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Collections of cells called engrams are thought to represent memories. Although there has been progress in identifying and manipulating single engrams, little is known about how multiple engrams interact to influence memory. In lateral amygdala (LA), neurons with increased excitability during training outcompete their neighbors for allocation to an engram. We examined whether competition based on neuronal excitability also governs the interaction between engrams. Mice received two distinct fear conditioning events separated by different intervals. LA neuron excitability was optogenetically manipulated and revealed a transient competitive process that integrates memories for events occurring closely in time (coallocating overlapping populations of neurons to both engrams) and separates memories for events occurring at distal times (disallocating nonoverlapping populations to each engram). Rashid et al Science 2016- Data for Figs 1-4, S1-S9Excel file with all data presented in manuscript (each sheet corresponds to specific figures as indicated).Rashid et al Science 2016.xlsx

OBJECTIVE. To assess whether HS severity is mirrored at the level of large-scale networks. METHODS. We studied preoperative high-resolution anatomical and diffusion-weighted MRI of 44 TLE patients with histopathological diagnosis of HS (n=25; TLE-HS) and isolated gliosis (n=19; TLE-G), and 25 healthy controls. Hippocampal measurements included surface-based subfield mapping of atrophy and T2 hyperintensity indexing cell loss and gliosis, respectively. Whole-brain connectomes were generated via diffusion tractography and examined using graph theory along with a novel network control theory paradigm which simulates functional dynamics from structural network data. RESULTS. Compared to controls, we observed markedly increased path length and decreased clustering in TLE-HS compared to controls, indicating lower global and local network efficiency, while TLE-G showed only subtle alterations. Similarly, network controllability was lower in TLE-HS only, suggesting limited range of functional dynamics. Hippocampal imaging markers were positively associated with macroscale network alterations, particularly in ipsilateral CA1-3. Systematic assessment across several networks revealed maximal changes in the hippocampal circuity. Findings were consistent when correcting for cortical thickness, suggesting independence from grey matter atrophy. CONCLUSIONS. Severe HS is associated with marked remodeling of connectome topology and structurally-governed functional dynamics in TLE, as opposed to isolated gliosis which has negligible effects. Cell loss, particularly in CA1-3, may exert a cascading effect on brain-wide connectomes, underlining coupled disease processes across multiple scales. Data_phen_conn_dryadPhenotypic information and mean connectome feature data for Bernhardt et al. (2019) Temporal lobe epilepsy: hippocampal pathology modulates white matter connectome topology and controllability. Neurology

Premise of the study: Polyploidization is a common and recurring phenomenon in plants and is often thought to be a mechanism of "instant speciation." Whether polyploidization is associated with the formation of new species ("cladogenesis") or simply occurs over time within a lineage ("anagenesis") has never, however, been assessed systematically. Methods: Here, we tested this hypothesis using phylogenetic and karyotypic information from 235 plant genera (mostly angiosperms). We first constructed a large database of combined sequence and chromosome number data sets using an automated procedure. We then applied likelihood models (ClaSSE) that estimate the degree of synchronization between polyploidization and speciation events in maximum likelihood and Bayesian frameworks. Key results: Our maximum likelihood analysis indicated that 35 genera supported a model that includes cladogenetic transitions over a model with only anagenetic transitions, whereas three genera supported a model that incorporates anagenetic transitions over one with only cladogenetic transitions. Furthermore, the Bayesian analysis supported a preponderance of cladogenetic change in four genera but did not support a preponderance of anagenetic change in any genus. Conclusions: Overall, these phylogenetic analyses provide the first broad confirmation that polyploidization is temporally associated with speciation events, suggesting that it is indeed a major speciation mechanism in plants, at least in some genera. PloiDBPhylogenetic trees inferred using MrBayes, ploidy estimates using ChromEvol, and TPL-based genus species diversity estimates for 223 genera.ploidb_dryad.tar.gz

