Network properties underlying seed germination control

We sought to gain a mechanistic understanding of the control of seed dormancy and germination by hormone balance. The field has matured to a stage where most of the key genes are known, and competing hypotheses have been proposed to explain how hormone balance works in seeds. During the meeting we simplified a more complex model of seed germination (Figure 1), reducing it to a tractable network. We then showed that if considered as a set of competing protein complexes the network took on the properties of a switch. Results from two models of the reduced network, which incorporated the biological switching phenomena, were found to be in good agreement with both wild and mutant phenotypic data. Our models made the novel prediction that one complex in particular was key to promoting germination, and this prediction can now be tested in the laboratory

Yield instability of winter oilseed rape modulated by early winter temperature

Yield stability is a major problem in oilseed rape with inter-annual variation accounting for between 30–50% of the crop value among the major global rapeseed producers. The United Kingdom has persistent problems with yield instability, but the underlying causes remain unclear. We tested whether temperature plays a role in UK winter oilseed rape (WOSR) yield variation through analysis of aggregated country-wide on-farm yield data and in annual Recommended List variety trial data run by the UK Agriculture and Horticulture Development Board (AHDB). Our analyses of the two independent datasets both show that mean temperature in early winter is strongly and uniquely linked to variation in WOSR yield, with a rise in mean temperature of 1 °C associated with an average reduction of 113 (+−21) kg ha−1 in yield. We propose that understanding the mechanism by which early winter chilling affects WOSR yield will enable the breeding of varieties with a more stable and resilient yield in Western Europe as climatic variation increases

Direct measurement of transcription rates reveals multiple mechanisms for configuration of the Arabidopsis ambient temperature response

Background Sensing and responding to ambient temperature is important for controlling growth and development of many organisms, in part by regulating mRNA levels. mRNA abundance can change with temperature, but it is unclear whether this results from changes in transcription or decay rates, and whether passive or active temperature regulation is involved. Results Using a base analog labelling method, we directly measured the temperature coefficient, Q10, of mRNA synthesis and degradation rates of the Arabidopsis transcriptome. We show that for most genes, transcript levels are buffered against passive increases in transcription rates by balancing passive increases in the rate of decay. Strikingly, for temperature-responsive transcripts, increasing temperature raises transcript abundance primarily by promoting faster transcription relative to decay and not vice versa, suggesting a global transcriptional process exists that controls mRNA abundance by temperature. This is partly accounted for by gene body H2A.Z which is associated with low transcription rate Q10, but is also influenced by other marks and transcription factor activities. Conclusions Our data show that less frequent chromatin states can produce temperature responses simply by virtue of their rarity and the difference between their thermal properties and those of the most common states, and underline the advantages of directly measuring transcription rate changes in dynamic systems, rather than inferring rates from changes in mRNA abundance. Background The mechanism for ambient temperature sensing in plants is unclear. Control of transcript levels is believed to be important in responses to temperature [1-4] but affects of ambient temperature on transcription and mRNA decay rates have not been measured. According to the work of Arrhenius [5] the temperature coefficient (Q10) of biochemical reactions is expected to be 2 to 3 at biological temperatures: yet less than 2% of Arabidopsis thaliana genes have a two-fold or greater difference in expression level between 17°C and 27°C [6]. The remaining genes either have rates buffered against changing temperatures, or passive increases in transcription rate must be offset by a balanced increase in decay rate, leading to higher turnover but static steady state levels. Despite this fundamental uncertainty, steady state transcriptomic responses to ambient temperature have been used to infer a role for chromatin modifications in temperature signaling [2,7]. 4-Thiouracil (4SU) is a non-toxic base analogue that has been shown to be incorporated into mammalian and yeast mRNA during transcription [8-12]. Biotinylation and column separation allow 4SU-labeled RNA to be separated from unlabeled RNA, and transcriptomic analysis using the separated samples can be used to simultaneously calculate mRNA synthesis and decay rates [8]. Here we use 4SU labeling to measure transcription rates and determine the Q10 genome-wide of mRNA synthesis and decay rates in Arabidopsis thaliana. We show that ambient temperature has large passive effects on both mRNA synthesis and decay rates, and that where temperature controls transcript abundance it does so by regulating transcription relative to decay and not vice versa. Our analysis suggests that transcription factor binding sites and epigenetic state combine to create a complex network of temperature responses in plants. Results Cells incorporate 4SU into RNA and this has been exploited in mammalian cells [8,11,12] and in yeast [13] to measure mRNA synthesis and decay rates. In order to determine whether plants can take up 4SU we floated intact seedlings in MS medium and monitored 4SU incorporation into RNA by biotinylation and dot blot (Figure S1a in Additional file 1). This clearly showed that plants incorporate 4SU from the environment into RNA and that concentrations as low as 1 mM lead to a signal detectable above background within 1 hour (Figure 1B). The resulting RNA could be separated from unlabeled RNA by biotinylation and passage through a streptavidin column as described previously. At 1.5 mM the flow-through can be depleted of detectable 4SU-labeled RNA, whilst labeled plant RNA is highly concentrated in the fraction recovered from the column [8,13] (Figure S1c in Additional file 1). To maximize recovery we chose a low concentration of 4SU at 1.5 mM [8] as high labeling frequencies are known to lead to binding of fewer more frequently labeled transcripts to the columns and reduce recovery. At this concentration Arabidopsis plants treated with 4SU showed the same growth and survival as control plants (Figure S2a in Additional file 1), suggesting 4SU has low toxicity in plants, as in other organisms. Therefore, 4SU dynamics in Arabidopsis seedlings resemble those described for other experimental systems. Preliminary experiments showed that RNA turnover was faster at 27°C compared to 12°C (Figure S2b in Additional file 1), suggesting that temperature generally affected transcription rates

