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.

Exploring the role of FBXL fbxl gene family in Soybean: Implications for plant height and seed size regulation.

F-box proteins constitute a significant family in eukaryotes and, as a component of the Skp1p-cullin-F-box complex, are considered critical for cellular protein degradation and other biological processes in plants. Despite their importance, the functions of F-box proteins, particularly those with C-terminal leucine-rich repeat (LRR) domains, remain largely unknown in plants. Therefore, the present study conducted genome-wide identification and in silico characterization of F-BOX proteins with C-terminal LRR domains in soybean (Glycine max L.) (GmFBXLs). A total of 45 GmFBXLs were identified. The phylogenetic analysis showed that GmFBXLs could be subdivided into ten subgroups and exhibited a close relationship with those from Arabidopsis thaliana, Cicer aretineum, and Medicago trunculata. It was observed that most cis-regulatory elements in the promoter regions of GmFBXLs are involved in hormone signalling, stress responses, and developmental stages. In silico transcriptome data illustrated diverse expression patterns of the identified GmFBXLs across various tissues, such as shoot apical meristem, flower, green pods, leaves, nodules, and roots. Overexpressing (OE) GmFBXL12 in Tianlong No.1 cultivar resulted in a significant difference in seed size, number of pods, and number of seeds per plant, indicated a potential increase in yield compared to wild type. This study offers valuable perspectives into the role of FBXLs in soybean, serving as a foundation for future research. Additionally, the identified OE lines represent valuable genetic resources for enhancing seed-related traits in soybean.

Molecular and genetic insights into secondary metabolic regulation underlying insect-pest resistance in legumes.

Insect pests pose a major threat to agricultural production, resulting in significant economic losses for countries. A high infestation of insects in any given area can severely reduce crop yield and quality. This review examines the existing resources for managing insect pests and highlights alternative eco-friendly techniques to enhance insect pest resistance in legumes. Recently, the application of plant secondary metabolites has gained popularity in controlling insect attacks. Plant secondary metabolites encompass a wide range of compounds such as alkaloids, flavonoids, and terpenoids, which are often synthesized through intricate biosynthetic pathways. Classical methods of metabolic engineering involve manipulating key enzymes and regulatory genes to enhance or redirect the production of secondary metabolites in plants. Additionally, the role of genetic approaches, such as quantitative trait loci mapping, genome-wide association (GWAS) mapping, and metabolome-based GWAS in insect pest management is discussed, also, the role of precision breeding, such as genome editing technologies and RNA interference for identifying pest resistance and manipulating the genome to develop insect-resistant cultivars are explored, highlighting the positive contribution of plant secondary metabolites engineering-based resistance against insect pests. It is suggested that by understanding the genes responsible for beneficial metabolite compositions, future research might hold immense potential to shed more light on the molecular regulation of secondary metabolite biosynthesis, leading to advancements in insect-resistant traits in crop plants. In the future, the utilization of metabolic engineering and biotechnological methods may serve as an alternative means of producing biologically active, economically valuable, and medically significant compounds found in plant secondary metabolites, thereby addressing the challenge of limited availability.

Transcriptome profiling reveals major structural genes, transcription factors and biosynthetic pathways involved in leaf senescence and nitrogen remobilization in rainfed spring wheat under different nitrogen fertilization rates.

The present study was undertaken to profile transcriptional changes in flag leaves between anthesis and end of grain filling stages of rainfed spring wheat cultivar under varying nitrogen (N) application rates: 0 kg/ha (NN), 52.5 kg/ha (LN), and 210 kg/ha (HN). A total of 4485 and 4627 differentially expressed genes (DEGs) were detected in LN and HN, respectively. The differential application of N altered several pathways; including plant hormone signal transduction, mitogen-activated protein kinase signaling pathway-plant, photosynthesis, phenylpropanoid biosynthesis and ATP-binding cassette transporters. Jasmonic acid, abscisic acid, salicylic acid and brassinosteroid related genes promoted leaf senescence in NN or LN, whereas auxin, gibberellin acid and cytokinins genes inhibited leaf senescence in HN. Major transcription factors: auxin/indole-3-acetic acid (AUX/IAA), no apical meristem (NAC) and WRKY expressed higher in either HN or LN than NN. The DEGs, pathways and transcription factors provide valuable insight for manipulation of leaf senescence and N remobilization in wheat.

