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Phylogenetic analysis was performed using single copy ortholog genes identified with BUSCO, for the 24 newly sequenced notothenioid genomes and 17 previously published genomes of seven notothenioids and ten further species of percomorph fishes. BUSCO (v2) was run with lineage “actinopterygii_odb9”, and the sequences of single- opy orthologs identified in each assembly and extracted for use in further analysis. We used MAFFT v.7.453 to align 266 selected BUSCO genes that were single copy in our annotated gene sets. The 266 alignments were inspected by eye, and apparently misaligned sequence regions were set to missing data. A total of 1,141,524 amino acids were set to missing out of 6,410,688, including nine alignments that were excluded completely, leaving 257 alignments for further analysis. We then aligned nucleotide sequences of the same BUSCO genes according to the amino-acid alignments, ensuring that regions corresponding to the removed sequences were again set to missing data in the nucleotide sequence alignments. Sites with high entropy (entropy like score > 0.5) or high proportion of missing data (gap rate > 0.2) were removed with BMGE v.1.1 and alignments with more than three completely missing sequences, a minimum length below 500 bp, or a standard deviation of among-sequence GC-content variation greater than 0.03 were excluded. These filters were passed by 228 alignments. Each of these alignments was subjected to Bayesian phylogenetic analysis with BEAST 2 v.2.6.0, with an uncorrelated lognormal relaxed clock model and a Markov-chain Monte Carlo chain (MCMC) length of 25 million iterations. “Strict” and “permissive” sets of alignments were compiled based on estimates of the mutation rate and its among-species variation and contained 140 and 200 of the alignments, respectively. For the strict set of 140 alignments, the permissive set of 200 alignments, and the “full” set of 257 alignments, we performed maximum-likelihood phylogenetic analyses with IQ-TREE v.1.7 after alignment concatenation, maintaining separate partitions with unlinked instances of the GTR+Gamma substitution model for each of the original alignments. Node support was assessed with 1,000 ultrafast bootstrap replicates. Each of the three analyses was complemented with an estimation of gene- and site-specific concordance factors, and the three resulting sets of gene trees were used for separate species-tree analyses with ASTRAL v.5.7.3. Finally, we estimated the phylogeny and the divergence times of notothenioid species with BEAST 2 from a concatenated alignment combining all alignments of the strict set. The original data blocks were grouped in 12 positions selected with the rcluster algorithm of PartitionFinder v.2.1.1, assuming linked branch lengths, equal weights for all model parameters, a minimum partition size of 5,000 bp, and the GTR+Gamma substitution model. The same substitution model was also assumed in the BEAST 2 analysis, together with the birth-death model of diversification and the uncorrelated lognormal relaxed clock model. Time calibration of the phylogeny was based on four age constraints defined according to a recent timeline of teleost evolution inferred from genome and fossil information, at the most recent common ancestors of clades: Eupercaria, around 97.47 MYA (2.5–97.5 inter-percentile range: 91.3–104.0 MYA); the clade combining Eupercaria, Ovalentaria, and Anabantaria – around 101.79 MYA (95.4–109.0 MYA); the clade combining these four groups with Syngnatharia and Pelagiaria – around 104.48 MYA (97.3–112.0 MYA); and the clade combining those six groups with Gobiaria – around 107.08 MYA (100.0–114.0 MYA). All constraints were implemented as lognormal prior distributions with mean values as specified above and a standard deviation between 0.033 and 0.036. Additionally, we constrained the unambiguous monophyly of the groups Notothenioidei, Perciformes, Ovalentaria, Anabantaria, and the clade combining the latter two groups. We performed six replicate BEAST 2 analyses with 330 million MCMC iterations, and convergence among MCMC chains was confirmed by ESS values greater than 120 for all model parameters and greater than 270 for the likelihood and the prior and posterior probabilities. The posterior tree distribution was summarised in the form of a maximum-clade credibility tree with TreeAnnotator v.2.6.0. We attempted to repeat the BEAST 2 analyses with the permissive and full datasets, but these proved too computationally demanding to complete. Nevertheless, the preliminary results from these analyses supported the same tree topology as the analyses with the strict dataset. Numerous novel adaptations characterise the radiation of notothenioids, the dominant fish group in the freezing seas of the Southern Ocean. To improve understanding of the evolution of this iconic fish group, we generated and analysed new genome assemblies for 24 species covering all major subgroups of the radiation, including five long-read assemblies. We present a new estimate for the onset of the radiation at 10.7 million years ago, based on a time-calibrated phylogeny derived from genome-wide sequence data. We identify a two-fold variation in genome size, driven by expansion of multiple transposable element families, and use the long-read data to reconstruct two evolutionarily important, highly repetitive gene family loci. First, we present the most complete reconstruction to date of the antifreeze glycoprotein gene family, whose emergence enabled survival in sub-zero temperatures, showing the expansion of the antifreeze gene locus from the ancestral to the derived state. Second, we trace the loss of haemoglobin genes in icefishes, the only vertebrates lacking functional haemoglobins, through complete reconstruction of the two haemoglobin gene clusters across notothenioid families. Both the haemoglobin and antifreeze genomic loci are characterised by multiple transposon expansions that may have driven the evolutionary history of these genes.

