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To understand the ecology of species and promote biotechnology through beneficial strain selection for improving starch yield in maize wet-milling steeping, bacterial diversity and community structure during the counter-current steeping process in a commercial steeping system were characterized and investigated. The microbial diversity in the steeping liquor, which consisted of 16 phyla, 131 families, and 290 genera, was more abundant compared to those present on the surface of unsteeped maize. As the counter-current steeping progressed, exposing newer maize to the older steepwater, Lactobacillus dominated, replacing Rahnella, Pseudomonas, Pantoea, and Serratia. The thermophilic and acidophilic microbial consortia were enriched through adaptive evolution engineering and employed to improve starch yield. Several steeping strategies were evaluated, including water alone, SO2 alone, mono-culture of B. coagulans, microbial consortia, and a combination of consortium and SO2. Combining the microbial consortium with SO2 significantly increased the starch yield to, about 66.4 ± 0.5%, a 22% and 46% increase over SO2 alone and the consortium alone, respectively. Scanning electron microscope (SEM) of steeped maize structure indicated that the combination of consortium and SO2 disrupted the protein matrix and widened gaps between starch granules in maize endosperm. This released proteins into the steepwater and left starch granules in the aleurone layer. The steeping strategy of using thermophilic and acidophilic microbial consortium as additives shows potential application as an environmentally friendly alternative to conventional maize steeping procedures. Highlights: Characterization of bacterial diversity in a commercial steeping system. Adaptation of a thermophilic and acidophilic microbial consortium for maize steeping. Development of an environmentally friendly strategy for maize steeping. Consortium combining SO2 leads to 66.4% increase in starch yield. Novel strategy disrupts protein matrix making starch granules to aleurone layer. [ABSTRACT FROM AUTHOR]

Maize production on the North China Plain (NCP) is critical to food security in China; however, currently, it is affected by climate change. Understanding the spatiotemporal distribution of the climate suitability for maize on the NCP in the present and future may help sustainably use climate‐related resources to ensure food security in China. In this study, 30 general circulation models from the Coupled Model Intercomparison Project Phase 5 and a statistical downscaling model (NWAI‐WG) were used to project meteorological data in 2021–2100 under representative concentration pathway 4.5 (RCP4.5) and RCP8.5 for 23 national climatic stations on the NCP. Based on agricultural climate suitability theory and the fuzzy mathematics method, the suitability of temperature, precipitation, and solar radiation on summer maize were analysed. The results showed that temperature suitability is decreasing for 2021–2100, especially during the stages from jointing to maturity; temperature suitability is the lowest in the southwest and increases to the northeast under both scenarios. Compared to 1996–2015, the precipitation suitability in 2021–2100 increases greatly under both scenarios, especially in the central part under RCP4.5 and in the north part under RCP8.5. Solar radiation suitability shows a decreasing trend for 1996–2015, however, an increasing trend for 2021–2100 under both scenarios. At spatial scale, the solar suitability increases from southwest to northeast. The integrated climate suitability under RCP4.5 in 2021–2100 is averaged approximately 0.8 and varies slightly, indicating climate change may do small effect on maize growth, though the high values shifting from the central part in 2021–2040 to the northern part in 2081–2100; however, under RCP8.5, the integrated climate suitability shows a downward trend, indicating that climate change will make many regions less suitable for maize growth. These results could provide basic information for agriculture to adapt to climate change and ensure food security for China. [ABSTRACT FROM AUTHOR]

SUMMARY: Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates. However, it is unclear how evolution contributes to metabolic variation in plants. Here, we investigated the metabolomics data from leaf and seed tissues in maize and rice. Using principal components analysis based on leaf metabolites but not seed metabolites, metabolomics data could be clearly separated for rice Indica and Japonica accessions, while two maize subgroups, temperate and tropical, showed more visible admixture. Rice and maize seed exhibited significant interspecific differences in metabolic variation, while within rice, leaf and seed displayed similar metabolic variations. Among 10 metabolic categories, flavonoids had higher variation in maize than rice, indicating flavonoids are a key constituent of interspecific metabolic divergence. Interestingly, metabolic regulation was also found to be reshaped dramatically from positive to negative correlations, indicative of the differential evolutionary processes in maize and rice. Moreover, perhaps due to this divergence significantly more metabolic interactions were identified in rice than maize. Furthermore, in rice, the leaf was found to harbor much more intense metabolic interactions than the seed. Our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice. Significance Statement: Metabolites are the intermediate and final products of metabolism, which play essential roles in plant growth, evolution and adaptation to changing climates, but it is unclear how evolution contributes to metabolic variation in plants. We investigated the metabolomics data from leaf and seed tissues in maize and rice, and our result suggests that metabolomes are valuable for tracking evolutionary history, thereby complementing and extending genomic insights concerning which features are responsible for interspecific differentiation in maize and rice. [ABSTRACT FROM AUTHOR]

