A temporal switch model for estimating transcriptional activity in gene expression

Motivation: The analysis and mechanistic modelling of time series gene expression data provided by techniques such as microarrays, NanoString, reverse transcription–polymerase chain reaction and advanced sequencing are invaluable for developing an understanding of the variation in key biological processes. We address this by proposing the estimation of a flexible dynamic model, which decouples temporal synthesis and degradation of mRNA and, hence, allows for transcriptional activity to switch between different states. Results: The model is flexible enough to capture a variety of observed transcriptional dynamics, including oscillatory behaviour, in a way that is compatible with the demands imposed by the quality, time-resolution and quantity of the data. We show that the timing and number of switch events in transcriptional activity can be estimated alongside individual gene mRNA stability with the help of a Bayesian reversible jump Markov chain Monte Carlo algorithm. To demonstrate the methodology, we focus on modelling the wild-type behaviour of a selection of 200 circadian genes of the model plant Arabidopsis thaliana. The results support the idea that using a mechanistic model to identify transcriptional switch points is likely to strongly contribute to efforts in elucidating and understanding key biological processes, such as transcription and degradation

Evidence for HI replenishment in massive galaxies through gas accretion from the cosmic web

We examine the H i -to-stellar mass ratio (H i fraction) for galaxies near filament backbones within the nearby Universe (d < 181 Mpc). This work uses the 6 degree Field Galaxy Survey (6dFGS) and the Discrete Persistent Structures Extractor (DisPerSE) to define the filamentary structure of the local cosmic web. H i spectral stacking of H i Parkes All Sky Survey (HIPASS) observations yield the H i fraction for filament galaxies and a field control sample. The H i fraction is measured for different stellar masses and 5th nearest neighbour projected densities (Σ5) to disentangle what influences cold gas in galaxies. For galaxies with stellar masses log(M⋆) ≤ 11 M⊙ in projected densities 0 ≤ Σ5 < 3 galaxies Mpc−2, all H i fractions of galaxies near filaments are statistically indistinguishable from the control sample. Galaxies with stellar masses log(M⋆) ≥ 11 M⊙ have a systematically higher H i fraction near filaments than the control sample. The greatest difference is 0.75 dex, which is 5.5σ difference at mean projected densities of 1.45 galaxies Mpc−2. We suggest that this is evidence for massive galaxies accreting cold gas from the intra-filament medium which can replenish some H i gas. This supports cold mode accretion where filament galaxies with a large gravitational potential can draw gas from the large scale structure

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

The regional weed vegetation in organic spring-sown cereals as shaped by local management, crop diversity and site

Bundesweit hat Mecklenburg Vorpommern einen sehr hohen Anteil an Ökologischer Landwirtschaft. Nach wie vor sind Unkräuter eine Herausforderung in diesen Agrarsystemen. Agrobiodiversität zu fördern, hat in Deutschland einen zunehmenden Stellenwert. Vor diesem Hintergrund sollten Unkräuter einerseits in langfristig handhabbaren Größenordnungen bleiben, andererseits aber auch eine artenreiche Flora bilden. Unser Ziel ist es, zu untersuchen, ob diese beiden Aspekte durch ein vielseitiges Management der Kulturpflanzen unterstützt werden können. Dafür wurden Unkraut und Management Daten von Sommergetreideflächen ökologisch wirtschaftender Betriebe in Mecklenburg-Vorpommern über zwei Jahre (2015-2016) erfasst. Die Auswirkungen von lokalen Umwelt- und Management-Faktoren auf die Unkrautgemeinschaften wurden multivariat analysiert und im Anschluss wurden Effekte der Variablen zur Kulturvielfalt separat untersucht. Wir fanden grundlegende Unterschiede in den Einflüssen des kurzfristigen Anbaumanagements, der langfristigen Kulturvielfaltsstrategien und den eher beständigen Standortfaktoren. Während Unkrautdichten vor allem durch direktes Management beeinflusst werden, verändern sich Unkrautartenvielfalt und –gemeinschaften, wenn Maßnahmen der Kulturvielfalt angewendet werden.Mecklenburg Vorpommern has one of the highest percentages of organic arable production nationwide. Weeds remain to be the main challenge within this agricultural system. There is also an increase in the national support of agrobiodiversity. Weeds should therefore be continuously kept within manageable limits, while on the other side encourage a specie rich weed flora. Our objective is to investigate to which extent these two aspects can be addressed through the use of diversified crop management. In order to research this objective, weed and management data of spring sown cereal crops were obtained from organic farms in the region over the course of two years (2015-2016). The impact of the local environment and management factors on the occurring weed communities was studied in multivariate analysis approaches, followed by the separate crop diversity effects. We found a fundamental difference between the workings of the short-term management, the long-term crop diversification strategies and the more continuos site variables on the weed vegetation. Weed densities were mostly affected by direct management, while weed diversity and communities were altered through the application of crop diversity variables

