Perturbations in plant energy homeostasis prime lateral root initiation via SnRK1-bZIP63-ARF19 signaling

Plants adjust their energy metabolism to continuous environmental fluctuations, resulting in a tremendous plasticity in their architec- ture. The regulatory circuits involved, however, remain largely unresolved. In Arabidopsis, moderate perturbations in photosyn- thetic activity, administered by short-term low light exposure or unexpected darkness, lead to increased lateral root (LR) initiation. Consistent with expression of low-energy markers, these treat- ments alter energy homeostasis and reduce sugar availability in roots. Here, we demonstrate that the LR response requires the met- abolic stress sensor kinase Snf1-RELATED-KINASE1 (SnRK1), which phosphorylates the transcription factor BASIC LEUCINE ZIPPER63 (bZIP63) that directly binds and activates the promoter of AUXIN RESPONSE FACTOR19 (ARF19), a key regulator of LR initiation. Con- sistently, starvation-induced ARF19 transcription is impaired in bzip63 mutants. This study highlights a positive developmental function of SnRK1. During energy limitation, LRs are initiated and primed for outgrowth upon recovery. Hence, this study provides mechanistic insights into how energy shapes the agronomically im- portant root system

All SNPs are not created equal: genome-wide association studies reveal a consistent pattern of enrichment among functionally annotated SNPs

Recent results indicate that genome-wide association studies (GWAS) have the potential to explain much of the heritability of common complex phenotypes, but methods are lacking to reliably identify the remaining associated single nucleotide polymorphisms (SNPs). We applied stratified False Discovery Rate (sFDR) methods to leverage genic enrichment in GWAS summary statistics data to uncover new loci likely to replicate in independent samples. Specifically, we use linkage disequilibrium-weighted annotations for each SNP in combination with nominal p-values to estimate the True Discovery Rate (TDR = 1−FDR) for strata determined by different genic categories. We show a consistent pattern of enrichment of polygenic effects in specific annotation categories across diverse phenotypes, with the greatest enrichment for SNPs tagging regulatory and coding genic elements, little enrichment in introns, and negative enrichment for intergenic SNPs. Stratified enrichment directly leads to increased TDR for a given p-value, mirrored by increased replication rates in independent samples. We show this in independent Crohn's disease GWAS, where we find a hundredfold variation in replication rate across genic categories. Applying a well-established sFDR methodology we demonstrate the utility of stratification for improving power of GWAS in complex phenotypes, with increased rejection rates from 20% in height to 300% in schizophrenia with traditional FDR and sFDR both fixed at 0.05. Our analyses demonstrate an inherent stratification among GWAS SNPs with important conceptual implications that can be leveraged by statistical methods to improve the discovery of loci

Search for dark matter produced in association with a single top quark and an energetic W boson in √s=13 TeV pp collisions with the ATLAS detector

This paper presents a search for dark matter, χ, using events with a single top quark and an energetic W boson. The analysis is based on proton–proton collision data collected with the ATLAS experiment at √s = 13 TeV during LHC Run 2 (2015–2018), corresponding to an integrated luminosity of 139 fb−1. The search considers final states with zero or one charged lepton (electron or muon), at least one b-jet and large missing transverse momentum. In addition, a result from a previous search considering two-charged-lepton final states is included in the interpretation of the results. The data are found to be in good agreement with the Standard Model predictions and the results are interpreted in terms of 95% confidence-level exclusion limits in the context of a class of dark matter models involving an extended twoHiggs-doublet sector together with a pseudoscalar mediator particle. The search is particularly sensitive to on-shell production of the charged Higgs boson state, H±, arising from the two-Higgs-doublet mixing, and its semi-invisible decays via the mediator particle, a: H± → W±a(→ χχ). Signal models with H± masses up to 1.5 TeV and a masses up to 350 GeV are excluded assuming a tan β value of 1. For masses of a of 150 (250) GeV, tan β values up to 2 are excluded for H± masses between 200 (400) GeV and 1.5 TeV. Signals with tan β values between 20 and 30 are excluded for H± masses between 500 and 800 GeV

A search for rare B → Dμ+μ− decays

A search for rare B→Dμ+μ− decays is performed using proton-proton collision data collected by the LHCb experiment, corresponding to an integrated luminosity of 9 fb−1. No significant signals are observed in the non-resonant μ+μ− modes, and upper limits of B(B0→D ̄ ̄ ̄ ̄0μ+μ−)<5.1×10−8, B(B+→D+sμ+μ−)<3.2×10−8, B(B0s→D ̄ ̄ ̄ ̄0μ+μ−)<1.6×10−7 and fc/fu⋅B(B+c→D+sμ+μ−)<9.6×10−8 are set at the 95\% confidence level, where fc and fu are the fragmentation fractions of a B meson with a c and u quark respectively in proton-proton collisions. Each result is either the first such measurement or an improvement by three orders of magnitude on an existing limit. Separate upper limits are calculated when the muon pair originates from a J/ψ→μ+μ− decay. The branching fraction of B+c→D+sJ/ψ multiplied by the fragmentation-fraction ratio is measured to be fc/fu⋅B(B+c→D+sJ/ψ)=(1.63±0.15±0.13)×10−5, where the first uncertainty is statistical and the second systematic

A genomic approach to therapeutic target validation identifies a glucose-lowering <i>GLP1R</i> variant protective for coronary heart disease

Regulatory authorities have indicated that new drugs to treat type 2 diabetes (T2D) should not be associated with an unacceptable increase in cardiovascular risk. Human genetics may be able to guide development of antidiabetic therapies by predicting cardiovascular and other health endpoints. We therefore investigated the association of variants in six genes that encode drug targets for obesity or T2D with a range of metabolic traits in up to 11,806 individuals by targeted exome sequencing and follow-up in 39,979 individuals by targeted genotyping, with additional in silico follow-up in consortia. We used these data to first compare associations of variants in genes encoding drug targets with the effects of pharmacological manipulation of those targets in clinical trials. We then tested the association of those variants with disease outcomes, including coronary heart disease, to predict cardiovascular safety of these agents. A low-frequency missense variant (Ala316Thr; rs10305492) in the gene encoding glucagon-like peptide-1 receptor (GLP1R), the target of GLP1R agonists, was associated with lower fasting glucose and T2D risk, consistent with GLP1R agonist therapies. The minor allele was also associated with protection against heart disease, thus providing evidence that GLP1R agonists are not likely to be associated with an unacceptable increase in cardiovascular risk. Our results provide an encouraging signal that these agents may be associated with benefit, a question currently being addressed in randomized controlled trials. Genetic variants associated with metabolic traits and multiple disease outcomes can be used to validate therapeutic targets at an early stage in the drug development process