Background: Clinical trials that end prematurely (or “terminate”) raise financial, ethical, and scientific concerns. The extent to which the results of such trials are disseminated and the reasons for termination have not been well characterized. Methods and Findings: A cross-sectional, descriptive study of terminated clinical trials posted on the ClinicalTrials.gov results database as of February 2013 was conducted. The main outcomes were to characterize the availability of primary outcome data on ClinicalTrials.gov and in the published literature and to identify the reasons for trial termination. Approximately 12% of trials with results posted on the ClinicalTrials.gov results database (905/7,646) were terminated. Most trials were terminated for reasons other than accumulated data from the trial (68%; 619/905), with an insufficient rate of accrual being the lead reason for termination among these trials (57%; 350/619). Of the remaining trials, 21% (193/905) were terminated based on data from the trial (findings of efficacy or toxicity) and 10% (93/905) did not specify a reason. Overall, data for a primary outcome measure were available on ClinicalTrials.gov and in the published literature for 72% (648/905) and 22% (198/905) of trials, respectively. Primary outcome data were reported on the ClinicalTrials.gov results database and in the published literature more frequently (91% and 46%, respectively) when the decision to terminate was based on data from the trial. Conclusions: Trials terminate for a variety of reasons, not all of which reflect failures in the process or an inability to achieve the intended goals. Primary outcome data were reported most often when termination was based on data from the trial. Further research is needed to identify best practices for disseminating the experience and data resulting from terminated trials in order to help ensure maximal societal benefit from the investments of trial participants and others involved with the study. DATA_Terminated Trials in ClinicalTrialsgov Results Database (19 Feb 2013)CSV data file containing data retrieved from the ClinicalTrials.gov registry and results database on February 19, 2013. Additional details are available in the ReadMe file.

Alzheimer's disease (AD) is a major public health priority with a large socioeconomic burden and complex etiology. The Alzheimer Disease Metabolomics Consortium (ADMC) and the Alzheimer Disease Neuroimaging Initiative (ADNI) aim to gain new biological insights in the disease etiology. We report here an untargeted lipidomics of serum specimens of 806 subjects within the ADNI1 cohort (188 AD, 392 mild cognitive impairment and 226 cognitively normal subjects) along with 83 quality control samples. Lipids were detected and measured using an ultra-high-performance liquid chromatography quadruple/time-of-flight mass spectrometry (UHPLC-QTOF MS) instrument operated in both negative and positive electrospray ionization modes. The dataset includes a total 513 unique lipid species out of which 341 are known lipids. For over 95% of the detected lipids, a relative standard deviation of better than 20% was achieved in the quality control samples, indicating high technical reproducibility. Association modeling of this dataset and available clinical, metabolomics and drug-use data will provide novel insights into the AD etiology. These datasets are available at the ADNI repository at http://adni.loni.usc.edu/.

