Polycomb proteins control floral determinacy by H3K27me3-mediated repression of pluripotency genes in Arabidopsis thaliana

Abstract

Polycomb group (PcG) protein-mediated histone methylation (H3K27me3) controls the correct spatiotemporal expression of numerous developmental regulators in Arabidopsis. Epigenetic silencing of the stem cell factor WUS in floral meristems (FMs) depends on H3K27me3 deposition by PcG proteins. However, the role of H3K27me3 in silencing of other meristematic regulator and pluripotency genes during FM determinacy has not yet been studied. To this end, we report the genome-wide dynamics of H3K27me3 levels during FM arrest and the consequences of strongly depleted PcG activity on early flower morphogenesis including enlarged and indeterminate FMs. Strong depletion of H3K27me3 levels results in misexpression of the FM identity gene AGL24, which partially leads to floral reversion causing ap1-like flowers and indeterminate FMs expressing ectopically WUS and STM. Loss of STM can rescue supernumerary floral organs and FM indeterminacy in H3K27me3-deficient flowers indicating that the hyperactivity of the FMs is at least partially a result of ectopic STM expression. Nonetheless, WUS remained essential for the FM activity. Our results demonstrate that PcG proteins promote FM determinacy at multi-levels of the floral gene regulatory network, silencing initially floral regulators like AGL24 that promotes FM indeterminacy, and subsequently, meristematic pluripotency genes such as WUS and STM during FM arrest.

The plant stem-cell niche and pluripotency: 15 years of an epigenetic perspective

“…In flower stage 6, KNU represses CLV3 and WUS (Shang et al, 2021). Many of these transcriptional regulations are supported or driven by changes in H3K4me3 (K4m) or H3K27me3 (K27m), which is also confirmed by the flower indeterminacy phenotypes by loss of H3K27me3 demethylases REF6, ELF6 and JMJ13 or PRC2 (Yan et al, 2018;Müller-Xing et al, 2022). Other genes directly or indirectly involved in WUS silencing: ARGONAUTE1 (AGO1), AUXIN RESPONSE TRANSCRIPTION FACTOR3 (ARF3/ETT), CRABS CLAW (CRC), FAR-RED ELONGATED HYPOCOTYLS3 (FHY3), PERIANTHIA (PAN), REBELOTE (RBL), SQUINT (SQN), YUCCA4 (YUC4) and the HD-ZIP class III transcription factors CORONA (CNA), PHABULOSA (PHB), PHAVOLUTA (PHV) and REVOLUTA (REV).…”

“…We recently revealed that during FM arrest also several other pluripotency genes, including STM and other TALE KNOX genes, are silenced by H3K27me3 (Figure 1F). This Frontiers in Plant Science frontiersin.org synchronized silencing of several pluripotency genes could accelerate FM determinacy in a way that cannot be achieved by silencing WUS alone (Müller-Xing et al, 2022).…”

“…Strongly depleted PRC2 function results in enlarged SAMs with increased STM expression levels and expanded expression domain of the stem-cell marker CLV3 , while WUS expression and domain size were decreased, indicating an uncoupling of stem-cell fate and WUS expression levels ( Müller-Xing et al., 2014a ; Müller-Xing et al., 2015 ; Müller-Xing et al., 2022 ). This downregulation of WUS might be caused by upregulation of WUS repressors such as KNU that is an H3K27me3-target.…”

“…Other genes directly or indirectly involved in WUS silencing: ARGONAUTE1 (AGO1), AUXIN RESPONSE TRANSCRIPTION FACTOR3 (ARF3/ETT), CRABS CLAW (CRC), FAR-RED ELONGATED HYPOCOTYLS3 (FHY3), PERIANTHIA (PAN), REBELOTE (RBL), SQUINT (SQN), YUCCA4 (YUC4) and the HD-ZIP class III transcription factors CORONA (CNA), PHABULOSA (PHB), PHAVOLUTA (PHV) and REVOLUTA (REV). (F) GRN of floral stem-cell determinacy sustained by changes in H3K27me3 levels at gene loci of pluripotency genes and other key regulators (after ( Müller-Xing et al., 2022 ), modified). STM enhances binding of WUS to the CLV3 chromatin through STM-WUS heterodimerization ( Su et al., 2020 ).…”

IBPred: A sequence-based predictor for identifying ion binding protein in phage

“…Many machine learning algorithms, such as support vector machine (SVM) [10] , [11] , [12] , deep learning (DL) [13] , [14] , [15] , [16] , [17] , [18] , [19] , extreme boosting algorithm (XGBoost) [20] , [21] , [22] , [23] , [24] , and stacking ensemble models [25] , [26] , [27] , [28] , [29] , [30] , etc., have been developed for protein function, structure, subcellular localization, and even other biological processes. Different feature descriptors such as amino acid composition (AAC) [31] , [32] , [33] , reduced amino acid composition [34] , [35] , [36] , g -gap dipeptide composition [37] , [38] , and secondary structure features [39] , etc., were adopted to represent protein sequences. While there is still no computational method to identify IBPs in phages, this study aims to design a novel model for IBP prediction.…”