Genetic and genomic analysis of the seed-filling process in maize based on a logistic model

Genetic dissection of maize grain moisture content and dehydration rate using high-density bin mapping in a recombinant inbred line population

Maize (Zea mays L.) grain moisture content (GMC) at harvest is a key determinant of seed preservation, grain quality, and drying costs, with the grain dehydration rate (GDR) playing a critical role in determining GMC. This study focused on understanding the genetic basis of GDR by utilizing a recombinant inbred line population of 310 lines derived from PB80 and PHJ65, assessed across three environments with high-density SNP markers. A genetic linkage map spanning 1237.36 cM with 5235 bin markers was constructed, leading to the identification of 23 quantitative trait loci (QTLs) associated with GMC and Area Under the Dry Down Curve (AUDDC) across multiple chromosomes, with several QTLs explaining over 10% of the phenotypic variance. Significant QTLs, including qGMC1.1, qGMC2.2, and qAUDDC2.2, were consistently detected across various environments and developmental stages. Transcriptomic analysis identified 21 candidate genes within these QTL regions, including key transcription factors and metabolism-related genes. These findings contribute to a better understanding of the genetic control of GMC and GDR, may serve as a foundation for future breeding efforts in maize breeding to enhance mechanized production efficiency and reduce post-harvest drying costs.

Integrated physiological, transcriptomic and metabolomic analyses reveal the mechanism of peanut kernel weight reduction under waterlogging stress

Waterlogging stress (WS) hinders kernel development and directly reduces peanut yield; however, the mechanism of kernel filling in response to WS remains unknown. The waterlogging-sensitive variety Huayu 39 was subjected to WS for 3 days at 7 days after the gynophores touched the ground (DAG). We found that WS affected kernel filling at 14, 21, and 28 DAG. WS decreased the average filling rate and kernel dry weight, while transcriptome sequencing and widely targeted metabolomic analysis revealed that WS inhibited the gene expression in starch and sucrose metabolism, which reduced sucrose input and transformation ability. Additionally, genes related to ethylene and melatonin synthesis and the accumulation of tryptophan and methionine were upregulated in response to WS. WS upregulated the expression of the gene encoding tryptophan decarboxylase (AhTDC), and overexpression of AhTDC in Arabidopsis significantly reduced the seed length, width, and weight. Therefore, WS reduced the kernel-filling rate, leading to a reduction in the 100-kernel weight. This survey informs the development of measures that alleviate the negative impact of WS on peanut yield and quality and provides a basis for exploring high-yield and high-quality cultivation, molecular-assisted breeding, and waterlogging prevention in peanut farming.

Genome-wide transcriptional responses to water deficit during seed development in Pisum sativum, focusing on sugar transport and metabolism

Agriculture is particularly impacted by global changes, drought being a main limiting factor of crop production. Here, we focus on pea (Pisum sativum), a model legume cultivated for its seed nutritional value. A water deficit (WD) was applied during its early reproductive phase, harvesting plant organs at two key developmental stages, either at the embryonic or the seed-filling stages. We combined phenotypic, physiological and transcriptome analyses to better understand the adaptive response to drought. First, we showed that apical growth arrest is a major phenotypic indicator of water stress. Sugar content was also greatly impacted, especially leaf fructose and starch contents. Our RNA-seq analysis identified 2001 genes regulated by WD in leaf, 3684 genes in root and 2273 genes in embryonic seed, while only 80 genes were regulated during seed-filling. Hence, a large transcriptional reprogramming occurred in response to WD in seeds during early embryonic stage, but no longer during the later stage of nutritional filling. Biological processes involved in transcriptional regulation, carbon transport and metabolism were greatly regulated by WD in both source and sink organs, as illustrated by the expression of genes encoding transcription factors, sugar transporters and enzymes of the starch synthesis pathway. We then looked at the transcriptomic changes during seed development, highlighting a transition from monosaccharide utilization at the embryonic stage to sucrose transport feeding the starch synthesis pathway at the seed-filling stage. Altogether, our study presents an integrative picture of sugar transport and metabolism in response to drought and during seed development at a genome-wide level.

Effect of carbons' structure and type on AC electrical properties of polymer composites: predicting the percolation threshold of permittivity through different models

The AC electrical properties of EVA- and NBR-based composites filled with different conductive fillers were investigated. Result shows several magnitudes of increment in AC electrical conductivity and dielectric permittivity after the addition of these conductive fillers, indicating that these materials can be used as supercapacitors. The magnitude of increment was varied according to polymer and filler types. Herein, we also have tested the applicability of different sigmoidal models to find out the percolation threshold value of permittivity for these binary polymer composite systems. It is observed that except sigmoidal-Boltzmann and sigmoidal-dose-response models, other sigmoidal models exhibit different values of percolation threshold when considered for any particular polymer composite system. The paper discusses the variation in results of percolation threshold with an emphasis on the advantages, disadvantages and limitations of these models. We also have applied the classical percolation theory to predict the percolation threshold of permittivity and compared with all the reported sigmoidal models. To judge the unanimous acceptability of these models, they tested vis-à-vis the permittivity results of various polymer composites reported in published literature. To comprehend, all the models except the sigmoidal-logistic-1 model were successfully applicable for predicting the percolation threshold of permittivity for polymer composites.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00396-023-05120-2.

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.

