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Legumes are extremely valuable because of their high protein content and several other nutritional components. The major challenge lies in maintaining the quantity and quality of protein and other nutritional compounds in view of climate change conditions. The global need for plant-based proteins has increased the demand for seeds with a high protein content that includes essential amino acids. Genome-wide association studies (GWAS) have evolved as a standard approach in agricultural genetics for examining such intricate characters. Recent development in machine learning methods shows promising applications for dimensionality reduction, which is a major challenge in GWAS. With the advancement in biotechnology, sequencing, and bioinformatics tools, estimation of linkage disequilibrium (LD) based associations between a genome-wide collection of single-nucleotide polymorphisms (SNPs) and desired phenotypic traits has become accessible. The markers from GWAS could be utilized for genomic selection (GS) to predict superior lines by calculating genomic estimated breeding values (GEBVs). For prediction accuracy, an assortment of statistical models could be utilized, such as ridge regression best linear unbiased prediction (rrBLUP), genomic best linear unbiased predictor (gBLUP), Bayesian, and random forest (RF). Both naturally diverse germplasm panels and family-based breeding populations can be used for association mapping based on the nature of the breeding system (inbred or outbred) in the plant species. MAGIC, MCILs, RIAILs, NAM, and ROAM are being used for association mapping in several crops. Several modifications of NAM, such as doubled haploid NAM (DH-NAM), backcross NAM (BC-NAM), and advanced backcross NAM (AB-NAM), have also been used in crops like rice, wheat, maize, barley mustard, etc. for reliable marker-trait associations (MTAs), phenotyping accuracy is equally important as genotyping. Highthroughput genotyping, phenomics, and computational techniques have advanced during the past few years, making it possible to explore such enormous datasets. Each population has unique virtues and flaws at the genomics and phenomics levels, which will be covered in more detail in this review study. The current investigation includes utilizing elite breeding lines as association mapping population, optimizing the choice of GWAS selection, population size, and hurdles in phenotyping, and statistical methods which will analyze competitive traits in legume breeding.

Background Testa color is an important trait of peanut ( Arachis hypogaea L.) which is closely related with the nutritional and commercial value. Pink and red are main color of peanut testa. However, the genetic mechanism of testa color regulation in peanut is not fully understood. To elucidate a clear picture of peanut testa regulatory model, samples of pink cultivar (Y9102), red cultivar (ZH12), and two RNA pools (bulk red and bulk pink) constructed from F 4 lines of Y9102 x ZH12 were compared through a bulk RNA-seq approach. Results A total of 2992 differential expressed genes (DEGs) were identified among which 317 and 1334 were up-regulated and 225 and 1116 were down-regulated in the bulk red-vs-bulk pink RNA pools and Y9102-vs-ZH12, respectively. KEGG analysis indicates that these genes were divided into significantly enriched metabolic pathways including phenylpropanoid, flavonoid/anthocyanin, isoflavonoid and lignin biosynthetic pathways. Notably, the expression of the anthocyanin upstream regulatory genes PAL , CHS , and CHI was upregulated in pink and red testa peanuts, indicating that their regulation may occur before to the advent of testa pigmentation. However, the differential expression of down-stream regulatory genes including F3H , DFR , and ANS revealed that deepening of testa color not only depends on their gene expression bias, but also linked with FLS inhibition. In addition, the down-regulation of HCT , IFS , HID , 7- IOMT , and I2’H genes provided an alternative mechanism for promoting anthocyanin accumulation via perturbation of lignin and isoflavone pathways. Furthermore, the co-expression module of MYB, bHLH, and WRKY transcription factors also suggested a fascinating transcriptional activation complex, where MYB-bHLH could utilize WRKY as a co-option during the testa color regulation by augmenting anthocyanin biosynthesis in peanut. Conclusions These findings reveal candidate functional genes and potential strategies for the manipulation of anthocyanin biosynthesis to improve peanut varieties with desirable testa color.

Sweetpotato ( Ipomoea batatas L.) with different depths of yellow color contains different compositions of carotenoids, which are beneficial for human health. In this study, we performed an integrated analysis of metabolomic and transcriptomic to identify key genes playing a major role in carotenoid coloration in sweetpotato tuberous roots. Herein, 14 carotenoids were identified in five sweetpotatoes. Orange-red and orange cultivars were dominated by β-carotene (385.33 μg/g and 85.07 μg/g), yellow cultivar had a high β-cryptoxanthin (11.23 μg/g), light-yellow cultivar was rich in zeaxanthin (5.12 μg/g), whereas lutein (3.34 μg/g) was the main carotenoid in white cultivar. Furthermore, 27 differentially expressed genes involved in carotenoid metabolism were identified based on comparative transcriptome. Weighted gene co-expression network analysis identified 15 transcription factors highly associated with carotenoid content in sweetpotatoes. These results provide valuable information for revealing the regulatory mechanism of carotenoid metabolism in different-colored sweetpotato tuberous roots.