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.

Identification of major genomic regions for soybean seed weight by genome-wide association study.

The hundred-seed weight (HSW) is an important yield component and one of the principal breeding traits in soybean. More than 250 quantitative trait loci (QTL) for soybean HSW have been identified. However, most of them have a large genomic region or are environmentally sensitive, which provide limited information for improving the phenotype in marker-assisted selection (MAS) and identifying the candidate genes. Here, we utilized 281 soybean accessions with 58,112 single nucleotide polymorphisms (SNPs) to dissect the genetic basis of HSW in across years in the northern Shaanxi province of China through one single-locus (SL) and three multi-locus (ML) genome-wide association study (GWAS) models. As a result, one hundred and fifty-four SNPs were detected to be significantly associated with HSW in at least one environment via SL-GWAS model, and 27 of these 154 SNPs were detected in all (three) environments and located within 7 linkage disequilibrium (LD) block regions with the distance of each block ranged from 40 to 610 Kb. A total of 15 quantitative trait nucleotides (QTNs) were identified by three ML-GWAS models. Combined with the results of different GWAS models, the 7 LD block regions associated with HSW detected by SL-GWAS model could be verified directly or indirectly by the results of ML-GWAS models. Eleven candidate genes underlying the stable loci that may regulate seed weight in soybean were predicted. The significantly associated SNPs and the stable loci as well as predicted candidate genes may be of great importance for marker-assisted breeding, polymerization breeding, and gene discovery for HSW in soybean. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-022-01310-y.

CRISPR-Cas9 based stress tolerance: New hope for abiotic stress tolerance in chickpea (Cicer arietinum).

Plants are subjected to biotic and abiotic stresses regularly, which irreparably harm agricultural production. Eco-friendly and sustainable technology to deal with this challenge is to breed abiotic stress tolerant cultivars. To generate crop plants conferring resistance against stresses, conventional breeding was used in the past, but because of the complex heredity of abiotic stress tolerance traits, such techniques remain insufficient in making greater enhancement. Genome-engineering based on CRISPR-Cas9 (clustered regularly interspaced short palindromic repeats-CRISPR associated protein9) has shown enormous potential in developing climate-resilient cultivars. Likewise, the development of chickpea transgenic lines by knockout of 4CL and REV7 genes exhibits drought tolerance which establishes a foundation for future studies in chickpea. In addition, the CRISPR-Cas9 system can boost yield potential under abiotic stress situations by producing non-transgenic plants having the required characteristics. This review article discusses the validation of gene function based on the CRISPR-Cas9 for the development of abiotic stress-tolerant crop plants, emphasizing the chickpea to open the new ventures of generating abiotic stress-tolerant chickpea varieties.

Genome-wide association study uncovers major genetic loci associated with seed flooding tolerance in soybean.

BACKGROUND: Seed flooding stress is one of the threatening environmental stressors that adversely limits soybean at the germination stage across the globe. The knowledge on the genetic basis underlying seed-flooding tolerance is limited. Therefore, we performed a genome-wide association study (GWAS) using 34,718 single nucleotide polymorphism (SNPs) in a panel of 243 worldwide soybean collections to identify genetic loci linked to soybean seed flooding tolerance at the germination stage. RESULTS: In the present study, GWAS was performed with two contrasting models, Mixed Linear Model (MLM) and Multi-Locus Random-SNP-Effect Mixed Linear Model (mrMLM) to identify significant SNPs associated with electrical conductivity (EC), germination rate (GR), shoot length (ShL), and root length (RL) traits at germination stage in soybean. With MLM, a total of 20, 40, 4, and 9 SNPs associated with EC, GR, ShL and RL, respectively, whereas in the same order mrMLM detected 27, 17, 13, and 18 SNPs. Among these SNPs, two major SNPs, Gm_08_11971416, and Gm_08_46239716 were found to be consistently connected with seed-flooding tolerance related traits, namely EC and GR across two environments. We also detected two SNPs, Gm_05_1000479 and Gm_01_53535790 linked to ShL and RL, respectively. Based on Gene Ontology enrichment analysis, gene functional annotations, and protein-protein interaction network analysis, we predicted eight candidate genes and three hub genes within the regions of the four SNPs with Cis-elements in promoter regions which may be involved in seed-flooding tolerance in soybeans and these warrant further screening and functional validation. CONCLUSIONS: Our findings demonstrate that GWAS based on high-density SNP markers is an efficient approach to dissect the genetic basis of complex traits and identify candidate genes in soybean. The trait associated SNPs could be used for genetic improvement in soybean breeding programs. The candidate genes could help researchers better understand the molecular mechanisms underlying seed-flooding stress tolerance in soybean.

