A novel TFL1 gene induces flowering in the mast seeding alpine snow tussock, Chionochloa pallens (Poaceae). Issue 3 (25th November 2021)

• Record Type: Journal Article
• Authors: Samarth, ; Lee, Robyn; Kelly, Dave; Turnbull, Matthew H.; Macknight, Richard; Poole, Anthony M.; Jameson, Paula E.
• Is Part Of: Molecular ecology. Volume 31:Issue 3(2022)
• Page Start: 822
• Page End: 838
• Publication Date: 2021-11-25
• Subjects: Anti‐TFL1 -- floral genes -- mast seeding -- PEBP family -- summer temperature -- TFL1 -- transcriptome profiling; Molecular ecology -- Periodicals; Molecular population biology -- Periodicals; 576
• DOI: 10.1111/mec.16273
• Languages: English
• ISSNs: 0962-1083

Abstract

Abstract: Masting, the synchronous, highly variable flowering across years by a population of perennial plants, has been reported to be precipitated by various factors including nitrogen levels, drought conditions, and spring and summer temperatures. However, the molecular mechanism leading to the initiation of flowering in masting plants in particular years remains largely unknown, despite the potential impact of climate change on masting phenology. We studied genes controlling flowering in the alpine snow tussock Chionochloa pallens (Poaceae), a strongly masting perennial grass. We used a range of in situ and manipulated plants to obtain leaf samples from tillers (shoots) which subsequently remained vegetative or flowered. Here, we show that a novel orthologue of TERMINAL FLOWER 1 ( TFL1 ; normally a repressor of flowering in other species) promotes the induction of flowering in C. pallens (hence Anti ‐ TFL1 ), a conclusion supported by structural, functional and expression analyses. Global transcriptomic analysis indicated differential expression of CpTPS1, CpGA20ox1, CpREF6 and CpHDA6, emphasizing the role of endogenous cues and epigenetic regulation in terms of responsiveness of plants to initiate flowering. Our molecular‐based study provides insights into the cellular mechanism of flowering in masting plants and will supplement ecological and statistical models to predict how masting will respond to global climate change.