Increased ambient temperature is inhibitory to plant immunity including auto-immunity. SNC1-dependent auto-immunity is, for example, fully suppressed at 28°C. We found that the Arabidopsis sumoylation mutant siz1 displays SNC1-dependent auto-immunity at 22°C but also at 28°C, which was EDS1 dependent at both temperatures. This siz1 auto-immune phenotype provided enhanced resistance to Pseudomonas at both temperatures. Moreover, the rosette size of siz1 recovered only weakly at 28°C, while this temperature fully rescues the growth defects of other SNC1-dependent auto-immune mutants. This thermo-insensitivity of siz1 correlated with a compromised thermosensory growth response, which was independent of the immune regulators PAD4 or SNC1. Our data reveal that this high temperature induced growth response strongly depends on COP1, while SIZ1 controls the amplitude of this growth response. This latter notion is supported by transcriptomics data, i.e. SIZ1 controls the amplitude and timing of high temperature transcriptional changes including a subset of the PIF4/BZR1 gene targets. Combined our data signify that SIZ1 suppresses an SNC1-dependent resistance response at both normal and high temperatures. At the same time, SIZ1 amplifies the dark and high temperature growth response, likely via COP1 and upstream of gene regulation by PIF4 and BRZ1.
Summary Aging and age-related pathology is a result of a still incompletely-understood intricate web of molecular and cellular processes. We present a C57BL/6J female mice in vivo aging study of five organs (liver, kidney, spleen, lung and brain), in which we compare genome-wide gene expression profiles during chronological aging with pathological changes throughout the entire murine lifespan (13, 26, 52, 78, 104 and 130 weeks). Relating gene expression changes to chronological aging revealed many differentially expressed genes (DEGs) and altered gene-sets (AGSs) were found in most organs, indicative of intra-organ generic aging processes. However, only ≤ 1% of these DEGs are found in all organs. For each organ, at least one of 18 tested pathological parameters showed a good age-predictive value, albeit with much inter- and intra-individual (organ) variation. Relating gene expression changes to pathology-related aging revealed correlated genes and gene-sets, which made it possible to characterize the difference between biological and chronological aging. In liver, kidney and brain, a limited number of overlapping pathology-related AGSs were found. Immune responses appeared to be common, yet the changes were specific in most organs. Furthermore, changes were observed in energy homeostasis, reactive oxygen species, cell cycle, cell motility and DNA damage. Comparison of chronological and pathology-related AGSs revealed substantial overlap and interesting differences. For example, the presence of immune processes in liver pathology-related AGSs which were not detected in chronological aging. The many cellular processes that are only found employing aging–related pathology could provide important new insights into the progress of aging.
Maternal mRNA present in mature oocytes plays an important role in the proper development of the early embryo. As the composition of the maternal transcriptome in general has been studied with pooled mature eggs, potential differences between individual eggs are unknown. Here we present a transcriptome study on individual zebrafish eggs from clutches of five mothers in which we focus on the differences in maternal mRNA abundance per gene between and within clutches. To minimize technical interference, we used mature, unfertilized eggs from siblings. About half of the number of analyzed genes was found to be expressed as maternal RNA. The expressed and non-expressed genes showed that maternal mRNA accumulation is a non-random process, as it is related to specific biological pathways and processes relevant in early embryogenesis. Moreover, it turned out that overall the composition of the maternal transcriptome is tightly regulated as about half of the expressed genes display a less than twofold expression range between the observed minimum and maximum expression values of a gene in the experiment. Even more, the maximum gene-expression difference within clutches is for 88% of the expressed genes lower than twofold. This means that expression differences observed in maternally expressed genes are primarily caused by differences between mothers, with only limited variability between eggs from the same mother. This was underlined by the fact that 99% of the expressed genes were found to be differentially expressed between any of the mothers in an ANOVA test. Furthermore, linking chromosome location, transcription factor binding sites, and miRNA target sites of the genes in clusters of distinct and unique mother-specific gene-expression, suggest biological relevance of the mother-specific signatures in the maternal transcriptome composition. Altogether, the maternal transcriptome composition of mature zebrafish oocytes seems to be tightly regulated with a distinct mother-specific signature.
Aims/hypothesis Type 2 diabetes is a complex metabolic disease with increasing prevalence worldwide. Improving the prediction of incident type 2 diabetes using epigenetic markers could help tailor prevention efforts to those at the highest risk. The aim of this study was to identify predictive methylation markers for incident type 2 diabetes by combining epigenome-wide association study (EWAS) results from five prospective European cohorts. Methods We conducted a meta-analysis of EWASs in blood collected 7–10 years prior to type 2 diabetes diagnosis. DNA methylation was measured with Illumina Infinium Methylation arrays. A total of 1250 cases and 1950 controls from five longitudinal cohorts were included: Doetinchem, ESTHER, KORA1, KORA2 and EPIC-Norfolk. Associations between DNA methylation and incident type 2 diabetes were examined using robust linear regression with adjustment for potential confounders. Inverse-variance fixed-effects meta-analysis of cohort-level individual CpG EWAS estimates was performed using METAL. The methylGSA R package was used for gene set enrichment analysis. Confirmation of genome-wide significant CpG sites was performed in a cohort of Indian Asians (LOLIPOP, UK). Results The meta-analysis identified 76 CpG sites that were differentially methylated in individuals with incident type 2 diabetes compared with control individuals (p values <1.1 × 10−7). Sixty-four out of 76 (84.2%) CpG sites were confirmed by directionally consistent effects and p values <0.05 in an independent cohort of Indian Asians. However, on adjustment for baseline BMI only four CpG sites remained genome-wide significant, and addition of the 76 CpG methylation risk score to a prediction model including established predictors of type 2 diabetes (age, sex, BMI and HbA1c) showed no improvement (AUC 0.757 vs 0.753). Gene set enrichment analysis of the full epigenome-wide results clearly showed enrichment of processes linked to insulin signalling, lipid homeostasis and inflammation. Conclusions/interpretation By combining results from five European cohorts, and thus significantly increasing study sample size, we identified 76 CpG sites associated with incident type 2 diabetes. Replication of 64 CpGs in an independent cohort of Indian Asians suggests that the association between DNA methylation levels and incident type 2 diabetes is robust and independent of ethnicity. Our data also indicate that BMI partly explains the association between DNA methylation and incident type 2 diabetes. Further studies are required to elucidate the underlying biological mechanisms and to determine potential causal roles of the differentially methylated CpG sites in type 2 diabetes development. Graphical abstract
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.