Early Pleistocene Obliquity‐Scale pCO2 Variability at ~1.5 Million Years Ago

In the early Pleistocene, global temperature cycles predominantly varied with ~41‐kyr (obliquity‐scale) periodicity. Atmospheric greenhouse gas concentrations likely played a role in these climate cycles; marine sediments provide an indirect geochemical means to estimate early Pleistocene CO2. Here we present a boron isotope‐based record of continuous high‐resolution surface ocean pH and inferred atmospheric CO2 changes. Our results show that, within a window of time in the early Pleistocene (1.38–1.54 Ma), pCO2 varied with obliquity, confirming that, analogous to late Pleistocene conditions, the carbon cycle and climate covaried at ~1.5 Ma. Pairing the reconstructed early Pleistocene pCO2 amplitude (92 ± 13 μatm) with a comparably smaller global surface temperature glacial/interglacial amplitude (3.0 ± 0.5 K) yields a surface temperature change to CO2 radiative forcing ratio of S[CO2]~0.75 (±0.5) °C−1·W−1·m−2, as compared to the late Pleistocene S[CO2] value of ~1.75 (±0.6) °C−1·W−1·m−2. This direct comparison of pCO2 and temperature implicitly incorporates the large ice sheet forcing as an internal feedback and is not directly applicable to future warming. We evaluate this result with a simple climate model and show that the presumably thinner, though extensive, northern hemisphere ice sheets would increase surface temperature sensitivity to radiative forcing. Thus, the mechanism to dampen actual temperature variability in the early Pleistocene more likely lies with Southern Ocean circulation dynamics or antiphase hemispheric forcing. We also compile this new carbon dioxide record with published Plio‐Pleistocene δ11B records using consistent boundary conditions and explore potential reasons for the discrepancy between Pliocene pCO2 based on different planktic foraminifera.Key PointsEarly Pleistocene pCO2 roughly varied with obliquity cyclesInterglacial pCO2 was similar in the early and late Pleistocene; glacial pCO2 declined over the mid‐Pleistocene transitionDiscrepancies between δ11B values and corresponding pCO2 estimates from G. ruber and T. sacculifer are observed and may indicate evolving vital effectsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/1/palo20675-sup-0004-2018PA003349-S03.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/2/palo20675.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/3/palo20675-sup-0002-2018PA003349-S01.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/4/palo20675_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/5/palo20675-sup-0005-2018PA003349-S04.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/147130/6/palo20675-sup-0003-2018PA003349-S02.pd

Bayesian inference for dynamic transcriptional regulation; the Hes1 system as a case study.

Motivation: In this study we address the problem of estimating the parameters of regulatory networks and provide the first application of Markov chain Monte Carlo (MCMC) methods to experimental data. As a case study we consider a stochastic model of the Hes1 system expressed in terms of stochastic differential equations (SDEs) to which rigorous likelihood methods of inference can be applied. When fitting continuous-time stochastic models to discretely observed time series the lengths of the sampling intervals are important, and much of our study addresses the problem when the data are sparse. Results: We estimate the parameters of an autoregulatory network providing results both for simulated and real experimental data from the Hes1 system. We develop an estimation algorithm using Markov chain Monte Carlo techniques which are flexible enough to allow for the imputation of latent data on a finer time scale and the presence of prior information about parameters which may be informed from other experiments as well as additional measurement error. Availability: Supplementary information is submitted with the paper. Contact

Predictability of individual circadian phase during daily routine for medical applications of circadian clocks

Background: Circadian timing of treatments can largely improve tolerability and efficacy in patients. Thus, drug metabolism and cell cycle are controlled by molecular clocks in each cell, and coordinated by the core body temperature 24-hour rhythm, which is generated by the hypothalamic pacemaker. Individual circadian phase is currently estimated with questionnaire-based chronotype, center-of-rest time, dim light melatonin onset (DLMO), or timing of CBT maximum (acrophase) or minimum (bathyphase). Methods: We aimed at circadian phase determination and read-out during daily routine in volunteers stratified by sex and age. We measured (i) chronotype; (ii) q1min CBT using two electronic pills swallowed 24-hours apart; (iii) DLMO through hourly salivary samples from 18:00 to bedtime; (iv) q1min accelerations and surface temperature at anterior chest level for seven days, using a tele-transmitting sensor. Circadian phases were computed using cosinor and Hidden-Markov modelling. Multivariate regression identified the combination of biomarkers that best predicted core temperature circadian bathyphase. Results: Amongst the 33 participants, individual circadian phases were spread over 5h10min (DLMO), 7h (CBT bathyphase) and 9h10 min (surface temperature acrophase). CBT bathyphase was accurately predicted, i.e. with an error <1h for 78.8% of the subjects, using a new digital health algorithm (INTime), combining time-invariant sex and chronotype score, with computed center-of-rest time and surface temperature bathyphase (adjusted R-squared = 0.637). Conclusion: INTime provided a continuous and reliable circadian phase estimate in real time. This model helps integrate circadian clocks into precision medicine and will enable treatment timing personalisation following further validation