More than anthocyanins pigments displaying red, blue and purple, in flowers, fruits and leaves, which determine economic traits of crops and ornamental plants, they play multiple functional roles in plant-environment interactions which protect plants from biotic and abiotic stresses (Zhang et al., 2014;Landi et al., 2015;Qi et al., 2020). Interaction between flavonoids of plants and their environments Wine grapes are often grown in regions characterized by dry and warm summers, and a proper irrigation strategy is essential for obtaining high-quality berries and wines (Buesa et al., 2021;Palai et al., 2022;Romero et al., 2022).Palai et al.studied that effect of the regulated deficit irrigation (RDI) on berry flavonoid content and its related biosynthetic pathways in Sangiovese grapevines, including the moderate (RDI-1M) or severe (RDI-1S) water deficit from pea-size berry to veraison, moderate (RDI-2M) or severe (RDI-2S) water deficit from veraison through harvest, and severe during the lag-phase (RDI-LS). [...]exogenous flavonoid treatment of inoculated plants led to fewer and smaller powdery mildew spots on the wheat leaves. [...]flavonoids is suggested to confer resistance to powdery mildew in wheat. Identification of function of candidate genes/loci involved in flavonoid accumulation, growth and development of plants Flavonol synthases play important role in regulating flavonoid metabolism, specifically the flavonol and anthocyanin branching pathways (Vu et al., 2015).Guo et al.used the targeted LC–MS to determine flavonoid-related substances in overexpression of GbFLSa in Populus poplar and CK, and revealed the content of proanthocyanins including catechin, epicatechin, epigallocatechin and gallocatechin, as well as expression levels of two DFRs, three ANSs and two LARs in transgenic poplars were significantly lower than that in nontransgenic plants.

Aflatoxin is considered a “hidden poison” due to its slow and adverse effect on various biological pathways in humans, particularly among children, in whom it leads to delayed development, stunted growth, liver damage, and liver cancer. Unfortunately, the unpredictable behavior of the fungus as well as climatic conditions pose serious challenges in precise phenotyping, genetic prediction and genetic improvement, leaving the complete onus of preventing aflatoxin contamination in crops on post-harvest management. Equipping popular crop varieties with genetic resistance to aflatoxin is key to effective lowering of infection in farmer’s fields. A combination of genetic resistance for in vitro seed colonization (IVSC), pre-harvest aflatoxin contamination (PAC) and aflatoxin production together with pre- and post-harvest management may provide a sustainable solution to aflatoxin contamination. In this context, modern “omics” approaches, including next-generation genomics technologies, can provide improved and decisive information and genetic solutions. Preventing contamination will not only drastically boost the consumption and trade of the crops and products across nations/regions, but more importantly, stave off deleterious health problems among consumers across the globe.

The production and consumption of soybeans are widespread due to their nutritional and industrial value. Nutrient enrichment is vital for improving the nutritional quality of soybeans. This study aimed to evaluate the effect of foliar application of amino acids (AA) and zinc (Zn) on agronomic traits and the accumulation of grain Zn in soybeans. The experimental design comprised 16 treatment combinations involving four levels of amino acid application (0, 50, 100, and 150 ml 100 L -1 ) and Zn (0, 2, 4, and 6 mg L -1 ) following a randomized complete block design with three replications in field conditions. The results demonstrated that the application of foliar Zn and AA did not affect the yield, whereas that of AA 50 *Zn 2 and AA 150 *Zn 2 affected the number of pods and branches. The effects of AA application on N and the protein content in grains were determined to be significant. The application of AA 100 *Zn 6 emerged as the most effective treatment for the enhancement of Zn biofortification in soybean grains. The combined foliar application of AA and Zn contributed to enhanced Zn accumulation in the grains.

Blanchability is the ability of seeds to shed their seed coat (testa) and is a trait of economic importance in the food processing industry, yet remains underexplored in breeding programs. In this study, blanchability was evaluated in 184 groundnut accessions from the ICRISAT minicore collection to identify associated genomic regions, candidate genes, and molecular markers. Significant variability was observed over two seasons, with values ranging from 3.98 to 70.08%. Ten genotypes, including ICG10890, ICG9507, ICG13982, and ICG297, showed high blanchability, with ICG297 emerging as a promising donor based on cluster analysis of blanchability and agronomic traits. Genome-wide associations study (GWAS) using the 58 K ‘Axiom_ Arachis ’ SNP array revealed 58 significant SNP-trait associations, highlighting important genes such as isocitrate dehydrogenase and ubiquitin ligase , which influence seed coat structure and cell wall integrity thereby affecting blanchability. Further, nine SNPs were selected via allele mining, among these four SNPs, on chromosomes A01 (snpAH00551, AhBL01 ), A06 (snpAH00554, AhBL02 ), B04 (snpAH00558, AhBL03 ), and B07 (snpAH00559, AhBL04 ), effectively distinguishing between high and low blanchability genotypes. These validated SNPs present valuable tools for genomics-assisted breeding. Overall, the finding contributes towards better understanding of the genetic basis of blanchability in groundnut, providing key genomic resources for improving processing-related traits.