In almost every natural environment, sounds are reflected by nearby objects, producing many delayed and distorted copies of the original sound, known as reverberation. Our brains usually cope well with reverberation, allowing us to recognize sound sources regardless of their environments. In contrast, reverberation can cause severe difficulties for speech recognition algorithms and hearing-impaired people. The present study examines how the auditory system copes with reverberation. We trained a linear model to recover a rich set of natural, anechoic sounds from their simulated reverberant counterparts. The model neurons achieved this by extending the inhibitory component of their receptive filters for more reverberant spaces, and did so in a frequency-dependent manner. These predicted effects were observed in the responses of auditory cortical neurons of ferrets in the same simulated reverberant environments. Together, these results suggest that auditory cortical neurons adapt to reverberation by adjusting their filtering properties in a manner consistent with dereverberation. We have provided our Matlab scripts for generating our figures on Github: https://github.com/PhantomSpike/DeReverb Spike data were recorded using Neuropixels electrodes in the auditory cortex of anaesthetised ferrets.

A key challenge in neuroimaging remains to understand where, when and now particularly how human brain networks compute over sensory inputs to achieve behavior. To study such dynamic algorithms from mass neural signals, we recorded the magnetoencephalographic (MEG) activity of participants who resolved the classic XOR, OR and AND functions as overt behavioral tasks (N = 10 participants/task, N-of-1 replications). Each function requires a different computation over the same inputs to produce the task- specific behavioral outputs. In each task, we found that source-localized MEG activity progresses through four computational stages identified within individual participants: (1) initial contra-lateral representation of each visual input in occipital cortex, (2) a joint linearly combined representation of both inputs in midline occipital cortex and right fusiform gyrus, followed by (3) nonlinear task-dependent input integration in temporal-parietal cortex and finally (4) behavioral response representation in post-central gyrus. We demonstrate the specific dynamics of each computation at the level of individual sources. The spatio-temporal patterns of the first two computations are similar across the three tasks; the last two computations are task specific. Our results therefore reveal where, when and how dynamic network algorithms perform different computations over the same inputs to produce different behaviors. This dataset includes source data and the related manuscript codes involved in the research Different Computations over the Same Inputs Produce Selective Behavior in Algorithmic Brain Networks published at eLife. Specifically, we provide all analyzed data reported in the paper including: Figure 1&3 related – Source Data in FigureSource1.mat. 1_DistancePattern.m 2_LinearRep.m 3_NonLinRep.m Figure 2 related – Source Data in FigureSource2.mat 4_DynaCoord.m

Obesity is a world wide problem and evidence suggests, that early lifetime undernourishment of caloric restirction predispose an organism for obesity and metabolic syndrome. We have raised two cohorts of zebrafish in an obesogenic environment (DIO) and compared several metabolic markers with fish raised under caloric restriction (CR) or fish shifted from CR to DIO at different periods in their life. We have looked morphologically at standard length and weight and found that fish on DIO grow faster in both axes. Fish shifted from CR to DIO show catch-up growth and not compensatory growth when shifted at one month, 3 months or 9 months of age. We have further characterized central agrp expression and hyperphagia, adipose tissue by histology as well as uCT imaging, hepatic histology, metabolic rate mitochondrial function as well as feeding induced glucose levels. We find that fish in an obesogenic environment develop markers of obesity which are not exacerbated by ealry lifetime food restriction.