MaizeCUBIC is a free database that describes genomic variations, gene expression, phenotypes and quantitative trait locus (QTLs) for a maize CUBIC population (24 founders and 1404 inbred offspring). The database not only includes information for over 14M single nucleotide polymorphism (SNPs) and 43K indels previously identified but also contains 660K structure variations (SVs) and 600M novel sequences newly identified in the present study, which represents a comprehensive high-density variant map for a diverse population. Based on these genomic variations, the database would demonstrate the mosaic structure for each progeny, reflecting a high-resolution reshuffle across parental genomes. A total of 23 agronomic traits measured on parents and progeny in five locations, where are representative of the maize main growing regions in China, were also included in the database. To further explore the genotype–phenotype relationships, two different methods of genome-wide association studies (GWAS) were employed for dissecting the genetic architecture of 23 agronomic traits. Additionally, the Basic Local Alignment Search Tool and primer design tools are developed to promote follow-up analysis and experimental verification. All the original data and corresponding analytical results can be accessed through user-friendly online queries and web interface dynamic visualization, as well as downloadable files. These data and tools provide valuable resources on genetic and genomic studies of maize and other crops. [ABSTRACT FROM AUTHOR]

Mining novel kernel size-related genes by pQTL mapping and multi-omics integrative analysis in developing maize kernels The results reveal that the transcript level alone does not always reliably predict protein abundance at the population scale, and protein abundance variation may play an important role in orchestrating the biological functions of genes involved in the same biological pathways. Keywords: proteomics; protein quantitative trait locus; multi-omics integration; kernel-related traits; maize EN proteomics protein quantitative trait locus multi-omics integration kernel-related traits maize 1489 1491 3 08/26/21 20210801 NES 210801 As a sink organ for starch, protein, oil and essential nutrients, the maize ( I Zea mays i ) kernel is not only the main target for yield and quality improvement but also a model system for genetic and molecular biology studies. [Extracted from the article]

Deciphering the influence of genetics on primary metabolism in plants will provide insights useful for genetic improvement and enhance our fundamental understanding of plant growth and development. Although maize (Zea mays) is a major crop for food and feed worldwide, the genetic architecture of its primary metabolism is largely unknown. Here, we use high-density linkage mapping to dissect large-scale metabolic traits measured in three different tissues (leaf at seedling stage, leaf at reproductive stage, and kernel at 15 d after pollination [ DAP ]) of a maize recombinant inbred line population. We identify 297 quantitative trait loci (QTLs) with moderate (86.2% of the mapped QTL , R  2 = 2.4 to 15%) to major effects (13.8% of the mapped QTL , R  2 >15%) for 79 primary metabolites across three tissues. Pairwise epistatic interactions between these identified loci are detected for more than 25.9% metabolites explaining 6.6% of the phenotypic variance on average (ranging between 1.7 and 16.6%), which implies that epistasis may play an important role for some metabolites. Key candidate genes are highlighted and mapped to carbohydrate metabolism, the tricarboxylic acid cycle, and several important amino acid biosynthetic and catabolic pathways, with two of them being further validated using candidate gene association and expression profiling analysis. Our results reveal a metabolite-metabolite-agronomic trait network that, together with the genetic determinants of maize primary metabolism identified herein, promotes efficient utilization of metabolites in maize improvement. [ABSTRACT FROM AUTHOR]

Alternative splicing (AS) enhances transcriptome diversity and plays important roles in regulating plant processes. Although widespread natural variation in AS has been observed in plants, how AS is regulated and contribute to phenotypic variation is poorly understood. Here, we report a population-level transcriptome assembly and genome-wide association study to identify splicing quantitative trait loci (sQTLs) in developing maize (Zea mays) kernels from 368 inbred lines. We detected 19,554 unique sQTLs for 6570 genes. Most sQTLs showed small isoform usage changes without involving major isoform switching between genotypes. The sQTL-affected isoforms tend to display distinct protein functions. We demonstrate that nonsense-mediated mRNA decay, microRNA-mediated regulation, and small interfering peptide-mediated peptide interference are frequently involved in sQTL regulation. The natural variation in AS and overall mRNA level appears to be independently regulated with different cis -sequences preferentially used. We identified 214 putative trans -acting splicing regulators, among which ZmGRP1 , encoding an hnRNP-like glycine-rich RNA binding protein, regulates the largest trans -cluster. Knockout of ZmGRP1 by CRISPR/Cas9 altered splicing of numerous downstream genes. We found that 739 sQTLs colocalized with previous marker-trait associations, most of which occurred without changes in overall mRNA level. Our findings uncover the importance of AS in diversifying gene function and regulating phenotypic variation. [ABSTRACT FROM AUTHOR]

Highlights: [•] We assessed crop coefficients for maize in semi-arid Hailiutu catchment, China. [•] Plant sap flow (SF) and soil evaporation were measured, and summed to obtain ET c . [•] ET c was estimated with the Penman–Monteith equation and an FAO crop coefficient (K c ). [•] Estimated and measured evapotranspiration rates agreed well. [•] Groundwater contributed 33% and 27% of maize ET c in 2011 and 2012, respectively. [ABSTRACT FROM AUTHOR]