Exploring genetic architecture for pod-related traits in soybean using image-based phenotyping.

Mature pod color (PC) and pod size (PS) served as important characteristics are used in the soybean breeding programs. However, manual phenotyping of such complex traits is time-consuming, laborious, and expensive for breeders. Here, we collected pod images from two different populations, namely, a soybean association panel (SAP) consisting of 187 accessions and an inter-specific recombinant inbred line (RIL) population containing 284 RILs. An image-based phenotyping method was developed and used to extract the pod color- and size-related parameters from images. Genome-wide association study (GWAS) and linkage mapping were performed to decipher the genetic control of pod color- and size-related traits across 2 successive years. Both populations exhibited wide phenotypic variations and continuous distribution in pod color- and size-related traits, indicating quantitative polygenic inheritance of these traits. GWAS and linkage mapping approaches identified the two major quantitative trait loci (QTL) underlying the pod color parameters, i.e., qPC3 and qPC19, located to chromosomes 3 and 19, respectively, and 12 stable QTLs for pod size-related traits across nine chromosomes. Several genes residing within the genomic region of stable QTL were identified as potential candidates underlying these pod-related traits based on the gene annotation and expression profiling data. Our results provide the useful information for fine-mapping/map-based cloning of QTL and marker-assisted selection of elite varieties with desirable pod traits. Supplementary Information: The online version contains supplementary material available at 10.1007/s11032-021-01223-2.

Identification of quantitative trait nucleotides and candidate genes for soybean seed weight by multiple models of genome-wide association study.

BACKGROUND: Seed weight is a complex yield-related trait with a lot of quantitative trait loci (QTL) reported through linkage mapping studies. Integration of QTL from linkage mapping into breeding program is challenging due to numerous limitations, therefore, Genome-wide association study (GWAS) provides more precise location of QTL due to higher resolution and diverse genetic diversity in un-related individuals. RESULTS: The present study utilized 573 breeding lines population with 61,166 single nucleotide polymorphisms (SNPs) to identify quantitative trait nucleotides (QTNs) and candidate genes for seed weight in Chinese summer-sowing soybean. GWAS was conducted with two single-locus models (SLMs) and six multi-locus models (MLMs). Thirty-nine SNPs were detected by the two SLMs while 209 SNPs were detected by the six MLMs. In all, two hundred and thirty-one QTNs were found to be associated with seed weight in YHSBLP with various effects. Out of these, seventy SNPs were concurrently detected by both SLMs and MLMs on 8 chromosomes. Ninety-four QTNs co-localized with previously reported QTL/QTN by linkage/association mapping studies. A total of 36 candidate genes were predicted. Out of these candidate genes, four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 and Glyma19g28070) were identified by the integration of co-expression network. Among them, three were relatively expressed higher in the high HSW genotypes at R5 stage compared with low HSW genotypes except Glyma12g33280. Our results show that using more models especially MLMs are effective to find important QTNs, and the identified HSW QTNs/genes could be utilized in molecular breeding work for soybean seed weight and yield. CONCLUSION: Application of two single-locus plus six multi-locus models of GWAS identified 231 QTNs. Four hub genes (Glyma06g44510, Glyma08g06420, Glyma12g33280 & Glyma19g28070) detected via integration of co-expression network among the predicted candidate genes.

