Biology subjects

Brar, M. S.

Publications and source records attributed to Brar, M. S..

5 recordsLinked to original sources

bioRxiv2026

Phenotypic plasticity, stalk geometry, and noncoding variation underpin stalk lodging resistance in maize

Stalk lodging causes severe yield losses in maize (Zea mays L.) worldwide, worsening food and feed security. Stalk lodging resistance is influenced by multiple traits at various levels of biological organization, collectively referred to as intermediate traits, but their identities, genetic bases, and interrelationships remain poorly resolved. Here, evaluation of multiple geometric and structural intermediate traits in a maize diversity panel across four environments showed that macroenvironmental variation is the predominant driver of phenotype plasticity and that plasticity varies with internode position along the stalk, consistent with height-dependent mechanosensing. Major and minor diameters, moment of inertia, and rind penetration resistance, were genetically tractable and showed strong genetic correlations with stalk flexural stiffness. Multivariate analyses revealed two distinct but complementary mechanistic pathways, represented by cross-sectional geometry and rind architecture, that contribute to stalk mechanical performance. Association analyses using whole-genome resequencing data identified 705 SNPs associated with intermediate traits, fewer than 20% of which overlapped genic regions, indicating that most associated variation resides outside annotated genes. Interestingly, about 22% of SNPs were shared between at least two traits, indicating substantial shared genetic control among intermediate traits. Candidate gene analyses highlighted novel promising candidate loci associated with intermediate traits while recovering genes previously implicated in stalk lodging resistance. The predominance of noncoding associations further suggests that regulatory variation may contribute substantially to natural variation in intermediate traits underlying stalk lodging resistance.

genetics↗

bioRxiv2025

Untargeted metabolomics reveals key metabolites and genes underlying salinity tolerance mechanisms in maize

Understanding the physiological, metabolic, and genetic mechanisms underlying salt tolerance is essential for improving crop resilience and productivity, yet their complex interactions remain poorly defined. We compared physiological and metabolic responses to salinity between two contrasting maize inbred lines: the salt-sensitive C68 and the salt-tolerant NC326. The senstitivity of C68 was characterized by reduced shoot and root dry weights and plant height, high tissue accumulation of Na and Cl, but low K, and lower leaf proline accumulation compared to the salt-tolerant NC326. Untargeted metabolomics identified 56 metabolites categorized as constitutively upregulated or salt-responsive. In NC326, constitutive accumulation of flavonoids, including schaftoside, tricin, and kaempferol-related compounds in leaves suggests adaptive priming against oxidative stress, while constitutively higher lipids and fatty acids in roots may enhance membrane stability. Salt-responsive metabolites, notably antioxidants and lanosterol, highlighted inducible oxidative-stress mitigation and membrane-stabilization strategies. By integrating metabolomic and genetic analyses, we identified 10 candidate genes involved in the biosynthesis of key metabolites. These findings establish a comprehensive platform for functional validation of metabolites and candidate genes for developing maize varieties with improved resilience to soil salinity through targeted breeding or biotechnological strategies. Plane Language SummarySalinity, or high salt content in soil, is a major challenge to crop growth worldwide, reducing food production. Maize, an important crop globally, struggles to grow under salty conditions. This study compared two maize types--one that grows well in salty soil and one that struggles--to understand how maize plants adapt to salt stress. Using advanced techniques, we measured hundreds of compounds (metabolites) in plant tissues to identify protective substances. We discovered that plants resistant to salt stress naturally produce higher amounts of protective substances, helping them avoid damage from salt. Additionally, we found specific metabolites that plants produce when exposed to salty conditions to protect their cells. We also identified genes that control the production of these important metabolites. This research provides new insights into how maize plants manage salt stress and highlights potential targets for developing crops that grow better in saline soils. Core IdeasO_LIMaize genotypes differ in growth, ion balance, and proline under salt stress. C_LIO_LIMetabolomics reveals pre-stress buildup of protective flavonoids and fatty acids. C_LIO_LISalt triggers metabolic changes like sterol increase to protect membranes. C_LIO_LIGenetic analysis links genes to key metabolites controlling salt tolerance. C_LIO_LIMetabolite-gene insights guide breeding of maize for salt resilience C_LI

plant biology↗

bioRxiv2025

Genomic prediction of stalk lodging resistance and the associated intermediate phenotypes in maize using whole-genome resequence and multi-environmental data

