Seasonal Plasticity in GABA\u3csup\u3eA\u3c/sup\u3e Signaling is Necessary for Restoring Phase Synchrony in the Master Circadian Clock Network

Annual changes in the environment threaten survival, and numerous biological processes in mammals adjust to this challenge via seasonal encoding by the suprachiasmatic nucleus (SCN). To tune behavior according to day length, SCN neurons display unified rhythms with synchronous phasing when days are short, but will divide into two sub-clusters when days are long. The transition between SCN states is critical for maintaining behavioral responses to seasonal change, but the mechanisms regulating this form of neuroplasticity remain unclear. Here we identify that a switch in chloride transport and GABAA signaling is critical for maintaining state plasticity in the SCN network. Further, we reveal that blocking excitatory GABAA signaling locks the SCN into its long day state. Collectively, these data demonstrate that plasticity in GABAA signaling dictates how clock neurons interact to maintain environmental encoding. Further, this work highlights factors that may influence susceptibility to seasonal disorders in humans

Positive Affect Predicts Cerebral Glucose Metabolism in Late Middle-aged Adults.

Positive affect is associated with a number of health benefits; however, few studies have examined the relationship between positive affect and cerebral glucose metabolism, a key energy source for neuronal function and a possible index of brain health. We sought to determine if positive affect was associated with cerebral glucose metabolism in late middle-aged adults (n = 133). Participants completed the positive affect subscale of the Center for Epidemiological Studies Depression Scale at two time points over a two-year period and underwent 18F-fluorodeoxyglucose-positron emission tomography scanning. After controlling for age, sex, perceived health status, depressive symptoms, anti-depressant use, family history of Alzheimer’s disease, APOE ε4 status and interval between visits, positive affect was associated with greater cerebral glucose metabolism across para-/limbic, frontal, temporal and parietal regions. Our findings provide evidence that positive affect in late midlife is associated with greater brain health in regions involved in affective processing and also known to be susceptible to early neuropathological processes. The current findings may have implications for interventions aimed at increasing positive affect to attenuate early neuropathological changes in at-risk individuals

Correction for Johansson et al., An open challenge to advance probabilistic forecasting for dengue epidemics.

Correction for “An open challenge to advance probabilistic forecasting for dengue epidemics,” by Michael A. Johansson, Karyn M. Apfeldorf, Scott Dobson, Jason Devita, Anna L. Buczak, Benjamin Baugher, Linda J. Moniz, Thomas Bagley, Steven M. Babin, Erhan Guven, Teresa K. Yamana, Jeffrey Shaman, Terry Moschou, Nick Lothian, Aaron Lane, Grant Osborne, Gao Jiang, Logan C. Brooks, David C. Farrow, Sangwon Hyun, Ryan J. Tibshirani, Roni Rosenfeld, Justin Lessler, Nicholas G. Reich, Derek A. T. Cummings, Stephen A. Lauer, Sean M. Moore, Hannah E. Clapham, Rachel Lowe, Trevor C. Bailey, Markel García-Díez, Marilia Sá Carvalho, Xavier Rodó, Tridip Sardar, Richard Paul, Evan L. Ray, Krzysztof Sakrejda, Alexandria C. Brown, Xi Meng, Osonde Osoba, Raffaele Vardavas, David Manheim, Melinda Moore, Dhananjai M. Rao, Travis C. Porco, Sarah Ackley, Fengchen Liu, Lee Worden, Matteo Convertino, Yang Liu, Abraham Reddy, Eloy Ortiz, Jorge Rivero, Humberto Brito, Alicia Juarrero, Leah R. Johnson, Robert B. Gramacy, Jeremy M. Cohen, Erin A. Mordecai, Courtney C. Murdock, Jason R. Rohr, Sadie J. Ryan, Anna M. Stewart-Ibarra, Daniel P. Weikel, Antarpreet Jutla, Rakibul Khan, Marissa Poultney, Rita R. Colwell, Brenda Rivera-García, Christopher M. Barker, Jesse E. Bell, Matthew Biggerstaff, David Swerdlow, Luis Mier-y-Teran-Romero, Brett M. Forshey, Juli Trtanj, Jason Asher, Matt Clay, Harold S. Margolis, Andrew M. Hebbeler, Dylan George, and Jean-Paul Chretien, which was first published November 11, 2019; 10.1073/pnas.1909865116. The authors note that the affiliation for Xavier Rodó should instead appear as Catalan Institution for Research and Advanced Studies (ICREA) and Climate and Health Program, Barcelona Institute for Global Health (ISGlobal). The corrected author and affiliation lines appear below. The online version has been corrected

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An open challenge to advance probabilistic forecasting for dengue epidemics.