For µCT imaging, adult zebrafish were fixed and decalcified in Bouin's solution at room temperature for 7 days, stored in PBS and imaged using a micro-computed tomography (µCT) device (SkyScan1272, Bruker BioSpin GmbH, Ettlingen, Germany). Zebrafish were placed individually in 1.5ml Eppendorf tubes using and an ultra-focus scan over the whole body was performed in a full-rotation in step-and-shoot mode. 322 projections (1008x672 pixels, 4x4 binning) were acquired per subscan with an x-ray tube voltage of 60 kV, power 0.166 mA, aluminum filter 0.25 mm,exposure time of 363 ms, 6 averages and a object-source distance of 86 mm. All CT images were reconstructed at an isotropic voxel size of 18 µm using a Feldkamp type algorithm (filtered back-projection). Fat-containing regions were appear hypo intense in µCT data and were segmented using Imalytics Preclinical (Gremse-IT GmbH, Aachen, Germany (Gremse et al., 2016; doi:10.7150/thno.13624). The volumetric fat percentage was calculated as the ratio of subcutaneous adipose tissue (SAT) or visceral adipose tissue (VAT) fat volume compared to the entire volume of the body cavity anterior of the anal fin and expressed per skeletal segment. Fish were raised as previously reported (Leibold and Hammerschmidt, 2015) for the following conditions:CG1: compensatory or catch up growth shifted at 1 month of ageCG3: compensatory or catch up growth shifted at 3 months of ageCG9: compensatory or catch up growth shifted at 9 months of ageCR: caloric restrictionDIO: diet induced obesityThe CT .nii files correlate to the groups as follows: Group 2: CG1; Group 3: DIO1; Group 6: CG3; Group 7 DIO3; Group 10: CG9; Group 11: DIO9; Group 1: CR1; Group 5: CR3; Group 9: CR9

To test associations between DNA methylation levels and gene expression levels in cis (cis eQTMs), we paired each Gene to CpGs closer than 500 kb from its TSS, either upstream or downstream. For each Gene, the TSS was defined based on HTA-2.0 annotation, using the start position for transcripts in the + strand, and the end position for transcripts in the - strand. CpGs position was obtained from Illumina 450K array annotation. Only CpGs in autosomal chromosomes (from chromosome 1 to 22) were tested. In the main analysis, we fitted for each CpG-Gene pair a linear regression model between gene expression and methylation levels adjusted for age, sex, cohort, and blood cell type composition. A second model was run without adjusting for blood cellular composition and it is only reported on the online web catalog, but not discussed in this manuscript. Although some of the unique associations of the unadjusted model might be real, others might be confounded by the large methylation and expression changes among blood cell types. To ensure that CpGs paired to a higher number of Genes do not have higher chances of being part of an eQTM, multiple-testing was controlled at the CpG level, following a procedure previously applied in the Genotype-Tissue Expression (GTEx) project (Gamazon et al., 2018). Briefly, our statistic used to test the hypothesis that a pair CpG-Gene is significantly associated is based on considering the lowest p-value observed for a given CpG and all its paired Gene (e.g., those in the 1 Mb window centered at the TSS). As we do not know the distribution of this statistic under the null, we used a permutation test. We generated 100 permuted gene expression datasets and ran our previous linear regression models obtaining 100 permuted p-values for each CpG-Gene pair. Then, for each CpG, we selected among all CpG-Gene pairs the minimum p-value in each permutation and fitted a beta distribution that is the distribution we obtain when dealing with extreme values (e.g. minimum) (Dudbridge and Gusnanto, 2008). Next, for each CpG, we took the minimum p-value observed in the real data and used the beta distribution to compute the probability of observing a lower p-value. We defined this probability as the empirical p-value of the CpG. Then, we considered as significant those CpGs with empirical p-values to be significant at 5% false discovery rate using Benjamini-Hochberg method. Finally, we applied a last step to identify all significant CpG-Gene pairs for all eCpGs. To do so, we defined a genome-wide empirical p-value threshold as the empirical p-value of the eCpG closest to the 5% false discovery rate threshold. We used this empirical p-value to calculate a nominal p-value threshold for each eCpG, based on the beta distribution obtained from the minimum permuted p-values. This nominal p-value threshold was defined as the value for which the inverse cumulative distribution of the beta distribution was equal to the empirical p-value. Then, for each eCpG, we considered as significant all eCpG-Gene variants with a p-value smaller than nominal p-value. For the meQTLs catalogue, we selected 9.9 M cis and trans meQTLs with a p-value <1e-7 in the ARIES dataset consisting of data from children of 7 years old (Gaunt et al., 2016). Then, we tested whether this subset of 9.9 M SNPs were also meQTLs in HELIX by running meQTL analyses using MatrixEQTL R package (Shabalin, 2012), adjusting for cohort, sex, age, blood cellular composition and the first 20 principal components (PCs) calculated from genome-wide genetic data of the GWAS variability. We confirmed 2.8 M meQTLs in HELIX (p-value <1e-7). Trans meQTLs represented <10% of the 2.8 M meQTLs. Enrichment of eCpGs for meQTLs was computed using a Chi-square test, using non eCpGs as background. Finally, we tested whether meQTLs were also eQTLs for the eGenes linked to the eCpGs. To this end, we run eQTL analyses (gene expression being the outcome and 2.8 M SNPs the predictors) with MatrixEQTL adjusting for cohort, sex, age, blood cellular composition and the first 20 GWAS PCs in HELIX. We considered as significant eQTLs the SNP-Gene pairs with p-value <1e-7 and with the direction of the effect consistent with the direction of the meQTL and the eQTM. Background: The identification of expression quantitative trait methylation (eQTMs), defined as associations between DNA methylation levels and gene expression, might help the biological interpretation of epigenome-wide association studies (EWAS). We aimed to identify autosomal cis eQTMs in children’s blood, using data from 832 children of the Human Early Life Exposome (HELIX) project. Methods: Blood DNA methylation and gene expression were measured with the Illumina 450K and the Affymetrix HTA v2 arrays, respectively. The relationship between methylation levels and expression of nearby genes (1 Mb window centered at the transcription start site, TSS) was assessed by fitting 13.6 M linear regressions adjusting for sex, age, cohort, and blood cell composition. Results: We identified 39,749 blood autosomal cis eQTMs, representing 21,966 unique CpGs (eCpGs, 5.7% of total CpGs) and 8,886 unique transcript clusters (eGenes, 15.3% of total transcript clusters, equivalent to genes). In 87.9% of these cis eQTMs, the eCpG was located at <250 kb from eGene’s TSS; and 58.8% of all eQTMs showed an inverse relationship between the methylation and expression levels. Only around half of the autosomal cis-eQTMs eGenes could be captured through annotation of the eCpG to the closest gene. eCpGs had less measurement error and were enriched for active blood regulatory regions and for CpGs reported to be associated with environmental exposures or phenotypic traits. 40.4% of eQTMs had at least one genetic variant associated with methylation and expression levels. The overlap of autosomal cis eQTMs in children’s blood with those described in adults was small (13.8%), and age-shared cis eQTMs tended to be proximal to the TSS and enriched for genetic variants. See HELIX_Blood_eQTM_READMEfile_20210205.xlsx.