Diallel Analysis and Heritability of Grain Yield, Yield Components, and Maturity Traits in Cowpea (Vigna unguiculata (L.) Walp.).

Information on combining ability and reciprocal effects (REC) facilitates efficient utilization of genetic materials in a breeding program. This study was conducted (at the CSIR-Savanna Agricultural Research Institute, Ghana) to determine general combining ability (GCA) and specific combining ability (SCA), heritability, genetic advance, GCA, and SCA effects as well as the relationship between parents per se performance and progenies for yield components and maturity traits in cowpea. The test populations were derived using a 5 × 5 complete diallel cross of parents with different yield attributes and maturity durations. The results indicated that GCA was predominant for number of days to 90% pod maturity, plant height at maturity, and hundred-seed weight. This showed that genes with additive effects conditioned these traits. Padi-Tuya, Songotra, and IT86D-610 were identified as good general combiners for grain yield, while Sanzi-Nya was identified as a general combiner for developing extra-early duration cowpea varieties. Crosses Songotra × Sanzi-Nya, SARC-1-57-2 × IT86D-610, Songotra × SARC-1-57-2, and Padi-Tuya × Songotra were identified as good specific combiners for days to 50% flowering, pod length, pods per plant, pod yield, grain yield, and seeds per pod. The findings from this study provide useful information on the inheritance of early maturity and yield traits in cowpea. This can be exploited to develop high yielding and early maturing cowpea varieties as climate smart strategy to mitigate climate change via breeding methods such as pedigree selection and marker assisted backcrossing (MABC). Pedigree selection method is being used to develop varieties from the hybrid with high and significant SCA for grain yield, whereas the development of extra-early duration varieties via MABC with Sanzi-Nya (general combiner for earliness traits) as a donor parent is ongoing.

Genome-Wide Detection of Major and Epistatic Effect QTLs for Seed Protein and Oil Content in Soybean Under Multiple Environments Using High-Density Bin Map.

Seed protein and oil content are the two important traits determining the quality and value of soybean. Development of improved cultivars requires detailed understanding of the genetic basis underlying the trait of interest. However, it is prerequisite to have a high-density linkage map for precisely mapping genomic regions, and therefore the present study used high-density genetic map containing 2267 recombination bin markers distributed on 20 chromosomes and spanned 2453.79 cM with an average distance of 1.08 cM between markers using restriction-site-associated DNA sequencing (RAD-seq) approach. A recombinant inbred line (RIL) population of 104 lines derived from a cross between Linhefenqingdou and Meng 8206 cultivars was evaluated in six different environments to identify main- and epistatic-effect quantitative trait loci (QTLs)as well as their interaction with environments. A total of 44 main-effect QTLs for protein and oil content were found to be distributed on 17 chromosomes, and 15 novel QTL were identified for the first time. Out of these QTLs, four were major and stable QTLs, viz., qPro-7-1, qOil-8-3, qOil-10-2 and qOil-10-4, detected in at least two environments plus combined environment with R² values >10%. Within the physical intervals of these four QTLs, 111 candidate genes were screened for their direct or indirect involvement in seed protein and oil biosynthesis/metabolism processes based on gene ontology and annotation information. Based on RNA sequencing (RNA-seq) data analysis, 15 of the 111 genes were highly expressed during seed development stage and root nodules that might be considered as the potential candidate genes. Seven QTLs associated with protein and oil content exhibited significant additive and additive × environment interaction effects, and environment-independent QTLs revealed higher additive effects. Moreover, three digenic epistatic QTLs pairs were identified, and no main-effect QTLs showed epistasis. In conclusion, the use of a high-density map identified closely linked flanking markers, provided better understanding of genetic architecture and candidate gene information, and revealed the scope available for improvement of soybean quality through marker assisted selection (MAS).

Identification and Genetic Dissection of Resistance to Red Crown Rot Disease in a Diverse Soybean Germplasm Population.