Pre-harvest sprouting (PHS) in groundnut leads to substantial yield losses and reduced seed quality, resulting in reduced market value of groundnuts. Breeding cultivars with 14–21 days of fresh seed dormancy (FSD) holds promise for precisely mitigating the yield and quality deterioration. In view of this, six multi-locus genome-wide association study (ML-GWAS) models alongside a single-locus GWAS (SL-GWAS) model were employed on a groundnut mini-core collection using multi season phenotyping and 58 K “Axiom_ Arachis ” array genotyping data. A total of 9 significant SNP-trait associations (STAs) for FSD were detected on A01, A04, A08, A09, B02, B04, B05, B07 and B09 chromosomes using six ML-GWAS models. Additionally, the SL-GWAS model identified 38 STAs across 14 chromosomes of groundnut. A single STA on chromosome B02 ( qFSD-B02-1 ) was consistently identified in both ML-GWAS and SL-GWAS models. Furthermore, candidate gene mining identified nine high confidence genes viz., Cytochrome P450 705 A , Dormancy/auxin associated family protein , WRKY family transcription factor , Protein kinase superfamily protein , serine/threonine protein phosphatase , myb transcription factor , transcriptional regulator STERILE APETALA-like , ethylene-responsive transcription factor 7-like and F-box protein interaction domain protein as prime regulators involved in Abscisic acid/Gibberellic acid signaling pathways regulating dormancy/germination. In addition, three of the allele-specific markers developed from the identified STAs were validated across a diverse panel. These markers hold potential for increasing dormancy in groundnut through marker-assisted selection (MAS). Thus, this research offers insights into genetic and molecular mechanisms underlying groundnut seed dormancy in addition to providing markers and donors for breeding future varieties with 2–3 weeks of FSD.

Anthocyanin is an important pigment that prevents oxidative stress and mediates adaptation of plants to salt stress. Peanuts with dark red and black testa are rich in anthocyanin. However, correlation between salt tolerance and anthocyanin content in black and dark red testa peanuts is unknown. In this study, three peanut cultivars namely YZ9102 (pink testa), JHR1 (red testa) and JHB1 (black testa) were subjected to sodium chloride (NaCl) stress. The plant growth, ion uptake, anthocyanin accumulation, oxidation resistance and photosynthetic traits were comparatively analyzed. We observed that the plant height, leaf area and biomass under salt stress was highly inhibited in pink color testa (YZ9102) as compare to black color testa (JHB1). JHB1, a black testa colored peanut was identified as the most salt-tolerance cultivar, followed by red (JHR1) and pink(YZ9102). During salt stress, JHB1 exhibited significantly higher levels of anthocyanin and flavonoid accumulation compared to JHR1 and YZ9102, along with increased relative activities of antioxidant protection and photosynthetic efficiency. However, the K + /Na + and Ca 2+ /Na + were consistently decreased among three cultivars under salt stress, suggesting that the salt tolerance of black testa peanut may not be related to ion absorption. Therefore, we predicted that salt tolerance of JHB1 may be attributed to the accumulation of the anthocyanin and flavonoids, which activated antioxidant protection against the oxidative damage to maintain the higher photosynthetic efficiency and plant growth. These findings will be useful for improving salt tolerance of peanuts.

Cultivated peanut ( Arachis hypogaea L.) is an important source of edible oil and protein. Peanut testa (seed coat) provides protection for seeds and serves as a carrier for diversity metabolites necessary for human health. There is significant diversity available for testa color in peanut germplasms. However, the kinds and type of metabolites in peanut testa has not been comprehensively investigated. In this study, we performed metabolite profiling using UPLC-MS/MS for four peanut germplasm lines with different testa colors, including pink, purple, red, and white. A total of 85 metabolites were identified in four peanuts. Comparative metabolomics analysis identified 78 differentially accumulated metabolites (DAMs). Some metabolites showed significant correlation with other metabolites. For instance, proanthocyanidins were positively correlated with cyanidin 3-O-rutinoside and malvin, and negatively correlated with pelargonidin-3-glucoside. We observed that the total proanthocyanidins are most abundant in pink peanut variety WH10. The red testa accumulated more isoflavones, flavonols and anthocyanidins compared with that in pink testa. These results provided valuable information about differential accumulation of metabolites in testa with different color, which are helpful for further investigation of the molecular mechanism underlying biosynthesis and accumulation of these metabolites in peanut.