A wide range of research has promised new tools for forecasting infectious disease dynamics, but little of that research is currently being applied in practice, because tools do not address key public health needs, do not produce probabilistic forecasts, have not been evaluated on external data, or do not provide sufficient forecast skill to be useful. We developed an open collaborative forecasting challenge to assess probabilistic forecasts for seasonal epidemics of dengue, a major global public health problem. Sixteen teams used a variety of methods and data to generate forecasts for 3 epidemiological targets (peak incidence, the week of the peak, and total incidence) over 8 dengue seasons in Iquitos, Peru and San Juan, Puerto Rico. Forecast skill was highly variable across teams and targets. While numerous forecasts showed high skill for midseason situational awareness, early season skill was low, and skill was generally lowest for high incidence seasons, those for which forecasts would be most valuable. A comparison of modeling approaches revealed that average forecast skill was lower for models including biologically meaningful data and mechanisms and that both multimodel and multiteam ensemble forecasts consistently outperformed individual model forecasts. Leveraging these insights, data, and the forecasting framework will be critical to improve forecast skill and the application of forecasts in real time for epidemic preparedness and response. Moreover, key components of this project-integration with public health needs, a common forecasting framework, shared and standardized data, and open participation-can help advance infectious disease forecasting beyond dengue

Stable inheritance of DNA methylation allows creation of epigenotype maps and the study of epiallele inheritance patterns in the absence of genetic variation

Abstract Background Differences in DNA methylation can arise as epialleles, which are loci that differ in chromatin state and are inherited over generations. Epialleles offer an additional source of variation that can affect phenotypic diversity beyond changes to nucleotide sequence. Previous research has looked at the rate at which spontaneous epialleles arise but it is currently unknown how they are maintained across generations. Results We used two Arabidopsis thaliana mutation accumulation (MA) lines and determined that over 99.998% of the methylated regions in the genome are stably inherited across each generation indicating that spontaneous epialleles are rare. We also developed a novel procedure that determines genotypes for offspring of genetically identical parents using only DNA methylation data. The resulting epigenotype maps are highly accurate and strongly agree with expected allele frequency and crossover number. Using epigenotype maps, we explore the inheritance of methylation states in regions of differential methylation between the parents of genetic crosses. Over half of the regions show methylation levels consistent with cis inheritance, whereas the other half show evidence of trans-chromosomal methylation and demethylation as well as other possibilities. Conclusions DNA methylation is stably inherited by offspring and spontaneous epialleles are rare. The epigenotyping procedure that we describe provides an important first step to epigenetic quantitative trait loci mapping in genetically identical individuals

Cell wall composition and digestibility alterations in Brachypodium distachyon achieved through reduced expression of the UDP-arabinopyranose mutase

Nucleotide-activated sugars are essential substrates for plant cell-wall carbohydrate-polymer biosynthesis. The most prevalent grass cell wall sugars are glucose (Glc), xylose (Xyl), and arabinose (Ara). These sugars are biosynthetically related via the UDP-sugar interconversion pathway. We sought to target and generate UDP-sugar interconversion pathway transgenic Brachypodium distachyon lines resulting in cell wall carbohydrate composition changes with improved digestibility and normal plant stature. Both RNAi-mediated gene-suppression and constitutive gene-expression approaches were performed. Cell walls from 336 T0 transgenic plants with normal appearance were screened for complete carbohydrate composition. RNAi mutants of BdRGP1, a UDP-arabinopyranose mutase, resulted in large alterations in cell wall carbohydrate composition with significant decreases in cell wall Ara content but with minimal change in plant stature. Five independent RNAi-RGP1 T1 plant lines were used for in-depth analysis of plant cell walls. Real-time PCR analysis indicated that gene expression levels for BdRGP1, BdRGP2 and BdRGP3 were reduced in RNAi-RGP1 plants to 15-20% of controls. Cell wall Ara content was reduced by 23-51% of control levels. No alterations in cell wall Xyl and Glc content were observed. Corresponding decreases in cell wall ferulic acid (FA) and ferulic acid-dimers (FA-dimers) were observed. Additionally, cell wall p-coumarates (pCA) were decreased. We demonstrate the cell wall pCA decrease corresponds to Ara-coupled pCA. Xylanase-mediated digestibility of RNAi-RGP1 Brachypodium cell walls resulted in a near two-fold increase of released total carbohydrate. However, cellulolytic hydrolysis of cell wall material was inhibited in leaves of RNAi-RGP1 mutants. Our results indicate that targeted manipulation of UDP-sugar biosynthesis can result in biomass with substantially altered compositions and highlights the complex effect cell wall composition has on digestibility

The evolution of CHROMOMETHYLASES and gene body DNA methylation in plants

Abstract Background The evolution of gene body methylation (gbM), its origins, and its functional consequences are poorly understood. By pairing the largest collection of transcriptomes (>1000) and methylomes (77) across Viridiplantae, we provide novel insights into the evolution of gbM and its relationship to CHROMOMETHYLASE (CMT) proteins. Results CMTs are evolutionary conserved DNA methyltransferases in Viridiplantae. Duplication events gave rise to what are now referred to as CMT1, 2 and 3. Independent losses of CMT1, 2, and 3 in eudicots, CMT2 and ZMET in monocots and monocots/commelinids, variation in copy number, and non-neutral evolution suggests overlapping or fluid functional evolution of this gene family. DNA methylation within genes is widespread and is found in all major taxonomic groups of Viridiplantae investigated. Genes enriched with methylated CGs (mCG) were also identified in species sister to angiosperms. The proportion of genes and DNA methylation patterns associated with gbM are restricted to angiosperms with a functional CMT3 or ortholog. However, mCG-enriched genes in the gymnosperm Pinus taeda shared some similarities with gbM genes in Amborella trichopoda. Additionally, gymnosperms and ferns share a CMT homolog closely related to CMT2 and 3. Hence, the dependency of gbM on a CMT most likely extends to all angiosperms and possibly gymnosperms and ferns. Conclusions The resulting gene family phylogeny of CMT transcripts from the most diverse sampling of plants to date redefines our understanding of CMT evolution and its evolutionary consequences on DNA methylation. Future, functional tests of homologous and paralogous CMTs will uncover novel roles and consequences to the epigenome