Web Supplementary Files Web Supplementary File 1 - FASTA files containing full-length reconstruction input sequences: full_length_reconstruction_input_sequence_fastas.zip Web Supplementary File 2 - FASTA files containing Muscle alignments of the full-length reconstruction input sequences. full_length_reconstruction_input_sequence_alns.zip Web Supplementary File 3 - FASTA file of full-length reconstructed sequences: full_length_reconstructions.fa Web Supplementary File 4 - Table of full-length reconstruction statistics: full_length_reconstruction_stats.csv Web Supplementary File 5 - FASTA files containing ORF reconstruction input sequences: orf_fastas.zip Web Supplementary File 6 - FASTA files containing Macse alignments of the ORF reconstruction input sequences: ORF_reconstruction_input_sequence_alns.zip Web Supplementary File 7 - Table of ORF reconstruction statistics: ORF_reconstructions.fa Web Supplementary File 8 - Table of ORF reconstruction statistics: ORF_reconstruction_stats.csv Web Supplementary File 9 - Table of Composite Sequences: bestfl_selection_fixed_CS_seqs.csv Web Supplementary File 10 - Database of gold standards: L1_goldstandards.csv Data Underlying Figures RepeatMasker scans of hg38 and ancestral genomes: anc_gen_RM_out_files.zip Figure 4 4A Source alignment of 54 composite sequences: 220121_dropped12+L1ME3A_muscle.nt.afa Tree produced using the alignment and FastTree: 220121_dropped12+L1ME3A.tree 4B Source alignment of 67 Dfam L1 subfamily 3’ end models: 200123_dfam_3ends.fa.muscle.aln Tree produced using the alignment: 200123_dfam_3ends.fa.muscle.aln.tree Figure 5 KZFP-TE enrichment p-values (from Barazandeh et al 2018): TE_KZFP_enrichment_pvals.xlsx KZFP-TE top 500 peak overlap (from Barazandeh et al 2018): top500_peak_overlap.xlsx Figure 6 RepeatMasker .out file for the Composite Sequence custom library queried against hg38: CS_RM_hg38.fa.out.gz Figure S2 RepeatMasker scan .out file of hg38 (CG corrected Kimura Divergence values are in last column): hg38+KimDiv_RM.out RepeatMasker scan .out file of the Progressive Cactus eutherian ancestral genome (CG corrected Kimura Divergence values are in last column): Progressive_Cactus_Euth+KimDiv_RM.out RepeatMasker scan .out file of the Ancestors 1.1 eutherian ancestral genome (CG corrected Kimura Divergence values are in last column): Ancestors_Euth+KimDiv_RM.out Figure S5 RepeatMasker scan .out files for Progressive Cactus simian and primate reconstructed ancestral genomes: progCactus_RM_outfiles.zip S5A FASTA files containing Cactus genome-derived reconstructed sequences equivalent to the L1MA2, L1MA4, and L1MD1-3 best full-length sequences: progCactus_reconstruction_bestFL_equivalents.zip S5B FASTA files containing Muscle alignments of Cactus genome-derived full-length reconstruction input sequences: progCactus_reconstruction_input_sequence_alns.zip Figure S6 S6A Results of Conserved Domain scans of Cactus genome-derived full-length reconstructed sequences: CD_search_results_short_nms.txt S6B-D Character posterior probabilities of “best” full-length reconstructed sequences: best_fl_post_probs.zip Figure S7 S7B-C Results of Conserved Domain scans of translated initial full-length reconstructed sequences: initial_recons_all_3frametrans_CD-search.txt Results of Conserved Domain scans of translated reconstructed ORFs: recons_ORF1-2_all_3frametrans_CD-search.csv Figure S15 S15A Source alignment of 67 composite sequences: bestfl_selection_fixed_CS_seqs_muscle.nt.afa Tree produced using the alignment: bestfl_selection_fixed_CS_seqs_muscle.nt.afa.tree S15B-E Source Muscle alignments for phylogenetic trees of reconstructed sequence components: ORF2: ORF2_keep54_muscle.nt.afa 5’ UTR: 5utr_keep54_muscle.nt.afa ORF1: ORF1_keep54_muscle.nt.afa 3’ UTR: 3utr_keep54_muscle.nt.afa Trees produced using above alignments: ORF2: ORF2_keep54_muscle.nt.afa.tree 5’ UTR: 5utr_keep54_muscle.nt.afa.tree ORF1: ORF1_keep54_muscle.nt.afa.tree 3’ UTR: 3utr_keep54_muscle.nt.afa.tree Figure S17 Unfiltered BLAST results of Composite Sequences queried against hg38: CS_hg38_blastn.csv.zip BED file of L1 instances annotated using BLAST pipeline: BLAST_L1_hits.bed

We carried out an admixture mapping study of lipid traits in two samples from Mexico City. Native American locus ancestry was significantly associated with triglyceride levels in a broad region of chromosome 11 overlapping the BUD13, ZNF259 and APOA5 genes. In our fine-mapping analysis of this region using dense genome-wide data, rs964184 is the only marker included in the 99% credible set of SNPs, providing strong support for rs964184 as the causal variant within this region. The frequency of the allele associated with increased triglyceride concentrations (rs964184-G) is between 30-40% higher in Native American populations from Mexico than in European populations. The evidence currently available for this variant indicates that it may be