Combining historical agricultural and climate datasets sheds new light on early 20th century barley performance

Barley (Hordeum vulgare ssp. vulgare) is cultivated globally across a wide range of environments, both in highly productive agricultural systems and in subsistence agriculture and provides valuable feedstock for the animal feed and malting industries. However, as the climate changes there is an urgent need to identify adapted barley varieties that will consistently yield highly under increased environmental stresses. Our ability to predict future local climates is only as good as the skill of the climate model, however we can look back over 100 years with much greater certainty. Historical weather datasets are an excellent resource for identifying causes of historical yield variability. In this research we combined recently digitised historical weather data from the early 20th century with published Irish spring barley trials data for two heritage varieties: Archer and Goldthorpe, following an analysis first published by Student in 1923. Using linear mixed models, we show that interannual variation in observed spring barley yields can be partially explained by recorded weather variability, in particular July maximum temperature and rainfall, and August maximum temperature. We find that while Archer largely yields more highly, Goldthorpe is more stable under wetter growing conditions, highlighting the importance of considering growing climate in variety selection. Furthermore, this study demonstrates the benefits of access to historical trials and climatic data and the importance of incorporating climate data in modern day breeding programmes to improve climate resilience of future varieties

Trait analysis reveals DOG1 determines initial depth of seed dormancy, but not changes during dormancy cycling that result in seedling emergence timing.

Seedling emergence timing is crucial in competitive plant communities and so contributes to species fitness. To understand the mechanistic basis of variation in seedling emergence timing, we exploited the contrasting behaviour of two Arabidopsis ecotypes; Cape Verde island (Cvi) and Burren (Bur-0). We used RNAseq analysis of RNA from exhumed seeds and quantitative trait loci (QTL) analyses on a mapping population from crossing the Cvi and Bur-0 ecotypes. We determined genome-wide expression patterns over an annual dormancy cycle in both ecotypes identifying nine major clusters based on the seasonal timing of gene expression, and variation in behaviour between them. QTL were identified for depth of seed dormancy and Seedling Emergence Timing (SET). Both analyses showed a key role for DOG1 in determining depth of dormancy, but did not support a direct role for DOG1 in generating altered seasonal patterns of seedling emergence. The principle QTL determining Seedling Emergence Timing (SET1: dormancy cycling) is physically close on chromosome 5, but distinct from DOG1. We show that SET1 and two other SET QTLs each contain a candidate gene (AHG1, ANAC60, PDF1 respectively) closely associated to DOG1 and abscisic acid signalling and suggest a model for the control of SET in the field

Continuing genetic improvement and biases in genetic gain estimates revealed in historical UK variety trials data