Breeding for stalk lodging resistance is of paramount importance to maintain and improve maize yield and quality and meet increasing food demand. The integration of environmental, phenotypic, and genotypic information offers the opportunity to develop genomic prediction strategies that can improve the genetic gain for complex traits such as stalk lodging. However, implementation of genomic predictions for stalk lodging resistance has been sparse primarily due to the lack of reliable and reproducible phenotyping strategies. In this study, we measured 10 traits related to stalk lodging resistance obtained from a novel phenotyping platform on approximately 31,000 individual stalks. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of different single and multi-environment genomic prediction models. In total, 555 maize inbred lines from the Wisconsin diversity panel were evaluated in four environments. The multi-environment models more than doubled the prediction accuracy compared to the single-environment model for most traits, particularly when predicting lines in a sparse testing design. Predictive correlations for stalk bending strength and stalk flexural stiffness, a non-destructive method for assessment of stalk lodging resistance, were moderately high and ranged between 0.32 to 0.89 and 0.26 to 0.88, respectively. In contrast, rind thickness was the most difficult trait to predict. Our results show that the use of multi-environmental data could improve genomic prediction accuracy for stalk lodging resistance and its intermediate phenotypes. This study will serve as a first step toward genetic improvement and the development of maize varieties resistant to stalk lodging. Core IdeasO_LIThe DARLING platform was successfully used to collect lodging resistance-related phenotypes C_LIO_LIProportion of variation explained by genotype by environment interaction was not negligible C_LIO_LIGenomic predictions for lodging resistance phenotypes ranged from moderate to high C_LIO_LIAccounting for genotype by environment interaction was found to be important for improved predictive performance C_LI Plain language summaryStalk lodging - when maize stalks break or fall over before harvest - can seriously reduce crop yields. Breeding maize that resists lodging is important to ensure reliable food production. We tested about 31,000 individual stalks for 10 traits related to lodging resistance using a new phenotyping system. These traits were combined with environmental information and whole-genome resequence data to investigate the predictive ability of single and multi-environment genomic prediction models. By analyzing 555 maize lines, we found that using data from multiple environments improved genomic prediction accuracy by more than twice as much as using data from a single environment. Traits such as bending strength and flexural stiffness were easier to predict, while rind thickness was more difficult. These results show that combining genetic, environmental, and phenotypic data can help breeders more accurately select maize plants with stronger stalks, leading to better, more resilient crops.

genetics↗

bioRxiv2025

High Density Phenotypic Map of Natural Variation for Intermediate Phenotypes Associated with Stalk Lodging Resistance in Maize

The world has food security needs that are currently not being met. Stalk lodging undermines crop productivity and incurs global yield losses of at least $6 billion in maize (Zea mays L.). Genetic architecture of stalk lodging resistance, a measure of the ability of the stalk to withstand lodging, remains poorly resolved, creating a bottleneck for genetic improvement. Identification of diverse plant traits at multiple length scales of biological organizations that contribute to stalk lodging resistance and characterization of natural variation for these traits is critical for improving stalk lodging resistance. We identified and evaluated 11 intermediate phenotypes, traits associated with stalk lodging resistance, in a maize diversity panel of 566 inbred lines evaluated over four environments. The identity of each of the 31,260 stalks evaluated in the study was preserved throughout the phenotyping pipeline which enabled capturing variation at the individual plant level. This high-density phenotypic dataset provided a foundation for statistical genomics, predictive modeling, and machine learning analyses to identify genes and genetic elements underlying stalk lodging resistance. Additionally, phenotypic characterization of multiple intermediate phenotypes on a diverse set of inbred lines provided excellent opportunities to understand the relative contribution of these traits to stalk lodging resistance. Besides improvement of maize for grain and animal feedstock, the inferences from this data will be valuable for improvement of stalk lodging resistance in other grass species.

plant biology↗

bioRxiv2025

Temporal analysis of physiological phenotypes identifies novel metabolic and genetic underpinnings of senescence in maize

Leaf senescence induces extensive metabolome reprogramming to optimize nutrient recycling, enhance resilience to abiotic and biotic stress, and improve productivity. However, the characterization of these metabolic shifts and the identification of key metabolites and pathways remains limited. We generated a temporal map of physiological and metabolic diversity in genetically diverse maize inbred lines varying for the staygreen trait. Combinatorial analysis of physiological and metabolic changes revealed substantial metabolic perturbations and identified 84 leaf metabolites associated with senescence. Non-staygreen inbred lines exhibited higher accumulation of primary metabolites including sugar alcohols such as mannitol and erythritol, and amino acids such as phenylalanine and arginine. In contrast, the staygreen inbred lines showed higher abundance of secondary metabolites, primarily phenylpropanoids, including caffeic acid, chlorogenic acid, and eriodictyol. Linking metabolome to the genome identified 56 novel candidate genes expressed in adult maize leaf that regulate metabolic flux during senescence. Reverse genetic analysis validated the role of naringenin chalcone and eriodictyol in both maize and Arabidopsis, demonstrating a conserved function of these phenylpropanoids in leaf senescence across monocots and dicots. Our study provides valuable insights into the coordinated physiological and metabolic changes driving leaf senescence and identifies novel genes underlying this complex developmental process.

plant biology↗