exerting its effect through three potential mechanisms: 1) modification of enhancer activity, 2) regulation of the expression of several genes in cis and/or trans, or 3) modification of the methylation patterns of the promoter of the APOA5 gene. MC-sample1-HDL-AMAdmixture Mapping results for HDL-cholesterol: Mexico City sample 1MC-sample1-LDL-AMAdmixture Mapping results for LDL-cholesterol: Mexico City sample 1MC-sample1-TCHOL-AMAdmixture Mapping results for Total-cholesterol: Mexico City sample 1MC-sample1-TG-AMAdmixture Mapping results for triglycerides: Mexico City sample 1MC-sample2-HDL-AMAdmixture Mapping results for HDL-cholesterol: Mexico City sample 2MC-sample2-LDL-AMAdmixture Mapping results for LDL-cholesterol: Mexico City sample 2MC-sample2-TCHOL-AMAdmixture Mapping results for Total-cholesterol: Mexico City sample 2MC-sample2-TG-AMAdmixture Mapping results for triglycerides: Mexico City sample 2Mexico-City-AM-signalsAdmixture Mapping signals identified in both Mexico City samples for all the lipid traits.

Living in permanent social groups forces animals to make decisions about when, how and with whom to interact, requiring decisions to be made that integrate multiple sources of information. Changing social environments can influence this decision-making process by constraining choice or altering the likelihood of a positive outcome. Here, we conceptualised grooming as a choice situation where an individual chooses one of a number of potential partners. Studying two wild populations of sympatric primate species, sooty mangabeys (Cercocebus atys atys) and Western chimpanzees (Pan troglodytes verus), we tested what properties of potential partners influenced grooming decisions, including their relative value based on available alternatives and the social relationships of potential partners with bystanders who could observe the outcome of the decision. Across 1,529 decision events, multiple partner attributes (e.g. dominance ranks, social relationship quality, reproductive state, partner sex) influenced choice. Individuals preferred to initiate grooming with partners of similar global rank, but this effect was driven by a bias towards partners with a high rank compared to other locally available options. Individuals also avoided grooming partners who had strong social relationships with at least one bystander. Results indicated flexible decision-making in grooming interactions in both species, based on a partner’s value given the local social environment. Viewing partner choice as a value-based decision-making process allows researchers to compare how different species solve similar social problems. Data Model1Data for Models 1-1 and 1-2Data Model2Data for Models 2-1 and 2-2Script Model 1 and 2Scripts necessary to analyse Models 1 and 2

Query strain identities and corresponding screening set.In order to obtain an IDTS-wide genetic interaction map, we modified the automated, high-density replica plating approaches previously developed for analyzing S. cerevisiae double mutants through Synthetic Genetic Array (SGA) analysis (Tong AH, Evangelista M, Parsons AB, Xu H, Bader GD, Page N, Robinson M, Raghibizadeh S, Hogue CW, Bussey H, Andrews B, Tyers M, Boone C (2001) Systematic genetic analysis with ordered arrays of yeast deletion mutants. Science 294: 2364-2368). Instead of looking at double mutants, however, we used yeast genetics to systematically assess the effects of Legionella effector co-expression on yeast growth. Query strains that express one effector were mated to an array of ~330 effectors in groups of ~10 queries at a time ("Analysis Set"). The arrays were then imaged using a high-resolution camera and the spot sizes were quantified using SGAtools (http://sgatools.ccbr.utoronto.ca/) (Wagih O, Usaj M, Baryshnikova A, VanderSluis B, Kuzmin E, Costanzo M, Myers CL, Andrews BJ, Boone CM, Parts L (2013) SGAtools: One-stop analysis and visualization of array-based genetic interaction screens. Nucleic acids research 41: W591-596). Outlier spot sizes flagged by the Jackknife filter (JK) in SGAtools were removed and the average and standard deviation of the remaining values were calculated and normalized to the average empty vector control. This spreadsheet lists all query strains and links them to one or more specific analysis set.Array_set_annotation.xlsSGA output for analysis sets 