Dormancy and endosperm presence influence the ex situ conservation potential in central European calcareous grassland plants

Tausch, Simone; Leipold, Martin; Reisch, Christoph

doi:10.1093/aobpla/plz035

Cited by 14 publications

(20 citation statements)

References 71 publications

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“…The former finding agrees well with the studies by Thompson et al, (2003) and Gioria et al (2020), which demonstrated that seed dormancy is an important mechanism promoting seed persistence in the soil but, overall, is a poor predictor of SSB characteristics. The weak predictive power of endosperm presence in inferring SSB characteristics supports the conclusion by Long et al (2015) that this trait, which can nevertheless serve as a good proxy for seed longevity in storage (Probert et al, 2009;Tausch et al, 2019), does not reflect species ability to persist in soil.…”

Section: Relative Importance Of Environmental Characteristics Seed Traits and Phylogeny In Predicting Ssb Characteristicssupporting

confidence: 67%

Machine learning algorithms predict soil seed bank persistence from easily available traits

Rosbakh

Pichler

Poschlod

2022

Preprint

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Question: Soil seed banks (SSB), i.e., pools of viable seeds in the soil and its surface, play a crucial role in plant biology and ecology. Information on seed persistence in soil is of great importance for fundamental and applied research, yet compiling datasets on this trait still requires enormous efforts. We asked whether the machine learning (ML) approach could be used to infer and predict SSB properties of a regional flora based on easily available data. Location: Eighteen calcareous grasslands located along an elevational gradient of almost 2000 m in the Bavarian Alps, Germany. Methods: We compared a commonly used ML model (random forest) with a conventional model (linear regression model) as to their ability to predict SSB presence/absence and density using empirical data on SSB characteristics (environmental, seed traits and phylogenetic predictors). Further, we identified the most important determinants of seed persistence in soil for predicting qualitative and quantitative SSB characteristics using the ML approach. Results: We demonstrated that the ML model predicts SSB characteristics significantly better than the linear regression model. A single set of predictors (either environment, or seed traits, or phylogenetic eigenvectors) was sufficient for the ML model to achieve high performance in predicting SSB characteristics. Importantly, we established that a few widely available SSB predictors can achieve high predictive power in the ML approach, suggesting a high flexibility of the developed approach for use in various study systems. Conclusions: Our study provides a novel methodological approach that combines empirical knowledge on the determinants of SSB characteristics with a modern, flexible statistical approach based on ML. It clearly demonstrates that ML can be developed into a key tool to facilitate labor-intensive, costly and time-consuming functional trait research.

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Section: Relative Importance Of Environmental Characteristics Seed Traits and Phylogeny In Predicting Ssb Characteristicssupporting

confidence: 67%

Machine learning algorithms predict soil seed bank persistence from easily available traits

Rosbakh

Pichler

Poschlod

2022

Preprint

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“…The germination ratio was measured at 7 d of growth in Murashige & Skoog (MS) medium (Supporting Information Methods S1, S2). Calculation of probit curve and P50 value was performed using the R package drc (Tausch et al ., 2019).…”

Section: Methodsmentioning

confidence: 99%

Apoplastic lipid barriers regulated by conserved homeobox transcription factors extend seed longevity in multiple plant species

et al. 2021

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Cutin and suberin are lipid polyesters deposited in specific apoplastic compartments. Their fundamental roles in plant biology include controlling the movement of gases, water and solutes, and conferring pathogen resistance. Both cutin and suberin have been shown to be present in the Arabidopsis seed coat where they regulate seed dormancy and longevity.In this study, we use accelerated and natural ageing seed assays, glutathione redox potential measures, optical and transmission electron microscopy and gas chromatography-mass spectrometry to demonstrate that increasing the accumulation of lipid polyesters in the seed coat is the mechanism by which the AtHB25 transcription factor regulates seed permeability and longevity.Chromatin immunoprecipitation during seed maturation revealed that the lipid polyester biosynthetic gene long-chain acyl-CoA synthetase 2 (LACS2) is a direct AtHB25 binding target. Gene transfer of this transcription factor to wheat and tomato demonstrated the importance of apoplastic lipid polyesters for the maintenance of seed viability.Our work establishes AtHB25 as a trans-species regulator of seed longevity and has identified the deposition of apoplastic lipid barriers as a key parameter to improve seed longevity in multiple plant species.

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“…Within 197 species across the globe [44] and 172 Australian species [8], life span of endospermic seeds stored at 45°C and 60% RH were on average 3.3-fold lower than non-endospermic seed. The positive effect of reduced endosperm on seed longevity was recently confirmed on the panel of 39 grassland species from a single habitat [45]. Why the presence of endosperm would reduce longevity remains unknown.…”

Section: Effects Of Maternal Tissues On Seed Longevitymentioning

confidence: 88%

Molecular and environmental factors regulating seed longevity

Zinsmeister

Leprince

Buitink

2020

Biochemical Journal

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Seed longevity is a central pivot of the preservation of biodiversity, being of main importance to face the challenges linked to global climate change and population growth. This complex, quantitative seed quality trait is acquired on the mother plant during the second part of seed development. Understanding what factors contribute to lifespan is one of the oldest and most challenging questions in plant biology. One of these challenges is to recognize that longevity depends on the storage conditions that are experimentally used because they determine the type and rate of deleterious conditions that lead to cell death and loss of viability. In this review, we will briefly review the different storage methods that accelerate the deteriorative reactions during storage and argue that a minimum amount of information is necessary to interpret the longevity data. Next, we will give an update on recent discoveries on the hormonal factors regulating longevity, both from the ABA signaling pathway but also other hormonal pathways. In addition, we will review the effect of both maternal and abiotic factors that influence longevity. In the last section of this review, we discuss the problems in unraveling cause-effect relationship between the time of death during storage and deteriorative reactions leading to seed ageing. We focus on the three major types of cellular damage, namely membrane permeability, lipid peroxidation and RNA integrity for which germination data on seed stored in dedicated seed banks for long period times are now available.

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Dormancy and endosperm presence influence the ex situ conservation potential in central European calcareous grassland plants

Cited by 14 publications

References 71 publications

Machine learning algorithms predict soil seed bank persistence from easily available traits

Machine learning algorithms predict soil seed bank persistence from easily available traits

Apoplastic lipid barriers regulated by conserved homeobox transcription factors extend seed longevity in multiple plant species

Molecular and environmental factors regulating seed longevity

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