High light can alleviate chilling stress in maize

Abstract

Chilling stress has the potential to significantly decrease growth and yield of sensitive crop plants such as maize. Based on previous work, high light during chilling may exacerbate stress via enhanced photoinhibition but may also aid acclimation responses to chilling. To further understand molecular processes behind responses to chilling with and without high light, two maize accessions with contrasting tolerance (B73 and F7) were exposed to three treatments: chilling, chilling combined with high light and high light alone. Transcriptome data indicated that the chilling treatment resulted in the largest stress response. Addition of high light to chilling stress had a mitigating, rather than additive effect on stress, as evident from alleviated repression of photosynthesis-related genes and less induction of stress-related pathways such as abscisic acid signalling and senescence compared with the response to chilling alone. Five transcription factors belonging to well-known stress-related transcription factor families were identified as candidates for driving the transcriptional changes behind the high-light induced mitigation of chilling stress. Physiological measurements of non-photochemical quenching and the maximum quantum efficiency of photosystem II corroborated the transcriptome results, showing that the addition of high light alleviated photoinhibition and membrane damage caused by chilling. High light alone had little effect on the plant transcriptome or physiological response. Overall, this study overturns previous reports, offers a new outlook on the impact of high light during chilling stress and has the potential to provide clearer targets for crop engineering.

The genetic basis of dynamic non-photochemical quenching and photosystem II efficiency in fluctuating light reveals novel molecular targets for maize (Zea mays) improvement

“…From the 188 gene models within the QTL confidence interval (Supplemental Table S4), expression levels of 10 genes were significantly correlated with the founder QTL effects (Supplemental Table S5). These genes included the minor PSII antenna CP24 (lhcb6) expression of which was significantly reduced in F7 based on both RNA-seq data representing all founder lines, as well as based on independent expression data for F7 and B73 (Figure 6C) from Cackett et al, (2023) Since CP24 is known to affect the structure and function of the PSII light harvesting antenna in Arabidopsis (Kovács et al, 2006), we decided to further explore a causative link with the QTL effects observed here. Immunoblot analysis of B73 and F7 using a CP24-specific antibody confirmed that F7 had severely reduced CP24 protein abundance compared to B73 (Figure 6F), which was consistent with a decreased abundance of higher order PSII-LHCII super complexes in blue native PAGE analysis of purified thylakoid membranes from both founder lines (Figure 6G) indicating significant truncation of PSII antenna size associated with the F7 haplotype.…”

“…(A) Chromosome 10 QTL for Fv/Fm (B) Founder QTL effects at chromosome ten QTL (C) Difference in expression of CP24 between B73 and F7 from Cackett et al . (2023).…”

“…From the 188 gene models within the QTL confidence interval (Supplemental Table S4), expression levels of 10 genes were significantly correlated with the founder QTL effects (Supplemental Table S5). These genes included the minor PSII antenna CP24 (lhcb6) expression of which was significantly reduced in F7 based on both RNA-seq data representing all founder lines, as well as based on independent expression data for F7 and B73 (Figure 6C) from Cackett et al, (2023) Since CP24 is known to affect the structure and function of the PSII light harvesting antenna in Arabidopsis (Kovács et al, 2006), we decided to further explore a causative link with the QTL effects observed here.…”

“…Transcript abundances were extracted and normalized using r/edgeR (Robinson et al, 2010). For QTL where founder effects were distinct between B73 and F7, we additionally queried gene expression difference between these two founders utilizing the RNAseq datasets described in (Lee Cackett et al, 2023).…”