Context The current pace of yield increase for major crops is not fast enough to meet future demand. Crop breeding programmes are under increasing pressure to improve existing crops further. Quantifying the contribution of these programmes to observed yield increases is important for evaluating their success and identifying if crop improvement goals are likely to be met. Objective In this paper we explore methods to study the genetic gain of two cereal species, wheat (Triticum aestivum L.) and barley (Hordeum vulgare L.). Specifically, the objective of this research was to identify sources of bias in genetic gain estimates of UK variety trials data. Methods Genetic gain was estimated for fungicide-treated and untreated UK winter wheat, winter barley and spring barley for 1982–2018 using UK National List and Recommended List variety trials data. Subsets of the winter wheat variety trials dataset were used to replicate shorter breeding cycles to quantify the impact of the number and choice of long-term check varieties on estimating genetic gain. Results While genetic and non-genetic contributions to changes in UK cereal performance are in line with previous estimates, we were able to identify previously undetected changes and biases in estimates of variety performance. Specifically, we observed an increasing yield difference between fungicide treated and untreated variety trials as varieties age, driven by both a breakdown in disease resistance and a previously unobserved long-term increase in yield as varieties age in treated trials. This shows that yields of long-term check varieties cannot be assumed to be stable over time. We found that genetic gain estimates were highly sensitive to the long-term check varieties chosen, whilst the inclusion of multiple checks decreased the standard error of the estimate. Conclusion The estimation of genetic gain is highly susceptible to bias. We provide recommendations on how to reduce the risk of bias for estimating genetic gain. Implications Accounting for sources of bias in genetic gain calculations is important in any programme of selection to prevent inaccurate quantification of yield progress

Regulation of Arabidopsis thaliana seed dormancy and germination by 12-oxo-phytodienoic acid.

We previously demonstrated that the oxylipin 12-oxo-phytodienoic acid (OPDA) acts along with abscisic acid to regulate seed germination in Arabidopsis thaliana, but the mechanistic details of this synergistic interaction remain to be elucidated. Here, we show that OPDA acts through the germination inhibition effects of abscisic acid, the abscisic acid-sensing ABI5 protein, and the gibberellin-sensing RGL2 DELLA protein. We further demonstrate that OPDA also acts through another dormancy-promoting factor, MOTHER-OF-FT-AND-TFL1 (MFT). Both abscisic acid and MFT positively feed back into the OPDA pathway by promoting its accumulation. These results confirm the central role of OPDA in regulating seed dormancy and germination in A. thaliana and underline the complexity of interactions between OPDA and other dormancy-promoting factors such as abscisic acid, RGL2, and MFT

SeedGerm: a cost‐effective phenotyping platform for automated seed imaging and machine‐learning based phenotypic analysis of crop seed germination

Efficient seed germination and establishment are important traits for field and glasshouse crops. Large-scale germination experiments are laborious and prone to observer errors, leading to the necessity for automated methods. We experimented with five crop species, including tomato, pepper, Brassica, barley, and maize, and concluded an approach for large-scale germination scoring. Here, we present the SeedGerm system, which combines cost-effective hardware and open-source software for seed germination experiments, automated seed imaging, and machine-learning based phenotypic analysis. The software can process multiple image series simultaneously and produce reliable analysis of germination- and establishment-related traits, in both comma-separated values (CSV) and processed images (PNG) formats. In this article, we describe the hardware and software design in detail. We also demonstrate that SeedGerm could match specialists’ scoring of radicle emergence. Germination curves were produced based on seed-level germination timing and rates rather than a fitted curve. In particular, by scoring germination across a diverse panel of Brassica napus varieties, SeedGerm implicates a gene important in abscisic acid (ABA) signalling in seeds. We compared SeedGerm with existing methods and concluded that it could have wide utilities in large-scale seed phenotyping and testing, for both research and routine seed technology applications

Custom Integrated Circuits

Contains reports on seven research projects.U.S. Air Force - Office of Scientific Research (Contract F49620-84-C-0004)National Science Foundation (Grant ECS81-18160)Defense Advanced Research Projects Agency (Contract NOO14-80-C-0622)National Science Foundation (Grant ECS83-10941