1-10.Query strains that express one effector were mated to an array of ~330 effectors in groups of ~10 queries at a time ("Analysis Set"). The arrays were then imaged using a high-resolution camera and the spot sizes were quantified using SGAtools (http://sgatools.ccbr.utoronto.ca/). Outlier spot sizes flagged by the Jackknife filter (JK) in SGAtools were removed and the average and standard deviation of the remaining values were calculated and normalized to the average empty vector control. This .zip archive includes spreadsheets that encompass the raw SGAtools data output from the paper for analysis sets 1-10.UrbanusMSB_SGA.zipUrbanus_SGA_1-10.zipSGA output for analysis sets 11-20.Query strains that express one effector were mated to an array of ~330 effectors in groups of ~10 queries at a time ("Analysis Set"). The arrays were then imaged using a high-resolution camera and the spot sizes were quantified using SGAtools (http://sgatools.ccbr.utoronto.ca/). Outlier spot sizes flagged by the Jackknife filter (JK) in SGAtools were removed and the average and standard deviation of the remaining values were calculated and normalized to the average empty vector control. This .zip archive includes spreadsheets that encompass the raw SGAtools data output from the paper for analysis sets 11-20.Urbanus_SGA_11-20.zipSGA output for analysis sets 21-30.Query strains that express one effector were mated to an array of ~330 effectors in groups of ~10 queries at a time ("Analysis Set"). The arrays were then imaged using a high-resolution camera and the spot sizes were quantified using SGAtools (http://sgatools.ccbr.utoronto.ca/). Outlier spot sizes flagged by the Jackknife filter (JK) in SGAtools were removed and the average and standard deviation of the remaining values were calculated and normalized to the average empty vector control. This .zip archive includes spreadsheets that encompass the raw SGAtools data output from the paper for analysis sets 21-30.Urbanus_SGA_21-30.zipSGA output for analysis sets 31-37.Query strains that express one effector were mated to an array of ~330 effectors in groups of ~10 queries at a time ("Analysis Set"). The arrays were then imaged using a high-resolution camera and the spot sizes were quantified using SGAtools (http://sgatools.ccbr.utoronto.ca/). Outlier spot sizes flagged by the Jackknife filter (JK) in SGAtools were removed and the average and standard deviation of the remaining values were calculated and normalized to the average empty vector control. This .zip archive includes spreadsheets that encompass the raw SGAtools data output from the paper for analysis sets 31-37.Urbanus_SGA_31-37.zip Pathogens deliver complex arsenals of translocated effector proteins to host cells during infection, but the extent to which these proteins are regulated once inside the eukaryotic cell remains poorly defined. Among all bacterial pathogens, Legionella pneumophila maintains the largest known set of translocated substrates, delivering over 300 proteins to the host cell via its Type IVB, Icm/Dot translocation system. Backed by a few notable examples of effector–effector regulation in L. pneumophila, we sought to define the extent of this phenomenon through a systematic analysis of effector–effector functional interaction. We used Saccharomyces cerevisiae, an established proxy for the eukaryotic host, to query > 108,000 pairwise genetic interactions between two compatible expression libraries of ~330 L. pneumophila‐translocated substrates. While capturing all known examples of effector–effector suppression, we identify fourteen novel translocated substrates that suppress the activity of other bacterial effectors and one pair with synergistic activities. In at least nine instances, this regulation is direct—a hallmark of an emerging class of proteins called metaeffectors, or “effectors of effectors”. Through detailed structural and functional analysis, we show that metaeffector activity derives from a diverse range of mechanisms, shapes evolution, and can be used to reveal important aspects of each cognate effector's function. Metaeffectors, along with other, indirect, forms of effector–effector modulation, may be a common feature of many intracellular pathogens—with unrealized potential to inform our understanding of how pathogens regulate their interactions with the host cell.