Impacts of Heat Stress around Flowering on Growth and Development Dynamic of Maize (Zea mays L.) Ear and Yield Formation

Heat stress around flowering is harmful to maize growth and yield. Ear traits are closely related to yield; however, the effects of heat stress before and after flowering on ear development and yield traits remain unclear for different heat-tolerant cultivars. In this study, field experiments were conducted in 2020 and 2021, including (i) three sowing dates, (ii) three temperature regimes: control (CK), heated before silking (V9-R1, TBS) and heated after silking (R1-R1 + 15 d, TAS), and (iii) two hybrids (ZD958: heat-tolerant; DH605: heat-sensitive). The results showed that heating had negative effects on all surveyed ear and yield traits except for increased ear length under TBS. The negative effects were larger (i) for TAS than for TBS, (ii) for DH605 than for ZD958, and (iii) for kernel number per plant (KNP) than for kernel weight (KW). The decreased ear traits were a result of a decreased growth rate during rapid ear growth periods. Floret pollination failure and kernel abortion were the main reasons for the decrease in KNP, mainly depending on the daily maximum temperature during V15-R1 + 7 d. The strong linear relationships between ear and yield traits suggested that ear traits could be used as important indicators for breeding heat-resistant varieties in the future.

Meta-QTL analysis explores the key genes, especially hormone related genes, involved in the regulation of grain water content and grain dehydration rate in maize

BACKGROUND

Low grain water content (GWC) at harvest of maize (Zea mays L.) is essential for mechanical harvesting, transportation and storage. Grain drying rate (GDR) is a key determinant of GWC. Many quantitative trait locus (QTLs) related to GDR and GWC have been reported, however, the confidence interval (CI) of these QTLs are too large and few QTLs has been fine-mapped or even been cloned. Meta-QTL (MQTL) analysis is an effective method to integrate QTLs information in independent populations, which helps to understand the genetic structure of quantitative traits.

RESULTS

In this study, MQTL analysis was performed using 282 QTLs from 25 experiments related GDR and GWC. Totally, 11 and 34 MQTLs were found to be associated with GDR and GWC, respectively. The average CI of GDR and GWC MQTLs was 24.44 and 22.13 cM which reduced the 57 and 65% compared to the average QTL interval for initial GDR and GWC QTL, respectively. Finally, 1494 and 5011 candidate genes related to GDR and GWC were identified in MQTL intervals, respectively. Among these genes, there are 48 genes related to hormone metabolism.

CONCLUSIONS

Our studies combined traditional QTL analyses, genome-wide association study and RNA-seq to analysis major locus for regulating GWC in maize.

Quantitative Trait Locus Analysis and Identification of Candidate Genes Affecting Seed Size and Shape in an Interspecific Backcross Inbred Line Population of Gossypium hirsutum × Gossypium barbadense

Seed size and shape are key agronomic traits affecting seedcotton yield and seed quality in cotton (Gossypium spp.). However, the genetic mechanisms that regulate the seed physical traits in cotton are largely unknown. In this study, an interspecific backcross inbred line (BIL) population of 250 BC1F7 lines, derived from the recurrent parent Upland CRI36 (Gossypium hirsutum) and Hai7124 (Gossypium barbadense), was used to investigate the genetic basis of cotton seed physical traits via quantitative trait locus (QTL) mapping and candidate gene identification. The BILs were tested in five environments, measuring eight seed size and shape-related traits, including 100-kernel weight, kernel length width and their ratio, kernel area, kernel girth, kernel diameter, and kernel roundness. Based on 7,709 single nucleotide polymorphic (SNP) markers, a total of 49 QTLs were detected and each explained 2.91-35.01% of the phenotypic variation, including nine stable QTLs mapped in at least three environments. Based on pathway enrichment, gene annotation, genome sequence, and expression analysis, five genes encoding starch synthase 4, transcription factor PIF7 and MYC4, ubiquitin-conjugating enzyme E27, and THO complex subunit 4A were identified as candidate genes that might be associated with seed size and shape. Our research provides valuable information to improve seed physical traits in cotton breeding.

Integration of Crop Growth Models and Genomic Prediction

Crop growth models (CGMs) consist of multiple equations that represent physiological processes of plants and simulate crop growth dynamically given environmental inputs. Because parameters of CGMs are often genotype-specific, gene effects can be related to environmental inputs through CGMs. Thus, CGMs are attractive tools for predicting genotype by environment (G×E) interactions. This chapter reviews CGMs, genetic analyses using these models, and the status of studies that integrate genomic prediction with CGMs. Examples of CGM analyses are also provided.

Multi-Locus Genome-Wide Association Study and Genomic Selection of Kernel Moisture Content at the Harvest Stage in Maize

Kernel moisture content at the harvest stage (KMC) is an important trait that affects the mechanical harvesting of maize grain, and the identification of genetic loci for KMC is beneficial for maize molecular breeding. In this study, we performed a multi-locus genome-wide association study (ML-GWAS) to identify quantitative trait nucleotides (QTNs) for KMC using an association mapping panel of 251 maize inbred lines that were genotyped with an Affymetrix CGMB56K SNP Array and phenotypically evaluated in three environments. Ninety-eight QTNs for KMC were detected using six ML-GWAS models (mrMLM, FASTmrMLM, FASTmrEMMA, PLARmEB, PKWmEB, and ISIS EM-BLASSO). Eleven of these QTNs were considered to be stable, as they were detected by at least four ML-GWAS models under a uniformed environment or in at least two environments and BLUP using the same ML-GWAS model. With qKMC5.6 removed, the remaining 10 stable QTNs explained <10% of the phenotypic variation, suggesting that KMC is mainly controlled by multiple minor-effect genetic loci. A total of 63 candidate genes were predicted from the 11 stable QTNs, and 10 candidate genes were highly expressed in the kernel at different time points after pollination. High prediction accuracy was achieved when the KMC-associated QTNs were included as fixed effects in genomic selection, and the best strategy was to integrate all KMC QTNs identified by all six ML-GWAS models. These results further our understanding of the genetic architecture of KMC and highlight the potential of genomic selection for KMC in maize breeding.