Many sensory systems use ribbon-type synapses to transmit their signals to downstream circuits. The properties of this synaptic transfer fundamentally dictate which aspects in the original stimulus will be accentuated or suppressed, thereby partially defining the detection limits of the circuit. Accordingly, sensory neurons have evolved a wide variety of ribbon geometries and vesicle pool properties to best support their diverse functional requirements. However, the need for diverse synaptic functions does not only arise across neuron types, but also within. Here we show that UV-cones, a single type of photoreceptor of the larval zebrafish eye, exhibit striking differences in their synaptic ultrastructure and consequent calcium to glutamate transfer function depending on their location in the eye. We arrive at this conclusion by combining serial section electron microscopy and simultaneous "dual-colour" 2-photon imaging of calcium and glutamate signals from the same synapse in vivo. We further use the functional dataset to fit a cascade-like model of the ribbon synapse with different vesicle pool sizes, transfer rates and other synaptic properties. Exploiting recent developments in simulation-based inference, we obtain full posterior estimates for the parameters and compare these across different retinal regions. The model enables us to extrapolate to new stimuli and to systematically investigate different response behaviours of various ribbon configurations. We also provide an interactive, easy-to-use version of this model as an online tool. Overall, we show that already on the synaptic level of single neuron types there exist highly specialized mechanisms which are advantageous for the encoding of different visual features.

Type VI Secretion Systems (T6SS) are widespread in bacteria and can dictate the development and organisation of polymicrobial ecosystems by mediating contact dependent killing. In Neisseria species, including Neisseria cinerea a commensal of the human respiratory tract, interbacterial contacts are mediated by Type four pili (Tfp) which promote formation of aggregates and govern the spatial dynamics of growing Neisseria microcolonies. Here we show that N. cinerea expresses a plasmid-encoded T6SS that is active and can limit growth of related pathogens. We explored the impact of Tfp expression on N. cinerea T6SS-dependent killing and show that expression of Tfp by prey strains enhances their susceptibility to T6SS, by keeping them in close proximity of T6SS wielding attacker strains. Our findings have important implications for understanding how spatial constraints during contact-dependent antagonism can shape the evolution of microbial communities. The README file contains an explanation of how to open and edit the whole genome sequence .dna files. Upon further sequence analysis of the PacBio plasmid sequence file of Neisseria cinerea CCUG346T, a duplicated region of approximately 16 kb in the plasmid sequence was identified. Further analysis of genomic DNA from the isolate was performed using overlapping PCR and sequencing. As a result, a modified plasmid map was generated from the PacBio sequence to remove the duplicated region and eliminate 16507 bp from the original sequence file (125,648 bp) resulting in a plasmid sequence of 108,141 bp. DNA Isolation and whole-genome sequencing (WGS) Genomic DNA was extracted using the Wizard Genomic Kit (Promega), and sequenced by PacBio (Earlham Institute, Norwich) using single-molecule real-time (SMRT) technology; reads were assembled de novo with HGAP3 (Chin et al., 2013).