challenging process. To overcome this bottleneck, new tools in breeding for resistance must be integrated to fast-track the discovery, introgression and pyramiding of APR genes. This review highlights recent advances in understanding the functions of APR genes in the well-studied wheat-rust pathosystem, the opportunities to adopt APR genes in other crops and the technology that can speed up the utilisation of new sources of APR in genebank accessions.

Identification of superior haplotypes in a diverse natural population for breeding desirable plant height in soybean

KEY MESSAGE

Plant height of soybean is associated with a haplotype block on chromosome 19, which classified 211 soybean accessions into five distinct groups showing significant differences for the target trait. Genetic variation is pivotal for crop improvement. Natural populations are precious genetic resources. However, efficient strategies for the targeted utilization of these resources for quantitative traits, such as plant height (PH), are scarce. Being an important agronomic trait associated with soybean yield and quality, it is imperative to unravel the genetic mechanisms underlying PH in soybean. Here, a genome-wide association study (GWAS) was performed to identify single nucleotide polymorphisms (SNPs) significantly associated with PH in a natural population of 211 cultivated soybeans, which was genotyped with NJAU 355 K Soy SNP Array and evaluated across six environments. A total of 128 SNPs distributed across 17 chromosomes were found to be significantly associated with PH across six environments and a combined environment. Three significant SNPs were consistently identified in at least three environments on Chr.02 (AX-93958260), Chr.17 (AX-94154834), and Chr.19 (AX-93897200). Genomic regions of ~ 130 kb flanking these three consistent SNPs were considered as stable QTLs, which included 169 genes. Of these, 22 genes (including Dt1) were prioritized and defined as putative candidates controlling PH. The genomic region flanking 12 most significant SNPs was in strong linkage disequilibrium (LD). These SNPs formed a single haplotype block containing five haplotypes for PH, namely Hap-A, Hap-B, Hap-C, Hap-D, and Hap-E. Deployment of such superior haplotypes in breeding programs will enable development of improved soybean varieties with desirable plant height.

Evaluation of an intelligent artificial climate chamber for high-throughput crop phenotyping in wheat

BACKGROUND

The superposition of COVID-19 and climate change has brought great challenges to global food security. As a major economic crop in the world, studying its phenotype to cultivate high-quality wheat varieties is an important way to increase grain yield. However, most of the existing phenotyping platforms have the disadvantages of high construction and maintenance costs, immobile and limited in use by climatic factors, while the traditional climate chambers lack phenotypic data acquisition, which makes crop phenotyping research and development difficult. Crop breeding progress is slow. At present, there is an urgent need to develop a low-cost, easy-to-promote, climate- and site-independent facility that combines the functions of crop cultivation and phenotype acquisition. We propose a movable cabin-type intelligent artificial climate chamber, and build an environmental control system, a crop phenotype monitoring system, and a crop phenotype acquisition system.

RESULT

We selected two wheat varieties with different early vigor to carry out the cultivation experiments and phenotype acquisition of wheat under different nitrogen fertilizer application rates in an intelligent artificial climate chamber. With the help of the crop phenotype acquisition system, images of wheat at the trefoil stage, pre-tillering stage, late tillering stage and jointing stage were collected, and then the phenotypic information including wheat leaf area, plant height, and canopy temperature were extracted by the crop type acquisition system. We compared systematic and manual measurements of crop phenotypes for wheat phenotypes. The results of the analysis showed that the systematic measurements of leaf area, plant height and canopy temperature of wheat in four growth periods were highly correlated with the artificial measurements. The correlation coefficient (r) is positive, and the determination coefficient (R²) is greater than 0.7156. The root mean square error (RSME) is less than 2.42. Among them, the crop phenotype-based collection system has the smallest measurement error for the phenotypic characteristics of wheat trefoil stage. The canopy temperature RSME is only 0.261. The systematic measurement values of wheat phenotypic characteristics were significantly positively correlated with the artificial measurement values, the fitting degree was good, and the errors were all within the acceptable range. The experiment showed that the phenotypic data obtained with the intelligent artificial climate chamber has high accuracy. We verified the feasibility of wheat cultivation and phenotype acquisition based on intelligent artificial climate chamber.

CONCLUSION

It is feasible to study wheat cultivation and canopy phenotype with the help of intelligent artificial climate chamber. Based on a variety of environmental monitoring sensors and environmental regulation equipment, the growth environment factors of crops can be adjusted. Based on high-precision mechanical transmission and multi-dimensional imaging sensors, crop images can be collected to extract crop phenotype information. Its use is not limited by environmental and climatic factors. Therefore, the intelligent artificial climate chamber is expected to be a powerful tool for breeders to develop excellent germplasm varieties.