Red crown rot (RCR) disease caused by Calonectria ilicicola negatively impacts soybean yield and quality. Unfortunately, the knowledge of the genetic architecture of RCR resistance in soybeans is limited. In this study, 299 diverse soybean accessions were used to explore their genetic diversity and resistance to RCR, and to mine for candidate genes via emergence rate (ER), survival rate (SR), and disease severity (DS) by a multi-locus random-SNP-effect mixed linear model of GWAS. All accessions had brown necrotic lesions on the primary root, with five genotypes identified as resistant. Nine single-nucleotide polymorphism (SNP) markers were detected to underlie RCR response (ER, SR, and DS). Two SNPs colocalized with at least two traits to form a haplotype block which possessed nine genes. Based on their annotation and the qRT-PCR, three genes, namely Glyma.08G074600, Glyma.08G074700, and Glyma.12G043600, are suggested to modulate soybean resistance to RCR. The findings from this study could serve as the foundation for breeding RCR-tolerant soybean varieties, and the candidate genes could be validated to deepen our understanding of soybean response to RCR.

Comparative Morpho-Physiological, Biochemical, and Gene Expressional Analyses Uncover Mechanisms of Waterlogging Tolerance in Two Soybean Introgression Lines.

Waterlogging is one of the key abiotic factors that severely impedes the growth and productivity of soybeans on a global scale. To develop soybean cultivars that are tolerant to waterlogging, it is a prerequisite to unravel the mechanisms governing soybean responses to waterlogging. Hence, we explored the morphological, physiological, biochemical, and transcriptional changes in two contrasting soybean introgression lines, A192 (waterlogging tolerant, WT) and A186 (waterlogging sensitive, WS), under waterlogging. In comparison to the WT line, waterlogging drastically decreased the root length (RL), shoot length (ShL), root fresh weight (RFW), shoot fresh weight (ShFW), root dry weight (RDW), and shoot dry weight (ShDW) of the WS line. Similarly, waterlogging inhibited soybean plant growth by suppressing the plant's photosynthetic capacity, enhancing oxidative damage from reactive oxygen species, and decreasing the chlorophyll content in the WS line but not in the WT line. To counteract the oxidative damage and lipid peroxidation, the WT line exhibited increased activity of antioxidant enzymes such as peroxidase (POD), superoxide dismutase (SOD), and catalase (CAT), as well as higher levels of proline content than the WS line. In addition, the expression of antioxidant enzyme genes (POD1, POD2, FeSOD, Cu/ZnSOD, CAT1, and CAT2) and ethylene-related genes (such as ACO1, ACO2, ACS1, and ACS2) were found to be up-regulated in WT line under waterlogging stress conditions. In contrast, these genes showed a down-regulation in their expression levels in the stressed WS line. The integration of morpho-physiological, biochemical, and gene expression analyses provide a comprehensive understanding of the responses of WT and WS lines to waterlogging conditions. These findings would be beneficial for the future development of soybean cultivars that can withstand waterlogging.

Genome-wide association study provides new insight into the underlying mechanism of drought tolerance during seed germination stage in soybean.

Drought is one of the major environmental issues that reduce crop yield. Seed germination is a crucial stage of plant development in all crop plants, including soybean. In soybean breeding, information about genetic mechanism of drought tolerance has great importance. However, at germination stage, there is relatively little knowledge on the genetic basis of soybean drought resistance. The objective of this work was to find the quantitative trait nucleotides (QTNs) linked to drought tolerance related three traits using a genome-wide association study (GWAS), viz., germination rate (GR), root length (RL), and whole seedling length (WSL), using germplasm population of 240 soybean PIs with 34,817 SNPs genotype data having MAF > 0.05. It was observed that heritability (H2) for GR, WSL, and RL across both environments (2020, and 2019) were high in the range of 0.76-0.99, showing that genetic factors play a vital role in drought tolerance as compared to environmental factors. A number of 23 and 27 QTNs were found to be linked to three traits using MLM and mrMLM, respectively. Three significant QTNs, qGR8-1, qWSL13-1, and qRL-8, were identified using both MLM and mrMLM methods among these QTNs. QTN8, located on chromosome 8 was consistently linked to two traits (GR and RL). The area (± 100 Kb) associated with this QTN was screened for drought tolerance based on gene annotation. Fifteen candidate genes were found by this screening. Based on the expression data, four candidate genes i.e. Glyma08g156800, Glyma08g160000, Glyma08g162700, and Glyma13g249600 were found to be linked to drought tolerance regulation in soybean. Hence, the current study provides evidence to understand the genetic constitution of drought tolerance during the germination stage and identified QTNs or genes could be utilized in molecular breeding to enhance the yield under drought stress.

