New insights into the response of maize to fluctuations in the light environment

Genome-Wide Identification of the Maize Chitinase Gene Family and Analysis of Its Response to Biotic and Abiotic Stresses

BACKGROUND/OBJECTIVES

Chitinases, enzymes belonging to the glycoside hydrolase family, play a crucial role in plant growth and stress response by hydrolyzing chitin, a natural polymer found in fungal cell walls. This study aimed to identify and analyze the maize chitinase gene family, assessing their response to various biotic and abiotic stresses to understand their potential role in plant defense mechanisms and stress tolerance.

METHODS

We employed bioinformatics tools to identify 43 chitinase genes in the maize B73_V5 genome. These genes were characterized for their chromosomal positions, gene and protein structures, phylogenetic relationships, functional enrichment, and collinearity. Based on previous RNA-seq data, the analysis assessed the expression patterns of these genes at different developmental stages and under multiple stress conditions.

RESULTS

The identified chitinase genes were unevenly distributed across maize chromosomes with a history of tandem duplications contributing to their divergence. The ZmChi protein family was predominantly hydrophilic and localized mainly in chloroplasts. Expression analysis revealed that certain chitinase genes were highly expressed at specific developmental stages and in response to various stresses, with ZmChi31 showing significant responsiveness to 11 different abiotic and biotic stresses.

CONCLUSIONS

This study provides new insights into the role of chitinase genes in maize stress response, establishing a theoretical framework for exploring the molecular basis of maize stress tolerance. The identification of stress-responsive chitinase genes, particularly ZmChi31, offers potential candidates for further study in enhancing maize resistance to environmental challenges.

Discovering novel genomic regions explaining adaptation of bread wheat to conservation agriculture through GWAS

To sustainably increase wheat yield to meet the growing world population's food demand in the face of climate change, Conservation Agriculture (CA) is a promising approach. Still, there is a lack of genomic studies investigating the genetic basis of crop adaptation to CA. To dissect the genetic architecture of 19 morpho-physiological traits that could be involved in the enhanced adaptation and performance of genotypes under CA, we performed GWAS to identify MTAs under four contrasting production regimes viz., conventional tillage timely sown (CTTS), conservation agriculture timely sown (CATS), conventional tillage late sown (CTLS) and conservation agriculture late sown (CALS) using an association panel of 183 advanced wheat breeding lines along with 5 checks. Traits like Phi2 (Quantum yield of photosystem II; CATS:0.37, CALS: 0.31), RC (Relative chlorophyll content; CATS:55.51, CALS: 54.47) and PS1 (Active photosystem I centers; CATS:2.45, CALS: 2.23) have higher mean values in CA compared to CT under both sowing times. GWAS identified 80 MTAs for the studied traits across four production environments. The phenotypic variation explained (PVE) by these QTNs ranged from 2.15 to 40.22%. Gene annotation provided highly informative SNPs associated with Phi2, NPQ (Quantum yield of non-photochemical quenching), PS1, and RC which were linked with genes that play crucial roles in the physiological adaptation under both CA and CT. A highly significant SNP AX94651261 (9.43% PVE) was identified to be associated with Phi2, while two SNP markers AX94730536 (30.90% PVE) and AX94683305 (16.99% PVE) were associated with NPQ. Identified QTNs upon validation can be used in marker-assisted breeding programs to develop CA adaptive genotypes.

Transcriptomic and metabolic signatures of diatom plasticity to light fluctuations

Unlike in terrestrial and freshwater ecosystems, light fields in oceans fluctuate due to both horizontal current and vertical mixing. Diatoms thrive and dominate the phytoplankton community in these fluctuating light fields. However, the molecular mechanisms that regulate diatom acclimation and adaptation to light fluctuations are poorly understood. Here, we performed transcriptome sequencing, metabolome profiling, and 13C-tracer labeling on the model diatom Phaeodactylum tricornutum. The diatom acclimated to constant light conditions was transferred to six different light conditions, including constant light (CL5d), short-term (1 h) high light (sHL1h), and short-term (1 h) and long-term (5 days) mild or severe light fluctuation conditions (mFL1h, sFL1h, mFL5d, and sFL5d) that mimicked land and ocean light levels. We identified 2,673 transcripts (25% of the total expressed genes) expressed differentially under different fluctuating light regimes. We also identified 497 transcription factors, 228 not reported previously, which exhibited higher expression under light fluctuations, including 7 with a light-sensitive PAS domain (Per-period circadian protein, Arnt-aryl hydrocarbon receptor nuclear translocator protein, Sim-single-minded protein) and 10 predicted to regulate genes related to light-harvesting complex proteins. Our data showed that prolonged preconditioning in severe light fluctuation enhanced photosynthesis in P. tricornutum under this condition, as evidenced by increased oxygen evolution accompanied by the upregulation of Rubisco and light-harvesting proteins. Furthermore, severe light fluctuation diverted the metabolic flux of assimilated carbon preferentially toward fatty acid storage over sugar and protein. Our results suggest that P. tricornutum use a series of complex and different responsive schemes in photosynthesis and carbon metabolism to optimize their growth under mild and severe light fluctuations. These insights underscore the importance of using more intense conditions when investigating the resilience of phytoplankton to light fluctuations.

Low Light Increases the Abundance of Light Reaction Proteins: Proteomics Analysis of Maize (Zea mays L.) Grown at High Planting Density

Maize (Zea mays L.) is usually planted at high density, so most of its leaves grow in low light. Certain morphological and physiological traits improve leaf photosynthetic capacity under low light, but how light absorption, transmission, and transport respond at the proteomic level remains unclear. Here, we used tandem mass tag (TMT) quantitative proteomics to investigate maize photosynthesis-related proteins under low light due to dense planting, finding increased levels of proteins related to photosystem II (PSII), PSI, and cytochrome b₆f. These increases likely promote intersystem electron transport and increased PSI end electron acceptor abundance. OJIP transient curves revealed increases in some fluorescence parameters under low light: quantum yield for electron transport (φE_o), probability that an electron moves beyond the primary acceptor Q_A^- (ψ_o), efficiency/probability of electron transfer from intersystem electron carriers to reduction end electron acceptors at the PSI acceptor side (δR_o), quantum yield for reduction of end electron acceptors at the PSI acceptor side (φR_o), and overall performance up to the PSI end electron acceptors (PI_total). Thus, densely planted maize shows elevated light utilization through increased electron transport efficiency, which promotes coordination between PSII and PSI, as reflected by higher apparent quantum efficiency (AQE), lower light compensation point (LCP), and lower dark respiration rate (R_d).