In maize, young kernels that are less competitive and have poor sink activity often abort. Studies have indicated that such poor competitiveness depends, in part, on the regulation by auxin (IAA) and abscisic acid (ABA). However, the mechanisms for such effects remain unclear. We used pollination-blocking and hand-pollination treatments accompanied by multi-omics and physiological tests, to identify underlying mechanism by which IAA and ABA, along with sugar signaling affect kernel development. Results showed that preventing pollination of the primary ears reactivated kernels in the secondary ears and altered both sugar metabolism and hormone signaling pathways. This was accompanied by increased enzyme activities in carbon metabolism and concentrations of glucose and starch, as well as increased levels of IAA and decreased levels of ABA in the reactivated kernels. Positive and negative correlations were observed between IAA, ABA contents and cell wall invertase (CWIN) activity, and glucose contents, respectively. In vitro culture revealed that the expression of genes involved in glucose utilization was upregulated by IAA, but downregulated by ABA. IAA could promote the expression of ABA signaling genes ZmPP2C9 and ZmPP2C13 but downregulated the expression of Zmnced5, an ABA biosynthesis gene, and ZmSnRK2.10, which is involved in ABA signal transduction. However, these genes showed opposite trends when IAA transport was inhibited. To summarize, we suggest a regulatory model for how IAA inhibits ABA metabolism by promoting the smooth utilization of glucose in reactivated young kernels. Our findings highlight the importance of IAA in ABA signaling by regulating glucose production and transport in maize.

Download full-text PDF

Source
http://dx.doi.org/10.1111/ppl.14019DOI Listing

Publication Analysis

Top Keywords

young kernels
12
iaa aba
12
aba
10
iaa
9
abscisic acid
8
reactivated young
8
reactivated kernels
8
aba signaling
8
glucose
6
kernels
5

Similar Publications

This paper explores the evolving landscape of Electromyogram (EMG) signal analysis, focusing on the growing prominence of deep learning (DL) algorithms for hand, wrist, and finger movement recognition. Such algorithms often come with high computational costs, potentially limiting the clinical translation on resource-limited devices and igniting more research on reduced complexity models. This prompts the question: is it time to shift the algorithmic focus in EMG pattern recognition, given the reported performance of some light-weight traditional or hybrid methods emphasizing synergy between different EMG signals? A comparative study is implemented between state-of-the-art deep learning extension for time series classification, denoted as Random Convolutional Kernel Transform (ROCKET), and simple, yet effective pattern recognition methods tailored to exploit basic forms of EMG signal synergies- Waveform Length Phasors (WLPHASOR), Root-Mean-Squared Phasor (RMSPHASOR), and the proposed novel Multi-Signal Waveform Length (MSWL).

View Article and Find Full Text PDF

High-Density Diffuse Optical Tomography (HD-DOT) presents as a promising tool for not only clinical use but also daily monitoring of mental states. This study employed wearable HD-DOT to evaluate mental fatigue, specifically examining the differences in functional near-infrared spectroscopy (fNIRS) data between states of low and high fatigue among healthy participants for data collection. Data processing involved filtering, channel selection, and dimensionality reduction through Uniform Manifold Approximation (UMAP) and Projection, followed by classification using Support Vector Machines (SVM).

View Article and Find Full Text PDF

The association of individual metals in PM with cardiovascular damage has been established in previous studies, but there are fewer studies on co-exposure to multiple metals and potential metabolic alterations in cardiovascular damage. To investigate the early cardiovascular effects of multiple metals and the mediating effects of metabolites, we conducted a panel study on young adults from 2017 Winter to 2018 Autumn in Caofeidian, China. A total of 180 serum samples were analyzed for metabolomic profiles using liquid chromatography-mass spectrometry.

View Article and Find Full Text PDF

The COVID-19 pandemic has underscored the critical need for effective public health strategies to combat infectious diseases. This study examines the epidemiological characteristics and spatial distribution of COVID-19 incidence and mortality in Zanjan Province, northwest Iran, to inform future epidemic preparedness. Using data from 39,739 hospitalized COVID-19 cases recorded between February 2020 and September 2021, sourced from the Medical Care Monitoring Center, we conducted descriptive and geospatial analyses.

View Article and Find Full Text PDF

Identification of the associations between co-exposure to organophosphate flame retardants and thyroid dysfunction and exposure risk factors in residents of Shanghai, China.

Environ Pollut

April 2025

Key Laboratory of the Public Health Safety, Ministry of Education, Department of Environmental Health, School of Public Health, Fudan University, Shanghai, 200032, China; Center for Water and Health, School of Public Health, Fudan University, Shanghai, 200032, China; Key Laboratory of Health Technology Assessment, National Health Commission of the People's Republic of China, Fudan University, Shanghai, 200032, China. Electronic address:

Toxicological studies indicate that organophosphate flame retardants (OPFRs) may cause thyroid dysfunction. However, population epidemiologic evidence is still limited and little is known about the effects of mixed exposures to OPFRs. This study included 436 community residents from Shanghai, China.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!