DArTseq-based SNP markers reveal high genetic diversity among early generation fall armyworm tolerant maize inbred lines.

Diversity analysis using molecular markers serves as a powerful tool in unravelling the intricacies of inclusivity within various populations and is an initial step in the assessment of populations and the development of inbred lines for host plant resistance in maize. This study was conducted to assess the genetic diversity and population structure of 242 newly developed S3 inbred lines using 3,305 single nucleotide polymorphism (SNP) markers and to also assess the level of homozygosity achieved in each of the inbred lines. A total of 1,184 SNP markers were found highly informative, with a mean polymorphic information content (PIC) of 0.23. Gene diversity was high among the inbred lines, ranging from 0.04 to 0.50, with an average of 0.27. The residual heterozygosity of the 242 S3 inbred lines averaged 8.8%, indicating moderately low heterozygosity levels among the inbred lines. Eighty-four percent of the 58,322 pairwise kinship coefficients among the inbred lines were near zero (0.00-0.05), with only 0.3% of them above 0.50. These results revealed that many of the inbred lines were distantly related, but none were redundant, suggesting each inbred line had a unique genetic makeup with great potential to provide novel alleles for maize improvement. The admixture-based structure analysis, principal coordinate analysis, and neighbour-joining clustering were concordant in dividing the 242 inbred lines into three subgroups based on the pedigree and selection history of the inbred lines. These findings could guide the effective use of the newly developed inbred lines and their evaluation in quantitative genetics and molecular studies to identify candidate lines for breeding locally adapted fall armyworm tolerant varieties in Ghana and other countries in West and Central Africa.

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.

Widely untargeted metabolomic profiling unearths metabolites and pathways involved in leaf senescence and N remobilization in spring-cultivated wheat under different N regimes.

Progression of leaf senescence consists of both degenerative and nutrient recycling processes in crops including wheat. However, the levels of metabolites in flag leaves in spring-cultivated wheat, as well as biosynthetic pathways involved under different nitrogen fertilization regimes, are largely unknown. Therefore, the present study employed a widely untargeted metabolomic profiling strategy to identify metabolites and biosynthetic pathways that could be used in a wheat improvement program aimed at manipulating the rate and onset of senescence by handling spring wheat (Dingxi 38) flag leaves sampled from no-, low-, and high-nitrogen (N) conditions (designated Groups 1, 2, and 3, respectively) across three sampling times: anthesis, grain filling, and end grain filling stages. Through ultrahigh-performance liquid chromatography-tandem mass spectrometry, a total of 826 metabolites comprising 107 flavonoids, 51 phenol lipids, 37 fatty acyls, 37 organooxygen compounds, 31 steroids and steroid derivatives, 18 phenols, and several unknown compounds were detected. Upon the application of the stringent screening criteria for differentially accumulated metabolites (DAMs), 28 and 23 metabolites were differentially accumulated in Group 1_vs_Group 2 and Group 1_vs_Group 3, respectively. From these, 1-O-Caffeoylglucose, Rhoifolin, Eurycomalactone;Ingenol, 4-Methoxyphenyl beta-D-glucopyranoside, and Baldrinal were detected as core conserved DAMs among the three groups with all accumulated higher in Group 1 than in the other two groups. Kyoto Encyclopedia of Genes and Genomes pathway analysis revealed that tropane, piperidine, and pyridine alkaloid biosynthesis; acarbose and validamycin biosynthesis; lysine degradation; and biosynthesis of alkaloids derived from ornithine, lysine, and nicotinic acid pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 2, while flavone and flavonol as well as anthocyanins biosynthetic pathways were the most significantly (p < 0.05) enriched in Group 1_vs_Group 3. The results from this study provide a foundation for the manipulation of the onset and rate of leaf senescence and N remobilization in wheat.

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.